PROSPECT: Profiling of Resistance Patterns & Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax and Therapeutic Target Identification

DTIC Science & Technology

2012-06-01

neoadjuvant therapies on disease-free, progression-free, and overall survival will vary across prognostically distinct groups. 3. Specific molecular... prognostically distinct subpopulations of patients with resectable NSCLC, and to assess the extent to which these molecular profiles correlate with tumor...overall survival, and will use Cox proportional hazards models and recursive partitioning methods to identify important biomarkers and prognostically

Whole brain radiotherapy and stereotactic radiosurgery for patients with recursive partitioning analysis I and lesions <5 cm(3): A matched pair analysis.

PubMed

Viani, Gustavo Arruda; Godoi da Silva, Lucas Bernardes; Viana, Bruno Silveira; Rossi, Bruno Tiago; Suguikawa, Elton; Zuliani, Gisele

2016-01-01

The intention of this study is to compare whole brain radiotherapy and stereotactic radiosurgery (WBRT + SRS) with WBRT in patients with 1-4 brain metastases to find a subgroup of patients that have a great benefit with aggressive treatment. Between December 2002 and December 2013, 60 patients with 1-4 brain metastases were treated by WBRT + SRS. In this period, 60 patients treated with WBRT were matched with patients treated with WBRT + SRS. The median survival for the entire cohort was 8.3 months. In the univariate analysis, WBRT + SRS (0.031), the presence of extracranial disease (P = 0.02), Karnofsky performance score <70 (P = 0.0001), and age >65 (P = 0.001) years were significant factors for survival. In the entire cohort, the median survival for recursive partitioning analysis (RPA) classes I, II, and III was 11, 7, and 3 months, respectively (P = 0.0001). In a stratified analysis, only RPA class I achieved statistical significance for 1-year survival between the groups (WBRT + SRS = 51% and WBRT = 23%, P = 0.03). Cox regression analysis revealed WBRT + SRS, age >65 years, and extracranial disease as independent prognostic factors. In the univariate analysis, lesion volume ≤5 cm 3 (P = 0.002) and WBRT + SRS (P = 0.003) were the significant factors associated with better brain control. WBRT plus SRS was an independent prognostic factor for survival. However, the combined treatment appears to be justified only in patients with RPA I and lesion volume ≤5 cm 3, independently of the number of lesions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kishi, Takahiro; Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.jp; Ueki, Nami

Purpose: This study aimed to evaluate the prognostic significance of the modified Glasgow Prognostic Score (mGPS) in patients with non-small cell lung cancer (NSCLC) who received stereotactic body radiation therapy (SBRT). Methods and Materials: Data from 165 patients who underwent SBRT for stage I NSCLC with histologic confirmation from January 1999 to September 2010 were collected retrospectively. Factors, including age, performance status, histology, Charlson comorbidity index, mGPS, and recursive partitioning analysis (RPA) class based on sex and T stage, were evaluated with regard to overall survival (OS) using the Cox proportional hazards model. The impact of the mGPS on causemore » of death and failure patterns was also analyzed. Results: The 3-year OS was 57.9%, with a median follow-up time of 3.5 years. A higher mGPS correlated significantly with poor OS (P<.001). The 3-year OS of lower mGPS patients was 66.4%, whereas that of higher mGPS patients was 44.5%. On multivariate analysis, mGPS and RPA class were significant factors for OS. A higher mGPS correlated significantly with lung cancer death (P=.019) and distant metastasis (P=.013). Conclusions: The mGPS was a significant predictor of clinical outcomes for SBRT in NSCLC patients.« less

Enhanced Trajectory Based Similarity Prediction with Uncertainty Quantification

DTIC Science & Technology

2014-10-02

challenge by obtaining the highest score by using a data-driven prognostics method to predict the RUL of a turbofan engine (Saxena & Goebel, PHM08...process for multi-regime health assessment. To illustrate multi-regime partitioning, the “ Turbofan Engine Degradation simulation” data set from...hence the name k- means. Figure 3 shows the results of the k-means clustering algorithm on the “ Turbofan Engine Degradation simulation” data set. As

Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non-Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235.

PubMed

Ohri, Nitin; Duan, Fenghai; Snyder, Bradley S; Wei, Bo; Machtay, Mitchell; Alavi, Abass; Siegel, Barry A; Johnson, Douglas W; Bradley, Jeffrey D; DeNittis, Albert; Werner-Wasik, Maria; El Naqa, Issam

2016-06-01

In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on (18)F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Patients with locally advanced NSCLC underwent (18)F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient's primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address overfitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan-Meier curves and log-rank testing were used to compare outcomes among patient groups. Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm(3), and the optimal SumMean cutpoint for tumors above 93.3 cm(3) was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P < 0.001). We have described an appropriate methodology to evaluate the prognostic value of textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non–Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235

PubMed Central

Ohri, Nitin; Duan, Fenghai; Snyder, Bradley S.; Wei, Bo; Machtay, Mitchell; Alavi, Abass; Siegel, Barry A.; Johnson, Douglas W.; Bradley, Jeffrey D.; DeNittis, Albert; Werner-Wasik, Maria; El Naqa, Issam

2016-01-01

In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on 18F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non–small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Methods Patients with locally advanced NSCLC underwent 18F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient’s primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address over-fitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan–Meier curves and log-rank testing were used to compare outcomes among patient groups. Results Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm3, and the optimal Sum-Mean cutpoint for tumors above 93.3 cm3 was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P < 0.001). Conclusion We have described an appropriate methodology to evaluate the prognostic value of textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted. PMID:26912429

Tumor Volume and Patient Weight as Predictors of Outcome in Children with Intermediate Risk Rhabdomyosarcoma (RMS): A Report from the Children’s Oncology Group

PubMed Central

Rodeberg, David A.; Stoner, Julie A.; Garcia-Henriquez, Norbert; Randall, R. Lor; Spunt, Sheri L.; Arndt, Carola A.; Kao, Simon; Paidas, Charles N.; Million, Lynn; Hawkins, Douglas S.

2010-01-01

Background To compare tumor volume and patient weight vs. traditional factors of tumor diameter and patient age, to determine which parameters best discriminates outcome among intermediate risk RMS patients. Methods Complete patient information for non-metastatic RMS patients enrolled in the Children’s Oncology Group (COG) intermediate risk study D9803 (1999–2005) was available for 370 patients. The Kaplan-Meier method was used to estimate survival distributions. A recursive partitioning model was used to identify prognostic factors associated with event-free survival (EFS). Cox-proportional hazards regression models were used to estimate the association between patient characteristics and the risk of failure or death. Results For all intermediate risk patients with RMS, a recursive partitioning algorithm for EFS suggests that prognostic groups should optimally be defined by tumor volume (transition point 20 cm3), weight (transition point 50 kg), and embryonal histology. Tumor volume and patient weight added significant outcome information to the standard prognostic factors including tumor diameter and age (p=0.02). The ability to resect the tumor completely was not significantly associated with the size of the patient, and patient weight did not significantly modify the association between tumor volume and EFS after adjustment for standard risk factors (p=0.2). Conclusion The factors most strongly associated with EFS were tumor volume, patient weight, and histology. Based on regression modeling, volume and weight are superior predictors of outcome compared to tumor diameter and patient age in children with intermediate risk RMS. Prognostic performance of tumor volume and patient weight should be assessed in an independent prospective study. PMID:24048802

Three list scheduling temporal partitioning algorithm of time space characteristic analysis and compare for dynamic reconfigurable computing

NASA Astrophysics Data System (ADS)

Chen, Naijin

2013-03-01

Level Based Partitioning (LBP) algorithm, Cluster Based Partitioning (CBP) algorithm and Enhance Static List (ESL) temporal partitioning algorithm based on adjacent matrix and adjacent table are designed and implemented in this paper. Also partitioning time and memory occupation based on three algorithms are compared. Experiment results show LBP partitioning algorithm possesses the least partitioning time and better parallel character, as far as memory occupation and partitioning time are concerned, algorithms based on adjacent table have less partitioning time and less space memory occupation.

Multidisciplinary treatment of brain metastases derived from clear cell renal cancer incorporating stereotactic radiosurgery.

PubMed

Samlowski, Wolfram E; Majer, Martin; Boucher, Kenneth M; Shrieve, Annabelle F; Dechet, Christopher; Jensen, Randy L; Shrieve, Dennis C

2008-11-01

Brain metastases are a frequent complication in patients with metastatic clear cell renal cancer. Survival after whole-brain radiotherapy (WBRT) is disappointing. A retrospective analysis of multimodality treatment was performed in patients who had received linear accelerator (LINAC)-based stereotactic radiosurgery (SRS). Thirty-two patients underwent SRS-based treatment for 71 metastatic foci between 2000 and 2006. All patients had a Karnofsky performance status >or=70 and all 32 patients had extracranial metastatic disease (Radiation Therapy Oncology Group recursive partitioning analysis [RPA] Class 2). Survival was calculated from the time of diagnosis of brain metastases. The minimum potential follow-up was 1 year after SRS. Univariate and multivariate analysis of potential prognostic factors affecting survival was performed. Twenty-six patients required only 1 SRS treatment (84%) to achieve central nervous system (CNS) control, whereas 5 patients received 2 to 3 treatments (16%). The median survival of renal cancer patients from the diagnosis of brain metastases was 10.1 months (95% confidence interval, 6.4-14.8 months). One-year and 3-year survival rates were 43% and 16%, respectively. The addition of surgery or WBRT did not appear to prolong survival. Immunotherapy after control of brain metastases with SRS appeared to result in significantly improved survival. Survival was also found to be strongly influenced by prognostic stratification of metastatic disease using Motzer or modified risk criteria. The results of the current study demonstrated that SRS-based treatment of patients with up to 5 brain metastases from clear cell renal cancer is feasible and results in excellent CNS control. Survival beyond 3 years from the time of diagnosis of brain metastases was achievable in 16% of patients and was associated with the use of systemic immunotherapy with interleukin-2 and interferon but not antiangiogenic agents.

Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Louie, Alexander V., E-mail: Dr.alexlouie@gmail.com; Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario; Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, Massachusetts

Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogrammore » for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.« less

Partitioning-based mechanisms under personalized differential privacy.

PubMed

Li, Haoran; Xiong, Li; Ji, Zhanglong; Jiang, Xiaoqian

2017-05-01

Differential privacy has recently emerged in private statistical aggregate analysis as one of the strongest privacy guarantees. A limitation of the model is that it provides the same privacy protection for all individuals in the database. However, it is common that data owners may have different privacy preferences for their data. Consequently, a global differential privacy parameter may provide excessive privacy protection for some users, while insufficient for others. In this paper, we propose two partitioning-based mechanisms, privacy-aware and utility-based partitioning, to handle personalized differential privacy parameters for each individual in a dataset while maximizing utility of the differentially private computation. The privacy-aware partitioning is to minimize the privacy budget waste, while utility-based partitioning is to maximize the utility for a given aggregate analysis. We also develop a t -round partitioning to take full advantage of remaining privacy budgets. Extensive experiments using real datasets show the effectiveness of our partitioning mechanisms.

Partitioning-based mechanisms under personalized differential privacy

PubMed Central

Li, Haoran; Xiong, Li; Ji, Zhanglong; Jiang, Xiaoqian

2017-01-01

Differential privacy has recently emerged in private statistical aggregate analysis as one of the strongest privacy guarantees. A limitation of the model is that it provides the same privacy protection for all individuals in the database. However, it is common that data owners may have different privacy preferences for their data. Consequently, a global differential privacy parameter may provide excessive privacy protection for some users, while insufficient for others. In this paper, we propose two partitioning-based mechanisms, privacy-aware and utility-based partitioning, to handle personalized differential privacy parameters for each individual in a dataset while maximizing utility of the differentially private computation. The privacy-aware partitioning is to minimize the privacy budget waste, while utility-based partitioning is to maximize the utility for a given aggregate analysis. We also develop a t-round partitioning to take full advantage of remaining privacy budgets. Extensive experiments using real datasets show the effectiveness of our partitioning mechanisms. PMID:28932827

Evaluation of a prognostic scoring system based on the systemic inflammatory and nutritional status of patients with locally advanced non-small-cell lung cancer treated with chemoradiotherapy.

PubMed

Mitsuyoshi, Takamasa; Matsuo, Yukinori; Itou, Hitoshi; Shintani, Takashi; Iizuka, Yusuke; Kim, Young Hak; Mizowaki, Takashi

2018-01-01

Systemic inflammation and poor nutritional status have a negative effect on the outcomes of cancer. Here, we analyzed the effects of the pretreatment inflammatory and nutritional status on clinical outcomes of locally advanced non-small-cell lung cancer (NSCLC) patients treated with chemoradiotherapy. We retrospectively reviewed 89 patients with locally advanced NSCLC treated with chemoradiotherapy between July 2006 and June 2013. Serum C-reactive protein (CRP) was assessed as an inflammatory marker, and serum albumin, body mass index (BMI) and skeletal mass index were assessed as nutritional status markers. The relationships between these markers and overall survival (OS) were assessed. The median OS was 24.6 months [95% confidence interval (CI): 19.4-39.3 months]. During follow-up, 58 patients (65%) had disease recurrence and 52 patients (58%) died. In multivariate Cox hazard analysis, CRP levels and BMI approached but did not achieve a significant association with OS (P = 0.062 and 0.094, respectively). Recursive partitioning analysis identified three prognostic groups based on hazard similarity (CRP-BMI scores): 0 = CRP < 0.3 mg/dl, 1 = CRP ≥ 0.3 mg/dl and BMI ≥ 18.5 kg/m2, and 2 = CRP ≥ 0.3 mg/dl and BMI < 18.5 kg/m2. The CRP-BMI score was significantly associated with OS (P = 0.023). Patients with scores of 0, 1 and 2 had median OS of 39.3, 24.5 and 14.5 months, respectively, and the scores also predicted the probability of receiving salvage treatment after recurrence. The CRP-BMI score is thus a simple and useful prognostic marker of clinical outcome for patients with locally advanced NSCLC treated with chemoradiotherapy. © The Author 2017. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Recursive partitioning analysis (RPA) classification predicts survival in patients with brain metastases from sarcoma.

PubMed

Grossman, Rachel; Ram, Zvi

2014-12-01

Sarcoma rarely metastasizes to the brain, and there are no specific treatment guidelines for these tumors. The recursive partitioning analysis (RPA) classification is a well-established prognostic scale used in many malignancies. In this study we assessed the clinical characteristics of metastatic sarcoma to the brain and the validity of the RPA classification system in a subset of 21 patients who underwent surgical resection of metastatic sarcoma to the brain We retrospectively analyzed the medical, radiological, surgical, pathological, and follow-up clinical records of 21 patients who were operated for metastatic sarcoma to the brain between 1996 and 2012. Gliosarcomas, sarcomas of the head and neck with local extension into the brain, and metastatic sarcomas to the spine were excluded from this reported series. The patients' mean age was 49.6 ± 14.2 years (range, 25-75 years) at the time of diagnosis. Sixteen patients had a known history of systemic sarcoma, mostly in the extremities, and had previously received systemic chemotherapy and radiation therapy for their primary tumor. The mean maximal tumor diameter in the brain was 4.9 ± 1.7 cm (range 1.7-7.2 cm). The group's median preoperative Karnofsky Performance Scale was 80, with 14 patients presenting with Karnofsky Performance Scale of 70 or greater. The median overall survival was 7 months (range 0.2-204 months). The median survival time stratified by the Radiation Therapy Oncology Group RPA classes were 31, 7, and 2 months for RPA class I, II, and III, respectively (P = 0.0001). This analysis is the first to support the prognostic utility of the Radiation Therapy Oncology Group RPA classification for sarcoma brain metastases and may be used as a treatment guideline tool in this rare disease. Copyright © 2014 Elsevier Inc. All rights reserved.

An Investigation of Document Partitions.

ERIC Educational Resources Information Center

Shaw, W. M., Jr.

1986-01-01

Empirical significance of document partitions is investigated as a function of index term-weight and similarity thresholds. Results show the same empirically preferred partitions can be detected by two independent strategies: an analysis of cluster-based retrieval analysis and an analysis of regularities in the underlying structure of the document…

Transcriptional Profiling of Breast Cancer Metastases Identifies Liver Metastasis-Selective Genes Associated with Adverse Outcome in Luminal A Primary Breast Cancer.

PubMed

Kimbung, Siker; Johansson, Ida; Danielsson, Anna; Veerla, Srinivas; Egyhazi Brage, Suzanne; Frostvik Stolt, Marianne; Skoog, Lambert; Carlsson, Lena; Einbeigi, Zakaria; Lidbrink, Elisabet; Linderholm, Barbro; Loman, Niklas; Malmström, Per-Olof; Söderberg, Martin; Walz, Thomas M; Fernö, Mårten; Hatschek, Thomas; Hedenfalk, Ingrid

2016-01-01

The complete molecular basis of the organ-specificity of metastasis is elusive. This study aimed to provide an independent characterization of the transcriptional landscape of breast cancer metastases with the specific objective to identify liver metastasis-selective genes of prognostic importance following primary tumor diagnosis. A cohort of 304 women with advanced breast cancer was studied. Associations between the site of recurrence and clinicopathologic features were investigated. Fine-needle aspirates of metastases (n = 91) were subjected to whole-genome transcriptional profiling. Liver metastasis-selective genes were identified by significance analysis of microarray (SAM) analyses and independently validated in external datasets. Finally, the prognostic relevance of the liver metastasis-selective genes in primary breast cancer was tested. Liver relapse was associated with estrogen receptor (ER) expression (P = 0.002), luminal B subtype (P = 0.01), and was prognostic for an inferior postrelapse survival (P = 0.01). The major variation in the transcriptional landscape of metastases was also associated with ER expression and molecular subtype. However, liver metastases displayed unique transcriptional fingerprints, characterized by downregulation of extracellular matrix (i.e., stromal) genes. Importantly, we identified a 17-gene liver metastasis-selective signature, which was significantly and independently prognostic for shorter relapse-free (P < 0.001) and overall (P = 0.001) survival in ER-positive tumors. Remarkably, this signature remained independently prognostic for shorter relapse-free survival (P = 0.001) among luminal A tumors. Extracellular matrix (stromal) genes can be used to partition breast cancer by site of relapse and may be used to further refine prognostication in ER positive primary breast cancer. ©2015 American Association for Cancer Research.

A Matched-Pair Analysis Comparing Whole-Brain Radiotherapy Plus Stereotactic Radiosurgery Versus Surgery Plus Whole-Brain Radiotherapy and a Boost to the Metastatic Site for One or Two Brain Metastases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rades, Dirk; Department of Radiation Oncology, University Medical Center, Hamburg; Kueter, Jan-Dirk

2009-03-15

Purpose: To compare the results of whole-brain radiotherapy plus stereotactic radiosurgery (WBRT+SRS) with those of surgery plus whole-brain radiotherapy and a boost to the metastatic site (OP+WBRT+boost) for patients with one or two brain metastases. Methods and Materials: Survival, intracerebral control, and local control of the treated metastases were retrospectively evaluated. To reduce the risk of selection bias, a matched-pair analysis was performed. The outcomes of 47 patients who received WBRT+SRS were compared with those of a second cohort of 47 patients who received OP+WBRT+boost. The two treatment groups were matched for the following potential prognostic factors: WBRT schedule, age,more » gender, performance status, tumor type, number of brain metastases, extracerebral metastases, recursive partitioning analysis class, and interval from tumor diagnosis to WBRT. Results: The 1-year survival rates were 65% after WBRT+SRS and 63% after OP+WBRT+boost (p = 0.19). The 1-year intracerebral control rates were 70% and 78% (p = 0.39), respectively. The 1-year local control rates were 84% and 83% (p = 0.87), respectively. On multivariate analyses, improved survival was significantly associated with better performance status (p = 0.009), no extracerebral metastases (p = 0.004), recursive partitioning analysis Class 1 (p = 0.004), and interval from tumor diagnosis to WBRT (p = 0.001). Intracerebral control was not significantly associated with any of the potential prognostic factors. Improved local control was significantly associated with no extracerebral metastases (p = 0.037). Conclusions: Treatment outcomes were not significantly different after WBRT+SRS compared with OP+WBRT+boost. However, WBRT+SRS is less invasive than OP+WBRT+boost and may be preferable for patients with one or two brain metastases. The results should be confirmed by randomized t0011ria.« less

Institutional, Retrospective Analysis of 777 Patients With Brain Metastases: Treatment Outcomes and Diagnosis-Specific Prognostic Factors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Antoni, Delphine, E-mail: Dantoni@strasbourg.unicancer.fr; Clavier, Jean-Baptiste; Pop, Marius

2013-07-15

Purpose: To retrospectively evaluate the prognostic factors and survival of a series of 777 patients with brain metastases (BM) from a single institution. Methods and Materials: Patients were treated with surgery followed by whole-brain radiation therapy (WBRT) or with WBRT alone in 16.3% and 83.7% of the cases, respectively. The patients were RPA (recursive partitioning analysis) class I, II, and III in 11.2%, 69.6%, and 18.4% of the cases, respectively; RPA class II-a, II-b, and II-c in 8.3%, 24.8%, and 66.9% of the cases, respectively; and with GPA (graded prognostic assessment) scores of 0-1.0, 1.5-2.0, 2.5-3.0, and 3.5-4.0 in 35%,more » 27.5%, 18.2%, and 8.6% of the cases, respectively. Results: The median overall survival (OS) times according to RPA class I, II, and III were 20.1, 5.1, and 1.3 months, respectively (P<.0001); according to RPA class II-a, II-b, II-c: 9.1, 8.9, and 4.0 months, respectively (P<.0001); and according to GPA score 0-1.0, 1.5-2.0, 2.5-3.0, and 3.5-4.0: 2.5, 4.4, 9.0, and 19.1 months, respectively (P<.0001). By multivariate analysis, the favorable independent prognostic factors for survival were as follows: for gastrointestinal tumor, a high Karnofsky performance status (KPS) (P=.0003) and an absence of extracranial metastases (ECM) (P=.003); for kidney cancer, few BM (P=.002); for melanoma, few BM (P=.01), an absence of ECM (P=.002), and few ECM (P=.0002); for lung cancer, age (P=.007), a high KPS (P<.0001), an absence of ECM (P<.0001), few ECM and BM (P<.0001 and P=.0006, respectively), and control of the primary tumor (P=.004); and for breast cancer, age (P=.001), a high KPS (P=.007), control of the primary tumor (P=.05), and few ECM and BM (P=.01 and P=.0002, respectively). The triple-negative subtype was a significant unfavorable factor (P=.007). Conclusion: Prognostic factors varied by pathology. Our analysis confirms the strength of prognostic factors used to determine the GPA score, including the genetic subtype for breast cancer.« less

Outcome and prognostic factors in patients with brain metastases from small-cell lung cancer treated with whole brain radiotherapy.

PubMed

Bernhardt, Denise; Adeberg, Sebastian; Bozorgmehr, Farastuk; Opfermann, Nils; Hoerner-Rieber, Juliane; König, Laila; Kappes, Jutta; Thomas, Michael; Herth, Felix; Heußel, Claus Peter; Warth, Arne; Debus, Jürgen; Steins, Martin; Rieken, Stefan

2017-08-01

The purpose of this study was to evaluate prognostic factors associated with overall survival (OS) and neurological progression free survival (nPFS) in small-cell lung cancer (SCLC) patients with brain metastases who received whole-brain radiotherapy (WBRT). From 2003 to 2015, 229 SCLC patients diagnosed with brain metastases who received WBRT were analyzed retrospectively. In this cohort 219 patients (95%) received a total photon dose of 30 Gy in 10 fractions. The prognostic factors evaluated for OS and nPFS were: age, Karnofsky Performance Status (KPS), number of brain metastases, synchronous versus metachronous disease, initial response to chemotherapy, the Radiation Therapy Oncology Group recursive partitioning analysis (RPA) class and thoracic radiation. Median OS after WBRT was 6 months and the median nPFS after WBRT was 11 months. Patients with synchronous cerebral metastases had a significantly better median OS with 8 months compared to patients with metachronous metastases with a median survival of 3 months (p < 0.0001; HR 0.46; 95% CI 0.31-0.67). Based on RPA classification median survival after WBRT was 17 months in RPA class I, 7 months in class II and 3 months in class III (p < 0.0001). Karnofsky performance status scale (KPS < 70%) was significantly associated with OS in both univariate (HR 2.84; p < 0.001) and multivariate analyses (HR 2.56; p = 0.011). Further, metachronous brain metastases (HR 1.8; p < 0.001), initial response to first-line chemotherapy (HR 0.51, p < 0.001) and RPA class III (HR 2.74; p < 0.001) were significantly associated with OS in univariate analysis. In multivariate analysis metachronous disease (HR 1.89; p < 0.001) and initial response to chemotherapy (HR 0.61; p < 0.001) were further identified as significant prognostic factors. NPFS was negatively significantly influenced by poor KPS (HR 2.56; p = 0.011), higher number of brain metastases (HR 1.97; p = 0.02), and higher RPA class (HR 2.26; p = 0.03) in univariate analysis. In this series, the main prognostic factors associated with OS were performance status, time of appearance of intracranial disease (synchronous vs. metachronous), initial response to chemotherapy and higher RPA class. NPFS was negatively influenced by poor KPS, multiplicity of brain metastases, and higher RPA class in univariate analysis. For patients with low performance status, metachronous disease or RPA class III, WBRT should be weighed against supportive therapy with steroids alone or palliative chemotherapy.

Overlapped Partitioning for Ensemble Classifiers of P300-Based Brain-Computer Interfaces

PubMed Central

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance. PMID:24695550

Overlapped partitioning for ensemble classifiers of P300-based brain-computer interfaces.

PubMed

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance.

Establishment of an Adjusted Prognosis Analysis Model for Initially Diagnosed Non-Small-Cell Lung Cancer With Brain Metastases From Sun Yat-Sen University Cancer Center.

PubMed

Dinglin, Xiao-Xiao; Ma, Shu-Xiang; Wang, Fang; Li, De-Lan; Liang, Jian-Zhong; Chen, Xin-Ru; Liu, Qing; Zeng, Yin-Duo; Chen, Li-Kun

2017-05-01

The current published prognosis models for brain metastases (BMs) from cancer have not addressed the issue of either newly diagnosed non-small-cell lung cancer (NSCLC) with BMs or the lung cancer genotype. We sought to build an adjusted prognosis analysis (APA) model, a new prognosis model specifically for NSCLC patients with BMs at the initial diagnosis using adjusted prognosis analysis (APA). The model was derived using data from 1158 consecutive patients, with 837 in the derivation cohort and 321 in the validation cohort. The patients had initially received a diagnosis of BMs from NSCLC at Sun Yat-Sen University Cancer Center from 1994 to 2015. The prognostic factors analyzed included patient characteristics, disease characteristics, and treatments. The APA model was built according to the numerical score derived from the hazard ratio of each independent prognostic variable. The predictive accuracy of the APA model was determined using a concordance index and was compared with current prognosis models. The results were validated using bootstrap resampling and a validation cohort. We established 2 prognostic models (APA 1 and 2) for the whole group of patients and for those with known epidermal growth factor receptor (EGFR) genotype, respectively. Six factors were independently associated with survival time: Karnofsky performance status, age, smoking history (replaced by EGFR mutation in APA 2), local treatment of intracranial metastases, EGFR-tyrosine kinase inhibitor treatment, and chemotherapy. Patients in the derivation cohort were stratified into low- (score, 0-2), moderate- (score, 3-5), and high-risk (score 6-7) groups according to the median survival time (16.6, 10.3, and 5.2 months, respectively; P < .001). The results were further confirmed in the validation cohort. Compared with recursive partition analysis and graded prognostic assessment, APA seems to be more suitable for initially diagnosed NSCLC with BMs. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

NASA Astrophysics Data System (ADS)

Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

2010-12-01

Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.

Prognostic Factors for Survival in Patients Treated With Stereotactic Radiosurgery for Recurrent Brain Metastases After Prior Whole Brain Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Caballero, Jorge A.; Sneed, Penny K., E-mail: psneed@radonc.ucsf.edu; Lamborn, Kathleen R.

2012-05-01

Purpose: To evaluate prognostic factors for survival after stereotactic radiosurgery (SRS) for new, progressive, or recurrent brain metastases (BM) after prior whole brain radiotherapy (WBRT). Methods and Materials: Patients treated between 1991 and 2007 with Gamma Knife SRS for BM after prior WBRT were retrospectively reviewed. Potential prognostic factors were analyzed overall and by primary site using univariate and stepwise multivariate analyses and recursive partitioning analysis, including age, Karnofsky performance status (KPS), primary tumor control, extracranial metastases, number of BM treated, total SRS target volume, and interval from WBRT to SRS. Results: A total of 310 patients were analyzed, includingmore » 90 breast, 113 non-small-cell lung, 31 small-cell lung, 42 melanoma, and 34 miscellaneous patients. The median age was 56, KPS 80, number of BM treated 3, and interval from WBRT to SRS 8.1 months; 76% had controlled primary tumor and 60% had extracranial metastases. The median survival was 8.4 months overall and 12.0 vs. 7.9 months for single vs. multiple BM treated (p = 0.001). There was no relationship between number of BM and survival after excluding single-BM patients. On multivariate analysis, favorable prognostic factors included age <50, smaller total target volume, and longer interval from WBRT to SRS in breast cancer patients; smaller number of BM, KPS >60, and controlled primary in non-small-cell lung cancer patients; and smaller total target volume in melanoma patients. Conclusions: Among patients treated with salvage SRS for BM after prior WBRT, prognostic factors appeared to vary by primary site. Although survival time was significantly longer for patients with a single BM, the median survival time of 7.9 months for patients with multiple BM seems sufficiently long for salvage SRS to appear to be worthwhile, and no evidence was found to support the use of a cutoff for number of BM appropriate for salvage SRS.« less

Prognostic factors affecting survival after whole brain radiotherapy in patients with brain metastasized lung cancer.

PubMed

Tsakonas, Georgios; Hellman, Fatou; Gubanski, Michael; Friesland, Signe; Tendler, Salomon; Lewensohn, Rolf; Ekman, Simon; de Petris, Luigi

2018-02-01

Whole-brain radiotherapy (WBRT) has been the standard of care for multiple NSCLC brain metastases but due to its toxicity and lack of survival benefit, its use in the palliative setting is being questioned. This was a single institution cohort study including brain metastasized lung cancer patients who received WBRT at Karolinska University Hospital. Information about Recursive Partitioning Analysis (RPA) and Graded Prognostic Assessment (GPA) scores, demographics, histopathological results and received oncological therapy were collected. Predictors of overall survival (OS) from the time of received WBRT were identified by Cox regression analyses. OS between GPA and RPA classes were compared by pairwise log rank test. A subgroup OS analysis was performed stratified by RPA class. The cohort consisted of 280 patients. RPA 1 and 2 classes had better OS compared to class 3, patients with GPA <1.5 points had better OS compared to GPA≥ 1.5 points and age >70 years was associated with worse OS (p< .0001 for all comparisons). In RPA class 2 subgroup analysis GPA ≥1.5 points, age ≤70 years and CNS surgery before salvage WBRT were independent positive prognostic factors. RPA class 3 patients should not receive WBRT, whereas RPA class 1 patients should receive WBRT if clinically indicated. RPA class 2 patients with age ≤70 years and GPA ≥1.5 points should be treated as RPA 1. WBRT should be omitted in RPA 2 patients with age >70. In RPA 2 patients with age ≤70 years and GPA <1.5 points WBRT could be a reasonable option.

Clinical outcome and molecular characterization of brain metastases from esophageal and gastric cancer: a systematic review.

PubMed

Ghidini, Michele; Petrelli, Fausto; Hahne, Jens Claus; De Giorgi, Annamaria; Toppo, Laura; Pizzo, Claudio; Ratti, Margherita; Barni, Sandro; Passalacqua, Rodolfo; Tomasello, Gianluca

2017-04-01

The aim of the study was to collect the available data on central nervous system (CNS) metastases from esophageal and gastric cancer. A PubMed, EMBASE, SCOPUS, Web of Science, LILACS, Ovid and Cochrane Library search was performed. Thirty-seven studies including 779 patients were considered. Among the data extracted, treatment of tumor and brain metastases (BMs), time to BMs development, number and subsite, extracerebral metastases rate, median overall survival (OS) and prognostic factors were included. For esophageal cancer, the median OS from diagnosis of BMs was 4.2 months. Prognostic factors for OS included: performance status, multimodal therapy, adjuvant chemotherapy, single BM, brain only disease and surgery. For gastric cancer, median OS was 2.4 months. Prognostic factors for OS included: recursive partitioning analysis class 2, stereotactic radiosurgery (SRT) and use of intrathecal therapy. HER2-positive gastric cancer was shown to be associated with a higher risk and shorter time to CNS relapse. Patients harboring BMs from gastric and esophageal tumors, except cases with single lesions that are treated aggressively, have a poor prognosis. SRT (plus or minus surgery and whole brain radiotherapy) seems to give better results in terms of longer OS after brain relapse.

Collagen analysis by second-harmonic generation microscopy predicts outcome of luminal breast cancer.

PubMed

Natal, Rodrigo A; Vassallo, José; Paiva, Geisilene R; Pelegati, Vitor B; Barbosa, Guilherme O; Mendonça, Guilherme R; Bondarik, Caroline; Derchain, Sophie F; Carvalho, Hernandes F; Lima, Carmen S; Cesar, Carlos L; Sarian, Luís Otávio

2018-04-01

Second-harmonic generation microscopy represents an important tool to evaluate extracellular matrix collagen structure, which undergoes changes during cancer progression. Thus, it is potentially relevant to assess breast cancer development. We propose the use of second-harmonic generation images of tumor stroma selected on hematoxylin and eosin-stained slides to evaluate the prognostic value of collagen fibers analyses in peri and intratumoral areas in patients diagnosed with invasive ductal breast carcinoma. Quantitative analyses of collagen parameters were performed using ImageJ software. These parameters presented significantly higher values in peri than in intratumoral areas. Higher intratumoral collagen uniformity was associated with high pathological stages and with the presence of axillary lymph node metastasis. In patients with immunohistochemistry-based luminal subtype, higher intratumoral collagen uniformity and quantity were independently associated with poorer relapse-free and overall survival, respectively. A multivariate response recursive partitioning model determined 12.857 and 11.894 as the best cut-offs for intratumoral collagen quantity and uniformity, respectively. These values have shown high sensitivity and specificity to differentiate distinct outcomes. Values of intratumoral collagen quantity and uniformity exceeding the cut-offs were strongly associated with poorer relapse-free and overall survival. Our findings support a promising prognostic value of quantitative evaluation of intratumoral collagen by second-harmonic generation imaging mainly in the luminal subtype breast cancer.

A prognostic classifier for patients with colorectal cancer liver metastasis, based on AURKA, PTGS2 and MMP9.

PubMed

Goos, Jeroen A C M; Coupé, Veerle M H; van de Wiel, Mark A; Diosdado, Begoña; Delis-Van Diemen, Pien M; Hiemstra, Annemieke C; de Cuba, Erienne M V; Beliën, Jeroen A M; Menke-van der Houven van Oordt, C Willemien; Geldof, Albert A; Meijer, Gerrit A; Hoekstra, Otto S; Fijneman, Remond J A

2016-01-12

Prognosis of patients with colorectal cancer liver metastasis (CRCLM) is estimated based on clinicopathological models. Stratifying patients based on tumor biology may have additional value. Tissue micro-arrays (TMAs), containing resected CRCLM and corresponding primary tumors from a multi-institutional cohort of 507 patients, were immunohistochemically stained for 18 candidate biomarkers. Cross-validated hazard rate ratios (HRRs) for overall survival (OS) and the proportion of HRRs with opposite effect (P(HRR < 1) or P(HRR > 1)) were calculated. A classifier was constructed by classification and regression tree (CART) analysis and its prognostic value determined by permutation analysis. Correlations between protein expression in primary tumor-CRCLM pairs were calculated. Based on their putative prognostic value, EGFR (P(HRR < 1) = .02), AURKA (P(HRR < 1) = .02), VEGFA (P(HRR < 1) = .02), PTGS2 (P(HRR < 1) = .01), SLC2A1 (P(HRR > 1) < 01), HIF1α (P(HRR > 1) = .06), KCNQ1 (P(HRR > 1) = .09), CEA (P (HRR > 1) = .05) and MMP9 (P(HRR < 1) = .07) were included in the CART analysis (n = 201). The resulting classifier was based on AURKA, PTGS2 and MMP9 expression and was associated with OS (HRR 2.79, p < .001), also after multivariate analysis (HRR 3.57, p < .001). The prognostic value of the biomarker-based classifier was superior to the clinicopathological model (p = .001). Prognostic value was highest for colon cancer patients (HRR 5.71, p < .001) and patients not treated with systemic therapy (HRR 3.48, p < .01). Classification based on protein expression in primary tumors could be based on AURKA expression only (HRR 2.59, p = .04). A classifier was generated for patients with CRCLM with improved prognostic value compared to the standard clinicopathological prognostic parameters, which may aid selection of patients who may benefit from adjuvant systemic therapy.

The Partition of Multi-Resolution LOD Based on Qtm

NASA Astrophysics Data System (ADS)

Hou, M.-L.; Xing, H.-Q.; Zhao, X.-S.; Chen, J.

2011-08-01

The partition hierarch of Quaternary Triangular Mesh (QTM) determine the accuracy of spatial analysis and application based on QTM. In order to resolve the problem that the partition hierarch of QTM is limited by the level of the computer hardware, the new method that Multi- Resolution LOD (Level of Details) based on QTM will be discussed in this paper. This method can make the resolution of the cells varying with the viewpoint position by partitioning the cells of QTM, selecting the particular area according to the viewpoint; dealing with the cracks caused by different subdivisions, it satisfies the request of unlimited partition in part.

Recursive partitioning identifies greater than 4 U of packed red blood cells per hour as an improved massive transfusion definition.

PubMed

Moren, Alexis Marika; Hamptom, David; Diggs, Brian; Kiraly, Laszlo; Fox, Erin E; Holcomb, John B; Rahbar, Mohammad Hossein; Brasel, Karen J; Cohen, Mitchell Jay; Bulger, Eileen M; Schreiber, Martin A

2015-12-01

Massive transfusion (MT) is classically defined as greater than 10 U of packed red blood cells (PRBCs) in 24 hours. This fails to capture the most severely injured patients. Extending the previous work of Savage and Rahbar, a rolling hourly rate-based definition of MT may more accurately define critically injured patients requiring early, aggressive resuscitation. The Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) trial collected data from 10 Level 1 trauma centers. Patients were placed into rate-based transfusion groups by maximal number of PRBCs transfused in any hour within the first 6 hours. A nonparametric analysis using classification trees partitioned data according to mortality at 24 hours using a predictor variable of maximum number PRBC units transfused in an hour. Dichotomous variables significant in previous scores and models as predictors of MT were used to identify critically ill patients: a positive finding on Focused Assessment with Sonography in Trauma (FAST) examination, Glasgow Coma Scale (GCS) score less than 8, heart rate greater than 120 beats/min, systolic blood pressure less than 90 mm Hg, penetrating mechanism of injury, international normalized ratio greater than 1.5, hemoglobin less than 11, and base deficit greater than 5. These critical indicators were then compared among the nodes of the classification tree. Patients omitted included those who did not receive PRBCs (n = 24) and those who did not have all eight critical indicators reported (n = 449). In a population of 1,245 patients, the classification tree included 772 patients. Analysis by recursive partitioning showed increased mortality among patients receiving greater than 13 U/h (73.9%, p < 0.01). In those patients receiving less than or equal to 13 U/h, mortality was greater in patients who received more than 4 U/h (16.7% vs. 6.0%, p < 0.01) (Fig. 1). Nodal analysis showed that the median number of critical indicators for each node was 3 (2-4) (≤4 U/h), 4 (3-5) (>4 U/h and ≤13 U/h), and 5 (4-5.5) (>13 U/h). A rate-based transfusion definition identifies a difference in mortality in patients who receive greater than 4 U/h of PRBCs. Redefining MT to greater than 4 U/h allows early identification of patients with a significant mortality risk who may be missed by the current definition. Prognostic/epidemiologic study, level III.

An efficient sampling approach for variance-based sensitivity analysis based on the law of total variance in the successive intervals without overlapping

NASA Astrophysics Data System (ADS)

Yun, Wanying; Lu, Zhenzhou; Jiang, Xian

2018-06-01

To efficiently execute the variance-based global sensitivity analysis, the law of total variance in the successive intervals without overlapping is proved at first, on which an efficient space-partition sampling-based approach is subsequently proposed in this paper. Through partitioning the sample points of output into different subsets according to different inputs, the proposed approach can efficiently evaluate all the main effects concurrently by one group of sample points. In addition, there is no need for optimizing the partition scheme in the proposed approach. The maximum length of subintervals is decreased by increasing the number of sample points of model input variables in the proposed approach, which guarantees the convergence condition of the space-partition approach well. Furthermore, a new interpretation on the thought of partition is illuminated from the perspective of the variance ratio function. Finally, three test examples and one engineering application are employed to demonstrate the accuracy, efficiency and robustness of the proposed approach.

Prognostic value of the Glasgow Prognostic Score for glioblastoma multiforme patients treated with radiotherapy and temozolomide.

PubMed

Topkan, Erkan; Selek, Ugur; Ozdemir, Yurday; Yildirim, Berna A; Guler, Ozan C; Ciner, Fuat; Mertsoylu, Huseyin; Tufan, Kadir

2018-04-25

To evaluate the prognostic value of the Glasgow Prognostic Score (GPS), the combination of C-reactive protein (CRP) and albumin, in glioblastoma multiforme (GBM) patients treated with radiotherapy (RT) and concurrent plus adjuvant temozolomide (GPS). Data of newly diagnosed GBM patients treated with partial brain RT and concurrent and adjuvant TMZ were retrospectively analyzed. The patients were grouped into three according to the GPS criteria: GPS-0: CRP < 10 mg/L and albumin > 35 g/L; GPS-1: CRP < 10 mg/L and albumin < 35 g/L or CRP > 10 mg/L and albumin > 35 g/L; and GPS-2: CRP > 10 mg/L and albumin < 35 g/L. Primary end-point was the association between the GPS groups and the overall survival (OS) outcomes. A total of 142 patients were analyzed (median age: 58 years, 66.2% male). There were 64 (45.1%), 40 (28.2%), and 38 (26.7%) patients in GPS-0, GPS-1, and GPS-2 groups, respectively. At median 15.7 months follow-up, the respective median and 5-year OS rates for the whole cohort were 16.2 months (95% CI 12.7-19.7) and 9.5%. In multivariate analyses GPS grouping emerged independently associated with the median OS (P < 0.001) in addition to the extent of surgery (P = 0.032), Karnofsky performance status (P = 0.009), and the Radiation Therapy Oncology Group recursive partitioning analysis (RTOG RPA) classification (P < 0.001). The GPS grouping and the RTOG RPA classification were found to be strongly correlated in prognostic stratification of GBM patients (correlation coefficient: 0.42; P < 0.001). The GPS appeared to be useful in prognostic stratification of GBM patients into three groups with significantly different survival durations resembling the RTOG RPA classification.

A comparison of the prognostic value of preoperative inflammation-based scores and TNM stage in patients with gastric cancer.

PubMed

Pan, Qun-Xiong; Su, Zi-Jian; Zhang, Jian-Hua; Wang, Chong-Ren; Ke, Shao-Ying

2015-01-01

People's Republic of China is one of the countries with the highest incidence of gastric cancer, accounting for 45% of all new gastric cancer cases in the world. Therefore, strong prognostic markers are critical for the diagnosis and survival of Chinese patients suffering from gastric cancer. Recent studies have begun to unravel the mechanisms linking the host inflammatory response to tumor growth, invasion and metastasis in gastric cancers. Based on this relationship between inflammation and cancer progression, several inflammation-based scores have been demonstrated to have prognostic value in many types of malignant solid tumors. To compare the prognostic value of inflammation-based prognostic scores and tumor node metastasis (TNM) stage in patients undergoing gastric cancer resection. The inflammation-based prognostic scores were calculated for 207 patients with gastric cancer who underwent surgery. Glasgow prognostic score (GPS), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), prognostic nutritional index (PNI), and prognostic index (PI) were analyzed. Linear trend chi-square test, likelihood ratio chi-square test, and receiver operating characteristic were performed to compare the prognostic value of the selected scores and TNM stage. In univariate analysis, preoperative serum C-reactive protein (P<0.001), serum albumin (P<0.001), GPS (P<0.001), PLR (P=0.002), NLR (P<0.001), PI (P<0.001), PNI (P<0.001), and TNM stage (P<0.001) were significantly associated with both overall survival and disease-free survival of patients with gastric cancer. In multivariate analysis, GPS (P=0.024), NLR (P=0.012), PI (P=0.001), TNM stage (P<0.001), and degree of differentiation (P=0.002) were independent predictors of gastric cancer survival. GPS and TNM stage had a comparable prognostic value and higher linear trend chi-square value, likelihood ratio chi-square value, and larger area under the receiver operating characteristic curve as compared to other inflammation-based prognostic scores. The present study indicates that preoperative GPS and TNM stage are robust predictors of gastric cancer survival as compared to NLR, PLR, PI, and PNI in patients undergoing tumor resection.

A comparison of the prognostic value of preoperative inflammation-based scores and TNM stage in patients with gastric cancer

PubMed Central

Pan, Qun-Xiong; Su, Zi-Jian; Zhang, Jian-Hua; Wang, Chong-Ren; Ke, Shao-Ying

2015-01-01

Background People’s Republic of China is one of the countries with the highest incidence of gastric cancer, accounting for 45% of all new gastric cancer cases in the world. Therefore, strong prognostic markers are critical for the diagnosis and survival of Chinese patients suffering from gastric cancer. Recent studies have begun to unravel the mechanisms linking the host inflammatory response to tumor growth, invasion and metastasis in gastric cancers. Based on this relationship between inflammation and cancer progression, several inflammation-based scores have been demonstrated to have prognostic value in many types of malignant solid tumors. Objective To compare the prognostic value of inflammation-based prognostic scores and tumor node metastasis (TNM) stage in patients undergoing gastric cancer resection. Methods The inflammation-based prognostic scores were calculated for 207 patients with gastric cancer who underwent surgery. Glasgow prognostic score (GPS), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), prognostic nutritional index (PNI), and prognostic index (PI) were analyzed. Linear trend chi-square test, likelihood ratio chi-square test, and receiver operating characteristic were performed to compare the prognostic value of the selected scores and TNM stage. Results In univariate analysis, preoperative serum C-reactive protein (P<0.001), serum albumin (P<0.001), GPS (P<0.001), PLR (P=0.002), NLR (P<0.001), PI (P<0.001), PNI (P<0.001), and TNM stage (P<0.001) were significantly associated with both overall survival and disease-free survival of patients with gastric cancer. In multivariate analysis, GPS (P=0.024), NLR (P=0.012), PI (P=0.001), TNM stage (P<0.001), and degree of differentiation (P=0.002) were independent predictors of gastric cancer survival. GPS and TNM stage had a comparable prognostic value and higher linear trend chi-square value, likelihood ratio chi-square value, and larger area under the receiver operating characteristic curve as compared to other inflammation-based prognostic scores. Conclusion The present study indicates that preoperative GPS and TNM stage are robust predictors of gastric cancer survival as compared to NLR, PLR, PI, and PNI in patients undergoing tumor resection. PMID:26124667

An inflammation-based cumulative prognostic score system in patients with diffuse large B cell lymphoma in rituximab era.

PubMed

Sun, Feifei; Zhu, Jia; Lu, Suying; Zhen, Zijun; Wang, Juan; Huang, Junting; Ding, Zonghui; Zeng, Musheng; Sun, Xiaofei

2018-01-02

Systemic inflammatory parameters are associated with poor outcomes in malignant patients. Several inflammation-based cumulative prognostic score systems were established for various solid tumors. However, there is few inflammation based cumulative prognostic score system for patients with diffuse large B cell lymphoma (DLBCL). We retrospectively reviewed 564 adult DLBCL patients who had received rituximab, cyclophosphamide, doxorubicin, vincristine and prednisolone (R-CHOP) therapy between Nov 1 2006 and Dec 30 2013 and assessed the prognostic significance of six systemic inflammatory parameters evaluated in previous studies by univariate and multivariate analysis:C-reactive protein(CRP), albumin levels, the lymphocyte-monocyte ratio (LMR), the neutrophil-lymphocyte ratio(NLR), the platelet-lymphocyte ratio(PLR)and fibrinogen levels. Multivariate analysis identified CRP, albumin levels and the LMR are three independent prognostic parameters for overall survival (OS). Based on these three factors, we constructed a novel inflammation-based cumulative prognostic score (ICPS) system. Four risk groups were formed: group ICPS = 0, ICPS = 1, ICPS = 2 and ICPS = 3. Advanced multivariate analysis indicated that the ICPS model is a prognostic score system independent of International Prognostic Index (IPI) for both progression-free survival (PFS) (p < 0.001) and OS (p < 0.001). The 3-year OS for patients with ICPS =0, ICPS =1, ICPS =2 and ICPS =3 were 95.6, 88.2, 76.0 and 62.2%, respectively (p < 0.001). The 3-year PFS for patients with ICPS = 0-1, ICPS = 2 and ICPS = 3 were 84.8, 71.6 and 54.5%, respectively (p < 0.001). The prognostic value of the ICPS model indicated that the degree of systemic inflammatory status was associated with clinical outcomes of patients with DLBCL in rituximab era. The ICPS model was shown to classify risk groups more accurately than any single inflammatory prognostic parameters. These findings may be useful for identifying candidates for further inflammation-related mechanism research or novel anti-inflammation target therapies.

Investigating a multigene prognostic assay based on significant pathways for Luminal A breast cancer through gene expression profile analysis.

PubMed

Gao, Haiyan; Yang, Mei; Zhang, Xiaolan

2018-04-01

The present study aimed to investigate potential recurrence-risk biomarkers based on significant pathways for Luminal A breast cancer through gene expression profile analysis. Initially, the gene expression profiles of Luminal A breast cancer patients were downloaded from The Cancer Genome Atlas database. The differentially expressed genes (DEGs) were identified using a Limma package and the hierarchical clustering analysis was conducted for the DEGs. In addition, the functional pathways were screened using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and rank ratio calculation. The multigene prognostic assay was exploited based on the statistically significant pathways and its prognostic function was tested using train set and verified using the gene expression data and survival data of Luminal A breast cancer patients downloaded from the Gene Expression Omnibus. A total of 300 DEGs were identified between good and poor outcome groups, including 176 upregulated genes and 124 downregulated genes. The DEGs may be used to effectively distinguish Luminal A samples with different prognoses verified by hierarchical clustering analysis. There were 9 pathways screened as significant pathways and a total of 18 DEGs involved in these 9 pathways were identified as prognostic biomarkers. According to the survival analysis and receiver operating characteristic curve, the obtained 18-gene prognostic assay exhibited good prognostic function with high sensitivity and specificity to both the train and test samples. In conclusion the 18-gene prognostic assay including the key genes, transcription factor 7-like 2, anterior parietal cortex and lymphocyte enhancer factor-1 may provide a new method for predicting outcomes and may be conducive to the promotion of precision medicine for Luminal A breast cancer.

Brain volume reduction after whole-brain radiotherapy: quantification and prognostic relevance.

PubMed

Hoffmann, Christian; Distel, Luitpold; Knippen, Stefan; Gryc, Thomas; Schmidt, Manuel Alexander; Fietkau, Rainer; Putz, Florian

2018-01-22

Recent studies have questioned the value of adding whole-brain radiotherapy (WBRT) to stereotactic radiosurgery (SRS) for brain metastasis treatment. Neurotoxicity, including radiation-induced brain volume reduction, could be one reason why not all patients benefit from the addition of WBRT. In this study, we quantified brain volume reduction after WBRT and assessed its prognostic significance. Brain volumes of 91 patients with cerebral metastases were measured during a 150-day period after commencing WBRT and were compared with their pretreatment volumes. The average daily relative change in brain volume of each patient, referred to as the "brain volume reduction rate," was calculated. Univariate and multivariate Cox regression analyses were performed to assess the prognostic significance of the brain volume reduction rate, as well as of 3 treatment-related and 9 pretreatment factors. A one-way analysis of variance was used to compare the brain volume reduction rate across recursive partitioning analysis (RPA) classes. On multivariate Cox regression analysis, the brain volume reduction rate was a significant predictor of overall survival after WBRT (P < 0.001), as well as the number of brain metastases (P = 0.002) and age (P = 0.008). Patients with a relatively favorable prognosis (RPA classes 1 and 2) experienced significantly less brain volume decrease after WBRT than patients with a poor prognosis (RPA class 3) (P = 0.001). There was no significant correlation between delivered radiation dose and brain volume reduction rate (P = 0.147). In this retrospective study, a smaller decrease in brain volume after WBRT was an independent predictor of longer overall survival. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Gastric cancer, nutritional status, and outcome.

PubMed

Liu, Xuechao; Qiu, Haibo; Kong, Pengfei; Zhou, Zhiwei; Sun, Xiaowei

2017-01-01

We aim to investigate the prognostic value of several nutrition-based indices, including the prognostic nutritional index (PNI), performance status, body mass index, serum albumin, and preoperative body weight loss in patients with gastric cancer (GC). We retrospectively analyzed the records of 1,330 consecutive patients with GC undergoing curative surgery between October 2000 and September 2012. The relationship between nutrition-based indices and overall survival (OS) was examined using Kaplan-Meier analysis and Cox regression model. Following multivariate analysis, the PNI and preoperative body weight loss were the only nutritional-based indices independently associated with OS (hazard ratio [HR]: 1.356, 95% confidence interval [CI]: 1.051-1.748, P =0.019; HR: 1.152, 95% CI: 1.014-1.310, P =0.030, retrospectively). In stage-stratified analysis, multivariate analysis revealed that preoperative body weight loss was identified as an independent prognostic factor only in patients with stage III GC (HR: 1.223, 95% CI: 1.065-1.405, P =0.004), while the prognostic significance of PNI was not significant (all P >0.05). In patients with stage III GC, preoperative body weight loss stratified 5-year OS from 41.1% to 26.5%. When stratified by adjuvant chemotherapy, the prognostic significance of preoperative body weight loss was maintained in patients treated with surgery plus adjuvant chemotherapy and in patients treated with surgery alone ( P <0.001; P =0.003). Preoperative body weight loss is an independent prognostic factor for OS in patients with GC, especially in stage III disease. Preoperative body weight loss appears to be a superior predictor of outcome compared with other established nutrition-based indices.

LPL is the strongest prognostic factor in a comparative analysis of RNA-based markers in early chronic lymphocytic leukemia.

PubMed

Kaderi, Mohd Arifin; Kanduri, Meena; Buhl, Anne Mette; Sevov, Marie; Cahill, Nicola; Gunnarsson, Rebeqa; Jansson, Mattias; Smedby, Karin Ekström; Hjalgrim, Henrik; Jurlander, Jesper; Juliusson, Gunnar; Mansouri, Larry; Rosenquist, Richard

2011-08-01

The expression levels of LPL, ZAP70, TCL1A, CLLU1 and MCL1 have recently been proposed as prognostic factors in chronic lymphocytic leukemia. However, few studies have systematically compared these different RNA-based markers. Using real-time quantitative PCR, we measured the mRNA expression levels of these genes in unsorted samples from 252 newly diagnosed chronic lymphocytic leukemia patients and correlated our data with established prognostic markers (for example Binet stage, CD38, IGHV gene mutational status and genomic aberrations) and clinical outcome. High expression levels of all RNA-based markers, except MCL1, predicted shorter overall survival and time to treatment, with LPL being the most significant. In multivariate analysis including the RNA-based markers, LPL expression was the only independent prognostic marker for overall survival and time to treatment. When studying LPL expression and the established markers, LPL expression retained its independent prognostic strength for overall survival. All of the RNA-based markers, albeit with varying ability, added prognostic information to established markers, with LPL expression giving the most significant results. Notably, high LPL expression predicted a worse outcome in good-prognosis subgroups, such as patients with mutated IGHV genes, Binet stage A, CD38 negativity or favorable cytogenetics. In particular, the combination of LPL expression and CD38 could further stratify Binet stage A patients. LPL expression is the strongest RNA-based prognostic marker in chronic lymphocytic leukemia that could potentially be applied to predict outcome in the clinical setting, particularly in the large group of patients with favorable prognosis.

Prognostic Value of Quantitative Stress Perfusion Cardiac Magnetic Resonance.

PubMed

Sammut, Eva C; Villa, Adriana D M; Di Giovine, Gabriella; Dancy, Luke; Bosio, Filippo; Gibbs, Thomas; Jeyabraba, Swarna; Schwenke, Susanne; Williams, Steven E; Marber, Michael; Alfakih, Khaled; Ismail, Tevfik F; Razavi, Reza; Chiribiri, Amedeo

2018-05-01

This study sought to evaluate the prognostic usefulness of visual and quantitative perfusion cardiac magnetic resonance (CMR) ischemic burden in an unselected group of patients and to assess the validity of consensus-based ischemic burden thresholds extrapolated from nuclear studies. There are limited data on the prognostic value of assessing myocardial ischemic burden by CMR, and there are none using quantitative perfusion analysis. Patients with suspected coronary artery disease referred for adenosine-stress perfusion CMR were included (n = 395; 70% male; age 58 ± 13 years). The primary endpoint was a composite of cardiovascular death, nonfatal myocardial infarction, aborted sudden death, and revascularization after 90 days. Perfusion scans were assessed visually and with quantitative analysis. Cross-validated Cox regression analysis and net reclassification improvement were used to assess the incremental prognostic value of visual or quantitative perfusion analysis over a baseline clinical model, initially as continuous covariates, then using accepted thresholds of ≥2 segments or ≥10% myocardium. After a median 460 days (interquartile range: 190 to 869 days) follow-up, 52 patients reached the primary endpoint. At 2 years, the addition of ischemic burden was found to increase prognostic value over a baseline model of age, sex, and late gadolinium enhancement (baseline model area under the curve [AUC]: 0.75; visual AUC: 0.84; quantitative AUC: 0.85). Dichotomized quantitative ischemic burden performed better than visual assessment (net reclassification improvement 0.043 vs. 0.003 against baseline model). This study was the first to address the prognostic benefit of quantitative analysis of perfusion CMR and to support the use of consensus-based ischemic burden thresholds by perfusion CMR for prognostic evaluation of patients with suspected coronary artery disease. Quantitative analysis provided incremental prognostic value to visual assessment and established risk factors, potentially representing an important step forward in the translation of quantitative CMR perfusion analysis to the clinical setting. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review.

PubMed

Chen, Jia-Mei; Li, Yan; Xu, Jun; Gong, Lei; Wang, Lin-Wei; Liu, Wen-Lou; Liu, Juan

2017-03-01

With the advance of digital pathology, image analysis has begun to show its advantages in information analysis of hematoxylin and eosin histopathology images. Generally, histological features in hematoxylin and eosin images are measured to evaluate tumor grade and prognosis for breast cancer. This review summarized recent works in image analysis of hematoxylin and eosin histopathology images for breast cancer prognosis. First, prognostic factors for breast cancer based on hematoxylin and eosin histopathology images were summarized. Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. Finally, the prognostic value of image features and image feature-based prognostic models was evaluated. Moreover, we discussed the issues of current analysis, and some directions for future research.

A clinical analysis of brain metastasis in gynecologic cancer: a retrospective multi-institute analysis.

PubMed

Kim, Young Zoon; Kwon, Jae Hyun; Lim, Soyi

2015-01-01

This study analyzes the clinical characteristics of the brain metastasis (BM) of gynecologic cancer based on the type of cancer. In addition, the study examines the factors influencing the survival. Total 61 BM patients of gynecologic cancer were analyzed retrospectively from January 2000 to December 2012 in terms of clinical and radiological characteristics by using medical and radiological records from three university hospitals. There were 19 (31.1%) uterine cancers, 32 (52.5%) ovarian cancers, and 10 (16.4%) cervical cancers. The mean interval to BM was 25.4 months (21.6 months in ovarian cancer, 27.8 months in uterine cancer, and 33.1 months in cervical cancer). The mean survival from BM was 16.7 months (14.1 months in ovarian cancer, 23.3 months in uterine cancer, and 8.8 months in cervical cancer). According to a multivariate analysis of factors influencing survival, type of primary cancer, Karnofsky performance score, status of primary cancer, recursive partitioning analysis class, and treatment modality, particularly combined therapies, were significantly related to the overall survival. These results suggest that, in addition to traditional prognostic factors in BM, multiple treatment methods such as neurosurgery and combined chemoradiotherapy may play an important role in prolonging the survival for BM patients of gynecologic cancer.

[On the partition of acupuncture academic schools].

PubMed

Yang, Pengyan; Luo, Xi; Xia, Youbing

2016-05-01

Nowadays extensive attention has been paid on the research of acupuncture academic schools, however, a widely accepted method of partition of acupuncture academic schools is still in need. In this paper, the methods of partition of acupuncture academic schools in the history have been arranged, and three typical methods of"partition of five schools" "partition of eighteen schools" and "two-stage based partition" are summarized. After adeep analysis on the disadvantages and advantages of these three methods, a new method of partition of acupuncture academic schools that is called "three-stage based partition" is proposed. In this method, after the overall acupuncture academic schools are divided into an ancient stage, a modern stage and a contemporary stage, each schoolis divided into its sub-school category. It is believed that this method of partition can remedy the weaknesses ofcurrent methods, but also explore a new model of inheritance and development under a different aspect through thedifferentiation and interaction of acupuncture academic schools at three stages.

Prognostic risk stratification derived from individual patient level data for men with advanced penile squamous cell carcinoma receiving first-line systemic therapy.

PubMed

Pond, Gregory R; Di Lorenzo, Giuseppe; Necchi, Andrea; Eigl, Bernhard J; Kolinsky, Michael P; Chacko, Raju T; Dorff, Tanya B; Harshman, Lauren C; Milowsky, Matthew I; Lee, Richard J; Galsky, Matthew D; Federico, Piera; Bolger, Graeme; DeShazo, Mollie; Mehta, Amitkumar; Goyal, Jatinder; Sonpavde, Guru

2014-05-01

Prognostic factors in men with penile squamous cell carcinoma (PSCC) receiving systemic therapy are unknown. A prognostic classification system in this disease may facilitate interpretation of outcomes and guide rational drug development. We performed a retrospective analysis to identify prognostic factors in men with PSCC receiving first-line systemic therapy for advanced disease. Individual patient level data were obtained from 13 institutions to study prognostic factors in the context of first-line systemic therapy for advanced PSCC. Cox proportional hazards regression analysis was conducted to examine the prognostic effect of these candidate factors on progression-free survival (PFS) and overall survival (OS): age, stage, hemoglobin, neutrophil count, lymphocyte count, albumin, site of metastasis (visceral or nonvisceral), smoking, circumcision, regimen, ECOG performance status (PS), lymphovascular invasion, precancerous lesion, and surgery following chemotherapy. The effect of different treatments was then evaluated adjusting for factors in the prognostic model. The study included 140 eligible men. Mean age across all men was 57.0 years. Among them, 8.6%, 21.4%, and 70.0% of patients had stage 2, 3, and 4 diseases, respectively; 40.7% had ECOG PS ≥ 1, 47.4% had visceral metastases, and 73.6% received cisplatin-based chemotherapy. The multivariate model of poor prognostic factors included visceral metastases (P<0.001) and ECOG PS ≥ 1 (P<0.001) for both PFS and OS. A risk stratification model constructed with 0, 1, and both poor prognostic factors was internally validated and demonstrated moderate discriminatory ability (c-statistic of 0.657 and 0.677 for OS and PFS, respectively). The median OS for the entire population was 9 months. Median OS was not reached, 8, and 7 months for those with 0, 1, and both risk factors, respectively. Cisplatin-based regimens were associated with better OS (P = 0.017) but not PFS (P = 0.37) compared with noncisplatin-based regimens after adjusting for the 2 prognostic factors. In men with advanced PSCC receiving first-line systemic therapy, visceral metastases and ECOG PS ≥ 1 were poor prognostic factors. A prognostic model including these factors exhibited moderate discriminatory ability for outcomes and warrants external validation. Patients receiving cisplatin-based regimens exhibited better outcomes compared with noncisplatin-based regimens after adjusting for prognostic factors. © 2013 Published by Elsevier Inc.

Comparison of Modeling Approaches for Carbon Partitioning: Impact on Estimates of Global Net Primary Production and Equilibrium Biomass of Woody Vegetation from MODIS GPP

NASA Astrophysics Data System (ADS)

Ise, T.; Litton, C. M.; Giardina, C. P.; Ito, A.

2009-12-01

Plant partitioning of carbon (C) to above- vs. belowground, to growth vs. respiration, and to short vs. long lived tissues exerts a large influence on ecosystem structure and function with implications for the global C budget. Importantly, outcomes of process-based terrestrial vegetation models are likely to vary substantially with different C partitioning algorithms. However, controls on C partitioning patterns remain poorly quantified, and studies have yielded variable, and at times contradictory, results. A recent meta-analysis of forest studies suggests that the ratio of net primary production (NPP) and gross primary production (GPP) is fairly conservative across large scales. To illustrate the effect of this unique meta-analysis-based partitioning scheme (MPS), we compared an application of MPS to a terrestrial satellite-based (MODIS) GPP to estimate NPP vs. two global process-based vegetation models (Biome-BGC and VISIT) to examine the influence of C partitioning on C budgets of woody plants. Due to the temperature dependence of maintenance respiration, NPP/GPP predicted by the process-based models increased with latitude while the ratio remained constant with MPS. Overall, global NPP estimated with MPS was 17 and 27% lower than the process-based models for temperate and boreal biomes, respectively, with smaller differences in the tropics. Global equilibrium biomass of woody plants was then calculated from the NPP estimates and tissue turnover rates from VISIT. Since turnover rates differed greatly across tissue types (i.e., metabolically active vs. structural), global equilibrium biomass estimates were sensitive to the partitioning scheme employed. The MPS estimate of global woody biomass was 7-21% lower than that of the process-based models. In summary, we found that model output for NPP and equilibrium biomass was quite sensitive to the choice of C partitioning schemes. Carbon use efficiency (CUE; NPP/GPP) by forest biome and the globe. Values are means for 2001-2006.

A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

DOE PAGES

Wang, Pin; Wang, Yunshan; Hang, Bo; ...

2016-07-11

Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A networkmore » was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.« less

A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Pin; Wang, Yunshan; Hang, Bo

Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A networkmore » was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.« less

An iterative network partition algorithm for accurate identification of dense network modules

PubMed Central

Sun, Siqi; Dong, Xinran; Fu, Yao; Tian, Weidong

2012-01-01

A key step in network analysis is to partition a complex network into dense modules. Currently, modularity is one of the most popular benefit functions used to partition network modules. However, recent studies suggested that it has an inherent limitation in detecting dense network modules. In this study, we observed that despite the limitation, modularity has the advantage of preserving the primary network structure of the undetected modules. Thus, we have developed a simple iterative Network Partition (iNP) algorithm to partition a network. The iNP algorithm provides a general framework in which any modularity-based algorithm can be implemented in the network partition step. Here, we tested iNP with three modularity-based algorithms: multi-step greedy (MSG), spectral clustering and Qcut. Compared with the original three methods, iNP achieved a significant improvement in the quality of network partition in a benchmark study with simulated networks, identified more modules with significantly better enrichment of functionally related genes in both yeast protein complex network and breast cancer gene co-expression network, and discovered more cancer-specific modules in the cancer gene co-expression network. As such, iNP should have a broad application as a general method to assist in the analysis of biological networks. PMID:22121225

An internally validated new clinical and inflammation-based prognostic score for patients with advanced hepatocellular carcinoma treated with sorafenib.

PubMed

Diaz-Beveridge, R; Bruixola, G; Lorente, D; Caballero, J; Rodrigo, E; Segura, Á; Akhoundova, D; Giménez, A; Aparicio, J

2018-03-01

Sorafenib is a standard treatment for patients (pts) with advanced hepatocellular carcinoma (aHCC), although the clinical benefit is heterogeneous between different pts groups. Among novel prognostic factors, a low baseline neutrophil-to-lymphocyte ratio (bNLR) and early-onset diarrhoea have been linked with a better prognosis. To identify prognostic factors in pts with aHCC treated with 1st-line sorafenib and to develop a new prognostic score to guide management. Retrospective review of 145 pts bNLR, overall toxicity, early toxicity rates and overall survival (OS) were assessed. Univariate and multivariate analysis of prognostic factors for OS was performed. The prognostic score was calculated from the coefficients found in the Cox analysis. ROC curves and pseudoR2 index were used for internal validation. Discrimination ability and calibration were tested by Harrel's c-index (HCI) and Akaike criteria (AIC). The optimal bNLR cut-off for the prediction of OS was 4 (AUC 0.62). Independent prognostic factors in multivariate analysis for OS were performance status (PS) (p < .0001), Child-Pugh (C-P) score (p = 0.005), early-onset diarrhoea (p = 0.006) and BNLR (0.011). The prognostic score based on these four variables was found efficient (HCI = 0.659; AIC = 1.180). Four risk groups for OS could be identified: a very low-risk (median OS = 48.6 months), a low-risk (median OS = 11.6 months), an intermediate-risk (median OS = 8.3 months) and a high-risk group (median OS = 4.4 months). PS and C-P score were the main prognostic factors for OS, followed by early-onset diarrhoea and bNLR. We identified four risk groups for OS depending on these parameters. This prognostic model could be useful for patient stratification, but an external validation is needed.

Can texture analysis of tooth microwear detect within guild niche partitioning in extinct species?

NASA Astrophysics Data System (ADS)

Purnell, Mark; Nedza, Christopher; Rychlik, Leszek

2017-04-01

Recent work shows that tooth microwear analysis can be applied further back in time and deeper into the phylogenetic history of vertebrate clades than previously thought (e.g. niche partitioning in early Jurassic insectivorous mammals; Gill et al., 2014, Nature). Furthermore, quantitative approaches to analysis based on parameterization of surface roughness are increasing the robustness and repeatability of this widely used dietary proxy. Discriminating between taxa within dietary guilds has the potential to significantly increase our ability to determine resource use and partitioning in fossil vertebrates, but how sensitive is the technique? To address this question we analysed tooth microwear texture in sympatric populations of shrew species (Neomys fodiens, Neomys anomalus, Sorex araneus, Sorex minutus) from BiaŁ owieza Forest, Poland. These populations are known to exhibit varying degrees of niche partitioning (Churchfield & Rychlik, 2006, J. Zool.) with greatest overlap between the Neomys species. Sorex araneus also exhibits some niche overlap with N. anomalus, while S. minutus is the most specialised. Multivariate analysis based only on tooth microwear textures recovers the same pattern of niche partitioning. Our results also suggest that tooth textures track seasonal differences in diet. Projecting data from fossils into the multivariate dietary space defined using microwear from extant taxa demonstrates that the technique is capable of subtle dietary discrimination in extinct insectivores.

Breast cancer brain metastases: differences in survival depending on biological subtype, RPA RTOG prognostic class and systemic treatment after whole-brain radiotherapy (WBRT).

PubMed

Niwińska, A; Murawska, M; Pogoda, K

2010-05-01

Patients with breast cancer brain metastasis are a heterogeneous group in relation to tumor biology and outcome. The group of 222 breast cancer patients with brain metastasis was divided into three biological subgroups. The propensity of biological subtypes for metastases to the brain and survivals depending on biological subtype, recursive partitioning analysis of Radiation Therapy Oncology Group (RPA RTOG) prognostic class and the use of systemic treatment after whole-brain radiotherapy were assessed. The rate of patients with triple-negative, human epidermal growth factor receptor 2 (HER2)-positive and luminal breast cancer with brain metastases was 28%, 53% and 19%, respectively. Median survival from brain metastases in triple-negative, HER2-positive and luminal subtype was 3.7, 9 and 15 months, respectively. Median survival from brain metastases in RPA RTOG prognostic class I, II and III was 15, 11 and 3 months, respectively. In the luminal and in the triple-negative subtype, systemic therapy prolonged survival from 3 to 14 months and from 3 to 4 months, respectively. In HER2-positive subtype, median survival without further treatment, after chemotherapy and after chemotherapy with targeted therapy were 3, 8 and 11 months, respectively. HER2-positive and triple-negative breast cancers have special predilection for metastases to the brain. Survival from brain metastases depended on performance status and the use of systemic treatment.

Partitioning Strategy Using Static Analysis Techniques

NASA Astrophysics Data System (ADS)

Seo, Yongjin; Soo Kim, Hyeon

2016-08-01

Flight software is software used in satellites' on-board computers. It has requirements such as real time and reliability. The IMA architecture is used to satisfy these requirements. The IMA architecture has the concept of partitions and this affected the configuration of flight software. That is, situations occurred in which software that had been loaded on one system was divided into many partitions when being loaded. For new issues, existing studies use experience based partitioning methods. However, these methods have a problem that they cannot be reused. In this respect, this paper proposes a partitioning method that is reusable and consistent.

Nutritional prognostic scores in patients with hilar cholangiocarcinoma treated by percutaneous transhepatic biliary stenting combined with 125I seed intracavitary irradiation: A retrospective observational study.

PubMed

Cui, Peiyuan; Pang, Qing; Wang, Yong; Qian, Zhen; Hu, Xiaosi; Wang, Wei; Li, Zongkuang; Zhou, Lei; Man, Zhongran; Yang, Song; Jin, Hao; Liu, Huichun

2018-06-01

We mainly aimed to preliminarily explore the prognostic values of nutrition-based prognostic scores in patients with advanced hilar cholangiocarcinoma (HCCA).We retrospectively analyzed 73 cases of HCCA, who underwent percutaneous transhepatic biliary stenting (PTBS) combined with I seed intracavitary irradiation from November 2012 to April 2017 in our department. The postoperative changes of total bilirubin (TBIL), direct bilirubin (DBIL), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and albumin (ALB) were observed. The preoperative clinical data were collected to calculate the nutrition-based scores, including controlling nutritional status (CONUT), C-reactive protein/albumin ratio (CAR), and prognostic nutritional index (PNI). Kaplan-Meier curve and Cox regression model were used for overall survival (OS) analyses.The serum levels of TBIL, DBIL, ALT, AST, and ALP significantly reduced, and ALB significantly increased at 1 month and 3 months postoperatively. The median survival time of the cohort was 12 months and the 1-year survival rate was 53.1%. Univariate analysis revealed that the statistically significant factors related to OS were CA19-9, TBIL, ALB, CONUT, and PNI. Multivariate analysis further identified CA19-9, CONUT, and PNI as independent prognostic factors.Nutrition-based prognostic scores, CONUT and PNI in particular, can be used as predictors of survival in unresectable HCCA.

A new extranodal scoring system based on the prognostically relevant extranodal sites in diffuse large B-cell lymphoma, not otherwise specified treated with chemoimmunotherapy.

PubMed

Hwang, Hee Sang; Yoon, Dok Hyun; Suh, Cheolwon; Huh, Jooryung

2016-08-01

Extranodal involvement is a well-known prognostic factor in patients with diffuse large B-cell lymphomas (DLBCL). Nevertheless, the prognostic impact of the extranodal scoring system included in the conventional international prognostic index (IPI) has been questioned in an era where rituximab treatment has become widespread. We investigated the prognostic impacts of individual sites of extranodal involvement in 761 patients with DLBCL who received rituximab-based chemoimmunotherapy. Subsequently, we established a new extranodal scoring system based on extranodal sites, showing significant prognostic correlation, and compared this system with conventional scoring systems, such as the IPI and the National Comprehensive Cancer Network-IPI (NCCN-IPI). An internal validation procedure, using bootstrapped samples, was also performed for both univariate and multivariate models. Using multivariate analysis with a backward variable selection, we found nine extranodal sites (the liver, lung, spleen, central nervous system, bone marrow, kidney, skin, adrenal glands, and peritoneum) that remained significant for use in the final model. Our newly established extranodal scoring system, based on these sites, was better correlated with patient survival than standard scoring systems, such as the IPI and the NCCN-IPI. Internal validation by bootstrapping demonstrated an improvement in model performance of our modified extranodal scoring system. Our new extranodal scoring system, based on the prognostically relevant sites, may improve the performance of conventional prognostic models of DLBCL in the rituximab era and warrants further external validation using large study populations.

Metabolic flux ratio analysis and cell staining suggest the existence of C4 photosynthesis in Phaeodactylum tricornutum.

PubMed

Huang, A; Liu, L; Zhao, P; Yang, C; Wang, G C

2016-03-01

Mechanisms for carbon fixation via photosynthesis in the diatom Phaeodactylum tricornutum Bohlin were studied recently but there remains a long-standing debate concerning the occurrence of C4 photosynthesis in this species. A thorough investigation of carbon metabolism and the evidence for C4 photosynthesis based on organelle partitioning was needed. In this study, we identified the flux ratios between C3 and C4 compounds in P. tricornutum using (13)C-labelling metabolic flux ratio analysis, and stained cells with various cell-permeant fluorescent probes to investigate the likely organelle partitioning required for single-cell C4 photosynthesis. Metabolic flux ratio analysis indicated the C3/C4 exchange ratios were high. Cell staining indicated organelle partitioning required for single-cell C4 photosynthesis might exist in P. tricornutum. The results of (13)C-labelling metabolic flux ratio analysis and cell staining suggest single-cell C4 photosynthesis exists in P. tricornutum. This study provides insights into photosynthesis patterns of P. tricornutum and the evidence for C4 photosynthesis based on (13)C-labelling metabolic flux ratio analysis and organelle partitioning. © 2015 The Society for Applied Microbiology.

Identification of prohibitin 1 as a potential prognostic biomarker in human pancreatic carcinoma using modified aqueous two-phase partition system combined with 2D-MALDI-TOF-TOF-MS/MS.

PubMed

Zhong, Ning; Cui, Yazhou; Zhou, Xiaoyan; Li, Tianliang; Han, Jinxiang

2015-02-01

Membrane proteins are an important source of potential targets for anticancer drugs or biomarkers for early diagnosis. In this study, we used a modified aqueous two-phase partition system combined with two-dimensional (2D) matrix-assisted laser desorption ionization (MALDI) time of flight (TOF) mass spectrometry (MS, 2D-MALDI-TOF-TOF-MS/MS) analysis to isolate and identify membrane proteins in PANC-1 pancreatic cancer cells. Using this method, we identified 55 proteins, of which 31 (56.4 %) were membrane proteins, which, according to gene ontology annotation, are associated with various cellular processes including cell signal transduction, differentiation, and apoptosis. Immunohistochemical analysis showed that the expression level of one of the identified mitochondria membrane proteins, prohibitin 1 (PHB1), is correlated with pancreatic carcinoma differentiation; PHB1 is expressed at a higher level in normal pancreatic tissue than in well-differentiated carcinoma tissue. Further studies showed that PHB1 plays a proapoptotic role in human pancreatic cancer cells, which suggests that PHB1 has antitumorigenic properties. In conclusion, we have provided a modified method for isolating and identifying membrane proteins and demonstrated that PHB1 may be a promising biomarker for early diagnosis and therapy of pancreatic (and potentially other) cancers.

Multivariate analysis of prognostic factors in synovial sarcoma.

PubMed

Koh, Kyoung Hwan; Cho, Eun Yoon; Kim, Dong Wook; Seo, Sung Wook

2009-11-01

Many studies have described the diversity of synovial sarcoma in terms of its biological characteristics and clinical features. Moreover, much effort has been expended on the identification of prognostic factors because of unpredictable behaviors of synovial sarcomas. However, with the exception of tumor size, published results have been inconsistent. We attempted to identify independent risk factors using survival analysis. Forty-one consecutive patients with synovial sarcoma were prospectively followed from January 1997 to March 2008. Overall and progression-free survival for age, sex, tumor size, tumor location, metastasis at presentation, histologic subtype, chemotherapy, radiation therapy, and resection margin were analyzed, and standard multivariate Cox proportional hazard regression analysis was used to evaluate potential prognostic factors. Tumor size (>5 cm), nonlimb-based tumors, metastasis at presentation, and a monophasic subtype were associated with poorer overall survival. Multivariate analysis showed metastasis at presentation and monophasic tumor subtype affected overall survival. For the progression-free survival, monophasic subtype was found to be only 1 prognostic factor. The study confirmed that histologic subtype is the single most important independent prognostic factors of synovial sarcoma regardless of tumor stage.

SAMPLING AND ANALYSIS OF SEMIVOLATILE AEROSOLS

EPA Science Inventory

Denuder based samplers can effectively separate semivolatile gases from particles and 'freeze' the partitioning in time. Conversely, samples collected on filters partition mass according to the conditions of the influent airstream, which may change over time. As a result thes...

ESTimating plant phylogeny: lessons from partitioning

PubMed Central

de la Torre, Jose EB; Egan, Mary G; Katari, Manpreet S; Brenner, Eric D; Stevenson, Dennis W; Coruzzi, Gloria M; DeSalle, Rob

2006-01-01

Background While Expressed Sequence Tags (ESTs) have proven a viable and efficient way to sample genomes, particularly those for which whole-genome sequencing is impractical, phylogenetic analysis using ESTs remains difficult. Sequencing errors and orthology determination are the major problems when using ESTs as a source of characters for systematics. Here we develop methods to incorporate EST sequence information in a simultaneous analysis framework to address controversial phylogenetic questions regarding the relationships among the major groups of seed plants. We use an automated, phylogenetically derived approach to orthology determination called OrthologID generate a phylogeny based on 43 process partitions, many of which are derived from ESTs, and examine several measures of support to assess the utility of EST data for phylogenies. Results A maximum parsimony (MP) analysis resulted in a single tree with relatively high support at all nodes in the tree despite rampant conflict among trees generated from the separate analysis of individual partitions. In a comparison of broader-scale groupings based on cellular compartment (ie: chloroplast, mitochondrial or nuclear) or function, only the nuclear partition tree (based largely on EST data) was found to be topologically identical to the tree based on the simultaneous analysis of all data. Despite topological conflict among the broader-scale groupings examined, only the tree based on morphological data showed statistically significant differences. Conclusion Based on the amount of character support contributed by EST data which make up a majority of the nuclear data set, and the lack of conflict of the nuclear data set with the simultaneous analysis tree, we conclude that the inclusion of EST data does provide a viable and efficient approach to address phylogenetic questions within a parsimony framework on a genomic scale, if problems of orthology determination and potential sequencing errors can be overcome. In addition, approaches that examine conflict and support in a simultaneous analysis framework allow for a more precise understanding of the evolutionary history of individual process partitions and may be a novel way to understand functional aspects of different kinds of cellular classes of gene products. PMID:16776834

Novel immunological and nutritional-based prognostic index for gastric cancer.

PubMed

Sun, Kai-Yu; Xu, Jian-Bo; Chen, Shu-Ling; Yuan, Yu-Jie; Wu, Hui; Peng, Jian-Jun; Chen, Chuang-Qi; Guo, Pi; Hao, Yuan-Tao; He, Yu-Long

2015-05-21

To assess the prognostic significance of immunological and nutritional-based indices, including the prognostic nutritional index (PNI), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio in gastric cancer. We retrospectively reviewed 632 gastric cancer patients who underwent gastrectomy between 1998 and 2008. Areas under the receiver operating characteristic curve were calculated to compare the predictive ability of the indices, together with estimating the sensitivity, specificity and agreement rate. Univariate and multivariate analyses were performed to identify risk factors for overall survival (OS). Propensity score analysis was performed to adjust variables to control for selection bias. Each index could predict OS in gastric cancer patients in univariate analysis, but only PNI had independent prognostic significance in multivariate analysis before and after adjustment with propensity scoring (hazard ratio, 1.668; 95% confidence interval: 1.368-2.035). In subgroup analysis, a low PNI predicted a significantly shorter OS in patients with stage II-III disease (P = 0.019, P < 0.001), T3-T4 tumors (P < 0.001), or lymph node metastasis (P < 0.001). Canton score, a combination of PNI, NLR, and platelet, was a better indicator for OS than PNI, with the largest area under the curve for 12-, 36-, 60-mo OS and overall OS (P = 0.022, P = 0.030, P < 0.001, and P = 0.024, respectively). The maximum sensitivity, specificity, and agreement rate of Canton score for predicting prognosis were 84.6%, 34.9%, and 70.1%, respectively. PNI is an independent prognostic factor for OS in gastric cancer. Canton score can be a novel preoperative prognostic index in gastric cancer.

Brain Network Regional Synchrony Analysis in Deafness

PubMed Central

Xu, Lei; Liang, Mao-Jin

2018-01-01

Deafness, the most common auditory disease, has greatly affected people for a long time. The major treatment for deafness is cochlear implantation (CI). However, till today, there is still a lack of objective and precise indicator serving as evaluation of the effectiveness of the cochlear implantation. The goal of this EEG-based study is to effectively distinguish CI children from those prelingual deafened children without cochlear implantation. The proposed method is based on the functional connectivity analysis, which focuses on the brain network regional synchrony. Specifically, we compute the functional connectivity between each channel pair first. Then, we quantify the brain network synchrony among regions of interests (ROIs), where both intraregional synchrony and interregional synchrony are computed. And finally the synchrony values are concatenated to form the feature vector for the SVM classifier. What is more, we develop a new ROI partition method of 128-channel EEG recording system. That is, both the existing ROI partition method and the proposed ROI partition method are used in the experiments. Compared with the existing EEG signal classification methods, our proposed method has achieved significant improvements as large as 87.20% and 86.30% when the existing ROI partition method and the proposed ROI partition method are used, respectively. It further demonstrates that the new ROI partition method is comparable to the existing ROI partition method. PMID:29854776

Gene Expression Analysis Of Circulating Hormone Refractory Prostate Cancer Micrometastases

DTIC Science & Technology

2011-02-01

of prostate cancer. We hypothesized that the copy number changes could be prognostic and aid in future chemotherapy regimen selection. After...Task 1 will be analyzed over the next year to elicit statistically meaningful prognostic DNA based biomarkers. Two of the patients (#8 and #13) had...HRPC), and to determine whether CECs can be used to predict survival in these patients. PATIENTS AND METHODS Several prognostic models that

Revisiting the immune microenvironment of diffuse large B-cell lymphoma using a tissue microarray and immunohistochemistry: robust semi-automated analysis reveals CD3 and FoxP3 as potential predictors of response to R-CHOP

PubMed Central

Coutinho, Rita; Clear, Andrew J.; Mazzola, Emanuele; Owen, Andrew; Greaves, Paul; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; da Silva, Maria Gomes; Cabeçadas, José; Neuberg, Donna; Calaminici, Maria; Gribben, John G.

2015-01-01

Gene expression studies have identified the microenvironment as a prognostic player in diffuse large B-cell lymphoma. However, there is a lack of simple immune biomarkers that can be applied in the clinical setting and could be helpful in stratifying patients. Immunohistochemistry has been used for this purpose but the results are inconsistent. We decided to reinvestigate the immune microenvironment and its impact using immunohistochemistry, with two systems of image analysis, in a large set of patients with diffuse large B-cell lymphoma. Diagnostic tissue from 309 patients was arrayed onto tissue microarrays. Results from 161 chemoimmunotherapy-treated patients were used for outcome prediction. Positive cells, percentage stained area and numbers of pixels/area were quantified and results were compared with the purpose of inferring consistency between the two semi-automated systems. Measurement cutpoints were assessed using a recursive partitioning algorithm classifying results according to survival. Kaplan-Meier estimators and Fisher exact tests were evaluated to check for significant differences between measurement classes, and for dependence between pairs of measurements, respectively. Results were validated by multivariate analysis incorporating the International Prognostic Index. The concordance between the two systems of image analysis was surprisingly high, supporting their applicability for immunohistochemistry studies. Patients with a high density of CD3 and FoxP3 by both methods had a better outcome. Automated analysis should be the preferred method for immunohistochemistry studies. Following the use of two methods of semi-automated analysis we suggest that CD3 and FoxP3 play a role in predicting response to chemoimmunotherapy in diffuse large B-cell lymphoma. PMID:25425693

Revisiting the immune microenvironment of diffuse large B-cell lymphoma using a tissue microarray and immunohistochemistry: robust semi-automated analysis reveals CD3 and FoxP3 as potential predictors of response to R-CHOP.

PubMed

Coutinho, Rita; Clear, Andrew J; Mazzola, Emanuele; Owen, Andrew; Greaves, Paul; Wilson, Andrew; Matthews, Janet; Lee, Abigail; Alvarez, Rute; da Silva, Maria Gomes; Cabeçadas, José; Neuberg, Donna; Calaminici, Maria; Gribben, John G

2015-03-01

Gene expression studies have identified the microenvironment as a prognostic player in diffuse large B-cell lymphoma. However, there is a lack of simple immune biomarkers that can be applied in the clinical setting and could be helpful in stratifying patients. Immunohistochemistry has been used for this purpose but the results are inconsistent. We decided to reinvestigate the immune microenvironment and its impact using immunohistochemistry, with two systems of image analysis, in a large set of patients with diffuse large B-cell lymphoma. Diagnostic tissue from 309 patients was arrayed onto tissue microarrays. Results from 161 chemoimmunotherapy-treated patients were used for outcome prediction. Positive cells, percentage stained area and numbers of pixels/area were quantified and results were compared with the purpose of inferring consistency between the two semi-automated systems. Measurement cutpoints were assessed using a recursive partitioning algorithm classifying results according to survival. Kaplan-Meier estimators and Fisher exact tests were evaluated to check for significant differences between measurement classes, and for dependence between pairs of measurements, respectively. Results were validated by multivariate analysis incorporating the International Prognostic Index. The concordance between the two systems of image analysis was surprisingly high, supporting their applicability for immunohistochemistry studies. Patients with a high density of CD3 and FoxP3 by both methods had a better outcome. Automated analysis should be the preferred method for immunohistochemistry studies. Following the use of two methods of semi-automated analysis we suggest that CD3 and FoxP3 play a role in predicting response to chemoimmunotherapy in diffuse large B-cell lymphoma. Copyright© Ferrata Storti Foundation.

Multi-viewpoint clustering analysis

NASA Technical Reports Server (NTRS)

Mehrotra, Mala; Wild, Chris

1993-01-01

In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems.

Identifying prognostic signature in ovarian cancer using DirGenerank

PubMed Central

Wang, Jian-Yong; Chen, Ling-Ling; Zhou, Xiong-Hui

2017-01-01

Identifying the prognostic genes in cancer is essential not only for the treatment of cancer patients, but also for drug discovery. However, it's still a big challenge to select the prognostic genes that can distinguish the risk of cancer patients across various data sets because of tumor heterogeneity. In this situation, the selected genes whose expression levels are statistically related to prognostic risks may be passengers. In this paper, based on gene expression data and prognostic data of ovarian cancer patients, we used conditional mutual information to construct gene dependency network in which the nodes (genes) with more out-degrees have more chances to be the modulators of cancer prognosis. After that, we proposed DirGenerank (Generank in direct netowrk) algorithm, which concerns both the gene dependency network and genes’ correlations to prognostic risks, to identify the gene signature that can predict the prognostic risks of ovarian cancer patients. Using ovarian cancer data set from TCGA (The Cancer Genome Atlas) as training data set, 40 genes with the highest importance were selected as prognostic signature. Survival analysis of these patients divided by the prognostic signature in testing data set and four independent data sets showed the signature can distinguish the prognostic risks of cancer patients significantly. Enrichment analysis of the signature with curated cancer genes and the drugs selected by CMAP showed the genes in the signature may be drug targets for therapy. In summary, we have proposed a useful pipeline to identify prognostic genes of cancer patients. PMID:28615526

Plant interspecies competition for sunlight: a mathematical model of canopy partitioning.

PubMed

Nevai, Andrew L; Vance, Richard R

2007-07-01

We examine the influence of canopy partitioning on the outcome of competition between two plant species that interact only by mutually shading each other. This analysis is based on a Kolmogorov-type canopy partitioning model for plant species with clonal growth form and fixed vertical leaf profiles (Vance and Nevai in J. Theor. Biol., 2007, to appear). We show that canopy partitioning is necessary for the stable coexistence of the two competing plant species. We also use implicit methods to show that, under certain conditions, the species' nullclines can intersect at most once. We use nullcline endpoint analysis to show that when the nullclines do intersect, and in such a way that they cross, then the resulting equilibrium point is always stable. We also construct surfaces that divide parameter space into regions within which the various outcomes of competition occur, and then study parameter dependence in the locations of these surfaces. The analysis presented here and in a companion paper (Nevai and Vance, The role of leaf height in plant competition for sunlight: analysis of a canopy partitioning model, in review) together shows that canopy partitioning is both necessary and, under appropriate parameter values, sufficient for the stable coexistence of two hypothetical plant species whose structure and growth are described by our model.

ExSurv: A Web Resource for Prognostic Analyses of Exons Across Human Cancers Using Clinical Transcriptomes

PubMed Central

Hashemikhabir, Seyedsasan; Budak, Gungor; Janga, Sarath Chandra

2016-01-01

Survival analysis in biomedical sciences is generally performed by correlating the levels of cellular components with patients’ clinical features as a common practice in prognostic biomarker discovery. While the common and primary focus of such analysis in cancer genomics so far has been to identify the potential prognostic genes, alternative splicing – a posttranscriptional regulatory mechanism that affects the functional form of a protein due to inclusion or exclusion of individual exons giving rise to alternative protein products, has increasingly gained attention due to the prevalence of splicing aberrations in cancer transcriptomes. Hence, uncovering the potential prognostic exons can not only help in rationally designing exon-specific therapeutics but also increase specificity toward more personalized treatment options. To address this gap and to provide a platform for rational identification of prognostic exons from cancer transcriptomes, we developed ExSurv (https://exsurv.soic.iupui.edu), a web-based platform for predicting the survival contribution of all annotated exons in the human genome using RNA sequencing-based expression profiles for cancer samples from four cancer types available from The Cancer Genome Atlas. ExSurv enables users to search for a gene of interest and shows survival probabilities for all the exons associated with a gene and found to be significant at the chosen threshold. ExSurv also includes raw expression values across the cancer cohort as well as the survival plots for prognostic exons. Our analysis of the resulting prognostic exons across four cancer types revealed that most of the survival-associated exons are unique to a cancer type with few processes such as cell adhesion, carboxylic, fatty acid metabolism, and regulation of T-cell signaling common across cancer types, possibly suggesting significant differences in the posttranscriptional regulatory pathways contributing to prognosis. PMID:27528797

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

PubMed

Cho, Gene Young; Moy, Linda; Kim, Sungheon G; Baete, Steven H; Moccaldi, Melanie; Babb, James S; Sodickson, Daniel K; Sigmund, Eric E

2016-08-01

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis. This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression. The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression. Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients. • Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

Research in interactive scene analysis

NASA Technical Reports Server (NTRS)

Tenenbaum, J. M.; Garvey, T. D.; Weyl, S. A.; Wolf, H. C.

1975-01-01

An interactive scene interpretation system (ISIS) was developed as a tool for constructing and experimenting with man-machine and automatic scene analysis methods tailored for particular image domains. A recently developed region analysis subsystem based on the paradigm of Brice and Fennema is described. Using this subsystem a series of experiments was conducted to determine good criteria for initially partitioning a scene into atomic regions and for merging these regions into a final partition of the scene along object boundaries. Semantic (problem-dependent) knowledge is essential for complete, correct partitions of complex real-world scenes. An interactive approach to semantic scene segmentation was developed and demonstrated on both landscape and indoor scenes. This approach provides a reasonable methodology for segmenting scenes that cannot be processed completely automatically, and is a promising basis for a future automatic system. A program is described that can automatically generate strategies for finding specific objects in a scene based on manually designated pictorial examples.

A CONCISE PANEL OF BIOMARKERS IDENTIFIES NEUROCOGNITIVE FUNCTIONING CHANGES IN HIV-INFECTED INDIVIDUALS

PubMed Central

Marcotte, Thomas D.; Deutsch, Reena; Michael, Benedict Daniel; Franklin, Donald; Cookson, Debra Rosario; Bharti, Ajay R.; Grant, Igor; Letendre, Scott L.

2013-01-01

Background Neurocognitive (NC) impairment (NCI) occurs commonly in people living with HIV. Despite substantial effort, no biomarkers have been sufficiently validated for diagnosis and prognosis of NCI in the clinic. The goal of this project was to identify diagnostic or prognostic biomarkers for NCI in a comprehensively characterized HIV cohort. Methods Multidisciplinary case review selected 98 HIV-infected individuals and categorized them into four NC groups using normative data: stably normal (SN), stably impaired (SI), worsening (Wo), or improving (Im). All subjects underwent comprehensive NC testing, phlebotomy, and lumbar puncture at two timepoints separated by a median of 6.2 months. Eight biomarkers were measured in CSF and blood by immunoassay. Results were analyzed using mixed model linear regression and staged recursive partitioning. Results At the first visit, subjects were mostly middle-aged (median 45) white (58%) men (84%) who had AIDS (70%). Of the 73% who took antiretroviral therapy (ART), 54% had HIV RNA levels below 50 c/mL in plasma. Mixed model linear regression identified that only MCP-1 in CSF was associated with neurocognitive change group. Recursive partitioning models aimed at diagnosis (i.e., correctly classifying neurocognitive status at the first visit) were complex and required most biomarkers to achieve misclassification limits. In contrast, prognostic models were more efficient. A combination of three biomarkers (sCD14, MCP-1, SDF-1α) correctly classified 82% of Wo and SN subjects, including 88% of SN subjects. A combination of two biomarkers (MCP-1, TNF-α) correctly classified 81% of Im and SI subjects, including 100% of SI subjects. Conclusions This analysis of well-characterized individuals identified concise panels of biomarkers associated with NC change. Across all analyses, the two most frequently identified biomarkers were sCD14 and MCP-1, indicators of monocyte/macrophage activation. While the panels differed depending on the outcome and on the degree of misclassification, nearly all stable patients were correctly classified. PMID:24101401

Glasgow prognostic score is superior to other inflammation-based scores in predicting survival of diffuse large B-cell lymphoma

PubMed Central

Wei, Xiaolei; Zhou, Lizhi; Wei, Qi; Zhang, Yuankun; Huang, Weimin; Feng, Ru

2017-01-01

Inflammation-based prognostic scores, such as the glasgow prognostic score (GPS), prognostic index (PI), prognostic nutritional index (PNI), neutrophil lymphocyte ratio (NLR) and platelet lymphocyte ratio (PLR) were related to survival in many solid tumors. Recent study showed that GPS can be used to predict outcome in diffuse large B-cell lymphoma (DLBCL). However, other inflammation related scores had not been reported and it also remained unknown which of them was the most useful to evaluate the survival in DLBCLs. In this retrospective study, a number of 252 newly diagnosed and histologically proven DLBCLs from January 2003 to December 2014 were included. The high GPS, high PI, high NLR, high PLR and low PNI were all associated with poor overall survival (p < 0.05) and event-free survival (p < 0.05) in univariate analysis. Multivariate analysis indicated that GPS (HR = 1.781, 95% CI = 1.065–2.979, p = 0.028) remained an independent prognostic predictor in DLBCL. The c-index of GPS (0.735, 95% CI = 0.645–0.824) was greater than that of PI (0.710, 95% CI = 0.621–0.799, p = 0.602), PNI (0.600, 95% CI = 0.517–0.683, p = 0.001), PLR (0.599, 95% CI = 0.510–0.689, p = 0.029) and NLR (0.572, 95% CI = 0.503–0.642, p = 0.005) by Harrell's concordance index. Especially in DLBCLs treated with R-CHOP, GPS still remained the most powerful prognostic score when comparing with others (p = 0.001 and p < 0.001, respectively for OS and EFS). In conclusion, it is indicated that inflammation-based prognostic scores such as GPS, PI, NLR, PNI and PLR all could be used to predict the outcome of DLBCLs. Among them, GPS is the most powerful indicator in predicting survival in DLBCLs, even in the rituximab era. PMID:29100345

Prognostic value of inflammation-based markers in patients with pancreatic cancer administered gemcitabine and erlotinib.

PubMed

Lee, Jae Min; Lee, Hong Sik; Hyun, Jong Jin; Choi, Hyuk Soon; Kim, Eun Sun; Keum, Bora; Seo, Yeon Seok; Jeen, Yoon Tae; Chun, Hoon Jai; Um, Soon Ho; Kim, Chang Duck

2016-07-15

To evaluate the value of systemic inflammation-based markers as prognostic factors for advanced pancreatic cancer (PC). Data from 82 patients who underwent combination chemotherapy with gemcitabine and erlotinib for PC from 2011 to 2014 were collected retrospectively. Data that included the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio, and the C-reactive protein (CRP)-to-albumin (CRP/Alb) ratio were analyzed. Kaplan-Meier curves, and univariate and multivariate Cox proportional hazards regression analyses were used to identify the prognostic factors associated with progression-free survival (PFS) and overall survival (OS). The univariate analysis demonstrated the prognostic value of the NLR (P = 0.049) and the CRP/Alb ratio (P = 0.047) in relation to PFS, and a positive relationship between an increase in inflammation-based markers and a poor prognosis in relation to OS. The multivariate analysis determined that an increased NLR (hazard ratio = 2.76, 95%CI: 1.33-5.75, P = 0.007) is an independent prognostic factor for poor OS. There was no association between the PLR and the patients' prognoses in those who had received chemotherapy that comprised gemcitabine and erlotinib in combination. The Kaplan-Meier method and the log-rank test determined significantly worse outcomes in relation to PFS and OS in patients with an NLR > 5 or a CRP/Alb ratio > 5. Systemic inflammation-based markers, including increases in the NLR and the CRP/Alb ratio, may be useful for predicting PC prognoses.

Analysis of red blood cell partitioning at bifurcations in simulated microvascular networks

NASA Astrophysics Data System (ADS)

Balogh, Peter; Bagchi, Prosenjit

2018-05-01

Partitioning of red blood cells (RBCs) at vascular bifurcations has been studied over many decades using in vivo, in vitro, and theoretical models. These studies have shown that RBCs usually do not distribute to the daughter vessels with the same proportion as the blood flow. Such disproportionality occurs, whereby the cell distribution fractions are either higher or lower than the flow fractions and have been referred to as classical partitioning and reverse partitioning, respectively. The current work presents a study of RBC partitioning based on, for the first time, a direct numerical simulation (DNS) of a flowing cell suspension through modeled vascular networks that are comprised of multiple bifurcations and have topological similarity to microvasculature in vivo. The flow of deformable RBCs at physiological hematocrits is considered through the networks, and the 3D dynamics of each individual cell are accurately resolved. The focus is on the detailed analysis of the partitioning, based on the DNS data, as it develops naturally in successive bifurcations, and the underlying mechanisms. We find that while the time-averaged partitioning at a bifurcation manifests in one of two ways, namely, the classical or reverse partitioning, the time-dependent behavior can cycle between these two types. We identify and analyze four different cellular-scale mechanisms underlying the time-dependent partitioning. These mechanisms arise, in general, either due to an asymmetry in the RBC distribution in the feeding vessels caused by the events at an upstream bifurcation or due to a temporary increase in cell concentration near capillary bifurcations. Using the DNS results, we show that a positive skewness in the hematocrit profile in the feeding vessel is associated with the classical partitioning, while a negative skewness is associated with the reverse one. We then present a detailed analysis of the two components of disproportionate partitioning as identified in prior studies, namely, plasma skimming and cell screening. The plasma skimming component is shown to under-predict the disproportionality, leaving the cell screening component to make up for the difference. The crossing of the separation surface by the cells is observed to be a dominant mechanism underlying the cell screening, which is shown to mitigate extreme heterogeneity in RBC distribution across the networks.

Models for liquid-liquid partition in the system dimethyl sulfoxide-organic solvent and their use for estimating descriptors for organic compounds.

PubMed

Karunasekara, Thushara; Poole, Colin F

2011-07-15

Partition coefficients for varied compounds were determined for the organic solvent-dimethyl sulfoxide biphasic partition system where the organic solvent is n-heptane or isopentyl ether. These partition coefficient databases are analyzed using the solvation parameter model facilitating a quantitative comparison of the dimethyl sulfoxide-based partition systems with other totally organic partition systems. Dimethyl sulfoxide is a moderately cohesive solvent, reasonably dipolar/polarizable and strongly hydrogen-bond basic. Although generally considered to be non-hydrogen-bond acidic, analysis of the partition coefficient database strongly supports reclassification as a weak hydrogen-bond acid in agreement with recent literature. The system constants for the n-heptane-dimethyl sulfoxide biphasic system provide an explanation of the mechanism for the selective isolation of polycyclic aromatic compounds from mixtures containing low-polarity hydrocarbons based on the capability of the polar interactions (dipolarity/polarizability and hydrogen-bonding) to overcome the opposing cohesive forces in dimethyl sulfoxide that are absent for the interactions with hydrocarbons of low polarity. In addition, dimethyl sulfoxide-organic solvent systems afford a complementary approach to other totally organic biphasic partition systems for descriptor measurements of compounds virtually insoluble in water. Copyright © 2011 Elsevier B.V. All rights reserved.

Prognostic Impact of the 6th and 7th American Joint Committee on Cancer TNM Staging Systems on Esophageal Cancer Patients Treated With Chemoradiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nomura, Motoo, E-mail: excell@hkg.odn.ne.jp; Department of Radiation Oncology, Aichi Cancer Center Hospital; Shitara, Kohei

2012-02-01

Purpose: The new 7th edition of the American Joint Committee on Cancer TNM staging system is based on pathologic data from esophageal cancers treated by surgery alone. There is no information available on evaluation of the new staging system with regard to prognosis of patients treated with chemoradiotherapy (CRT). The objective of this study was to evaluate the prognostic impact of the new staging system on esophageal cancer patients treated with CRT. Methods and Materials: A retrospective review was performed on 301 consecutive esophageal squamous cell carcinoma patients treated with CRT. Comparisons were made of the prognostic impacts of themore » 6th and 7th staging systems and the prognostic impacts of stage and prognostic groups, which were newly defined in the 7th edition. Results: There were significant differences between Stages I and III (p < 0.01) according to both editions. However, the 7th edition poorly distinguishes the prognoses of Stages III and IV (p = 0.36 by multivariate analysis) in comparison to the 6th edition (p = 0.08 by multivariate analysis), although these differences were not significant. For all patients, T, M, and gender were independent prognostic factors by multivariate analysis (p < 0.05). For the Stage I and II prognostic groups, survival curves showed a stepwise decrease with increase in stage, except for Stage IIA. However, there were no significant differences seen between each prognostic stage. Conclusions: Our study indicates there are several problems with the 7th TNM staging system regarding prognostic factors in patients undergoing CRT.« less

Multilevel Green's function interpolation method for scattering from composite metallic and dielectric objects.

PubMed

Shi, Yan; Wang, Hao Gang; Li, Long; Chan, Chi Hou

2008-10-01

A multilevel Green's function interpolation method based on two kinds of multilevel partitioning schemes--the quasi-2D and the hybrid partitioning scheme--is proposed for analyzing electromagnetic scattering from objects comprising both conducting and dielectric parts. The problem is formulated using the surface integral equation for homogeneous dielectric and conducting bodies. A quasi-2D multilevel partitioning scheme is devised to improve the efficiency of the Green's function interpolation. In contrast to previous multilevel partitioning schemes, noncubic groups are introduced to discretize the whole EM structure in this quasi-2D multilevel partitioning scheme. Based on the detailed analysis of the dimension of the group in this partitioning scheme, a hybrid quasi-2D/3D multilevel partitioning scheme is proposed to effectively handle objects with fine local structures. Selection criteria for some key parameters relating to the interpolation technique are given. The proposed algorithm is ideal for the solution of problems involving objects such as missiles, microstrip antenna arrays, photonic bandgap structures, etc. Numerical examples are presented to show that CPU time is between O(N) and O(N log N) while the computer memory requirement is O(N).

Anatomical location differences between mutated and wild-type isocitrate dehydrogenase 1 in low-grade gliomas.

PubMed

Yu, Jinhua; Shi, Zhifeng; Ji, Chunhong; Lian, Yuxi; Wang, Yuanyuan; Chen, Liang; Mao, Ying

2017-10-01

Anatomical location of gliomas has been considered as a factor implicating the contributions of a specific precursor cells during the tumor growth. Isocitrate dehydrogenase 1 (IDH1) is a pathognomonic biomarker with a significant impact on the development of gliomas and remarkable prognostic effect. The correlation between anatomical location of tumor and IDH1 states for low-grade gliomas was analyzed quantitatively in this study. Ninety-two patients diagnosed of low-grade glioma pathologically were recruited in this study, including 65 patients with IDH1-mutated glioma and 27 patients with wide-type IDH1. A convolutional neural network was designed to segment the tumor from three-dimensional magnetic resonance imaging images. Voxel-based lesion symptom mapping was then employed to study the tumor location distribution differences between gliomas with mutated and wild-type IDH1. In order to characterize the location differences quantitatively, the Automated Anatomical Labeling Atlas was used to partition the standard brain atlas into 116 anatomical volumes of interests (AVOIs). The percentages of tumors with different IDH1 states in 116 AVOIs were calculated and compared. Support vector machine and AdaBoost algorithms were used to estimate the IDH1 status based on the 116 location features of each patient. Experimental results proved that the quantitative tumor location measurement could be a very important group of imaging features in biomarker estimation based on radiomics analysis of glioma.

Disparities in pediatric leukemia early survival in Argentina: a population-based study.

PubMed

Garibotti, Gilda; Moreno, Florencia; Dussel, Veronica; Orellana, Liliana

2014-10-01

To identify disparities-using recursive partitioning (RP)-in early survival for children with leukemias treated in Argentina, and to depict the main characteristics of the most vulnerable groups. This secondary data analysis evaluated 12-month survival (12-ms) in 3 987 children diagnosed between 2000 and 2008 with lymphoid leukemia (LL) and myeloid leukemia (ML) and registered in Argentina's population-based oncopediatric registry. Prognostic groups based on age at diagnosis, gender, socioeconomic index of the province of residence, and migration to a different province to receive health care were identified using the RP method. Overall 12-ms for LL and ML cases was 83.7% and 59.9% respectively. RP detected major gaps in 12-ms. Among 1-10-year-old LL patients from poorer provinces, 12-ms for those who did and did not migrate was 87.0% and 78.2% respectively. Survival of ML patients < 2 years old from provinces with a low/medium socioeconomic index was 38.9% compared to 62.1% for those in the same age group from richer provinces. For 2-14-year-old ML patients living in poor provinces, patient migration was associated with a 30% increase in 12-ms. Major disparities in leukemia survival among Argentine children were found. Patient migration and socioeconomic index of residence province were associated with survival. The RP method was instrumental in identifying and characterizing vulnerable groups.

CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas.

PubMed

Ganeshan, B; Miles, K A; Babikir, S; Shortman, R; Afaq, A; Ardeshna, K M; Groves, A M; Kayani, I

2017-03-01

The purpose of this study was to investigate the ability of computed tomography texture analysis (CTTA) to provide additional prognostic information in patients with Hodgkin's lymphoma (HL) and high-grade non-Hodgkin's lymphoma (NHL). This retrospective, pilot-study approved by the IRB comprised 45 lymphoma patients undergoing routine 18F-FDG-PET-CT. Progression-free survival (PFS) was determined from clinical follow-up (mean-duration: 40 months; range: 10-62 months). Non-contrast-enhanced low-dose CT images were submitted to CTTA comprising image filtration to highlight features of different sizes followed by histogram-analysis using kurtosis. Prognostic value of CTTA was compared to PET FDG-uptake value, tumour-stage, tumour-bulk, lymphoma-type, treatment-regime, and interim FDG-PET (iPET) status using Kaplan-Meier analysis. Cox regression analysis determined the independence of significantly prognostic imaging and clinical features. A total of 27 patients had aggressive NHL and 18 had HL. Mean PFS was 48.5 months. There was no significant difference in pre-treatment CTTA between the lymphoma sub-types. Kaplan-Meier analysis found pre-treatment CTTA (medium feature scale, p=0.010) and iPET status (p<0.001) to be significant predictors of PFS. Cox analysis revealed that an interaction between pre-treatment CTTA and iPET status was the only independent predictor of PFS (HR: 25.5, 95% CI: 5.4-120, p<0.001). Specifically, pre-treatment CTTA risk stratified patients with negative iPET. CTTA can potentially provide prognostic information complementary to iPET for patients with HL and aggressive NHL. • CT texture-analysis (CTTA) provides prognostic information complementary to interim FDG-PET in Lymphoma. • Pre-treatment CTTA and interim PET status were significant predictors of progression-free survival. • Patients with negative interim PET could be further stratified by pre-treatment CTTA. • Provide precision surveillance where additional imaging reserved for patients at greatest recurrence-risk. • Assists in risk-adapted treatment strategy based on interim PET and CTTA.

Predicting axillary lymph node metastasis from kinetic statistics of DCE-MRI breast images

NASA Astrophysics Data System (ADS)

Ashraf, Ahmed B.; Lin, Lilie; Gavenonis, Sara C.; Mies, Carolyn; Xanthopoulos, Eric; Kontos, Despina

2012-03-01

The presence of axillary lymph node metastases is the most important prognostic factor in breast cancer and can influence the selection of adjuvant therapy, both chemotherapy and radiotherapy. In this work we present a set of kinetic statistics derived from DCE-MRI for predicting axillary node status. Breast DCE-MRI images from 69 women with known nodal status were analyzed retrospectively under HIPAA and IRB approval. Axillary lymph nodes were positive in 12 patients while 57 patients had no axillary lymph node involvement. Kinetic curves for each pixel were computed and a pixel-wise map of time-to-peak (TTP) was obtained. Pixels were first partitioned according to the similarity of their kinetic behavior, based on TTP values. For every kinetic curve, the following pixel-wise features were computed: peak enhancement (PE), wash-in-slope (WIS), wash-out-slope (WOS). Partition-wise statistics for every feature map were calculated, resulting in a total of 21 kinetic statistic features. ANOVA analysis was done to select features that differ significantly between node positive and node negative women. Using the computed kinetic statistic features a leave-one-out SVM classifier was learned that performs with AUC=0.77 under the ROC curve, outperforming the conventional kinetic measures, including maximum peak enhancement (MPE) and signal enhancement ratio (SER), (AUCs of 0.61 and 0.57 respectively). These findings suggest that our DCE-MRI kinetic statistic features can be used to improve the prediction of axillary node status in breast cancer patients. Such features could ultimately be used as imaging biomarkers to guide personalized treatment choices for women diagnosed with breast cancer.

A survival tree method for the analysis of discrete event times in clinical and epidemiological studies.

PubMed

Schmid, Matthias; Küchenhoff, Helmut; Hoerauf, Achim; Tutz, Gerhard

2016-02-28

Survival trees are a popular alternative to parametric survival modeling when there are interactions between the predictor variables or when the aim is to stratify patients into prognostic subgroups. A limitation of classical survival tree methodology is that most algorithms for tree construction are designed for continuous outcome variables. Hence, classical methods might not be appropriate if failure time data are measured on a discrete time scale (as is often the case in longitudinal studies where data are collected, e.g., quarterly or yearly). To address this issue, we develop a method for discrete survival tree construction. The proposed technique is based on the result that the likelihood of a discrete survival model is equivalent to the likelihood of a regression model for binary outcome data. Hence, we modify tree construction methods for binary outcomes such that they result in optimized partitions for the estimation of discrete hazard functions. By applying the proposed method to data from a randomized trial in patients with filarial lymphedema, we demonstrate how discrete survival trees can be used to identify clinically relevant patient groups with similar survival behavior. Copyright © 2015 John Wiley & Sons, Ltd.

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

NASA Astrophysics Data System (ADS)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

Prognostic factors in patients with spinal metastasis: a systematic review and meta-analysis.

PubMed

Luksanapruksa, Panya; Buchowski, Jacob M; Hotchkiss, William; Tongsai, Sasima; Wilartratsami, Sirichai; Chotivichit, Areesak

2017-05-01

Incidence of symptomatic spinal metastasis has increased owing to improvement in treatment of the disease. One of the key factors that influences decision-making is expected patient survival. To our knowledge, no systematic reviews or meta-analysis have been conducted that review independent prognostic factors in spinal metastases. This study aimed to determine independent prognostic factors that affect outcome in patients with metastatic spine disease. This is a systematic literature review and meta-analysis of publications for prognostic factors in spinal metastatic disease. Pooled patient results from cohort and observational studies. Meta-analysis for poor prognostic factors as determined by hazard ratio (HR) and 95% confidential interval (95% CI). We systematically searched relevant publications in PubMed and Embase. The following search terms were used: ("'spinal metastases'" OR "'vertebral metastases'" OR "spinal metastasis" OR 'vertebral metastases') AND ('"prognostic factors"' OR "'survival'"). Inclusion criteria were prospective and retrospective cohort series that report HR and 95% CI of independent prognostic factors from multivariate analysis. Two reviewers independently assessed all papers. The quality of included papers was assessed by using Newcastle-Ottawa Scale for cohort studies and publication bias was assessed by using funnel plot, Begg test, and Egger test. The prognostic factors that were mentioned in at least three publications were pooled. Meta-analysis was performed using HR and 95% CI as the primary outcomes of interest. Heterogeneity was assessed using the I 2 method. A total of 3,959 abstracts (1,382 from PubMed and 2,577 from Embase) were identified through database search and 40 publications were identified through review of cited publications. The reviewers selected a total of 51 studies for qualitative synthesis and 43 studies for meta-analysis. Seventeen poor prognostic factors were identified. These included presence of a neurologic deficit before surgery, non-ambulatory status before radiotherapy (RT), non-ambulatory status before surgery, presence of bone metastases, presence of multiple bone metastases (>2 sites), presence of multiple spinal metastases (>3 sites), development of motor deficit in <7 days before initiating RT, development of motor deficit in <14 days before initiating RT, time interval from cancer diagnosis to RT <15 months, Karnofsky Performance Score (KPS) 10-40, KPS 50-70, KPS<70, Eastern Cooperative Oncology Group (ECOG) grade 3-4, male gender, presence of visceral metastases, moderate growth tumor on Tomita score (TS) classification, and rapid growth tumor on TS classification. Seventeen independent poor prognostic factors were identified in this study. These can be categorized into cancer-specific and nonspecific prognostic factors. A tumor-based prognostic scoring system that combines all specific and general factors may enhance the accuracy of survival prediction in patients with metastatic spine disease. Copyright © 2016 Elsevier Inc. All rights reserved.

[Application of standardized systems for assessment of prognosis of the traumatic process in patients with penetrating abdominal wounds and hepatic injuries].

PubMed

Hur'iev, S O; Novykov, F M; Shuryhin, O Iu; Ivanov, V I

2011-04-01

There were examined 131 injured persons, suffering penetrating abdominal wounding and hepatic injury. Correlation analysis was done, basing on studying of the results of the injured persons state estimation, using prognostic scales, aiming to prognosticate the traumatic process course.

Utility of Inflammatory Marker- and Nutritional Status-based Prognostic Factors for Predicting the Prognosis of Stage IV Gastric Cancer Patients Undergoing Non-curative Surgery.

PubMed

Mimatsu, Kenji; Fukino, Nobutada; Ogasawara, Yasuo; Saino, Yoko; Oida, Takatsugu

2017-08-01

The present study aimed to compare the utility of various inflammatory marker- and nutritional status-based prognostic factors, including many previous established prognostic factors, for predicting the prognosis of stage IV gastric cancer patients undergoing non-curative surgery. A total of 33 patients with stage IV gastric cancer who had undergone palliative gastrectomy and gastrojejunostomy were included in the study. Univariate and multivariate analyses were performed to evaluate the relationships between the mGPS, PNI, NLR, PLR, the CONUT, various clinicopathological factors and cancer-specific survival (CS). Among patients who received non-curative surgery, univariate analysis of CS identified the following significant risk factors: chemotherapy, mGPS and NLR, and multivariate analysis revealed that the mGPS was independently associated with CS. The mGPS was a more useful prognostic factor than the PNI, NLR, PLR and CONUT in patients undergoing non-curative surgery for stage IV gastric cancer. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

PubMed

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Cluster formation and drag reduction-proposed mechanism of particle recirculation within the partition column of the bottom spray fluid-bed coater.

PubMed

Wang, Li Kun; Heng, Paul Wan Sia; Liew, Celine Valeria

2015-04-01

Bottom spray fluid-bed coating is a common technique for coating multiparticulates. Under the quality-by-design framework, particle recirculation within the partition column is one of the main variability sources affecting particle coating and coat uniformity. However, the occurrence and mechanism of particle recirculation within the partition column of the coater are not well understood. The purpose of this study was to visualize and define particle recirculation within the partition column. Based on different combinations of partition gap setting, air accelerator insert diameter, and particle size fraction, particle movements within the partition column were captured using a high-speed video camera. The particle recirculation probability and voidage information were mapped using a visiometric process analyzer. High-speed images showed that particles contributing to the recirculation phenomenon were behaving as clustered colonies. Fluid dynamics analysis indicated that particle recirculation within the partition column may be attributed to the combined effect of cluster formation and drag reduction. Both visiometric process analysis and particle coating experiments showed that smaller particles had greater propensity toward cluster formation than larger particles. The influence of cluster formation on coating performance and possible solutions to cluster formation were further discussed. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Prognostic significance of interventricular septal thickness in patients with AL amyloidosis.

PubMed

Cho, Hyunsoo; Kim, Soo-Jeong; Shim, Chi Young; Hong, Geu-Ru; Ha, Jong-Won; Kim, Yu Ri; Yang, Woo Ick; Chung, Haerim; Jang, Ji Eun; Cheong, June-Won; Min, Yoo Hong; Kim, Jin Seok

2017-09-01

The major prognostic determinant of immunoglobulin light chain (AL) amyloidosis is cardiac involvement. However, the role of interventricular septal thickness (IVST), which reflects the extent of cardiac involvement, remains unclear. Therefore, we analyzed 77 patients with newly diagnosed AL amyloidosis and evaluated the prognostic role of IVST. Fifty patients (64.9%) had cardiac involvement and 17 patients (22.1%) showed IVST >15mm. Among all patients, the revised Mayo Clinic Stage III-IV and IVST >15mm were independently associated with inferior overall survival (OS) in a multivariable analysis. IVST >15mm was also adversely prognostic for OS in a subgroup of advanced-stage (revised Mayo Clinic stage III-IV) patients in a multivariable analysis (P<0.001). Furthermore, advanced-stage patients with IVST >15mm did not show survival benefit from treatment with bortezomib-based regimens and/or autologous stem-cell transplantation (ASCT). Our study demonstrated that IVST >15mm is adversely prognostic independent of the revised Mayo Clinic staging system in patients with AL amyloidosis. In addition, the degree of IVST might be used as a useful prognostic indicator that can guide the management of patients with AL amyloidosis especially at an advanced stage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prognostic model based on nailfold capillaroscopy for identifying Raynaud's phenomenon patients at high risk for the development of a scleroderma spectrum disorder: PRINCE (prognostic index for nailfold capillaroscopic examination).

PubMed

Ingegnoli, Francesca; Boracchi, Patrizia; Gualtierotti, Roberta; Lubatti, Chiara; Meani, Laura; Zahalkova, Lenka; Zeni, Silvana; Fantini, Flavio

2008-07-01

To construct a prognostic index based on nailfold capillaroscopic examinations that is capable of predicting the 5-year transition from isolated Raynaud's phenomenon (RP) to RP secondary to scleroderma spectrum disorders (SSDs). The study involved 104 consecutive adult patients with a clinical history of isolated RP, and the index was externally validated in another cohort of 100 patients with the same characteristics. Both groups were followed up for 1-8 years. Six variables were examined because of their potential prognostic relevance (branching, enlarged and giant loops, capillary disorganization, microhemorrhages, and the number of capillaries). The only factors that played a significant prognostic role were the presence of giant loops (hazard ratio [HR] 2.64, P = 0.008) and microhemorrhages (HR 2.33, P = 0.01), and the number of capillaries (analyzed as a continuous variable). The adjusted prognostic role of these factors was evaluated by means of multivariate regression analysis, and the results were used to construct an algorithm-based prognostic index. The model was internally and externally validated. Our prognostic capillaroscopic index identifies RP patients in whom the risk of developing SSDs is high. This model is a weighted combination of different capillaroscopy parameters that allows physicians to stratify RP patients easily, using a relatively simple diagram to deduce the prognosis. Our results suggest that this index could be used in clinical practice, and its further inclusion in prospective studies will undoubtedly help in exploring its potential in predicting treatment response.

Cluster analysis and prediction of treatment outcomes for chronic rhinosinusitis.

PubMed

Soler, Zachary M; Hyer, J Madison; Rudmik, Luke; Ramakrishnan, Viswanathan; Smith, Timothy L; Schlosser, Rodney J

2016-04-01

Current clinical classifications of chronic rhinosinusitis (CRS) have weak prognostic utility regarding treatment outcomes. Simplified discriminant analysis based on unsupervised clustering has identified novel phenotypic subgroups of CRS, but prognostic utility is unknown. We sought to determine whether discriminant analysis allows prognostication in patients choosing surgery versus continued medical management. A multi-institutional prospective study of patients with CRS in whom initial medical therapy failed who then self-selected continued medical management or surgical treatment was used to separate patients into 5 clusters based on a previously described discriminant analysis using total Sino-Nasal Outcome Test-22 (SNOT-22) score, age, and missed productivity. Patients completed the SNOT-22 at baseline and for 18 months of follow-up. Baseline demographic and objective measures included olfactory testing, computed tomography, and endoscopy scoring. SNOT-22 outcomes for surgical versus continued medical treatment were compared across clusters. Data were available on 690 patients. Baseline differences in demographics, comorbidities, objective disease measures, and patient-reported outcomes were similar to previous clustering reports. Three of 5 clusters identified by means of discriminant analysis had improved SNOT-22 outcomes with surgical intervention when compared with continued medical management (surgery was a mean of 21.2 points better across these 3 clusters at 6 months, P < .05). These differences were sustained at 18 months of follow-up. Two of 5 clusters had similar outcomes when comparing surgery with continued medical management. A simplified discriminant analysis based on 3 common clinical variables is able to cluster patients and provide prognostic information regarding surgical treatment versus continued medical management in patients with CRS. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Stage Separation Failure: Model Based Diagnostics and Prognostics

NASA Technical Reports Server (NTRS)

Luchinsky, Dmitry; Hafiychuk, Vasyl; Kulikov, Igor; Smelyanskiy, Vadim; Patterson-Hine, Ann; Hanson, John; Hill, Ashley

2010-01-01

Safety of the next-generation space flight vehicles requires development of an in-flight Failure Detection and Prognostic (FD&P) system. Development of such system is challenging task that involves analysis of many hard hitting engineering problems across the board. In this paper we report progress in the development of FD&P for the re-contact fault between upper stage nozzle and the inter-stage caused by the first stage and upper stage separation failure. A high-fidelity models and analytical estimations are applied to analyze the following sequence of events: (i) structural dynamics of the nozzle extension during the impact; (ii) structural stability of the deformed nozzle in the presence of the pressure and temperature loads induced by the hot gas flow during engine start up; and (iii) the fault induced thrust changes in the steady burning regime. The diagnostic is based on the measurements of the impact torque. The prognostic is based on the analysis of the correlation between the actuator signal and fault-induced changes in the nozzle structural stability and thrust.

Evaluation of an inflammation-based prognostic score in patients with metastatic renal cancer.

PubMed

Ramsey, Sara; Lamb, Gavin W A; Aitchison, Michael; Graham, John; McMillan, Donald C

2007-01-15

Recently, it was shown that an inflammation-based prognostic score, the Glasgow Prognostic Score (GPS), provides additional prognostic information in patients with advanced cancer. The objective of the current study was to examine the value of the GPS compared with established scoring systems in predicting cancer-specific survival in patients with metastatic renal cancer. One hundred nineteen patients who underwent immunotherapy for metastatic renal cancer were recruited. The Memorial Sloan-Kettering Cancer Center (MSKCC) score and the Metastatic Renal Carcinoma Comprehensive Prognostic System (MRCCPS) score were calculated as described previously. Patients who had both an elevated C-reactive protein level (>10 mg/L) and hypoalbuminemia (<35 g/L) were allocated a GPS of 2. Patients who had only 1 of those 2 biochemical abnormalities were allocated a GPS of 1. Patients who had neither abnormality were allocated a GPS of 0. On multivariate analysis of significant individual factors, only calcium (hazard ratio [HR], 3.21; 95% confidence interval [95% CI], 1.51-6.83; P = .002), white cell count (HR, 1.66; 95% CI, 1.17-2.35; P = .004), albumin (HR, 2.63; 95% CI, 1.38-5.03; P = .003), and C-reactive protein (HR, 2.85; 95% CI; 1.49-5.45; P = .002) were associated independently with cancer-specific survival. On multivariate analysis of the different scoring systems, the MSKCC (HR, 1.88; 95% CI, 1.22-2.88; P = .004), the MRCCPS (HR, 1.42; 95% CI, 0.97-2.09; P = .071), and the GPS (HR, 2.35; 95% CI, 1.51-3.67; P < .001) were associated independently with cancer-specific survival. An inflammation-based prognostic score (GPS) predicted survival independent of established scoring systems in patients with metastatic renal cancer.

Prognostic indices for early mortality in ischaemic stroke - meta-analysis.

PubMed

Mattishent, K; Kwok, C S; Mahtani, A; Pelpola, K; Myint, P K; Loke, Y K

2016-01-01

Several models have been developed to predict mortality in ischaemic stroke. We aimed to evaluate systematically the performance of published stroke prognostic scores. We searched MEDLINE and EMBASE in February 2014 for prognostic models (published between 2003 and 2014) used in predicting early mortality (<6 months) after ischaemic stroke. We evaluated discriminant ability of the tools through meta-analysis of the area under the curve receiver operating characteristic curve (AUROC) or c-statistic. We evaluated the following components of study validity: collection of prognostic variables, neuroimaging, treatment pathways and missing data. We identified 18 articles (involving 163 240 patients) reporting on the performance of prognostic models for mortality in ischaemic stroke, with 15 articles providing AUC for meta-analysis. Most studies were either retrospective, or post hoc analyses of prospectively collected data; all but three reported validation data. The iSCORE had the largest number of validation cohorts (five) within our systematic review and showed good performance in four different countries, pooled AUC 0.84 (95% CI 0.82-0.87). We identified other potentially useful prognostic tools that have yet to be as extensively validated as iSCORE - these include SOAR (2 studies, pooled AUC 0.79, 95% CI 0.78-0.80), GWTG (2 studies, pooled AUC 0.72, 95% CI 0.72-0.72) and PLAN (1 study, pooled AUC 0.85, 95% CI 0.84-0.87). Our meta-analysis has identified and summarized the performance of several prognostic scores with modest to good predictive accuracy for early mortality in ischaemic stroke, with the iSCORE having the broadest evidence base. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Postoperative staging of the neck dissection using extracapsular spread and lymph node ratio as prognostic factors in HPV-negative head and neck squamous cell carcinoma patients.

PubMed

Majercakova, Katarina; Valero, Cristina; López, Montserrat; García, Jacinto; Farré, Nuria; Quer, Miquel; León, Xavier

2018-02-01

The presence of nodes with extracapsular spread (ECS) and the lymph node ratio (LNR) have prognostic competence in the pathologic evaluation of patients with a head and neck squamous cell carcinoma (HNSCC) treated with a neck dissection. The purpose of this study is to assess the effect of ECS & LNR on prognosis of HPV negative HNSCC patients treated with neck dissection and to compare to 8th edition TNM/AJCC classification. We carried out a retrospective study of 1383 patients with HNSCC treated with a neck dissection between 1985 and 2013. We developed a classification of the patients according to the presence of nodes with ECS and the LNR value with a recursive partitioning analysis (RPA) model. We obtained a classification tree with four terminal nodes: for patients without ECS (including patients pN0) the cut-off point for LNR was 1.6%, while for patients with lymph nodes with ECS it was 11.4%. The 5-year disease-specific survival for patients without ECS/LNR < 1.6% was 83.3%; for patients without ECS/LNR ≥ 1.6% it was 61.5%; for patients with ECS/LNR < 11.4% it was 33.7%; and for patients with ECS/LNR ≥ 11.4% it was 18.5%. The classification obtained with RPA had better discrimination between categories than the 8th edition of the TNM/AJCC classification. ECS status and LNR value proved high prognostic capacity in the pathological evaluation of the neck dissection. The combination of ECS and LNR improved the predictive capacity of the 8th edition of the TNM/AJCC classification in HPV-negative HNSCC patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Physicochemical properties/descriptors governing the solubility and partitioning of chemicals in water-solvent-gas systems. Part 1. Partitioning between octanol and air.

PubMed

Raevsky, O A; Grigor'ev, V J; Raevskaja, O E; Schaper, K-J

2006-06-01

QSPR analyses of a data set containing experimental partition coefficients in the three systems octanol-water, water-gas, and octanol-gas for 98 chemicals have shown that it is possible to calculate any partition coefficient in the system 'gas phase/octanol/water' by three different approaches: (1) from experimental partition coefficients obtained in the corresponding two other subsystems. However, in many cases these data may not be available. Therefore, a solution may be approached (2), a traditional QSPR analysis based on e.g. HYBOT descriptors (hydrogen bond acceptor and donor factors, SigmaCa and SigmaCd, together with polarisability alpha, a steric bulk effect descriptor) and supplemented with substructural indicator variables. (3) A very promising approach which is a combination of the similarity concept and QSPR based on HYBOT descriptors. In this approach observed partition coefficients of structurally nearest neighbours of a compound-of-interest are used. In addition, contributions arising from differences in alpha, SigmaCa, and SigmaCd values between the compound-of-interest and its nearest neighbour(s), respectively, are considered. In this investigation highly significant relationships were obtained by approaches (1) and (3) for the octanol/gas phase partition coefficient (log Log).

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

PubMed

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Software framework for prognostic health monitoring of ocean-based power generation

NASA Astrophysics Data System (ADS)

Bowren, Mark

On August 5, 2010 the U.S. Department of Energy (DOE) has designated the Center for Ocean Energy Technology (COET) at Florida Atlantic University (FAU) as a national center for ocean energy research and development of prototypes for open-ocean power generation. Maintenance on ocean-based machinery can be very costly. To avoid unnecessary maintenance it is necessary to monitor the condition of each machine in order to predict problems. This kind of prognostic health monitoring (PHM) requires a condition-based maintenance (CBM) system that supports diagnostic and prognostic analysis of large amounts of data. Research in this field led to the creation of ISO13374 and the development of a standard open-architecture for machine condition monitoring. This thesis explores an implementation of such a system for ocean-based machinery using this framework and current open-standard technologies.

Practical prognostic index for patients with metastatic recurrent breast cancer: retrospective analysis of 2,322 patients from the GEICAM Spanish El Alamo Register.

PubMed

Puente, Javier; López-Tarruella, Sara; Ruiz, Amparo; Lluch, Ana; Pastor, Miguel; Alba, Emilio; de la Haba, Juan; Ramos, Manuel; Cirera, Luis; Antón, Antonio; Llombart, Antoni; Plazaola, Arrate; Fernández-Aramburo, Antonio; Sastre, Javier; Díaz-Rubio, Eduardo; Martin, Miguel

2010-07-01

Women with recurrent metastatic breast cancer from a Spanish hospital registry (El Alamo, GEICAM) were analyzed in order to identify the most helpful prognostic factors to predict survival and to ultimately construct a practical prognostic index. The inclusion criteria covered women patients diagnosed with operable invasive breast cancer who had metastatic recurrence between 1990 and 1997 in GEICAM hospitals. Patients with stage IV breast cancer at initial diagnosis or with isolated loco-regional recurrence were excluded from this analysis. Data from 2,322 patients with recurrent breast cancer after primary treatment (surgery, radiation and systemic adjuvant treatment) were used to construct the prognostic index. The prognostic index score for each individual patient was calculated by totalling up the scores of each independent variable. The maximum score obtainable was 26.1. Nine-hundred and sixty-two patients who had complete data for all the variables were used in the computation of the prognostic index score. We were able to stratify them into three prognostic groups based on the prognostic index score: 322 patients in the good risk group (score < or =13.5), 308 patients in the intermediate risk group (score 13.51-15.60) and 332 patients in the poor risk group (score > or =15.61). The median survivals for these groups were 3.69, 2.27 and 1.02 years, respectively (P < 0.0001). In conclusion, risk scores are extraordinarily valuable tools, highly recommendable in the clinical practice.

An Aircraft Lifecycle Approach for the Cost-Benefit Analysis of Prognostics and Condition-Based Maintenance-Based on Discrete-Event Simulation

DTIC Science & Technology

2014-10-02

MPD. This manufacturer documentation contains maintenance tasks with specification of intervals and required man-hours that are to be carried out...failures, without consideration of false alarms and missed failures (see also section 4.1.3). The task redundancy rate is the percentage of preventive...Prognostics and Health Management ROI return on investment RUL remaining useful life TCG task code group SB Service Bulletin XML Extensible Markup

Electromechanical actuators affected by multiple failures: Prognostic method based on spectral analysis techniques

NASA Astrophysics Data System (ADS)

Belmonte, D.; Vedova, M. D. L. Dalla; Ferro, C.; Maggiore, P.

2017-06-01

The proposal of prognostic algorithms able to identify precursors of incipient failures of primary flight command electromechanical actuators (EMA) is beneficial for the anticipation of the incoming failure: an early and correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. An innovative prognostic model-based approach, able to recognize the EMA progressive degradations before his anomalous behaviors become critical, is proposed: the Fault Detection and Identification (FDI) of the considered incipient failures is performed analyzing proper system operational parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. Subsequently, these operational parameters will be correlated with the actual EMA health condition by means of failure maps created by a reference monitoring model-based algorithm. In this work, the proposed method has been tested in case of EMA affected by combined progressive failures: in particular, partial stator single phase turn to turn short-circuit and rotor static eccentricity are considered. In order to evaluate the prognostic method, a numerical test-bench has been conceived. Results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify an eventual malfunctioning, minimizing the risk of fake alarms or unannounced failures.

The Prognostic Value of the 8th Edition of the American Joint Committee on Cancer (AJCC) Staging System in HER2-Enriched Subtype Breast Cancer, a Retrospective Analysis.

PubMed

Zhou, Bin; Xu, Ling; Ye, Jingming; Xin, Ling; Duan, Xuening; Liu, Yinhua

2017-08-01

The American Joint Committee on Cancer (AJCC) released its 8th edition of tumor staging which is to be implemented in early 2018. The present study aimed to analyze the prognostic value of AJCC 8th edition Cancer Staging System in HER2-enriched breast cancer, on a retrospective cohort. This study was a retrospective single-center study of HER2-enriched breast cancer cases diagnosed from January 2008 to December 2014. Clinicopathological features and follow up data including disease-free survival (DFS) and overall survival (OS) were analyzed to explore prognostic factors for disease outcome. We restaged patients based on the 8th edition of the AJCC cancer staging system and analyzed prognostic value of the Anatomic Stage Group and the Prognostic Stage Group. The study enrolled 170 HER2-enriched subtype breast cancer patients with 5-year disease free survival (DFS) of 85.1% and 5-year overall survival (OS) of 86.8%. Prognostic stages of 117 cases (68.8%) changed compared with anatomic stages, with 116 upstaged cases and 1 downstaged case. The Anatomic Stage Groups had a significant prognostic impact on DFS (χ 2 =16.752, p<0.001) and OS (χ 2 =25.038, p<0.001). The Prognostic Staging Groups had a significant prognostic impact on DFS (χ 2 =6.577, p=0.037) and OS (χ 2 =21.762, p<0.001). In the multivariate analysis, both stage groups were independent predictors of OS. Both Anatomic and Prognostic Stage Groups in the 8th edition of the AJCC breast cancer staging system had prognostic value in HER2-enriched subtype breast cancer. The Prognostic Stage system was a breakthrough on the basis of anatomic staging system. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Validation of cytogenetic risk groups according to International Prognostic Scoring Systems by peripheral blood CD34+FISH: results from a German diagnostic study in comparison with an international control group

PubMed Central

Braulke, Friederike; Platzbecker, Uwe; Müller-Thomas, Catharina; Götze, Katharina; Germing, Ulrich; Brümmendorf, Tim H.; Nolte, Florian; Hofmann, Wolf-Karsten; Giagounidis, Aristoteles A. N.; Lübbert, Michael; Greenberg, Peter L.; Bennett, John M.; Solé, Francesc; Mallo, Mar; Slovak, Marilyn L.; Ohyashiki, Kazuma; Le Beau, Michelle M.; Tüchler, Heinz; Pfeilstöcker, Michael; Nösslinger, Thomas; Hildebrandt, Barbara; Shirneshan, Katayoon; Aul, Carlo; Stauder, Reinhard; Sperr, Wolfgang R.; Valent, Peter; Fonatsch, Christa; Trümper, Lorenz; Haase, Detlef; Schanz, Julie

2015-01-01

International Prognostic Scoring Systems are used to determine the individual risk profile of myelodysplastic syndrome patients. For the assessment of International Prognostic Scoring Systems, an adequate chromosome banding analysis of the bone marrow is essential. Cytogenetic information is not available for a substantial number of patients (5%–20%) with dry marrow or an insufficient number of metaphase cells. For these patients, a valid risk classification is impossible. In the study presented here, the International Prognostic Scoring Systems were validated based on fluorescence in situ hybridization analyses using extended probe panels applied to cluster of differentiation 34 positive (CD34+) peripheral blood cells of 328 MDS patients of our prospective multicenter German diagnostic study and compared to chromosome banding results of 2902 previously published patients with myelodysplastic syndromes. For cytogenetic risk classification by fluorescence in situ hybridization analyses of CD34+ peripheral blood cells, the groups differed significantly for overall and leukemia-free survival by uni- and multivariate analyses without discrepancies between treated and untreated patients. Including cytogenetic data of fluorescence in situ hybridization analyses of peripheral CD34+ blood cells (instead of bone marrow banding analysis) into the complete International Prognostic Scoring System assessment, the prognostic risk groups separated significantly for overall and leukemia-free survival. Our data show that a reliable stratification to the risk groups of the International Prognostic Scoring Systems is possible from peripheral blood in patients with missing chromosome banding analysis by using a comprehensive probe panel (clinicaltrials.gov identifier:01355913). PMID:25344522

Evidence-Based Diagnostic Algorithm for Glioma: Analysis of the Results of Pathology Panel Review and Molecular Parameters of EORTC 26951 and 26882 Trials.

PubMed

Kros, Johan M; Huizer, Karin; Hernández-Laín, Aurelio; Marucci, Gianluca; Michotte, Alex; Pollo, Bianca; Rushing, Elisabeth J; Ribalta, Teresa; French, Pim; Jaminé, David; Bekka, Nawal; Lacombe, Denis; van den Bent, Martin J; Gorlia, Thierry

2015-06-10

With the rapid discovery of prognostic and predictive molecular parameters for glioma, the status of histopathology in the diagnostic process should be scrutinized. Our project aimed to construct a diagnostic algorithm for gliomas based on molecular and histologic parameters with independent prognostic values. The pathology slides of 636 patients with gliomas who had been included in EORTC 26951 and 26882 trials were reviewed using virtual microscopy by a panel of six neuropathologists who independently scored 18 histologic features and provided an overall diagnosis. The molecular data for IDH1, 1p/19q loss, EGFR amplification, loss of chromosome 10 and chromosome arm 10q, gain of chromosome 7, and hypermethylation of the promoter of MGMT were available for some of the cases. The slides were divided in discovery (n = 426) and validation sets (n = 210). The diagnostic algorithm resulting from analysis of the discovery set was validated in the latter. In 66% of cases, consensus of overall diagnosis was present. A diagnostic algorithm consisting of two molecular markers and one consensus histologic feature was created by conditional inference tree analysis. The order of prognostic significance was: 1p/19q loss, EGFR amplification, and astrocytic morphology, which resulted in the identification of four diagnostic nodes. Validation of the nodes in the validation set confirmed the prognostic value (P < .001). We succeeded in the creation of a timely diagnostic algorithm for anaplastic glioma based on multivariable analysis of consensus histopathology and molecular parameters. © 2015 by American Society of Clinical Oncology.

Prognostic Value of Pretherapeutic Tumor-to-Blood Standardized Uptake Ratio in Patients with Esophageal Carcinoma.

PubMed

Bütof, Rebecca; Hofheinz, Frank; Zöphel, Klaus; Stadelmann, Tobias; Schmollack, Julia; Jentsch, Christina; Löck, Steffen; Kotzerke, Jörg; Baumann, Michael; van den Hoff, Jörg

2015-08-01

Despite ongoing efforts to develop new treatment options, the prognosis for patients with inoperable esophageal carcinoma is still poor and the reliability of individual therapy outcome prediction based on clinical parameters is not convincing. The aim of this work was to investigate whether PET can provide independent prognostic information in such a patient group and whether the tumor-to-blood standardized uptake ratio (SUR) can improve the prognostic value of tracer uptake values. (18)F-FDG PET/CT was performed in 130 consecutive patients (mean age ± SD, 63 ± 11 y; 113 men, 17 women) with newly diagnosed esophageal cancer before definitive radiochemotherapy. In the PET images, the metabolically active tumor volume (MTV) of the primary tumor was delineated with an adaptive threshold method. The blood standardized uptake value (SUV) was determined by manually delineating the aorta in the low-dose CT. SUR values were computed as the ratio of tumor SUV and blood SUV. Uptake values were scan-time-corrected to 60 min after injection. Univariate Cox regression and Kaplan-Meier analysis with respect to overall survival (OS), distant metastases-free survival (DM), and locoregional tumor control (LRC) was performed. Additionally, a multivariate Cox regression including clinically relevant parameters was performed. In multivariate Cox regression with respect to OS, including T stage, N stage, and smoking state, MTV- and SUR-based parameters were significant prognostic factors for OS with similar effect size. Multivariate analysis with respect to DM revealed smoking state, MTV, and all SUR-based parameters as significant prognostic factors. The highest hazard ratios (HRs) were found for scan-time-corrected maximum SUR (HR = 3.9) and mean SUR (HR = 4.4). None of the PET parameters was associated with LRC. Univariate Cox regression with respect to LRC revealed a significant effect only for N stage greater than 0 (P = 0.048). PET provides independent prognostic information for OS and DM but not for LRC in patients with locally advanced esophageal carcinoma treated with definitive radiochemotherapy in addition to clinical parameters. Among the investigated uptake-based parameters, only SUR was an independent prognostic factor for OS and DM. These results suggest that the prognostic value of tracer uptake can be improved when characterized by SUR instead of SUV. Further investigations are required to confirm these preliminary results. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Assessment of the prognostic and predictive utility of the Breast Cancer Index (BCI): an NCIC CTG MA.14 study.

PubMed

Sgroi, Dennis C; Chapman, Judy-Anne W; Badovinac-Crnjevic, T; Zarella, Elizabeth; Binns, Shemeica; Zhang, Yi; Schnabel, Catherine A; Erlander, Mark G; Pritchard, Kathleen I; Han, Lei; Shepherd, Lois E; Goss, Paul E; Pollak, Michael

2016-01-04

Biomarkers that can be used to accurately assess the residual risk of disease recurrence in women with hormone receptor-positive breast cancer are clinically valuable. We evaluated the prognostic value of the Breast Cancer Index (BCI), a continuous risk index based on a combination of HOXB13:IL17BR and molecular grade index, in women with early breast cancer treated with either tamoxifen alone or tamoxifen plus octreotide in the NCIC MA.14 phase III clinical trial (ClinicalTrials.gov Identifier NCT00002864; registered 1 November 1999). Gene expression analysis of BCI by real-time polymerase chain reaction was performed blinded to outcome on RNA extracted from archived formalin-fixed, paraffin-embedded tumor samples of 299 patients with both lymph node-negative (LN-) and lymph node-positive (LN+) disease enrolled in the MA.14 trial. Our primary objective was to determine the prognostic performance of BCI based on relapse-free survival (RFS). MA.14 patients experienced similar RFS on both treatment arms. Association of gene expression data with RFS was evaluated in univariate analysis with a stratified log-rank test statistic, depicted with a Kaplan-Meier plot and an adjusted Cox survivor plot. In the multivariate assessment, we used stratified Cox regression. The prognostic performance of an emerging, optimized linear BCI model was also assessed in a post hoc analysis. Of 299 samples, 292 were assessed successfully for BCI for 146 patients accrued in each MA.14 treatment arm. BCI risk groups had a significant univariate association with RFS (stratified log-rank p = 0.005, unstratified log-rank p = 0.007). Adjusted 10-year RFS in BCI low-, intermediate-, and high-risk groups was 87.5 %, 83.9 %, and 74.7 %, respectively. BCI had a significant prognostic effect [hazard ratio (HR) 2.34, 95 % confidence interval (CI) 1.33-4.11; p = 0.004], although not a predictive effect, on RFS in stratified multivariate analysis, adjusted for pathological tumor stage (HR 2.22, 95 % CI 1.22-4.07; p = 0.01). In the post hoc multivariate analysis, higher linear BCI was associated with shorter RFS (p = 0.002). BCI had a strong prognostic effect on RFS in patients with early-stage breast cancer treated with tamoxifen alone or with tamoxifen and octreotide. BCI was prognostic in both LN- and LN+ patients. This retrospective study is an independent validation of the prognostic performance of BCI in a prospective trial.

Dose Escalation of Whole-Brain Radiotherapy for Brain Metastases From Melanoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rades, Dirk, E-mail: Rades.Dirk@gmx.ne; Heisterkamp, Christine; Huttenlocher, Stefan

2010-06-01

Purpose: The majority of patients with brain metastases from melanoma receive whole-brain radiotherapy (WBRT). However, the results are poor. Hypofractionation regimens failed to improve the outcome of these patients. This study investigates a potential benefit from escalation of the WBRT dose beyond the 'standard' regimen 30 Gy in 10 fractions (10x3 Gy). Methods and Materials: Data from 51 melanoma patients receiving WBRT alone were retrospectively analyzed. A dosage of 10x3 Gy (n = 33) was compared with higher doses including 40 Gy/20 fractions (n = 11) and 45 Gy/15 fractions (n = 7) for survival (OS) and local (intracerebral) controlmore » (LC). Additional potential prognostic factors were evaluated: age, gender, performance status, number of metastases, extracerebral metastases, and recursive partitioning analysis (RPA) class. Results: At 6 months, OS rates were 27% after 10x3 Gy and 50% after higher doses (p = 0.009). The OS rates at 12 months were 4% and 20%. On multivariate analysis, higher WBRT doses (p = 0.010), fewer than four brain metastases (p = 0.012), no extracerebral metastases (p = 0.006), and RPA class 1 (p = 0.005) were associated with improved OS. The LC rates at 6 months were 23% after 10x3 Gy and 50% after higher doses (p = 0.021). The LC rates at 12 months were 0% and 13%. On multivariate analysis, higher WBRT doses (p = 0.020) and fewer than brain metastases (p = 0.002) were associated with better LC. Conclusions: Given the limitations of a retrospective study, the findings suggest that patients with brain metastases from melanoma receiving WBRT alone may benefit from dose escalation beyond 10x3 Gy. The hypothesis generated by this study must be confirmed in a randomized trial stratifying for significant prognostic factors.« less

KPS/LDH index: a simple tool for identifying patients with metastatic melanoma who are unlikely to benefit from palliative whole brain radiotherapy.

PubMed

Partl, Richard; Fastner, Gerd; Kaiser, Julia; Kronhuber, Elisabeth; Cetin-Strohmer, Klaudia; Steffal, Claudia; Böhmer-Breitfelder, Barbara; Mayer, Johannes; Avian, Alexander; Berghold, Andrea

2016-02-01

Low Karnofsky performance status (KPS) and elevated lactate dehydrogenases (LDHs) as a surrogate marker for tumor load and cell turnover may depict patients with a very short life expectancy. To validate this finding and compare it to other indices, namely, the recursive partitioning analysis (RPA) and diagnosis-specific graded prognostic assessment (DS-GPA), a multicenter analysis was undertaken. A retrospective analysis of 234 metastatic melanoma patients uniformly treated with palliative whole brain radiotherapy (WBRT) was done. Univariate and multivariate analyses were used to determine the impact of patient-, tumor-, and treatment-related parameters on overall survival (OS). KPS and LDH emerged as independent factors predicting OS. By combining KPS and LDH values (KPS/LDH index), groups of patients with statistically significant differences in median OS (days; 95 % CI) after onset of WBRT were identified: group 1 (KPS ≥ 70/normal LDH) 234 (96-372), group 2 (KPS ≥ 70/elevated LDH) 112 (69-155), group 3 (KPS <70/normal LDH) 43 (12-74), and group 4 (KPS <70/elevated LDH) 29 (17-41). Between all four groups, statistically significant differences were observed. The RPA and DS-GPA indices failed to distinguish significantly between good and moderate prognosis and were inferior in predicting a very unfavorable prognosis. The parameters KPS and LDH independently impacted on OS. The combination of both (KPS/LDH index) identified patients with a very short life expectancy, who might be better served by recommending best supportive care instead of WBRT. The KPS/LDH index is simple and effective in terms of time and cost as compared to other prognostic indices.

Levelized cost-benefit analysis of proposed diagnostics for the Ammunition Transfer Arm of the US Army`s Future Armored Resupply Vehicle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilkinson, V.K.; Young, J.M.

1995-07-01

The US Army`s Project Manager, Advanced Field Artillery System/Future Armored Resupply Vehicle (PM-AFAS/FARV) is sponsoring the development of technologies that can be applied to the resupply vehicle for the Advanced Field Artillery System. The Engineering Technology Division of the Oak Ridge National Laboratory has proposed adding diagnostics/prognostics systems to four components of the Ammunition Transfer Arm of this vehicle, and a cost-benefit analysis was performed on the diagnostics/prognostics to show the potential savings that may be gained by incorporating these systems onto the vehicle. Possible savings could be in the form of reduced downtime, less unexpected or unnecessary maintenance, fewermore » regular maintenance checks. and/or tower collateral damage or loss. The diagnostics/prognostics systems are used to (1) help determine component problems, (2) determine the condition of the components, and (3) estimate the remaining life of the monitored components. The four components on the arm that are targeted for diagnostics/prognostics are (1) the electromechanical brakes, (2) the linear actuators, (3) the wheel/roller bearings, and (4) the conveyor drive system. These would be monitored using electrical signature analysis, vibration analysis, or a combination of both. Annual failure rates for the four components were obtained along with specifications for vehicle costs, crews, number of missions, etc. Accident scenarios based on component failures were postulated, and event trees for these scenarios were constructed to estimate the annual loss of the resupply vehicle, crew, arm. or mission aborts. A levelized cost-benefit analysis was then performed to examine the costs of such failures, both with and without some level of failure reduction due to the diagnostics/prognostics systems. Any savings resulting from using diagnostics/prognostics were calculated.« less

Dynamically heterogenous partitions and phylogenetic inference: an evaluation of analytical strategies with cytochrome b and ND6 gene sequences in cranes.

PubMed

Krajewski, C; Fain, M G; Buckley, L; King, D G

1999-11-01

ki ctes over whether molecular sequence data should be partitioned for phylogenetic analysis often confound two types of heterogeneity among partitions. We distinguish historical heterogeneity (i.e., different partitions have different evolutionary relationships) from dynamic heterogeneity (i.e., different partitions show different patterns of sequence evolution) and explore the impact of the latter on phylogenetic accuracy and precision with a two-gene, mitochondrial data set for cranes. The well-established phylogeny of cranes allows us to contrast tree-based estimates of relevant parameter values with estimates based on pairwise comparisons and to ascertain the effects of incorporating different amounts of process information into phylogenetic estimates. We show that codon positions in the cytochrome b and NADH dehydrogenase subunit 6 genes are dynamically heterogenous under both Poisson and invariable-sites + gamma-rates versions of the F84 model and that heterogeneity includes variation in base composition and transition bias as well as substitution rate. Estimates of transition-bias and relative-rate parameters from pairwise sequence comparisons were comparable to those obtained as tree-based maximum likelihood estimates. Neither rate-category nor mixed-model partitioning strategies resulted in a loss of phylogenetic precision relative to unpartitioned analyses. We suggest that weighted-average distances provide a computationally feasible alternative to direct maximum likelihood estimates of phylogeny for mixed-model analyses of large, dynamically heterogenous data sets. Copyright 1999 Academic Press.

Improved parallel data partitioning by nested dissection with applications to information retrieval.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolf, Michael M.; Chevalier, Cedric; Boman, Erik Gunnar

The computational work in many information retrieval and analysis algorithms is based on sparse linear algebra. Sparse matrix-vector multiplication is a common kernel in many of these computations. Thus, an important related combinatorial problem in parallel computing is how to distribute the matrix and the vectors among processors so as to minimize the communication cost. We focus on minimizing the total communication volume while keeping the computation balanced across processes. In [1], the first two authors presented a new 2D partitioning method, the nested dissection partitioning algorithm. In this paper, we improve on that algorithm and show that it ismore » a good option for data partitioning in information retrieval. We also show partitioning time can be substantially reduced by using the SCOTCH software, and quality improves in some cases, too.« less

Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores.

PubMed

Haile, Sarah R; Guerra, Beniamino; Soriano, Joan B; Puhan, Milo A

2017-12-21

Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.

Prognostic value of platelet-to-lymphocyte ratio in pancreatic cancer: a comprehensive meta-analysis of 17 cohort studies.

PubMed

Zhou, Yongping; Cheng, Sijin; Fathy, Abdel Hamid; Qian, Haixin; Zhao, Yongzhao

2018-01-01

Several studies were conducted to explore the prognostic value of platelet-to-lymphocyte ratio (PLR) in pancreatic cancer and have reported contradictory results. This study aims to summarize the prognostic role of PLR in pancreatic cancer. Embase, PubMed and Cochrane Library were completely searched. The cohort studies focusing on the prognostic role of PLR in pancreatic cancer were eligible. The overall survival (OS) and progression-free survival (PFS) were analyzed. Fifteen papers containing 17 cohort studies with pancreatic cancer were identified. The results showed patients that with low PLR might have longer OS when compared to the patients with high PLR (hazard ratio=1.28, 95% CI=1.17-1.40, P <0.00001; I 2 =42%). Similar results were observed in the subgroup analyses of OS, which was based on the analysis model, ethnicity, sample size and cut-off value. Further analyses based on the adjusted potential confounders were conducted, including CA199, neutrophil-to-lymphocyte ratio, modified Glasgow Prognostic Score, albumin, C-reactive protein, Eastern Cooperative Oncology Group, stage, tumor size, nodal involvement, tumor differentiation, margin status, age and gender, which confirmed that low PLR was a protective factor in pancreatic cancer. In addition, low PLR was significantly associated with longer PFS when compared to high PLR in pancreatic cancer (hazard ratio=1.27, 95% CI=1.03-1.57, P =0.03; I 2 =33%). In conclusion, it was found that high PLR is an unfavorable predictor of OS and PFS in patients with pancreatic cancer, and PLR is a promising prognostic biomarker for pancreatic cancer.

The prognostic value of preoperative inflammation-based prognostic scores and nutritional status for overall survival in resected patients with nonmetastatic Siewert type II/III adenocarcinoma of esophagogastric junction.

PubMed

Zhang, Lixiang; Su, Yezhou; Chen, Zhangming; Wei, Zhijian; Han, Wenxiu; Xu, Aman

2017-07-01

Immune and nutritional status of patients have been reported to predict postoperative complications, recurrence, and prognosis of patients with cancer. Therefore, this retrospective study aimed to explore the prognostic value of preoperative inflammation-based prognostic scores [neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR)] and nutritional status [prognostic nutritional index (PNI), body mass index (BMI), hemoglobin, albumin, and prealbumin] for overall survival (OS) in adenocarcinoma of esophagogastric junction (AEG) patients. A total of 355 patients diagnosed with Siewert type II/III AEG and underwent surgery between October 2010 and December 2011 were followed up until October 2016. Receiver operating characteristic (ROC) curve analysis was used to determine the cutoff values of NLR, PLR, and PNI. Kaplan-Meier curves and Cox regression analyses were used to calculate the OS characteristics. The ideal cutoff values for predicting OS were 3.5 for NLR, 171 for PLR, and 51.3 for PNI according to the ROC curve. The patients with hemoglobin <120 g/L (P = .001), prealbumin <180 mg/L (P = .000), PNI <51.3 (P = .010), NLR >3.5 (P = .000), PLR >171 (P = .006), and low BMI group (P = .000) had shorter OS. And multivariate survival analysis using the Cox proportional hazards model showed that the tumor-node-metastasis stage, BMI, NLR, and prealbumin levels were independent risk factors for the OS. Our study demonstrated that preoperative prealbumin, BMI, and NLR were independent prognostic factors of AEG patients.

Cost-Utility of a Prognostic Test Guiding Adjuvant Chemotherapy Decisions in Early-Stage Non-Small Cell Lung Cancer.

PubMed

Stenehjem, David D; Bellows, Brandon K; Yager, Kraig M; Jones, Joshua; Kaldate, Rajesh; Siebert, Uwe; Brixner, Diana I

2016-02-01

A prognostic test was developed to guide adjuvant chemotherapy (ACT) decisions in early-stage non-small cell lung cancer (NSCLC) adenocarcinomas. The objective of this study was to compare the cost-utility of the prognostic test to the current standard of care (SoC) in patients with early-stage NSCLC. Lifetime costs (2014 U.S. dollars) and effectiveness (quality-adjusted life-years [QALYs]) of ACT treatment decisions were examined using a Markov microsimulation model from a U.S. third-party payer perspective. Cancer stage distribution and probability of receiving ACT with the SoC were based on data from an academic cancer center. The probability of receiving ACT with the prognostic test was estimated from a physician survey. Risk classification was based on the 5-year predicted NSCLC-related mortality. Treatment benefit with ACT was based on the prognostic score. Discounting at a 3% annual rate was applied to costs and QALYs. Deterministic one-way and probabilistic sensitivity analyses examined parameter uncertainty. Lifetime costs and effectiveness were $137,403 and 5.45 QALYs with the prognostic test and $127,359 and 5.17 QALYs with the SoC. The resulting incremental cost-effectiveness ratio for the prognostic test versus the SoC was $35,867/QALY gained. One-way sensitivity analyses indicated the model was most sensitive to the utility of patients without recurrence after ACT and the ACT treatment benefit. Probabilistic sensitivity analysis indicated the prognostic test was cost-effective in 65.5% of simulations at a willingness to pay of $50,000/QALY. The study suggests using a prognostic test to guide ACT decisions in early-stage NSCLC is potentially cost-effective compared with using the SoC based on globally accepted willingness-to-pay thresholds. Providing prognostic information to decision makers may help some patients with high-risk early stage non-small cell lung cancer receive appropriate adjuvant chemotherapy while avoiding the associated toxicities and costs in patients with low-risk disease. This study used an economic model to assess the effectiveness and costs associated with using a prognostic test to guide adjuvant chemotherapy decisions compared with the current standard of care in patients with non-small cell lung cancer. When compared with current standard care, the prognostic test was potentially cost effective at commonly accepted thresholds in the U.S. This study can be used to help inform decision makers who are considering using prognostic tests. ©AlphaMed Press.

Age distribution and age-related outcomes of olfactory neuroblastoma: a population-based analysis.

PubMed

Yin, Zhenzhen; Wang, Youyou; Wu, Yuemei; Zhang, Ximei; Wang, Fengming; Wang, Peiguo; Tao, Zhen; Yuan, Zhiyong

2018-01-01

The objective of the study was to describe the age distribution and to evaluate the role of prognostic value of age on survival in patients diagnosed with olfactory neuroblastoma (ONB). A population-based retrospective analysis was conducted. The population-based study of patients in the Surveillance, Epidemiology, and End Results (SEER) tumor registry, who were diagnosed with ONB from 1973 to 2014, were retrospectively analyzed. The cohort included 876 patients with a median age of 54 years. There was a unimodal distribution of age and ONBs most frequently occurred in the fifth to sixth decades of life. Kaplan-Meier analysis demonstrated overall survival (OS) and cancer-specific survival (CSS) rates of 69% and 78% at 5 years. Multivariable Cox regression analysis showed that age, SEER stage, and surgery were independent prognostic factors for CSS. The risk of overall death and cancer-specific death increased 3.1% and 1.6% per year, respectively. Patients aged >60 years presented significantly poor OS and CSS compared with patients aged ≤60 years, even in patients with loco-regional disease or in those treated with surgery. This study highlights the growing evidence that there is a unimodal age distribution of ONB and that age is an important adverse prognostic factor.

Binary partition tree analysis based on region evolution and its application to tree simplification.

PubMed

Lu, Huihai; Woods, John C; Ghanbari, Mohammed

2007-04-01

Pyramid image representations via tree structures are recognized methods for region-based image analysis. Binary partition trees can be applied which document the merging process with small details found at the bottom levels and larger ones close to the root. Hindsight of the merging process is stored within the tree structure and provides the change histories of an image property from the leaf to the root node. In this work, the change histories are modelled by evolvement functions and their second order statistics are analyzed by using a knee function. Knee values show the reluctancy of each merge. We have systematically formulated these findings to provide a novel framework for binary partition tree analysis, where tree simplification is demonstrated. Based on an evolvement function, for each upward path in a tree, the tree node associated with the first reluctant merge is considered as a pruning candidate. The result is a simplified version providing a reduced solution space and still complying with the definition of a binary tree. The experiments show that image details are preserved whilst the number of nodes is dramatically reduced. An image filtering tool also results which preserves object boundaries and has applications for segmentation.

Comprehensive analysis and validation of contemporary survival prognosticators in Korean patients with metastatic renal cell carcinoma treated with targeted therapy: prognostic impact of pretreatment neutrophil-to-lymphocyte ratio.

PubMed

Koo, Kyo Chul; Lee, Kwang Suk; Cho, Kang Su; Rha, Koon Ho; Hong, Sung Joon; Chung, Byung Ha

2016-06-01

In line with the era of targeted therapy (TT), an increasing number of prognosticators are becoming available for patients with metastatic renal cell carcinoma (mRCC). Here, potential prognosticators of cancer-specific survival (CSS) were identified based on the contemporary literature and were comprehensively validated in an independent cohort of patients treated for mRCC. Data were collected from 478 patients treated with TT for mRCC between January 1999 and July 2013 at a single institution. The analysis included 25 clinicopathological covariates that included both traditional and contemporary prognosticators. Multivariate Cox regression models were used to quantify the effect of covariates on CSS. Median survival from the initial diagnosis of metastasis was 24.5 (IQR, 11.5-55.7) months. There were 303 (63.4 %) cancer-specific deaths, yielding a 2-year CSS rate of 62.5 %. Low Karnofsky performance status (KPS), hypercalcemia, neutrophil-to-lymphocyte ratio (NLR), the number of metastatic sites (≥2), and the presence of brain metastases were independent adverse prognosticators of CSS. The C-index of the model was 0.78. Patients with at least one adverse prognosticator demonstrated lower 2-year CSS rates compared to those with no prognosticators (53.9 vs. 70.6 %; log rank p < 0.001). Together with traditional prognosticators such as KPS, hypercalcemia, and the number and location of metastases, the NLR was an independent predictor of CSS in patients with mRCC treated with TT. Our findings could be useful for guiding clinical decision making including stratification of patients for TT and inclusion in clinical trials.

Prognostic Analysis System and Methods of Operation

NASA Technical Reports Server (NTRS)

MacKey, Ryan M. E. (Inventor); Sneddon, Robert (Inventor)

2014-01-01

A prognostic analysis system and methods of operating the system are provided. In particular, a prognostic analysis system for the analysis of physical system health applicable to mechanical, electrical, chemical and optical systems and methods of operating the system are described herein.

Inference and Analysis of Population Structure Using Genetic Data and Network Theory.

PubMed

Greenbaum, Gili; Templeton, Alan R; Bar-David, Shirli

2016-04-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). Copyright © 2016 by the Genetics Society of America.

Prognostics and Health Management of Wind Turbines: Current Status and Future Opportunities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, Shuangwen

Prognostics and health management is not a new concept. It has been used in relatively mature industries, such as aviation and electronics, to help improve operation and maintenance (O&M) practices. In the wind industry, prognostics and health management is relatively new. The level for both wind industry applications and research and development (R&D) has increased in recent years because of its potential for reducing O&M cost of wind power, especially for turbines installed offshore. The majority of wind industry application efforts has been focused on diagnosis based on various sensing and feature extraction techniques. For R&D, activities are being conductedmore » in almost all areas of a typical prognostics and health management framework (i.e., sensing, data collection, feature extraction, diagnosis, prognosis, and maintenance scheduling). This presentation provides an overview of the current status of wind turbine prognostics and health management that focuses on drivetrain condition monitoring through vibration, oil debris, and oil condition analysis techniques. It also discusses turbine component health diagnosis through data mining and modeling based on supervisory control and data acquisition system data. Finally, it provides a brief survey of R&D activities for wind turbine prognostics and health management, along with future opportunities.« less

Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

PubMed

Drier, Yotam; Domany, Eytan

2011-03-14

The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

MODFLOW-CDSS, a version of MODFLOW-2005 with modifications for Colorado Decision Support Systems

USGS Publications Warehouse

Banta, Edward R.

2011-01-01

MODFLOW-CDSS is a three-dimensional, finite-difference groundwater-flow model based on MODFLOW-2005, with two modifications. The first modification is the introduction of a Partition Stress Boundaries capability, which enables the user to partition a selected subset of MODFLOW's stress-boundary packages, with each partition defined by a separate input file. Volumetric water-budget components of each partition are tracked and listed separately in the volumetric water-budget tables. The second modification enables the user to specify that execution of a simulation should continue despite failure of the solver to satisfy convergence criteria. This modification is particularly intended to be used in conjunction with automated model-analysis software; its use is not recommended for other purposes.

The prognostic role of CD68 and FoxP3 expression in patients with primary central nervous system lymphoma.

PubMed

Cho, Hyunsoo; Kim, Se Hoon; Kim, Soo-Jeong; Chang, Jong Hee; Yang, Woo Ick; Suh, Chang-Ok; Cheong, June-Won; Kim, Yu Ri; Lee, Jung Yeon; Jang, Ji Eun; Kim, Yundeok; Min, Yoo Hong; Kim, Jin Seok

2017-07-01

The prognostic role of CD68 and FoxP3 in primary central nervous system lymphoma (PCNSL) has not been evaluated. Thus, we examined the prognostic significance of CD68 and FoxP3 expression in tumor samples of 76 newly diagnosed immunocompetent PCNSL patients. All patients were treated initially with high-dose methotrexate (HD-MTX)-based chemotherapy, and 16 (21.1%) patients received upfront autologous stem cell transplantation (ASCT) consolidation. High expression of CD68 (>55 cells/high-power field) or FoxP3 (>15 cells/high-power field) was observed in 10 patients, respectively. High CD68 expression was associated with inferior overall survival (OS) and progression-free survival (PFS) in multivariate analysis (P = 0.023 and P = 0.021, respectively). In addition, we performed subgroup analysis based on upfront ASCT. High CD68 expression was also associated with inferior OS and PFS in multivariate analysis (P = 0.013 and P < 0.001, respectively) among patients who did not receive upfront ASCT (n = 60), but not in patients who received upfront ASCT. The expression of FoxP3 was not significantly associated with survival. Therefore, we identified a prognostic significance of high CD68 expression in PCNSL, which suggests a need for further clinical trials and biological studies on the role of PCNSL tumor microenvironment.

Drug Distribution. Part 1. Models to Predict Membrane Partitioning.

PubMed

Nagar, Swati; Korzekwa, Ken

2017-03-01

Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution. Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs. The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs). Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.

Pseudobulbar affect as a negative prognostic indicator in amyotrophic lateral sclerosis.

PubMed

Tortelli, R; Arcuti, S; Copetti, M; Barone, R; Zecca, C; Capozzo, R; Barulli, M R; Simone, I L; Logroscino, G

2018-07-01

To evaluate whether the presence of pseudobulbar affect (PBA) in an early stage of the disease influences survival in a population-based incident cohort of amyotrophic lateral sclerosis (ALS). Incident ALS cases, diagnosed according to El Escorial criteria, were enrolled from a prospective population-based registry in Puglia, Southern Italy. The Center for Neurologic Study-Lability Scale (CNS-LS), a self-administered questionnaire, was used to evaluate PBA. Total scores range from 7 to 35. A score ≥13 was used to identify PBA. Cox proportional hazard models were used for survival analysis. The modified C-statistic for censored survival data was used for models' discrimination. RECursive Partitioning and AMalgamation (RECPAM) analysis was used to identify subgroups of patients with different patterns of risk, depending on baseline characteristics. We enrolled 94 sporadic ALS, median age of 64 years (range: 26-80). At the censoring date, 65 of 94 (69.2%), 39 of 60 (65.0%), and 26 of 34 (76.5%) patients reached the outcome (tracheotomy/death), in the whole, non-PBA and in the PBA groups, respectively. Kaplan-Meier survival curves for the two subgroups were not significantly different (log-rank test: 1.3, P = .25). The discrimination ability of a multivariable model with demographic and clinical variables of interest was not improved by adding PBA. In the RECPAM analysis, ALSFRSr and the total score of CNS-LS scale (

Validation of cytogenetic risk groups according to International Prognostic Scoring Systems by peripheral blood CD34+FISH: results from a German diagnostic study in comparison with an international control group.

PubMed

Braulke, Friederike; Platzbecker, Uwe; Müller-Thomas, Catharina; Götze, Katharina; Germing, Ulrich; Brümmendorf, Tim H; Nolte, Florian; Hofmann, Wolf-Karsten; Giagounidis, Aristoteles A N; Lübbert, Michael; Greenberg, Peter L; Bennett, John M; Solé, Francesc; Mallo, Mar; Slovak, Marilyn L; Ohyashiki, Kazuma; Le Beau, Michelle M; Tüchler, Heinz; Pfeilstöcker, Michael; Nösslinger, Thomas; Hildebrandt, Barbara; Shirneshan, Katayoon; Aul, Carlo; Stauder, Reinhard; Sperr, Wolfgang R; Valent, Peter; Fonatsch, Christa; Trümper, Lorenz; Haase, Detlef; Schanz, Julie

2015-02-01

International Prognostic Scoring Systems are used to determine the individual risk profile of myelodysplastic syndrome patients. For the assessment of International Prognostic Scoring Systems, an adequate chromosome banding analysis of the bone marrow is essential. Cytogenetic information is not available for a substantial number of patients (5%-20%) with dry marrow or an insufficient number of metaphase cells. For these patients, a valid risk classification is impossible. In the study presented here, the International Prognostic Scoring Systems were validated based on fluorescence in situ hybridization analyses using extended probe panels applied to cluster of differentiation 34 positive (CD34(+)) peripheral blood cells of 328 MDS patients of our prospective multicenter German diagnostic study and compared to chromosome banding results of 2902 previously published patients with myelodysplastic syndromes. For cytogenetic risk classification by fluorescence in situ hybridization analyses of CD34(+) peripheral blood cells, the groups differed significantly for overall and leukemia-free survival by uni- and multivariate analyses without discrepancies between treated and untreated patients. Including cytogenetic data of fluorescence in situ hybridization analyses of peripheral CD34(+) blood cells (instead of bone marrow banding analysis) into the complete International Prognostic Scoring System assessment, the prognostic risk groups separated significantly for overall and leukemia-free survival. Our data show that a reliable stratification to the risk groups of the International Prognostic Scoring Systems is possible from peripheral blood in patients with missing chromosome banding analysis by using a comprehensive probe panel (clinicaltrials.gov identifier:01355913). Copyright© Ferrata Storti Foundation.

Clustering Financial Time Series by Network Community Analysis

NASA Astrophysics Data System (ADS)

Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma.

PubMed

Giridhar, Karthik V; Sosa, Carlos P; Hillman, David W; Sanhueza, Cristobal; Dalpiaz, Candace L; Costello, Brian A; Quevedo, Fernando J; Pitot, Henry C; Dronca, Roxana S; Ertz, Donna; Cheville, John C; Donkena, Krishna Vanaja; Kohli, Manish

2017-11-03

The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. In an independent validation of set of 47 patients with mCCRCC, transcript expression of the 18 candidate genes were quantified using a customized NanoString probeset. Cox regression multivariate analysis confirmed that two of the candidate genes were significantly associated with overall survival. Higher expression of BAG1 [hazard ratio (HR) of 0.14, p < 0.0001, 95% confidence interval (CI) 0.04-0.36] and NOP56 (HR 0.13, p < 0.0001, 95% CI 0.05-0.34) were associated with better prognosis. A prognostic model incorporating expression of BAG1 and NOP56 into the MSKCC score improved prognostication significantly over a model using the MSKCC prognostic score only ( p < 0.0001). Prognostic value of using whole blood mRNA gene profiling in mCCRCC is feasible and should be prospectively confirmed in larger studies.

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma

PubMed Central

Sosa, Carlos P.; Hillman, David W.; Sanhueza, Cristobal; Dalpiaz, Candace L.; Costello, Brian A.; Quevedo, Fernando J.; Pitot, Henry C.; Dronca, Roxana S.; Ertz, Donna; Cheville, John C.; Donkena, Krishna Vanaja; Kohli, Manish

2017-01-01

The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. In an independent validation of set of 47 patients with mCCRCC, transcript expression of the 18 candidate genes were quantified using a customized NanoString probeset. Cox regression multivariate analysis confirmed that two of the candidate genes were significantly associated with overall survival. Higher expression of BAG1 [hazard ratio (HR) of 0.14, p < 0.0001, 95% confidence interval (CI) 0.04–0.36] and NOP56 (HR 0.13, p < 0.0001, 95% CI 0.05–0.34) were associated with better prognosis. A prognostic model incorporating expression of BAG1 and NOP56 into the MSKCC score improved prognostication significantly over a model using the MSKCC prognostic score only (p < 0.0001). Prognostic value of using whole blood mRNA gene profiling in mCCRCC is feasible and should be prospectively confirmed in larger studies. PMID:29099775

Nomograms Predicting Progression-Free Survival, Overall Survival, and Pelvic Recurrence in Locally Advanced Cervical Cancer Developed From an Analysis of Identifiable Prognostic Factors in Patients From NRG Oncology/Gynecologic Oncology Group Randomized Trials of Chemoradiotherapy

PubMed Central

Rose, Peter G.; Java, James; Whitney, Charles W.; Stehman, Frederick B.; Lanciano, Rachelle; Thomas, Gillian M.; DiSilvestro, Paul A.

2015-01-01

Purpose To evaluate the prognostic factors in locally advanced cervical cancer limited to the pelvis and develop nomograms for 2-year progression-free survival (PFS), 5-year overall survival (OS), and pelvic recurrence. Patients and Methods We retrospectively reviewed 2,042 patients with locally advanced cervical carcinoma enrolled onto Gynecologic Oncology Group clinical trials of concurrent cisplatin-based chemotherapy and radiotherapy. Nomograms for 2-year PFS, five-year OS, and pelvic recurrence were created as visualizations of Cox proportional hazards regression models. The models were validated by bootstrap-corrected, relatively unbiased estimates of discrimination and calibration. Results Multivariable analysis identified prognostic factors including histology, race/ethnicity, performance status, tumor size, International Federation of Gynecology and Obstetrics stage, tumor grade, pelvic node status, and treatment with concurrent cisplatin-based chemotherapy. PFS, OS, and pelvic recurrence nomograms had bootstrap-corrected concordance indices of 0.62, 0.64, and 0.73, respectively, and were well calibrated. Conclusion Prognostic factors were used to develop nomograms for 2-year PFS, 5-year OS, and pelvic recurrence for locally advanced cervical cancer clinically limited to the pelvis treated with concurrent cisplatin-based chemotherapy and radiotherapy. These nomograms can be used to better estimate individual and collective outcomes. PMID:25732170

Entropy-Based Adaptive Nuclear Texture Features are Independent Prognostic Markers in a Total Population of Uterine Sarcomas

PubMed Central

Nielsen, Birgitte; Hveem, Tarjei Sveinsgjerd; Kildal, Wanja; Abeler, Vera M; Kristensen, Gunnar B; Albregtsen, Fritz; Danielsen, Håvard E; Rohde, Gustavo K

2015-01-01

Nuclear texture analysis measures the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image and is a promising quantitative tool for prognosis of cancer. The aim of this study was to evaluate the prognostic value of entropy-based adaptive nuclear texture features in a total population of 354 uterine sarcomas. Isolated nuclei (monolayers) were prepared from 50 µm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices, and two superior adaptive texture features were calculated from each matrix. The 5-year crude survival was significantly higher (P < 0.001) for patients with high texture feature values (72%) than for patients with low feature values (36%). When combining DNA ploidy classification (diploid/nondiploid) and texture (high/low feature value), the patients could be stratified into three risk groups with 5-year crude survival of 77, 57, and 34% (Hazard Ratios (HR) of 1, 2.3, and 4.1, P < 0.001). Entropy-based adaptive nuclear texture was an independent prognostic marker for crude survival in multivariate analysis including relevant clinicopathological features (HR = 2.1, P = 0.001), and should therefore be considered as a potential prognostic marker in uterine sarcomas. © The Authors. Published 2014 International Society for Advancement of Cytometry PMID:25483227

Interactomic approach for evaluating nucleophosmin-binding proteins as biomarkers for Ewing's sarcoma.

PubMed

Haga, Ayako; Ogawara, Yoko; Kubota, Daisuke; Kitabayashi, Issay; Murakami, Yasufumi; Kondo, Tadashi

2013-06-01

Nucleophosmin (NPM) is a novel prognostic biomarker for Ewing's sarcoma. To evaluate the prognostic utility of NPM, we conducted an interactomic approach to characterize the NPM protein complex in Ewing's sarcoma cells. A gene suppression assay revealed that NPM promoted cell proliferation and the invasive properties of Ewing's sarcoma cells. FLAG-tag-based affinity purification coupled with liquid chromatography-tandem mass spectrometry identified 106 proteins in the NPM protein complex. The functional classification suggested that the NPM complex participates in critical biological events, including ribosome biogenesis, regulation of transcription and translation, and protein folding, that are mediated by these proteins. In addition to JAK1, a candidate prognostic biomarker for Ewing's sarcoma, the NPM complex, includes 11 proteins known as prognostic biomarkers for other malignancies. Meta-analysis of gene expression profiles of 32 patients with Ewing's sarcoma revealed that 6 of 106 were significantly and independently associated with survival period. These observations suggest a functional role as well as prognostic value of these NPM complex proteins in Ewing's sarcoma. Further, our study suggests the potential applications of interactomics in conjunction with meta-analysis for biomarker discovery. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation of prognostic factors in liver-limited metastatic colorectal cancer: a preplanned analysis of the FIRE-1 trial

PubMed Central

Giessen, C; Fischer von Weikersthal, L; Laubender, R P; Stintzing, S; Modest, D P; Schalhorn, A; Schulz, C; Heinemann, V

2013-01-01

Background: Liver-limited disease (LLD) denotes a specific subgroup of metastatic colorectal cancer (mCRC) patients. Patients and Methods: A total of 479 patients with unresectable mCRC from an irinotecan-based randomised phase III trial were evaluated. Patients with LLD and non-LLD and hepatic resection were differentiated. Based on baseline patient characteristic, prognostic factors for hepatic resection were evaluated. Furthermore, prognostic factors for median overall survival (OS) were estimated via Cox regression in LLD patients. Results: Secondary liver resection was performed in 38 out of 479 patients (resection rate: 7.9%). Prognostic factors for hepatic resection were LLD, lactate dehydrogenase (LDH), node-negative primary, alkaline phosphatase (AP) and Karnofsky performance status (PS). Median OS was significantly increased after hepatic resection (48 months), whereas OS in LLD (17 months) and non-LLD (19 months) was comparable in non-resected patients. With the inapplicability of Koehne's risk classification in LLD patients, a new score based on only the independent prognostic factors LDH and white blood cell (WBC) provided markedly improved information on the outcome. Conclusion: Patients undergoing hepatic resection showed favourable long-term survival, whereas non-resected LLD patients and non-LLD patients did not differ with regard to progression-free survival and OS. The LDH levels and WBC count were confirmed as prognostic factors and provide a useful and simple score for OS-related risk stratification also in LLD. PMID:23963138

Extensions to regret-based decision curve analysis: an application to hospice referral for terminal patients.

PubMed

Tsalatsanis, Athanasios; Barnes, Laura E; Hozo, Iztok; Djulbegovic, Benjamin

2011-12-23

Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned.

Extensions to Regret-based Decision Curve Analysis: An application to hospice referral for terminal patients

PubMed Central

2011-01-01

Background Despite the well documented advantages of hospice care, most terminally ill patients do not reap the maximum benefit from hospice services, with the majority of them receiving hospice care either prematurely or delayed. Decision systems to improve the hospice referral process are sorely needed. Methods We present a novel theoretical framework that is based on well-established methodologies of prognostication and decision analysis to assist with the hospice referral process for terminally ill patients. We linked the SUPPORT statistical model, widely regarded as one of the most accurate models for prognostication of terminally ill patients, with the recently developed regret based decision curve analysis (regret DCA). We extend the regret DCA methodology to consider harms associated with the prognostication test as well as harms and effects of the management strategies. In order to enable patients and physicians in making these complex decisions in real-time, we developed an easily accessible web-based decision support system available at the point of care. Results The web-based decision support system facilitates the hospice referral process in three steps. First, the patient or surrogate is interviewed to elicit his/her personal preferences regarding the continuation of life-sustaining treatment vs. palliative care. Then, regret DCA is employed to identify the best strategy for the particular patient in terms of threshold probability at which he/she is indifferent between continuation of treatment and of hospice referral. Finally, if necessary, the probabilities of survival and death for the particular patient are computed based on the SUPPORT prognostication model and contrasted with the patient's threshold probability. The web-based design of the CDSS enables patients, physicians, and family members to participate in the decision process from anywhere internet access is available. Conclusions We present a theoretical framework to facilitate the hospice referral process. Further rigorous clinical evaluation including testing in a prospective randomized controlled trial is required and planned. PMID:22196308

Clinicopathologic and prognostic significance of C-reactive protein/albumin ratio in patients with solid tumors: an updated systemic review and meta-analysis.

PubMed

Wu, Jiayuan; Tan, Wenkai; Chen, Lin; Huang, Zhe; Mai, Shao

2018-03-02

C-reactive protein/albumin ratio (CAR) was originally used as a novel inflammation-based prognostic score in predicting outcomes in septic patients. Recently, more and more studies have reported the prognostic value of pretreatment CAR in solid tumors. However, the results remain controversial rather than conclusive. We conducted a meta-analysis based on 24 studies with 10203 patients to explore the relationship between CAR and survival outcomes in patients with solid tumors. The correlation between CAR and clinicopathological parameters was also assessed. Hazard ratio (HR) or odds ratio (OR) with its 95% confidence interval (CI) was applied to be the effect size estimate. The overall results showed that elevated CAR was associated with shorter overall survival (OS) (including 23 studies and 10067 patients) and poorer disease-free survival (DFS) (including 6 studies and 2904 patients). Significant associations between high CAR level and poor OS were also found in the subgroup analyses of study region, cancer type, primary treatment, clinical stage, cut-off selection, sample size, and cut-off value. Moreover, subgroup analyses demonstrated that study region, primary treatment, clinical stage, sample size, and cut-off value did not alter the prognostic value of CAR for DFS. Furthermore, elevated CAR was correlated with certain phenotypes of tumor aggressiveness, such as poor histological grade, serious clinical stage, advanced tumor depth, positive lymph node metastasis, and positive distant metastasis. Together, our meta-analysis suggests that elevated level of serum CAR predicts worse survival and unfavorable clinical characteristics in cancer patients, and CAR may serve as an effective prognostic factor for solid tumors.

Prognostic significance of IDH 1 mutation in patients with glioblastoma multiforme.

PubMed

Khan, Inamullah; Waqas, Muhammad; Shamim, Muhammad Shahzad

2017-05-01

Focus of brain tumour research is shifting towards tumour genesis and genetics, and possible development of individualized treatment plans. Genetic analysis shows recurrent mutation in isocitrate dehydrogenase (IDH1) gene in most Glioblastoma multiforme (GBM) cells. In this review we evaluated the prognostic significance of IDH 1 mutation on the basis of published evidence. Multiple retrospective clinical analyses correlate the presence of IDH1 mutation in GBM with good prognostic outcomes compared to wild-type IDH1. A systematic review reported similar results. Based on the review of current literature IDH1 mutation is an independent factor for longer overall survival (OS) and progression free survival (PFS) in GBM patients when compared to wild-type IDH1. The prognostic significance opens up new avenues for treatment.

Partition of some key regulating services in terrestrial ecosystems: Meta-analysis and review.

PubMed

Viglizzo, E F; Jobbágy, E G; Ricard, M F; Paruelo, J M

2016-08-15

Our knowledge about the functional foundations of ecosystem service (ES) provision is still limited and more research is needed to elucidate key functional mechanisms. Using a simplified eco-hydrological scheme, in this work we analyzed how land-use decisions modify the partition of some essential regulatory ES by altering basic relationships between biomass stocks and water flows. A comprehensive meta-analysis and review was conducted based on global, regional and local data from peer-reviewed publications. We analyzed five datasets comprising 1348 studies and 3948 records on precipitation (PPT), aboveground biomass (AGB), AGB change, evapotranspiration (ET), water yield (WY), WY change, runoff (R) and infiltration (I). The conceptual framework was focused on ES that are associated with the ecological functions (e.g., intermediate ES) of ET, WY, R and I. ES included soil protection, carbon sequestration, local climate regulation, water-flow regulation and water recharge. To address the problem of data normality, the analysis included both parametric and non-parametric regression analysis. Results demonstrate that PPT is a first-order biophysical factor that controls ES release at the broader scales. At decreasing scales, ES are partitioned as result of PPT interactions with other biophysical and anthropogenic factors. At intermediate scales, land-use change interacts with PPT modifying ES partition as it the case of afforestation in dry regions, where ET and climate regulation may be enhanced at the expense of R and water-flow regulation. At smaller scales, site-specific conditions such as topography interact with PPT and AGB displaying different ES partition formats. The probable implications of future land-use and climate change on some key ES production and partition are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

PubMed

Molgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner; Kent, Peter; Kongsted, Alice

2017-08-09

Heterogeneity in patients with low back pain is well recognised and different approaches to subgrouping have been proposed. One statistical technique that is increasingly being used is Latent Class Analysis as it performs subgrouping based on pattern recognition with high accuracy. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two-stage approach. However, their prognostic capacity was unexplored. This study (i) determined whether the subgrouping approaches were associated with the future outcomes of pain intensity, pain frequency and disability, (ii) assessed whether one of these two approaches was more strongly or more consistently associated with these outcomes, and (iii) assessed the performance of the novel subgroupings as compared to the following variables: two existing subgrouping tools (STarT Back Tool and Quebec Task Force classification), four baseline characteristics and a group of previously identified domain-specific patient categorisations (collectively, the 'comparator variables'). This was a longitudinal cohort study of 928 patients consulting for low back pain in primary care. The associations between each subgroup approach and outcomes at 2 weeks, 3 and 12 months, and with weekly SMS responses were tested in linear regression models, and their prognostic capacity (variance explained) was compared to that of the comparator variables listed above. The two previously identified subgroupings were similarly associated with all outcomes. The prognostic capacity of both subgroupings was better than that of the comparator variables, except for participants' recovery beliefs and the domain-specific categorisations, but was still limited. The explained variance ranged from 4.3%-6.9% for pain intensity and from 6.8%-20.3% for disability, and highest at the 2 weeks follow-up. Latent Class-derived subgroups provided additional prognostic information when compared to a range of variables, but the improvements were not substantial enough to warrant further development into a new prognostic tool. Further research could investigate if these novel subgrouping approaches may help to improve existing tools that subgroup low back pain patients.

Investigating the Effect of Damage Progression Model Choice on Prognostics Performance

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Narasimhan, Sriram; Saha, Sankalita; Saha, Bhaskar; Goebel, Kai

2011-01-01

The success of model-based approaches to systems health management depends largely on the quality of the underlying models. In model-based prognostics, it is especially the quality of the damage progression models, i.e., the models describing how damage evolves as the system operates, that determines the accuracy and precision of remaining useful life predictions. Several common forms of these models are generally assumed in the literature, but are often not supported by physical evidence or physics-based analysis. In this paper, using a centrifugal pump as a case study, we develop different damage progression models. In simulation, we investigate how model changes influence prognostics performance. Results demonstrate that, in some cases, simple damage progression models are sufficient. But, in general, the results show a clear need for damage progression models that are accurate over long time horizons under varied loading conditions.

Inflammation-based prognostic score is a useful predictor of postoperative outcome in patients with extrahepatic cholangiocarcinoma.

PubMed

Oshiro, Yukio; Sasaki, Ryoko; Fukunaga, Kiyoshi; Kondo, Tadashi; Oda, Tatsuya; Takahashi, Hideto; Ohkohchi, Nobuhiro

2013-03-01

Recent studies have revealed that the Glasgow prognostic score (GPS), an inflammation-based prognostic score, is useful for predicting outcome in a variety of cancers. This study sought to investigate the significance of GPS for prognostication of patients who underwent surgery with extrahepatic cholangiocarcinoma. We retrospectively analyzed a total of 62 patients who underwent resection for extrahepatic cholangiocarcinoma. We calculated the GPS as follows: patients with both an elevated C-reactive protein (>10 mg/L) and hypoalbuminemia (<35 g/L) were allocated a score of 2; patients with one or none of these abnormalities were allocated a s ore of 1 or 0, respectively. Prognostic significance was analyzed by the log-rank test and a Cox proportional hazards model. Overall survival rate was 25.5 % at 5 years for all 62 patients. Venous invasion (p = 0.01), pathological primary tumor category (p = 0.013), lymph node metastasis category (p < 0.001), TNM stage (p < 0.001), and GPS (p = 0.008) were significantly associated with survival by univariate analysis. A Cox model demonstrated that increased GPS was an independent predictive factor with poor prognosis. The preoperative GPS is a useful predictor of postoperative outcome in patients with extrahepatic cholangiocarcinoma.

The potential of cloud point system as a novel two-phase partitioning system for biotransformation.

PubMed

Wang, Zhilong

2007-05-01

Although the extractive biotransformation in two-phase partitioning systems have been studied extensively, such as the water-organic solvent two-phase system, the aqueous two-phase system, the reverse micelle system, and the room temperature ionic liquid, etc., this has not yet resulted in a widespread industrial application. Based on the discussion of the main obstacles, an exploitation of a cloud point system, which has already been applied in a separation field known as a cloud point extraction, as a novel two-phase partitioning system for biotransformation, is reviewed by analysis of some topical examples. At the end of the review, the process control and downstream processing in the application of the novel two-phase partitioning system for biotransformation are also briefly discussed.

A nomogram to predict prognostic values of various inflammatory biomarkers in patients with esophageal squamous cell carcinoma

PubMed Central

Liu, Jin-Shi; Huang, Ying; Yang, Xun; Feng, Ji-Feng

2015-01-01

Background: Inflammation plays an important role in cancer progression and prognosis. However, the prognostic values of inflammatory biomarkers in esophageal cancer (EC) were not established. In the present study, therefore, we initially used a nomogram to predict prognostic values of various inflammatory biomarkers in patients with esophageal squamous cell carcinoma (ESCC). Methods: A total of 326 ESCC patients were included in this retrospective study. Glasgow prognostic score (GPS), neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR) and lymphocyte monocyte ratio (LMR) were analyzed in the current study. Kaplan-Meier method was used to calculate the cancer-specific survival (CSS). Cox regression analysis was also performed to evaluate the prognostic factors. A nomogram was established to predict the prognosis for CSS. Results: Patients were divided into 3 groups according to GPS (GPS 0, 1 and 2) and 2 groups according to NLR (≤3.45 and >3.45), PLR (≤166.5 and >166.5) and LMR (≤2.30 and >2.30). The 5-year CSS in patients with GPS 0, 1 and 2 were 49.2%, 26.8% and 11.9%, respectively (P<0.001). In addition, patients with NLR (>3.45), PLR (>166.5) and LMR (≤2.30) were significantly associated with decreased CSS, respectively (P<0.001). Multivariate analysis revealed that GPS (P<0.001), PLR (P=0.002) and LMR (P=0.002) were independent prognostic factors in patients with ESCC. In addition, a nomogram was established according to all significantly independent factors for CSS. The Harrell’s c-index for CSS prediction was 0.72. Conclusion: GPS, PLR and LMR were potential prognostic biomarkers in patients with ESCC. The nomogram based on CSS could be used as an accurately prognostic prediction for patients with ESCC. PMID:26328248

Expression and prognostic examination of heat shock proteins (HSP 27, HSP 70, and HSP 90) in medulloblastoma.

PubMed

Hauser, Péter; Hanzély, Zoltán; Jakab, Zsuzsanna; Oláh, Lászlóné; Szabó, Erika; Jeney, András; Schuler, Dezso; Fekete, Gyoörgy; Bognár, László; Garami, Miklós

2006-07-01

Expression of heat shock proteins (HSPs) is of prognostic significance in several tumor types. HSP expression levels were determined in medulloblastomas and tested whether HSPs expression was associated with prognostic parameters. Expression of antiapoptotic HSP 27, HSP 70, and HSP 90 was investigated by immunohistochemistry, on paraffin-embedded sections from 65 patients. Expression of HSPs was validated on internal vascular controls and by Western blotting analysis. Sample evaluation was based on the estimated percentage of HSP positive tumor cells. For survival analysis Kaplan-Meier method, for statistical analysis chi2 test, univariate analysis, and log rank test were applied. Expression of HSPs varied in medulloblastomas. On the basis of the average expression rate of HSPs, at HSP 27 and HSP 90 with a 10% cut off, and at HSP 70 with a 70% cut off 2 groups were created. The amount of expression of any of the HSP types was not significantly associated with known prognostic factors (age of patient, extent of resection, presence of metastasis) and histologic subtype. After an average follow-up period of 4.30 years, no significant difference was observed in survival depending on the expression of HSP 27 or HSP 70 or HSP 90. The high expression of HSPs indicates that these proteins are potential therapeutic targets.

Prognostics of Power MOSFET

NASA Technical Reports Server (NTRS)

Celaya, Jose Ramon; Saxena, Abhinav; Vashchenko, Vladislay; Saha, Sankalita; Goebel, Kai Frank

2011-01-01

This paper demonstrates how to apply prognostics to power MOSFETs (metal oxide field effect transistor). The methodology uses thermal cycling to age devices and Gaussian process regression to perform prognostics. The approach is validated with experiments on 100V power MOSFETs. The failure mechanism for the stress conditions is determined to be die-attachment degradation. Change in ON-state resistance is used as a precursor of failure due to its dependence on junction temperature. The experimental data is augmented with a finite element analysis simulation that is based on a two-transistor model. The simulation assists in the interpretation of the degradation phenomena and SOA (safe operation area) change.

Current status of accurate prognostic awareness in advanced/terminally ill cancer patients: Systematic review and meta-regression analysis.

PubMed

Chen, Chen Hsiu; Kuo, Su Ching; Tang, Siew Tzuh

2017-05-01

No systematic meta-analysis is available on the prevalence of cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. To examine the prevalence of advanced/terminal cancer patients' accurate prognostic awareness and differences in accurate prognostic awareness by publication year, region, assessment method, and service received. Systematic review and meta-analysis. MEDLINE, Embase, The Cochrane Library, CINAHL, and PsycINFO were systematically searched on accurate prognostic awareness in adult patients with advanced/terminal cancer (1990-2014). Pooled prevalences were calculated for accurate prognostic awareness by a random-effects model. Differences in weighted estimates of accurate prognostic awareness were compared by meta-regression. In total, 34 articles were retrieved for systematic review and meta-analysis. At best, only about half of advanced/terminal cancer patients accurately understood their prognosis (49.1%; 95% confidence interval: 42.7%-55.5%; range: 5.4%-85.7%). Accurate prognostic awareness was independent of service received and publication year, but highest in Australia, followed by East Asia, North America, and southern Europe and the United Kingdom (67.7%, 60.7%, 52.8%, and 36.0%, respectively; p = 0.019). Accurate prognostic awareness was higher by clinician assessment than by patient report (63.2% vs 44.5%, p < 0.001). Less than half of advanced/terminal cancer patients accurately understood their prognosis, with significant variations by region and assessment method. Healthcare professionals should thoroughly assess advanced/terminal cancer patients' preferences for prognostic information and engage them in prognostic discussion early in the cancer trajectory, thus facilitating their accurate prognostic awareness and the quality of end-of-life care decision-making.

Direct optimization, affine gap costs, and node stability.

PubMed

Aagesen, Lone

2005-09-01

The outcome of a phylogenetic analysis based on DNA sequence data is highly dependent on the homology-assignment step and may vary with alignment parameter costs. Robustness to changes in parameter costs is therefore a desired quality of a data set because the final conclusions will be less dependent on selecting a precise optimal cost set. Here, node stability is explored in relationship to separate versus combined analysis in three different data sets, all including several data partitions. Robustness to changes in cost sets is measured as number of successive changes that can be made in a given cost set before a specific clade is lost. The changes are in all cases base change cost, gap penalties, and adding/removing/changing affine gap costs. When combining data partitions, the number of clades that appear in the entire parameter space is not remarkably increased, in some cases this number even decreased. However, when combining data partitions the trees from cost sets including affine gap costs were always more similar than the trees were from cost sets without affine gap costs. This was not the case when the data partitions were analyzed independently. When data sets were combined approximately 80% of the clades found under cost sets including affine gap costs resisted at least one change to the cost set.

Improving the representation of mixed-phase cloud microphysics in the ICON-LEM

NASA Astrophysics Data System (ADS)

Tonttila, Juha; Hoose, Corinna; Milbrandt, Jason; Morrison, Hugh

2017-04-01

The representation of ice-phase cloud microphysics in ICON-LEM (the Large-Eddy Model configuration of the ICOsahedral Nonhydrostatic model) is improved by implementing the recently published Predicted Particle Properties (P3) scheme into the model. In the typical two-moment microphysical schemes, such as that previously used in ICON-LEM, ice-phase particles must be partitioned into several prescribed categories. It is inherently difficult to distinguish between categories such as graupel and hail based on just the particle size, yet this partitioning may significantly affect the simulation of convective clouds. The P3 scheme avoids the problems associated with predefined ice-phase categories that are inherent in traditional microphysics schemes by introducing the concept of "free" ice-phase categories, whereby the prognostic variables enable the prediction of a wide range of smoothly varying physical properties and hence particle types. To our knowledge, this is the first application of the P3 scheme in a large-eddy model with horizontal grid spacings on the order of 100 m. We will present results from ICON-LEM simulations with the new P3 scheme comprising idealized stratiform and convective cloud cases. We will also present real-case limited-area simulations focusing on the HOPE (HD(CP)2 Observational Prototype Experiment) intensive observation campaign. The results are compared with a matching set of simulations employing the two-moment scheme and the performance of the model is also evaluated against observations in the context of the HOPE simulations, comprising data from ground based remote sensing instruments.

A new biologic prognostic model based on immunohistochemistry predicts survival in patients with diffuse large B-cell lymphoma.

PubMed

Perry, Anamarija M; Cardesa-Salzmann, Teresa M; Meyer, Paul N; Colomo, Luis; Smith, Lynette M; Fu, Kai; Greiner, Timothy C; Delabie, Jan; Gascoyne, Randy D; Rimsza, Lisa; Jaffe, Elaine S; Ott, German; Rosenwald, Andreas; Braziel, Rita M; Tubbs, Raymond; Cook, James R; Staudt, Louis M; Connors, Joseph M; Sehn, Laurie H; Vose, Julie M; López-Guillermo, Armando; Campo, Elias; Chan, Wing C; Weisenburger, Dennis D

2012-09-13

Biologic factors that predict the survival of patients with a diffuse large B-cell lymphoma, such as cell of origin and stromal signatures, have been discovered by gene expression profiling. We attempted to simulate these gene expression profiling findings and create a new biologic prognostic model based on immunohistochemistry. We studied 199 patients (125 in the training set, 74 in the validation set) with de novo diffuse large B-cell lymphoma treated with rituximab and CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) or CHOP-like therapies, and immunohistochemical stains were performed on paraffin-embedded tissue microarrays. In the model, 1 point was awarded for each adverse prognostic factor: nongerminal center B cell-like subtype, SPARC (secreted protein, acidic, and rich in cysteine) < 5%, and microvascular density quartile 4. The model using these 3 biologic markers was highly predictive of overall survival and event-free survival in multivariate analysis after adjusting for the International Prognostic Index in both the training and validation sets. This new model delineates 2 groups of patients, 1 with a low biologic score (0-1) and good survival and the other with a high score (2-3) and poor survival. This new biologic prognostic model could be used with the International Prognostic Index to stratify patients for novel or risk-adapted therapies.

Prognostic value of Child-Turcotte criteria in medically treated cirrhosis.

PubMed

Christensen, E; Schlichting, P; Fauerholdt, L; Gluud, C; Andersen, P K; Juhl, E; Poulsen, H; Tygstrup, N

1984-01-01

The Child- Turcotte criteria (CTC) (based on serum bilirubin and albumin, ascites, neurological disorder and nutrition) are established prognostic factors in patients with cirrhosis having portacaval shunt surgery. The objective of this study was to evaluate the prognostic value of CTC in conservatively treated cirrhosis. Patients (n = 245) with histologically verified cirrhosis from a control group of a controlled clinical trial were studied. Data at entry into the trial were used to classify patients according to CTC. Survival curves for up to 16 years were made, and survival rates were compared using the log-rank test. Survival decreased significantly with increasing degree of abnormality (A----B----C) of albumin (p less than 0.001), ascites (p less than 0.001), bilirubin (p = 0.02) and nutritional status (p = 0.03). Survival was insignificantly influenced by neurological status (p = 0.11) probably because none of the patients had hepatic coma at entry into the trial. The five variables in CTC were combined to a score. With increasing score, the median survival time decreased from 6.4 years (score 5) to 2 months (scores 12 or more). Furthermore, the mortality from hepatic failure, gastrointestinal bleeding or hepatocellular carcinoma increased significantly with increasing score. CTC provide valuable and easily obtainable prognostic information in cirrhosis. However, CTC are inferior to a prognostic index based on multivariate analysis of prognostic factors.

[The diagnostic value of microsatellite LOH analysis and the prognostic relevance of angiogenic gene expression in urinary bladder cancer].

PubMed

Szarvas, Tibor

2009-12-01

Bladder cancer is the second most common malignancy affecting the urinary system. Currently, histology is the only tool that determines therapy and patients' prognosis. As the treatment of non-invasive (Ta/T1) and muscle invasive (T2-T4) bladder tumors are completely different, correct staging is important, although it is often hampered by disturbing factors. Molecular methods offer new prospects for early disease detection, confirmation of unclear histological findings and prognostication. Applying molecular biological methods, the present study is searching for answers to current diagnostic and prognostic problems in bladder carcinoma. We analyzed tumor, blood and/or urine samples of 334 bladder cancer patients and 117 control individuals. Genetic alterations were analyzed in urine samples of patients and controls, both by PCR-based microsatellite loss of heterozigosity (LOH) analysis using 12 fluorescently labeled primers and by DNA hybridization based UroVysion FISH technique using 4 probes, to assess the diagnostic values of these methods. Whole genome microsatellite analysis (with 400 markers) was performed in tumor and blood specimens of bladder cancer patients to find chromosomal regions, the loss of which may be associated with tumor stage. Furthermore, we assessed the prognostic value of Tie2, VEGF, Angiopoietin-1 and -2. We concluded that DNA analysis of voided urine samples by microsatellite analysis and FISH are sensitive and non-invasive methods to detect bladder cancer. Furthermore, we established a panel of microsatellite markers that could differentiate between non-invasive and invasive bladder cancer. However, further analyses in a larger cohort of patients are needed to assess their specificity and sensitivity. Finally, we identified high Ang-2 and low Tie2 gene expression as significant and independent risk factors of tumor recurrence and cancer related survival.

Implications of prognostic factors and risk groups in the management of differentiated thyroid cancer.

PubMed

Shaha, Ashok R

2004-03-01

The outcome in differentiated thyroid cancer generally depends on the stage of the disease at the time of presentation; prognostic factors such as age, grade, size, extension, or distant metastasis; and risk groups (eg, low or high risk). The author has reviewed a large number of patients with differentiated thyroid cancer to analyze their hypothesis and to confirm that various risk groups have a major implication in relation to extent of the treatment and outcome. Differentiated thyroid cancers make up 90% of all thyroid tumors. The prognostic factors are well defined, such as age, size of the tumor, extrathyroidal extension, presence of distant metastasis, histological appearance, and grade of the tumor. The author has previously divided the risk groups into low-, intermediate-, and high-risk categories based on prognostic factors. The study describes the author's treatment approach related to the extent of thyroidectomy and adjuvant therapy based on various risk groups and the long-term survival. Retrospective. In a retrospective review of 1038 patients with differentiated thyroid carcinoma, various prognostic factors were studied by univariate and multivariate analysis. The significant prognostic factors were studied in detail and, based on these prognostic factors, the patients were divided into low-, intermediate- and high-risk groups. The survival curves were plotted by Kaplan-Meier method. The long-term survivals in low-, intermediate- and high-risk groups were 99%, 87%, and 57% respectively. Based on these risk groups, a decision tree was made regarding extent of thyroidectomy and adjuvant treatment. In the high-risk group and selected patients in the intermediate-risk group, aggressive surgery including removal of all gross disease and extrathyroidal extension with postoperative radioactive iodine ablation is recommended. In the low-risk group and selected patients in the intermediate-risk group, lobectomy appears to be satisfactory with excellent long-term outcome. The surgical treatment offers the best long-term results in low-risk patients, and the role of adjuvant treatment in this group is questionable. The decisions in the management of well-differentiated thyroid cancer should be based on various prognostic factors and risk groups. The long-term survival in the low-risk group is excellent, and consideration should be given to conservative surgical resection depending on the extent of the disease. In the high-risk group and selected patients in the intermediate-risk group, total thyroidectomy with radioactive ablation is warranted. A consideration may be given to external-beam radiation therapy in selected high-risk patients. It is apparent, based on the author's clinical experience and critical retrospective analysis, that the author's hypothesis that risk groups are extremely important in the long-term outcome of patients with differentiated thyroid cancer is correct. Based on various risk groups, the author currently is able to guide the treatment policies for thyroid cancer.

A prognostic index for natural killer cell lymphoma after non-anthracycline-based treatment: a multicentre, retrospective analysis.

PubMed

Kim, Seok Jin; Yoon, Dok Hyun; Jaccard, Arnaud; Chng, Wee Joo; Lim, Soon Thye; Hong, Huangming; Park, Yong; Chang, Kian Meng; Maeda, Yoshinobu; Ishida, Fumihiro; Shin, Dong-Yeop; Kim, Jin Seok; Jeong, Seong Hyun; Yang, Deok-Hwan; Jo, Jae-Cheol; Lee, Gyeong-Won; Choi, Chul Won; Lee, Won-Sik; Chen, Tsai-Yun; Kim, Kiyeun; Jung, Sin-Ho; Murayama, Tohru; Oki, Yasuhiro; Advani, Ranjana; d'Amore, Francesco; Schmitz, Norbert; Suh, Cheolwon; Suzuki, Ritsuro; Kwong, Yok Lam; Lin, Tong-Yu; Kim, Won Seog

2016-03-01

The clinical outcome of extranodal natural killer T-cell lymphoma (ENKTL) has improved substantially as a result of new treatment strategies with non-anthracycline-based chemotherapies and upfront use of concurrent chemoradiotherapy or radiotherapy. A new prognostic model based on the outcomes obtained with these contemporary treatments was warranted. We did a retrospective study of patients with newly diagnosed ENKTL without any previous treatment history for the disease who were given non-anthracycline-based chemotherapies with or without upfront concurrent chemoradiotherapy or radiotherapy with curative intent. A prognostic model to predict overall survival and progression-free survival on the basis of pretreatment clinical and laboratory characteristics was developed by filling a multivariable model on the basis of the dataset with complete data for the selected risk factors for an unbiased prediction model. The final model was applied to the patients who had complete data for the selected risk factors. We did a validation analysis of the prognostic model in an independent cohort. We did multivariate analyses of 527 patients who were included from 38 hospitals in 11 countries in the training cohort. Analyses showed that age greater than 60 years, stage III or IV disease, distant lymph-node involvement, and non-nasal type disease were significantly associated with overall survival and progression-free survival. We used these data as the basis for the prognostic index of natural killer lymphoma (PINK), in which patients are stratified into low-risk (no risk factors), intermediate-risk (one risk factor), or high-risk (two or more risk factors) groups, which were associated with 3-year overall survival of 81% (95% CI 75-86), 62% (55-70), and 25% (20-34), respectively. In the 328 patients with data for Epstein-Barr virus DNA, a detectable viral DNA titre was an independent prognostic factor for overall survival. When these data were added to PINK as the basis for another prognostic index (PINK-E)-which had similar low-risk (zero or one risk factor), intermediate-risk (two risk factors), and high-risk (three or more risk factors) categories-significant associations with overall survival were noted (81% [95% CI 75-87%], 55% (44-66), and 28% (18-40%), respectively). These results were validated and confirmed in an independent cohort, although the PINK-E model was only significantly associated with the high-risk group compared with the low-risk group. PINK and PINK-E are new prognostic models that can be used to develop risk-adapted treatment approaches for patients with ENKTL being treated in the contemporary era of non-anthracycline-based therapy. Samsung Biomedical Research Institute. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

Liu, Bangjian; Huang, Yujing; Sun, Yuanjue; Zhang, Jianjun; Yao, Yang; Shen, Zan; Xiang, Dongxi; He, Aina

2016-01-01

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients. PMID:28008988

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castle, Katherine O., E-mail: kocastle@mdanderson.org; Hoffman, Karen E.; Levy, Lawrence B.

Purpose: The benefit of adding androgen deprivation therapy (ADT) to dose-escalated radiation therapy (RT) for men with intermediate-risk prostate cancer is unclear; therefore, we assessed the impact of adding ADT to dose-escalated RT on freedom from failure (FFF). Methods: Three groups of men treated with intensity modulated RT or 3-dimensional conformal RT (75.6-78 Gy) from 1993-2008 for prostate cancer were categorized as (1) 326 intermediate-risk patients treated with RT alone, (2) 218 intermediate-risk patients treated with RT and ≤6 months of ADT, and (3) 274 low-risk patients treated with definitive RT. Median follow-up was 58 months. Recursive partitioning analysis basedmore » on FFF using Gleason score (GS), T stage, and pretreatment PSA concentration was applied to the intermediate-risk patients treated with RT alone. The Kaplan-Meier method was used to estimate 5-year FFF. Results: Based on recursive partitioning analysis, intermediate-risk patients treated with RT alone were divided into 3 prognostic groups: (1) 188 favorable patients: GS 6, ≤T2b or GS 3+4, ≤T1c; (2) 71 marginal patients: GS 3+4, T2a-b; and (3) 68 unfavorable patients: GS 4+3 or T2c disease. Hazard ratios (HR) for recurrence in each group were 1.0, 2.1, and 4.6, respectively. When intermediate-risk patients treated with RT alone were compared to intermediate-risk patients treated with RT and ADT, the greatest benefit from ADT was seen for the unfavorable intermediate-risk patients (FFF, 74% vs 94%, respectively; P=.005). Favorable intermediate-risk patients had no significant benefit from the addition of ADT to RT (FFF, 94% vs 95%, respectively; P=.85), and FFF for favorable intermediate-risk patients treated with RT alone approached that of low-risk patients treated with RT alone (98%). Conclusions: Patients with favorable intermediate-risk prostate cancer did not benefit from the addition of ADT to dose-escalated RT, and their FFF was nearly as good as patients with low-risk disease. In patients with GS 4+3 or T2c disease, the addition of ADT to dose-escalated RT did improve FFF.« less

Prognostic molecular markers with no impact on decision-making: the paradox of gliomas based on a prospective study.

PubMed

Wager, M; Menei, P; Guilhot, J; Levillain, P; Michalak, S; Bataille, B; Blanc, J-L; Lapierre, F; Rigoard, P; Milin, S; Duthe, F; Bonneau, D; Larsen, C-J; Karayan-Tapon, L

2008-06-03

This study assessed the prognostic value of several markers involved in gliomagenesis, and compared it with that of other clinical and imaging markers already used. Four-hundred and sixteen adult patients with newly diagnosed glioma were included over a 3-year period and tumour suppressor genes, oncogenes, MGMT and hTERT expressions, losses of heterozygosity, as well as relevant clinical and imaging information were recorded. This prospective study was based on all adult gliomas. Analyses were performed on patient groups selected according to World Health Organization histoprognostic criteria and on the entire cohort. The endpoint was overall survival, estimated by the Kaplan-Meier method. Univariate analysis was followed by multivariate analysis according to a Cox model. p14(ARF), p16(INK4A) and PTEN expressions, and 10p 10q23, 10q26 and 13q LOH for the entire cohort, hTERT expression for high-grade tumours, EGFR for glioblastomas, 10q26 LOH for grade III tumours and anaplastic oligodendrogliomas were found to be correlated with overall survival on univariate analysis and age and grade on multivariate analysis only. This study confirms the prognostic value of several markers. However, the scattering of the values explained by tumour heterogeneity prevents their use in individual decision-making.

On the Prognostic Efficiency of Topological Descriptors for Magnetograms of Active Regions

NASA Astrophysics Data System (ADS)

Knyazeva, I. S.; Urtiev, F. A.; Makarenko, N. G.

2017-12-01

Solar flare prediction remains an important practical task of space weather. An increase in the amount and quality of observational data and the development of machine-learning methods has led to an improvement in prediction techniques. Additional information has been retrieved from the vector magnetograms; these have been recently supplemented by traditional line-of-sight (LOS) magnetograms. In this work, the problem of the comparative prognostic efficiency of features obtained on the basis of vector data and LOS magnetograms is discussed. Invariants obtained from a topological analysis of LOS magnetograms are used as complexity characteristics of magnetic patterns. Alternatively, the so-called SHARP parameters were used; they were calculated by the data analysis group of the Stanford University Laboratory on the basis of HMI/SDO vector magnetograms and are available online at the website (http://jsoc.stanford.edu/) with the solar dynamics observatory (SDO) database for the entire history of SDO observations. It has been found that the efficiency of large-flare prediction based on topological descriptors of LOS magnetograms in epignosis mode is at least s no worse than the results of prognostic schemes based on vector features. The advantages of the use of topological invariants based on LOS data are discussed.

Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection.

PubMed

Van Steen, Kristel; Curran, Desmond; Kramer, Jocelyn; Molenberghs, Geert; Van Vreckem, Ann; Bottomley, Andrew; Sylvester, Richard

2002-12-30

Clinical and quality of life (QL) variables from an EORTC clinical trial of first line chemotherapy in advanced breast cancer were used in a prognostic factor analysis of survival and response to chemotherapy. For response, different final multivariate models were obtained from forward and backward selection methods, suggesting a disconcerting instability. Quality of life was measured using the EORTC QLQ-C30 questionnaire completed by patients. Subscales on the questionnaire are known to be highly correlated, and therefore it was hypothesized that multicollinearity contributed to model instability. A correlation matrix indicated that global QL was highly correlated with 7 out of 11 variables. In a first attempt to explore multicollinearity, we used global QL as dependent variable in a regression model with other QL subscales as predictors. Afterwards, standard diagnostic tests for multicollinearity were performed. An exploratory principal components analysis and factor analysis of the QL subscales identified at most three important components and indicated that inclusion of global QL made minimal difference to the loadings on each component, suggesting that it is redundant in the model. In a second approach, we advocate a bootstrap technique to assess the stability of the models. Based on these analyses and since global QL exacerbates problems of multicollinearity, we therefore recommend that global QL be excluded from prognostic factor analyses using the QLQ-C30. The prognostic factor analysis was rerun without global QL in the model, and selected the same significant prognostic factors as before. Copyright 2002 John Wiley & Sons, Ltd.

Prognostic value of bone marrow involvement by clonal immunoglobulin gene rearrangements in follicular lymphoma

PubMed Central

Berget, Ellen; Helgeland, Lars; Liseth, Knut; Løkeland, Turid; Molven, Anders; Vintermyr, Olav Karsten

2014-01-01

Aims We aimed to evaluate the prognostic value of routine use of PCR amplification of immunoglobulin gene rearrangements in bone marrow (BM) staging in patients with follicular lymphoma (FL). Methods Clonal rearrangements were assessed by immunoglobulin heavy and light-chain gene rearrangement analysis in BM aspirates from 96 patients diagnosed with FL and related to morphological detection of BM involvement in biopsies. In 71 patients, results were also compared with concurrent flow cytometry analysis. Results BM involvement was detected by PCR in 34.4% (33/96) of patients. The presence of clonal rearrangements by PCR was associated with advanced clinical stage (I–III vs IV; p<0.001), high FL International Prognostic Index (FLIPI) score (0–1, 2 vs ≥3; p=0.003), and detection of BM involvement by morphology and flow cytometry analysis (p<0.001 for both). PCR-positive patients had a significantly poorer survival than PCR-negative patients (p=0.001, log-rank test). Thirteen patients positive by PCR but without morphologically detectable BM involvement, had significantly poorer survival than patients with negative morphology and negative PCR result (p=0.002). The poor survival associated with BM involvement by PCR was independent of the FLIPI score (p=0.007, Cox regression). BM involvement by morphology or flow cytometry did not show a significant impact on survival. Conclusions Our results showed that routine use of PCR-based clonality analysis significantly improved the prognostic impact of BM staging in patients with FL. BM involvement by PCR was also an independent adverse prognostic factor. PMID:25233852

Evaluating biomarkers for prognostic enrichment of clinical trials.

PubMed

Kerr, Kathleen F; Roth, Jeremy; Zhu, Kehao; Thiessen-Philbrook, Heather; Meisner, Allison; Wilson, Francis Perry; Coca, Steven; Parikh, Chirag R

2017-12-01

A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

The Deformation Behavior Analysis and Mechanical Modeling of Step/Intercritical Quenching and Partitioning-Treated Multiphase Steels

NASA Astrophysics Data System (ADS)

Zhao, Hongshan; Li, Wei; Wang, Li; Zhou, Shu; Jin, Xuejun

2016-08-01

T wo types of multiphase steels containing blocky or fine martensite have been used to study the phase interaction and the TRIP effect. These steels were obtained by step-quenching and partitioning (S-QP820) or intercritical-quenching and partitioning (I-QP800 & I-QP820). The retained austenite (RA) in S-QP820 specimen containing blocky martensite transformed too early to prevent the local failure at high strain due to the local strain concentration. In contrast, plentiful RA in I-QP800 specimen containing finely dispersed martensite transformed uniformly at high strain, which led to optimized strength and elongation. By applying a coordinate conversion method to the microhardness test, the load partitioning between ferrite and partitioned martensite was proved to follow the linear mixture law. The mechanical behavior of multiphase S-QP820 steel can be modeled based on the Mecking-Kocks theory, Bouquerel's spherical assumption, and Gladman-type mixture law. Finally, the transformation-induced martensite hardening effect has been studied on a bake-hardened specimen.

Inference and Analysis of Population Structure Using Genetic Data and Network Theory

PubMed Central

Greenbaum, Gili; Templeton, Alan R.; Bar-David, Shirli

2016-01-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition’s modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). PMID:26888080

[Problem of bioterrorism under modern conditions].

PubMed

Vorob'ev, A A; Boev, B V; Bondarenko, V M; Gintsburg, A L

2002-01-01

It is practically impossible to discuss the problem of bioterrorism (BT) and to develop effective programs of decreasing the losses and expenses suffered by the society from the BT acts without evaluation of the threat and prognosis of consequences based on research and empiric data. Stained international situation following the act of terrorism (attack on the USA) on September 11, 2001, makes the scenarios of the bacterial weapon use (the causative agents of plague, smallpox, anthrax, etc.) by international terrorists most probable. In this connection studies on the analysis and prognostication of the consequences of BT, including mathematical and computer modelling, are necessary. The authors present the results of initiative studies on the analysis and prognostication of the consequences of the hypothetical act of BT with the use of the smallpox causative agent in a city with the population of about 1,000,000 inhabitants. The analytical prognostic studies on the operative analysis and prognostication of the consequences of the BT act with the use of the smallpox causative agent has demonstrated that the mathematical (computer) model of the epidemic outbreak of smallpox is an effective instrument of calculation studies. Prognostic evaluations of the consequences of the act of BT under the conditions of different reaction of public health services (time of detection, interventions) have been obtained with the use of modelling. In addition, the computer model is necessary for training health specialists to react adequately to the acts of BT with the use of different kinds of bacteriological weapons.

Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

PubMed

Rakha, E A; Soria, D; Green, A R; Lemetre, C; Powe, D G; Nolan, C C; Garibaldi, J M; Ball, G; Ellis, I O

2014-04-02

Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. In this study, we hypothesised that molecular features of BC are a key driver of tumour behaviour and when coupled with a novel and bespoke application of established clinicopathologic prognostic variables can predict both clinical outcome and relevant therapeutic options more accurately than existing methods. In the current study, a comprehensive panel of biomarkers with relevance to BC was applied to a large and well-characterised series of BC, using immunohistochemistry and different multivariate clustering techniques, to identify the key molecular classes. Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). The NPI+ was then used to predict outcome in the different molecular classes. Seven core molecular classes were identified using a selective panel of 10 biomarkers. Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Outcome analysis showed that using the bespoke NPI formulae for each biological BC class provides improved patient outcome stratification superior to the traditional NPI. This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.

Mechanisms and Therapy for Cancer Metastasis to the Brain.

PubMed

Franchino, Federica; Rudà, Roberta; Soffietti, Riccardo

2018-01-01

Advances in chemotherapy and targeted therapies have improved survival in cancer patients with an increase of the incidence of newly diagnosed brain metastases (BMs). Intracranial metastases are symptomatic in 60-70% of patients. Magnetic resonance imaging (MRI) with gadolinium is more sensitive than computed tomography and advanced neuroimaging techniques have been increasingly used in the detection, treatment planning, and follow-up of BM. Apart from the morphological analysis, the most effective tool for characterizing BM is immunohistochemistry. Molecular alterations not always reflect those of the primary tumor. More sophisticated methods of tumor analysis detecting circulating biomarkers in fluids (liquid biopsy), including circulating DNA, circulating tumor cells, and extracellular vesicles, containing tumor DNA and macromolecules (microRNA), have shown promise regarding tumor treatment response and progression. The choice of therapeutic approaches is guided by prognostic scores (Recursive Partitioning Analysis and diagnostic-specific Graded Prognostic Assessment-DS-GPA). The survival benefit of surgical resection seems limited to the subgroup of patients with controlled systemic disease and good performance status. Leptomeningeal disease (LMD) can be a complication, especially in posterior fossa metastases undergoing a "piecemeal" resection. Radiosurgery of the resection cavity may offer comparable survival and local control as postoperative whole-brain radiotherapy (WBRT). WBRT alone is now the treatment of choice only for patients with single or multiple BMs not amenable to surgery or radiosurgery, or with poor prognostic factors. To reduce the neurocognitive sequelae of WBRT intensity modulated radiotherapy with hippocampal sparing, and pharmacological approaches (memantine and donepezil) have been investigated. In the last decade, a multitude of molecular abnormalities have been discovered. Approximately 33% of patients with non-small cell lung cancer (NSCLC) tumors and epidermal growth factor receptor mutations develop BMs, which are targetable with different generations of tyrosine kinase inhibitors (TKIs: gefitinib, erlotinib, afatinib, icotinib, and osimertinib). Other "druggable" alterations seen in up to 5% of NSCLC patients are the rearrangements of the "anaplastic lymphoma kinase" gene TKI (crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib). In human epidermal growth factor receptor 2-positive, breast cancer targeted therapies have been widely used (trastuzumab, trastuzumab-emtansine, lapatinib-capecitabine, and neratinib). Novel targeted and immunotherapeutic agents have also revolutionized the systemic management of melanoma (ipilimumab, nivolumab, pembrolizumab, and BRAF inhibitors dabrafenib and vemurafenib).

Prognostic factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia: a systematic review and meta-analysis.

PubMed

Lee, Yee Mei; Lang, Dora; Lockwood, Craig

Increasing numbers of studies identify new prognostic factors for categorising chemotherapy-induced febrile neutropenia adult cancer patients into high- or low-risk groups for adverse outcomes. These groupings are used to tailor therapy according to level of risk. However many emerging factors with prognostic significance remain controversial, being based on single studies only. A systematic review was conducted to determine the strength of association of all identified factors associated with the outcomes of chemotherapy-induced febrile neutropenia patients. The participants included were adults of 15 years old and above, with a cancer diagnosis and who underwent cancer treatment.The review focused on clinical factors and their association with the outcomes of cancer patients with chemotherapy-induced febrile neutropenia at presentation of fever.All quantitative studies published in English which investigated clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia were considered.The primary outcome of interest was to identify the clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia. Electronic databases searched from their respective inception date up to December 2011 include MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Science-Direct, Scopus and Mednar. The quality of the included studies was subjected to assessment by two independent reviewers. The standardised critical appraisal tool from the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) was used to assess the following criteria: representativeness of study population; clearly defined prognostic factors and outcomes; whether potential confounders were addressed and appropriate statistical analysis was undertaken for the study design. Data extraction was performed using a modified version of the standardised extraction tool from the JBI-MAStARI. Prognostic factors and the accompanying odds ratio reported for the significance of these factors that were identified by multivariate regression, were extracted from each included study. Studies results were pooled in statistical meta-analysis using Review Manager 5.1. Where statistical pooling was not possible, the findings were presented in narrative form. Seven studies (four prospective cohort and three retrospective cohort) investigating 22 factors in total were included. Fixed effects meta-analysis showed: hypotension [OR=1.66, 95%CI, 1.14-2.41, p=0.008] and thrombocytopenia [OR=3.92, 95%CI, 2.19-7.01, p<0.00001)] were associated with high-risk of adverse outcomes for febrile neutropenia. Other factors that were statistically significant from single studies included: age of patients, clinical presentation at fever onset, presence or absence of co-morbidities, infections, duration and severity of neutropenia state. Five prognostic factors failed to demonstrate an association between the variables and the outcomes measured and they include: presence of pneumonia, total febrile days, median days to fever, recovery from neutropenia and presence of moderate clinical symptoms in association with Gram-negative bacteraemia. Despite the overall limitations identified in the included studies, this review has provided a synthesis of the best available evidence for the prognostic factors used in risk stratification of febrile neutropenia patients. However, the dynamic aspects of prognostic model development, validation and utilisation have not been addressed adequately thus far. Given the findings of this review, it is timely to address these issues and improve the utilisation of prognostic models in the management of febrile neutropenia patients. The identified factors are similar to the factors in current prognostic models. However, additional factors that were reported to be statistically significant in this review (thrombocytopenia, presence of central venous catheter, and duration and severity of neutropenia) have not previously been included in prognostic models. This review has found these factors may improve the performance of current models by adding or replacing some of the factors. The role of risk stratification of chemotherapy-induced febrile neutropenia patients continues to evolve as the practice of risk-based therapy has been demonstrated to be beneficial to patients, clinicians and health care organisations. Further research to identify new factors /markers is needed to develop a new model which is reliable and accurate for these patients, regardless of cancer types. A robust and well-validated prognostic model is the key to enhance patient safety in the risk-based management of cancer patients with chemotherapy-induced febrile neutropenia.

Multivariate meta-analysis of prognostic factor studies with multiple cut-points and/or methods of measurement.

PubMed

Riley, Richard D; Elia, Eleni G; Malin, Gemma; Hemming, Karla; Price, Malcolm P

2015-07-30

A prognostic factor is any measure that is associated with the risk of future health outcomes in those with existing disease. Often, the prognostic ability of a factor is evaluated in multiple studies. However, meta-analysis is difficult because primary studies often use different methods of measurement and/or different cut-points to dichotomise continuous factors into 'high' and 'low' groups; selective reporting is also common. We illustrate how multivariate random effects meta-analysis models can accommodate multiple prognostic effect estimates from the same study, relating to multiple cut-points and/or methods of measurement. The models account for within-study and between-study correlations, which utilises more information and reduces the impact of unreported cut-points and/or measurement methods in some studies. The applicability of the approach is improved with individual participant data and by assuming a functional relationship between prognostic effect and cut-point to reduce the number of unknown parameters. The models provide important inferential results for each cut-point and method of measurement, including the summary prognostic effect, the between-study variance and a 95% prediction interval for the prognostic effect in new populations. Two applications are presented. The first reveals that, in a multivariate meta-analysis using published results, the Apgar score is prognostic of neonatal mortality but effect sizes are smaller at most cut-points than previously thought. In the second, a multivariate meta-analysis of two methods of measurement provides weak evidence that microvessel density is prognostic of mortality in lung cancer, even when individual participant data are available so that a continuous prognostic trend is examined (rather than cut-points). © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

A Danish population-based analysis of 105 mantle cell lymphoma patients: incidences, clinical features, response, survival and prognostic factors.

PubMed

Andersen, N S; Jensen, M K; de Nully Brown, P; Geisler, C H

2002-02-01

This study presents the first large clinical analysis of 105 unselected mantle cell lymphoma (MCL) patients diagnosed from 1992 to 2000 in a well-defined Danish population. The annual incidences were 0.7/100000 for men and 0.2/100000 for women, with no significant change during the study period. Of 97 evaluable cases, 43% achieved a complete response (CR) after initial therapy. The median disease-free (DFS) and overall survival (OS) rates were 15 and 30 months, respectively. In multivariate analysis, splenomegaly (P=0.002), anaemia (P=0.0001) and age (P=0.002), but not the international prognostic index (IPI) and the Ann Arbor staging system, had an independent impact on survival. Moreover, in a sub-analysis of 45 younger MCL patients (<65 years), a trend towards an OS plateau of 58% was observed in cases without splenomegaly and anaemia (n=29). Thus, in contrast to previously suggested prognostic factors, these variables may prove useful for clinical decisions in a significant subset of MCL patients.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

NASA Technical Reports Server (NTRS)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Integrated analysis of DNA methylation, immunohistochemistry and mRNA expression, data identifies a Methylation Expression Index (MEI) robustly associated with survival of ER-positive breast cancer patients

PubMed Central

Garcia-Closas, Montserrat; Davis, Sean; Meltzer, Paul; Lissowska, Jolanta; Horne, Hisani N.; Sherman, Mark E.; Lee, Maxwell

2015-01-01

Identification of prognostic gene expression signatures may enable improved decisions about management of breast cancer. To identify a prognostic signature for breast cancer, we performed DNA methylation profiling and identified methylation markers that were associated with expression of ER, PR, HER2, CK5/6 and EGFR proteins. Methylation markers that were correlated with corresponding mRNA expression levels were identified using 208 invasive tumors from a population-based case-control study conducted in Poland. Using this approach, we defined the Methylation Expression Index (MEI) signature that was based on a weighted sum of mRNA levels of 57 genes. Classification of cases as low or high MEI scores were related to survival using Cox regression models. In the Polish study, women with ER-positive low MEI cancers had reduced survival at a median of 5.20 years of follow-up, HR=2.85 95%CI=1.25-6.47. Low MEI was also related to decreased survival in four independent datasets totaling over 2500 ER-positive breast cancers. These results suggest that integrated analysis of tumor expression markers, DNA methylation, and mRNA data can be an important approach for identifying breast cancer prognostic signatures. Prospective assessment of MEI along with other prognostic signatures should be evaluated in future studies. PMID:25773928

Distributed Prognostic Health Management with Gaussian Process Regression

NASA Technical Reports Server (NTRS)

Saha, Sankalita; Saha, Bhaskar; Saxena, Abhinav; Goebel, Kai Frank

2010-01-01

Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. A major challenge encountered in such design is formulation of optimal distributed prognostics algorithms. In this paper. we present a distributed GPR based prognostics algorithm whose target platform is a wireless sensor network. In addition to challenges encountered in a distributed implementation, a wireless network poses constraints on communication patterns, thereby making the problem more challenging. The prognostics application that was used to demonstrate our new algorithms is battery prognostics. In order to present trade-offs within different prognostic approaches, we present comparison with the distributed implementation of a particle filter based prognostics for the same battery data.

Prognostic value of the pretreatment neutrophil-to-lymphocyte ratio in cervical cancer: a meta-analysis and systematic review.

PubMed

Wu, Jiayuan; Chen, Manyu; Liang, Caixia; Su, Wenmei

2017-02-21

The prognostic value of pretreatment neutrophil-to-lymphocyte ratio (NLR) in cervical cancer remains controversial. We conducted a meta-analysis based on the data from 13 studies with 3729 patients to evaluate the association between the pretreatment NLR and the clinical outcomes of overall survival and progression-free survival in patients with cervical cancer. The relationship between NLR and clinicopathological parameters was also assessed. Hazard ratio (HR) or odds ratio (OR) with its 95% confidence interval (CI) was used as the effect size estimate. Our analysis indicated that elevated pretreatment NLR was a poor prognostic marker for patients with cervical cancer because it predicted unfavorable overall survival (HR = 1.375, 95% CI: 1.200-1.576) and progression-free survival (HR = 1.646, 95% CI: 1.313-2.065). Increased NLR is also significantly associated with the larger tumor size (OR = 1.780, 95% CI: 1.090-2.908), advanced clinical stage (OR = 2.443, 95% CI: 1.730-3.451), and positive lymph node metastasis (OR = 2.380, 95% CI: 1.775-3.190). By these results, high pretreatment NLR predicted a shorter survival period for patients with cervical cancer, and it could be served as a novel index of prognostic evaluation in patients with cervical cancer.

Prognostic Factors for Recovery After Anterior Debridement/Bone Grafting and Posterior Instrumentation for Lumbar Spinal Tuberculosis.

PubMed

Yao, Yuan; Zhang, Huiyu; Liu, Huan; Zhang, Zhengfeng; Tang, Yu; Zhou, Yue

2017-08-01

Anterior debridement/bone grafting/posterior instrumentation is a common selection for the treatment of lumbar spinal tuberculosis (LST). To date, no study has focused on the prognostic factors for recovery after this surgery. We included 144 patients who experienced anterior debridement/bone grafting/posterior instrumentation for LST. The recovery rate based on the Japanese Orthopedic Association (JOA) score was used to assess recovery. The Kaplan-Meier method and Cox regression analysis were used to identify the prognostic factors for recovery postoperatively. For the prognostic factors worth further consideration, the changes in JOA scores within the 24-month follow-up period were identified by repeated-measures analysis of variance. Paralysis/nonparalysis, duration of symptoms (≥3/<3 months), number of involved vertebrae (>2/≤2), and posterior open/percutaneous instrumentation were identified as prognostic factors for recovery postoperatively. The prognostic factor of open/percutaneous instrumentation was then further compared for potential clinical application. Patients in the percutaneous instrumentation group achieved higher JOA scores than those in the open instrumentation group in the early stages postoperatively (1-3 months), but this effect equalized at 6 months postoperatively. Patients in the open instrumentation group experienced longer operation time and less cost than those in the percutaneous instrumentation group. Nonparalysis, shorter symptom duration, fewer involved vertebrae, and posterior percutaneous instrumentation (compared with open instrumentation) are considered favorable prognostic factors. Patients in the percutaneous instrumentation group achieved higher JOA scores than those in the open instrumentation group in the early stages postoperatively (1-3 months), but no significant difference was observed in long-term JOA scores (6-24 months). Copyright © 2017. Published by Elsevier Inc.

Localized primary gastrointestinal diffuse large B cell lymphoma received a surgical approach: an analysis of prognostic factors and comparison of staging systems in 101 patients from a single institution.

PubMed

Zhang, Shengting; Wang, Li; Yu, Dong; Shen, Yang; Cheng, Shu; Zhang, Li; Qian, Ying; Shen, Zhixiang; Li, Qinyu; Zhao, Weili

2015-08-15

Diffuse large B cell lymphoma (DLBCL) represents the most common histological subtype of primary gastrointestinal lymphoma and is a heterogeneous group of disease. Prognostic characterization of individual patients is an essential prerequisite for a proper risk-based therapeutic choice. Clinical and pathological prognostic factors were identified, and predictive value of four previously described prognostic systems were assessed in 101 primary gastrointestinal DLBCL (PG-DLBCL) patients with localized disease, including Ann Arbor staging with Musshoff modification, International Prognostic Index (IPI), Lugano classification, and Paris staging system. Univariate factors correlated with inferior survival time were clinical parameters [age>60 years old, multiple extranodal/gastrointestinal involvement, elevated serum lactate dehydrogenase and β2-microglobulin, and decreased serum albumin], as well as pathological parameters (invasion depth beyond serosa, involvement of regional lymph node or adjacent tissue, Ki-67 index, and Bcl-2 expression). Major independent variables of adverse outcome indicated by multivariate analysis were multiple gastrointestinal involvement. In patients unfit for Rituximab but received surgery, radical surgery significantly prolonged the survival time, comparing with alleviative surgery. Addition of Rituximab could overcome the negative prognostic effect of alleviative surgery. Among the four prognostic systems, IPI and Lugano classification clearly separated patients into different risk groups. IPI was able to further stratify the early-stage patients of Lugano classification into groups with distinct prognosis. Radical surgery might be proposed for the patients unfit for Rituximab treatment, and a combination of clinical and pathological staging systems was more helpful to predict the disease outcome of PG-DLBCL patients.

Prognostic value of interim FDG-PET in R-CHOP-treated diffuse large B-cell lymphoma: Systematic review and meta-analysis.

PubMed

Adams, Hugo J A; Kwee, Thomas C

2016-10-01

This study aimed to systematically review and meta-analyze the prognostic value of interim (18)F-fluoro-2-deoxy-d-glucose positron emission tomography (FDG-PET) in diffuse large B-cell lymphoma (DLBCL) patients treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP). MEDLINE and EMBASE were systematically searched for suitable studies. Included studies were methodologically appraised, and results were summarized both descriptively and meta-analytically. Nine studies, comprising a total of 996 R-CHOP-treated DLBCL patients, were included. Overall, studies were of moderate methodological quality. The area under the summary receiver operating curve (AUC) of interim FDG-PET in predicting treatment failure and death were 0.651 and 0.817, respectively. There was no heterogeneity in diagnostic odds ratios across available studies (I(2)=0.0%). At multivariable analysis, 2 studies reported interim FDG-PET to have independent prognostic value in addition to the International Prognostic Index (IPI) in predicting treatment failure, whereas 3 studies reported that this was not the case. One study reported interim FDG-PET to have independent prognostic value in addition to the IPI in predicting death, whereas 2 studies reported that this was not the case. In conclusion, interim FDG-PET in R-CHOP-treated DLBCL has some correlation with outcome, but its prognostic value is homogeneously suboptimal across studies and it has not consistently proven to surpass the prognostic potential of the IPI. Moreover, there is a lack of studies that compared interim FDG-PET to the recently developed and superior National Comprehensive Cancer Network-IPI. Therefore, at present there is no scientific base to support the clinical use of interim FDG-PET in R-CHOP-treated DLBCL. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Validation of the prognostic value of lymph node ratio in patients with cutaneous melanoma: a population-based study of 8,177 cases.

PubMed

Mocellin, Simone; Pasquali, Sandro; Rossi, Carlo Riccardo; Nitti, Donato

2011-07-01

The proportion of positive among examined lymph nodes (lymph node ratio [LNR]) has been recently proposed as an useful and easy-to-calculate prognostic factor for patients with cutaneous melanoma. However, its independence from the standard prognostic system TNM has not been formally proven in a large series of patients. Patients with histologically proven cutaneous melanoma were identified from the Surveillance Epidemiology End Results database. Disease-specific survival was the clinical outcome of interest. The prognostic ability of conventional factors and LNR was assessed by multivariable survival analysis using the Cox regression model. Eligible patients (n = 8,177) were diagnosed with melanoma between 1998 and 2006. Among lymph node-positive cases (n = 3,872), most LNR values ranged from 1% to 10% (n = 2,187). In the whole series (≥5 lymph nodes examined) LNR significantly contributed to the Cox model independently of the TNM effect on survival (hazard ratio, 1.28; 95% confidence interval, 1.23-1.32; P < .0001). On subgroup analysis, the significant and independent prognostic value of LNR was confirmed both in patients with ≥10 lymph nodes examined (n = 4,381) and in those with TNM stage III disease (n = 3,658). In all cases, LNR increased the prognostic accuracy of the survival model. In this large series of patients, the LNR independently predicted disease-specific survival, improving the prognostic accuracy of the TNM system. Accordingly, the LNR should be taken into account for the stratification of patients' risk, both in clinical and research settings. Copyright © 2011 Mosby, Inc. All rights reserved.

Serum C-reactive protein (CRP) as a simple and independent prognostic factor in extranodal natural killer/T-cell lymphoma, nasal type.

PubMed

Li, Ya-Jun; Li, Zhi-Ming; Xia, Yi; Huang, Jia-Jia; Huang, Hui-Qiang; Xia, Zhong-Jun; Lin, Tong-Yu; Li, Su; Cai, Xiu-Yu; Wu-Xiao, Zhi-Jun; Jiang, Wen-Qi

2013-01-01

C-reactive protein (CRP) is a biomarker of the inflammatory response, and it shows significant prognostic value for several types of solid tumors. The prognostic significance of CRP for lymphoma has not been fully examined. We evaluated the prognostic role of baseline serum CRP levels in patients with extranodal natural killer (NK)/T-cell lymphoma (ENKTL). We retrospectively analyzed 185 patients with newly diagnosed ENKTL. The prognostic value of the serum CRP level was evaluated for the low-CRP group (CRP≤10 mg/L) versus the high-CRP group (CRP>10 mg/L). The prognostic value of the International Prognostic Index (IPI) and the Korean Prognostic Index (KPI) were evaluated and compared with the newly developed prognostic model. Patients in the high-CRP group tended to display increased adverse clinical characteristics, lower rates of complete remission (P<0.001), inferior progression-free survival (PFS, P = 0.001), and inferior overall survival (OS, P<0.001). Multivariate analysis demonstrated that elevated serum CRP levels, age >60 years, hypoalbuminemia, and elevated lactate dehydrogenase levels were independent adverse predictors of OS. Based on these four independent predictors, we constructed a new prognostic model that identified 4 groups with varying OS: group 1, no adverse factors; group 2, 1 factor; group 3, 2 factors; and group 4, 3 or 4 factors (P<0.001). The novel prognostic model was found to be superior to both the IPI in discriminating patients with different outcomes in the IPI low-risk group and the KPI in distinguishing between the low- and intermediate-low-risk groups, the intermediate-low- and high-intermediate-risk groups, and the high-intermediate- and high-risk groups. Our results suggest that pretreatment serum CRP levels represent an independent predictor of clinical outcome for patients with ENKTL. The prognostic value of the new prognostic model is superior to both IPI and KPI.

Serum C-Reactive Protein (CRP) as a Simple and Independent Prognostic Factor in Extranodal Natural Killer/T-Cell Lymphoma, Nasal Type

PubMed Central

Xia, Yi; Huang, Jia-Jia; Huang, Hui-Qiang; Xia, Zhong-Jun; Lin, Tong-Yu; Li, Su; Cai, Xiu-Yu; Wu-Xiao, Zhi-Jun; Jiang, Wen-Qi

2013-01-01

Background C-reactive protein (CRP) is a biomarker of the inflammatory response, and it shows significant prognostic value for several types of solid tumors. The prognostic significance of CRP for lymphoma has not been fully examined. We evaluated the prognostic role of baseline serum CRP levels in patients with extranodal natural killer (NK)/T-cell lymphoma (ENKTL). Methods We retrospectively analyzed 185 patients with newly diagnosed ENKTL. The prognostic value of the serum CRP level was evaluated for the low-CRP group (CRP≤10 mg/L) versus the high-CRP group (CRP>10 mg/L). The prognostic value of the International Prognostic Index (IPI) and the Korean Prognostic Index (KPI) were evaluated and compared with the newly developed prognostic model. Results Patients in the high-CRP group tended to display increased adverse clinical characteristics, lower rates of complete remission (P<0.001), inferior progression-free survival (PFS, P = 0.001), and inferior overall survival (OS, P<0.001). Multivariate analysis demonstrated that elevated serum CRP levels, age >60 years, hypoalbuminemia, and elevated lactate dehydrogenase levels were independent adverse predictors of OS. Based on these four independent predictors, we constructed a new prognostic model that identified 4 groups with varying OS: group 1, no adverse factors; group 2, 1 factor; group 3, 2 factors; and group 4, 3 or 4 factors (P<0.001). The novel prognostic model was found to be superior to both the IPI in discriminating patients with different outcomes in the IPI low-risk group and the KPI in distinguishing between the low- and intermediate-low-risk groups, the intermediate-low- and high-intermediate-risk groups, and the high-intermediate- and high-risk groups. Conclusions Our results suggest that pretreatment serum CRP levels represent an independent predictor of clinical outcome for patients with ENKTL. The prognostic value of the new prognostic model is superior to both IPI and KPI. PMID:23724031

Quantitative fibronectin to help decision-making in women with symptoms of preterm labour (QUIDS) part 1: Individual participant data meta-analysis and health economic analysis

PubMed Central

Wotherspoon, Lisa M; Boyd, Kathleen A; Morris, Rachel K; Jackson, Lesley; Chandiramani, Manju; David, Anna L; Khalil, Asma; Shennan, Andrew; Hodgetts Morton, Victoria; Lavender, Tina; Khan, Khalid; Harper-Clarke, Susan; Mol, Ben W; Riley, Richard D; Norrie, John; Norman, Jane E

2018-01-01

Introduction The aim of the QUIDS study is to develop a decision support tool for the management of women with symptoms and signs of preterm labour, based on a validated prognostic model using quantitative fetal fibronectin (qfFN) concentration, in combination with clinical risk factors. Methods and analysis The study will evaluate the Rapid fFN 10Q System (Hologic, Marlborough, Massachusetts) which quantifies fFN in a vaginal swab. In part 1 of the study, we will develop and internally validate a prognostic model using an individual participant data (IPD) meta-analysis of existing studies containing women with symptoms of preterm labour alongside fFN measurements and pregnancy outcome. An economic analysis will be undertaken to assess potential cost-effectiveness of the qfFN prognostic model. The primary endpoint will be the ability of the prognostic model to rule out spontaneous preterm birth within 7 days. Six eligible studies were identified by systematic review of the literature and five agreed to provide their IPD (n=5 studies, 1783 women and 139 events of preterm delivery within 7 days of testing). Ethics and dissemination The study is funded by the National Institute of Healthcare Research Health Technology Assessment (HTA 14/32/01). It has been approved by the West of Scotland Research Ethics Committee (16/WS/0068). PROSPERO registration number CRD42015027590. Version Protocol version 2, date 1 November 2016. PMID:29627817

Development of prognostic model for predicting survival after retrograde placement of ureteral stent in advanced gastrointestinal cancer patients and its evaluation by decision curve analysis.

PubMed

Kawano, Shingo; Komai, Yoshinobu; Ishioka, Junichiro; Sakai, Yasuyuki; Fuse, Nozomu; Ito, Masaaki; Kihara, Kazunori; Saito, Norio

2016-10-01

The aim of this study was to determine risk factors for survival after retrograde placement of ureteral stents and develop a prognostic model for advanced gastrointestinal tract (GIT: esophagus, stomach, colon and rectum) cancer patients. We examined the clinical records of 122 patients who underwent retrograde placement of a ureteral stent against malignant extrinsic ureteral obstruction. A prediction model for survival after stenting was developed. We compared its clinical usefulness with our previous model based on the results from nephrostomy cases by decision curve analysis. Median follow-up period was 201 days (8-1490) and 97 deaths occurred. The 1-year survival rate in this cohort was 29%. Based on multivariate analysis, primary site of colon origin, absence of retroperitoneal lymph node metastasis and serum albumin >3g/dL were significantly associated with a prolonged survival time. To develop a prognostic model, we divided the patients into 3 risk groups of favorable: 0-1 factors (N.=53), intermediate: 2 risk factors (N.=54), and poor: 3 risk factors (N.=15). There were significant differences in the survival profiles of these 3 risk groups (P<0.0001). Decision curve analyses revealed that the current model has a superior net benefit than our previous model for most of the examined probabilities. We have developed a novel prognostic model for GIT cancer patients who were treated with retrograde placement of a ureteral stent. The current model should help urologists and medical oncologists to predict survival in cases of malignant extrinsic ureteral obstruction.

Distributed Prognostics based on Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, I.

2014-01-01

Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based models are constructed that describe the operation of a system and how it fails. Such approaches consist of an estimation phase, in which the health state of the system is first identified, and a prediction phase, in which the health state is projected forward in time to determine the end of life. Centralized solutions to these problems are often computationally expensive, do not scale well as the size of the system grows, and introduce a single point of failure. In this paper, we propose a novel distributed model-based prognostics scheme that formally describes how to decompose both the estimation and prediction problems into independent local subproblems whose solutions may be easily composed into a global solution. The decomposition of the prognostics problem is achieved through structural decomposition of the underlying models. The decomposition algorithm creates from the global system model a set of local submodels suitable for prognostics. Independent local estimation and prediction problems are formed based on these local submodels, resulting in a scalable distributed prognostics approach that allows the local subproblems to be solved in parallel, thus offering increases in computational efficiency. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the distributed approach, compare the performance with a centralized approach, and establish its scalability. Index Terms-model-based prognostics, distributed prognostics, structural model decomposition ABBREVIATIONS

Comparison of Source Partitioning Methods for CO2 and H2O Fluxes Based on High Frequency Eddy Covariance Data

NASA Astrophysics Data System (ADS)

Klosterhalfen, Anne; Moene, Arnold; Schmidt, Marius; Ney, Patrizia; Graf, Alexander

2017-04-01

Source partitioning of eddy covariance (EC) measurements of CO2 into respiration and photosynthesis is routinely used for a better understanding of the exchange of greenhouse gases, especially between terrestrial ecosystems and the atmosphere. The most frequently used methods are usually based either on relations of fluxes to environmental drivers or on chamber measurements. However, they often depend strongly on assumptions or invasive measurements and do usually not offer partitioning estimates for latent heat fluxes into evaporation and transpiration. SCANLON and SAHU (2008) and SCANLON and KUSTAS (2010) proposed an promising method to estimate the contributions of transpiration and evaporation using measured high frequency time series of CO2 and H2O fluxes - no extra instrumentation necessary. This method (SK10 in the following) is based on the spatial separation and relative strength of sources and sinks of CO2 and water vapor among the sub-canopy and canopy. Assuming that air from those sources and sinks is not yet perfectly mixed before reaching EC sensors, partitioning is estimated based on the separate application of the flux-variance similarity theory to the stomatal and non-stomatal components of the regarded fluxes, as well as on additional assumptions on stomatal water use efficiency (WUE). The CO2 partitioning method after THOMAS et al. (2008) (TH08 in the following) also follows the argument that the dissimilarities of sources and sinks in and below a canopy affect the relation between H2O and CO2 fluctuations. Instead of involving assumptions on WUE, TH08 directly screens their scattergram for signals of joint respiration and evaporation events and applies a conditional sampling methodology. In spite of their different main targets (H2O vs. CO2), both methods can yield partitioning estimates on both fluxes. We therefore compare various sub-methods of SK10 and TH08 including own modifications (e.g., cluster analysis) to each other, to established source partitioning methods, and to chamber measurements at various agroecosystems. Further, profile measurements and a canopy-resolving Large Eddy Simulation model are used to test the assumptions involved in SK10. Scanlon, T.M., Kustas, W.P., 2010. Partitioning carbon dioxide and water vapor fluxes using correlation analysis. Agricultural and Forest Meteorology 150 (1), 89-99. Scanlon, T.M., Sahu, P., 2008. On the correlation structure of water vapor and carbon dioxide in the atmospheric surface layer: A basis for flux partitioning. Water Resources Research 44 (10), W10418, 15 pp. Thomas, C., Martin, J.G., Goeckede, M., Siqueira, M.B., Foken, T., Law, B.E., Loescher H.W., Katul, G., 2008. Estimating daytime subcanopy respiration from conditional sampling methods applied to multi-scalar high frequency turbulence time series. Agricultural and Forest Meteorology 148 (8-9), 1210-1229.

A novel literature-based approach to identify genetic and molecular predictors of survival in glioblastoma multiforme: Analysis of 14,678 patients using systematic review and meta-analytical tools.

PubMed

Thuy, Matthew N T; Kam, Jeremy K T; Lee, Geoffrey C Y; Tao, Peter L; Ling, Dorothy Q; Cheng, Melissa; Goh, Su Kah; Papachristos, Alexander J; Shukla, Lipi; Wall, Krystal-Leigh; Smoll, Nicolas R; Jones, Jordan J; Gikenye, Njeri; Soh, Bob; Moffat, Brad; Johnson, Nick; Drummond, Katharine J

2015-05-01

Glioblastoma multiforme (GBM) has a poor prognosis despite maximal multimodal therapy. Biomarkers of relevance to prognosis which may also identify treatment targets are needed. A few hundred genetic and molecular predictors have been implicated in the literature, however with the exception of IDH1 and O6-MGMT, there is uncertainty regarding their true prognostic relevance. This study analyses reported genetic and molecular predictors of prognosis in GBM. For each, its relationship with univariate overall survival in adults with GBM is described. A systematic search of MEDLINE (1998-July 2010) was performed. Eligible papers studied the effect of any genetic or molecular marker on univariate overall survival in adult patients with histologically diagnosed GBM. Primary outcomes were median survival difference in months and univariate hazard ratios. Analyses included converting 126 Kaplan-Meier curves and 27 raw data sets into primary outcomes. Seventy-four random effects meta-analyses were performed on 39 unique genetic or molecular factors. Objective criteria were designed to classify factors into the categories of clearly prognostic, weakly prognostic, non-prognostic and promising. Included were 304 publications and 174 studies involving 14,678 unique patients from 33 countries. We identified 422 reported genetic and molecular predictors, of which 52 had ⩾2 studies. IDH1 mutation and O6-MGMT were classified as clearly prognostic, validating the methodology. High Ki-67/MIB-1 and loss of heterozygosity of chromosome 10/10q were classified as weakly prognostic. Four factors were classified as non-prognostic and 13 factors were classified as promising and worthy of additional investigation. Funnel plot analysis did not identify any evidence of publication bias. This study demonstrates a novel literature and meta-analytical based approach to maximise the value that can be derived from the plethora of literature reports of molecular and genetic factors in GBM. Caution is advised in over-interpreting the results due to study limitations. Further research to develop this methodology and improvements in study reporting are suggested. Copyright © 2014 Elsevier Ltd. All rights reserved.

Copula-based analysis of rhythm

NASA Astrophysics Data System (ADS)

García, J. E.; González-López, V. A.; Viola, M. L. Lanfredi

2016-06-01

In this paper we establish stochastic profiles of the rhythm for three languages: English, Japanese and Spanish. We model the increase or decrease of the acoustical energy, collected into three bands coming from the acoustic signal. The number of parameters needed to specify a discrete multivariate Markov chain grows exponentially with the order and dimension of the chain. In this case the size of the database is not large enough for a consistent estimation of the model. We apply a strategy to estimate a multivariate process with an order greater than the order achieved using standard procedures. The new strategy consist on obtaining a partition of the state space which is constructed from a combination of the partitions corresponding to the three marginal processes, one for each band of energy, and the partition coming from to the multivariate Markov chain. Then, all the partitions are linked using a copula, in order to estimate the transition probabilities.

Significant Scales in Community Structure

NASA Astrophysics Data System (ADS)

Traag, V. A.; Krings, G.; van Dooren, P.

2013-10-01

Many complex networks show signs of modular structure, uncovered by community detection. Although many methods succeed in revealing various partitions, it remains difficult to detect at what scale some partition is significant. This problem shows foremost in multi-resolution methods. We here introduce an efficient method for scanning for resolutions in one such method. Additionally, we introduce the notion of ``significance'' of a partition, based on subgraph probabilities. Significance is independent of the exact method used, so could also be applied in other methods, and can be interpreted as the gain in encoding a graph by making use of a partition. Using significance, we can determine ``good'' resolution parameters, which we demonstrate on benchmark networks. Moreover, optimizing significance itself also shows excellent performance. We demonstrate our method on voting data from the European Parliament. Our analysis suggests the European Parliament has become increasingly ideologically divided and that nationality plays no role.

Implementation of hybrid clustering based on partitioning around medoids algorithm and divisive analysis on human Papillomavirus DNA

NASA Astrophysics Data System (ADS)

Arimbi, Mentari Dian; Bustamam, Alhadi; Lestari, Dian

2017-03-01

Data clustering can be executed through partition or hierarchical method for many types of data including DNA sequences. Both clustering methods can be combined by processing partition algorithm in the first level and hierarchical in the second level, called hybrid clustering. In the partition phase some popular methods such as PAM, K-means, or Fuzzy c-means methods could be applied. In this study we selected partitioning around medoids (PAM) in our partition stage. Furthermore, following the partition algorithm, in hierarchical stage we applied divisive analysis algorithm (DIANA) in order to have more specific clusters and sub clusters structures. The number of main clusters is determined using Davies Bouldin Index (DBI) value. We choose the optimal number of clusters if the results minimize the DBI value. In this work, we conduct the clustering on 1252 HPV DNA sequences data from GenBank. The characteristic extraction is initially performed, followed by normalizing and genetic distance calculation using Euclidean distance. In our implementation, we used the hybrid PAM and DIANA using the R open source programming tool. In our results, we obtained 3 main clusters with average DBI value is 0.979, using PAM in the first stage. After executing DIANA in the second stage, we obtained 4 sub clusters for Cluster-1, 9 sub clusters for Cluster-2 and 2 sub clusters in Cluster-3, with the BDI value 0.972, 0.771, and 0.768 for each main cluster respectively. Since the second stage produce lower DBI value compare to the DBI value in the first stage, we conclude that this hybrid approach can improve the accuracy of our clustering results.

Prognostic factors and risk stratification in patients with castration-resistant prostate cancer receiving docetaxel-based chemotherapy.

PubMed

Yamashita, Shimpei; Kohjimoto, Yasuo; Iguchi, Takashi; Koike, Hiroyuki; Kusumoto, Hiroki; Iba, Akinori; Kikkawa, Kazuro; Kodama, Yoshiki; Matsumura, Nagahide; Hara, Isao

2016-03-22

While novel drugs have been developed, docetaxel remains one of the standard initial systemic therapies for castration-resistant prostate cancer (CRPC) patients. Despite the excellent anti-tumor effect of docetaxel, its severe adverse effects sometimes distress patients. Therefore, it would be very helpful to predict the efficacy of docetaxel before treatment. The aims of this study were to evaluate the potential value of patient characteristics in predicting overall survival (OS) and to develop a risk classification for CRPC patients treated with docetaxel-based chemotherapy. This study included 79 patients with CRPC treated with docetaxel. The variables, including patient characteristics at diagnosis and at the start of chemotherapy, were retrospectively collected. Prognostic factors predicting OS were analyzed using the Cox proportional hazard model. Risk stratification for overall survival was determined based on the results of multivariate analysis. PSA response ≥50 % was observed in 55 (69.6 %) of all patients, and the median OS was 22.5 months. The multivariate analysis showed that age, serum PSA level at the start of chemotherapy, and Hb were independent prognostic factors for OS. In addition, ECOG performance status (PS) and the CRP-to-albumin ratio were not significant but were considered possible predictors for OS. Risk stratification according to the number of these risk factors could effectively stratify CRPC patients treated with docetaxel in terms of OS. Age, serum PSA level at the start of chemotherapy, and Hb were identified as independent prognostic factors of OS. ECOG PS and the CRP-to-albumin ratio were not significant, but were considered possible predictors for OS in Japanese CRPC patients treated with docetaxel. Risk stratification based on these factors could be helpful for estimating overall survival.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers.

PubMed

Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won

2017-12-12

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers

PubMed Central

Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won

2017-01-01

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice. PMID:29312619

A physically based catchment partitioning method for hydrological analysis

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Riboni, Vittoria

2000-07-01

We propose a partitioning method for the topographic surface, which is particularly suitable for hydrological distributed modelling and shallow-landslide distributed modelling. The model provides variable mesh size and appears to be a natural evolution of contour-based digital terrain models. The proposed method allows the drainage network to be derived from the contour lines. The single channels are calculated via a search for the steepest downslope lines. Then, for each network node, the contributing area is determined by means of a search for both steepest upslope and downslope lines. This leads to the basin being partitioned into physically based finite elements delimited by irregular polygons. In particular, the distributed computation of local geomorphological parameters (i.e. aspect, average slope and elevation, main stream length, concentration time, etc.) can be performed easily for each single element. The contributing area system, together with the information on the distribution of geomorphological parameters provide a useful tool for distributed hydrological modelling and simulation of environmental processes such as erosion, sediment transport and shallow landslides.

Chemical amplification based on fluid partitioning

DOEpatents

Anderson, Brian L [Lodi, CA; Colston, Jr., Billy W.; Elkin, Chris [San Ramon, CA

2006-05-09

A system for nucleic acid amplification of a sample comprises partitioning the sample into partitioned sections and performing PCR on the partitioned sections of the sample. Another embodiment of the invention provides a system for nucleic acid amplification and detection of a sample comprising partitioning the sample into partitioned sections, performing PCR on the partitioned sections of the sample, and detecting and analyzing the partitioned sections of the sample.

Heterogeneity of Prognostic Studies of 24-Hour Blood Pressure Variability: Systematic Review and Meta-Analysis

PubMed Central

Taylor, Kathryn S.; Heneghan, Carl J.; Stevens, Richard J.; Adams, Emily C.; Nunan, David; Ward, Alison

2015-01-01

In addition to mean blood pressure, blood pressure variability is hypothesized to have important prognostic value in evaluating cardiovascular risk. We aimed to assess the prognostic value of blood pressure variability within 24 hours. Using MEDLINE, EMBASE and Cochrane Library to April 2013, we conducted a systematic review of prospective studies of adults, with at least one year follow-up and any day, night or 24-hour blood pressure variability measure as a predictor of one or more of the following outcomes: all-cause mortality, cardiovascular mortality, all cardiovascular events, stroke and coronary heart disease. We examined how blood pressure variability is defined and how its prognostic use is reported. We analysed relative risks adjusted for covariates including the appropriate mean blood pressure and considered the potential for meta-analysis. Our analysis of methods included 24 studies and analysis of predictions included 16 studies. There were 36 different measures of blood pressure variability and 13 definitions of night- and day-time periods. Median follow-up was 5.5 years (interquartile range 4.2–7.0). Comparing measures of dispersion, coefficient of variation was less well researched than standard deviation. Night dipping based on percentage change was the most researched measure and the only measure for which data could be meaningfully pooled. Night dipping or lower night-time blood pressure was associated with lower risk of cardiovascular events. The interpretation and use in clinical practice of 24-hour blood pressure variability, as an important prognostic indicator of cardiovascular events, is hampered by insufficient evidence and divergent methodologies. We recommend greater standardisation of methods. PMID:25984791

Research on the Automatic Fusion Strategy of Fixed Value Boundary Based on the Weak Coupling Condition of Grid Partition

NASA Astrophysics Data System (ADS)

Wang, X. Y.; Dou, J. M.; Shen, H.; Li, J.; Yang, G. S.; Fan, R. Q.; Shen, Q.

2018-03-01

With the continuous strengthening of power grids, the network structure is becoming more and more complicated. An open and regional data modeling is used to complete the calculation of the protection fixed value based on the local region. At the same time, a high precision, quasi real-time boundary fusion technique is needed to seamlessly integrate the various regions so as to constitute an integrated fault computing platform which can conduct transient stability analysis of covering the whole network with high accuracy and multiple modes, deal with the impact results of non-single fault, interlocking fault and build “the first line of defense” of the power grid. The boundary fusion algorithm in this paper is an automatic fusion algorithm based on the boundary accurate coupling of the networking power grid partition, which takes the actual operation mode for qualification, complete the boundary coupling algorithm of various weak coupling partition based on open-loop mode, improving the fusion efficiency, truly reflecting its transient stability level, and effectively solving the problems of too much data, too many difficulties of partition fusion, and no effective fusion due to mutually exclusive conditions. In this paper, the basic principle of fusion process is introduced firstly, and then the method of boundary fusion customization is introduced by scene description. Finally, an example is given to illustrate the specific algorithm on how it effectively implements the boundary fusion after grid partition and to verify the accuracy and efficiency of the algorithm.

Independent Prognostic Factors for Acute Organophosphorus Pesticide Poisoning.

PubMed

Tang, Weidong; Ruan, Feng; Chen, Qi; Chen, Suping; Shao, Xuebo; Gao, Jianbo; Zhang, Mao

2016-07-01

Acute organophosphorus pesticide poisoning (AOPP) is becoming a significant problem and a potential cause of human mortality because of the abuse of organophosphate compounds. This study aims to determine the independent prognostic factors of AOPP by using multivariate logistic regression analysis. The clinical data for 71 subjects with AOPP admitted to our hospital were retrospectively analyzed. This information included the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, admission blood cholinesterase levels, 6-h post-admission blood cholinesterase levels, cholinesterase activity, blood pH, and other factors. Univariate analysis and multivariate logistic regression analyses were conducted to identify all prognostic factors and independent prognostic factors, respectively. A receiver operating characteristic curve was plotted to analyze the testing power of independent prognostic factors. Twelve of 71 subjects died. Admission blood lactate levels, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, blood pH, and APACHE II scores were identified as prognostic factors for AOPP according to the univariate analysis, whereas only 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, and blood pH were independent prognostic factors identified by multivariate logistic regression analysis. The receiver operating characteristic analysis suggested that post-admission 6-h lactate clearance rates were of moderate diagnostic value. High 6-h post-admission blood lactate levels, low blood pH, and low post-admission 6-h lactate clearance rates were independent prognostic factors identified by multivariate logistic regression analysis. Copyright © 2016 by Daedalus Enterprises.

Adjuvant Chemotherapy Improves the Probability of Freedom From Recurrence in Patients With Resected Stage IB Lung Adenocarcinoma.

PubMed

Hung, Jung-Jyh; Wu, Yu-Chung; Chou, Teh-Ying; Jeng, Wen-Juei; Yeh, Yi-Chen; Hsu, Wen-Hu

2016-04-01

The benefit of adjuvant chemotherapy remains controversial for patients with stage IB non-small-cell lung cancer (NSCLC). This study investigated the effect of adjuvant chemotherapy and the predictors of benefit from adjuvant chemotherapy in patients with stage IB lung adenocarcinoma. A total of 243 patients with completely resected pathologic stage IB lung adenocarcinoma were included in the study. Predictors of the benefits of improved overall survival (OS) or probability of freedom from recurrence (FFR) from platinum-based adjuvant chemotherapy in patients with resected stage IB lung adenocarcinoma were investigated. Among the 243 patients, 70 (28.8%) had received platinum-based doublet adjuvant chemotherapy. A micropapillary/solid-predominant pattern (versus an acinar/papillary-predominant pattern) was a significantly worse prognostic factor for probability of FFR (p = 0.033). Although adjuvant chemotherapy (versus surgical intervention alone) was not a significant prognostic factor for OS (p = 0.303), it was a significant prognostic factor for a better probability of FFR (p = 0.029) on multivariate analysis. In propensity-score-matched pairs, there was no significant difference in OS between patients who received adjuvant chemotherapy and those who did not (p = 0.386). Patients who received adjuvant chemotherapy had a significantly better probability of FFR than those who did not (p = 0.043). For patients with a predominantly micropapillary/solid pattern, adjuvant chemotherapy (p = 0.033) was a significant prognostic factor for a better probability of FFR on multivariate analysis. Adjuvant chemotherapy is a favorable prognostic factor for the probability of FFR in patients with stage IB lung adenocarcinoma, particularly in those with a micropapillary/solid-predominant pattern. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

SurvMicro: assessment of miRNA-based prognostic signatures for cancer clinical outcomes by multivariate survival analysis.

PubMed

Aguirre-Gamboa, Raul; Trevino, Victor

2014-06-01

MicroRNAs (miRNAs) play a key role in post-transcriptional regulation of mRNA levels. Their function in cancer has been studied by high-throughput methods generating valuable sources of public information. Thus, miRNA signatures predicting cancer clinical outcomes are emerging. An important step to propose miRNA-based biomarkers before clinical validation is their evaluation in independent cohorts. Although it can be carried out using public data, such task is time-consuming and requires a specialized analysis. Therefore, to aid and simplify the evaluation of prognostic miRNA signatures in cancer, we developed SurvMicro, a free and easy-to-use web tool that assesses miRNA signatures from publicly available miRNA profiles using multivariate survival analysis. SurvMicro is composed of a wide and updated database of >40 cohorts in different tissues and a web tool where survival analysis can be done in minutes. We presented evaluations to portray the straightforward functionality of SurvMicro in liver and lung cancer. To our knowledge, SurvMicro is the only bioinformatic tool that aids the evaluation of multivariate prognostic miRNA signatures in cancer. SurvMicro and its tutorial are freely available at http://bioinformatica.mty.itesm.mx/SurvMicro. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

The proliferation marker Ki67, but not neuroendocrine expression, is an independent factor in the prediction of prognosis of primary prostate cancer patients

PubMed Central

Pascale, Mariarosa; Aversa, Cinzia; Barbazza, Renzo; Marongiu, Barbara; Siracusano, Salvatore; Stoffel, Flavio; Sulfaro, Sando; Roggero, Enrico; Stanta, Giorgio

2016-01-01

Abstract Background Neuroendocrine markers, which could indicate for aggressive variants of prostate cancer and Ki67 (a well-known marker in oncology for defining tumor proliferation), have already been associated with clinical outcome in prostate cancer. The aim of this study was to investigate the prognostic value of those markers in primary prostate cancer patients. Patients and methods NSE (neuron specific enolase), ChrA (chromogranin A), Syp (Synaptophysin) and Ki67 staining were performed by immunohistochemistry. Then, the prognostic impact of their expression on overall survival was investigated in 166 primary prostate cancer patients by univariate and multivariate analyses. Results NSE, ChrA, Syp and Ki67 were positive in 50, 45, 54 and 146 out of 166 patients, respectively. In Kaplan-Meier analysis only diffuse NSE staining (negative vs diffuse, p = 0.004) and Ki67 (≤ 10% vs > 10%, p < 0.0001) were significantly associated with overall survival. Ki67 expression, but not NSE, resulted as an independent prognostic factor for overall survival in multivariate analysis. Conclusions A prognostic model incorporating Ki67 expression with clinical-pathological covariates could provide additional prognostic information. Ki67 may thus improve prediction of prostate cancer outcome based on standard clinical-pathological parameters improving prognosis and management of prostate cancer patients. PMID:27679548

Evaluating surrogate endpoints, prognostic markers, and predictive markers: Some simple themes.

PubMed

Baker, Stuart G; Kramer, Barnett S

2015-08-01

A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. We organized our discussion around a different theme for each topic. "Fundamentally an extrapolation" refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. "Decision analysis to the rescue" refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. "The appeal of simplicity" refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. © The Author(s) 2014.

Correlation of soil and sediment organic matter polarity to aqueous sorption of nonionic compounds

USGS Publications Warehouse

Kile, D.E.; Wershaw, R. L.; Chiou, C.T.

1999-01-01

Polarities of the soiL/sediment organic matter (SOM) in 19 soil and 9 freshwater sediment sam pies were determined from solid-state 13C-CP/MAS NMR spectra and compared with published partition coefficients (K(oc)) of carbon tetrachloride (CT) from aqueous solution. Nondestructive analysis of whole samples by solid-state NMR permits a direct assessment of the polarity of SOM that is not possible by elemental analysis. The percent of organic carbon associated with polar functional groups was estimated from the combined fraction of carbohydrate and carboxylamide-ester carbons. A plot of the measured partition coefficients (K(oc)) of carbon tetrachloride (CT) vs. percent polar organic carbon (POC) shows distinctly different populations of soils and sediments as well as a roughly inverse trend among the soil/sediment populations. Plots of K(oc) values for CT against other structural group carbon fractions did not yield distinct populations. The results indicate that the polarity of SOM is a significant factor in accounting for differences in K(oc) between the organic matter in soils and sediments. The alternate direct correlation of the sum of aliphatic and aromatic structural carbons with K(oc) illustrates the influence of nonpolar hydrocarbon on solute partition interaction. Additional elemental analysis data of selected samples further substantiate the effect of the organic matter polarity on the partition efficiency of nonpolar solutes. The separation between soil and sediment samples based on percent POC reflects definite differences of the properties of soil and sediment organic matters that are attributable to diagenesis.Polarities of the soil/sediment organic matter (SOM) in 19 soil and 9 freshwater sediment samples were determined from solid-state 13C-CP/MAS NMR spectra and compared with published partition coefficients (Koc) of carbon tetrachloride (CT) from aqueous solution. Nondestructive analysis of whole samples by solid-state NMR permits a direct assessment of the polarity of SOM that is not possible by elemental analysis. The percent of organic carbon associated with polar functional groups was estimated from the combined fraction of carbohydrate and carboxyl-amide-ester carbons. A plot of the measured partition coefficients (Koc) of carbon tetrachloride (CT) vs. percent polar organic carbon (POC) shows distinctly different populations of soils and sediments as well as a roughly inverse trend among the soil/sediment populations. Plots of Koc values for CT against other structural group carbon fractions did not yield distinct populations. The results indicate that the polarity of SOM is a significant factor in accounting for differences in Koc between the organic matter in soils and sediments. The alternate direct correlation of the sum of aliphatic and aromatic structural carbons with Koc illustrates the influence of nonpolar hydrocarbon on solute partition interaction. Additional elemental analysis data of selected samples further substantiate the effect of the organic matter polarity on the partition efficiency of nonpolar solutes. The separation between soil and sediment samples based on percent POC reflects definite differences of the properties of soil and sediment organic matters that are attributable to diagenesis.

Construction and Analysis of Multi-Rate Partitioned Runge-Kutta Methods

DTIC Science & Technology

2012-06-01

ANALYSIS OF MULTI-RATE PARTITIONED RUNGE-KUTTA METHODS by Patrick R. Mugg June 2012 Thesis Advisor: Francis Giraldo Second Reader: Hong...COVERED Master’s Thesis 4. TITLE AND SUBTITLE Construction and Analysis of Multi-Rate Partitioned Runge-Kutta Methods 5. FUNDING NUMBERS 6. AUTHOR...The most widely known and used procedure for analyzing stability is the Von Neumann Method , such that Von Neumann’s stability analysis looks at

Model-based recursive partitioning to identify risk clusters for metabolic syndrome and its components: findings from the International Mobility in Aging Study

PubMed Central

Pirkle, Catherine M; Wu, Yan Yan; Zunzunegui, Maria-Victoria; Gómez, José Fernando

2018-01-01

Objective Conceptual models underpinning much epidemiological research on ageing acknowledge that environmental, social and biological systems interact to influence health outcomes. Recursive partitioning is a data-driven approach that allows for concurrent exploration of distinct mixtures, or clusters, of individuals that have a particular outcome. Our aim is to use recursive partitioning to examine risk clusters for metabolic syndrome (MetS) and its components, in order to identify vulnerable populations. Study design Cross-sectional analysis of baseline data from a prospective longitudinal cohort called the International Mobility in Aging Study (IMIAS). Setting IMIAS includes sites from three middle-income countries—Tirana (Albania), Natal (Brazil) and Manizales (Colombia)—and two from Canada—Kingston (Ontario) and Saint-Hyacinthe (Quebec). Participants Community-dwelling male and female adults, aged 64–75 years (n=2002). Primary and secondary outcome measures We apply recursive partitioning to investigate social and behavioural risk factors for MetS and its components. Model-based recursive partitioning (MOB) was used to cluster participants into age-adjusted risk groups based on variabilities in: study site, sex, education, living arrangements, childhood adversities, adult occupation, current employment status, income, perceived income sufficiency, smoking status and weekly minutes of physical activity. Results 43% of participants had MetS. Using MOB, the primary partitioning variable was participant sex. Among women from middle-incomes sites, the predicted proportion with MetS ranged from 58% to 68%. Canadian women with limited physical activity had elevated predicted proportions of MetS (49%, 95% CI 39% to 58%). Among men, MetS ranged from 26% to 41% depending on childhood social adversity and education. Clustering for MetS components differed from the syndrome and across components. Study site was a primary partitioning variable for all components except HDL cholesterol. Sex was important for most components. Conclusion MOB is a promising technique for identifying disease risk clusters (eg, vulnerable populations) in modestly sized samples. PMID:29500203

Adaptively loaded IM/DD optical OFDM based on set-partitioned QAM formats.

PubMed

Zhao, Jian; Chen, Lian-Kuan

2017-04-17

We investigate the constellation design and symbol error rate (SER) of set-partitioned (SP) quadrature amplitude modulation (QAM) formats. Based on the SER analysis, we derive the adaptive bit and power loading algorithm for SP QAM based intensity-modulation direct-detection (IM/DD) orthogonal frequency division multiplexing (OFDM). We experimentally show that the proposed system significantly outperforms the conventional adaptively-loaded IM/DD OFDM and can increase the data rate from 36 Gbit/s to 42 Gbit/s in the presence of severe dispersion-induced spectral nulls after 40-km single-mode fiber. It is also shown that the adaptive algorithm greatly enhances the tolerance to fiber nonlinearity and allows for more power budget.

Chemical amplification based on fluid partitioning in an immiscible liquid

DOEpatents

Anderson, Brian L.; Colston, Bill W.; Elkin, Christopher J.

2010-09-28

A system for nucleic acid amplification of a sample comprises partitioning the sample into partitioned sections and performing PCR on the partitioned sections of the sample. Another embodiment of the invention provides a system for nucleic acid amplification and detection of a sample comprising partitioning the sample into partitioned sections, performing PCR on the partitioned sections of the sample, and detecting and analyzing the partitioned sections of the sample.

Improving Cluster Analysis with Automatic Variable Selection Based on Trees

DTIC Science & Technology

2014-12-01

regression trees Daisy DISsimilAritY PAM partitioning around medoids PMA penalized multivariate analysis SPC sparse principal components UPGMA unweighted...unweighted pair-group average method ( UPGMA ). This method measures dissimilarities between all objects in two clusters and takes the average value

The evolving field of prognostication and risk stratification in MDS: Recent developments and future directions.

PubMed

Lee, Eun-Ju; Podoltsev, Nikolai; Gore, Steven D; Zeidan, Amer M

2016-01-01

The clinical course of patients with myelodysplastic syndromes (MDS) is characterized by wide variability reflecting the underlying genetic and biological heterogeneity of the disease. Accurate prediction of outcomes for individual patients is an integral part of the evidence-based risk/benefit calculations that are necessary for tailoring the aggressiveness of therapeutic interventions. While several prognostication tools have been developed and validated for risk stratification, each of these systems has limitations. The recent progress in genomic sequencing techniques has led to discoveries of recurrent molecular mutations in MDS patients with independent impact on relevant clinical outcomes. Reliable assays of these mutations have already entered the clinic and efforts are currently ongoing to formally incorporate mutational analysis into the existing clinicopathologic risk stratification tools. Additionally, mutational analysis holds promise for going beyond prognostication to therapeutic selection and individualized treatment-specific prediction of outcomes; abilities that would revolutionize MDS patient care. Despite these exciting developments, the best way of incorporating molecular testing for use in prognostication and prediction of outcomes in clinical practice remains undefined and further research is warranted. Copyright © 2015 Elsevier Ltd. All rights reserved.

The modified glasgow prognostic score is an independent prognostic indicator in neoadjuvantly treated adenocarcinoma of the esophagogastric junction

PubMed Central

Jomrich, Gerd; Hollenstein, Marlene; John, Maximilian; Baierl, Andreas; Paireder, Matthias; Kristo, Ivan; Ilhan-Mutlu, Aysegül; Asari, Reza; Preusser, Matthias; Schoppmann, Sebastian F.

2018-01-01

The modified Glasgow Prognostic Score (mGPS) combines the indicators of decreased plasma albumin and elevated CRP. In a number of malignancies, elevated mGPS is associated with poor survival. Aim of this study was to investigate the prognostic role of mGPS in patients with neoadjuvantly treated adenocarcinomas of the esophagogastric junction 256 patients from a prospective database undergoing surgical resection after neoadjuvant treatment between 2003 and 2014 were evaluated. mGPS was scored as 0, 1, or 2 based on CRP (>1.0 mg/dl) and albumin (<35 g/L) from blood samples taken prior (preNT-mGPS) and after (postNT-mGPS) neoadjuvant therapy. Scores were correlated with clinicopathological patients’ characteristics. From 155 Patients, sufficient data was available. Median follow-up was 63.8 months (33.3–89.5 months). In univariate analysis, Cox proportional hazard model shows significant shorter patients OS (p = 0.04) and DFS (p = 0.02) for increased postNT-mGPS, preNT-hypoalbuminemia (OS: p = 0.003; DFS: p = 0.002) and post-NT-CRP (OS: p = 0.03; DFS: p = 0.04). Elevated postNT-mGPS and preNT-hypoalbuminemia remained significant prognostic factors in multivariate analysis for OS (p = 0.02; p = 0.005,) and DFS (p = 0.02, p = 0.004) with tumor differentiation and tumor staging as significant covariates. PostNT-mGPS and preNT-hypoalbuminemia are independent prognostic indicators in patients with neoadjuvantly treated adenocarcinomas of the esophagogastric junction and significantly associated with diminished OS and DFS. PMID:29467943

Red blood cell distribution width as a predictor of survival in nasal-type, extranodal natural killer/T-cell lymphoma

PubMed Central

He, Qiao; Cai, Shaolei; Li, Shi; Zeng, Jian; Zhang, Qing; Gao, Yu; Yu, Sisi

2017-01-01

We retrospectively enrolled 191 nasal-type, extranodal natural killer/T-cell lymphoma (ENKTL) patients newly diagnosed from 2008 to 2016 at the Sichuan Cancer Hospital, in order to evaluate the relationship between disease outcomes, demographic and clinical factors, and red blood cell distribution width (RDW). C-index, fisher's exact test, univariate analysis, and cox regression analysis were applied. The median age of patients was 44 years and 134 (70%) were men. The cutoff of RDW was 46.2 fL determined by Cutoff Finder. Patients with RDW≤46.2 fL had significantly better progression-free survival (PFS) (3-year PFS, 80.4% vs. 63.1%; P=0.01) and overall survival (OS) (3-year OS, 83.2% vs. 65.5%; P=0.004) than those with RDW>46.2 fL. Multivariate analysis demonstrated that elevated RDW is an independent adverse predictor of OS (P=0.021, HR=2.04). RDW is an independent predictor of survival outcomes in ENKTL, which we found to be superior to both the prognostic index of natural killer lymphoma (PINK) and the Korean Prognostic Index (KPI) in discriminating patients with different outcomes in low-risk and high-risk groups (all P < 0.05). The new models combining RDW with the International Prognostic Index (IPI), KPI, and PINK showed more powerful prognostic value than corresponding original models. RDW represents an easily available and inexpensive marker for risk stratification in patients with ENKTL treated with radiotherapy-based treatment. Further prospective studies are warranted to confirm the prognostic value of RDW in ENKTL. PMID:29190934

Red blood cell distribution width as a predictor of survival in nasal-type, extranodal natural killer/T-cell lymphoma.

PubMed

Luo, Huaichao; Quan, Xiaoying; Song, Xiao-Yu; Zhang, Li; Yin, Yilin; He, Qiao; Cai, Shaolei; Li, Shi; Zeng, Jian; Zhang, Qing; Gao, Yu; Yu, Sisi

2017-11-03

We retrospectively enrolled 191 nasal-type, extranodal natural killer/T-cell lymphoma (ENKTL) patients newly diagnosed from 2008 to 2016 at the Sichuan Cancer Hospital, in order to evaluate the relationship between disease outcomes, demographic and clinical factors, and red blood cell distribution width (RDW). C-index, fisher's exact test, univariate analysis, and cox regression analysis were applied. The median age of patients was 44 years and 134 (70%) were men. The cutoff of RDW was 46.2 fL determined by Cutoff Finder. Patients with RDW≤46.2 fL had significantly better progression-free survival (PFS) (3-year PFS, 80.4% vs. 63.1%; P =0.01) and overall survival (OS) (3-year OS, 83.2% vs. 65.5%; P =0.004) than those with RDW>46.2 fL. Multivariate analysis demonstrated that elevated RDW is an independent adverse predictor of OS ( P =0.021, HR=2.04). RDW is an independent predictor of survival outcomes in ENKTL, which we found to be superior to both the prognostic index of natural killer lymphoma (PINK) and the Korean Prognostic Index (KPI) in discriminating patients with different outcomes in low-risk and high-risk groups (all P < 0.05). The new models combining RDW with the International Prognostic Index (IPI), KPI, and PINK showed more powerful prognostic value than corresponding original models. RDW represents an easily available and inexpensive marker for risk stratification in patients with ENKTL treated with radiotherapy-based treatment. Further prospective studies are warranted to confirm the prognostic value of RDW in ENKTL.

Prognostic implications of preoperative anemia in urothelial carcinoma: A meta-analysis.

PubMed

Luo, Fei; Wang, Ya-Shen; Su, Yan-Hui; Zhang, Zhi-Hua; Sun, Hong-Hong; Li, Jian

2017-01-01

The prognostic significance of preoperative anemia (PA) has been identified in various malignancies. However, its predictive role in urothelial carcinoma (UC) remains controversial. The aim of this study was to investigate the prognostic value of PA in UC patients. We performed a meta-analysis of the association between PA and survival outcome in UC patients. Electronic databases were searched up to June 30, 2016. Study characteristics and prognostic data were extracted from each included study. Cancer-specific survival (CSS), recurrence-free survival (RFS), and overall survival (OS) were pooled using hazard ratio (HR) with corresponding 95% confidence intervals (CI). Herein, 12 studies comprising 3815 patients were included in the meta-analysis. There were 1593 (41.76%) patients in the PA group and 2222 (58.24%) in the control group. The overall pooled HRs of PA for CSS, RFS, and OS were significant at 2.21, (95% CI: 1.83-2.65, Pheterogeneity = 0.49, I2 = 0%), 1.87 (95% CI: 1.59-2.20, Pheterogeneity = 0.22, I2 = 28%), and 2.04(95% CI: 1.76-2.37, Pheterogeneity = 0.36, I2 = 9%) respectively. Stratified analyses indicated that PA was a predictor of poor prognosis based on ethnicity, sample size, tumor T stage, G grade, lymphovascular invasion (LVI), concomitant carcinoma in situ (CIS), and follow-up values. Our findings show that PA has negative prognostic effects on the survival outcome (CSS, RFS, and OS) in UC patients and can serve as a useful and cost-effective marker to aid prognosis prediction.

Prognostic implications of preoperative anemia in urothelial carcinoma: A meta-analysis

PubMed Central

Luo, Fei; Wang, Ya-Shen; Su, Yan-Hui; Zhang, Zhi-Hua; Sun, Hong-Hong; Li, Jian

2017-01-01

The prognostic significance of preoperative anemia (PA) has been identified in various malignancies. However, its predictive role in urothelial carcinoma (UC) remains controversial. The aim of this study was to investigate the prognostic value of PA in UC patients. We performed a meta-analysis of the association between PA and survival outcome in UC patients. Electronic databases were searched up to June 30, 2016. Study characteristics and prognostic data were extracted from each included study. Cancer-specific survival (CSS), recurrence-free survival (RFS), and overall survival (OS) were pooled using hazard ratio (HR) with corresponding 95% confidence intervals (CI). Herein, 12 studies comprising 3815 patients were included in the meta-analysis. There were 1593 (41.76%) patients in the PA group and 2222 (58.24%) in the control group. The overall pooled HRs of PA for CSS, RFS, and OS were significant at 2.21, (95% CI: 1.83–2.65, Pheterogeneity = 0.49, I2 = 0%), 1.87 (95% CI: 1.59–2.20, Pheterogeneity = 0.22, I2 = 28%), and 2.04(95% CI: 1.76–2.37, Pheterogeneity = 0.36, I2 = 9%) respectively. Stratified analyses indicated that PA was a predictor of poor prognosis based on ethnicity, sample size, tumor T stage, G grade, lymphovascular invasion (LVI), concomitant carcinoma in situ (CIS), and follow-up values. Our findings show that PA has negative prognostic effects on the survival outcome (CSS, RFS, and OS) in UC patients and can serve as a useful and cost-effective marker to aid prognosis prediction. PMID:28182725

Optical and Gravimetric Partitioning of Coastal Ocean Suspended Particulate Inorganic Matter (PIM)

NASA Astrophysics Data System (ADS)

Stavn, R. H.; Zhang, X.; Falster, A. U.; Gray, D. J.; Rick, J. J.; Gould, R. W., Jr.

2016-02-01

Recent work on the composition of suspended particulates of estuarine and coastal waters increases our capabilities to investigate the biogeochemal processes occurring in these waters. The biogeochemical properties associated with the particulates involve primarily sorption/desorption of dissolved matter onto the particle surfaces, which vary with the types of particulates. Therefore, the breakdown into chemical components of suspended matter will greatly expand the biogeochemistry of the coastal ocean region. The gravimetric techniques for these studies are here expanded and refined. In addition, new optical inversions greatly expand our capabilities to study spatial extent of the components of suspended particulate matter. The partitioning of a gravimetric PIM determination into clay minerals and amorphous silica is aided by electron microprobe analysis. The amorphous silica is further partitioned into contributions by detrital material and by the tests of living diatoms based on an empirical formula relating the chlorophyll content of cultured living diatoms in log phase growth to their frustules determined after gravimetric analysis of the ashed diatom residue. The optical inversion of composition of suspended particulates is based on the entire volume scattering function (VSF) measured in the field with a Multispectral Volume Scattering Meter and a LISST 100 meter. The VSF is partitioned into an optimal combination of contributions by particle subpopulations, each of which is uniquely represented by a refractive index and a log-normal size distribution. These subpopulations are aggregated to represent the two components of PIM using the corresponding refractive indices and sizes which also yield a particle size distribution for the two components. The gravimetric results of partitioning PIM into clay minerals and amorphous silica confirm the optical inversions from the VSF.

A Model-Based Prognostics Approach Applied to Pneumatic Valves

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Goebel, Kai

2011-01-01

Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.

pH recycling aqueous two-phase systems applied in extraction of Maitake β-Glucan and mechanism analysis using low-field nuclear magnetic resonance.

PubMed

Hou, Huiyun; Cao, Xuejun

2015-07-31

In this paper, a recycling aqueous two-phase systems (ATPS) based on two pH-response copolymers PADB and PMDM were used in purification of β-Glucan from Grifola frondosa. The main parameters, such as polymer concentration, type and concentration of salt, extraction temperature and pH, were investigated to optimize partition conditions. The results demonstrated that β-Glucan was extracted into PADB-rich phase, while impurities were extracted into PMDM-rich phase. In this 2.5% PADB/2.5% PMDM ATPS, 7.489 partition coefficient and 96.92% extraction recovery for β-Glucan were obtained in the presence of 30mmol/L KBr, at pH 8.20, 30°C. The phase-forming copolymers could be recycled by adjusting pH, with recoveries of over 96.0%. Furthermore, the partition mechanism of Maitake β-Glucan in PADB/PMDM aqueous two-phase systems was studied. Fourier transform infrared spectra, ForteBio Octet system and low-field nuclear magnetic resonance (LF-NMR) were introduced for elucidating the partition mechanism of β-Glucan. Especially, LF-NMR was firstly used in the mechanism analysis in partition of aqueous two-phase systems. The change of transverse relaxation time (T2) in ATPS could reflect the interaction between polymers and β-Glucan. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluating the Prognostic Value of microRNA-203 in Solid Tumors Based on a Meta-Analysis and the Cancer Genome Atlas (TCGA) Datasets.

PubMed

Shao, Yingjie; Gu, Wendong; Ning, Zhonghua; Song, Xing; Pei, Honglei; Jiang, Jingting

2017-01-01

It has been reported that miR-203 expression was aberrant in various types of cancers, and it could be used as a prognostic biomarker. Therefore, in this study, we aimed to evaluate the prognostic value of miR-203 expression in solid tumors by using meta-analysis and The Cancer Genome Atlas (TCGA) datasets. By doing a literature research in PubMed, Embase and the Cochrane Library (last update by December 2016), we were able to identify the studies assessing the prognostic role of miR-203 in various tumors. We then used TCGA datasets to validate the results of meta-analysis. 33 studies from 26 articles were qualified and enrolled in this meta-analysis. Pooled analyses showed that higher expression of miR-203 in tissues couldn't predict poor overall survival (OS) and progression-free survival (PFS) in solid tumors. However, the results of subgroup analyses revealed that the upregulation of tissue miR-203 expression was associated with poor OS in colorectal cancer (hazard ratio (HR)=1.81, 95% confidence intervals (CI) 1.31-2.49; P<0.001), pancreatic cancer (HR=1.19, 95% CI 1.09-1.31; P<0.001) and ovarian cancer (HR=1.85, 95% CI 1.45-2.37; P<0.001); but it had opposite association in liver cancer (HR=0.52, 95% CI 0.28-0.97; P=0.040) and esophageal cancer (HR=0.41, 95% CI 0.25-0.66; P<0.001). Based on TCGA datasets, we found the same results for pancreatic cancer and esophageal cancer, but not for colorectal cancer and liver cancer. Moreover, patients with high circulating miR-203 in blood had significantly poor OS and PFS in colorectal cancer and breast cancer. Our study showed that the prognostic values of tissue miR-203 varied in different tumor types. In addition, the upregulation of circulating miR-203 in blood was associated with poor prognosis in colorectal cancer and breast cancer. © 2017 The Author(s)Published by S. Karger AG, Basel.

Apparatus for chemical amplification based on fluid partitioning in an immiscible liquid

DOEpatents

Anderson, Brian L [Lodi, CA; Colston, Bill W [San Ramon, CA; Elkin, Christopher J [San Ramon, CA

2012-05-08

A system for nucleic acid amplification of a sample comprises partitioning the sample into partitioned sections and performing PCR on the partitioned sections of the sample. Another embodiment of the invention provides a system for nucleic acid amplification and detection of a sample comprising partitioning the sample into partitioned sections, performing PCR on the partitioned sections of the sample, and detecting and analyzing the partitioned sections of the sample.

Method for chemical amplification based on fluid partitioning in an immiscible liquid

DOEpatents

Anderson, Brian L.; Colston, Bill W.; Elkin, Christopher J.

2015-06-02

A system for nucleic acid amplification of a sample comprises partitioning the sample into partitioned sections and performing PCR on the partitioned sections of the sample. Another embodiment of the invention provides a system for nucleic acid amplification and detection of a sample comprising partitioning the sample into partitioned sections, performing PCR on the partitioned sections of the sample, and detecting and analyzing the partitioned sections of the sample.

Method for chemical amplification based on fluid partitioning in an immiscible liquid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, Brian L.; Colston, Bill W.; Elkin, Christopher J.

A system for nucleic acid amplification of a sample comprises partitioning the sample into partitioned sections and performing PCR on the partitioned sections of the sample. Another embodiment of the invention provides a system for nucleic acid amplification and detection of a sample comprising partitioning the sample into partitioned sections, performing PCR on the partitioned sections of the sample, and detecting and analyzing the partitioned sections of the sample.

A framework for quantifying net benefits of alternative prognostic models.

PubMed

Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

2012-01-30

New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd.

A framework for quantifying net benefits of alternative prognostic models‡

PubMed Central

Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

2012-01-01

New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21905066

[Prognostic value of three different staging schemes based on pN, MLR and LODDS in patients with T3 esophageal cancer].

PubMed

Wang, L; Cai, L; Chen, Q; Jiang, Y H

2017-10-23

Objective: To evaluate the prognostic value of three different staging schemes based on positive lymph nodes (pN), metastatic lymph nodes ratio (MLR) and log odds of positive lymph nodes (LODDS) in patients with T3 esophageal cancer. Methods: From 2007 to 2014, clinicopathological characteristics of 905 patients who were pathologically diagnosed as T3 esophageal cancer and underwent radical esophagectomy in Zhejiang Cancer Hospital were retrospectively analyzed. Kaplan-Meier curves and Multivariate Cox proportional hazards models were used to evaluate the independent prognostic factors. The values of three lymph node staging schemes for predicting 5-year survival were analyzed by using receiver operating characteristic (ROC) curves. Results: The 1-, 3- and 5-year overall survival rates of patients with T3 esophageal cancer were 80.9%, 50.0% and 38.4%, respectively. Multivariate analysis showed that MLR stage, LODDS stage and differentiation were independent prognostic survival factors ( P <0.05 for all). ROC curves showed that the area under the curve of pN stage, MLR stage, LODDS stage was 0.607, 0.613 and 0.618, respectively. However, the differences were not statistically significant ( P >0.05). Conclusions: LODDS is an independent prognostic factor for patients with T3 esophageal cancer. The value of LODDS staging system may be superior to pN staging system for evaluating the prognosis of these patients.

Construction of a new, objective prognostic score for terminally ill cancer patients: a multicenter study.

PubMed

Suh, Sang-Yeon; Choi, Youn Seon; Shim, Jae Yong; Kim, Young Sung; Yeom, Chang Hwan; Kim, Daeyoung; Park, Shin Ae; Kim, Sooa; Seo, Ji Yeon; Kim, Su Hyun; Kim, Daegyeun; Choi, Sung-Eun; Ahn, Hong-Yup

2010-02-01

The goal of this study was to develop a new, objective prognostic score (OPS) for terminally ill cancer patients based on an integrated model that includes novel objective prognostic factors. A multicenter study of 209 terminally ill cancer patients from six training hospitals in Korea were prospectively followed until death. The Cox proportional hazard model was used to adjust for the influence of clinical and laboratory variables on survival time. The OPS was calculated from the sum of partial scores obtained from seven significant predictors determined by the final model. The partial score was based on the hazard ratio of each predictor. The accuracy of the OPS was evaluated. The overall median survival was 26 days. On the multivariate analysis, reduced oral intake, resting dyspnea, low performance status, leukocytosis, elevated bilirubin, elevated creatinine, and elevated lactate dehydrogenase (LDH) were identified as poor prognostic factors. The range of OPS was from 0.0 to 7.0. For the above cutoff point of 3.0, the 3-week prediction sensitivity was 74.7%, the specificity was 76.5%, and the overall accuracy was 75.5%. We developed the new OPS, without clinician's survival estimates but including a new prognostic factor (LDH). This new instrument demonstrated accurate prediction of the 3-week survival. The OPS had acceptable accuracy in this study population (training set). Further validation is required on an independent population (testing set).

An Element-Based Concurrent Partitioner for Unstructured Finite Element Meshes

NASA Technical Reports Server (NTRS)

Ding, Hong Q.; Ferraro, Robert D.

1996-01-01

A concurrent partitioner for partitioning unstructured finite element meshes on distributed memory architectures is developed. The partitioner uses an element-based partitioning strategy. Its main advantage over the more conventional node-based partitioning strategy is its modular programming approach to the development of parallel applications. The partitioner first partitions element centroids using a recursive inertial bisection algorithm. Elements and nodes then migrate according to the partitioned centroids, using a data request communication template for unpredictable incoming messages. Our scalable implementation is contrasted to a non-scalable implementation which is a straightforward parallelization of a sequential partitioner.

Using Cox's proportional hazards model for prognostication in carcinoma of the upper aero-digestive tract.

PubMed

Wolfensberger, M

1992-01-01

One of the major short comings of the traditional TNM system is its limited potential for prognostication. With the development of multifactorial analysis techniques, such as Cox's proportional hazards model, it has become possible to simultaneously evaluate a large number of prognostic variables. Cox's model allows both the identification of prognostically relevant variables and the quantification of their prognostic influence. These characteristics make it a helpful tool for analysis as well as for prognostication. The goal of the present study was to develop a prognostic index for patients with carcinoma of the upper aero-digestive tract which makes use of all prognostically relevant variables. To accomplish this, the survival data of 800 patients with squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx or larynx were analyzed. Sixty-one variables were screened for prognostic significance; of these only 19 variables (including age, tumor location, T, N and M stages, resection margins, capsular invasion of nodal metastases, and treatment modality) were found to significantly correlate with prognosis. With the help of Cox's equation, a prognostic index (PI) was computed for every combination of prognostic factors. To test the proposed model, the prognostic index was applied to 120 patients with carcinoma of the oral cavity or oropharynx. A comparison of predicted and observed survival showed good overall correlation, although actual survival tended to be better than predicted.

Evaluation of 2 whole-brain radiotherapy schedules and prognostic factors for brain metastases in breast cancer patients.

PubMed

Rades, Dirk; Lohynska, Radka; Veninga, Theo; Stalpers, Lukas J A; Schild, Steven E

2007-12-01

The majority of breast cancer patients with brain metastases receive whole-brain radiotherapy (WBRT) and have a survival of only a few months. A short WBRT regimen would be preferable if it provides survival that is similar to that achieved with longer programs. This retrospective study compared survival and local control within the brain resulting from short-course WBRT with longer programs in 207 breast cancer patients. Sixty-nine patients treated with 5 fractions of 4 grays (Gy) each given within 5 days were compared with 138 patients treated with 10 fractions of 3 Gy each given over 2 weeks or 20 fractions of 2 Gy each given over 4 weeks. Six additional potential prognostic factors were investigated: age, Karnofsky performance score (KPS), number of brain metastases, the presence of extracranial metastases, interval from tumor diagnosis to WBRT, and recursive partitioning analysis (RPA) class. On univariate analysis, the WBRT regimen was not found to be associated with survival (P=.254) or local control (P=.397). Improved survival was associated with a KPS>70 (P<.001), single brain metastasis (P=.023), the absence of extracranial metastases (P<.001), and lower RPA class (P<.001). On multivariate analysis, which was performed without RPA class because this is a confounding variable, KPS (relative risk [RR] of 4.00; P<.001) and the presence of extracranial metastases (RR of 1.54; P=.024) maintained statistical significance. On univariate analysis, local control was associated with KPS (P<.001) and RPA class (P<.001). On multivariate analysis, local control was found to be associated with a KPS>70 (RR of 5.75; P<.001). Short-course WBRT with 5 fractions of 4 Gy each resulted in survival and local control that were similar to longer programs in breast cancer patients with brain metastases. The dose of 5 fractions of 4 Gy each appears preferable for the majority of these patients because it is less time consuming and more convenient. Copyright (c) 2007 American Cancer Society.

Predictive and Prognostic Factors in Definition of Risk Groups in Endometrial Carcinoma

PubMed Central

Sorbe, Bengt

2012-01-01

Background. The aim was to evaluate predictive and prognostic factors in a large consecutive series of endometrial carcinomas and to discuss pre- and postoperative risk groups based on these factors. Material and Methods. In a consecutive series of 4,543 endometrial carcinomas predictive and prognostic factors were analyzed with regard to recurrence rate and survival. The patients were treated with primary surgery and adjuvant radiotherapy. Two preoperative and three postoperative risk groups were defined. DNA ploidy was included in the definitions. Eight predictive or prognostic factors were used in multivariate analyses. Results. The overall recurrence rate of the complete series was 11.4%. Median time to relapse was 19.7 months. In a multivariate logistic regression analysis, FIGO grade, myometrial infiltration, and DNA ploidy were independent and statistically predictive factors with regard to recurrence rate. The 5-year overall survival rate was 73%. Tumor stage was the single most important factor with FIGO grade on the second place. DNA ploidy was also a significant prognostic factor. In the preoperative risk group definitions three factors were used: histology, FIGO grade, and DNA ploidy. Conclusions. DNA ploidy was an important and significant predictive and prognostic factor and should be used both in preoperative and postoperative risk group definitions. PMID:23209924

The Diagnostic and Prognostic Value of Hematological and Chemical Abnormalities in Soft Tissue Sarcoma: A Comparative Study in Patients with Benign and Malignant Soft Tissue Tumors.

PubMed

Ariizumi, Takashi; Kawashima, Hiroyuki; Ogose, Akira; Sasaki, Taro; Hotta, Tetsuo; Hatano, Hiroshi; Morita, Tetsuro; Endo, Naoto

2018-01-01

The value of routine blood tests in malignant soft tissue tumors remains uncertain. To determine if these tests can be used for screening, the routine pretreatment blood test findings were retrospectively investigated in 359 patients with benign and malignant soft tissue tumors. Additionally, the prognostic potential of pretreatment blood abnormalities was evaluated in patients with soft tissue sarcomas. We compared clinical factors and blood tests findings between patients with benign and malignant soft tissue tumors using univariate and multivariate analysis. Subsequently, patients with malignant tumors were divided into two groups based on blood test reference values, and the prognostic significance of each parameter was evaluated. In the univariate analysis, age, tumor size, and tumor depth were significant clinical diagnostic factors. Significant increases in the granulocyte count, C-reactive protein (CRP) level, erythrocyte sedimentation rate (ESR), and γ-glutamyl transpeptidase (γ-GTP) levels were found in patients with malignant soft tissue tumors. Multiple logistic regression showed that tumor size and ESR were independent factors that predicted malignant soft tissue tumors. The Kaplan-Meier survival analysis revealed that granulocyte counts, γ-GTP levels, and CRP levels correlated significantly with overall survival. Thus, pretreatment routine blood tests are useful diagnostic and prognostic markers for diagnosing soft tissue sarcoma. © 2018 by the Association of Clinical Scientists, Inc.

Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

NASA Astrophysics Data System (ADS)

Wang, Dong; Zhao, Yang; Yang, Fangfang; Tsui, Kwok-Leung

2017-09-01

Brownian motion with adaptive drift has attracted much attention in prognostics because its first hitting time is highly relevant to remaining useful life prediction and it follows the inverse Gaussian distribution. Besides linear degradation modeling, nonlinear-drifted Brownian motion has been developed to model nonlinear degradation. Moreover, the first hitting time distribution of the nonlinear-drifted Brownian motion has been approximated by time-space transformation. In the previous studies, the drift coefficient is the only hidden state used in state space modeling of the nonlinear-drifted Brownian motion. Besides the drift coefficient, parameters of a nonlinear function used in the nonlinear-drifted Brownian motion should be treated as additional hidden states of state space modeling to make the nonlinear-drifted Brownian motion more flexible. In this paper, a prognostic method based on nonlinear-drifted Brownian motion with multiple hidden states is proposed and then it is applied to predict remaining useful life of rechargeable batteries. 26 sets of rechargeable battery degradation samples are analyzed to validate the effectiveness of the proposed prognostic method. Moreover, some comparisons with a standard particle filter based prognostic method, a spherical cubature particle filter based prognostic method and two classic Bayesian prognostic methods are conducted to highlight the superiority of the proposed prognostic method. Results show that the proposed prognostic method has lower average prediction errors than the particle filter based prognostic methods and the classic Bayesian prognostic methods for battery remaining useful life prediction.

Phytochemistry of cimicifugic acids and associated bases in Cimicifuga racemosa root extracts.

PubMed

Gödecke, Tanja; Nikolic, Dejan; Lankin, David C; Chen, Shao-Nong; Powell, Sharla L; Dietz, Birgit; Bolton, Judy L; van Breemen, Richard B; Farnsworth, Norman R; Pauli, Guido F

2009-01-01

Earlier studies reported serotonergic activity for cimicifugic acids (CA) isolated from Cimicifuga racemosa. The discovery of strongly basic alkaloids, cimipronidines, from the active extract partition and evaluation of previously employed work-up procedures has led to the hypothesis of strong acid/base association in the extract. Re-isolation of the CAs was desired to permit further detailed studies. Based on the acid/base association hypothesis, a new separation scheme of the active partition was required, which separates acids from associated bases. A new 5-HT(7) bioassay guided work-up procedure was developed that concentrates activity into one partition. The latter was subjected to a new two-step centrifugal partitioning chromatography (CPC) method, which applies pH zone refinement gradient (pHZR CPC) to dissociate the acid/base complexes. The resulting CA fraction was subjected to a second CPC step. Fractions and compounds were monitored by (1)H NMR using a structure-based spin-pattern analysis facilitating dereplication of the known acids. Bioassay results were obtained for the pHZR CPC fractions and for purified CAs. A new CA was characterised. While none of the pure CAs was active, the serotonergic activity was concentrated in a single pHZR CPC fraction, which was subsequently shown to contain low levels of the potent 5-HT(7) ligand, N(omega)-methylserotonin. This study shows that CAs are not responsible for serotonergic activity in black cohosh. New phytochemical methodology (pHZR CPC) and a sensitive dereplication method (LC-MS) led to the identification of N(omega)-methylserotonin as serotonergic active principle. Copyright (c) 2009 John Wiley & Sons, Ltd.

Phytochemistry of Cimicifugic Acids and Associated Bases in Cimicifuga racemosa Root Extracts

PubMed Central

GÖdecke, Tanja; Nikolic, Dejan; Lankin, David C.; Chen, Shao-Nong; Powell, Sharla L.; Dietz, Birgit; Bolton, Judy L.; Van Breemen, Richard B.; Farnsworth, Norman R.; Pauli, Guido F.

2009-01-01

Introduction Earlier studies reported serotonergic activity for cimicifugic acids (CA) isolated from Cimicifuga racemosa. The discovery of strongly basic alkaloids, cimipronidines, from the active extract partition and evaluation of previously employed work-up procedures has led to the hypothesis of strong acid/base association in the extract. Objective Re-isolation of the CAs was desired to permit further detailed studies. Based on the acid/base association hypothesis, a new separation scheme of the active partition was required, which separates acids from associated bases. Methodology A new 5-HT7 bioassay guided work-up procedure was developed that concentrates activity into one partition. The latter was subjected to a new 2-step centrifugal partitioning chromatography (CPC) method, which applies pH zone refinement gradient (pHZR CPC) to dissociate the acid/base complexes. The resulting CA fraction was subjected to a second CPC step. Fractions and compounds were monitored by 1H NMR using a structure based spin-pattern analysis facilitating dereplication of the known acids. Bioassay results were obtained for the pHZR CPC fractions and for purified CAs. Results A new CA was characterized. While none of the pure CAs was active, the serotonergic activity was concentrated in a single pHZR CPC fraction, which was subsequently shown to contain low levels of the potent 5-HT7 ligand, Nω–methylserotonin. Conclusion This study shows that CAs are not responsible for serotonergic activity in black cohosh. New phytochemical methodology (pHZR CPC) and a sensitive dereplication method (LC-MS) led to the identification of Nω–methylserotonin as serotonergic active principle. PMID:19140115

Rational bases for the use of the Immunoscore in routine clinical settings as a prognostic and predictive biomarker in cancer patients

PubMed Central

Kirilovsky, Amos; Marliot, Florence; El Sissy, Carine; Haicheur, Nacilla; Galon, Jérôme

2016-01-01

The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) tumor, nodes, metastasis (TNM) classification system based on tumor features is used for prognosis estimation and treatment recommendations in most cancers. However, the clinical outcome can vary significantly among patients within the same tumor stage and TNM classification does not predict response to therapy. Therefore, many efforts have been focused on the identification of new markers. Multiple tumor cell-based approaches have been proposed but very few have been translated into the clinic. The recent demonstration of the essential role of the immune system in tumor progression has allowed great advances in the understanding of this complex disease and in the design of novel therapies. The analysis of the immune infiltrate by imaging techniques in large patient cohorts highlighted the prognostic impact of the in situ immune cell infiltrate in tumors. Moreover, the characterization of the immune infiltrates (e.g. type, density, distribution within the tumor, phenotype, activation status) in patients treated with checkpoint-blockade strategies could provide information to predict the disease outcome. In colorectal cancer, we have developed a prognostic score (‘Immunoscore’) that takes into account the distribution of the density of both CD3+ lymphocytes and CD8+ cytotoxic T cells in the tumor core and the invasive margin that could outperform TNM staging. Currently, an international retrospective study is under way to validate the Immunoscore prognostic performance in patients with colon cancer. The use of Immunoscore in clinical practice could improve the patients’ prognostic assessment and therapeutic management. PMID:27121213

Comparative effectiveness of incorporating a hypothetical DCIS prognostic marker into breast cancer screening.

PubMed

Trentham-Dietz, Amy; Ergun, Mehmet Ali; Alagoz, Oguzhan; Stout, Natasha K; Gangnon, Ronald E; Hampton, John M; Dittus, Kim; James, Ted A; Vacek, Pamela M; Herschorn, Sally D; Burnside, Elizabeth S; Tosteson, Anna N A; Weaver, Donald L; Sprague, Brian L

2018-02-01

Due to limitations in the ability to identify non-progressive disease, ductal carcinoma in situ (DCIS) is usually managed similarly to localized invasive breast cancer. We used simulation modeling to evaluate the potential impact of a hypothetical test that identifies non-progressive DCIS. A discrete-event model simulated a cohort of U.S. women undergoing digital screening mammography. All women diagnosed with DCIS underwent the hypothetical DCIS prognostic test. Women with test results indicating progressive DCIS received standard breast cancer treatment and a decrement to quality of life corresponding to the treatment. If the DCIS test indicated non-progressive DCIS, no treatment was received and women continued routine annual surveillance mammography. A range of test performance characteristics and prevalence of non-progressive disease were simulated. Analysis compared discounted quality-adjusted life years (QALYs) and costs for test scenarios to base-case scenarios without the test. Compared to the base case, a perfect prognostic test resulted in a 40% decrease in treatment costs, from $13,321 to $8005 USD per DCIS case. A perfect test produced 0.04 additional QALYs (16 days) for women diagnosed with DCIS, added to the base case of 5.88 QALYs per DCIS case. The results were sensitive to the performance characteristics of the prognostic test, the proportion of DCIS cases that were non-progressive in the model, and the frequency of mammography screening in the population. A prognostic test that identifies non-progressive DCIS would substantially reduce treatment costs but result in only modest improvements in quality of life when averaged over all DCIS cases.

Prognostic value of Ki-67 index in adult medulloblastoma after accounting for molecular subgroup: a retrospective clinical and molecular analysis.

PubMed

Zhao, Fu; Zhang, Jing; Li, Peng; Zhou, Qiangyi; Zhang, Shun; Zhao, Chi; Wang, Bo; Yang, Zhijun; Li, Chunde; Liu, Pinan

2018-04-23

Medulloblastoma (MB) is a rare primary brain tumor in adults. We previously evaluated that combining both clinical and molecular classification could improve current risk stratification for adult MB. In this study, we aimed to identify the prognostic value of Ki-67 index in adult MB. Ki-67 index of 51 primary adult MBs was reassessed using a computer-based image analysis (Image-Pro Plus). All patients were followed up ranging from 12 months up to 15 years. Gene expression profiling and immunochemistry were used to establish the molecular subgroups in adult MB. Combined risk stratification models were designed based on clinical characteristics, molecular classification and Ki-67 index, and identified by multivariable Cox proportional hazards analysis. In our cohort, the mean Ki-67 value was 30.0 ± 11.3% (range 6.56-63.55%). The average Ki-67 value was significantly higher in LC/AMB than in CMB and DNMB (P = .001). Among three molecular subgroups, Group 4-tumors had the highest average Ki-67 value compared with WNT- and SHH-tumors (P = .004). Patients with Ki-67 index large than 30% displayed poorer overall survival (OS) and progression free survival (PFS) than those with Ki-67 less than 30% (OS: P = .001; PFS: P = .006). Ki-67 index (i.e. > 30%, < 30%) was identified as an independent significant prognostic factor (OS: P = .017; PFS: P = .024) by using multivariate Cox proportional hazards model. In conclusion, Ki-67 index can be considered as a valuable independent prognostic biomarker for adult patients with MB.

Model‐based analysis of the influence of catchment properties on hydrologic partitioning across five mountain headwater subcatchments

PubMed Central

Wagener, Thorsten; McGlynn, Brian

2015-01-01

Abstract Ungauged headwater basins are an abundant part of the river network, but dominant influences on headwater hydrologic response remain difficult to predict. To address this gap, we investigated the ability of a physically based watershed model (the Distributed Hydrology‐Soil‐Vegetation Model) to represent controls on metrics of hydrologic partitioning across five adjacent headwater subcatchments. The five study subcatchments, located in Tenderfoot Creek Experimental Forest in central Montana, have similar climate but variable topography and vegetation distribution. This facilitated a comparative hydrology approach to interpret how parameters that influence partitioning, detected via global sensitivity analysis, differ across catchments. Model parameters were constrained a priori using existing regional information and expert knowledge. Influential parameters were compared to perceptions of catchment functioning and its variability across subcatchments. Despite between‐catchment differences in topography and vegetation, hydrologic partitioning across all metrics and all subcatchments was sensitive to a similar subset of snow, vegetation, and soil parameters. Results also highlighted one subcatchment with low certainty in parameter sensitivity, indicating that the model poorly represented some complexities in this subcatchment likely because an important process is missing or poorly characterized in the mechanistic model. For use in other basins, this method can assess parameter sensitivities as a function of the specific ungauged system to which it is applied. Overall, this approach can be employed to identify dominant modeled controls on catchment response and their agreement with system understanding. PMID:27642197

Acute lymphoblastic leukemia in children and adolescents: prognostic factors and analysis of survival

PubMed Central

Lustosa de Sousa, Daniel Willian; de Almeida Ferreira, Francisco Valdeci; Cavalcante Félix, Francisco Helder; de Oliveira Lopes, Marcos Vinicios

2015-01-01

Objective To describe the clinical and laboratory features of children and adolescents with acute lymphoblastic leukemia treated at three referral centers in Ceará and evaluate prognostic factors for survival, including age, gender, presenting white blood cell count, immunophenotype, DNA index and early response to treatment. Methods Seventy-six under 19-year-old patients with newly diagnosed acute lymphoblastic leukemia treated with the Grupo Brasileiro de Tratamento de Leucemia da Infância – acute lymphoblastic leukemia-93 and -99 protocols between September 2007 and December 2009 were analyzed. The diagnosis was based on cytological, immunophenotypic and cytogenetic criteria. Associations between variables, prognostic factors and response to treatment were analyzed using the chi-square test and Fisher's exact test. Overall and event-free survival were estimated by Kaplan–Meier analysis and compared using the log-rank test. A Cox proportional hazards model was used to identify independent prognostic factors. Results The average age at diagnosis was 6.3 ± 0.5 years and males were predominant (65%). The most frequently observed clinical features were hepatomegaly, splenomegaly and lymphadenopathy. Central nervous system involvement and mediastinal enlargement occurred in 6.6% and 11.8%, respectively. B-acute lymphoblastic leukemia was more common (89.5%) than T-acute lymphoblastic leukemia. A DNA index >1.16 was found in 19% of patients and was associated with favorable prognosis. On Day 8 of induction therapy, 95% of the patients had lymphoblast counts <1000/μL and white blood cell counts <5.0 × 109/L. The remission induction rate was 95%, the induction mortality rate was 2.6% and overall survival was 72%. Conclusion The prognostic factors identified are compatible with the literature. The 5-year overall and event-free survival rates were lower than those reported for developed countries. As shown by the multivariate analysis, age and baseline white blood cell count were independent prognostic factors. PMID:26190424

On N = 1 partition functions without R-symmetry

DOE PAGES

Knodel, Gino; Liu, James T.; Zayas, Leopoldo A. Pando

2015-03-25

Here, we examine the dependence of four-dimensional Euclidean N = 1 partition functions on coupling constants. In particular, we focus on backgrounds without R-symmetry, which arise in the rigid limit of old minimal supergravity. Backgrounds preserving a single supercharge may be classified as having either trivial or SU(2) structure, with the former including S 4. We show that, in the absence of additional symmetries, the partition function depends non-trivially on all couplings in the trivial structure case, and (anti)-holomorphically on couplings in the SU(2) structure case. In both cases, this allows for ambiguities in the form of finite counterterms, whichmore » in principle render the partition function unphysical. However, we argue that on dimensional grounds, ambiguities are restricted to finite powers in relevant couplings, and can therefore be kept under control. On the other hand, for backgrounds preserving supercharges of opposite chiralities, the partition function is completely independent of all couplings. In this case, the background admits an R-symmetry, and the partition function is physical, in agreement with the results obtained in the rigid limit of new minimal supergravity. Based on a systematic analysis of supersymmetric invariants, we also demonstrate that N = 1 localization is not possible for backgrounds without R-symmetry.« less

Predicting cannabis abuse screening test (CAST) scores: a recursive partitioning analysis using survey data from Czech Republic, Italy, the Netherlands and Sweden.

PubMed

Blankers, Matthijs; Frijns, Tom; Belackova, Vendula; Rossi, Carla; Svensson, Bengt; Trautmann, Franz; van Laar, Margriet

2014-01-01

Cannabis is Europe's most commonly used illicit drug. Some users do not develop dependence or other problems, whereas others do. Many factors are associated with the occurrence of cannabis-related disorders. This makes it difficult to identify key risk factors and markers to profile at-risk cannabis users using traditional hypothesis-driven approaches. Therefore, the use of a data-mining technique called binary recursive partitioning is demonstrated in this study by creating a classification tree to profile at-risk users. 59 variables on cannabis use and drug market experiences were extracted from an internet-based survey dataset collected in four European countries (Czech Republic, Italy, Netherlands and Sweden), n = 2617. These 59 potential predictors of problematic cannabis use were used to partition individual respondents into subgroups with low and high risk of having a cannabis use disorder, based on their responses on the Cannabis Abuse Screening Test. Both a generic model for the four countries combined and four country-specific models were constructed. Of the 59 variables included in the first analysis step, only three variables were required to construct a generic partitioning model to classify high risk cannabis users with 65-73% accuracy. Based on the generic model for the four countries combined, the highest risk for cannabis use disorder is seen in participants reporting a cannabis use on more than 200 days in the last 12 months. In comparison to the generic model, the country-specific models led to modest, non-significant improvements in classification accuracy, with an exception for Italy (p = 0.01). Using recursive partitioning, it is feasible to construct classification trees based on only a few variables with acceptable performance to classify cannabis users into groups with low or high risk of meeting criteria for cannabis use disorder. The number of cannabis use days in the last 12 months is the most relevant variable. The identified variables may be considered for use in future screeners for cannabis use disorders.

Support vector methods for survival analysis: a comparison between ranking and regression approaches.

PubMed

Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

2011-10-01

To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods including only regression or both regression and ranking constraints on clinical data. On high dimensional data, the former model performs better. However, this approach does not have a theoretical link with standard statistical models for survival data. This link can be made by means of transformation models when ranking constraints are included. Copyright © 2011 Elsevier B.V. All rights reserved.

A stable partitioned FSI algorithm for rigid bodies and incompressible flow. Part I: Model problem analysis

NASA Astrophysics Data System (ADS)

Banks, J. W.; Henshaw, W. D.; Schwendeman, D. W.; Tang, Qi

2017-08-01

A stable partitioned algorithm is developed for fluid-structure interaction (FSI) problems involving viscous incompressible flow and rigid bodies. This added-mass partitioned (AMP) algorithm remains stable, without sub-iterations, for light and even zero mass rigid bodies when added-mass and viscous added-damping effects are large. The scheme is based on a generalized Robin interface condition for the fluid pressure that includes terms involving the linear acceleration and angular acceleration of the rigid body. Added-mass effects are handled in the Robin condition by inclusion of a boundary integral term that depends on the pressure. Added-damping effects due to the viscous shear forces on the body are treated by inclusion of added-damping tensors that are derived through a linearization of the integrals defining the force and torque. Added-damping effects may be important at low Reynolds number, or, for example, in the case of a rotating cylinder or rotating sphere when the rotational moments of inertia are small. In this first part of a two-part series, the properties of the AMP scheme are motivated and evaluated through the development and analysis of some model problems. The analysis shows when and why the traditional partitioned scheme becomes unstable due to either added-mass or added-damping effects. The analysis also identifies the proper form of the added-damping which depends on the discrete time-step and the grid-spacing normal to the rigid body. The results of the analysis are confirmed with numerical simulations that also demonstrate a second-order accurate implementation of the AMP scheme.

A new machine-learning method to prognosticate paraquat poisoned patients by combining coagulation, liver, and kidney indices.

PubMed

Hu, Lufeng; Li, Huaizhong; Cai, Zhennao; Lin, Feiyan; Hong, Guangliang; Chen, Huiling; Lu, Zhongqiu

2017-01-01

The prognosis of paraquat (PQ) poisoning is highly correlated to plasma PQ concentration, which has been identified as the most important index in PQ poisoning. This study investigated the predictive value of coagulation, liver, and kidney indices in prognosticating PQ-poisoning patients, when aligned with plasma PQ concentrations. Coagulation, liver, and kidney indices were first analyzed by variance analysis, receiver operating characteristic curves, and Fisher discriminant analysis. Then, a new, intelligent, machine learning-based system was established to effectively provide prognostic analysis of PQ-poisoning patients based on a combination of the aforementioned indices. In the proposed system, an enhanced extreme learning machine wrapped with a grey wolf-optimization strategy was developed to predict the risk status from a pool of 103 patients (56 males and 47 females); of these, 52 subjects were deceased and 51 alive. The proposed method was rigorously evaluated against this real-life dataset, in terms of accuracy, Matthews correlation coefficients, sensitivity, and specificity. Additionally, the feature selection was investigated to identify correlating factors for risk status. The results demonstrated that there were significant differences in the coagulation, liver, and kidney indices between deceased and surviving subjects (p<0.05). Aspartate aminotransferase, prothrombin time, prothrombin activity, total bilirubin, direct bilirubin, indirect bilirubin, alanine aminotransferase, urea nitrogen, and creatinine were the most highly correlated indices in PQ poisoning and showed statistical significance (p<0.05) in predicting PQ-poisoning prognoses. According to the feature selection, the most important correlated indices were found to be associated with aspartate aminotransferase, the aspartate aminotransferase to alanine ratio, creatinine, prothrombin time, and prothrombin activity. The method proposed here showed excellent results that were better than that produced based on blood-PQ concentration alone. These promising results indicated that the combination of these indices can provide a new avenue for prognosticating the outcome of PQ poisoning.

Refining prognosis in lung cancer: A report on the quality and relevance of clinical prognostic tools

PubMed Central

Mahar, Alyson L.; Compton, Carolyn; McShane, Lisa M.; Halabi, Susan; Asamura, Hisao; Rami-Porta, Ramon; Groome, Patti A.

2015-01-01

Introduction Accurate, individualized prognostication for lung cancer patients requires the integration of standard patient and pathologic factors, biologic, genetic, and other molecular characteristics of the tumor. Clinical prognostic tools aim to aggregate information on an individual patient to predict disease outcomes such as overall survival, but little is known about their clinical utility and accuracy in lung cancer. Methods A systematic search of the scientific literature for clinical prognostic tools in lung cancer published Jan 1, 1996-Jan 27, 2015 was performed. In addition, web-based resources were searched. A priori criteria determined by the Molecular Modellers Working Group of the American Joint Committee on Cancer were used to investigate the quality and usefulness of tools. Criteria included clinical presentation, model development approaches, validation strategies, and performance metrics. Results Thirty-two prognostic tools were identified. Patients with metastases were the most frequently considered population in non-small cell lung cancer. All tools for small cell lung cancer covered that entire patient population. Included prognostic factors varied considerably across tools. Internal validity was not formally evaluated for most tools and only eleven were evaluated for external validity. Two key considerations were highlighted for tool development: identification of an explicit purpose related to a relevant clinical population and clear decision-points, and prioritized inclusion of established prognostic factors over emerging factors. Conclusions Prognostic tools will contribute more meaningfully to the practice of personalized medicine if better study design and analysis approaches are used in their development and validation. PMID:26313682

Correlation Between Magnetic Resonance Imaging-Based Evaluation of Extramural Vascular Invasion and Prognostic Parameters of T3 Stage Rectal Cancer.

PubMed

Yu, Jing; Huang, Dong-Ya; Xu, Hui-Xin; Li, Yang; Xu, Qing

2016-01-01

The aim of this study was to analyze the correlation between magnetic resonance imaging-based extramural vascular invasion (EMVI) and the prognostic clinical and histological parameters of stage T3 rectal cancers. Eighty-six patients with T3 stage rectal cancer who received surgical resection without neoadjuvant therapy were included. Magnetic resonance imaging-based EMVI scores were determined. Correlations between the scores and pretreatment carcinoembryonic antigen levels, tumor differentiation grade, nodal stage, and vascular endothelial growth factor expression were analyzed using Spearman rank coefficient analysis. Magnetic resonance imaging-based EMVI scores were statistically different (P = 0.001) between histological nodal stages (N0 vs N1 vs N2). Correlations were found between magnetic resonance imaging-based EMVI scores and tumor histological grade (rs = 0.227, P = 0.035), histological nodal stage (rs = 0.524, P < 0.001), and vascular endothelial growth factor expression (rs = 0.422; P = 0.016). Magnetic resonance imaging-based EMVI score is correlated with prognostic parameters of T3 stage rectal cancers and has the potential to become an imaging biomarker of tumor aggressiveness. Magnetic resonance imaging-based EMVI may be useful in helping the multidisciplinary team to stratify T3 rectal cancer patients for neoadjuvant therapies.

Clinical implications of six inflammatory biomarkers as prognostic indicators in Ewing sarcoma

PubMed Central

Li, Yong-Jiang; Yang, Xi; Zhang, Wen-Biao; Yi, Cheng; Wang, Feng; Li, Ping

2017-01-01

Cancer-related systemic inflammation responses have been correlated with cancer development and progression. The prognostic significance of several inflammatory indicators, including neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), Glasgow Prognostic Score (GPS), C-reactive protein to albumin ratio (CRP/Alb ratio), lymphocyte–monocyte ratio (LMR), and neutrophil–platelet score (NPS), were found to be correlated with prognosis in several cancers. However, the prognostic role of these inflammatory biomarkers in Ewing sarcoma has not been evaluated. This study enrolled 122 Ewing patients. Receiver operating characteristic (ROC) analysis was generated to determine optimal cutoff values; areas under the curves (AUCs) were assessed to show the discriminatory ability of the biomarkers; Kaplan–Meier analysis was conducted to plot the survival curves; and Cox multivariate survival analysis was performed to identify independent prognostic factors. The optimal cutoff values of CRP/Alb ratio, NLR, PLR, and LMR were 0.225, 2.38, 131, and 4.41, respectively. CRP/Alb ratio had a significantly larger AUC than NLR, PLR, LMR, and NPS. Higher levels of CRP/Alb ratio (hazard ratio [HR] 2.41, P=0.005), GPS (HR 2.27, P=0.006), NLR (HR 2.07, P=0.013), and PLR (HR 1.85, P=0.032) were significantly correlated with poor prognosis. As the biomarkers had internal correlations, only the CRP/Alb ratio was involved in the multivariate Cox analysis and remained an independent prognostic indicator. The study demonstrated that CRP/Alb ratio, GPS, and NLR were effective prognostic indicators for patients with Ewing sarcoma, and the CRP/Alb ratio was the most robust prognostic indicator with a discriminatory ability superior to that of the other indicators; however, PLR, LMR, and NPS may not be suitable as prognostic indicators in Ewing sarcoma. PMID:29033609

Towards Prognostics of Power MOSFETs: Accelerated Aging and Precursors of Failure

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saxena, Abhinav; Wysocki, Philip; Saha, Sankalita; Goebel, Kai

2010-01-01

This paper presents research results dealing with power MOSFETs (metal oxide semiconductor field effect transistor) within the prognostics and health management of electronics. Experimental results are presented for the identification of the on-resistance as a precursor to failure of devices with die-attach degradation as a failure mechanism. Devices are aged under power cycling in order to trigger die-attach damage. In situ measurements of key electrical and thermal parameters are collected throughout the aging process and further used for analysis and computation of the on-resistance parameter. Experimental results show that the devices experience die-attach damage and that the on-resistance captures the degradation process in such a way that it could be used for the development of prognostics algorithms (data-driven or physics-based).

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

Microstructural evolution during quenching and partitioning of 0.2C-1.5Mn-1.3Si steels with Cr or Ni additions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierce, Dean T.; Coughlin, D. R.; Clarke, Kester D.

Here, the influence of Cr and Ni additions and quench and partition (Q&P) processing parameters on the microstructural development, including carbide formation and austenite retention during Q&P, was studied in two steels with a base composition of 0.2C-1.5Mn-1.3Si wt.% and additions of 1.5 wt.% Cr (1.5Cr) or Ni (1.5Ni). Additions of 1.5 wt.% Cr significantly slowed the kinetics of austenite decomposition relative to the 1.5Ni alloy at all partitioning temperatures, promoting greater austenite retention, lower retained austenite carbon (C) contents, and reduced sensitivity of the retained austenite amounts to processing variables. In the 1.5Cr alloy after partitioning at 400 °Cmore » for 300 s, η-carbides were identified by transmission electron microscopy (TEM) and atom probe tomography (APT) revealed no significant enrichment of substitutional elements in the carbides. In the 1.5Ni alloy after partitioning at 450 °C for 300 s, both plate-like and globular carbides were observed by TEM. APT analysis of the globular carbides clearly revealed significant Si rejection and Mn enrichment. Mössbauer effect spectroscopy was used to quantify the amount of carbides after Q&P. In general, carbide amounts below ~0.3% of Fe were measured in both alloys after partitioning for short times (10 s), irrespective of quench or partitioning temperature, which corresponds to a relatively small portion of the bulk C. With increasing partitioning time, carbide amounts remained approximately constant or increased, depending on the alloy, quench temperature, and/or partitioning temperature.« less

Microstructural evolution during quenching and partitioning of 0.2C-1.5Mn-1.3Si steels with Cr or Ni additions

DOE PAGES

Pierce, Dean T.; Coughlin, D. R.; Clarke, Kester D.; ...

2018-03-08

Here, the influence of Cr and Ni additions and quench and partition (Q&P) processing parameters on the microstructural development, including carbide formation and austenite retention during Q&P, was studied in two steels with a base composition of 0.2C-1.5Mn-1.3Si wt.% and additions of 1.5 wt.% Cr (1.5Cr) or Ni (1.5Ni). Additions of 1.5 wt.% Cr significantly slowed the kinetics of austenite decomposition relative to the 1.5Ni alloy at all partitioning temperatures, promoting greater austenite retention, lower retained austenite carbon (C) contents, and reduced sensitivity of the retained austenite amounts to processing variables. In the 1.5Cr alloy after partitioning at 400 °Cmore » for 300 s, η-carbides were identified by transmission electron microscopy (TEM) and atom probe tomography (APT) revealed no significant enrichment of substitutional elements in the carbides. In the 1.5Ni alloy after partitioning at 450 °C for 300 s, both plate-like and globular carbides were observed by TEM. APT analysis of the globular carbides clearly revealed significant Si rejection and Mn enrichment. Mössbauer effect spectroscopy was used to quantify the amount of carbides after Q&P. In general, carbide amounts below ~0.3% of Fe were measured in both alloys after partitioning for short times (10 s), irrespective of quench or partitioning temperature, which corresponds to a relatively small portion of the bulk C. With increasing partitioning time, carbide amounts remained approximately constant or increased, depending on the alloy, quench temperature, and/or partitioning temperature.« less

Preoperative serum lipids as prognostic predictors in esophageal squamous cell carcinoma patients with esophagectomy.

PubMed

Chen, Pengxiang; Han, Lihui; Wang, Cong; Jia, Yibin; Song, Qingxu; Wang, Jianbo; Guan, Shanghui; Tan, Bingxu; Liu, Bowen; Jia, Wenqiao; Cui, Jianfeng; Zhou, Wei; Cheng, Yufeng

2017-06-20

This study was to evaluate the prognostic significance of serum lipids in esophageal squamous cell carcinoma patients who underwent esophagectomy. Preoperative serum lipids were collected from 214 patients who were diagnosed with esophageal squamous cell carcinoma. All of the patients received esophagectomy in Qilu Hospital of Shandong University from January 2007 to December 2008. The records and data were analyzed retrospectively. We found that low total cholesterol (for T stage, p = 0.006; for TNM stage, p = 0.039) and low-density lipoprotein cholesterol (for T stage, p = 0.031; for TNM stage, p = 0.035) were associated with advanced T stage and TNM stage. Kaplan-Meier survival analysis indicated that low total cholesterol and low-density lipoprotein cholesterol were associated with shorter disease-free survival(for total cholesterol, p = 0.045; for low-density lipoprotein cholesterol, p < 0.001) and overall survival (for total cholesterol, p = 0.043; for low-density lipoprotein cholesterol, p < 0.001). Lower low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratio (LHR) indicated poorer disease-free survival and overall survival (both p < 0.001). In the multivariate analysis, low-density lipoprotein cholesterol and LHR were independent prognostic factors for disease-free survival and overall survival. In conclusion, our study indicated that preoperative serum total cholesterol and low-density lipoprotein cholesterol are prognostic factors for esophageal squamous cell carcinoma patients who underwent esophagectomy. LHR can serve as a promising serum lipids-based prognostic indicator.

Evaluating surrogate endpoints, prognostic markers, and predictive markers — some simple themes

PubMed Central

Baker, Stuart G.; Kramer, Barnett S.

2014-01-01

Background A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. Methods We organized our discussion around a different theme for each topic. Results “Fundamentally an extrapolation” refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. “Decision analysis to the rescue” refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. “The appeal of simplicity” refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. Conclusion The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. PMID:25385934

Nailfold capillaroscopy for day-to-day clinical use: construction of a simple scoring modality as a clinical prognostic index for digital trophic lesions.

PubMed

Smith, Vanessa; De Keyser, Filip; Pizzorni, Carmen; Van Praet, Jens T; Decuman, Saskia; Sulli, Alberto; Deschepper, Ellen; Cutolo, Maurizio

2011-01-01

Construction of a simple nailfold videocapillaroscopic (NVC) scoring modality as a prognostic index for digital trophic lesions for day-to-day clinical use. An association with a single simple (semi)-quantitatively scored NVC parameter, mean score of capillary loss, was explored in 71 consecutive patients with systemic sclerosis (SSc), and reliable reduction in the number of investigated fields (F32-F16-F8-F4). The cut-off value of the prognostic index (mean score of capillary loss calculated over a reduced number of fields) for present/future digital trophic lesions was selected by receiver operating curve (ROC) analysis. Reduction in the number of fields for mean score of capillary loss was reliable from F32 to F8 (intraclass correlation coefficient of F16/F32: 0.97; F8/F32: 0.90). Based on ROC analysis, a prognostic index (mean score of capillary loss as calculated over F8) with a cut-off value of 1.67 is proposed. This value has a sensitivity of 72.22/70.00, specificity of 70.59/69.77, positive likelihood ratio of 2.46/2.32 and a negative likelihood ratio of 0.39/0.43 for present/future digital trophic lesions. A simple prognostic index for digital trophic lesions for daily use in SSc clinics is proposed, limited to the mean score of capillary loss as calculated over eight fields (8 fingers, 1 field per finger).

Time-dependent summary receiver operating characteristics for meta-analysis of prognostic studies.

PubMed

Hattori, Satoshi; Zhou, Xiao-Hua

2016-11-20

Prognostic studies are widely conducted to examine whether biomarkers are associated with patient's prognoses and play important roles in medical decisions. Because findings from one prognostic study may be very limited, meta-analyses may be useful to obtain sound evidence. However, prognostic studies are often analyzed by relying on a study-specific cut-off value, which can lead to difficulty in applying the standard meta-analysis techniques. In this paper, we propose two methods to estimate a time-dependent version of the summary receiver operating characteristics curve for meta-analyses of prognostic studies with a right-censored time-to-event outcome. We introduce a bivariate normal model for the pair of time-dependent sensitivity and specificity and propose a method to form inferences based on summary statistics reported in published papers. This method provides a valid inference asymptotically. In addition, we consider a bivariate binomial model. To draw inferences from this bivariate binomial model, we introduce a multiple imputation method. The multiple imputation is found to be approximately proper multiple imputation, and thus the standard Rubin's variance formula is justified from a Bayesian view point. Our simulation study and application to a real dataset revealed that both methods work well with a moderate or large number of studies and the bivariate binomial model coupled with the multiple imputation outperforms the bivariate normal model with a small number of studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Zone-size nonuniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer.

PubMed

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Lee, Li-yu; Chang, Joseph Tung-Chieh; Tsan, Din-Li; Ng, Shu-Hang; Wang, Hung-Ming; Liao, Chun-Ta; Yang, Lan-Yan; Hsu, Ching-Han; Yen, Tzu-Chen

2015-03-01

The question as to whether the regional textural features extracted from PET images predict prognosis in oropharyngeal squamous cell carcinoma (OPSCC) remains open. In this study, we investigated the prognostic impact of regional heterogeneity in patients with T3/T4 OPSCC. We retrospectively reviewed the records of 88 patients with T3 or T4 OPSCC who had completed primary therapy. Progression-free survival (PFS) and disease-specific survival (DSS) were the main outcome measures. In an exploratory analysis, a standardized uptake value of 2.5 (SUV 2.5) was taken as the cut-off value for the detection of tumour boundaries. A fixed threshold at 42 % of the maximum SUV (SUVmax 42 %) and an adaptive threshold method were then used for validation. Regional textural features were extracted from pretreatment (18)F-FDG PET/CT images using the grey-level run length encoding method and grey-level size zone matrix. The prognostic significance of PET textural features was examined using receiver operating characteristic (ROC) curves and Cox regression analysis. Zone-size nonuniformity (ZSNU) was identified as an independent predictor of PFS and DSS. Its prognostic impact was confirmed using both the SUVmax 42 % and the adaptive threshold segmentation methods. Based on (1) total lesion glycolysis, (2) uniformity (a local scale texture parameter), and (3) ZSNU, we devised a prognostic stratification system that allowed the identification of four distinct risk groups. The model combining the three prognostic parameters showed a higher predictive value than each variable alone. ZSNU is an independent predictor of outcome in patients with advanced T-stage OPSCC, and may improve their prognostic stratification.

Immunoscore encompassing CD3+ and CD8+ T cell densities in distant metastasis is a robust prognostic marker for advanced colorectal cancer

PubMed Central

Kwak, Yoonjin; Koh, Jiwon; Kim, Duck-Woo; Kang, Sung-Bum; Kim, Woo Ho; Lee, Hye Seung

2016-01-01

Background The immunoscore (IS), an index based on the density of CD3+ and CD8+ tumor-infiltrating lymphocytes (TILs) in the tumor center (CT) and invasive margin (IM), has gained considerable attention as a prognostic marker. Tumor-associated macrophages (TAMs) have also been reported to have prognostic value. However, its clinical significance has not been fully clarified in patients with advanced CRC who present with distant metastases. Methods The density of CD3+, CD4+, CD8+, FOXP3+, CD68+, and CD163+ immune cells within CRC tissue procured from three sites–the primary CT, IM, and distant metastasis (DM)–was determined using immunohistochemistry and digital image analyzer (n=196). The IS was obtained by quantifying the densities of CD3+ and CD8+ TILs in the CT and IM. IS-metastatic and IS-macrophage–additional IS models designed in this study–were obtained by adding the score of CD3 and CD8 in DM and the score of CD163 in primary tumors (CT and IM), respectively, to the IS. Result Higher IS, IS-metastatic, and IS-macrophage values were significantly correlated with better prognosis (p=0.020, p≤0.001, and p=0.005, respectively). Multivariate analysis revealed that only IS-metastatic was an independent prognostic marker (p=0.012). No significant correlation was observed between KRAS mutation and three IS models. However, in the subgroup analysis, IS-metastatic showed a prognostic association regardless of the KRAS mutational status. Conclusion IS is a reproducible method for predicting the survival of patients with advanced CRC. Additionally, an IS including the CD3+ and CD8+ TIL densities at DM could be a strong prognostic marker for advanced CRC. PMID:27835889

Serum prognostic biomarkers in head and neck cancer patients.

PubMed

Lin, Ho-Sheng; Siddiq, Fauzia; Talwar, Harvinder S; Chen, Wei; Voichita, Calin; Draghici, Sorin; Jeyapalan, Gerald; Chatterjee, Madhumita; Fribley, Andrew; Yoo, George H; Sethi, Seema; Kim, Harold; Sukari, Ammar; Folbe, Adam J; Tainsky, Michael A

2014-08-01

A reliable estimate of survival is important as it may impact treatment choice. The objective of this study is to identify serum autoantibody biomarkers that can be used to improve prognostication for patients affected with head and neck squamous cell carcinoma (HNSCC). Prospective cohort study. A panel of 130 serum biomarkers, previously selected for cancer detection using microarray-based serological profiling and specialized bioinformatics, were evaluated for their potential as prognostic biomarkers in a cohort of 119 HNSCC patients followed for up to 12.7 years. A biomarker was considered positive if its reactivity to the particular patient's serum was greater than one standard deviation above the mean reactivity to sera from the other 118 patients, using a leave-one-out cross-validation model. Survival curves were estimated according to the Kaplan-Meier method, and statistically significant differences in survival were examined using the log rank test. Independent prognostic biomarkers were identified following analysis using multivariate Cox proportional hazards models. Poor overall survival was associated with African Americans (hazard ratio [HR] for death = 2.61; 95% confidence interval [CI]: 1.58-4.33; P = .000), advanced stage (HR = 2.79; 95% CI: 1.40-5.57; P = .004), and recurrent disease (HR = 6.66; 95% CI: 2.54-17.44; P = .000). On multivariable Cox analysis adjusted for covariates (race and stage), six of the 130 markers evaluated were found to be independent prognosticators of overall survival. The results shown here are promising and demonstrate the potential use of serum biomarkers for prognostication in HNSCC patients. Further clinical trials to include larger samples of patients across multiple centers may be warranted. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Serum Prognostic Biomarkers in Head and Neck Cancer Patients

PubMed Central

Lin, Ho-Sheng; Siddiq, Fauzia; Talwar, Harvinder S.; Chen, Wei; Voichita, Calin; Draghici, Sorin; Jeyapalan, Gerald; Chatterjee, Madhumita; Fribley, Andrew; Yoo, George H.; Sethi, Seema; Kim, Harold; Sukari, Ammar; Folbe, Adam J.; Tainsky, Michael A.

2014-01-01

Objectives/Hypothesis A reliable estimate of survival is important as it may impact treatment choice. The objective of this study is to identify serum autoantibody biomarkers that can be used to improve prognostication for patients affected with head and neck squamous cell carcinoma (HNSCC). Study Design Prospective cohort study. Methods A panel of 130 serum biomarkers, previously selected for cancer detection using microarray-based serological profiling and specialized bioinformatics, were evaluated for their potential as prognostic biomarkers in a cohort of 119 HNSCC patients followed for up to 12.7 years. A biomarker was considered positive if its reactivity to the particular patient’s serum was greater than one standard deviation above the mean reactivity to sera from the other 118 patients, using a leave-one-out cross-validation model. Survival curves were estimated according to the Kaplan-Meier method, and statistically significant differences in survival were examined using the log rank test. Independent prognostic biomarkers were identified following analysis using multivariate Cox proportional hazards models. Results Poor overall survival was associated with African Americans (hazard ratio [HR] for death =2.61; 95% confidence interval [CI]: 1.58–4.33; P =.000), advanced stage (HR =2.79; 95% CI: 1.40–5.57; P =.004), and recurrent disease (HR =6.66; 95% CI: 2.54–17.44; P =.000). On multivariable Cox analysis adjusted for covariates (race and stage), six of the 130 markers evaluated were found to be independent prognosticators of overall survival. Conclusions The results shown here are promising and demonstrate the potential use of serum biomarkers for prognostication in HNSCC patients. Further clinical trials to include larger samples of patients across multiple centers may be warranted. PMID:24347532

Treatment Results and Prognostic Indicators in Thymic Epithelial Tumors: A Clinicopathological Analysis of 45 Patients

PubMed Central

Ansari, Mansour; Dehsara, Farzin; Mohammadianpanah, Mohammad; Mosalaei, Ahmad; Omidvari, Shapour; Ahmadloo, Niloofar

2014-01-01

Background: Thymomas are rare epithelial tumors arising from thymus gland. This study aims at investigating the clinical presentation, prognostic factors and treatment outcome of forty five patients with thymoma and thymic carcinoma. Methods: Forty-five patients being histologically diagnosed with thymoma or thymic carcinoma that were treated and followed-up at a tertiary academic hospital during January 1987 and December 2008 were selected for the present study. Twelve patients were solely treated with surgery, 14 with surgery followed by adjuvant radiotherapy, 12 with sequential combined treatment of surgery, radiotherapy and/or chemotherapy and 7 with non-surgical approach including radiotherapy and/or chemotherapy.  Tumors were classified based on the new World Health Organization (WHO) histological classification. Results: There were 18 women and 27 men with a median age of 43 years. Twelve patients (26.7%) had stage I, 7 (17.8%) had stage II, 23 (51%) had stage III and 2 (4.5%) had stage IV disease. Tumors types were categorized as type A (n=4), type AB (n=10), type B1 (n=9), type B2 (n=10), type B3 (n=5) and type C (n=7). In univariate analysis for overall survival, disease stage (P=0.001), tumor size (P=0.017) and the extent of surgical resection (P<0.001) were prognostic factors. Regarding the multivariate analysis, only the extent of the surgical resection (P<0.001) was the independent prognostic factor and non-surgical treatment had a negative influence on the survival. The 5-year and 10-year overall survival rates were 70.8% and 62.9%, respectively. Conclusion: Complete surgical resection is the most important prognostic factor in patients with thymic epithelial tumors. PMID:25031486

Treatment results and prognostic indicators in thymic epithelial tumors: a clinicopathological analysis of 45 patients.

PubMed

Ansari, Mansour; Dehsara, Farzin; Mohammadianpanah, Mohammad; Mosalaei, Ahmad; Omidvari, Shapour; Ahmadloo, Niloofar

2014-07-01

Thymomas are rare epithelial tumors arising from thymus gland. This study aims at investigating the clinical presentation, prognostic factors and treatment outcome of forty five patients with thymoma and thymic carcinoma. Forty-five patients being histologically diagnosed with thymoma or thymic carcinoma that were treated and followed-up at a tertiary academic hospital during January 1987 and December 2008 were selected for the present study. Twelve patients were solely treated with surgery, 14 with surgery followed by adjuvant radiotherapy, 12 with sequential combined treatment of surgery, radiotherapy and/or chemotherapy and 7 with non-surgical approach including radiotherapy and/or chemotherapy.  Tumors were classified based on the new World Health Organization (WHO) histological classification. There were 18 women and 27 men with a median age of 43 years. Twelve patients (26.7%) had stage I, 7 (17.8%) had stage II, 23 (51%) had stage III and 2 (4.5%) had stage IV disease. Tumors types were categorized as type A (n=4), type AB (n=10), type B1 (n=9), type B2 (n=10), type B3 (n=5) and type C (n=7). In univariate analysis for overall survival, disease stage (P=0.001), tumor size (P=0.017) and the extent of surgical resection (P<0.001) were prognostic factors. Regarding the multivariate analysis, only the extent of the surgical resection (P<0.001) was the independent prognostic factor and non-surgical treatment had a negative influence on the survival. The 5-year and 10-year overall survival rates were 70.8% and 62.9%, respectively. Complete surgical resection is the most important prognostic factor in patients with thymic epithelial tumors.

A Distributed Approach to System-Level Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, Indranil

2012-01-01

Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key technology for systems health management that leads to improved safety and reliability with reduced costs. The prognostics problem is often approached from a component-centric view. However, in most cases, it is not specifically component lifetimes that are important, but, rather, the lifetimes of the systems in which these components reside. The system-level prognostics problem can be quite difficult due to the increased scale and scope of the prognostics problem and the relative Jack of scalability and efficiency of typical prognostics approaches. In order to address these is ues, we develop a distributed solution to the system-level prognostics problem, based on the concept of structural model decomposition. The system model is decomposed into independent submodels. Independent local prognostics subproblems are then formed based on these local submodels, resul ting in a scalable, efficient, and flexible distributed approach to the system-level prognostics problem. We provide a formulation of the system-level prognostics problem and demonstrate the approach on a four-wheeled rover simulation testbed. The results show that the system-level prognostics problem can be accurately and efficiently solved in a distributed fashion.

Role of genotype-based approach in the clinical management of adult acute myeloid leukemia with normal cytogenetics.

PubMed

Cagnetta, Antonia; Adamia, Sophia; Acharya, Chirag; Patrone, Franco; Miglino, Maurizio; Nencioni, Alessio; Gobbi, Marco; Cea, Michele

2014-06-01

Acute myeloid leukemia (AML) is the most common form of acute leukemia affecting adults. Although it is a complex disease driven by numerous genetic and epigenetic abnormalities, nearly 50% of patients exhibit a normal karyotype (CN-AML) with an intermediate cytogenetic risk. However, a widespread genomic analysis has recently shown the recurrence of genomic aberrations in this category (mutations of FLT3, CEBPA, NPM1, RUNX1, TET2, IDH1/2, DNMT3A, ASXL1, MLL and WT1) thus revealing its marked genomic heterogeneity. In this perspective, a global gene expression analysis of AML patients provides an independent prognostic marker to categorize each patient into clinic-pathologic subgroups based on its molecular genetic defects. Consistently such classification, taking into account the uniqueness of each AML patient, furnishes an individualized treatment approach leading a step closer to personalized medicine. Overall the genome-wide analysis of AML patients, by providing novel insights into biology of this tumor, furnishes accurate prognostic markers as well as useful tools for selecting the most appropriate treatment option. Moreover it provides novel therapeutic targets useful to enhance efficacy of the current anti-AML therapeutics. Here we describe the prognostic relevance of such new genetic data and discuss how this approach can be used to improve survival and treatment of AML patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hierarchical image feature extraction by an irregular pyramid of polygonal partitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skurikhin, Alexei N

2008-01-01

We present an algorithmic framework for hierarchical image segmentation and feature extraction. We build a successive fine-to-coarse hierarchy of irregular polygonal partitions of the original image. This multiscale hierarchy forms the basis for object-oriented image analysis. The framework incorporates the Gestalt principles of visual perception, such as proximity and closure, and exploits spectral and textural similarities of polygonal partitions, while iteratively grouping them until dissimilarity criteria are exceeded. Seed polygons are built upon a triangular mesh composed of irregular sized triangles, whose spatial arrangement is adapted to the image content. This is achieved by building the triangular mesh on themore » top of detected spectral discontinuities (such as edges), which form a network of constraints for the Delaunay triangulation. The image is then represented as a spatial network in the form of a graph with vertices corresponding to the polygonal partitions and edges reflecting their relations. The iterative agglomeration of partitions into object-oriented segments is formulated as Minimum Spanning Tree (MST) construction. An important characteristic of the approach is that the agglomeration of polygonal partitions is constrained by the detected edges; thus the shapes of agglomerated partitions are more likely to correspond to the outlines of real-world objects. The constructed partitions and their spatial relations are characterized using spectral, textural and structural features based on proximity graphs. The framework allows searching for object-oriented features of interest across multiple levels of details of the built hierarchy and can be generalized to the multi-criteria MST to account for multiple criteria important for an application.« less

Automatic partitioning of head CTA for enabling segmentation

NASA Astrophysics Data System (ADS)

Suryanarayanan, Srikanth; Mullick, Rakesh; Mallya, Yogish; Kamath, Vidya; Nagaraj, Nithin

2004-05-01

Radiologists perform a CT Angiography procedure to examine vascular structures and associated pathologies such as aneurysms. Volume rendering is used to exploit volumetric capabilities of CT that provides complete interactive 3-D visualization. However, bone forms an occluding structure and must be segmented out. The anatomical complexity of the head creates a major challenge in the segmentation of bone and vessel. An analysis of the head volume reveals varying spatial relationships between vessel and bone that can be separated into three sub-volumes: "proximal", "middle", and "distal". The "proximal" and "distal" sub-volumes contain good spatial separation between bone and vessel (carotid referenced here). Bone and vessel appear contiguous in the "middle" partition that remains the most challenging region for segmentation. The partition algorithm is used to automatically identify these partition locations so that different segmentation methods can be developed for each sub-volume. The partition locations are computed using bone, image entropy, and sinus profiles along with a rule-based method. The algorithm is validated on 21 cases (varying volume sizes, resolution, clinical sites, pathologies) using ground truth identified visually. The algorithm is also computationally efficient, processing a 500+ slice volume in 6 seconds (an impressive 0.01 seconds / slice) that makes it an attractive algorithm for pre-processing large volumes. The partition algorithm is integrated into the segmentation workflow. Fast and simple algorithms are implemented for processing the "proximal" and "distal" partitions. Complex methods are restricted to only the "middle" partition. The partitionenabled segmentation has been successfully tested and results are shown from multiple cases.

Prognostic scoring systems for myelodysplastic syndromes (MDS) in a population-based setting: a report from the Swedish MDS register.

PubMed

Moreno Berggren, Daniel; Folkvaljon, Yasin; Engvall, Marie; Sundberg, Johan; Lambe, Mats; Antunovic, Petar; Garelius, Hege; Lorenz, Fryderyk; Nilsson, Lars; Rasmussen, Bengt; Lehmann, Sören; Hellström-Lindberg, Eva; Jädersten, Martin; Ejerblad, Elisabeth

2018-06-01

The myelodysplastic syndromes (MDS) have highly variable outcomes and prognostic scoring systems are important tools for risk assessment and to guide therapeutic decisions. However, few population-based studies have compared the value of the different scoring systems. With data from the nationwide Swedish population-based MDS register we validated the International Prognostic Scoring System (IPSS), revised IPSS (IPSS-R) and the World Health Organization (WHO) Classification-based Prognostic Scoring System (WPSS). We also present population-based data on incidence, clinical characteristics including detailed cytogenetics and outcome from the register. The study encompassed 1329 patients reported to the register between 2009 and 2013, 14% of these had therapy-related MDS (t-MDS). Based on the MDS register, the yearly crude incidence of MDS in Sweden was 2·9 per 100 000 inhabitants. IPSS-R had a significantly better prognostic power than IPSS (P < 0·001). There was a trend for better prognostic power of IPSS-R compared to WPSS (P = 0·05) and for WPSS compared to IPSS (P = 0·07). IPSS-R was superior to both IPSS and WPSS for patients aged ≤70 years. Patients with t-MDS had a worse outcome compared to de novo MDS (d-MDS), however, the validity of the prognostic scoring systems was comparable for d-MDS and t-MDS. In conclusion, population-based studies are important to validate prognostic scores in a 'real-world' setting. In our nationwide cohort, the IPSS-R showed the best predictive power. © 2018 John Wiley & Sons Ltd.

Prognostic Significance of Human Apurinic/Apyrimidinic Endonuclease (APE/Ref-1) Expression in Rectal Cancer Treated With Preoperative Radiochemotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jun-Sang, E-mail: k423j@cnu.ac.kr; Cancer Research Institute, Chungnam National University, Daejeon; Kim, Jin-Man

Purpose: Human apurinic endonuclease/redox factor 1 (APE/Ref-1) mediates repair of radiation-induced DNA lesions and regulates transcription via redox-based activation. We investigated the predictive and prognostic significance of APE/Ref-1 expression in pretreatment biopsy specimens in locally advanced rectal cancer (LARC) (cT3-T4 or N+). Methods and Materials: APE/Ref-1 expression was analyzed by immunohistochemistry in pretreatment biopsy specimens obtained from 83 patients with LARC. Patients received preoperative radiotherapy of 50.4 Gy in 28 fractions, combined with oral capecitabine and leucovorin chemotherapy, followed by curative surgery. The prognostic significance of various clinicopathologic characteristics, including APE/Ref-1 protein expression, was evaluated. Results: APE/Ref-1 was expressed inmore » 97% of patient samples. Exclusive APE/Ref-1 nuclear staining was observed in 49 of 83 samples (59%), and mixed nuclear and cytoplasmic staining was observed in 31 samples (37%). APE/Ref-1 nuclear expression levels were low in 49 patients (59%) and high in 34 patients (41%). The level of APE/Ref-1 nuclear expression was not a prognostic factor for overall and disease-free survival. Cytoplasmic expression of APE/Ref-1 was a borderline-significant predictive factor for pathologic tumor response (p = 0.08) and a significant prognostic factor for disease-free survival, as shown by univariate analysis (p = 0.037). Multivariate analysis confirmed that cytoplasmic localization of APE/Ref-1 is a significant predictor of disease-free survival (hazard ratio, 0.45; p = 0.046). Conclusions: APE/Ref-1 was expressed in a majority of pretreatment biopsy specimens from patients with LARC. The level of APE/Ref-1 nuclear expression was not a significant predictive and prognostic factor; however, cytoplasmic localization of the protein was negatively associated with disease-free survival. These results indicate that cytoplasmic expression of APE/Ref-1 represents an adverse prognostic factor for LARC patients who receive preoperative radiochemotherapy.« less

Development of a prognostic tool for the occurrence of feather pecking and cannibalism in laying hens.

PubMed

Kaesberg, A-K U; Louton, H; Erhard, M; Schmidt, P; Zepp, M; Helmer, F; Schwarzer, A

2018-03-01

In July 2015, a German voluntary decree stipulated that the keeping of beak-trimmed laying hens after the 1st of January 2017 will no longer be permitted. Simultaneously, the present project was initiated to validate a newly developed prognostic tool for laying hen farmers to forecast, at the beginning of a laying period, the probability of future problems with feather pecking and cannibalism in their flock. For this purpose, we used a computer-based prognostic tool in form of a questionnaire that was easy and quick to complete and facilitated comparisons of different flocks. It contained various possible risk factors that were classified into 3 score categories (1 = "no need for action," 2 = "intermediate need for action," 3 = "instant need for action"). For the validation of this tool, 43 flocks of 41 farms were examined twice, at the beginning of the laying period (around the 20th wk of life) and around the 67th wk of life. At both visits, the designated investigators filled out the questionnaire and assessed the plumage condition and the skin lesions (as indicators of occurrence of feather pecking and cannibalism) of 50 laying hens of each flock. The average prognostic score of the first visit was compared with the existence of feather pecking and cannibalism in each flock at the end of the laying period. The results showed that the prognostic score was negatively correlated with the plumage score (r = -0.32; 95% confidence interval [CI]: [-0.56; -0.02]) and positively correlated with the skin lesion score (r = 0.38; 95% CI: [0.09; 0.61]). These relationships demonstrate that a better prognostic score was associated with a better plumage and skin lesion score. After performing a principal component analysis on the single scores, we found that only 6 components are sufficient to obtain highly sensitive and specific prognostic results. Thus, the data of this analysis should be used for creating applicable software for use on laying hen farms.

Analysis of a Suspected Drug Sample

ERIC Educational Resources Information Center

Schurter, Eric J.; Zook-Gerdau, Lois Anne; Szalay, Paul

2011-01-01

This general chemistry laboratory uses differences in solubility to separate a mixture of caffeine and aspirin while introducing the instrumental analysis methods of GCMS and FTIR. The drug mixture is separated by partitioning aspirin and caffeine between dichloromethane and aqueous base. TLC and reference standards are used to identify aspirin…

Importance of partitioning membranes of the brain and the influence of the neck in head injury modelling.

PubMed

Kumaresan, S; Radhakrishnan, S

1996-01-01

A head injury model consisting of the skull, the CSF, the brain and its partitioning membranes and the neck region is simulated by considering its near actual geometry. Three-dimensional finite-element analysis is carried out to investigate the influence of the partitioning membranes of the brain and the neck in head injury analysis through free-vibration analysis and transient analysis. In free-vibration analysis, the first five modal frequencies are calculated, and in transient analysis intracranial pressure and maximum shear stress in the brain are determined for a given occipital impact load.

Prognostic factors in children and adolescents with acute myeloid leukemia (excluding children with Down syndrome and acute promyelocytic leukemia): univariate and recursive partitioning analysis of patients treated on Pediatric Oncology Group (POG) Study 8821.

PubMed

Chang, M; Raimondi, S C; Ravindranath, Y; Carroll, A J; Camitta, B; Gresik, M V; Steuber, C P; Weinstein, H

2000-07-01

The purpose of the paper was to define clinical or biological features associated with the risk for treatment failure for children with acute myeloid leukemia. Data from 560 children and adolescents with newly diagnosed acute myeloid leukemia who entered the Pediatric Oncology Group Study 8821 from June 1988 to March 1993 were analyzed by univariate and recursive partitioning methods. Children with Down syndrome or acute promyelocytic leukemia were excluded from the study. Factors examined included age, number of leukocytes, sex, FAB morphologic subtype, cytogenetic findings, and extramedullary disease at the time of diagnosis. The overall event-free survival (EFS) rate at 4 years was 32.7% (s.e. = 2.2%). Age > or =2 years, fewer than 50 x 10(9)/I leukocytes, and t(8;21) or inv(16), and normal chromosomes were associated with higher rates of EFS (P value = 0.003, 0.049, 0.0003, 0.031, respectively), whereas the M5 subtype of AML (P value = 0.0003) and chromosome abnormalities other than t(8;21) and inv(16) were associated with lower rates of EFS (P value = 0.0001). Recursive partitioning analysis defined three groups of patients with widely varied prognoses: female patients with t(8;21), inv(16), or a normal karyotype (n = 89) had the best prognosis (4-year EFS = 55.1%, s.e. = 5.7%); male patients with t(8;21), inv(16) or normal chromosomes (n = 106) had an intermediate prognosis (4-year EFS = 38.1%, s.e. = 5.3%); patients with chromosome abnormalities other than t(8;21) and inv(16) (n = 233) had the worst prognosis (4-year EFS = 27.0%, s.e. = 3.2%). One hundred and thirty-two patients (24%) could not be grouped because of missing cytogenetic data, mainly due to inadequate marrow samples. The results suggest that pediatric patients with acute myeloid leukemia can be categorized into three potential risk groups for prognosis and that differences in sex and chromosomal abnormalities are associated with differences in estimates of EFS. These results are tentative and must be confirmed by a large prospective clinical trial.

The nature and barium partitioning between immiscible melts - A comparison of experimental and natural systems with reference to lunar granite petrogenesis

NASA Technical Reports Server (NTRS)

Neal, C. R.; Taylor, L. A.

1989-01-01

Elemental partitioning between immiscible melts has been studied using experimental liquid-liquid Kds and those determined by analysis of immiscible glasses in basalt mesostases in order to investigate lunar granite petrogenesis. Experimental data show that Ba is partitioned into the basic immiscible melt, while probe analysis results show that Ba is partitioned into the granitic immiscible melt. It is concluded that lunar granite of significant size can only occur in a plutonic or deep hypabyssal environment.

Inflammation-based prognostic score is a novel predictor of postoperative outcome in patients with colorectal cancer.

PubMed

Ishizuka, Mitsuru; Nagata, Hitoshi; Takagi, Kazutoshi; Horie, Toru; Kubota, Keiichi

2007-12-01

To investigate the significance of preoperative Glasgow prognostic score (GPS) for postoperative prognostication of patients with colorectal cancer. Recent studies have revealed that the GPS, an inflammation-based prognostic score that includes only C-reactive protein (CRP) and albumin, is a useful tool for predicting postoperative outcome in cancer patients. However, few studies have investigated the GPS in the field of colorectal surgery. The GPS was calculated on the basis of admission data as follows: patients with an elevated level of both CRP (>10 mg/L) and hypoalbuminemia (Alb <35 g/L) were allocated a score of 2, and patients showing 1 or none of these blood chemistry abnormalities were allocated a score of 1 or 0, respectively. Prognostic significance was analyzed by univariate and multivariate analyses. A total of 315 patients were evaluated. Kaplan-Meier analysis and log-rank test revealed that a higher GPS predicted a higher risk of postoperative mortality (P < 0.01). Univariate analyses revealed that postoperative TNM was the most sensitive predictor of postoperative mortality (odds ratio, 0.148; 95% confidence interval, 0.072-0.304; P < 0.0001). Multivariate analyses using factors such as age, sex, tumor site, serum carcinoembryonic antigen, CA19-9, CA72-4, CRP, albumin, and GPS revealed that GPS (odds ratio, 0.165; 95% confidence interval, 0.037-0.732; P = 0.0177) was associated with postoperative mortality. Preoperative GPS is considered to be a useful predictor of postoperative mortality in patients with colorectal cancer.

Autophagy-related prognostic signature for breast cancer.

PubMed

Gu, Yunyan; Li, Pengfei; Peng, Fuduan; Zhang, Mengmeng; Zhang, Yuanyuan; Liang, Haihai; Zhao, Wenyuan; Qi, Lishuang; Wang, Hongwei; Wang, Chenguang; Guo, Zheng

2016-03-01

Autophagy is a process that degrades intracellular constituents, such as long-lived or damaged proteins and organelles, to buffer metabolic stress under starvation conditions. Deregulation of autophagy is involved in the progression of cancer. However, the predictive value of autophagy for breast cancer prognosis remains unclear. First, based on gene expression profiling, we found that autophagy genes were implicated in breast cancer. Then, using the Cox proportional hazard regression model, we detected autophagy prognostic signature for breast cancer in a training dataset. We identified a set of eight autophagy genes (BCL2, BIRC5, EIF4EBP1, ERO1L, FOS, GAPDH, ITPR1 and VEGFA) that were significantly associated with overall survival in breast cancer. The eight autophagy genes were assigned as a autophagy-related prognostic signature for breast cancer. Based on the autophagy-related signature, the training dataset GSE21653 could be classified into high-risk and low-risk subgroups with significantly different survival times (HR = 2.72, 95% CI = (1.91, 3.87); P = 1.37 × 10(-5)). Inactivation of autophagy was associated with shortened survival of breast cancer patients. The prognostic value of the autophagy-related signature was confirmed in the testing dataset GSE3494 (HR = 2.12, 95% CI = (1.48, 3.03); P = 1.65 × 10(-3)) and GSE7390 (HR = 1.76, 95% CI = (1.22, 2.54); P = 9.95 × 10(-4)). Further analysis revealed that the prognostic value of the autophagy signature was independent of known clinical prognostic factors, including age, tumor size, grade, estrogen receptor status, progesterone receptor status, ERBB2 status, lymph node status and TP53 mutation status. Finally, we demonstrated that the autophagy signature could also predict distant metastasis-free survival for breast cancer. © 2015 Wiley Periodicals, Inc.

Equilibrium water and solute uptake in silicone hydrogels.

PubMed

Liu, D E; Dursch, T J; Oh, Y; Bregante, D T; Chan, S Y; Radke, C J

2015-05-01

Equilibrium water content of and solute partitioning in silicone hydrogels (SiHys) are investigated using gravimetric analysis, fluorescence confocal laser-scanning microscopy (FCLSM), and back extraction with UV/Vis-absorption spectrophotometry. Synthesized silicone hydrogels consist of silicone monomer, hydrophilic monomer, cross-linking agent, and triblock-copolymer macromer used as an amphiphilic compatibilizer to prevent macrophase separation. In all cases, immiscibility of the silicone and hydrophilic polymers results in microphase-separated morphologies. To investigate solute uptake in each of the SiHy microphases, equilibrium partition coefficients are obtained for two hydrophilic solutes (i.e., theophylline and caffeine dissolved in aqueous phosphate-buffered saline) and two oleophilic solutes (i.e., Nile Red and Bodipy Green dissolved in silicone oil), respectively. Measured water contents and aqueous-solute partition coefficients increase linearly with increasing solvent-free hydrophilic-polymer volume fraction. Conversely, oleophilic-solute partition coefficients decrease linearly with rising solvent-free hydrophilic-polymer volume fraction (i.e., decreasing hydrophobic silicone-polymer fraction). We quantitatively predict equilibrium SiHy water and solute uptake assuming that water and aqueous solutes reside only in hydrophilic microdomains, whereas oleophilic solutes partition predominately into silicone microdomains. Predicted water contents and solute partition coefficients are in excellent agreement with experiment. Our new procedure permits a priori estimation of SiHy water contents and solute partition coefficients based solely on properties of silicone and hydrophilic homopolymer hydrogels, eliminating the need for further mixed-polymer-hydrogel experiments. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Task-specific image partitioning.

PubMed

Kim, Sungwoong; Nowozin, Sebastian; Kohli, Pushmeet; Yoo, Chang D

2013-02-01

Image partitioning is an important preprocessing step for many of the state-of-the-art algorithms used for performing high-level computer vision tasks. Typically, partitioning is conducted without regard to the task in hand. We propose a task-specific image partitioning framework to produce a region-based image representation that will lead to a higher task performance than that reached using any task-oblivious partitioning framework and existing supervised partitioning framework, albeit few in number. The proposed method partitions the image by means of correlation clustering, maximizing a linear discriminant function defined over a superpixel graph. The parameters of the discriminant function that define task-specific similarity/dissimilarity among superpixels are estimated based on structured support vector machine (S-SVM) using task-specific training data. The S-SVM learning leads to a better generalization ability while the construction of the superpixel graph used to define the discriminant function allows a rich set of features to be incorporated to improve discriminability and robustness. We evaluate the learned task-aware partitioning algorithms on three benchmark datasets. Results show that task-aware partitioning leads to better labeling performance than the partitioning computed by the state-of-the-art general-purpose and supervised partitioning algorithms. We believe that the task-specific image partitioning paradigm is widely applicable to improving performance in high-level image understanding tasks.

Self-digitization chip for single-cell genotyping of cancer-related mutations

PubMed Central

Monroe, Luke D.; Kreutz, Jason E.; Schneider, Thomas; Fujimoto, Bryant S.; Chiu, Daniel T.; Radich, Jerald P.; Paguirigan, Amy L.

2018-01-01

Cancer is a heterogeneous disease, and patient-level genetic assessments can guide therapy choice and impact prognosis. However, little is known about the impact of genetic variability within a tumor, intratumoral heterogeneity (ITH), on disease progression or outcome. Current approaches using bulk tumor specimens can suggest the presence of ITH, but only single-cell genetic methods have the resolution to describe the underlying clonal structures themselves. Current techniques tend to be labor and resource intensive and challenging to characterize with respect to sources of biological and technical variability. We have developed a platform using a microfluidic self-digitization chip to partition cells in stationary volumes for cell imaging and allele-specific PCR. Genotyping data from only confirmed single-cell volumes is obtained and subject to a variety of relevant quality control assessments such as allele dropout, false positive, and false negative rates. We demonstrate single-cell genotyping of the NPM1 type A mutation, an important prognostic indicator in acute myeloid leukemia, on single cells of the cell line OCI-AML3, describing a more complex zygosity distribution than would be predicted via bulk analysis. PMID:29718986

Self-digitization chip for single-cell genotyping of cancer-related mutations.

PubMed

Thompson, Alison M; Smith, Jordan L; Monroe, Luke D; Kreutz, Jason E; Schneider, Thomas; Fujimoto, Bryant S; Chiu, Daniel T; Radich, Jerald P; Paguirigan, Amy L

2018-01-01

Cancer is a heterogeneous disease, and patient-level genetic assessments can guide therapy choice and impact prognosis. However, little is known about the impact of genetic variability within a tumor, intratumoral heterogeneity (ITH), on disease progression or outcome. Current approaches using bulk tumor specimens can suggest the presence of ITH, but only single-cell genetic methods have the resolution to describe the underlying clonal structures themselves. Current techniques tend to be labor and resource intensive and challenging to characterize with respect to sources of biological and technical variability. We have developed a platform using a microfluidic self-digitization chip to partition cells in stationary volumes for cell imaging and allele-specific PCR. Genotyping data from only confirmed single-cell volumes is obtained and subject to a variety of relevant quality control assessments such as allele dropout, false positive, and false negative rates. We demonstrate single-cell genotyping of the NPM1 type A mutation, an important prognostic indicator in acute myeloid leukemia, on single cells of the cell line OCI-AML3, describing a more complex zygosity distribution than would be predicted via bulk analysis.

Radiotherapeutic and surgical management for newly diagnosed brain metastasis(es): An American Society for Radiation Oncology evidence-based guideline

PubMed Central

Tsao, May N.; Rades, Dirk; Wirth, Andrew; Lo, Simon S.; Danielson, Brita L.; Gaspar, Laurie E.; Sperduto, Paul W.; Vogelbaum, Michael A.; Radawski, Jeffrey D.; Wang, Jian Z.; Gillin, Michael T.; Mohideen, Najeeb; Hahn, Carol A.; Chang, Eric L.

2012-01-01

Purpose To systematically review the evidence for the radiotherapeutic and surgical management of patients newly diagnosed with intraparenchymal brain metastases. Methods and Materials Key clinical questions to be addressed in this evidence-based Guideline were identified. Fully published randomized controlled trials dealing with the management of newly diagnosed intraparenchymal brain metastases were searched systematically and reviewed. The U.S. Preventative Services Task Force levels of evidence were used to classify various options of management. Results The choice of management in patients with newly diagnosed single or multiple brain metastases depends on estimated prognosis and the aims of treatment (survival, local treated lesion control, distant brain control, neurocognitive preservation). Single brain metastasis and good prognosis (expected survival 3 months or more): For a single brain metastasis larger than 3 to 4 cm and amenable to safe complete resection, whole brain radiotherapy (WBRT) and surgery (level 1) should be considered. Another alternative is surgery and radiosurgery/radiation boost to the resection cavity (level 3). For single metastasis less than 3 to 4 cm, radiosurgery alone or WBRT and radiosurgery or WBRT and surgery (all based on level 1 evidence) should be considered. Another alternative is surgery and radiosurgery or radiation boost to the resection cavity (level 3). For single brain metastasis (less than 3 to 4 cm) that is not resectable or incompletely resected, WBRT and radiosurgery, or radiosurgery alone should be considered (level 1). For nonresectable single brain metastasis (larger than 3 to 4 cm), WBRT should be considered (level 3). Multiple brain metastases and good prognosis (expected survival 3 months or more): For selected patients with multiple brain metastases (all less than 3 to 4 cm), radiosurgery alone, WBRT and radiosurgery, or WBRT alone should be considered, based on level 1 evidence. Safe resection of a brain metastasis or metastases causing significant mass effect and postoperative WBRT may also be considered (level 3). Patients with poor prognosis (expected survival less than 3 months): Patients with either single or multiple brain metastases with poor prognosis should be considered for palliative care with or without WBRT (level 3). It should be recognized, however, that there are limitations in the ability of physicians to accurately predict patient survival. Prognostic systems such as recursive partitioning analysis, and diagnosis-specific graded prognostic assessment may be helpful. Conclusions Radiotherapeutic intervention (WBRT or radiosurgery) is associated with improved brain control. In selected patients with single brain metastasis, radiosurgery or surgery has been found to improve survival and locally treated metastasis control (compared with WBRT alone). PMID:25925626

Prognostic factors and genes associated with endometrial cancer based on gene expression profiling by bioinformatics analysis.

PubMed

Zhang, Ying; Zhang, Wei; Li, Xinglan; Li, Dapeng; Zhang, Xiaoling; Yin, Yajie; Deng, Xiangyun; Sheng, Xiugui

2016-06-01

Endometrial cancer (EC) is the most prevalent malignancy worldwide. Although several efforts had been made to explore the molecular mechanism responsible for EC progression, it is still not fully understood. To evaluate the clinical characteristics and prognostic factors of patients with EC, and further to search for novel genes associated with EC progression. We recruited 328 patients with EC and analyzed prognostic factors using Cox proportional hazard regression model. Further, a gene expression profile of EC was used to identify the differentially expressed genes (DEGs) between normal samples and tumor samples. Subsequently, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis ( http://www.genome.jp/kegg/ ) for DEGs were performed, and then protein-protein interaction (PPI) network of DEGs as well as the subnetwork of PPI were constructed with plug-in, MCODE by mapping DEGs into the Search Tool for the Retrieval of Interacting Genes database. Our results showed that body mass index (BMI), hypertension, myometrial invasion, pathological type, and Glut4 positive expression were prognostic factors in EC (P < 0.05). Bioinformatics analysis showed that upregulated DEGs were associated with cell cycle, and downregulated DEGs were related to MAPK pathway. Meanwhile, PPI network analysis revealed that upregulated CDK1 and CCNA2 as well as downregulated JUN and FOS were listed in top two nodes with high degrees. Patients with EC should be given more focused attentions in respect of pathological type, BMI, hypertension, and Glut4-positive expression. In addition, CDK1, CCNA2, JUN, and FOS might play important roles in EC development.

Quantitative fibronectin to help decision-making in women with symptoms of preterm labour (QUIDS) part 1: Individual participant data meta-analysis and health economic analysis.

PubMed

Stock, Sarah J; Wotherspoon, Lisa M; Boyd, Kathleen A; Morris, Rachel K; Dorling, Jon; Jackson, Lesley; Chandiramani, Manju; David, Anna L; Khalil, Asma; Shennan, Andrew; Hodgetts Morton, Victoria; Lavender, Tina; Khan, Khalid; Harper-Clarke, Susan; Mol, Ben W; Riley, Richard D; Norrie, John; Norman, Jane E

2018-04-07

The aim of the QUIDS study is to develop a decision support tool for the management of women with symptoms and signs of preterm labour, based on a validated prognostic model using quantitative fetal fibronectin (qfFN) concentration, in combination with clinical risk factors. The study will evaluate the Rapid fFN 10Q System (Hologic, Marlborough, Massachusetts) which quantifies fFN in a vaginal swab. In part 1 of the study, we will develop and internally validate a prognostic model using an individual participant data (IPD) meta-analysis of existing studies containing women with symptoms of preterm labour alongside fFN measurements and pregnancy outcome. An economic analysis will be undertaken to assess potential cost-effectiveness of the qfFN prognostic model. The primary endpoint will be the ability of the prognostic model to rule out spontaneous preterm birth within 7 days. Six eligible studies were identified by systematic review of the literature and five agreed to provide their IPD (n=5 studies, 1783 women and 139 events of preterm delivery within 7 days of testing). The study is funded by the National Institute of Healthcare Research Health Technology Assessment (HTA 14/32/01). It has been approved by the West of Scotland Research Ethics Committee (16/WS/0068). CRD42015027590. Protocol version 2, date 1 November 2016. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Prognostic roles for fibroblast growth factor receptor family members in malignant peripheral nerve sheath tumor.

PubMed

Zhou, Wenya; Du, Xiaoling; Song, Fengju; Zheng, Hong; Chen, Kexin; Zhang, Wei; Yang, Jilong

2016-04-19

Malignant peripheral nerve sheath tumors (MPNST) are rare, highly malignant, and poorly understood sarcomas. The often poor outcome of MPNST highlights the necessity of identifying prognostic predictors for this aggressive sarcoma. Here, we investigate the role of fibroblast growth factor receptor (FGFR) family members in human MPNSTs. aCGH and bioinformatics analysis identified frequent amplification of the FGFR1 gene. FISH analysis revealed that 26.9% MPNST samples had amplification of FGFR1, with both focal and polysomy patterns observed. IHC identified that FGFR1 protein expression was positively correlated with FGFR1 gene amplification. High expression of FGFR1 protein was associated with better overall survival (OS) and was an independent prognostic predictor for OS of MPNST patients. Additionally, combined expression of FGFR1 and FGFR2 protein characterized a subtype of MPNST with better OS. FGFR4 protein was expressed 82.3% of MPNST samples, and was associated with poor disease-free survival. We performed microarray-based comparative genomic hybridization (aCGH) profiling of two cohorts of primary MPNST tissue samples including 25 patients treated at The University of Texas MD Anderson Cancer Center and 26 patients from Tianjin Medical University Cancer Institute and Hospital. Fluorescence in situ hybridization (FISH) was used to validate the gene amplification detected by aCGH analysis. Another cohort of 63 formalin-fixed paraffin-embedded MPNST samples (including 52 samples for FISH assay) was obtained to explore FGFR1, 2, 3, and 4 protein expression by immunohistochemical (IHC) analysis. Our integrated genomic and molecular studies provide evidence that FGFRs play different prognostic roles in MPNST.

Tobacco, Marijuana, and Alcohol Use in University Students: A Cluster Analysis

PubMed Central

Primack, Brian A.; Kim, Kevin H.; Shensa, Ariel; Sidani, Jaime E.; Barnett, Tracey E.; Switzer, Galen E.

2012-01-01

Objective Segmentation of populations may facilitate development of targeted substance abuse prevention programs. We aimed to partition a national sample of university students according to profiles based on substance use. Participants We used 2008–2009 data from the National College Health Assessment from the American College Health Association. Our sample consisted of 111,245 individuals from 158 institutions. Method We partitioned the sample using cluster analysis according to current substance use behaviors. We examined the association of cluster membership with individual and institutional characteristics. Results Cluster analysis yielded six distinct clusters. Three individual factors—gender, year in school, and fraternity/sorority membership—were the most strongly associated with cluster membership. Conclusions In a large sample of university students, we were able to identify six distinct patterns of substance abuse. It may be valuable to target specific populations of college-aged substance users based on individual factors. However, comprehensive intervention will require a multifaceted approach. PMID:22686360

Four-miRNA signature as a prognostic tool for lung adenocarcinoma.

PubMed

Lin, Yan; Lv, Yufeng; Liang, Rong; Yuan, Chunling; Zhang, Jinyan; He, Dan; Zheng, Xiaowen; Zhang, Jianfeng

2018-01-01

The aim of this study was to generate a novel miRNA expression signature to accurately predict prognosis for patients with lung adenocarcinoma (LUAD). Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between LUAD and paired healthy tissues. We then evaluated the prognostic values of the differentially expressed miRNAs using univariate/multivariate Cox regression analysis. This analysis was ultimately used to construct a four-miRNA signature that effectively predicted patient survival. Finally, we analyzed potential functional roles of the target genes for these four miRNAs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Based on our cutoff criteria ( P <0.05 and |log2FC| >1.0), we identified a total of 187 differentially expressed miRNAs, including 148 that were upregulated in LUAD tissues and 39 that were downregulated. Four miRNAs (miR-148a-5p, miR-31-5p, miR-548v, and miR-550a-5p) were independently associated with survival based on Kaplan-Meier analysis. We generated a signature index based on the expression of these four miRNAs and stratified patients into low- and high-risk groups. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group ( P =0.002). A functional enrichment analysis suggested that the target genes of these four miRNAs were involved in protein phosphorylation and the Hippo and sphingolipid signaling pathways. Taken together, our results suggest that our four-miRNA signature can be used as a prognostic tool for patients with LUAD.

An Uncertainty Quantification Framework for Prognostics and Condition-Based Monitoring

NASA Technical Reports Server (NTRS)

Sankararaman, Shankar; Goebel, Kai

2014-01-01

This paper presents a computational framework for uncertainty quantification in prognostics in the context of condition-based monitoring of aerospace systems. The different sources of uncertainty and the various uncertainty quantification activities in condition-based prognostics are outlined in detail, and it is demonstrated that the Bayesian subjective approach is suitable for interpreting uncertainty in online monitoring. A state-space model-based framework for prognostics, that can rigorously account for the various sources of uncertainty, is presented. Prognostics consists of two important steps. First, the state of the system is estimated using Bayesian tracking, and then, the future states of the system are predicted until failure, thereby computing the remaining useful life of the system. The proposed framework is illustrated using the power system of a planetary rover test-bed, which is being developed and studied at NASA Ames Research Center.

Prognostic significance of peripheral monocyte count in patients with extranodal natural killer/T-cell lymphoma.

PubMed

Huang, Jia-Jia; Li, Ya-Jun; Xia, Yi; Wang, Yu; Wei, Wen-Xiao; Zhu, Ying-Jie; Lin, Tong-Yu; Huang, Hui-Qiang; Jiang, Wen-Qi; Li, Zhi-Ming

2013-05-03

Extranodal natural killer/T-cell lymphoma (ENKL) has heterogeneous clinical manifestations and prognosis. This study aims to evaluate the prognostic impact of absolute monocyte count (AMC) in ENKL, and provide some immunologically relevant information for better risk stratification in patients with ENKL. Retrospective data from 163 patients newly diagnosed with ENKL were analyzed. The absolute monocyte count (AMC) at diagnosis was analyzed as continuous and dichotomized variables. Independent prognostic factors of survival were determined by Cox regression analysis. The AMC at diagnosis were related to overall survival (OS) and progression-free survival (PFS) in patients with ENKL. Multivariate analysis identified AMC as independent prognostic factors of survival, independent of International Prognostic Index (IPI) and Korean prognostic index (KPI). The prognostic index incorporating AMC and absolute lymphocyte count (ALC), another surrogate factor of immune status, could be used to stratify all 163 patients with ENKL into different prognostic groups. For patients who received chemotherapy followed by radiotherapy (102 cases), the three AMC/ALC index categories identified patients with significantly different survivals. When superimposed on IPI or KPI categories, the AMC/ALC index was better able to identify high-risk patients in the low-risk IPI or KPI category. The baseline peripheral monocyte count is shown to be an effective prognostic indicator of survival in ENKL patients. The prognostic index related to tumor microenvironment might be helpful to identify high-risk patients with ENKL.

Independent Prognostic Value of Serum Markers in Diffuse Large B-Cell Lymphoma in the Era of the NCCN-IPI.

PubMed

Melchardt, Thomas; Troppan, Katharina; Weiss, Lukas; Hufnagl, Clemens; Neureiter, Daniel; Tränkenschuh, Wolfgang; Schlick, Konstantin; Huemer, Florian; Deutsch, Alexander; Neumeister, Peter; Greil, Richard; Pichler, Martin; Egle, Alexander

2015-12-01

Several serum parameters have been evaluated for adding prognostic value to clinical scoring systems in diffuse large B-cell lymphoma (DLBCL), but none of the reports used multivariate testing of more than one parameter at a time. The goal of this study was to validate widely available serum parameters for their independent prognostic impact in the era of the National Comprehensive Cancer Network-International Prognostic Index (NCCN-IPI) score to determine which were the most useful. This retrospective bicenter analysis includes 515 unselected patients with DLBCL who were treated with rituximab and anthracycline-based chemoimmunotherapy between 2004 and January 2014. Anemia, high C-reactive protein, and high bilirubin levels had an independent prognostic value for survival in multivariate analyses in addition to the NCCN-IPI, whereas neutrophil-to-lymphocyte ratio, high gamma-glutamyl transferase levels, and platelets-to-lymphocyte ratio did not. In our cohort, we describe the most promising markers to improve the NCCN-IPI. Anemia and high C-reactive protein levels retain their power in multivariate testing even in the era of the NCCN-IPI. The negative role of high bilirubin levels may be associated as a marker of liver function. Further studies are warranted to incorporate these markers into prognostic models and define their role opposite novel molecular markers. Copyright © 2015 by the National Comprehensive Cancer Network.

Polymers as Reference Partitioning Phase: Polymer Calibration for an Analytically Operational Approach To Quantify Multimedia Phase Partitioning.

PubMed

Gilbert, Dorothea; Witt, Gesine; Smedes, Foppe; Mayer, Philipp

2016-06-07

Polymers are increasingly applied for the enrichment of hydrophobic organic chemicals (HOCs) from various types of samples and media in many analytical partitioning-based measuring techniques. We propose using polymers as a reference partitioning phase and introduce polymer-polymer partitioning as the basis for a deeper insight into partitioning differences of HOCs between polymers, calibrating analytical methods, and consistency checking of existing and calculation of new partition coefficients. Polymer-polymer partition coefficients were determined for polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), and organochlorine pesticides (OCPs) by equilibrating 13 silicones, including polydimethylsiloxane (PDMS) and low-density polyethylene (LDPE) in methanol-water solutions. Methanol as cosolvent ensured that all polymers reached equilibrium while its effect on the polymers' properties did not significantly affect silicone-silicone partition coefficients. However, we noticed minor cosolvent effects on determined polymer-polymer partition coefficients. Polymer-polymer partition coefficients near unity confirmed identical absorption capacities of several PDMS materials, whereas larger deviations from unity were indicated within the group of silicones and between silicones and LDPE. Uncertainty in polymer volume due to imprecise coating thickness or the presence of fillers was identified as the source of error for partition coefficients. New polymer-based (LDPE-lipid, PDMS-air) and multimedia partition coefficients (lipid-water, air-water) were calculated by applying the new concept of a polymer as reference partitioning phase and by using polymer-polymer partition coefficients as conversion factors. The present study encourages the use of polymer-polymer partition coefficients, recognizing that polymers can serve as a linking third phase for a quantitative understanding of equilibrium partitioning of HOCs between any two phases.

Prognostic value of echocardiographic indices of left atrial morphology and function in dogs with myxomatous mitral valve disease

PubMed Central

Romito, Giovanni; Guglielmini, Carlo; Diana, Alessia; Pelle, Nazzareno G.; Contiero, Barbara; Cipone, Mario

2018-01-01

Background The prognostic relevance of left atrial (LA) morphological and functional variables, including those derived from speckle tracking echocardiography (STE), has been little investigated in veterinary medicine. Objectives To assess the prognostic value of several echocardiographic variables, with a focus on LA morphological and functional variables in dogs with myxomatous mitral valve disease (MMVD). Animals One‐hundred and fifteen dogs of different breeds with MMVD. Methods Prospective cohort study. Conventional morphologic and echo‐Doppler variables, LA areas and volumes, and STE‐based LA strain analysis were performed in all dogs. A survival analysis was performed to test for the best echocardiographic predictors of cardiac‐related death. Results Most of the tested variables, including all LA STE‐derived variables were univariate predictors of cardiac death in Cox proportional hazard analysis. Because of strong correlation between many variables, only left atrium to aorta ratio (LA/Ao > 1.7), mitral valve E wave velocity (MV E vel > 1.3 m/s), LA maximal volume (LAVmax > 3.53 mL/kg), peak atrial longitudinal strain (PALS < 30%), and contraction strain index (CSI per 1% increase) were entered in the univariate analysis, and all were predictors of cardiac death. However, only the MV E vel (hazard ratio [HR], 4.45; confidence interval [CI], 1.76‐11.24; P < .001) and LAVmax (HR, 2.32; CI, 1.10‐4.89; P = .024) remained statistically significant in the multivariable analysis. Conclusions and Clinical Importance The assessment of LA dimension and function provides useful prognostic information in dogs with MMVD. Considering all the LA variables, LAVmax appears the strongest predictor of cardiac death, being superior to LA/Ao and STE‐derived variables. PMID:29572938

Unsupervised segmentation of MRI knees using image partition forests

NASA Astrophysics Data System (ADS)

Marčan, Marija; Voiculescu, Irina

2016-03-01

Nowadays many people are affected by arthritis, a condition of the joints with limited prevention measures, but with various options of treatment the most radical of which is surgical. In order for surgery to be successful, it can make use of careful analysis of patient-based models generated from medical images, usually by manual segmentation. In this work we show how to automate the segmentation of a crucial and complex joint -- the knee. To achieve this goal we rely on our novel way of representing a 3D voxel volume as a hierarchical structure of partitions which we have named Image Partition Forest (IPF). The IPF contains several partition layers of increasing coarseness, with partitions nested across layers in the form of adjacency graphs. On the basis of a set of properties (size, mean intensity, coordinates) of each node in the IPF we classify nodes into different features. Values indicating whether or not any particular node belongs to the femur or tibia are assigned through node filtering and node-based region growing. So far we have evaluated our method on 15 MRI knee images. Our unsupervised segmentation compared against a hand-segmented gold standard has achieved an average Dice similarity coefficient of 0.95 for femur and 0.93 for tibia, and an average symmetric surface distance of 0.98 mm for femur and 0.73 mm for tibia. The paper also discusses ways to introduce stricter morphological and spatial conditioning in the bone labelling process.

A Lego Mindstorms NXT based test bench for multiagent exploratory systems and distributed network partitioning

NASA Astrophysics Data System (ADS)

Patil, Riya Raghuvir

Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for selfpartitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the LegoRTM Mindstorms' NXT on a graphical programming platform using National Instruments' LabVIEW(TM) forming a team of communicating agents via NXT-Bee radio module. We single out mobility, communication and self-partition as the core elements of the work. The goal is to randomly explore a precinct for reference sites. Agents who have discovered the reference sites announce their target acquisition to form a network formed based upon the distance of each agent with the other wherein the self-partitioning begins to find an optimal partition. Further, to illustrate the work, an experimental test-bench of five Lego NXT robots is presented.

Prognostics for Microgrid Components

NASA Technical Reports Server (NTRS)

Saxena, Abhinav

2012-01-01

Prognostics is the science of predicting future performance and potential failures based on targeted condition monitoring. Moving away from the traditional reliability centric view, prognostics aims at detecting and quantifying the time to impending failures. This advance warning provides the opportunity to take actions that can preserve uptime, reduce cost of damage, or extend the life of the component. The talk will focus on the concepts and basics of prognostics from the viewpoint of condition-based systems health management. Differences with other techniques used in systems health management and philosophies of prognostics used in other domains will be shown. Examples relevant to micro grid systems and subsystems will be used to illustrate various types of prediction scenarios and the resources it take to set up a desired prognostic system. Specifically, the implementation results for power storage and power semiconductor components will demonstrate specific solution approaches of prognostics. The role of constituent elements of prognostics, such as model, prediction algorithms, failure threshold, run-to-failure data, requirements and specifications, and post-prognostic reasoning will be explained. A discussion on performance evaluation and performance metrics will conclude the technical discussion followed by general comments on open research problems and challenges in prognostics.

Rational bases for the use of the Immunoscore in routine clinical settings as a prognostic and predictive biomarker in cancer patients.

PubMed

Kirilovsky, Amos; Marliot, Florence; El Sissy, Carine; Haicheur, Nacilla; Galon, Jérôme; Pagès, Franck

2016-08-01

The American Joint Committee on Cancer/Union Internationale Contre le Cancer (AJCC/UICC) tumor, nodes, metastasis (TNM) classification system based on tumor features is used for prognosis estimation and treatment recommendations in most cancers. However, the clinical outcome can vary significantly among patients within the same tumor stage and TNM classification does not predict response to therapy. Therefore, many efforts have been focused on the identification of new markers. Multiple tumor cell-based approaches have been proposed but very few have been translated into the clinic. The recent demonstration of the essential role of the immune system in tumor progression has allowed great advances in the understanding of this complex disease and in the design of novel therapies. The analysis of the immune infiltrate by imaging techniques in large patient cohorts highlighted the prognostic impact of the in situ immune cell infiltrate in tumors. Moreover, the characterization of the immune infiltrates (e.g. type, density, distribution within the tumor, phenotype, activation status) in patients treated with checkpoint-blockade strategies could provide information to predict the disease outcome. In colorectal cancer, we have developed a prognostic score ('Immunoscore') that takes into account the distribution of the density of both CD3(+) lymphocytes and CD8(+) cytotoxic T cells in the tumor core and the invasive margin that could outperform TNM staging. Currently, an international retrospective study is under way to validate the Immunoscore prognostic performance in patients with colon cancer. The use of Immunoscore in clinical practice could improve the patients' prognostic assessment and therapeutic management. © The Japanese Society for Immunology. 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Prognostic significance of immunohistochemistry-based markers and algorithms in immunochemotherapy-treated diffuse large B cell lymphoma patients.

PubMed

Culpin, Rachel E; Sieniawski, Michal; Angus, Brian; Menon, Geetha K; Proctor, Stephen J; Milne, Paul; McCabe, Kate; Mainou-Fowler, Tryfonia

2013-12-01

To reassess the prognostic validity of immunohistochemical markers and algorithms identified in the CHOP era in immunochemotherapy-treated diffuse large B cell lymphoma patients. The prognostic significance of immunohistochemical markers (CD10, Bcl-6, Bcl-2, MUM1, Ki-67, CD5, GCET1, FoxP1, LMO2) and algorithms (Hans, Hans*, Muris, Choi, Choi*, Nyman, Visco-Young, Tally) was assessed using clinical diagnostic blocks taken from an unselected, population-based cohort of 190 patients treated with R-CHOP. Dichotomizing expression, low CD10 (<10%), low LMO2 (<70%) or high Bcl-2 (≥80%) predicted shorter overall survival (OS; P = 0.033, P = 0.010 and P = 0.008, respectively). High Bcl-2 (≥80%), low Bcl-6 (<60%), low GCET1 (<20%) or low LMO2 (<70%) predicted shorter progression-free survival (PFS; P = 0.001, P = 0.048, P = 0.045 and P = 0.002, respectively). The Hans, Hans* and Muris classifiers predicted OS (P = 0.022, P = 0.037 and P = 0.011) and PFS (P = 0.021, P = 0.020 and P = 0.004). The Choi, Choi* and Tally were associated with PFS (P = 0.049, P = 0.009 and P = 0.023). In multivariate analysis, the International Prognostic Index (IPI) was the only independent predictor of outcome (OS; HR: 2.60, P < 0.001 and PFS; HR: 2.91, P < 0.001). Results highlight the controversy surrounding immunohistochemistry-based algorithms in the R-CHOP era. The need for more robust markers, applicable to the clinic, for incorporation into improved prognostic systems is emphasized. © 2013 John Wiley & Sons Ltd.

PAM50 gene signatures and breast cancer prognosis with adjuvant anthracycline- and taxane-based chemotherapy: correlative analysis of C9741 (Alliance)

PubMed Central

Liu, Minetta C; Pitcher, Brandelyn N; Mardis, Elaine R; Davies, Sherri R; Friedman, Paula N; Snider, Jacqueline E; Vickery, Tammi L; Reed, Jerry P; DeSchryver, Katherine; Singh, Baljit; Gradishar, William J; Perez, Edith A; Martino, Silvana; Citron, Marc L; Norton, Larry; Winer, Eric P; Hudis, Clifford A; Carey, Lisa A; Bernard, Philip S; Nielsen, Torsten O; Perou, Charles M; Ellis, Matthew J; Barry, William T

2016-01-01

PAM50 intrinsic breast cancer subtypes are prognostic independent of standard clinicopathologic factors. CALGB 9741 demonstrated improved recurrence-free (RFS) and overall survival (OS) with 2-weekly dose-dense (DD) versus 3-weekly therapy. A significant interaction between intrinsic subtypes and DD-therapy benefit was hypothesized. Suitable tumor samples were available from 1,471 (73%) of 2,005 subjects. Multiplexed gene-expression profiling generated the PAM50 subtype call, proliferation score, and risk of recurrence score (ROR-PT) for the evaluable subset of 1,311 treated patients. The interaction between DD-therapy benefit and intrinsic subtype was tested in a Cox proportional hazards model using two-sided alpha=0.05. Additional multivariable Cox models evaluated the proliferation and ROR-PT scores as continuous measures with selected clinical covariates. Improved outcomes for DD therapy in the evaluable subset mirrored results from the complete data set (RFS; hazard ratio=1.20; 95% confidence interval=0.99–1.44) with 12.3-year median follow-up. Intrinsic subtypes were prognostic of RFS (P<0.0001) irrespective of treatment assignment. No subtype-specific treatment effect on RFS was identified (interaction P=0.44). Proliferation and ROR-PT scores were prognostic for RFS (both P<0.0001), but no association with treatment benefit was seen (P=0.14 and 0.59, respectively). Results were similar for OS. The prognostic value of PAM50 intrinsic subtype was greater than estrogen receptor/HER2 immunohistochemistry classification. PAM50 gene signatures were highly prognostic but did not predict for improved outcomes with DD anthracycline- and taxane-based therapy. Clinical validation studies will assess the ability of PAM50 and other gene signatures to stratify patients and individualize treatment based on expected risks of distant recurrence. PMID:28691057

US Intergroup Anal Carcinoma Trial: Tumor Diameter Predicts for Colostomy

PubMed Central

Ajani, Jaffer A.; Winter, Kathryn A.; Gunderson, Leonard L.; Pedersen, John; Benson, Al B.; Thomas, Charles R.; Mayer, Robert J.; Haddock, Michael G.; Rich, Tyvin A.; Willett, Christopher G.

2009-01-01

Purpose The US Gastrointestinal Intergroup Radiation Therapy Oncology Group 98-11 anal carcinoma trial showed that cisplatin-based concurrent chemoradiotherapy resulted in a significantly higher rate of colostomy compared with mitomycin-based therapy. Established prognostic variables for patients with anal carcinoma include tumor diameter, clinical nodal status, and sex, but pretreatment variables that would predict the likelihood of colostomy are unknown. Methods A secondary analysis was performed by combining patients in the two treatment arms to evaluate whether new predictive and prognostic variables would emerge. Univariate and multivariate analyses were carried out to correlate overall survival (OS), disease-free survival, and time to colostomy (TTC) with pretreatment and treatment variables. Results Of 682 patients enrolled, 644 patients were assessable and analyzed. In the multivariate analysis, tumor-related prognosticators for poorer OS included node-positive cancer (P ≤ .0001), large (> 5 cm) tumor diameter (P = .01), and male sex (P = .016). In the treatment-related categories, cisplatin-based therapy was statistically significantly associated with a higher rate of colostomy (P = .03) than was mitomycin-based therapy. In the pretreatment variables category, only large tumor diameter independently predicted for TTC (P = .008). Similarly, the cumulative 5-year colostomy rate was statistically significantly higher for large tumor diameter than for small tumor diameter (Gray's test; P = .0074). Clinical nodal status and sex were not predictive of TTC. Conclusion The combined analysis of the two arms of RTOG 98-11, representing the largest prospective database, reveals that tumor diameter (irrespective of the nodal status) is the only independent pretreatment variable that predicts TTC and 5-year colostomy rate in patients with anal carcinoma. PMID:19139424

Outcome and prognostic factors in metastatic urothelial carcinoma patients receiving second-line chemotherapy: an analysis of real-world clinical practice data in Japan.

PubMed

Matsumoto, Ryuji; Abe, Takashige; Ishizaki, Junji; Kikuchi, Hiroshi; Harabayashi, Toru; Minami, Keita; Sazawa, Ataru; Mochizuki, Tango; Akino, Tomoshige; Murakumo, Masashi; Osawa, Takahiro; Maruyama, Satoru; Murai, Sachiyo; Shinohara, Nobuo

2018-06-25

The objective of the present study was to investigate the survival outcome and prognostic factors of metastatic urothelial carcinoma patients treated with second-line systemic chemotherapy in real-world clinical practice. Overall, 114 patients with metastatic urothelial carcinoma undergoing second-line systemic chemotherapy were included in this retrospective analysis. The dominant second-line chemotherapy was a paclitaxel-based combination regimen (60%, 68/114). We assessed the progression-free survival and overall survival times using the Kaplan-Meier method. The Cox proportional hazards model was applied to identify the factors affecting overall survival. The median progression-free survival and overall survival times were 4 and 9 months, respectively. In the multivariate analysis, an Eastern Cooperative Oncology Group performance status score greater than 0 at presentation, C-reactive protein level ≧1 mg/dl and poor response to prior chemotherapy were adverse prognostic indicators. Patients with 0, 1, 2 and 3 of those risk factors had a median overall survival of 17, 12, 7 and 3 months, respectively. The Eastern Cooperative Oncology Group performance status at presentation, C-reactive protein level and response to prior chemotherapy were prognostic factors for metastatic urothelial carcinoma patients undergoing second-line chemotherapy. In the future, this information might help guide the choice of salvage treatment, such as second-line chemotherapy or immune checkpoint inhibitors, after the failure of first-line chemotherapy.

[The prognostic value of variables from the quality assurance program and of the rehabilitation-discharge report of the LVA Baden-Württemberg for early retirement: results of a retrospective cohort-study].

PubMed

Küpper-Nybelen, J; Rothenbacher, D; Jacobi, E; Brenner, H

2003-12-01

Since 1997 the LVA Baden-Württemberg pension insurance agency has implemented an instrument to measure the outcome quality of in-patient rehabilitation. The objective of this study was to evaluate the prognostic value of various short-term rehabilitation success markers and of variables of the quality assurance program and the rehab-discharge report of the LVA Baden-Württemberg on early retirement by means of a retrospective cohort study. The analysis was based on routinely registered data of patients who underwent in-hospital rehabilitation in a hospital accredited by the LVA Baden-Württemberg between June 1997 and June 1999. Baseline data included information from medical discharge reports and from the quality assurance programme. Follow-up information with regard to disability was collected until July 2000. The prognostic value of the quality assurance programme and of 4 standardized documented items from the medical discharge report was estimated by proportional hazards regression. In this analysis 6,823 patients aged 30-59 years who underwent an in-patient rehab programme between June 1997 and July 1999 in 5 of 6 LVA rehab clinics were included. During follow-up (mean duration: 1.8 years) 908 (13.3%) patients retired because of health-related disability. The variables with the strongest prognostic values were the evaluation of the patient health status by the physician and the patients themselves and the capacity to work. The variables with the highest prognostic value were the evaluation on a 1-6 visual analogue scale; a better assessment by one mark of the health status by physician and patient himself, respectively, was associated with a 53% and 40% reduced risk of disability. Fitness for work at discharge was the most prognostic variable from the discharge report. Patients who were able to work had a 78% reduced risk of disability compared to patients unable to work. Also of prognostic relevance were a positive performance and the duration of the inability to work the year before rehabilitation. The variables of the newly developed quality assurance programme of the LVA clearly demonstrated a prognostic value in terms of risk for subsequent early retirement. It should be considered to include the ability to work at discharge in the programme to further improve its prognostic value.

Atmospheric concentrations, sources and gas-particle partitioning of PAHs in Beijing after the 29th Olympic Games.

PubMed

Ma, Wan-Li; Sun, De-Zhi; Shen, Wei-Guo; Yang, Meng; Qi, Hong; Liu, Li-Yan; Shen, Ji-Min; Li, Yi-Fan

2011-07-01

A comprehensive sampling campaign was carried out to study atmospheric concentration of polycyclic aromatic hydrocarbons (PAHs) in Beijing and to evaluate the effectiveness of source control strategies in reducing PAHs pollution after the 29th Olympic Games. The sub-cooled liquid vapor pressure (logP(L)(o))-based model and octanol-air partition coefficient (K(oa))-based model were applied based on each seasonal dateset. Regression analysis among log K(P), logP(L)(o) and log K(oa) exhibited high significant correlations for four seasons. Source factors were identified by principle component analysis and contributions were further estimated by multiple linear regression. Pyrogenic sources and coke oven emission were identified as major sources for both the non-heating and heating seasons. As compared with literatures, the mean PAH concentrations before and after the 29th Olympic Games were reduced by more than 60%, indicating that the source control measures were effective for reducing PAHs pollution in Beijing. Copyright © 2011 Elsevier Ltd. All rights reserved.

Comparison of Prognostic and Diagnostic Approaches to Modeling Evapotranspiration in the Nile River Basin

NASA Astrophysics Data System (ADS)

Yilmaz, M.; Anderson, M. C.; Zaitchik, B. F.; Crow, W. T.; Hain, C.; Ozdogan, M.; Chun, J. A.

2012-12-01

Actual evapotranspiration (ET) can be estimated using both prognostic and diagnostic modeling approaches, providing independent yet complementary information for hydrologic applications. Both approaches have advantages and disadvantages. When provided with temporally continuous atmospheric forcing data, prognostic models offer continuous sub-daily ET information together with the full set of water and energy balance fluxes and states (i.e. soil moisture, runoff, sensible and latent heat). On the other hand, the diagnostic modeling approach provides ET estimates over regions where reliable information about available soil water is not known (e.g., due to irrigation practices or shallow ground water levels not included in the prognostic model structure, unknown soil texture or plant rooting depth, etc). Prognostic model-based ET estimates are of great interest whenever consistent and complete water budget information is required or when there is a need to project ET for climate or land use change scenarios. Diagnostic models establish a stronger link to remote sensing observations, can be applied in regions with limited or questionable atmospheric forcing data, and provide valuable observation-derived information about the current land-surface state. Analysis of independently obtained ET estimates is particularly important in data poor regions. Such comparisons can help to reduce the uncertainty in the modeled ET estimates and to exclude outliers based on physical considerations. The Nile river basin is home to tens of millions of people whose daily life depends on water extracted from the river Nile. Yet the complete basin scale water balance of the Nile has been studied only a few times, and the temporal and the spatial distribution of hydrological fluxes (particularly ET) are still a subject of active research. This is due in part to a scarcity of ground-based station data for validation. In such regions, comparison between prognostic and diagnostic model output may be a valuable model evaluation tool. Motivated by the complementary information that exists in prognostic and diagnostic energy balance modeling, as well as the need for evaluation of water consumption estimates over the Nile basin, the purpose of this study is to 1) better describe the conceptual differences between prognostic and diagnostic modeling, 2) present the potential for diagnostic models to capture important hydrologic features that are not explicitly represented in prognostic model, 3) explore the differences in these two approaches over the Nile Basin, where ground data are sparse and transnational data sharing is unreliable. More specifically, we will compare output from the Noah prognostic model and the Atmosphere-Land Exchange Inverse (ALEXI) diagnostic model generated over ground truth data-poor Nile basin. Preliminary results indicate spatially, temporally, and magnitude wise consistent flux estimates for ALEXI and NOAH over irrigated Delta region, while there are differences over river-fed wetlands.

Target Detection and Classification Using Seismic and PIR Sensors

DTIC Science & Technology

2012-06-01

time series analysis via wavelet - based partitioning,” Signal Process...regard, this paper presents a wavelet - based method for target detection and classification. The proposed method has been validated on data sets of...The work reported in this paper makes use of a wavelet - based feature extraction method , called Symbolic Dynamic Filtering (SDF) [12]–[14]. The

Prognostic categories and timing of negative prognostic communication from critical care physicians to family members at end-of-life in an intensive care unit.

PubMed

Gutierrez, Karen M

2013-09-01

Negative prognostic communication is often delayed in intensive care units, which limits time for families to prepare for end-of-life. This descriptive study, informed by ethnographic methods, was focused on exploring critical care physician communication of negative prognoses to families and identifying timing influences. Prognostic communication of critical care physicians to nurses and family members was observed and physicians and family members were interviewed. Physician perception of prognostic certainty, based on an accumulation of empirical data, and the perceived need for decision-making, drove the timing of prognostic communication, rather than family needs. Although prognoses were initially identified using intuitive knowledge for patients in one of the six identified prognostic categories, utilizing decision-making to drive prognostic communication resulted in delayed prognostic communication to families until end-of-life (EOL) decisions could be justified with empirical data. Providers will better meet the needs of families who desire earlier prognostic information by separating prognostic communication from decision-making and communicating the possibility of a poor prognosis based on intuitive knowledge, while acknowledging the uncertainty inherent in prognostication. This sets the stage for later prognostic discussions focused on EOL decisions, including limiting or withdrawing treatment, which can be timed when empirical data substantiate intuitive prognoses. This allows additional time for families to anticipate and prepare for end-of-life decision-making. © 2012 John Wiley & Sons Ltd.

Boundaries on Range-Range Constrained Admissible Regions for Optical Space Surveillance

NASA Astrophysics Data System (ADS)

Gaebler, J. A.; Axelrad, P.; Schumacher, P. W., Jr.

We propose a new type of admissible-region analysis for track initiation in multi-satellite problems when apparent angles measured at known stations are the only observable. The goal is to create an efficient and parallelizable algorithm for computing initial candidate orbits for a large number of new targets. It takes at least three angles-only observations to establish an orbit by traditional means. Thus one is faced with a problem that requires N-choose-3 sets of calculations to test every possible combination of the N observations. An alternative approach is to reduce the number of combinations by making hypotheses of the range to a target along the observed line-of-sight. If realistic bounds on the range are imposed, consistent with a given partition of the space of orbital elements, a pair of range possibilities can be evaluated via Lambert’s method to find candidate orbits for that that partition, which then requires Nchoose- 2 times M-choose-2 combinations, where M is the average number of range hypotheses per observation. The contribution of this work is a set of constraints that establish bounds on the range-range hypothesis region for a given element-space partition, thereby minimizing M. Two effective constraints were identified, which together, constrain the hypothesis region in range-range space to nearly that of the true admissible region based on an orbital partition. The first constraint is based on the geometry of the vacant orbital focus. The second constraint is based on time-of-flight and Lagrange’s form of Kepler’s equation. A complete and efficient parallelization of the problem is possible on this approach because the element partitions can be arbitrary and can be handled independently of each other.

Adjusted Analyses in Studies Addressing Therapy and Harm: Users' Guides to the Medical Literature.

PubMed

Agoritsas, Thomas; Merglen, Arnaud; Shah, Nilay D; O'Donnell, Martin; Guyatt, Gordon H

2017-02-21

Observational studies almost always have bias because prognostic factors are unequally distributed between patients exposed or not exposed to an intervention. The standard approach to dealing with this problem is adjusted or stratified analysis. Its principle is to use measurement of risk factors to create prognostically homogeneous groups and to combine effect estimates across groups.The purpose of this Users' Guide is to introduce readers to fundamental concepts underlying adjustment as a way of dealing with prognostic imbalance and to the basic principles and relative trustworthiness of various adjustment strategies.One alternative to the standard approach is propensity analysis, in which groups are matched according to the likelihood of membership in exposed or unexposed groups. Propensity methods can deal with multiple prognostic factors, even if there are relatively few patients having outcome events. However, propensity methods do not address other limitations of traditional adjustment: investigators may not have measured all relevant prognostic factors (or not accurately), and unknown factors may bias the results.A second approach, instrumental variable analysis, relies on identifying a variable associated with the likelihood of receiving the intervention but not associated with any prognostic factor or with the outcome (other than through the intervention); this could mimic randomization. However, as with assumptions of other adjustment approaches, it is never certain if an instrumental variable analysis eliminates bias.Although all these approaches can reduce the risk of bias in observational studies, none replace the balance of both known and unknown prognostic factors offered by randomization.

Analyzing the Responses of 7-8 Year Olds When Solving Partitioning Problems

ERIC Educational Resources Information Center

Badillo, Edelmira; Font, Vicenç; Edo, Mequè

2015-01-01

We analyze the mathematical solutions of 7- to 8-year-old pupils while individually solving an arithmetic problem. The analysis was based on the "configuration of objects," an instrument derived from the onto-semiotic approach to mathematical knowledge. Results are illustrated through a number of cases. From the analysis of mathematical…

Programmed Death Cell Ligand 1 (PD-L1) Is Associated With Survival in Stage I Non-Small Cell Lung Cancer.

PubMed

Sepesi, Boris; Cuentas, Edwin Parra; Canales, Jaime Rodriguez; Behrens, Carmen; Correa, Arlene M; Vaporciyan, Ara; Weissferdt, Annikka; Kalhor, Neda; Moran, Cesar; Swisher, Stephen; Wistuba, Ignacio

2017-01-01

Programmed cell death ligand (PD-L1) has been studied as a predictive immunotherapy biomarker. We investigated PD-L1 expression in the whole tumor and in tumor-infiltrating macrophages (TIMs) as a prognostic biomarker in surgically resected pathologic stage I non-small cell lung cancer. Pathologic specimen from 113 patients with stage I lung cancer (pT1-2a, N0, M0, tumor size 1-5 cm, 79 adenocarcinoma, 34 squamous cell carcinoma) were analyzed for PD-L1 expression in the tumor and in the TIMs using immunohistochemistry and image analysis. Statistics included recursive partitioning, univariable, multivariable, and Kaplan-Meier analyses. Patients whose tumors expressed <4.7% PD-L1 (N = 87) experienced significantly better overall survival (OS) (P = 0.001) than patients with PD-L1 >4.7% (N = 26). Patients with PD-L1 expression in macrophages <6.3% (N = 24) also experienced significantly better (P = 0.005) OS than patients with >6.3% (N = 89). The best outcomes were observed in patients with low PD-L1 expression in both tumor and macrophages with 5-year OS of 94% (N = 17). Contrarily, patients with high PD-L1 expression in both tumor and macrophages experienced 5-year OS of 20% (N = 19). Low PD-L1 expression in the tumor and in the TIMs was independently associated with survival in multivariable analysis (P = 0.000 and P = 0.030, respectively). Lower PD-L1 % expression in the tumor and in the TIMs seems to be associated with significantly better OS in surgically resected stage I lung cancer. Additional studies are needed to validate PD-L1 as a prognostic biomarker in lung cancer and to study the mechanisms of intratumoral immune response. Copyright © 2017 Elsevier Inc. All rights reserved.

Using Cluster Analysis to Compartmentalize a Large Managed Wetland Based on Physical, Biological, and Climatic Geospatial Attributes.

PubMed

Hahus, Ian; Migliaccio, Kati; Douglas-Mankin, Kyle; Klarenberg, Geraldine; Muñoz-Carpena, Rafael

2018-04-27

Hierarchical and partitional cluster analyses were used to compartmentalize Water Conservation Area 1, a managed wetland within the Arthur R. Marshall Loxahatchee National Wildlife Refuge in southeast Florida, USA, based on physical, biological, and climatic geospatial attributes. Single, complete, average, and Ward's linkages were tested during the hierarchical cluster analyses, with average linkage providing the best results. In general, the partitional method, partitioning around medoids, found clusters that were more evenly sized and more spatially aggregated than those resulting from the hierarchical analyses. However, hierarchical analysis appeared to be better suited to identify outlier regions that were significantly different from other areas. The clusters identified by geospatial attributes were similar to clusters developed for the interior marsh in a separate study using water quality attributes, suggesting that similar factors have influenced variations in both the set of physical, biological, and climatic attributes selected in this study and water quality parameters. However, geospatial data allowed further subdivision of several interior marsh clusters identified from the water quality data, potentially indicating zones with important differences in function. Identification of these zones can be useful to managers and modelers by informing the distribution of monitoring equipment and personnel as well as delineating regions that may respond similarly to future changes in management or climate.

Weak-value amplification and optimal parameter estimation in the presence of correlated noise

NASA Astrophysics Data System (ADS)

Sinclair, Josiah; Hallaji, Matin; Steinberg, Aephraim M.; Tollaksen, Jeff; Jordan, Andrew N.

2017-11-01

We analytically and numerically investigate the performance of weak-value amplification (WVA) and related parameter estimation methods in the presence of temporally correlated noise. WVA is a special instance of a general measurement strategy that involves sorting data into separate subsets based on the outcome of a second "partitioning" measurement. Using a simplified correlated noise model that can be analyzed exactly together with optimal statistical estimators, we compare WVA to a conventional measurement method. We find that WVA indeed yields a much lower variance of the parameter of interest than the conventional technique does, optimized in the absence of any partitioning measurements. In contrast, a statistically optimal analysis that employs partitioning measurements, incorporating all partitioned results and their known correlations, is found to yield an improvement—typically slight—over the noise reduction achieved by WVA. This result occurs because the simple WVA technique is not tailored to any specific noise environment and therefore does not make use of correlations between the different partitions. We also compare WVA to traditional background subtraction, a familiar technique where measurement outcomes are partitioned to eliminate unknown offsets or errors in calibration. Surprisingly, for the cases we consider, background subtraction turns out to be a special case of the optimal partitioning approach, possessing a similar typically slight advantage over WVA. These results give deeper insight into the role of partitioning measurements (with or without postselection) in enhancing measurement precision, which some have found puzzling. They also resolve previously made conflicting claims about the usefulness of weak-value amplification to precision measurement in the presence of correlated noise. We finish by presenting numerical results to model a more realistic laboratory situation of time-decaying correlations, showing that our conclusions hold for a wide range of statistical models.

New Comprehensive Cytogenetic Scoring System for Primary Myelodysplastic Syndromes (MDS) and Oligoblastic Acute Myeloid Leukemia After MDS Derived From an International Database Merge

PubMed Central

Schanz, Julie; Tüchler, Heinz; Solé, Francesc; Mallo, Mar; Luño, Elisa; Cervera, José; Granada, Isabel; Hildebrandt, Barbara; Slovak, Marilyn L.; Ohyashiki, Kazuma; Steidl, Christian; Fonatsch, Christa; Pfeilstöcker, Michael; Nösslinger, Thomas; Valent, Peter; Giagounidis, Aristoteles; Aul, Carlo; Lübbert, Michael; Stauder, Reinhard; Krieger, Otto; Garcia-Manero, Guillermo; Faderl, Stefan; Pierce, Sherry; Le Beau, Michelle M.; Bennett, John M.; Greenberg, Peter; Germing, Ulrich; Haase, Detlef

2012-01-01

Purpose The karyotype is a strong independent prognostic factor in myelodysplastic syndromes (MDS). Since the implementation of the International Prognostic Scoring System (IPSS) in 1997, knowledge concerning the prognostic impact of abnormalities has increased substantially. The present study proposes a new and comprehensive cytogenetic scoring system based on an international data collection of 2,902 patients. Patients and Methods Patients were included from the German-Austrian MDS Study Group (n = 1,193), the International MDS Risk Analysis Workshop (n = 816), the Spanish Hematological Cytogenetics Working Group (n = 849), and the International Working Group on MDS Cytogenetics (n = 44) databases. Patients with primary MDS and oligoblastic acute myeloid leukemia (AML) after MDS treated with supportive care only were evaluated for overall survival (OS) and AML evolution. Internal validation by bootstrap analysis and external validation in an independent patient cohort were performed to confirm the results. Results In total, 19 cytogenetic categories were defined, providing clear prognostic classification in 91% of all patients. The abnormalities were classified into five prognostic subgroups (P < .001): very good (median OS, 61 months; hazard ratio [HR], 0.5; n = 81); good (49 months; HR, 1.0 [reference category]; n = 1,809); intermediate (26 months; HR, 1.6; n = 529); poor (16 months; HR, 2.6; n = 148); and very poor (6 months; HR, 4.2; n = 187). The internal and external validations confirmed the results of the score. Conclusion In conclusion, these data should contribute to the ongoing efforts to update the IPSS by refining the cytogenetic risk categories. PMID:22331955

Adjusting for multiple prognostic factors in the analysis of randomised trials

PubMed Central

2013-01-01

Background When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not generally need to depend on the method of randomisation used. Most methods of analysis work well with large sample sizes, however treating strata as random effects should be the analysis method of choice with binary or time-to-event outcomes and a small sample size. PMID:23898993

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

PubMed

Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

A novel scoring system for gastric cancer risk assessment based on the expression of three CLIP4 DNA methylation-associated genes

PubMed Central

Hu, Chenggong; Zhou, Yongfang; Liu, Chang; Kang, Yan

2018-01-01

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-associated mortality worldwide. In the current study, comprehensive bioinformatic analyses were performed to develop a novel scoring system for GC risk assessment based on CAP-Gly domain containing linker protein family member 4 (CLIP4) DNA methylation status. Two GC datasets with methylation sequencing information and mRNA expression profiling were downloaded from the The Cancer Genome Atlas and Gene Expression Omnibus databases. Differentially expressed genes (DEGs) between the CLIP4 hypermethylation and CLIP4 hypomethylation groups were screened using the limma package in R 3.3.1, and survival analysis of these DEGs was performed using the survival package. A risk scoring system was established via regression factor-weighted gene expression based on linear combination to screen the most important genes associated with CLIP4 methylation and prognosis. Genes associated with high/low-risk value were selected using the limma package. Functional enrichment analysis of the top 500 DEGs that positively and negatively associated with risk values was performed using DAVID 6.8 online and the gene set enrichment analysis (GSEA) software. In total, 35 genes were identified to be that significantly associated with prognosis and CLIP4 DNA methylation, and three prognostic signature genes, claudin-11 (CLDN11), apolipoprotein D (APOD), and chordin like 1 (CHRDL1), were used to establish a risk assessment system. The prognostic scoring system exhibited efficiency in classifying patients with different prognoses, where the low-risk groups had significantly longer overall survival times than those in the high-risk groups. CLDN11, APOD and CHRDL1 exhibited reduced expression in the hypermethylation and low-risk groups compare with the hypomethylation and high-risk groups, respectively. Multivariate Cox analysis indicated that risk value could be used as an independent prognostic factor. In functional analysis, six functional gene ontology terms and five GSEA pathways were associated with CLDN11, APOD and CHRDL1. The results established the credibility of the scoring system in this study. Additionally, these three genes, which were significantly associated with CLIP4 DNA methylation and GC risk assessment, were identified as potential prognostic biomarkers. PMID:29901187

Markov Modeling of Component Fault Growth over a Derived Domain of Feasible Output Control Effort Modifications

NASA Technical Reports Server (NTRS)

Bole, Brian; Goebel, Kai; Vachtsevanos, George

2012-01-01

This paper introduces a novel Markov process formulation of stochastic fault growth modeling, in order to facilitate the development and analysis of prognostics-based control adaptation. A metric representing the relative deviation between the nominal output of a system and the net output that is actually enacted by an implemented prognostics-based control routine, will be used to define the action space of the formulated Markov process. The state space of the Markov process will be defined in terms of an abstracted metric representing the relative health remaining in each of the system s components. The proposed formulation of component fault dynamics will conveniently relate feasible system output performance modifications to predictions of future component health deterioration.

Prognostic value of stromal decorin expression in patients with breast cancer: a meta-analysis.

PubMed

Li, Shuang-Jiang; Chen, Da-Li; Zhang, Wen-Biao; Shen, Cheng; Che, Guo-Wei

2015-11-01

Numbers of studies have investigated the biological functions of decorin (DCN) in oncogenesis, tumor progression, angiogenesis and metastasis. Although many of them aim to highlight the prognostic value of stromal DCN expression in breast cancer, some controversial results still exist and a consensus has not been reached until now. Therefore, our meta-analysis aims to determine the prognostic significance of stromal DCN expression in breast cancer patients. PubMed, EMBASE, the Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for full-text literatures met out inclusion criteria. We applied the hazard ratio (HR) with 95% confidence interval (CI) as the appropriate summarized statistics. Q-test and I(2) statistic were employed to estimate the level of heterogeneity across the included studies. Sensitivity analysis was conducted to further identify the possible origins of heterogeneity. The publication bias was detected by Begg's test and Egger's test. There were three English literatures (involving 6 studies) included into our meta-analysis. On the one hand, both the summarized outcomes based on univariate analysis (HR: 0.513; 95% CI: 0.406-0.648; P<0.001) and multivariate analysis (HR: 0.544; 95% CI: 0.388-0.763; P<0.001) indicated that stromal DCN expression could promise the high cancer-specific survival (CSS) of breast cancer patients. On the other hand, both the summarized outcomes based on univariate analysis (HR: 0.504; 95% CI: 0.389-0.651; P<0.001) and multivariate analysis (HR: 0.568; 95% CI: 0.400-0.806; P=0.002) also indicated that stromal DCN expression was positively associated with high disease-free survival (DFS) of breast cancer patients. No significant heterogeneity or publication bias was observed within this meta-analysis. The present evidences indicate that high stromal DCN expression can significantly predict the good prognosis in patients with breast cancer. The discoveries from our meta-analysis have better be confirmed in the updated review pooling more relevant investigations in the future.

Prognostic Value of RUNX1 Mutations in AML: A Meta-Analysis

PubMed

Jalili, Mahdi; Yaghmaie, Marjan; Ahmadvand, Mohammad; Alimoghaddam, Kamran; Mousavi, Seyed Asadollah; Vaezi, Mohammad; Ghavamzadeh, Ardeshir

2018-02-26

The RUNX1 (AML1) gene is a relatively infrequent mutational target in cases of acute myeloid leukemia (AML). Previous work indicated that RUNX1 mutations can have pathological and prognostic implications. To evaluate prognostic value, we conducted a meta-analysis of 4 previous published works with data for survival according to RUNX1 mutation status. Pooled hazard ratios for overall survival and disease-free survival were 1.55 (95% confidence interval (CI) = 1.11–2.15; p-value = 0.01) and 1.76 (95% CI = 1.24–2.52; p-value = 0.002), respectively, for cases positive for RUNX1 mutations. This evidence supports clinical implications of RUNX1 mutations in the development and progression of AML cases and points to the possibility of a distinct category within the newer WHO classification. Though it must be kept in mind that the present work was based on data extracted from observational studies, the findings suggest that the RUNX1 status can contribute to risk-stratification and decision-making in management of AML. Creative Commons Attribution License

Multiple Damage Progression Paths in Model-Based Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Goebel, Kai Frank

2011-01-01

Model-based prognostics approaches employ domain knowledge about a system, its components, and how they fail through the use of physics-based models. Component wear is driven by several different degradation phenomena, each resulting in their own damage progression path, overlapping to contribute to the overall degradation of the component. We develop a model-based prognostics methodology using particle filters, in which the problem of characterizing multiple damage progression paths is cast as a joint state-parameter estimation problem. The estimate is represented as a probability distribution, allowing the prediction of end of life and remaining useful life within a probabilistic framework that supports uncertainty management. We also develop a novel variance control mechanism that maintains an uncertainty bound around the hidden parameters to limit the amount of estimation uncertainty and, consequently, reduce prediction uncertainty. We construct a detailed physics-based model of a centrifugal pump, to which we apply our model-based prognostics algorithms. We illustrate the operation of the prognostic solution with a number of simulation-based experiments and demonstrate the performance of the chosen approach when multiple damage mechanisms are active

The Impact of Local and Regional Disease Extent on Overall Survival in Patients With Advanced Stage IIIB/IV Non-Small Cell Lung Carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Higginson, Daniel S., E-mail: daniel.higginson@gmail.com; Chen, Ronald C.; Tracton, Gregg

2012-11-01

Purpose: Patients with advanced stage IIIB or stage IV non-small cell lung carcinoma are typically treated with initial platinum-based chemotherapy. A variety of factors (eg, performance status, gender, age, histology, weight loss, and smoking history) are generally accepted as predictors of overall survival. Because uncontrolled pulmonary disease constitutes a major cause of death in these patients, we hypothesized that clinical and radiographic factors related to intrathoracic disease at diagnosis may be prognostically significant in addition to conventional factors. The results have implications regarding the selection of patients for whom palliative thoracic radiation therapy may be of most benefit. Methods andmore » Materials: We conducted a pooled analysis of 189 patients enrolled at a single institution into 9 prospective phase II and III clinical trials involving first-line, platinum-based chemotherapy. Baseline clinical and radiographic characteristics before trial enrollment were analyzed as possible predictors for subsequent overall survival. To assess the relationship between anatomic location and volume of disease within the thorax and its effect on survival, the pre-enrollment computed tomography images were also analyzed by contouring central and peripheral intrapulmonary disease. Results: On univariate survival analysis, multiple pulmonary-related factors were significantly associated with worse overall survival, including pulmonary symptoms at presentation (P=.0046), total volume of intrathoracic disease (P=.0006), and evidence of obstruction of major bronchi or vessels on prechemotherapy computed tomography (P<.0001). When partitioned into central and peripheral volumes, central (P<.0001) but not peripheral (P=.74) disease was associated with worse survival. On multivariate analysis with known factors, pulmonary symptoms (hazard ratio, 1.46; P=.042), central disease volume (hazard ratio, 1.47; P=.042), and bronchial/vascular compression (hazard ratio, 1.54; P=.022) remained significant. Conclusions: Patients with bulky central disease, bronchial/vascular compression, and/or pulmonary symptoms exhibited worse overall survival after first-line, platinum-based chemotherapy. A subset of these patients may be studied to determine whether early, planned palliative thoracic radiation could also be of benefit.« less

Prognostic significance of peripheral monocyte count in patients with extranodal natural killer/T-cell lymphoma

PubMed Central

2013-01-01

Background Extranodal natural killer/T-cell lymphoma (ENKL) has heterogeneous clinical manifestations and prognosis. This study aims to evaluate the prognostic impact of absolute monocyte count (AMC) in ENKL, and provide some immunologically relevant information for better risk stratification in patients with ENKL. Methods Retrospective data from 163 patients newly diagnosed with ENKL were analyzed. The absolute monocyte count (AMC) at diagnosis was analyzed as continuous and dichotomized variables. Independent prognostic factors of survival were determined by Cox regression analysis. Results The AMC at diagnosis were related to overall survival (OS) and progression-free survival (PFS) in patients with ENKL. Multivariate analysis identified AMC as independent prognostic factors of survival, independent of International Prognostic Index (IPI) and Korean prognostic index (KPI). The prognostic index incorporating AMC and absolute lymphocyte count (ALC), another surrogate factor of immune status, could be used to stratify all 163 patients with ENKL into different prognostic groups. For patients who received chemotherapy followed by radiotherapy (102 cases), the three AMC/ALC index categories identified patients with significantly different survivals. When superimposed on IPI or KPI categories, the AMC/ALC index was better able to identify high-risk patients in the low-risk IPI or KPI category. Conclusion The baseline peripheral monocyte count is shown to be an effective prognostic indicator of survival in ENKL patients. The prognostic index related to tumor microenvironment might be helpful to identify high-risk patients with ENKL. PMID:23638998

A hybrid PCA-CART-MARS-based prognostic approach of the remaining useful life for aircraft engines.

PubMed

Sánchez Lasheras, Fernando; García Nieto, Paulino José; de Cos Juez, Francisco Javier; Mayo Bayón, Ricardo; González Suárez, Victor Manuel

2015-03-23

Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS) technique with the principal component analysis (PCA), dendrograms and classification and regression trees (CARTs). Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL) with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.). Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks) also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

PubMed Central

Lasheras, Fernando Sánchez; Nieto, Paulino José García; de Cos Juez, Francisco Javier; Bayón, Ricardo Mayo; Suárez, Victor Manuel González

2015-01-01

Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS) technique with the principal component analysis (PCA), dendrograms and classification and regression trees (CARTs). Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL) with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.). Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks) also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines. PMID:25806876

[PROGNOSTIC MODELS IN MODERN MANAGEMENT OF VULVAR CANCER].

PubMed

Tsvetkov, Ch; Gorchev, G; Tomov, S; Nikolova, M; Genchev, G

2016-01-01

The aim of the research was to evaluate and analyse prognosis and prognostic factors in patients with squamous cell vulvar carcinoma after primary surgery with individual approach applied during the course of treatment. In the period between January 2000 and July 2010, 113 patients with squamous cell carcinoma of the vulva were diagnosed and operated on at Gynecologic Oncology Clinic of Medical University, Pleven. All the patients were monitored at the same clinic. Individual approach was applied to each patient and whenever it was possible, more conservative operative techniques were applied. The probable clinicopathological characteristics influencing the overall survival and recurrence free survival were analyzed. Univariate statistical analysis and Cox regression analysis were made in order to evaluate the characteristics, which were statistically significant for overall survival and survival without recurrence. A multivariate logistic regression analysis (Forward Wald procedure) was applied to evaluate the combined influence of the significant factors. While performing the multivariate analysis, the synergic effect of the independent prognostic factors of both kinds of survivals was also evaluated. Approaching individually each patient, we applied the following operative techniques: 1. Deep total radical vulvectomy with separate incisions for lymph dissection (LD) or without dissection--68 (60.18 %) patients. 2. En-bloc vulvectomy with bilateral LD without vulva reconstruction--10 (8.85%) 3. Modified radical vulvactomy (hemivulvectomy, patial vulvactomy)--25 (22.02%). 4. wide-local excision--3 (2.65%). 5. Simple (total /partial) vulvectomy--5 (4.43%) patients. 6. En-bloc resection with reconstruction--2 (1.77%) After a thorough analysis of the overall survival and recurrence free survival, we made the conclusion that the relapse occurrence and clinical stage of FIGO were independent prognostic factors for overall survival and the independent prognostic factors for recurrence free survival were: metastatic inguinal nodes (unilateral or bilateral), tumor size (above or below 3 cm) and lymphovascular space invasion. On the basis of these results we created two prognostic models: 1. A prognostic model of overall survival 2. A prognostic model for survival without recurrence. Following the surgical staging of the disease, were able to gather and analyse important clinicopathological indexes, which gave us the opportunity to form prognostic groups for overall survival and recurrence-free survival.

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less

Chaos synchronization basing on symbolic dynamics with nongenerating partition.

PubMed

Wang, Xingyuan; Wang, Mogei; Liu, Zhenzhen

2009-06-01

Using symbolic dynamics and information theory, we study the information transmission needed for synchronizing unidirectionally coupled oscillators. It is found that when sustaining chaos synchronization with nongenerating partition, the synchronization error will be larger than a critical value, although the required coupled channel capacity can be smaller than the case of using a generating partition. Then we show that no matter whether a generating or nongenerating partition is in use, a high-quality detector can guarantee the lead of the response oscillator, while the lag responding can make up the low precision of the detector. A practicable synchronization scheme basing on a nongenerating partition is also proposed in this paper.

The structure-AChE inhibitory activity relationships study in a series of pyridazine analogues.

PubMed

Saracoglu, M; Kandemirli, F

2009-07-01

The structure-activity relationships (SAR) are investigated by means of the Electronic-Topological Method (ETM) followed by the Neural Networks application (ETM-NN) for a class of anti-cholinesterase inhibitors (AChE, 53 molecules) being pyridazine derivatives. AChE activities of the series were measured in IC(50) units, and relative to the activity levels, the series was partitioned into classes of active and inactive compounds. Based on pharmacophores and antipharmacophores calculated by the ETM-software as sub-matrices containing important spatial and electronic characteristics, a system for the activity prognostication is developed. Input data for the ETM were taken as the results of conformational and quantum-mechanics calculations. To predict the activity, we used one of the most well known neural networks, namely, the feed-forward neural networks (FFNNs) trained with the back propagation algorithm. The supervised learning was performed using a variant of FFNN known as the Associative Neural Networks (ASNN). The result of the testing revealed that the high ETM's ability of predicting both activity and inactivity of potential AChE inhibitors. Analysis of HOMOs for the compounds containing Ph1 and APh1 has shown that atoms with the highest values of the atomic orbital coefficients are mainly those atoms that enter into the pharmacophores. Thus, the set of pharmacophores and antipharmacophores found as the result of this study forms a basis for a system of the anti-cholinesterase activity prediction.

Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods.

PubMed

Parkinson, Craig; Foley, Kieran; Whybra, Philip; Hills, Robert; Roberts, Ashley; Marshall, Chris; Staffurth, John; Spezi, Emiliano

2018-04-11

Prognosis in oesophageal cancer (OC) is poor. The 5-year overall survival (OS) rate is approximately 15%. Personalised medicine is hoped to increase the 5- and 10-year OS rates. Quantitative analysis of PET is gaining substantial interest in prognostic research but requires the accurate definition of the metabolic tumour volume. This study compares prognostic models developed in the same patient cohort using individual PET segmentation algorithms and assesses the impact on patient risk stratification. Consecutive patients (n = 427) with biopsy-proven OC were included in final analysis. All patients were staged with PET/CT between September 2010 and July 2016. Nine automatic PET segmentation methods were studied. All tumour contours were subjectively analysed for accuracy, and segmentation methods with < 90% accuracy were excluded. Standardised image features were calculated, and a series of prognostic models were developed using identical clinical data. The proportion of patients changing risk classification group were calculated. Out of nine PET segmentation methods studied, clustering means (KM2), general clustering means (GCM3), adaptive thresholding (AT) and watershed thresholding (WT) methods were included for analysis. Known clinical prognostic factors (age, treatment and staging) were significant in all of the developed prognostic models. AT and KM2 segmentation methods developed identical prognostic models. Patient risk stratification was dependent on the segmentation method used to develop the prognostic model with up to 73 patients (17.1%) changing risk stratification group. Prognostic models incorporating quantitative image features are dependent on the method used to delineate the primary tumour. This has a subsequent effect on risk stratification, with patients changing groups depending on the image segmentation method used.

Cancer of the ovary, fallopian tube, and peritoneum: a population-based comparison of the prognostic factors and outcomes.

PubMed

Rottmann, Miriam; Burges, A; Mahner, S; Anthuber, C; Beck, T; Grab, D; Schnelzer, A; Kiechle, M; Mayr, D; Pölcher, M; Schubert-Fritschle, G; Engel, J

2017-09-01

The objective was to compare the prognostic factors and outcomes among primary ovarian cancer (OC), fallopian tube cancer (FC), and peritoneal cancer (PC) patients in a population-based setting. We analysed 5399 OC, 327 FC, and 416 PC patients diagnosed between 1998 and 2014 in the catchment area of the Munich Cancer Registry (meanwhile 4.8 million inhabitants). Tumour site differences were examined by comparing prognostic factors, treatments, the time to progression, and survival. The effect of the tumour site was additionally analysed by a Cox regression model. The median age at diagnosis, histology, and FIGO stage significantly differed among the tumour sites (p < 0.001); PC patients were older, more often diagnosed with a serous subtype, and in FIGO stage III or IV. The time to progression and survival significantly differed among the tumour sites. When stratified by FIGO stage, the differences in time to progression disappeared, and the differences in survival considerably weakened. The differences in the multivariate survival analysis showed an almost identical outcome in PC patients (HR 1.07 [0.91-1.25]) and an improved survival of FC patients (HR 0.63 [0.49-0.81]) compared to that of OC patients. The comparison of OC, FC, and PC patients in this large-scale population-based study showed differences in the prognostic factors. These differences primarily account for the inferior outcome of PC patients, and for the improved survival of FC compared to OC patients.

Prognostic Classifier Based on Genome-Wide DNA Methylation Profiling in Well-Differentiated Thyroid Tumors.

PubMed

Bisarro Dos Reis, Mariana; Barros-Filho, Mateus Camargo; Marchi, Fábio Albuquerque; Beltrami, Caroline Moraes; Kuasne, Hellen; Pinto, Clóvis Antônio Lopes; Ambatipudi, Srikant; Herceg, Zdenko; Kowalski, Luiz Paulo; Rogatto, Silvia Regina

2017-11-01

Even though the majority of well-differentiated thyroid carcinoma (WDTC) is indolent, a number of cases display an aggressive behavior. Cumulative evidence suggests that the deregulation of DNA methylation has the potential to point out molecular markers associated with worse prognosis. To identify a prognostic epigenetic signature in thyroid cancer. Genome-wide DNA methylation assays (450k platform, Illumina) were performed in a cohort of 50 nonneoplastic thyroid tissues (NTs), 17 benign thyroid lesions (BTLs), and 74 thyroid carcinomas (60 papillary, 8 follicular, 2 Hürthle cell, 1 poorly differentiated, and 3 anaplastic). A prognostic classifier for WDTC was developed via diagonal linear discriminant analysis. The results were compared with The Cancer Genome Atlas (TCGA) database. A specific epigenetic profile was detected according to each histological subtype. BTLs and follicular carcinomas showed a greater number of methylated CpG in comparison with NTs, whereas hypomethylation was predominant in papillary and undifferentiated carcinomas. A prognostic classifier based on 21 DNA methylation probes was able to predict poor outcome in patients with WDTC (sensitivity 63%, specificity 92% for internal data; sensitivity 64%, specificity 88% for TCGA data). High-risk score based on the classifier was considered an independent factor of poor outcome (Cox regression, P < 0.001). The methylation profile of thyroid lesions exhibited a specific signature according to the histological subtype. A meaningful algorithm composed of 21 probes was capable of predicting the recurrence in WDTC. Copyright © 2017 Endocrine Society

Single nucleotide polymorphism array karyotyping: a diagnostic and prognostic tool in myelodysplastic syndromes with unsuccessful conventional cytogenetic testing.

PubMed

Arenillas, Leonor; Mallo, Mar; Ramos, Fernando; Guinta, Kathryn; Barragán, Eva; Lumbreras, Eva; Larráyoz, María-José; De Paz, Raquel; Tormo, Mar; Abáigar, María; Pedro, Carme; Cervera, José; Such, Esperanza; José Calasanz, María; Díez-Campelo, María; Sanz, Guillermo F; Hernández, Jesús María; Luño, Elisa; Saumell, Sílvia; Maciejewski, Jaroslaw; Florensa, Lourdes; Solé, Francesc

2013-12-01

Cytogenetic aberrations identified by metaphase cytogenetics (MC) have diagnostic, prognostic, and therapeutic implications in myelodysplastic syndromes (MDS). However, in some MDS patients MC study is unsuccesful. Single nucleotide polymorphism array (SNP-A) based karyotyping could be helpful in these cases. We performed SNP-A in 62 samples from bone marrow or peripheral blood of primary MDS with an unsuccessful MC study. SNP-A analysis enabled the detection of aberrations in 31 (50%) patients. We used the copy number alteration information to apply the International Prognostic Scoring System (IPSS) and we observed differences in survival between the low/intermediate-1 and intermediate-2/high risk patients. We also saw differences in survival between very low/low/intermediate and the high/very high patients when we applied the revised IPSS (IPSS-R). In conclusion, SNP-A can be used successfully in PB samples and the identification of CNA by SNP-A improve the diagnostic and prognostic evaluation of this group of MDS patients. Copyright © 2013 Wiley Periodicals, Inc.

Prognostics of Power Mosfets Under Thermal Stress Accelerated Aging Using Data-Driven and Model-Based Methodologies

NASA Technical Reports Server (NTRS)

Celaya, Jose; Saxena, Abhinav; Saha, Sankalita; Goebel, Kai F.

2011-01-01

An approach for predicting remaining useful life of power MOSFETs (metal oxide field effect transistor) devices has been developed. Power MOSFETs are semiconductor switching devices that are instrumental in electronics equipment such as those used in operation and control of modern aircraft and spacecraft. The MOSFETs examined here were aged under thermal overstress in a controlled experiment and continuous performance degradation data were collected from the accelerated aging experiment. Dieattach degradation was determined to be the primary failure mode. The collected run-to-failure data were analyzed and it was revealed that ON-state resistance increased as die-attach degraded under high thermal stresses. Results from finite element simulation analysis support the observations from the experimental data. Data-driven and model based prognostics algorithms were investigated where ON-state resistance was used as the primary precursor of failure feature. A Gaussian process regression algorithm was explored as an example for a data-driven technique and an extended Kalman filter and a particle filter were used as examples for model-based techniques. Both methods were able to provide valid results. Prognostic performance metrics were employed to evaluate and compare the algorithms.

Match and mismatch - comparing plant phenological metrics from ground-observations and from a prognostic model

NASA Astrophysics Data System (ADS)

Rutishauser, This; Stöckli, Reto; Jeanneret, François; Peñuelas, Josep

2010-05-01

Changes in the seasonality of life cycles of plants as recorded in phenological observations have been widely analysed at the species level with data available for many decades back in time. At the same time, seasonality changes in satellite-based observations and prognostic phenology models comprise information at the pixel-size or landscape scale. Change analysis of satellite-based records is restricted due to relatively short satellite records that further include gaps while model-based analyses are biased due to current model deficiencies., At 30 selected sites across Europe, we analysed three different sources of plant seasonality during the 1971-2000 period. Data consisted of (1) species-specific development stages of flowering and leave-out with different species observed at each site. (2) We used a synthetic phenological metric that integrates the common interannual phenological signal across all species at one site. (3) We estimated daily Leaf Area Index with a prognostic phenology model. The prior uncertainties of the model's empirical parameter space are constrained by assimilating the Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) and Leaf Area Index (LAI) from the MODerate Resolution Imaging Spectroradiometer (MODIS). We extracted the day of year when the 25%, 50% and 75% thresholds were passed each spring. The question arises how the three phenological signals compare and correlate across climate zones in Europe. Is there a match between single species observations, species-based ground-observed metrics and the landscape-scale prognostic model? Are there single key-species across Europe that best represent a landscape scale measure from the prognostic model? Can one source substitute another and serve as proxy-data? What can we learn from potential mismatches? Focusing on changes in spring this contribution presents first results of an ongoing comparison study from a number of European test sites that will be extended to the pan-European phenological database Cost725 and PEP725.

A new Leukemia Prognostic Scoring System for refractory/relapsed adult acute myelogeneous leukaemia patients: a GOELAMS study.

PubMed

Chevallier, P; Labopin, M; Turlure, P; Prebet, T; Pigneux, A; Hunault, M; Filanovsky, K; Cornillet-Lefebvre, P; Luquet, I; Lode, L; Richebourg, S; Blanchet, O; Gachard, N; Vey, N; Ifrah, N; Milpied, N; Harousseau, J-L; Bene, M-C; Mohty, M; Delaunay, J

2011-06-01

A simplified prognostic score is presented based on the multivariate analysis of 138 refractory/relapsed acute myeloid leukaemia (AML) patients (median age 55 years, range: 19-70) receiving a combination of intensive chemotherapy+Gemtuzumab as salvage regimen. Overall, 2-year event-free survival (EFS) and overall survival (OS) were 29±4% and 36±4%, respectively. Disease status (relapse <12 months, including refractory patients), FLT3-ITD-positive status and high-risk cytogenetics were the three strongest independent adverse prognostic factors for OS and EFS in this series. We then defined three subgroups with striking different outcomes at 2 years: no adverse factor (favourable, N=36): OS 58%, EFS 45%; one adverse factor (intermediate, N=54): OS 37%, EFS 31%; two or three adverse factors (poor, N=43): OS 12%, EFS 12% (P<10(-4), P=0.001). This new simplified Leukemia Prognostic Scoring System was then validated on an independent cohort of 111 refractory/relapsed AML patients. This new simplified prognostic score, using three clinical and biological parameters routinely applied, allow to discriminate around two third of the patients who should benefit from a salvage intensive regimen in the setting of refractory/relapsed AML patients. The other one third of the patients should receive investigational therapy.

A consensus prognostic gene expression classifier for ER positive breast cancer

PubMed Central

Teschendorff, Andrew E; Naderi, Ali; Barbosa-Morais, Nuno L; Pinder, Sarah E; Ellis, Ian O; Aparicio, Sam; Brenton, James D; Caldas, Carlos

2006-01-01

Background A consensus prognostic gene expression classifier is still elusive in heterogeneous diseases such as breast cancer. Results Here we perform a combined analysis of three major breast cancer microarray data sets to hone in on a universally valid prognostic molecular classifier in estrogen receptor (ER) positive tumors. Using a recently developed robust measure of prognostic separation, we further validate the prognostic classifier in three external independent cohorts, confirming the validity of our molecular classifier in a total of 877 ER positive samples. Furthermore, we find that molecular classifiers may not outperform classical prognostic indices but that they can be used in hybrid molecular-pathological classification schemes to improve prognostic separation. Conclusion The prognostic molecular classifier presented here is the first to be valid in over 877 ER positive breast cancer samples and across three different microarray platforms. Larger multi-institutional studies will be needed to fully determine the added prognostic value of molecular classifiers when combined with standard prognostic factors. PMID:17076897

A Hybrid Stochastic-Neuro-Fuzzy Model-Based System for In-Flight Gas Turbine Engine Diagnostics

DTIC Science & Technology

2001-04-05

Margin (ADM) and (ii) Fault Detection Margin (FDM). Key Words: ANFIS, Engine Health Monitoring , Gas Path Analysis, and Stochastic Analysis Adaptive Network...The paper illustrates the application of a hybrid Stochastic- Fuzzy -Inference Model-Based System (StoFIS) to fault diagnostics and prognostics for both...operational history monitored on-line by the engine health management (EHM) system. To capture the complex functional relationships between different

Immunization-based scores as independent prognostic predictors in soft tissue sarcoma patients

PubMed Central

Jiang, Shan-Shan; Jiang, Long; Weng, De-Sheng; Li, Yuan-fang; Pan, Qiu-Zhong; Zhao, Jing-Jing; Tang, Yan; Zhou, Zhi-Wei; Xia, Jian-Chuan

2017-01-01

Background: The purpose of this study was to examine and compare the prognostic value of different immunization-based scoring systems in patients with soft tissue sarcoma (STS). Methods: We conducted a retrospective study evaluating a cohort of 165 patients diagnosed with STS between July 2007 and July 2014. The relative Glasgow prognostic score (GPS) of these patients was calculated using 3 different systems: the traditional GPS system (tGPS), the modified GPS system 1 (m1GPS), and the modified GPS system 2 (m2GPS). Then, we evaluated the relationships between each GPS system and clinicopathological characteristics. The mean follow-up for survivors in the cohort was 73.7 months as of March 2015. Results: The most favorable overall survival (OS) rate was associated with the score 0 groups, and the poorest progression-free survival (PFS) rate was associated with the score 2 groups, regardless of which system was used to calculate the score. Specifically, the m1GPS provided the greatest accuracy in predicting OS and PFS. Moreover, the same effect was observed in a separate analysis restricted to patients with metastases. Remarkably, in patients with a score of 2 as measured by all 3 systems, local treatment resulted in a poorer prognosis compared to patients with a score of 2 who did not receive local treatment. Conclusion: The GPS is a valuable prognostic marker and has the capability to predict the appropriate treatment strategy for STS patients with metastases. The modified GPS systems demonstrated superior prognostic and predictive value compared with the traditional GPS system. PMID:28367240

Real-world data on Len/Dex combination at second-line therapy of multiple myeloma: treatment at biochemical relapse is a significant prognostic factor for progression-free survival.

PubMed

Katroditou, Eirini; Kyrtsonis, Marie-Christine; Delimpasi, Sosana; Kyriakou, Despoina; Symeonidis, Argiris; Spanoudakis, Emmanouil; Vasilopoulos, Georgios; Anagnostopoulos, Achilles; Kioumi, Anna; Zikos, Panagiotis; Aktypi, Anthi; Briasoulis, Evangelos; Megalakaki, Aikaterini; Repousis, Panayiotis; Adamopoulos, Ioannis; Gogos, Dimitrios; Kotsopoulou, Maria; Pappa, Vassiliki; Papadaki, Eleni; Fotiou, Despoina; Nikolaou, Eftychia; Giannopoulou, Evlambia; Hatzimichael, Eleftheria; Giannakoulas, Nikolaos; Douka, Vassiliki; Kokoviadou, Kyriaki; Timotheatou, Despoina; Terpos, Evangelos

2018-05-13

We evaluated progression-free survival (PFS) rate of patients treated with lenalidomide/dexamethasone (Len/Dex), the efficacy of the combination, and the prognostic significance of treatment at biochemical vs. clinical relapse on PFS in 207 consecutive myeloma patients treated with Len/Dex in second line, according to routine clinical practice in Greece. First-line treatment included bortezomib-based (63.3%) or immunomodulatory drug-based (34.8%) therapies; 25% of patients underwent autologous stem cell transplantation. Overall response rate was 73.4% (17.8% complete response and 23.7% very good partial response); median time to best response was 6.7 months. Overall, median PFS and 12-month PFS rate was 19.2 months and 67.6%, respectively. 67.5% of patients had biochemical relapse and 32.5% had clinical relapse prior to initiation of Len/Dex. Median PFS was 24 months for patients treated at biochemical relapse vs. 13.2 months for those treated at clinical relapse (HR:0.63, p = 0.006) and the difference remained significant after adjustment for other prognostic factors. Type of relapse was the strongest prognostic factor for PFS in multivariate analysis. These real-world data confirm the efficacy of Len/Dex combination at first relapse; more importantly, it is demonstrated for the first time outside a clinical trial setting that starting therapy with Len/Dex at biochemical, rather than at clinical relapse, is a significant prognostic factor for PFS, inducing a 37% reduction of the probability of disease progression or death.

Spatial coding-based approach for partitioning big spatial data in Hadoop

NASA Astrophysics Data System (ADS)

Yao, Xiaochuang; Mokbel, Mohamed F.; Alarabi, Louai; Eldawy, Ahmed; Yang, Jianyu; Yun, Wenju; Li, Lin; Ye, Sijing; Zhu, Dehai

2017-09-01

Spatial data partitioning (SDP) plays a powerful role in distributed storage and parallel computing for spatial data. However, due to skew distribution of spatial data and varying volume of spatial vector objects, it leads to a significant challenge to ensure both optimal performance of spatial operation and data balance in the cluster. To tackle this problem, we proposed a spatial coding-based approach for partitioning big spatial data in Hadoop. This approach, firstly, compressed the whole big spatial data based on spatial coding matrix to create a sensing information set (SIS), including spatial code, size, count and other information. SIS was then employed to build spatial partitioning matrix, which was used to spilt all spatial objects into different partitions in the cluster finally. Based on our approach, the neighbouring spatial objects can be partitioned into the same block. At the same time, it also can minimize the data skew in Hadoop distributed file system (HDFS). The presented approach with a case study in this paper is compared against random sampling based partitioning, with three measurement standards, namely, the spatial index quality, data skew in HDFS, and range query performance. The experimental results show that our method based on spatial coding technique can improve the query performance of big spatial data, as well as the data balance in HDFS. We implemented and deployed this approach in Hadoop, and it is also able to support efficiently any other distributed big spatial data systems.

Long-term outcomes and prognostic factors for patients with esophageal cancer following radiotherapy

PubMed Central

Chen, Chuang-Zhen; Chen, Jian-Zhou; Li, De-Rui; Lin, Zhi-Xiong; Zhou, Ming-Zhen; Li, Dong-Sheng; Chen, Zhi-Jian

2013-01-01

AIM: To evaluate long-term outcomes and prognostic factors for esophageal squamous cell carcinoma (SCC) treated with three dimensional conformal radiotherapy (3D-CRT). METHODS: Between January 2005 and December 2006, 153 patients (120 males, 33 females) with pathologically confirmed esophageal SCC and treated with 3D-CRT in Cancer Hospital of Shantou University were included in this retrospective analysis. Median age was 60 years (range: 37-84 years). The proportion of tumor location was as follows: upper thorax (including the cervical region), 73 (48%); middle thorax, 73 (48%); lower thorax, 7 (5%), respectively. The median radiation dose was 64 Gy (range: 50-74 Gy). Fifty four cases (35%) received cisplatin-based concurrent chemotherapy. Univariate and multivariate analysis were performed to determine the association between the correlative factors and prognosis. RESULTS: The five-year overall survival rate was 26.3%, with a median follow-up of 49 mo (range: 3-66 mo) for patients who were still alive. On univariate analysis, lesion location, lesion length by barium esophagogram, computed tomography imaging characteristics including Y diameter (anterior-posterior, AP, extent of tumor), gross tumor volume of primary lesion (GTV-E), volume of positive lymph nodes (GTV-LN), and the total target volume (GTV-T = GTV-E + GTV-LN) were prognostic for overall survival. By multivariate analysis, only the Y diameter [hazard ratio (HR) 2.219, 95%CI 1.141-4.316, P = 0.019] and the GTV-T (HR 1.372, 95%CI 1.044-1.803, P = 0.023) were independent prognostic factors for survival. CONCLUSION: The overall survival of esophageal carcinoma patients undergoing 3D-CRT was promising. The best predictors for survival were GTV-T and Y diameter. PMID:23539205

Long-term outcomes and prognostic factors for patients with esophageal cancer following radiotherapy.

PubMed

Chen, Chuang-Zhen; Chen, Jian-Zhou; Li, De-Rui; Lin, Zhi-Xiong; Zhou, Ming-Zhen; Li, Dong-Sheng; Chen, Zhi-Jian

2013-03-14

To evaluate long-term outcomes and prognostic factors for esophageal squamous cell carcinoma (SCC) treated with three dimensional conformal radiotherapy (3D-CRT). Between January 2005 and December 2006, 153 patients (120 males, 33 females) with pathologically confirmed esophageal SCC and treated with 3D-CRT in Cancer Hospital of Shantou University were included in this retrospective analysis. Median age was 60 years (range: 37-84 years). The proportion of tumor location was as follows: upper thorax (including the cervical region), 73 (48%); middle thorax, 73 (48%); lower thorax, 7 (5%), respectively. The median radiation dose was 64 Gy (range: 50-74 Gy). Fifty four cases (35%) received cisplatin-based concurrent chemotherapy. Univariate and multivariate analysis were performed to determine the association between the correlative factors and prognosis. The five-year overall survival rate was 26.3%, with a median follow-up of 49 mo (range: 3-66 mo) for patients who were still alive. On univariate analysis, lesion location, lesion length by barium esophagogram, computed tomography imaging characteristics including Y diameter (anterior-posterior, AP, extent of tumor), gross tumor volume of primary lesion (GTV-E), volume of positive lymph nodes (GTV-LN), and the total target volume (GTV-T = GTV-E + GTV-LN) were prognostic for overall survival. By multivariate analysis, only the Y diameter [hazard ratio (HR) 2.219, 95%CI 1.141-4.316, P = 0.019] and the GTV-T (HR 1.372, 95%CI 1.044-1.803, P = 0.023) were independent prognostic factors for survival. The overall survival of esophageal carcinoma patients undergoing 3D-CRT was promising. The best predictors for survival were GTV-T and Y diameter.

Introducing a novel highly prognostic grading scheme based on tumour budding and cell nest size for squamous cell carcinoma of the uterine cervix.

PubMed

Jesinghaus, Moritz; Strehl, Johanna; Boxberg, Melanie; Brühl, Frido; Wenzel, Adrian; Konukiewitz, Björn; Schlitter, Anna M; Steiger, Katja; Warth, Arne; Schnelzer, Andreas; Kiechle, Marion; Beckmann, Matthias W; Noske, Aurelia; Hartmann, Arndt; Mehlhorn, Grit; Koch, Martin C; Weichert, Wilko

2018-04-01

A novel histopathological grading system based on tumour budding and cell nest size has recently been shown to outperform conventional (WHO-based) grading algorithms in several tumour entities such as lung, oral, and oesophageal squamous cell carcinoma (SCC) in terms of prognostic patient stratification. Here, we tested the prognostic value of this innovative grading approach in two completely independent cohorts of SCC of the uterine cervix. To improve morphology-based grading, we investigated tumour budding activity and cell nest size as well as several other histomorphological factors (e.g., keratinization, nuclear size, mitotic activity) in a test cohort (n = 125) and an independent validation cohort (n = 122) of cervical SCC. All parameters were correlated with clinicopathological factors and patient outcome. Small cell nest size and high tumour budding activity were strongly associated with a dismal patient prognosis (p < 0.001 for overall survival [OS], disease-specific survival, and disease-free survival; test cohort) in both cohorts of cervical SCC. A novel grading algorithm combining these two parameters proved to be a highly effective, stage-independent prognosticator in both cohorts (OS: p < 0.001, test cohort; p = 0.001, validation cohort). In the test cohort, multivariate statistical analysis of the novel grade revealed that the hazard ratio (HR) for OS was 2.3 for G2 and 5.1 for G3 tumours compared to G1 neoplasms (p = 0.010). In the validation cohort, HR for OS was 3.0 for G2 and 7.2 for G3 tumours (p = 0.012). In conclusion, our novel grading algorithm incorporating cell nest size and tumour budding allows strongly prognostic histopathological grading of cervical SCC superior to WHO-based grading. Therefore, our data can be regarded as a cross-organ validation of previous results demonstrated for oesophageal, lung, and oral SCC. We suggest this grading algorithm as an additional morphology-based parameter for the routine diagnostic assessment of this tumour entity. © 2018 The Authors The Journal of Pathology: Clinical Research published by The Pathological Society of Great Britain and Ireland and John Wiley & Sons Ltd.

Value of coronary computed tomography as a prognostic tool.

PubMed

Contractor, Tahmeed; Parekh, Maansi; Ahmed, Shameer; Martinez, Matthew W

2012-08-01

Coronary computed tomography angiography (CCTA) has become an important part of our armamentarium for noninvasive diagnosis of coronary artery disease (CAD). Emerging technologies have produced lower radiation dose, improved spatial and temporal resolution, as well as information about coronary physiology. Although the prognostic role of coronary artery calcium scoring is known, similar evidence for CCTA has only recently emerged. Initial, small studies in various patient populations have indicated that CCTA-identified CAD may have a prognostic value. These findings were confirmed in a recent analysis of the international, prospective Coronary CT Angiography Evaluation For Clinical Outcomes: An International Multicenter (CONFIRM) registry. An incremental increase in mortality was found with a worse severity of CAD on a per-patient, per-vessel, and per-segment basis. In addition, age-, sex-, and ethnicity-based differences in mortality were also found. Whether changing our management algorithms based on these findings will affect outcomes is unclear. Large prospective studies utilizing targeted management strategies for obstructive and nonobstructive CAD are required to incorporate these recent findings into our daily practice. © 2012 Wiley Periodicals, Inc.

Gene expression-based molecular diagnostic system for malignant gliomas is superior to histological diagnosis.

PubMed

Shirahata, Mitsuaki; Iwao-Koizumi, Kyoko; Saito, Sakae; Ueno, Noriko; Oda, Masashi; Hashimoto, Nobuo; Takahashi, Jun A; Kato, Kikuya

2007-12-15

Current morphology-based glioma classification methods do not adequately reflect the complex biology of gliomas, thus limiting their prognostic ability. In this study, we focused on anaplastic oligodendroglioma and glioblastoma, which typically follow distinct clinical courses. Our goal was to construct a clinically useful molecular diagnostic system based on gene expression profiling. The expression of 3,456 genes in 32 patients, 12 and 20 of whom had prognostically distinct anaplastic oligodendroglioma and glioblastoma, respectively, was measured by PCR array. Next to unsupervised methods, we did supervised analysis using a weighted voting algorithm to construct a diagnostic system discriminating anaplastic oligodendroglioma from glioblastoma. The diagnostic accuracy of this system was evaluated by leave-one-out cross-validation. The clinical utility was tested on a microarray-based data set of 50 malignant gliomas from a previous study. Unsupervised analysis showed divergent global gene expression patterns between the two tumor classes. A supervised binary classification model showed 100% (95% confidence interval, 89.4-100%) diagnostic accuracy by leave-one-out cross-validation using 168 diagnostic genes. Applied to a gene expression data set from a previous study, our model correlated better with outcome than histologic diagnosis, and also displayed 96.6% (28 of 29) consistency with the molecular classification scheme used for these histologically controversial gliomas in the original article. Furthermore, we observed that histologically diagnosed glioblastoma samples that shared anaplastic oligodendroglioma molecular characteristics tended to be associated with longer survival. Our molecular diagnostic system showed reproducible clinical utility and prognostic ability superior to traditional histopathologic diagnosis for malignant glioma.

Intratumoral stromal morphometry predicts disease recurrence but not response to 5-fluorouracil-results from the QUASAR trial of colorectal cancer.

PubMed

Hutchins, Gordon G A; Treanor, Darren; Wright, Alexander; Handley, Kelly; Magill, Laura; Tinkler-Hundal, Emma; Southward, Katie; Seymour, Matthew; Kerr, David; Gray, Richard; Quirke, Philip

2018-02-01

The biological importance of tumour-associated stroma is becoming increasingly apparent, but its clinical utility remains ill-defined. For stage II/Dukes B colorectal cancer (CRC), clinical biomarkers are urgently required to direct therapeutic options. We report here prognostic/predictive analyses, and molecular associations, of stromal morphometric quantification in the Quick and Simple and Reliable (QUASAR) trial of CRC. Relative proportions of tumour epithelium (PoT) or stroma (PoS) were morphometrically quantified on digitised haematoxylin and eosin (H&E) sections derived from 1800 patients enrolled in QUASAR, which randomised 3239 (91% stage II) CRC patients between adjuvant fluorouracil/folinic acid (FUFA) chemotherapy and observation. The prognostic and predictive values of PoT/PoS measurements were determined by the use of stratified log-rank analyses. A high proportion of tumour stroma (≥50%) was associated with an increased recurrence risk: 31.3% (143/457) recurrence for ≥50% versus 21.9% (294/1343) for <50% [rate ratio (RR) 1.62; 95% confidence interval (CI) 1.30-2.02; P < 0.0001]. Of patients with stromal proportions of ≥65%, 40% (46/115) had recurrent disease within 10 years. The adverse prognostic effect of a high stromal proportion was independent of established prognostic variables, and was maintained in stage II/Dukes B patients (RR 1.62; 95% CI 1.26-2.08; P = 0.0002). KRAS mutation in the presence of a high stromal proportion augmented recurrence risk (RR 2.93; 95% CI 1.87-4.59; P = 0.0005). Stromal morphometry did not predict response to FUFA chemotherapy. Simple digital morphometry applied to a single representative H&E section identifies CRC patients with a >50% higher risk of disease recurrence. This technique can reliably partition patients into subpopulations with different risks of tumour recurrence in a simple and cost-effective manner. Further prospective validation is warranted. © 2017 John Wiley & Sons Ltd.

Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

PubMed

Zabor, Emily C; Coit, Daniel; Gershenwald, Jeffrey E; McMasters, Kelly M; Michaelson, James S; Stromberg, Arnold J; Panageas, Katherine S

2018-02-22

Prognostic models are increasingly being made available online, where they can be publicly accessed by both patients and clinicians. These online tools are an important resource for patients to better understand their prognosis and for clinicians to make informed decisions about treatment and follow-up. The goal of this analysis was to highlight the possible variability in multiple online prognostic tools in a single disease. To demonstrate the variability in survival predictions across online prognostic tools, we applied a single validation dataset to three online melanoma prognostic tools. Data on melanoma patients treated at Memorial Sloan Kettering Cancer Center between 2000 and 2014 were retrospectively collected. Calibration was assessed using calibration plots and discrimination was assessed using the C-index. In this demonstration project, we found important differences across the three models that led to variability in individual patients' predicted survival across the tools, especially in the lower range of predictions. In a validation test using a single-institution data set, calibration and discrimination varied across the three models. This study underscores the potential variability both within and across online tools, and highlights the importance of using methodological rigor when developing a prognostic model that will be made publicly available online. The results also reinforce that careful development and thoughtful interpretation, including understanding a given tool's limitations, are required in order for online prognostic tools that provide survival predictions to be a useful resource for both patients and clinicians.

Hepatoprotective action of various partitions of methanol extract of Bauhinia purpurea leaves against paracetamol-induced liver toxicity: involvement of the antioxidant mechanisms.

PubMed

Zakaria, Zainul Amiruddin; Yahya, Farhana; Mamat, Siti Syariah; Mahmood, Nur Diyana; Mohtarrudin, Nurhafizah; Taher, Muhammad; Hamid, Siti Selina Abdul; Teh, Lay Kek; Salleh, Mohd Zaki

2016-06-11

Methanol extract of Bauhinia purpurea L. (family Fabaceae) (MEBP) possesses high antioxidant and anti-inflammatory activities and recently reported to exert hepatoprotection against paracetamol (PCM)-induced liver injury in rats. In an attempt to identify the hepatoprotective bioactive compounds in MEBP, the extract was prepared in different partitions and subjected to the PCM-induced liver injury model in rats. Dried MEBP was partitioned successively to obtain petroleum ether (PEBP), ethylacetate (EABP) and aqueous (AQBP) partitions, respectively. All partitions were subjected to in vitro antioxidant (i.e. total phenolic content (TPC), 2,2-diphenyl-1-picrylhydrazyl (DPPH)- and superoxide-radicals scavenging assay, and oxygen radical absorbance capacity (ORAC) assay) and anti-inflammatory (i.e. lipooxygenase (LOX) and xanthine oxidase (XO) assay) analysis. The partitions, prepared in the dose range of 50, 250 and 500 mg/kg, together with a vehicle (10 % DMSO) and standard drug (200 mg/kg silymarin) were administered orally for 7 consecutive days prior to subjection to the 3 mg/kg PCM-induced liver injury model in rats. Following the hepatic injury induction, blood samples and liver were collected for the respective biochemical parameter and histopathological studies. Body weight changes and liver weight were also recorded. The partitions were also subjected to the phytochemical screening and HPLC analysis. Of all partitions, EABP possessed high TPC value and demonstrated remarkable antioxidant activity when assessed using the DPPH- and superoxide-radical scavenging assay, as well as ORAC assay, which was followed by AQBP and PEBP. All partitions also showed low anti-inflammatory activity via the LOX and XO pathways. In the hepatoprotective study, the effectiveness of the partitions is in the order of EABP>AQBP>PEBP, which is supported by the microscopic analysis and histopathological scoring. In the biochemical analysis, EABP also exerted the most effective effect by reducing the serum level of alanine transaminase (ALT) and aspartate transaminase (AST) at all doses tested in comparison to the other partitions. Phytochemical screening and HPLC analysis suggested the presence of: flavonoids, condensed tannins and triterpenes in EABP; flavonoids, condensed tannins and saponins in PEBP and; only saponins in AQBP. EABP demonstrates the most effective hepatoprotection against PCM-induced liver injury in rats. This observation could be attributed to its remarkable antioxidant activity and the presence of flavonoids that might probably act synergistically with other biocompounds to cause the hepatoprotection.

TU-CD-BRB-08: Radiomic Analysis of FDG-PET Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated with SBRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cui, Y; Shirato, H; Song, J

2015-06-15

Purpose: This study aims to identify novel prognostic imaging biomarkers in locally advanced pancreatic cancer (LAPC) using quantitative, high-throughput image analysis. Methods: 86 patients with LAPC receiving chemotherapy followed by SBRT were retrospectively studied. All patients had a baseline FDG-PET scan prior to SBRT. For each patient, we extracted 435 PET imaging features of five types: statistical, morphological, textural, histogram, and wavelet. These features went through redundancy checks, robustness analysis, as well as a prescreening process based on their concordance indices with respect to the relevant outcomes. We then performed principle component analysis on the remaining features (number ranged frommore » 10 to 16), and fitted a Cox proportional hazard regression model using the first 3 principle components. Kaplan-Meier analysis was used to assess the ability to distinguish high versus low-risk patients separated by median predicted survival. To avoid overfitting, all evaluations were based on leave-one-out cross validation (LOOCV), in which each holdout patient was assigned to a risk group according to the model obtained from a separate training set. Results: For predicting overall survival (OS), the most dominant imaging features were wavelet coefficients. There was a statistically significant difference in OS between patients with predicted high and low-risk based on LOOCV (hazard ratio: 2.26, p<0.001). Similar imaging features were also strongly associated with local progression-free survival (LPFS) (hazard ratio: 1.53, p=0.026) on LOOCV. In comparison, neither SUVmax nor TLG was associated with LPFS (p=0.103, p=0.433) (Table 1). Results for progression-free survival and distant progression-free survival showed similar trends. Conclusion: Radiomic analysis identified novel imaging features that showed improved prognostic value over conventional methods. These features characterize the degree of intra-tumor heterogeneity reflected on FDG-PET images, and their biological underpinnings warrant further investigation. If validated in large, prospective cohorts, this method could be used to stratify patients based on individualized risk.« less

Realizing the Translational Potential of Telomere Length Variation as a Tissue-Based Prognostic Marker for Prostate Cancer

DTIC Science & Technology

2014-10-01

Telomere Length Variation as a Tissue- Based Prognostic Marker for Prostate Cancer PRINCIPAL INVESTIGATOR: Elizabeth A. Platz CONTRACTING...Translational Potential of Telomere Length Variation as a Tissue- Based Prognostic Marker for Prostate Cancer 5b. GRANT NUMBER W81XWH-12-1-0545 5c...combination of telomere length variability in prostate cancer cells and short telomere length in cancer-associated stromal cells is an independent

Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example

PubMed Central

Winzer, Klaus-Jürgen; Buchholz, Anika; Schumacher, Martin; Sauerbrei, Willi

2016-01-01

Background Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches. Methods and Findings Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived. Conclusions The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases. PMID:26938061

Prognostic Impact of Primary Tumor Location on Clinical Outcomes of Metastatic Colorectal Cancer Treated With Cetuximab Plus Oxaliplatin-Based Chemotherapy: A Subgroup Analysis of the JACCRO CC-05/06 Trials.

PubMed

Sunakawa, Yu; Ichikawa, Wataru; Tsuji, Akihito; Denda, Tadamichi; Segawa, Yoshihiko; Negoro, Yuji; Shimada, Ken; Kochi, Mitsugu; Nakamura, Masato; Kotaka, Masahito; Tanioka, Hiroaki; Takagane, Akinori; Tani, Satoshi; Yamaguchi, Tatsuro; Watanabe, Takanori; Takeuchi, Masahiro; Fujii, Masashi; Nakajima, Toshifusa

2017-09-01

Primary tumor location is a critical prognostic factor in metastatic colorectal cancer (mCRC); however, it remains unclear whether tumor location is a predictor of the response to cetuximab treatment. It is also uncertain if BRAF mutation contributes to the impact of tumor location on survival. We assessed the prognostic impact of tumor location on clinical outcomes in mCRC patients treated with first-line cetuximab chemotherapy. The associations of tumor location with overall survival and progression-free survival were evaluated in mCRC patients with KRAS exon 2 wild-type tumors who were enrolled onto 2 clinical trials: JACCRO CC-05 of cetuximab plus FOLFOX (n = 57, UMIN000004197) and CC-06 of cetuximab plus SOX (n = 61, UMIN000007022). Tumors proximal or from splenic flexure to rectum were defined as right-sided or left-sided, respectively. In addition, exploratory RAS and BRAF mutation analyses were performed. A total of 110 patients were assessable for tumor location; 90 had left-sided tumors. Left-sided tumors were significantly associated with longer overall survival (36.2 vs. 12.6 months, hazard ratio = 0.28, P < .0001) and progression-free survival (11.1 vs. 5.6 months, hazard ratio = 0.47, P = .0041) than right-sided tumors; similar results were obtained in multivariate analysis. A subanalysis showed that the association was evident in the FOLFOX group and that tumor location was an independent prognostic factor irrespective of BRAF status in RAS wild-type patients. Primary tumor location might be a predictor of survival independent of BRAF status in mCRC patients who receive first-line cetuximab combined with oxaliplatin-based chemotherapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Genomic Analysis of Complex Microbial Communities in Wounds

DTIC Science & Technology

2012-01-01

thoroughly in the ecology literature. Permutation Multivariate Analysis of Variance ( PerMANOVA ). We used PerMANOVA to test the null-hypothesis of no...difference between the bacterial communities found within a single wound compared to those from different patients (α = 0.05). PerMANOVA is a...permutation-based version of the multivariate analysis of variance (MANOVA). PerMANOVA uses the distances between samples to partition variance and

Survival Outcomes of Whole-Pelvic Versus Prostate-Only Radiation Therapy for High-Risk Prostate Cancer Patients With Use of the National Cancer Data Base

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amini, Arya; Jones, Bernard L.; Yeh, Norman

Purpose/Objectives: The addition of whole pelvic (WP) compared with prostate-only (PO) radiation therapy (RT) for clinically node-negative prostate cancer remains controversial. The purpose of our study was to evaluate the survival benefit of adding WPRT versus PO-RT for high-risk, node-negative prostate cancer, using the National Cancer Data Base (NCDB). Methods and Materials: Patients with high-risk prostate cancer treated from 2004 to 2006, with available data for RT volume, coded as prostate and pelvis (WPRT) or prostate alone (PO-RT) were included. Multivariate analysis (MVA) and propensity-score matched analysis (PSM) were performed. Recursive partitioning analysis (RPA) based on overall survival (OS) usingmore » Gleason score (GS), T stage, and pretreatment prostate-specific antigen (PSA) was also conducted. Results: A total of 14,817 patients were included: 7606 (51.3%) received WPRT, and 7211 (48.7%) received PO-RT. The median follow-up time was 81 months (range, 2-122 months). Under MVA, the addition of WPRT for high-risk patients had no OS benefit compared with PO-RT (HR 1.05; P=.100). On subset analysis, patients receiving dose-escalated RT also did not benefit from WPRT (HR 1.01; P=.908). PSM confirmed no survival benefit with the addition of WPRT for high-risk patients (HR 1.05; P=.141). In addition, RPA was unable to demonstrate a survival benefit of WPRT for any subset. Other prognostic factors for inferior OS under MVA included older age (HR 1.25; P<.001), increasing comorbidity scores (HR 1.46; P<.001), higher T stage (HR 1.17; P<.001), PSA (HR 1.81; P<.001), and GS (HR 1.29; P<.001), and decreasing median county household income (HR 1.15; P=.011). Factors improving OS included the addition of androgen deprivation therapy (HR 0.92; P=.033), combination external beam RT plus brachytherapy boost (HR 0.71; P<.001), and treatment at an academic/research institution (HR 0.84; P=.002). Conclusion: In the largest reported analysis of WPRT for patients with high-risk prostate cancer treated in the dose-escalated era, the addition of WPRT demonstrated no survival advantage compared with PO-RT.« less

NCCN-IPI score-independent prognostic potential of pretreatment uric acid levels for clinical outcome of diffuse large B-cell lymphoma patients

PubMed Central

Prochazka, Katharina T; Melchardt, Thomas; Posch, Florian; Schlick, Konstantin; Deutsch, Alexander; Beham-Schmid, Christine; Weiss, Lukas; Gary, Thomas; Neureiter, Daniel; Klieser, Eckhard; Greil, Richard; Neumeister, Peter; Egle, Alexander; Pichler, Martin

2016-01-01

Background: Blood-based parameters are gaining increasing interest as potential prognostic biomarkers in patients with diffuse large B-cell lymphoma (DLBCL). The aim of this study was to comprehensively evaluate the prognostic significance of pretreatment plasma uric acid levels in patients with newly diagnosed DLBCL. Methods: The clinical course of 539 DLBCL patients, diagnosed and treated between 2004 and 2013 at two Austrian high-volume centres with rituximab-based immunochemotherapy was evaluated retrospectively. The prognostic influence of uric acid on overall survival (OS) and progression-free survival (PFS) were studied including multi-state modelling, and analysis of conditional survival. Results: Five-year OS and PFS were 50.4% (95% CI: 39.2–60.6) and 44.0% (33.4–54.0) in patients with uric acid levels above the 75th percentile of the uric acid distribution (Q3, cut-off: 6.8 mg dl−1), and 66.2% (60.4–71.5) and 59.6% (53.7–65.0%) in patients with lower levels (log-rank P=0.002 and P=0.0045, respectively). In univariable time-to-event analysis, elevated uric acid levels were associated with a worse PFS (hazard ratio (HR) per 1 log increase in uric acid 1.47, 95% CI: 1.10–1.97, P=0.009) and a worse OS (HR=1.60, 95% CI: 1.16–2.19, P=0.004). These associations prevailed upon multivariable adjustment for the NCCN-IPI score. Uric acid levels significantly improved the predictive performance of the R-IPI and NCCN-IPI scores, and in multi-state analysis, it emerged as a highly significant predictor of an increased risk of death without developing recurrence (transition-HR=4.47, 95% CI: 2.17–9.23, P<0.0001). Conclusions: We demonstrate that elevated uric acid levels predict poor long-term outcomes in DLBCL patients beyond the NCCN-IPI risk index. PMID:27764838

ALEXI analysis of water consumption in the Nile Basin

USDA-ARS?s Scientific Manuscript database

Remote sensing can be used to generate diagnostic estimates of evapotranspiration (ET) that provide information regarding consumptive water use across landscapes. These satellite-based assessments can be a valuable complement to prognostic simulations of basin-scale water budgets, providing an inde...

Diffusion-weighted MRI derived apparent diffusion coefficient identifies prognostically distinct subgroups of pediatric diffuse intrinsic pontine glioma.

PubMed

Lober, Robert M; Cho, Yoon-Jae; Tang, Yujie; Barnes, Patrick D; Edwards, Michael S; Vogel, Hannes; Fisher, Paul G; Monje, Michelle; Yeom, Kristen W

2014-03-01

While pediatric diffuse intrinsic pontine gliomas (DIPG) remain fatal, recent data have shown subgroups with distinct molecular biology and clinical behavior. We hypothesized that diffusion-weighted MRI can be used as a prognostic marker to stratify DIPG subsets with distinct clinical behavior. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted MRI were computed in 20 consecutive children with treatment-naïve DIPG tumors. The median ADC for the cohort was used to stratify the tumors into low and high ADC groups. Survival, gender, therapy, and potential steroid effects were compared between the ADC groups. Median age at diagnosis was 6.6 (range 2.3-13.2) years, with median follow-up seven (range 1-36) months. There were 14 boys and six girls. Seventeen patients received radiotherapy, five received chemotherapy, and six underwent cerebrospinal fluid diversion. The median ADC of 1,295 × 10(-6) mm(2)/s for the cohort partitioned tumors into low or high diffusion groups, which had distinct median survivals of 3 and 13 months, respectively (log-rank p < 0.001). Low ADC tumors were found only in boys, whereas high ADC tumors were found in both boys and girls. Available tissue specimens in three low ADC tumors demonstrated high-grade histology, whereas one high ADC tumor demonstrated low-grade histology with a histone H3.1 K27M mutation and high-grade metastatic lesion at autopsy. ADC derived from diffusion-weighted MRI may identify prognostically distinct subgroups of pediatric DIPG.

PREFERENTIAL PARTITIONING OF A PAH AND PCB TO A MARINE SEDIMENT AMENDED WITH SEVERAL SOURCES OF SOOT CARBON

EPA Science Inventory

Over the last decade, several studies reported that the partitioning of PAHs to sediments, in some cases, did not follow predictions based on equilibrium partitioning theory. One explanation for these differences is the presence of a second sedimentary phase with partitioning cha...

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-07-17

The explosion of biological data has largely influenced the focus of today’s biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-06-01

The explosion of biological data has largely influenced the focus of today's biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Topological structures in the equities market network

PubMed Central

Leibon, Gregory; Pauls, Scott; Rockmore, Daniel; Savell, Robert

2008-01-01

We present a new method for articulating scale-dependent topological descriptions of the network structure inherent in many complex systems. The technique is based on “partition decoupled null models,” a new class of null models that incorporate the interaction of clustered partitions into a random model and generalize the Gaussian ensemble. As an application, we analyze a correlation matrix derived from 4 years of close prices of equities in the New York Stock Exchange (NYSE) and National Association of Securities Dealers Automated Quotation (NASDAQ). In this example, we expose (i) a natural structure composed of 2 interacting partitions of the market that both agrees with and generalizes standard notions of scale (e.g., sector and industry) and (ii) structure in the first partition that is a topological manifestation of a well-known pattern of capital flow called “sector rotation.” Our approach gives rise to a natural form of multiresolution analysis of the underlying time series that naturally decomposes the basic data in terms of the effects of the different scales at which it clusters. We support our conclusions and show the robustness of the technique with a successful analysis on a simulated network with an embedded topological structure. The equities market is a prototypical complex system, and we expect that our approach will be of use in understanding a broad class of complex systems in which correlation structures are resident.

Analysis of Different Cost Functions in the Geosect Airspace Partitioning Tool

NASA Technical Reports Server (NTRS)

Wong, Gregory L.

2010-01-01

A new cost function representing air traffic controller workload is implemented in the Geosect airspace partitioning tool. Geosect currently uses a combination of aircraft count and dwell time to select optimal airspace partitions that balance controller workload. This is referred to as the aircraft count/dwell time hybrid cost function. The new cost function is based on Simplified Dynamic Density, a measure of different aspects of air traffic controller workload. Three sectorizations are compared. These are the current sectorization, Geosect's sectorization based on the aircraft count/dwell time hybrid cost function, and Geosect s sectorization based on the Simplified Dynamic Density cost function. Each sectorization is evaluated for maximum and average workload along with workload balance using the Simplified Dynamic Density as the workload measure. In addition, the Airspace Concept Evaluation System, a nationwide air traffic simulator, is used to determine the capacity and delay incurred by each sectorization. The sectorization resulting from the Simplified Dynamic Density cost function had a lower maximum workload measure than the other sectorizations, and the sectorization based on the combination of aircraft count and dwell time did a better job of balancing workload and balancing capacity. However, the current sectorization had the lowest average workload, highest sector capacity, and the least system delay.

Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

NASA Astrophysics Data System (ADS)

Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

2017-07-01

Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

Prediction of the First Variceal Haemorrhage

PubMed Central

1997-01-01

We followed 87 cirrhotic patients with esophageal varices and without previous hemorrhage for a mean period of 24 mo to prospectively evaluate the occurance of variceal bleeding within (early) or after (late) 6 mo from entry and the contribution of portal Doppler ultrasound parameters to the prediction of early and late hemorrhage. Clinical, biochemical, endoscopic and portal Doppler ultrasound parameters were recorded at entry. Variceal bleeding occurred in 22 patients (25.3%). Nine (40.9%) bled within the first 6 mo. Cox regression analysis identified variceal size, cherry-red spots, serum bilirubin and congestion index of the portal vein (the ratio of portal vein [cross-sectional area] and portal blood flow velocity) as the only independent predictors of first variceal hemorrhage. Discriminant analysis was used to find the prognostic index cut off points to identify patients who bled within 6 mo (prognostic group 1) or after 6 mo (prognostic group 2) or remained free of bleeding (prognostic group 3). The cumulative proportion of patients correctly classified was 73% in prognostic group 1, 47% in prognostic group 2 and more than 80% in prognostic group 3. The addition of Doppler ultrasound flowmetry to clinical, biochemical and endoscopic parameter only improved the classification of patients with early bleeding. PMID:9184882

A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients

PubMed Central

Molloy, Timothy J.; Roepman, Paul; Naume, Bjørn; van't Veer, Laura J.

2012-01-01

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays. PMID:22384245

Stereotactic radiosurgery alone versus resection plus whole-brain radiotherapy for 1 or 2 brain metastases in recursive partitioning analysis class 1 and 2 patients.

PubMed

Rades, Dirk; Bohlen, Guenther; Pluemer, Andre; Veninga, Theo; Hanssens, Patrick; Dunst, Juergen; Schild, Steven E

2007-06-15

The objective of this study was to compare stereotactic radiosurgery (SRS) alone with resection plus whole-brain radiotherapy (WBRT) for the treatment of patients in recursive partitioning analysis (RPA) class 1 and 2 who had 1 or 2 brain metastases. Two hundred six patients in RPA class 1 and 2 who had 1 or 2 brain metastases were analyzed retrospectively. Patients in Group A (n = 94) received from 18 grays (Gy) to 25 Gy SRS, and patients in Group B (n = 112) underwent resection of their metastases and received 10 x 3 Gy/20 x 2 Gy WBRT. Eight other potential prognostic factors were evaluated regarding overall survival (OS), brain control (BC), and local control (LC) of treated metastases: age, sex, performance status, tumor type, number of brain metastases, extracranial metastases, RPA class, and interval from tumor diagnosis to treatment of brain metastases. A comparison of the 2 treatment groups did not reveal significantly different OS (P = .19), BC (P = .52), or LC (P = .25). In RPA subgroup analyses, outcome also did not differ significantly for either RPA class of patients (P values from .21 to .83). On multivariate analysis, improved OS was associated with age < or =60 years (relative risk [RR], 1.75; P = .002), better performance status (RR, 1.67; P = .015), no extracranial metastases (RR, 2.84; P < .001), interval from tumor diagnosis to treatment >12 months (RR, 1.70; P = .003), and RPA class 1 (RR, 1.51; P = .016). Improved BC was associated with a single metastasis (RR, 1.54; P = .034) and an interval from tumor diagnosis to treatment >12 months (RR, 1.58; P = .019), and improved LC was associated with an interval from tumor diagnosis to treatment >12 months (RR, 1.59; P = .047). SRS alone appeared to be as effective as resection plus WBRT in the treatment of 1 or 2 brain metastases for patients in RPA class 1 and 2. Patient outcomes were associated with age, Karnofsky performance status, number of brain metastases, extracranial metastases, RPA class, and interval from tumor diagnosis to treatment. Copyright 2007 American Cancer Society.

Proposal for a new risk stratification classification for meningioma based on patient age, WHO tumor grade, size, localization, and karyotype

PubMed Central

Domingues, Patrícia Henriques; Sousa, Pablo; Otero, Álvaro; Gonçalves, Jesus Maria; Ruiz, Laura; de Oliveira, Catarina; Lopes, Maria Celeste; Orfao, Alberto; Tabernero, Maria Dolores

2014-01-01

Background Tumor recurrence remains the major clinical complication of meningiomas, the majority of recurrences occurring among WHO grade I/benign tumors. In the present study, we propose a new scoring system for the prognostic stratification of meningioma patients based on analysis of a large series of meningiomas followed for a median of >5 years. Methods Tumor cytogenetics were systematically investigated by interphase fluorescence in situ hybridization in 302 meningioma samples, and the proposed classification was further validated in an independent series of cases (n = 132) analyzed by high-density (500K) single-nucleotide polymorphism (SNP) arrays. Results Overall, we found an adverse impact on patient relapse-free survival (RFS) for males, presence of brain edema, younger patients (<55 years), tumor size >50 mm, tumor localization at intraventricular and anterior cranial base areas, WHO grade II/III meningiomas, and complex karyotypes; the latter 5 variables showed an independent predictive value in multivariate analysis. Based on these parameters, a prognostic score was established for each individual case, and patients were stratified into 4 risk categories with significantly different (P < .001) outcomes. These included a good prognosis group, consisting of approximately 20% of cases, that showed a RFS of 100% ± 0% at 10 years and a very poor-prognosis group with a RFS rate of 0% ± 0% at 10 years. The prognostic impact of the scoring system proposed here was also retained when WHO grade I cases were considered separately (P < .001). Conclusions Based on this risk-stratification classification, different strategies may be adopted for follow-up, and eventually also for treatment, of meningioma patients at different risks for relapse. PMID:24536048

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Unavailability of thymidine kinase does not preclude the use of German comprehensive prognostic index: results of an external validation analysis in early chronic lymphocytic leukemia and comparison with MD Anderson Cancer Center model.

PubMed

Molica, Stefano; Giannarelli, Diana; Mirabelli, Rosanna; Levato, Luciano; Russo, Antonio; Linardi, Maria; Gentile, Massimo; Morabito, Fortunato

2016-01-01

A comprehensive prognostic index that includes clinical (i.e., age, sex, ECOG performance status), serum (i.e., ß2-microglobulin, thymidine kinase [TK]), and molecular (i.e., IGVH mutational status, del 17p, del 11q) markers developed by the German CLL Study Group (GCLLSG) was externally validated in a prospective, community-based cohort consisting of 338 patients with early chronic lymphocytic leukemia (CLL) using as endpoint the time to first treatment (TTFT). Because serum TK was not available, a slightly modified version of the model based on seven instead of eight prognostic variables was used. By German index, 62.9% of patients were scored as having low-risk CLL (score 0-2), whereas 37.1% had intermediate-risk CLL (score 3-5). This stratification translated into a significant difference in the TTFT [HR = 4.21; 95% C.I. (2.71-6.53); P < 0.0001]. Also the 2007 MD Anderson Cancer Center (MDACC) score, barely based on traditional clinical parameters, showed comparable reliability [HR = 2.73; 95% C.I. (1.79-4.17); P < 0.0001]. A comparative performance assessment between the two models revealed that prediction of the TTFT was more accurate with German score. The c-statistic of the MDACC model was 0.65 (range, 0.53-0.78) a level below that of the German index [0.71 (range, 0.60-0.82)] and below the accepted 0.7 threshold necessary to have value at the individual patient level. Results of this external comparative validation analysis strongly support the German score as the benchmark for comparison of any novel prognostic scheme aimed at evaluating the TTFT in patients with early CLL even when a modified version which does not include TK is utilized. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Partitioning medical image databases for content-based queries on a Grid.

PubMed

Montagnat, J; Breton, V; E Magnin, I

2005-01-01

In this paper we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned into subsets to be processed on different grid nodes. A theoretical model of the application complexity and estimates of the grid execution overhead are used to efficiently partition the database. We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time. Grids are promising for content-based image retrieval in medical databases.

Preoperative serum C-reactive protein levels and post-operative lymph node ratio are important predictors of survival after pancreaticoduodenectomy for pancreatic ductal adenocarcinoma.

PubMed

Sanjay, Pandanaboyana; de Figueiredo, Rodrigo S; Leaver, Heather; Ogston, Simon; Kulli, Christoph; Polignano, Francesco M; Tait, Iain S

2012-03-10

There is paucity of data on the prognostic value of pre-operative inflammatory response and post-operative lymph node ratio on patient survival after pancreatic-head resection for pancreatic ductal adenocarcinoma. To evaluate the role of the preoperative inflammatory response and postoperative pathology criteria to identify predictive and/or prognostic variables for pancreatic ductal adenocarcinoma. All patients who underwent pancreaticoduodenectomy for pancreatic ductal adenocarcinoma between 2002 and 2008 were reviewed retrospectively. The following impacts on patient survival were assessed: i) preoperative serum CRP levels, white cell count, neutrophil count, neutrophil/lymphocyte ratio, lymphocyte count, platelet/lymphocyte ratio; and ii) post-operative pathology criteria including lymph node status and lymph node ratio. Fifty-one patients underwent potentially curative resection for pancreatic ductal adenocarcinoma during the study period. An elevated preoperative CRP level (greater than 3 mg/L) was found to be a significant adverse prognostic factor (P=0.015) predicting a poor survival, whereas white cell count (P=0.278), neutrophil count (P=0.850), neutrophil/lymphocyte ratio (P=0.272), platelet/lymphocyte ratio (P=0.532) and lymphocyte count (P=0.721) were not significant prognosticators at univariate analysis. Presence of metastatic lymph nodes did not adversely affect survival (P=0.050), however a raised lymph node ratio predicted poor survival at univariate analysis (P<0.001). The preoperative serum CRP level retained significance at multivariate analysis (P=0.011), together with lymph node ratio (P<0.001) and tumour size (greater than 2 cm; P=0.008). A pre-operative elevated serum CRP level and raised post-operative lymph node ratio represent significant independent prognostic factors that predict poor prognosis in patients undergoing curative resection for pancreatic ductal adenocarcinoma. There is potential for future neo-adjuvant and adjuvant treatment strategies in pancreatic cancer to be tailored based on preoperative and postoperative factors that predict a poor survival.

Variable length adjacent partitioning for PTS based PAPR reduction of OFDM signal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibraheem, Zeyid T.; Rahman, Md. Mijanur; Yaakob, S. N.

2015-05-15

Peak-to-Average power ratio (PAPR) is a major drawback in OFDM communication. It leads the power amplifier into nonlinear region operation resulting into loss of data integrity. As such, there is a strong motivation to find techniques to reduce PAPR. Partial Transmit Sequence (PTS) is an attractive scheme for this purpose. Judicious partitioning the OFDM data frame into disjoint subsets is a pivotal component of any PTS scheme. Out of the existing partitioning techniques, adjacent partitioning is characterized by an attractive trade-off between cost and performance. With an aim of determining effects of length variability of adjacent partitions, we performed anmore » investigation into the performances of a variable length adjacent partitioning (VL-AP) and fixed length adjacent partitioning in comparison with other partitioning schemes such as pseudorandom partitioning. Simulation results with different modulation and partitioning scenarios showed that fixed length adjacent partition had better performance compared to variable length adjacent partitioning. As expected, simulation results showed a slightly better performance of pseudorandom partitioning technique compared to fixed and variable adjacent partitioning schemes. However, as the pseudorandom technique incurs high computational complexities, adjacent partitioning schemes were still seen as favorable candidates for PAPR reduction.« less

Gas-particle partitioning of semi-volatile organics on organic aerosols using a predictive activity coefficient model: analysis of the effects of parameter choices on model performance

NASA Astrophysics Data System (ADS)

Chandramouli, Bharadwaj; Jang, Myoseon; Kamens, Richard M.

The partitioning of a diverse set of semivolatile organic compounds (SOCs) on a variety of organic aerosols was studied using smog chamber experimental data. Existing data on the partitioning of SOCs on aerosols from wood combustion, diesel combustion, and the α-pinene-O 3 reaction was augmented by carrying out smog chamber partitioning experiments on aerosols from meat cooking, and catalyzed and uncatalyzed gasoline engine exhaust. Model compositions for aerosols from meat cooking and gasoline combustion emissions were used to calculate activity coefficients for the SOCs in the organic aerosols and the Pankow absorptive gas/particle partitioning model was used to calculate the partitioning coefficient Kp and quantitate the predictive improvements of using the activity coefficient. The slope of the log K p vs. log p L0 correlation for partitioning on aerosols from meat cooking improved from -0.81 to -0.94 after incorporation of activity coefficients iγ om. A stepwise regression analysis of the partitioning model revealed that for the data set used in this study, partitioning predictions on α-pinene-O 3 secondary aerosol and wood combustion aerosol showed statistically significant improvement after incorporation of iγ om, which can be attributed to their overall polarity. The partitioning model was sensitive to changes in aerosol composition when updated compositions for α-pinene-O 3 aerosol and wood combustion aerosol were used. The octanol-air partitioning coefficient's ( KOA) effectiveness as a partitioning correlator over a variety of aerosol types was evaluated. The slope of the log K p- log K OA correlation was not constant over the aerosol types and SOCs used in the study and the use of KOA for partitioning correlations can potentially lead to significant deviations, especially for polar aerosols.

Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma.

PubMed

Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

2015-02-28

To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P<0.001) and objective tumor response (P=0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P=0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P<0.001). Multivariate analysis identified tumor stage (P<0.001) and tumor type (P=0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P<0.001), surgical treatment (P=0.009), and multi-modal treatment (P=0.002) were identified as independent post-treatment prognostic factors. TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC.

Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma

PubMed Central

Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

2015-01-01

AIM: To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). METHODS: A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. RESULTS: In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P < 0.001) and objective tumor response (P = 0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P = 0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P < 0.001). Multivariate analysis identified tumor stage (P < 0.001) and tumor type (P = 0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P < 0.001), surgical treatment (P = 0.009), and multi-modal treatment (P = 0.002) were identified as independent post-treatment prognostic factors. CONCLUSION: TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC. PMID:25741147

Age as an independent prognostic factor in patients with glioblastoma: a Radiation Therapy Oncology Group and American College of Surgeons National Cancer Data Base comparison.

PubMed

Siker, Malika L; Wang, Meihua; Porter, Kimberly; Nelson, Diana F; Curran, Walter J; Michalski, Jeff M; Souhami, Luis; Chakravarti, Arnab; Yung, W K Alfred; Delrowe, John; Coughlin, Christopher T; Mehta, Minesh P

2011-08-01

Glioblastoma (GBM) is rare in early adulthood and little information is available on this subgroup. We investigated whether young age (18-30 years) had an independent effect on survival. We retrospectively reviewed patients from two large databases: Radiation Therapy Oncology Group (RTOG) and American College of Surgeons National Cancer Data Base (NCDB). In the RTOG evaluation, we analyzed all eligible GBM cases from 17 RTOG studies from 1974 to 2002. All patients with GBM during 1985-1998 in the NCDB were examined for comparison. Patients were divided into three cohorts: ages 18-30, 31-49, and ≥50. Overall survival, as a function of age (discreet and continuous), was assessed. The RTOG review included 3,136 patients: 112 (3.6%) were 18-30, 780 (24.9%) were 31-49, and 2,244 (71.6%) were ≥50. The median survival times of the three groups were 21.0, 13.5, and 9.1 months (P < 0.0001). Significant improvement in survival for younger patients was demonstrated with adjustment for recursive partitioning analysis (RPA) class. Of the 37,260 patients analyzed in the NCDB, 796 (2.1%) were 18-30, 5,711 (15.3%) were 31-49, and 30,753 (82.5%) were ≥50. The median survival times of the three groups were 18.0, 12.8, and 6.3 months (P < 0.0001). Data were not available for RPA class from this series. GBM is rare in young adulthood, comprising 2.1-3.6% of our patients. They have superior survival, even when adjusted for RPA class. More investigations on the unique biologic and clinical characteristics of tumors in this population are needed.

Prognostic and diagnostic impact of fibrinogen, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio on thymic epithelial tumors outcome

PubMed Central

Janik, Stefan; Raunegger, Thomas; Hacker, Philipp; Ghanim, Bahil; Einwallner, Elisa; Müllauer, Leonhard; Schiefer, Ana-Iris; Moser, Julia; Klepetko, Walter; Ankersmit, Hendrik Jan; Moser, Bernhard

2018-01-01

Background Peripheral blood-derived inflammation-based markers, such as Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Fibrinogen have been identified as prognostic markers in various solid malignancies. Here we aimed to investigate the prognostic and diagnostic impact of NLR, PLR, and Fibrinogen in patients with thymic epithelial tumors (TETs). Results Pretreatment Fibrinogen serum concentrations, NLRs and PLRs were highest in patients with TCs and advanced tumor stages. High pretreatment Fibrinogen serum concentration (≥452.5 mg/dL) was significantly associated with worse cause specific survival (CSS; p = 0.001) and freedom from recurrence (FFR; p = 0.043), high NLR (≥4.0) with worse FFR (p = 0.008), and high PLR (≥136.5) with worse CSS (p = 0.032). Longitudinal analysis revealed that compared to patients without tumor recurrence, patients with tumor recurrence had significantly higher NLR (11.8 ± 4.0 vs. 4.70 ± 0.5; p = 0.001) and PLR (410.8 ± 149.1 vs. 228.3 ± 23.7; p = 0.031). Conclusion Overall, Fibrinogen serum concentrations, NLRs, and PLRs were associated with higher tumor stage, more aggressive tumor behavior, recurrence, and worse outcome. Prospective multicenter studies of the diagnostic and prognostic potential of Fibrinogen, NLR, and PLR are warranted. Methods This retrospective analysis included 122 patients with TETs who underwent surgical resection between 1999-2015. Fibrinogen serum concentrations, NLRs, and PLRs were measured in patients preoperatively, postoperatively, and later during follow-up. These markers were analyzed for association with several clinical variables, including tumor stage, tumor subtype, FFR, and CSS and to evaluate their prognostic and diagnostic impact for detecting tumor recurrence. PMID:29774108

Caspase-3 activity, response to chemotherapy and clinical outcome in patients with colon cancer.

PubMed

de Oca, Javier; Azuara, Daniel; Sanchez-Santos, Raquel; Navarro, Matilde; Capella, Gabriel; Moreno, Victor; Sola, Anna; Hotter, Georgina; Biondo, Sebastiano; Osorio, Alfonso; Martí-Ragué, Joan; Rafecas, Antoni

2008-01-01

The prognostic value of the degree of apoptosis in colorectal cancer is controversial. This study evaluates the putative clinical usefulness of measuring caspase-3 activity as a prognostic factor in colonic cancer patients receiving 5-fluoracil adjuvant chemotherapy. We evaluated caspase-3-like protease activity in tumours and in normal colon tissue. Specimens were studied from 54 patients. These patients had either stage III cancer (Dukes stage C) or high-risk stage II cancer (Dukes stage B2 with invasion of adjacent organs, lymphatic or vascular infiltration or carcinoembryonic antigen [CEA] >5). Median follow-up was 73 months. Univariate analysis was performed previously to explore the relation of different variables (age, sex, preoperative CEA, tumour size, Dukes stage, vascular invasion, lymphatic invasion, caspase-3 activity in tumour and caspase-3 activity in normal mucosa) as prognostic factors of tumour recurrence after chemotherapy treatment. Subsequently, a multivariate Cox regression model was performed. Median values of caspase-3 activity in tumours were more than twice those in normal mucosa (88.1 vs 40.6 U, p=0.001), showing a statistically significant correlation (r=0.34). Significant prognostic factors of recurrence in multivariate analysis were: male sex (odds ratio, OR=3.53 [1.13-10.90], p=0.02), age (OR=1.09 [1.01-1.18], p=0.03), Dukes stage (OR=1.93 [1.01-3.70]), caspase-3 activity in normal mucosa (OR=1.02 [1.01-1.04], p=0.017) and caspase-3 activity in tumour (OR=1.02 [1.01-1.03], p=0.013). Low caspase-3 activity in the normal mucosa and tumour are independent prognostic factors of tumour recurrence in patients receiving adjuvant 5-fluoracil-based treatment in colon cancer, correlating with poor disease-free survival and higher recurrence rate.

Circulating Tumor Cells in Breast Cancer Patients Treated by Neoadjuvant Chemotherapy: A Meta-analysis.

PubMed

Bidard, François-Clément; Michiels, Stefan; Riethdorf, Sabine; Mueller, Volkmar; Esserman, Laura J; Lucci, Anthony; Naume, Bjørn; Horiguchi, Jun; Gisbert-Criado, Rafael; Sleijfer, Stefan; Toi, Masakazu; Garcia-Saenz, Jose A; Hartkopf, Andreas; Generali, Daniele; Rothé, Françoise; Smerage, Jeffrey; Muinelo-Romay, Laura; Stebbing, Justin; Viens, Patrice; Magbanua, Mark Jesus M; Hall, Carolyn S; Engebraaten, Olav; Takata, Daisuke; Vidal-Martínez, José; Onstenk, Wendy; Fujisawa, Noriyoshi; Diaz-Rubio, Eduardo; Taran, Florin-Andrei; Cappelletti, Maria Rosa; Ignatiadis, Michail; Proudhon, Charlotte; Wolf, Denise M; Bauldry, Jessica B; Borgen, Elin; Nagaoka, Rin; Carañana, Vicente; Kraan, Jaco; Maestro, Marisa; Brucker, Sara Yvonne; Weber, Karsten; Reyal, Fabien; Amara, Dominic; Karhade, Mandar G; Mathiesen, Randi R; Tokiniwa, Hideaki; Llombart-Cussac, Antonio; Meddis, Alessandra; Blanche, Paul; d'Hollander, Koenraad; Cottu, Paul; Park, John W; Loibl, Sibylle; Latouche, Aurélien; Pierga, Jean-Yves; Pantel, Klaus

2018-04-12

We conducted a meta-analysis in nonmetastatic breast cancer patients treated by neoadjuvant chemotherapy (NCT) to assess the clinical validity of circulating tumor cell (CTC) detection as a prognostic marker. We collected individual patient data from 21 studies in which CTC detection by CellSearch was performed in early breast cancer patients treated with NCT. The primary end point was overall survival, analyzed according to CTC detection, using Cox regression models stratified by study. Secondary end points included distant disease-free survival, locoregional relapse-free interval, and pathological complete response. All statistical tests were two-sided. Data from patients were collected before NCT (n = 1574) and before surgery (n = 1200). CTC detection revealed one or more CTCs in 25.2% of patients before NCT; this was associated with tumor size (P < .001). The number of CTCs detected had a detrimental and decremental impact on overall survival (P < .001), distant disease-free survival (P < .001), and locoregional relapse-free interval (P < .001), but not on pathological complete response. Patients with one, two, three to four, and five or more CTCs before NCT displayed hazard ratios of death of 1.09 (95% confidence interval [CI] = 0.65 to 1.69), 2.63 (95% CI = 1.42 to 4.54), 3.83 (95% CI = 2.08 to 6.66), and 6.25 (95% CI = 4.34 to 9.09), respectively. In 861 patients with full data available, adding CTC detection before NCT increased the prognostic ability of multivariable prognostic models for overall survival (P < .001), distant disease-free survival (P < .001), and locoregional relapse-free interval (P = .008). CTC count is an independent and quantitative prognostic factor in early breast cancer patients treated by NCT. It complements current prognostic models based on tumor characteristics and response to therapy.

Bimodality of intratumor Ki67 expression is an independent prognostic factor of overall survival in patients with invasive breast carcinoma.

PubMed

Laurinavicius, Arvydas; Plancoulaine, Benoit; Rasmusson, Allan; Besusparis, Justinas; Augulis, Renaldas; Meskauskas, Raimundas; Herlin, Paulette; Laurinaviciene, Aida; Abdelhadi Muftah, Abir A; Miligy, Islam; Aleskandarany, Mohammed; Rakha, Emad A; Green, Andrew R; Ellis, Ian O

2016-04-01

Proliferative activity, assessed by Ki67 immunohistochemistry (IHC), is an established prognostic and predictive biomarker of breast cancer (BC). However, it remains under-utilized due to lack of standardized robust measurement methodologies and significant intratumor heterogeneity of expression. A recently proposed methodology for IHC biomarker assessment in whole slide images (WSI), based on systematic subsampling of tissue information extracted by digital image analysis (DIA) into hexagonal tiling arrays, enables computation of a comprehensive set of Ki67 indicators, including intratumor variability. In this study, the tiling methodology was applied to assess Ki67 expression in WSI of 152 surgically removed Ki67-stained (on full-face sections) BC specimens and to test which, if any, Ki67 indicators can predict overall survival (OS). Visual Ki67 IHC estimates and conventional clinico-pathologic parameters were also included in the study. Analysis revealed linearly independent intrinsic factors of the Ki67 IHC variance: proliferation (level of expression), disordered texture (entropy), tumor size and Nottingham Prognostic Index, bimodality, and correlation. All visual and DIA-generated indicators of the level of Ki67 expression provided significant cutoff values as single predictors of OS. However, only bimodality indicators (Ashman's D, in particular) were independent predictors of OS in the context of hormone receptor and HER2 status. From this, we conclude that spatial heterogeneity of proliferative tumor activity, measured by DIA of Ki67 IHC expression and analyzed by the hexagonal tiling approach, can serve as an independent prognostic indicator of OS in BC patients that outperforms the prognostic power of the level of proliferative activity.

Innovative Bayesian and Parsimony Phylogeny of Dung Beetles (Coleoptera, Scarabaeidae, Scarabaeinae) Enhanced by Ontology-Based Partitioning of Morphological Characters

PubMed Central

Tarasov, Sergei; Génier, François

2015-01-01

Scarabaeine dung beetles are the dominant dung feeding group of insects and are widely used as model organisms in conservation, ecology and developmental biology. Due to the conflicts among 13 recently published phylogenies dealing with the higher-level relationships of dung beetles, the phylogeny of this lineage remains largely unresolved. In this study, we conduct rigorous phylogenetic analyses of dung beetles, based on an unprecedented taxon sample (110 taxa) and detailed investigation of morphology (205 characters). We provide the description of morphology and thoroughly illustrate the used characters. Along with parsimony, traditionally used in the analysis of morphological data, we also apply the Bayesian method with a novel approach that uses anatomy ontology for matrix partitioning. This approach allows for heterogeneity in evolutionary rates among characters from different anatomical regions. Anatomy ontology generates a number of parameter-partition schemes which we compare using Bayes factor. We also test the effect of inclusion of autapomorphies in the morphological analysis, which hitherto has not been examined. Generally, schemes with more parameters were favored in the Bayesian comparison suggesting that characters located on different body regions evolve at different rates and that partitioning of the data matrix using anatomy ontology is reasonable; however, trees from the parsimony and all the Bayesian analyses were quite consistent. The hypothesized phylogeny reveals many novel clades and provides additional support for some clades recovered in previous analyses. Our results provide a solid basis for a new classification of dung beetles, in which the taxonomic limits of the tribes Dichotomiini, Deltochilini and Coprini are restricted and many new tribes must be described. Based on the consistency of the phylogeny with biogeography, we speculate that dung beetles may have originated in the Mesozoic contrary to the traditional view pointing to a Cenozoic origin. PMID:25781019

Partitioning of Evapotranspiration Using a Stable Water Isotope Technique in a High Temperature Agricultural Production System

NASA Astrophysics Data System (ADS)

Lu, X.; Liang, L.; Wang, L.; Jenerette, D.; Grantz, D. A.

2015-12-01

Agricultural production in the hot and arid low desert systems of southern California relies heavily on irrigation. A better understanding of how much and to what extent the irrigation water is transpired by crops relative to being lost through evaporation will contribute to better management of increasingly limited agricultural water resources. In this study, we examined the evapotranspiration (ET) partitioning over a field of forage sorghum (S. bicolor) during a growing season with several irrigation cycles. In several field campaigns we used continuous measurements of near-surface variations in the stable isotopic composition of water vapor (δ2H). We employed custom built transparent chambers coupled with a laser-based isotope analyzer and used Keeling plot and mass balance methods for surface flux partitioning. The preliminary results show that δT is more enriched than δE in the early growing season, and becomes less enriched than δE later in the season as canopy cover increases. There is an increase in the contribution of transpiration to ET as (1) leaf area index increases, and (2) as soil surface moisture declines. These results are consistent with theory, and extend these measurements to an environment that experiences extreme soil surface temperatures. The data further support the use of chamber based methods with stable isotopic analysis for characterization of ET partitioning in challenging field environments.

Characterization of 1577 primary prostate cancers reveals novel biological and clinicopathologic insights into molecular subtypes.

PubMed

Tomlins, Scott A; Alshalalfa, Mohammed; Davicioni, Elai; Erho, Nicholas; Yousefi, Kasra; Zhao, Shuang; Haddad, Zaid; Den, Robert B; Dicker, Adam P; Trock, Bruce J; DeMarzo, Angelo M; Ross, Ashley E; Schaeffer, Edward M; Klein, Eric A; Magi-Galluzzi, Cristina; Karnes, R Jeffrey; Jenkins, Robert B; Feng, Felix Y

2015-10-01

Prostate cancer (PCa) molecular subtypes have been defined by essentially mutually exclusive events, including ETS gene fusions (most commonly involving ERG) and SPINK1 overexpression. Clinical assessment may aid in disease stratification, complementing available prognostic tests. To determine the analytical validity and clinicopatholgic associations of microarray-based molecular subtyping. We analyzed Affymetrix GeneChip expression profiles for 1577 patients from eight radical prostatectomy cohorts, including 1351 cases assessed using the Decipher prognostic assay (GenomeDx Biosciences, San Diego, CA, USA) performed in a laboratory with Clinical Laboratory Improvements Amendment certification. A microarray-based (m-) random forest ERG classification model was trained and validated. Outlier expression analysis was used to predict other mutually exclusive non-ERG ETS gene rearrangements (ETS(+)) or SPINK1 overexpression (SPINK1(+)). Associations with clinical features and outcomes by multivariate logistic regression analysis and receiver operating curves. The m-ERG classifier showed 95% accuracy in an independent validation subset (155 samples). Across cohorts, 45% of PCas were classified as m-ERG(+), 9% as m-ETS(+), 8% as m-SPINK1(+), and 38% as triple negative (m-ERG(-)/m-ETS(-)/m-SPINK1(-)). Gene expression profiling supports three underlying molecularly defined groups: m-ERG(+), m-ETS(+), and m-SPINK1(+)/triple negative. On multivariate analysis, m-ERG(+) tumors were associated with lower preoperative serum prostate-specific antigen and Gleason scores, but greater extraprostatic extension (p<0.001). m-ETS(+) tumors were associated with seminal vesicle invasion (p=0.01), while m-SPINK1(+)/triple negative tumors had higher Gleason scores and were more frequent in Black/African American patients (p<0.001). Clinical outcomes were not significantly different among subtypes. A clinically available prognostic test (Decipher) can also assess PCa molecular subtypes, obviating the need for additional testing. Clinicopathologic differences were found among subtypes based on global expression patterns. Molecular subtyping of prostate cancer can be achieved using extra data generated from a clinical-grade, genome-wide expression-profiling prognostic assay (Decipher). Transcriptomic and clinical analysis support three distinct molecular subtypes: (1) m-ERG(+), (2) m-ETS(+), and (3) m-SPINK1(+)/triple negative (m-ERG(-)/m-ETS(-)/m-SPINK1(-)). Incorporation of subtyping into a clinically available assay may facilitate additional applications beyond routine prognosis. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

EXPLORATORY ANALYSIS OF THE EFFECTS OF PARTICULATE CHARACTERISTICS ON THE VARIATION IN PARTITIONING OF NONPOLAR ORGANIC CONTAMINANTS TO MARINE SEDIMENTS

EPA Science Inventory

The partitioning of nonpolar organic contaminants to marine sediments is considered to be controlled by the amount of organic carbon present. However, several studies propose that other characteristics of sediments may affect the partitioning of contaminants. For this exploratory...

Newly identified poor prognostic factors for adult T-cell leukemia-lymphoma treated with allogeneic hematopoietic stem cell transplantation.

PubMed

Tokunaga, Masahito; Uto, Hirofumi; Takeuchi, Shogo; Nakano, Nobuaki; Kubota, Ayumu; Tokunaga, Mayumi; Takatsuka, Yoshifusa; Seto, Masao; Ido, Akio; Utsunomiya, Atae

2017-01-01

To explore pre-transplantation prognostic factors for adult T-cell leukemia-lymphoma (ATL), we retrospectively analyzed allogeneic hematopoietic stem cell transplantation (allo-HSCT) in 70 patients at our institute (63 acute type and seven lymphoma type patients). Forty-five patients died after HSCT and the three-year overall survival (OS) rate was 35.2%. By univariate analysis, the adverse prognostic factors for OS were performance status ≥2, hematopoietic cell transplantation-specific comorbidity index (HCT-CI) score ≥3, European Group for Blood and Marrow Transplantation (EBMT) risk score ≥5, HSCT from an HLA-mismatched donor, serum soluble interleukin-2 receptor (sIL-2R) level ≥10,000 U/mL, lymphocyte count ≥4000/μL, and hemoglobin <9 g/dL at the time of HSCT. EBMT risk score and sIL-2R were identified as significant adverse prognostic factors using multivariate analysis. This analysis clearly demonstrates for the first time that HCT-CI and EBMT risk scores are reliable prognostic factors for ATL patients receiving allo-HSCT.

Estimating average annual per cent change in trend analysis

PubMed Central

Clegg, Limin X; Hankey, Benjamin F; Tiwari, Ram; Feuer, Eric J; Edwards, Brenda K

2009-01-01

Trends in incidence or mortality rates over a specified time interval are usually described by the conventional annual per cent change (cAPC), under the assumption of a constant rate of change. When this assumption does not hold over the entire time interval, the trend may be characterized using the annual per cent changes from segmented analysis (sAPCs). This approach assumes that the change in rates is constant over each time partition defined by the transition points, but varies among different time partitions. Different groups (e.g. racial subgroups), however, may have different transition points and thus different time partitions over which they have constant rates of change, making comparison of sAPCs problematic across groups over a common time interval of interest (e.g. the past 10 years). We propose a new measure, the average annual per cent change (AAPC), which uses sAPCs to summarize and compare trends for a specific time period. The advantage of the proposed AAPC is that it takes into account the trend transitions, whereas cAPC does not and can lead to erroneous conclusions. In addition, when the trend is constant over the entire time interval of interest, the AAPC has the advantage of reducing to both cAPC and sAPC. Moreover, because the estimated AAPC is based on the segmented analysis over the entire data series, any selected subinterval within a single time partition will yield the same AAPC estimate—that is it will be equal to the estimated sAPC for that time partition. The cAPC, however, is re-estimated using data only from that selected subinterval; thus, its estimate may be sensitive to the subinterval selected. The AAPC estimation has been incorporated into the segmented regression (free) software Joinpoint, which is used by many registries throughout the world for characterizing trends in cancer rates. Copyright © 2009 John Wiley & Sons, Ltd. PMID:19856324

Two-protein signature of novel serological markers apolipoprotein-A2 and serum amyloid alpha predicts prognosis in patients with metastatic renal cell cancer and improves the currently used prognostic survival models.

PubMed

Vermaat, J S; van der Tweel, I; Mehra, N; Sleijfer, S; Haanen, J B; Roodhart, J M; Engwegen, J Y; Korse, C M; Langenberg, M H; Kruit, W; Groenewegen, G; Giles, R H; Schellens, J H; Beijnen, J H; Voest, E E

2010-07-01

In metastatic renal cell cancer (mRCC), the Memorial Sloan-Kettering Cancer Center (MSKCC) risk model is widely used for clinical trial design and patient management. To improve prognostication, we applied proteomics to identify novel serological proteins associated with overall survival (OS). Sera from 114 mRCC patients were screened by surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS). Identified proteins were related to OS. Three proteins were subsequently validated with enzyme-linked immunosorbent assays and immunoturbidimetry. Prognostic models were statistically bootstrapped to correct for overestimation. SELDI-TOF MS detected 10 proteins associated with OS. Of these, apolipoprotein A2 (ApoA2), serum amyloid alpha (SAA) and transthyretin were validated for their association with OS (P = 5.5 x 10(-9), P = 1.1 x 10(-7) and P = 0.0004, respectively). Combining ApoA2 and SAA yielded a prognostic two-protein signature [Akaike's Information Criteria (AIC) = 732, P = 5.2 x 10(-7)]. Including previously identified prognostic factors, multivariable Cox regression analysis revealed ApoA2, SAA, lactate dehydrogenase, performance status and number of metastasis sites as independent factors for survival. Using these five factors, categorization of patients into three risk groups generated a novel protein-based model predicting patient prognosis (AIC = 713, P = 4.3 x 10(-11)) more robustly than the MSKCC model (AIC = 729, P = 1.3 x 10(-7)). Applying this protein-based model instead of the MSKCC model would have changed the risk group in 38% of the patients. Proteomics and subsequent validation yielded two novel prognostic markers and survival models which improved prediction of OS in mRCC patients over commonly used risk models. Implementation of these models has the potential to improve current risk stratification, although prospective validation will still be necessary.

The Optimization of In-Memory Space Partitioning Trees for Cache Utilization

NASA Astrophysics Data System (ADS)

Yeo, Myung Ho; Min, Young Soo; Bok, Kyoung Soo; Yoo, Jae Soo

In this paper, a novel cache conscious indexing technique based on space partitioning trees is proposed. Many researchers investigated efficient cache conscious indexing techniques which improve retrieval performance of in-memory database management system recently. However, most studies considered data partitioning and targeted fast information retrieval. Existing data partitioning-based index structures significantly degrade performance due to the redundant accesses of overlapped spaces. Specially, R-tree-based index structures suffer from the propagation of MBR (Minimum Bounding Rectangle) information by updating data frequently. In this paper, we propose an in-memory space partitioning index structure for optimal cache utilization. The proposed index structure is compared with the existing index structures in terms of update performance, insertion performance and cache-utilization rate in a variety of environments. The results demonstrate that the proposed index structure offers better performance than existing index structures.

Nutritional status in the era of target therapy: poor nutrition is a prognostic factor in non-small cell lung cancer with activating epidermal growth factor receptor mutations.

PubMed

Park, Sehhoon; Park, Seongyeol; Lee, Se-Hoon; Suh, Beomseok; Keam, Bhumsuk; Kim, Tae Min; Kim, Dong-Wan; Kim, Young Whan; Heo, Dae Seog

2016-11-01

Pretreatment nutritional status is an important prognostic factor in patients treated with conventional cytotoxic chemotherapy. In the era of target therapies, its value is overlooked and has not been investigated. The aim of our study is to evaluate the value of nutritional status in targeted therapy. A total of 2012 patients with non-small cell lung cancer (NSCLC) were reviewed and 630 patients with activating epidermal growth factor receptor (EGFR) mutation treated with EGFR tyrosine kinase inhibitor (TKI) were enrolled for the final analysis. Anemia, body mass index (BMI), and prognostic nutritional index (PNI) were considered as nutritional factors. Hazard ratio (HR), progression-free survival (PFS) and overall survival (OS) for each group were calculated by Cox proportional analysis. In addition, scores were applied for each category and the sum of scores was used for survival analysis. In univariable analysis, anemia (HR, 1.29; p = 0.015), BMI lower than 18.5 (HR, 1.98; p = 0.002), and PNI lower than 45 (HR, 1.57; p < 0.001) were poor prognostic factors for PFS. Among them, BMI and PNI were independent in multi-variable analysis. All of these were also significant prognostic values for OS. The higher the sum of scores, the poorer PFS and OS were observed. Pretreatment nutritional status is a prognostic marker in NSCLC patients treated with EGFR TKI. Hence, baseline nutritional status should be more carefully evaluated and adequate nutrition should be supplied to these patients.

The degree of circumferential tumour involvement as a prognostic factor in oesophageal cancer.

PubMed

Sillah, Karim; Pritchard, Susan A; Watkins, Gillian R; McShane, James; West, Catharine M; Page, Richard; Welch, Ian M

2009-08-01

Tumour length is an adverse prognostic factor in oesophageal cancer. However, the prognostic role of the degree of oesophageal circumference (DOC) involved by tumour with or without resection margin invasion is not clear. This work assessed the relationship between DOC involved by tumour, clinico-pathological variables and prognosis. The clinico-pathological details of 320 patients who underwent potentially curative oesophagogastrectomy for cancer between 1994 and 2007 were analysed. The DOC involved with tumour measured macroscopically on the resected specimen was classified as small (<2.5 cm, n = 115), large (> or = 2.5 cm, n = 144) or circumferential (i.e. involving the whole circumference, n = 61). Univariate and multivariate survival analyses were carried out. The DOC with tumour was higher in ulcerating tumours than stenosing or polypoidal types (p = 0.017). Tumour length, T-stage, neoadjuvant chemotherapy and vascular invasion were independently associated with DOC with tumour on multivariate analysis (p < 0.05 for all). DOC > or = 2.5 cm was an adverse prognostic factor in univariate analysis (p = 0.002) with a hazard ratio of 1.52 [95% CI 1.13-2.04] compared with those <2.5 cm. Circumferential tumours had a similar prognosis to tumours > or = 2.5 cm (p = 0.60). The prognostic significance of DOC with tumour was lost in multivariate analysis where the factors retaining independence were patient age, T-stage, lymph node metastasis, vascular invasion and positive resection margins. However, when patients were stratified by use of neoadjuvant chemotherapy (n = 121), the DOC with tumour retained prognostic significance on multivariate analysis in the 199 patients who did not undergo neoadjuvant chemotherapy (p = 0.04). The DOC with tumour appears to provide prognostic information in oesophageal cancer surgery, especially in patients who do not undergo preoperative chemotherapy.

Number of negative lymph nodes should be considered for incorporation into staging for breast cancer

PubMed Central

Wu, San-Gang; Wang, Yan; Zhou, Juan; Sun, Jia-Yuan; Li, Feng-Yan; Lin, Huan-Xin; He, Zhen-Yu

2015-01-01

This study aimed to investigate the prognostic value of the number of involved lymph nodes (pN), number of removed lymph nodes (RLNs), lymph node ratio (LNR), number of negative lymph nodes (NLNs), and log odds of positive lymph nodes (LODDS) in breast cancer patients. The records of 2,515 breast cancer patients who received a mastectomy or breast-conserving surgery were retrospectively reviewed. The log-rank test was used to compare survival curves, and Cox regression analysis was performed to identify prognostic factors. The median follow-up time was 64.2 months, and the 8-year disease-free survival (DFS) and overall survival (OS) were 74.6% and 82.3%, respectively. Univariate analysis showed that pN stage, LNR, number of RLNs, and number of NLNs were significant prognostic factors for DFS and OS (all, P < 0.05). LODDS was a significant prognostic factor for OS (P = 0.021). Multivariate analysis indicated that pN stage and the number of NLNs were independent prognostic factors for DFS and OS. A higher number of NLNs was associated with higher DFS and OS, and a higher number of involved lymph nodes were associated with poorer DFS and OS. Patients with a NLNs count > 9 had better survival (P < 0.001). Subgroup analysis showed that the NLNs count had a prognostic value in patients with different pT stages and different lymph node status (log-rank P < 0.05). For breast cancer, pN stage and NLNs count have a better prognostic value compared to the RLNs count, LNR, and LODDS. Number of negative lymph nodes should be considered for incorporation into staging for breast cancer. PMID:25973321

A dynamic re-partitioning strategy based on the distribution of key in Spark

NASA Astrophysics Data System (ADS)

Zhang, Tianyu; Lian, Xin

2018-05-01

Spark is a memory-based distributed data processing framework, has the ability of processing massive data and becomes a focus in Big Data. But the performance of Spark Shuffle depends on the distribution of data. The naive Hash partition function of Spark can not guarantee load balancing when data is skewed. The time of job is affected by the node which has more data to process. In order to handle this problem, dynamic sampling is used. In the process of task execution, histogram is used to count the key frequency distribution of each node, and then generate the global key frequency distribution. After analyzing the distribution of key, load balance of data partition is achieved. Results show that the Dynamic Re-Partitioning function is better than the default Hash partition, Fine Partition and the Balanced-Schedule strategy, it can reduce the execution time of the task and improve the efficiency of the whole cluster.

Development of TLSER model and QSAR model for predicting partition coefficients of hydrophobic organic chemicals between low density polyethylene film and water.

PubMed

Liu, Huihui; Wei, Mengbi; Yang, Xianhai; Yin, Cen; He, Xiao

2017-01-01

Partition coefficients are vital parameters for measuring accurately the chemicals concentrations by passive sampling devices. Given the wide use of low density polyethylene (LDPE) film in passive sampling, we developed a theoretical linear solvation energy relationship (TLSER) model and a quantitative structure-activity relationship (QSAR) model for the prediction of the partition coefficient of chemicals between LDPE and water (K pew ). For chemicals with the octanol-water partition coefficient (log K ow ) <8, a TLSER model with V x (McGowan volume) and qA - (the most negative charge on O, N, S, X atoms) as descriptors was developed, but the model had relatively low determination coefficient (R 2 ) and cross-validated coefficient (Q 2 ). In order to further explore the theoretical mechanisms involved in the partition process, a QSAR model with four descriptors (MLOGP (Moriguchi octanol-water partition coeff.), P_VSA_s_3 (P_VSA-like on I-state, bin 3), Hy (hydrophilic factor) and NssO (number of atoms of type ssO)) was established, and statistical analysis indicated that the model had satisfactory goodness-of-fit, robustness and predictive ability. For chemicals with log K OW >8, a TLSER model with V x and a QSAR model with MLOGP as descriptor were developed. This is the first paper to explore the models for highly hydrophobic chemicals. The applicability domain of the models, characterized by the Euclidean distance-based method and Williams plot, covered a large number of structurally diverse chemicals, which included nearly all the common hydrophobic organic compounds. Additionally, through mechanism interpretation, we explored the structural features those governing the partition behavior of chemicals between LDPE and water. Copyright © 2016 Elsevier B.V. All rights reserved.

Uncertain Henry's law constants compromise equilibrium partitioning calculations of atmospheric oxidation products

NASA Astrophysics Data System (ADS)

Wang, Chen; Yuan, Tiange; Wood, Stephen A.; Goss, Kai-Uwe; Li, Jingyi; Ying, Qi; Wania, Frank

2017-06-01

Gas-particle partitioning governs the distribution, removal, and transport of organic compounds in the atmosphere and the formation of secondary organic aerosol (SOA). The large variety of atmospheric species and their wide range of properties make predicting this partitioning equilibrium challenging. Here we expand on earlier work and predict gas-organic and gas-aqueous phase partitioning coefficients for 3414 atmospherically relevant molecules using COSMOtherm, SPARC Performs Automated Reasoning in Chemistry (SPARC), and poly-parameter linear free-energy relationships. The Master Chemical Mechanism generated the structures by oxidizing primary emitted volatile organic compounds. Predictions for gas-organic phase partitioning coefficients (KWIOM/G) by different methods are on average within 1 order of magnitude of each other, irrespective of the numbers of functional groups, except for predictions by COSMOtherm and SPARC for compounds with more than three functional groups, which have a slightly higher discrepancy. Discrepancies between predictions of gas-aqueous partitioning (KW/G) are much larger and increase with the number of functional groups in the molecule. In particular, COSMOtherm often predicts much lower KW/G for highly functionalized compounds than the other methods. While the quantum-chemistry-based COSMOtherm accounts for the influence of intra-molecular interactions on conformation, highly functionalized molecules likely fall outside of the applicability domain of the other techniques, which at least in part rely on empirical data for calibration. Further analysis suggests that atmospheric phase distribution calculations are sensitive to the partitioning coefficient estimation method, in particular to the estimated value of KW/G. The large uncertainty in KW/G predictions for highly functionalized organic compounds needs to be resolved to improve the quantitative treatment of SOA formation.

[Partial stomach partitioning gastrojejunostomy in the treatment of the malignant gastric outlet obstruction].

PubMed

Abdel-lah-Fernández, Omar; Parreño-Manchado, Felipe Carlos; García-Plaza, Asunción; Álvarez-Delgado, Alberto

2015-01-01

In patients with unresectable gastric cancer and outlet obstruction syndrome, gastric partitioning gastrojejunostomy is an alternative, which could avoid the drawbacks of the standard techniques. Comparison of antroduodenal stent, conventional gastrojejunostomy and gastric partitioning gastrojejunostomy. A retrospective, cross-sectional study was conducted on patients with unresectable distal gastric cancer and gastric outlet obstruction, treated with the three different techniques over the last 12 years, comparing results based on oral tolerance and complications. An analysis was performed on the results using the Student-t test for independent variables. The 22 patients were divided in 3 groups: group I (6 cases) stent, group II (9 cases) conventional gastrojejunostomy, and group III (7 cases) gastric partitioning gastrojejunostomy, respectively. The stent allows a shorter "postoperative" stay and early onset of oral tolerance (P<0.05), however, the gastric partitioning gastrojejunostomy achieve normal diet at 15th day (P<0.05). The mortality rate was higher in the stent group (33%) compared with surgical techniques, with a morbidity of 4/6 (66.7%) in Group I, 6/9 (66.7%) Group II, and 3/7 (42%) Group III. Re-interventions: 2/6 Group I, 3/9 Group II, and 0/7 Group III. The median survival was superior in the gastric partitioning gastrojejunostomy, achieving an overall survival of 6.5 months. The gastric partitioning gastrojejunostomy for treatment of gastric outlet obstruction in unresectable advanced gastric cancer is a safe technique, allowing a more complete diet with lower morbidity and improved survival. Copyright © 2015 Academia Mexicana de Cirugía A.C. Published by Masson Doyma México S.A. All rights reserved.

What are the structural features that drive partitioning of proteins in aqueous two-phase systems?

PubMed

Wu, Zhonghua; Hu, Gang; Wang, Kui; Zaslavsky, Boris Yu; Kurgan, Lukasz; Uversky, Vladimir N

2017-01-01

Protein partitioning in aqueous two-phase systems (ATPSs) represents a convenient, inexpensive, and easy to scale-up protein separation technique. Since partition behavior of a protein dramatically depends on an ATPS composition, it would be highly beneficial to have reliable means for (even qualitative) prediction of partitioning of a target protein under different conditions. Our aim was to understand which structural features of proteins contribute to partitioning of a query protein in a given ATPS. We undertook a systematic empirical analysis of relations between 57 numerical structural descriptors derived from the corresponding amino acid sequences and crystal structures of 10 well-characterized proteins and the partition behavior of these proteins in 29 different ATPSs. This analysis revealed that just a few structural characteristics of proteins can accurately determine behavior of these proteins in a given ATPS. However, partition behavior of proteins in different ATPSs relies on different structural features. In other words, we could not find a unique set of protein structural features derived from their crystal structures that could be used for the description of the protein partition behavior of all proteins in all ATPSs analyzed in this study. We likely need to gain better insight into relationships between protein-solvent interactions and protein structure peculiarities, in particular given limitations of the used here crystal structures, to be able to construct a model that accurately predicts protein partition behavior across all ATPSs. Copyright © 2016 Elsevier B.V. All rights reserved.

Prognostic factors in prostate cancer patients treated by radical external beam radiotherapy.

PubMed

Garibaldi, Elisabetta; Gabriele, Domenico; Maggio, Angelo; Delmastro, Elena; Garibaldi, Monica; Russo, Filippo; Bresciani, Sara; Stasi, Michele; Gabriele, Pietro

2017-09-01

The aim of this paper was to analyze, retrospectively, in prostate cancer patients treated in our Centre with external beam radiotherapy, the prognostic factors and their impact on the outcome in terms of cancer-specific survival (CSS), biochemical disease-free survival (BDFS) and clinical disease-free survival (CDFS). From October 1999 and March 2012, 1080 patients were treated with radiotherapy at our Institution: 87% of them were classified as ≤cT2, 83% had a Gleason Score (GS) ≤7, their mean of iPSA was 18 ng/mL, and the rate of clinical positive nodes was 1%. The mean follow-up was 81 months. The statistically significant prognostic factors for all groups of patients at both, univariate and multivariate analysis, were the GS and the iPSA. In intermediate- and high- or very-high-risk patients at multivariate analysis other prognostic factors for CSS were positive nodes on computed tomography (CT) scan and rectal preparation during the treatment; for BDFS, the prognostic factors were patient risk classification, positive lymph nodes on CT scan and rectal/bladder preparation; for CDFS, the prognostic factors were the number of positive core on biopsy (P=0.003), positive lymph nodes on CT scan, and radiotherapy (RT) dose. In high/very-high risk patient group at multivariate analysis other prognostic factors for CSS were clinical/radiological stage and RT dose, for BDFS they were adjuvant hormone therapy, clinical/radiological stage, and RT dose >77.7 Gy, and for CDFS they were clinical/radiological stage and RT dose >77.7 Gy. The results of this study confirm the prognostic factors described in the recent literature, with the addition of rectal/bladder preparation, generally known for its effect on toxicity but not yet on outcome.

Bayesian approach to estimate AUC, partition coefficient and drug targeting index for studies with serial sacrifice design.

PubMed

Wang, Tianli; Baron, Kyle; Zhong, Wei; Brundage, Richard; Elmquist, William

2014-03-01

The current study presents a Bayesian approach to non-compartmental analysis (NCA), which provides the accurate and precise estimate of AUC 0 (∞) and any AUC 0 (∞) -based NCA parameter or derivation. In order to assess the performance of the proposed method, 1,000 simulated datasets were generated in different scenarios. A Bayesian method was used to estimate the tissue and plasma AUC 0 (∞) s and the tissue-to-plasma AUC 0 (∞) ratio. The posterior medians and the coverage of 95% credible intervals for the true parameter values were examined. The method was applied to laboratory data from a mice brain distribution study with serial sacrifice design for illustration. Bayesian NCA approach is accurate and precise in point estimation of the AUC 0 (∞) and the partition coefficient under a serial sacrifice design. It also provides a consistently good variance estimate, even considering the variability of the data and the physiological structure of the pharmacokinetic model. The application in the case study obtained a physiologically reasonable posterior distribution of AUC, with a posterior median close to the value estimated by classic Bailer-type methods. This Bayesian NCA approach for sparse data analysis provides statistical inference on the variability of AUC 0 (∞) -based parameters such as partition coefficient and drug targeting index, so that the comparison of these parameters following destructive sampling becomes statistically feasible.

Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors

PubMed Central

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-01-01

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of log BB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (log P), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental log BB data had been determined in vivo. In particular, since molecules with log BB > 0.3 cross the blood-brain barrier (BBB) readily while molecules with log BB < −1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the log BB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings. PMID:20427217

Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors.

PubMed

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-06-01

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of logBB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (logP), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental logBB data had been determined in vivo. In particular, since molecules with logBB>0.3 cross the blood-brain barrier (BBB) readily while molecules with logBB<-1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the logBB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings. Published by Elsevier Inc.

Analysis of ParB-centromere interactions by multiplex SPR imaging reveals specific patterns for binding ParB in six centromeres of Burkholderiales chromosomes and plasmids

PubMed Central

Pillet, Flavien; Passot, Fanny Marie

2017-01-01

Bacterial centromeres–also called parS, are cis-acting DNA sequences which, together with the proteins ParA and ParB, are involved in the segregation of chromosomes and plasmids. The specific binding of ParB to parS nucleates the assembly of a large ParB/DNA complex from which ParA—the motor protein, segregates the sister replicons. Closely related families of partition systems, called Bsr, were identified on the chromosomes and large plasmids of the multi-chromosomal bacterium Burkholderia cenocepacia and other species from the order Burkholeriales. The centromeres of the Bsr partition families are 16 bp palindromes, displaying similar base compositions, notably a central CG dinucleotide. Despite centromeres bind the cognate ParB with a narrow specificity, weak ParB-parS non cognate interactions were nevertheless detected between few Bsr partition systems of replicons not belonging to the same genome. These observations suggested that Bsr partition systems could have a common ancestry but that evolution mostly erased the possibilities of cross-reactions between them, in particular to prevent replicon incompatibility. To detect novel similarities between Bsr partition systems, we have analyzed the binding of six Bsr parS sequences and a wide collection of modified derivatives, to their cognate ParB. The study was carried out by Surface Plasmon Resonance imaging (SPRi) mulitplex analysis enabling a systematic survey of each nucleotide position within the centromere. We found that in each parS some positions could be changed while maintaining binding to ParB. Each centromere displays its own pattern of changes, but some positions are shared more or less widely. In addition from these changes we could speculate evolutionary links between these centromeres. PMID:28562673

Analysis of ParB-centromere interactions by multiplex SPR imaging reveals specific patterns for binding ParB in six centromeres of Burkholderiales chromosomes and plasmids.

PubMed

Pillet, Flavien; Passot, Fanny Marie; Pasta, Franck; Anton Leberre, Véronique; Bouet, Jean-Yves

2017-01-01

Bacterial centromeres-also called parS, are cis-acting DNA sequences which, together with the proteins ParA and ParB, are involved in the segregation of chromosomes and plasmids. The specific binding of ParB to parS nucleates the assembly of a large ParB/DNA complex from which ParA-the motor protein, segregates the sister replicons. Closely related families of partition systems, called Bsr, were identified on the chromosomes and large plasmids of the multi-chromosomal bacterium Burkholderia cenocepacia and other species from the order Burkholeriales. The centromeres of the Bsr partition families are 16 bp palindromes, displaying similar base compositions, notably a central CG dinucleotide. Despite centromeres bind the cognate ParB with a narrow specificity, weak ParB-parS non cognate interactions were nevertheless detected between few Bsr partition systems of replicons not belonging to the same genome. These observations suggested that Bsr partition systems could have a common ancestry but that evolution mostly erased the possibilities of cross-reactions between them, in particular to prevent replicon incompatibility. To detect novel similarities between Bsr partition systems, we have analyzed the binding of six Bsr parS sequences and a wide collection of modified derivatives, to their cognate ParB. The study was carried out by Surface Plasmon Resonance imaging (SPRi) mulitplex analysis enabling a systematic survey of each nucleotide position within the centromere. We found that in each parS some positions could be changed while maintaining binding to ParB. Each centromere displays its own pattern of changes, but some positions are shared more or less widely. In addition from these changes we could speculate evolutionary links between these centromeres.

Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial.

PubMed

Albain, Kathy S; Barlow, William E; Shak, Steven; Hortobagyi, Gabriel N; Livingston, Robert B; Yeh, I-Tien; Ravdin, Peter; Bugarini, Roberto; Baehner, Frederick L; Davidson, Nancy E; Sledge, George W; Winer, Eric P; Hudis, Clifford; Ingle, James N; Perez, Edith A; Pritchard, Kathleen I; Shepherd, Lois; Gralow, Julie R; Yoshizawa, Carl; Allred, D Craig; Osborne, C Kent; Hayes, Daniel F

2010-01-01

The 21-gene recurrence score assay is prognostic for women with node-negative, oestrogen-receptor-positive breast cancer treated with tamoxifen. A low recurrence score predicts little benefit of chemotherapy. For node-positive breast cancer, we investigated whether the recurrence score was prognostic in women treated with tamoxifen alone and whether it identified those who might not benefit from anthracycline-based chemotherapy, despite higher risks of recurrence. The phase 3 trial SWOG-8814 for postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer showed that chemotherapy with cyclophosphamide, doxorubicin, and fluorouracil (CAF) before tamoxifen (CAF-T) added survival benefit to treatment with tamoxifen alone. Optional tumour banking yielded specimens for determination of recurrence score by RT-PCR. In this retrospective analysis, we assessed the effect of recurrence score on disease-free survival by treatment group (tamoxifen vs CAF-T) using Cox regression, adjusting for number of positive nodes. There were 367 specimens (40% of the 927 patients in the tamoxifen and CAF-T groups) with sufficient RNA for analysis (tamoxifen, n=148; CAF-T, n=219). The recurrence score was prognostic in the tamoxifen-alone group (p=0.006; hazard ratio [HR] 2.64, 95% CI 1.33-5.27, for a 50-point difference in recurrence score). There was no benefit of CAF in patients with a low recurrence score (score <18; log-rank p=0.97; HR 1.02, 0.54-1.93), but an improvement in disease-free survival for those with a high recurrence score (score > or =31; log-rank p=0.033; HR 0.59, 0.35-1.01), after adjustment for number of positive nodes. The recurrence score by treatment interaction was significant in the first 5 years (p=0.029), with no additional prediction beyond 5 years (p=0.58), although the cumulative benefit remained at 10 years. Results were similar for overall survival and breast-cancer-specific survival. The recurrence score is prognostic for tamoxifen-treated patients with positive nodes and predicts significant benefit of CAF in tumours with a high recurrence score. A low recurrence score identifies women who might not benefit from anthracycline-based chemotherapy, despite positive nodes. National Cancer Institute and Genomic Health. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma.

PubMed

Grinchuk, Oleg V; Yenamandra, Surya P; Iyer, Ramakrishnan; Singh, Malay; Lee, Hwee Kuan; Lim, Kiat Hon; Chow, Pierce Kah-Hoe; Kuznetsov, Vladamir A

2018-01-01

Currently, molecular markers are not used when determining the prognosis and treatment strategy for patients with hepatocellular carcinoma (HCC). In the present study, we proposed that the identification of common pro-oncogenic pathways in primary tumors (PT) and adjacent non-malignant tissues (AT) typically used to predict HCC patient risks may result in HCC biomarker discovery. We examined the genome-wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients. The workflow integrated differentially expressed gene selection, gene ontology enrichment, computational classification, survival predictions, image analysis and experimental validation methods. We developed a 24-ribosomal gene-based HCC classifier (RGC), which is prognostically significant in both PT and AT. The RGC gene overexpression in PT was associated with a poor prognosis in the training (hazard ratio = 8.2, P = 9.4 × 10 -6 ) and cross-cohort validation (hazard ratio = 2.63, P = 0.004) datasets. The multivariate survival analysis demonstrated the significant and independent prognostic value of the RGC. The RGC displayed a significant prognostic value in AT of the training (hazard ratio = 5.0, P = 0.03) and cross-validation (hazard ratio = 1.9, P = 0.03) HCC groups, confirming the accuracy and robustness of the RGC. Our experimental and bioinformatics analyses suggested a key role for c-MYC in the pro-oncogenic pattern of ribosomal biogenesis co-regulation in PT and AT. Microarray, quantitative RT-PCR and quantitative immunohistochemical studies of the PT showed that DKK1 in PT is the perspective biomarker for poor HCC outcomes. The common co-transcriptional pattern of ribosome biogenesis genes in PT and AT from HCC patients suggests a new scalable prognostic system, as supported by the model of tumor-like metabolic redirection/assimilation in non-malignant AT. The RGC, comprising 24 ribosomal genes, is introduced as a robust and reproducible prognostic model for stratifying HCC patient risks. The adjacent non-malignant liver tissue alone, or in combination with HCC tissue biopsy, could be an important target for developing predictive and monitoring strategies, as well as evidence-based therapeutic interventions, that aim to reduce the risk of post-surgery relapse in HCC patients. © 2017 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

Active control of sound transmission through a double panel partition

NASA Astrophysics Data System (ADS)

Sas, P.; Bao, C.; Augusztinovicz, F.; Desmet, W.

1995-03-01

The feasibility of improving the insertion loss of lightweight double panel partitions by using small loudspeakers as active noise control sources inside the air gap between both panels of the partition is investigated analytically, numerically and experimentally in this paper. A theoretical analysis of the mechanisms of the fluid-structure interaction of double panel structures is presented in order to gain insight into the physical phenomena underlying the behaviour of a coupled vibro-acoustic system controlled by active methods. The analysis, based on modal coupling theory, enables one to derive some qualitative predictions concerning the potentials and limitations of the proposed approach. The theoretical analysis is valid only for geometrically simple structures. For more complex geometries, numerical simulations are required. Therefore the potential use of active noise control inside double panel structures has been analyzed by using coupled finite element and boundary element methods. To verify the conclusions drawn from the theoretical analysis and the numerical calculation and, above all, to demonstrate the potential of the proposed approach, experiments have been conducted with a laboratory set-up. The performance of the proposed approach was evaluated in terms of relative insertion loss measurements. It is shown that a considerable improvement of the insertion loss has been achieved around the lightly damped resonances of the system for the frequency range investigated (60-220 Hz).

The Shock and Vibration Digest, Volume 17, Number 8

DTIC Science & Technology

1985-08-01

ate, transmit, and radiate audible sound. dures are based on acoustic power flow, statistical energy analysis (SEA), and modal methods [22-283. A...modified partition area. features of the acoustic field. I.--1 85-1642 Statistical Energy Analysis , Structural Reso- nances, and Beam Networks BUILDING...energy methods, Structural resonance L.J. Lee Heriot-Watt Univ., Chambers St., Edinburgh The statistical energy analysis method is EHI 1HX, Scotland

A New Model for Optimal Mechanical and Thermal Performance of Cement-Based Partition Wall

PubMed Central

Huang, Shiping; Hu, Mengyu; Cui, Nannan; Wang, Weifeng

2018-01-01

The prefabricated cement-based partition wall has been widely used in assembled buildings because of its high manufacturing efficiency, high-quality surface, and simple and convenient construction process. In this paper, a general porous partition wall that is made from cement-based materials was proposed to meet the optimal mechanical and thermal performance during transportation, construction and its service life. The porosity of the proposed partition wall is formed by elliptic-cylinder-type cavities. The finite element method was used to investigate the mechanical and thermal behaviour, which shows that the proposed model has distinct advantages over the current partition wall that is used in the building industry. It is found that, by controlling the eccentricity of the elliptic-cylinder cavities, the proposed wall stiffness can be adjusted to respond to the imposed loads and to improve the thermal performance, which can be used for the optimum design. Finally, design guidance is provided to obtain the optimal mechanical and thermal performance. The proposed model could be used as a promising candidate for partition wall in the building industry. PMID:29673176

A New Model for Optimal Mechanical and Thermal Performance of Cement-Based Partition Wall.

PubMed

Huang, Shiping; Hu, Mengyu; Huang, Yonghui; Cui, Nannan; Wang, Weifeng

2018-04-17

The prefabricated cement-based partition wall has been widely used in assembled buildings because of its high manufacturing efficiency, high-quality surface, and simple and convenient construction process. In this paper, a general porous partition wall that is made from cement-based materials was proposed to meet the optimal mechanical and thermal performance during transportation, construction and its service life. The porosity of the proposed partition wall is formed by elliptic-cylinder-type cavities. The finite element method was used to investigate the mechanical and thermal behaviour, which shows that the proposed model has distinct advantages over the current partition wall that is used in the building industry. It is found that, by controlling the eccentricity of the elliptic-cylinder cavities, the proposed wall stiffness can be adjusted to respond to the imposed loads and to improve the thermal performance, which can be used for the optimum design. Finally, design guidance is provided to obtain the optimal mechanical and thermal performance. The proposed model could be used as a promising candidate for partition wall in the building industry.

An Assessment of the State-of-the-Art in Multidisciplinary Aeromechanical Analyses

DTIC Science & Technology

2008-01-01

monolithic formulations. In summary, for aerospace structures, partitioned formulations provide fundamental advantages over fully coupled ones, in addition...important frequencies of local analysis directly to global analysis using detailed modeling. Performed ju- diciously, based on a fundamental understanding of...in 2000 has com- prehensively described the problem, and reviewed the status of fundamental understanding, experimental data, and analytical

Analysis of swainsonine and swainsonine N-oxide as trimethylsilyl derivatives by Liquid Chromatography-Mass Spectrometry and their relative occurrence in plants toxic to livestock

USDA-ARS?s Scientific Manuscript database

A liquid chromatography-mass spectrometry method was developed for the analysis of the indolizidine alkaloid swainsonine and its N-oxide. The method is based on a one step solvent partitioning extraction procedure followed by trimethylsilylation of the dried extract and subsequent detection and qua...

Feynman graphs and the large dimensional limit of multipartite entanglement

NASA Astrophysics Data System (ADS)

Di Martino, Sara; Facchi, Paolo; Florio, Giuseppe

2018-01-01

In this paper, we extend the analysis of multipartite entanglement, based on techniques from classical statistical mechanics, to a system composed of n d-level parties (qudits). We introduce a suitable partition function at a fictitious temperature with the average local purity of the system as Hamiltonian. In particular, we analyze the high-temperature expansion of this partition function, prove the convergence of the series, and study its asymptotic behavior as d → ∞. We make use of a diagrammatic technique, classify the graphs, and study their degeneracy. We are thus able to evaluate their contributions and estimate the moments of the distribution of the local purity.

The challenge to unify treatment of high-temperature fatigue - A partisan proposal based on strainrange partitioning

NASA Technical Reports Server (NTRS)

Manson, S. S.

1972-01-01

The strainrange partitioning concept divides the imposed strain into four basic ranges involving time-dependent and time-independent components. It is shown that some of the results presented at the symposium can be better correlated on the basis of this concept than by alternative methods. It is also suggested that methods of data generation and analysis can be helpfully guided by this approach. Potential applicability of the concept to the treatment of frequency and hold-time effects, environmental influence, crack initiation and growth, thermal fatigue, and code specifications are briefly considered. A required experimental program is outlined.

A Retrospective Survival Analysis of Anatomic and Prognostic Stage Group Based on the American Joint Committee on Cancer 8th Edition Cancer Staging Manual in Luminal B Human Epidermal Growth Factor Receptor 2-negative Breast Cancer.

PubMed

Xu, Ling; Li, Jiang-Hong; Ye, Jing-Ming; Duan, Xue-Ning; Cheng, Yuan-Jia; Xin, Ling; Liu, Qian; Zhou, Bin; Liu, Yin-Hua

2017-08-20

Current understanding of tumor biology suggests that breast cancer is a group of diseases with different intrinsic molecular subtypes. Anatomic staging system alone is insufficient to provide future outcome information. The American Joint Committee on Cancer (AJCC) expert panel updated the 8th edition of the staging manual with prognostic stage groups by incorporating biomarkers into the anatomic stage groups. In this study, we retrospectively analyzed the data from our center in China using the anatomic and prognostic staging system based on the AJCC 8th edition staging manual. We reviewed the data from January 2008 to December 2014 for cases with Luminal B Human Epidermal Growth Factor Receptor 2 (HER2)-negative breast cancer in our center. All cases were restaged using the AJCC 8th edition anatomic and prognostic staging system. The Kaplan-Meier method and log-rank test were used to compare the survival differences between different subgroups. SPSS software version 19.0 (IBM Corp., Armonk, NY, USA) was used for the statistical analyses. This study consisted of 796 patients with Luminal B HER-negative breast cancer. The 5-year disease-free survival (DFS) of 769 Stage I-III patients was 89.7%, and the 5-year overall survival (OS) of all 796 patients was 91.7%. Both 5-year DFS and 5-year OS were significantly different in the different anatomic and prognostic stage groups. There were 372 cases (46.7%) assigned to a different group. The prognostic Stage II and III patients restaged from anatomic Stage III had significant differences in 5-year DFS (χ2 = 11.319, P= 0.001) and 5-year OS (χ2 = 5.225, P= 0.022). In addition, cases restaged as prognostic Stage I, II, or III from the anatomic Stage II group had statistically significant differences in 5-year DFS (χ2 = 6.510, P= 0.039) but no significant differences in 5-year OS (χ2 = 5.087, P= 0.079). However, the restaged prognostic Stage I and II cases from anatomic Stage I had no statistically significant differences in either 5-year DFS (χ2 = 0.440, P= 0.507) or 5-year OS (χ2 = 1.530, P= 0.216). The prognostic staging system proposed in the AJCC 8th edition refines the anatomic stage group in Luminal B HER2-negative breast cancer and will lead to a more personalized approach to breast cancer treatment.

A supermatrix analysis of genomic, morphological, and paleontological data from crown Cetacea

PubMed Central

2011-01-01

Background Cetacea (dolphins, porpoises, and whales) is a clade of aquatic species that includes the most massive, deepest diving, and largest brained mammals. Understanding the temporal pattern of diversification in the group as well as the evolution of cetacean anatomy and behavior requires a robust and well-resolved phylogenetic hypothesis. Although a large body of molecular data has accumulated over the past 20 years, DNA sequences of cetaceans have not been directly integrated with the rich, cetacean fossil record to reconcile discrepancies among molecular and morphological characters. Results We combined new nuclear DNA sequences, including segments of six genes (~2800 basepairs) from the functionally extinct Yangtze River dolphin, with an expanded morphological matrix and published genomic data. Diverse analyses of these data resolved the relationships of 74 taxa that represent all extant families and 11 extinct families of Cetacea. The resulting supermatrix (61,155 characters) and its sub-partitions were analyzed using parsimony methods. Bayesian and maximum likelihood (ML) searches were conducted on the molecular partition, and a molecular scaffold obtained from these searches was used to constrain a parsimony search of the morphological partition. Based on analysis of the supermatrix and model-based analyses of the molecular partition, we found overwhelming support for 15 extant clades. When extinct taxa are included, we recovered trees that are significantly correlated with the fossil record. These trees were used to reconstruct the timing of cetacean diversification and the evolution of characters shared by "river dolphins," a non-monophyletic set of species according to all of our phylogenetic analyses. Conclusions The parsimony analysis of the supermatrix and the analysis of morphology constrained to fit the ML/Bayesian molecular tree yielded broadly congruent phylogenetic hypotheses. In trees from both analyses, all Oligocene taxa included in our study fell outside crown Mysticeti and crown Odontoceti, suggesting that these two clades radiated in the late Oligocene or later, contra some recent molecular clock studies. Our trees also imply that many character states shared by river dolphins evolved in their oceanic ancestors, contradicting the hypothesis that these characters are convergent adaptations to fluvial habitats. PMID:21518443

A supermatrix analysis of genomic, morphological, and paleontological data from crown Cetacea.

PubMed

Geisler, Jonathan H; McGowen, Michael R; Yang, Guang; Gatesy, John

2011-04-25

Cetacea (dolphins, porpoises, and whales) is a clade of aquatic species that includes the most massive, deepest diving, and largest brained mammals. Understanding the temporal pattern of diversification in the group as well as the evolution of cetacean anatomy and behavior requires a robust and well-resolved phylogenetic hypothesis. Although a large body of molecular data has accumulated over the past 20 years, DNA sequences of cetaceans have not been directly integrated with the rich, cetacean fossil record to reconcile discrepancies among molecular and morphological characters. We combined new nuclear DNA sequences, including segments of six genes (~2800 basepairs) from the functionally extinct Yangtze River dolphin, with an expanded morphological matrix and published genomic data. Diverse analyses of these data resolved the relationships of 74 taxa that represent all extant families and 11 extinct families of Cetacea. The resulting supermatrix (61,155 characters) and its sub-partitions were analyzed using parsimony methods. Bayesian and maximum likelihood (ML) searches were conducted on the molecular partition, and a molecular scaffold obtained from these searches was used to constrain a parsimony search of the morphological partition. Based on analysis of the supermatrix and model-based analyses of the molecular partition, we found overwhelming support for 15 extant clades. When extinct taxa are included, we recovered trees that are significantly correlated with the fossil record. These trees were used to reconstruct the timing of cetacean diversification and the evolution of characters shared by "river dolphins," a non-monophyletic set of species according to all of our phylogenetic analyses. The parsimony analysis of the supermatrix and the analysis of morphology constrained to fit the ML/Bayesian molecular tree yielded broadly congruent phylogenetic hypotheses. In trees from both analyses, all Oligocene taxa included in our study fell outside crown Mysticeti and crown Odontoceti, suggesting that these two clades radiated in the late Oligocene or later, contra some recent molecular clock studies. Our trees also imply that many character states shared by river dolphins evolved in their oceanic ancestors, contradicting the hypothesis that these characters are convergent adaptations to fluvial habitats.

Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients.

PubMed

Kim, Yun Hak; Jeong, Dae Cheon; Pak, Kyoungjune; Goh, Tae Sik; Lee, Chi-Seung; Han, Myoung-Eun; Kim, Ji-Young; Liangwen, Liu; Kim, Chi Dae; Jang, Jeon Yeob; Cha, Wonjae; Oh, Sae-Ock

2017-09-29

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients.

Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients

PubMed Central

Kim, Yun Hak; Jeong, Dae Cheon; Pak, Kyoungjune; Goh, Tae Sik; Lee, Chi-Seung; Han, Myoung-Eun; Kim, Ji-Young; Liangwen, Liu; Kim, Chi Dae; Jang, Jeon Yeob; Cha, Wonjae; Oh, Sae-Ock

2017-01-01

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients. PMID:29100405

The prognostic value of reactive stroma on prostate needle biopsy: a population-based study.

PubMed

Saeter, Thorstein; Vlatkovic, Ljiljana; Waaler, Gudmund; Servoll, Einar; Nesland, Jahn M; Axcrona, Karol; Axcrona, Ulrika

2015-05-01

Reactive tumor stroma has been shown to play an active role in prostatic carcinogenesis. A grading system for reactive stroma in prostate cancer (PC) has recently been established and found to predict biochemical recurrence and prostate cancer-specific mortality (PCSM) in prostatectomized patients. To the best of our knowledge, there has been no study investigating the prognostic value of reactive stromal grading (RSG) with regard to PCSM when evaluated in diagnostic prostate needle biopsies. A population-based study on 318 patients, encompassing all cases of PC diagnosed by needle biopsies and without evidence of systemic metastasis at the time of diagnosis in Aust-Agder County in the period 1991-1999. Patients were identified by cross-referencing the Cancer Registry of Norway. Clinical data were obtained by review of medical charts. The endpoint was PCSM. RSG was evaluated on haematoxylin and eosin stained sections according to previously described criteria; grade 0, 0-5% reactive stroma; grade 1, 6-15%; grade 2, 16-50%; grade 3, 51-100%. RSG could be evaluated in 278 patients. The median follow- up time was 110 months (interquartile range: 51-171). The 10-year PC - specific survival rate for RSGs of 0, 1, 2, and 3 was 96%, 81%, 69%, and 63%, respectively (P < 0.005). RSG remained independently associated with PCSM in a multivariate Cox regression analysis adjusting for prostate-specific antigen level, clinical stage, Gleason score, and mode of treatment. The concordance index of the multivariate model was 0.814 CONCLUSIONS: Our study demonstrates that RSG in diagnostic prostate needle biopsies predicts PCSM independently of other evaluable prognostic factors. Hence, RSG could be used in addition to traditional prognostic factors for prognostication and treatment stratification of PC patients. © 2015 Wiley Periodicals, Inc.

Partition coefficients of organic compounds in lipid-water systems and correlations with fish bioconcentration factors

USGS Publications Warehouse

Chiou, C.T.

1985-01-01

Triolein-water partition coefficients (KtW) have been determined for 38 slightly water-soluble organic compounds, and their magnitudes have been compared with the corresponding octanol-water partition coefficients (KOW). In the absence of major solvent-solute interaction effects in the organic solvent phase, the conventional treatment (based on Raoult's law) predicts sharply lower partition coefficients for most of the solutes in triolein because of its considerably higher molecular weight, whereas the Flory-Huggins treatment predicts higher partition coefficients with triolein. The data are in much better agreement with the Flory-Huggins model. As expected from the similarity in the partition coefficients, the water solubility (which was previously found to be the major determinant of the KOW) is also the major determinant for the Ktw. When the published BCF values (bioconcentration factors) of organic compounds in fish are based on the lipid content rather than on total mass, they are approximately equal to the Ktw, which suggests at least near equilibrium for solute partitioning between water and fish lipid. The close correlation between Ktw and Kow suggests that Kow is also a good predictor for lipid-water partition coefficients and bioconcentration factors.

Partitioning of functional gene expression data using principal points.

PubMed

Kim, Jaehee; Kim, Haseong

2017-10-12

DNA microarrays offer motivation and hope for the simultaneous study of variations in multiple genes. Gene expression is a temporal process that allows variations in expression levels with a characterized gene function over a period of time. Temporal gene expression curves can be treated as functional data since they are considered as independent realizations of a stochastic process. This process requires appropriate models to identify patterns of gene functions. The partitioning of the functional data can find homogeneous subgroups of entities for the massive genes within the inherent biological networks. Therefor it can be a useful technique for the analysis of time-course gene expression data. We propose a new self-consistent partitioning method of functional coefficients for individual expression profiles based on the orthonormal basis system. A principal points based functional partitioning method is proposed for time-course gene expression data. The method explores the relationship between genes using Legendre coefficients as principal points to extract the features of gene functions. Our proposed method provides high connectivity in connectedness after clustering for simulated data and finds a significant subsets of genes with the increased connectivity. Our approach has comparative advantages that fewer coefficients are used from the functional data and self-consistency of principal points for partitioning. As real data applications, we are able to find partitioned genes through the gene expressions found in budding yeast data and Escherichia coli data. The proposed method benefitted from the use of principal points, dimension reduction, and choice of orthogonal basis system as well as provides appropriately connected genes in the resulting subsets. We illustrate our method by applying with each set of cell-cycle-regulated time-course yeast genes and E. coli genes. The proposed method is able to identify highly connected genes and to explore the complex dynamics of biological systems in functional genomics.

Keeping data continuous when analyzing the prognostic impact of a tumor marker: an example with cathepsin D in breast cancer.

PubMed

Bossard, N; Descotes, F; Bremond, A G; Bobin, Y; De Saint Hilaire, P; Golfier, F; Awada, A; Mathevet, P M; Berrerd, L; Barbier, Y; Estève, J

2003-11-01

The prognostic value of cathepsin D has been recently recognized, but as many quantitative tumor markers, its clinical use remains unclear partly because of methodological issues in defining cut-off values. Guidelines have been proposed for analyzing quantitative prognostic factors, underlining the need for keeping data continuous, instead of categorizing them. Flexible approaches, parametric and non-parametric, have been proposed in order to improve the knowledge of the functional form relating a continuous factor to the risk. We studied the prognostic value of cathepsin D in a retrospective hospital cohort of 771 patients with breast cancer, and focused our overall survival analysis, based on the Cox regression, on two flexible approaches: smoothing splines and fractional polynomials. We also determined a cut-off value from the maximum likelihood estimate of a threshold model. These different approaches complemented each other for (1) identifying the functional form relating cathepsin D to the risk, and obtaining a cut-off value and (2) optimizing the adjustment for complex covariate like age at diagnosis in the final multivariate Cox model. We found a significant increase in the death rate, reaching 70% with a doubling of the level of cathepsin D, after the threshold of 37.5 pmol mg(-1). The proper prognostic impact of this marker could be confirmed and a methodology providing appropriate ways to use markers in clinical practice was proposed.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

PubMed Central

2010-01-01

Background Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. Methods We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. Results An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. Conclusions This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples. PMID:20584321

Monkey search algorithm for ECE components partitioning

NASA Astrophysics Data System (ADS)

Kuliev, Elmar; Kureichik, Vladimir; Kureichik, Vladimir, Jr.

2018-05-01

The paper considers one of the important design problems – a partitioning of electronic computer equipment (ECE) components (blocks). It belongs to the NP-hard class of problems and has a combinatorial and logic nature. In the paper, a partitioning problem formulation can be found as a partition of graph into parts. To solve the given problem, the authors suggest using a bioinspired approach based on a monkey search algorithm. Based on the developed software, computational experiments were carried out that show the algorithm efficiency, as well as its recommended settings for obtaining more effective solutions in comparison with a genetic algorithm.

Prognostic value of echocardiographic indices of left atrial morphology and function in dogs with myxomatous mitral valve disease.

PubMed

Baron Toaldo, Marco; Romito, Giovanni; Guglielmini, Carlo; Diana, Alessia; Pelle, Nazzareno G; Contiero, Barbara; Cipone, Mario

2018-05-01

The prognostic relevance of left atrial (LA) morphological and functional variables, including those derived from speckle tracking echocardiography (STE), has been little investigated in veterinary medicine. To assess the prognostic value of several echocardiographic variables, with a focus on LA morphological and functional variables in dogs with myxomatous mitral valve disease (MMVD). One-hundred and fifteen dogs of different breeds with MMVD. Prospective cohort study. Conventional morphologic and echo-Doppler variables, LA areas and volumes, and STE-based LA strain analysis were performed in all dogs. A survival analysis was performed to test for the best echocardiographic predictors of cardiac-related death. Most of the tested variables, including all LA STE-derived variables were univariate predictors of cardiac death in Cox proportional hazard analysis. Because of strong correlation between many variables, only left atrium to aorta ratio (LA/Ao > 1.7), mitral valve E wave velocity (MV E vel > 1.3 m/s), LA maximal volume (LAVmax > 3.53 mL/kg), peak atrial longitudinal strain (PALS < 30%), and contraction strain index (CSI per 1% increase) were entered in the univariate analysis, and all were predictors of cardiac death. However, only the MV E vel (hazard ratio [HR], 4.45; confidence interval [CI], 1.76-11.24; P < .001) and LAVmax (HR, 2.32; CI, 1.10-4.89; P = .024) remained statistically significant in the multivariable analysis. The assessment of LA dimension and function provides useful prognostic information in dogs with MMVD. Considering all the LA variables, LAVmax appears the strongest predictor of cardiac death, being superior to LA/Ao and STE-derived variables. Copyright © 2018 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Prognostic score–based balance measures for propensity score methods in comparative effectiveness research

PubMed Central

Stuart, Elizabeth A.; Lee, Brian K.; Leacy, Finbarr P.

2013-01-01

Objective Examining covariate balance is the prescribed method for determining when propensity score methods are successful at reducing bias. This study assessed the performance of various balance measures, including a proposed balance measure based on the prognostic score (also known as the disease-risk score), to determine which balance measures best correlate with bias in the treatment effect estimate. Study Design and Setting The correlations of multiple common balance measures with bias in the treatment effect estimate produced by weighting by the odds, subclassification on the propensity score, and full matching on the propensity score were calculated. Simulated data were used, based on realistic data settings. Settings included both continuous and binary covariates and continuous covariates only. Results The standardized mean difference in prognostic scores, the mean standardized mean difference, and the mean t-statistic all had high correlations with bias in the effect estimate. Overall, prognostic scores displayed the highest correlations of all the balance measures considered. Prognostic score measure performance was generally not affected by model misspecification and performed well under a variety of scenarios. Conclusion Researchers should consider using prognostic score–based balance measures for assessing the performance of propensity score methods for reducing bias in non-experimental studies. PMID:23849158

Prognostic Role of Phospho-STAT3 in Patients with Cancers of the Digestive System: A Systematic Review and Meta-Analysis.

PubMed

Li, Mu-xing; Bi, Xin-yu; Huang, Zhen; Zhao, Jian-jun; Han, Yue; Li, Zhi-Yu; Zhang, Ye-fan; Li, Yuan; Chen, Xiao; Hu, Xu-hui; Zhao, Hong; Cai, Jian-qiang

2015-01-01

The definite prognostic role of p-STAT3 has not been well defined. We performed a meta-analysis evaluating the prognostic role of p-STAT3 expression in patients with digestive system cancers. We searched the available articles reporting the prognostic value of p-STAT3 in patients with cancers of the digestive system, mainly including colorectal cancer, gastric cancer, hepatocellular carcinoma, esophagus cancer and pancreatic cancer. The pooled hazard ratios (HRs) with 95 % confidence intervals (95 % CIs) of overall survival (OS) and disease-free survival (DFS) were used to assess the prognostic role of p-STAT3 expression level in cancer tissues. And the association between p-STAT3 expression and clinicopathological characteristics was evaluated. A total of 22 studies with 3585 patients were finally enrolled in the meta-analysis. The results showed that elevated p-STAT3 expression level predicted inferior OS (HR = 1.809, 95% CI: 1.442-2.270, P < 0.001) and DFS (HR = 1.481, 95% CI: 1.028-2.133, P = 0.035) in patients with malignant cancers of the digestive system. Increased expression of p-STAT3 is significantly related with tumor cell differentiation (Odds ratio (OR) = 1.895, 95% CI: 1.364-2.632, P < 0.001) and lymph node metastases (OR = 2.108, 95% CI: 1.104-4.024, P = 0.024). Sensitivity analysis suggested that the pooled HR was stable and omitting a single study did not change the significance of the pooled HR. Funnel plots and Egger's tests revealed there was no significant publication bias in the meta-analysis. Phospho-STAT3 might be a prognostic factor of patients with digestive system cancers. More well designed studies with adequate follow-up are needed to gain a thorough understanding of the prognostic role of p-STAT3.

The prognostic value of KRAS mutation by cell-free DNA in cancer patients: A systematic review and meta-analysis.

PubMed

Zhuang, Rongyuan; Li, Song; Li, Qian; Guo, Xi; Shen, Feng; Sun, Hong; Liu, Tianshu

2017-01-01

KRAS mutation has been found in various types of cancer. However, the prognostic value of KRAS mutation in cell-free DNA (cfDNA) in cancer patients was conflicting. In the present study, a meta-analysis was conducted to clarify its prognostic significance. Literature searches of Cochrane Library, EMBASE, PubMed and Web of Science were performed to identify studies related to KRAS mutation detected by cfDNA and survival in cancer patients. Two evaluators reviewed and extracted the information independently. Review Manager 5.3 software was used to perform the statistical analysis. Thirty studies were included in the present meta-analysis. Our analysis showed that KRAS mutation in cfDNA was associated with a poorer survival in cancer patients for overall survival (OS, HR 2.02, 95% CI 1.63-2.51, P<0.01) and progression-free survival (PFS, HR 1.64, 95% CI 1.27-2.13, P<0.01). In subgroup analyses, KRAS mutation in pancreatic cancer, colorectal cancer, non-small cell lung cancer and ovarian epithelial cancer had HRs of 2.81 (95% CI 1.83-4.30, P<0.01), 1.67 (95% CI 1.25-2.42, P<0.01), 1.64 (95% CI 1.13-2.39, P = 0.01) and 2.17 (95% 1.12-4.21, p = 0.02) for OS, respectively. In addition, the ethnicity didn't influence the prognostic value of KRAS mutation in cfDNA in cancer patients (p = 0.39). Prognostic value of KRAS mutation was slightly higher in plasma than in serum (HR 2.13 vs 1.65), but no difference was observed (p = 0.37). Briefly, KRAS mutation in cfDNA was a survival prognostic biomarker in cancer patients. Its prognostic value was different in various types of cancer.

Prognostic significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with stage III and IV colorectal cancer

PubMed Central

Kim, Jae Hyun; Lee, Jun Yeop; Kim, Hae Koo; Lee, Jin Wook; Jung, Sung Gyu; Jung, Kyoungwon; Kim, Sung Eun; Moon, Won; Park, Moo In; Park, Seun Ja

2017-01-01

AIM To evaluate the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in patients with colorectal cancer (CRC). METHODS Between April 1996 and December 2010, medical records from a total of 1868 patients with CRC were retrospectively reviewed. The values of simple inflammatory markers including NLR and PLR in predicting the long-term outcomes of these patients were evaluated using Kaplan-Meier curves and Cox regression models. RESULTS The median follow-up duration was 46 mo (interquartile range, 22-73). The estimation of NLR and PLR was based on the time of diagnosis. In multivariate Cox regression analysis, high NLR (≥ 3.0) and high PLR (≥ 160) were independent risk factors predicting poor long-term outcomes in patients with stage III and IV CRC. However, high NLR and high PLR were not prognostic factors in patients with stage I and II CRC. CONCLUSION In this study, we identified that high NLR (≥ 3.0) and high PLR (≥ 160) are useful prognostic factors to predict long-term outcomes in patients with stage III and IV CRC. PMID:28210087

Prognostic alternative mRNA splicing signature in non-small cell lung cancer.

PubMed

Li, Yuan; Sun, Nan; Lu, Zhiliang; Sun, Shouguo; Huang, Jianbing; Chen, Zhaoli; He, Jie

2017-05-01

Alternative splicing provides a major mechanism to generate protein diversity. Increasing evidence suggests a link of dysregulation of splicing associated with cancer. Genome-wide alternative splicing profiling in lung cancer remains largely unstudied. We generated alternative splicing profiles in 491 lung adenocarcinoma (LUAD) and 471 lung squamous cell carcinoma (LUSC) patients in TCGA using RNA-seq data, prognostic models and splicing networks were built by integrated bioinformatics analysis. A total of 3691 and 2403 alternative splicing events were significantly associated with patient survival in LUAD and LUSC, respectively, including EGFR, CD44, PIK3C3, RRAS2, MAPKAP1 and FGFR2. The area under the curve of the receiver-operator characteristic curve for prognostic predictor in NSCLC was 0.817 at 2000 days of overall survival which were also over 0.8 in LUAD and LUSC, separately. Interestingly, splicing correlation networks uncovered opposite roles of splicing factors in LUAD and LUSC. We created prognostic predictors based on alternative splicing events with high performances for risk stratification in NSCLC patients and uncovered interesting splicing networks in LUAD and LUSC which could be underlying mechanisms. Copyright © 2017 Elsevier B.V. All rights reserved.

Novel pathologic scoring tools predict end-stage kidney disease in light chain (AL) amyloidosis.

PubMed

Rubinstein, Samuel; Cornell, Robert F; Du, Liping; Concepcion, Beatrice; Goodman, Stacey; Harrell, Shelton; Horst, Sara; Lenihan, Daniel; Slosky, David; Fogo, Agnes; Langone, Anthony

2017-09-01

Light chain (AL) amyloidosis frequently involves the kidney, causing significant morbidity and mortality. A pathologic scoring system with prognostic utility has not been developed. We hypothesized that the extent of amyloid deposition and degree of scarring injury on kidney biopsy, could provide prognostic value, and aimed to develop pathologic scoring tools based on these features. This is a case-control study of 39 patients treated for AL amyloidosis with biopsy-proven kidney involvement at a large academic medical center. Our novel scoring tools, composite scarring injury score (CSIS) and amyloid score (AS) were applied to each kidney biopsy. The primary outcome was progression to dialysis-dependent end-stage kidney disease (ESKD) using a 12-month landmark analysis. At 12 months, nine patients had progressed to ESKD. Patients with an AS ≥7.5 had a significantly higher cumulative incidence of ESKD than those with AS <7.5 (p = .04, 95% CI 0.13-0.64). Using a 12-month landmark analysis, AS correlated with progression to ESKD. These data suggest that a kidney biopsy, in addition to providing diagnostic information, can be the basis for a pathologic scoring system with prognostic significance.

Assessing the effects of architectural variations on light partitioning within virtual wheat–pea mixtures

PubMed Central

Barillot, Romain; Escobar-Gutiérrez, Abraham J.; Fournier, Christian; Huynh, Pierre; Combes, Didier

2014-01-01

Background and Aims Predicting light partitioning in crop mixtures is a critical step in improving the productivity of such complex systems, and light interception has been shown to be closely linked to plant architecture. The aim of the present work was to analyse the relationships between plant architecture and light partitioning within wheat–pea (Triticum aestivum–Pisum sativum) mixtures. An existing model for wheat was utilized and a new model for pea morphogenesis was developed. Both models were then used to assess the effects of architectural variations in light partitioning. Methods First, a deterministic model (L-Pea) was developed in order to obtain dynamic reconstructions of pea architecture. The L-Pea model is based on L-systems formalism and consists of modules for ‘vegetative development’ and ‘organ extension’. A tripartite simulator was then built up from pea and wheat models interfaced with a radiative transfer model. Architectural parameters from both plant models, selected on the basis of their contribution to leaf area index (LAI), height and leaf geometry, were then modified in order to generate contrasting architectures of wheat and pea. Key results By scaling down the analysis to the organ level, it could be shown that the number of branches/tillers and length of internodes significantly determined the partitioning of light within mixtures. Temporal relationships between light partitioning and the LAI and height of the different species showed that light capture was mainly related to the architectural traits involved in plant LAI during the early stages of development, and in plant height during the onset of interspecific competition. Conclusions In silico experiments enabled the study of the intrinsic effects of architectural parameters on the partitioning of light in crop mixtures of wheat and pea. The findings show that plant architecture is an important criterion for the identification/breeding of plant ideotypes, particularly with respect to light partitioning. PMID:24907314

Molecular phylogeny of the aquatic beetle family Noteridae (Coleoptera: Adephaga) with an emphasis on data partitioning strategies.

PubMed

Baca, Stephen M; Toussaint, Emmanuel F A; Miller, Kelly B; Short, Andrew E Z

2017-02-01

The first molecular phylogenetic hypothesis for the aquatic beetle family Noteridae is inferred using DNA sequence data from five gene fragments (mitochondrial and nuclear): COI, H3, 16S, 18S, and 28S. Our analysis is the most comprehensive phylogenetic reconstruction of Noteridae to date, and includes 53 species representing all subfamilies, tribes and 16 of the 17 genera within the family. We examine the impact of data partitioning on phylogenetic inference by comparing two different algorithm-based partitioning strategies: one using predefined subsets of the dataset, and another recently introduced method, which uses the k-means algorithm to iteratively divide the dataset into clusters of sites evolving at similar rates across sampled loci. We conducted both maximum likelihood and Bayesian inference analyses using these different partitioning schemes. Resulting trees are strongly incongruent with prior classifications of Noteridae. We recover variant tree topologies and support values among the implemented partitioning schemes. Bayes factors calculated with marginal likelihoods of Bayesian analyses support a priori partitioning over k-means and unpartitioned data strategies. Our study substantiates the importance of data partitioning in phylogenetic inference, and underscores the use of comparative analyses to determine optimal analytical strategies. Our analyses recover Noterini Thomson to be paraphyletic with respect to three other tribes. The genera Suphisellus Crotch and Hydrocanthus Say are also recovered as paraphyletic. Following the results of the preferred partitioning scheme, we here propose a revised classification of Noteridae, comprising two subfamilies, three tribes and 18 genera. The following taxonomic changes are made: Notomicrinae sensu n. (= Phreatodytinae syn. n.) is expanded to include the tribe Phreatodytini; Noterini sensu n. (= Neohydrocoptini syn. n., Pronoterini syn. n., Tonerini syn. n.) is expanded to include all genera of the Noterinae; The genus Suphisellus Crotch is expanded to include species of Pronoterus Sharp syn. n.; and the former subgenus Sternocanthus Guignot stat. rev. is resurrected from synonymy and elevated to genus rank. Copyright © 2016 Elsevier Inc. All rights reserved.

Accelerated Aging in Electrolytic Capacitors for Prognostics

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan; Saha, Sankalita; Biswas, Gautam; Goebel, Kai Frank

2012-01-01

The focus of this work is the analysis of different degradation phenomena based on thermal overstress and electrical overstress accelerated aging systems and the use of accelerated aging techniques for prognostics algorithm development. Results on thermal overstress and electrical overstress experiments are presented. In addition, preliminary results toward the development of physics-based degradation models are presented focusing on the electrolyte evaporation failure mechanism. An empirical degradation model based on percentage capacitance loss under electrical overstress is presented and used in: (i) a Bayesian-based implementation of model-based prognostics using a discrete Kalman filter for health state estimation, and (ii) a dynamic system representation of the degradation model for forecasting and remaining useful life (RUL) estimation. A leave-one-out validation methodology is used to assess the validity of the methodology under the small sample size constrain. The results observed on the RUL estimation are consistent through the validation tests comparing relative accuracy and prediction error. It has been observed that the inaccuracy of the model to represent the change in degradation behavior observed at the end of the test data is consistent throughout the validation tests, indicating the need of a more detailed degradation model or the use of an algorithm that could estimate model parameters on-line. Based on the observed degradation process under different stress intensity with rest periods, the need for more sophisticated degradation models is further supported. The current degradation model does not represent the capacitance recovery over rest periods following an accelerated aging stress period.

Prognostic significance of SRSF2 mutations in myelodysplastic syndromes and chronic myelomonocytic leukemia: a meta-analysis.

PubMed

Arbab Jafari, Pourya; Ayatollahi, Hossein; Sadeghi, Ramin; Sheikhi, Maryam; Asghari, Amir

2018-05-14

Serine/arginine-rich splicing factor 2 (SRSF2) mutations were detected frequently in myelodysplastic syndrome (MDS) and chronic myelomonocytic leukemia (CMML) patients. However, its prognostic value has not yet been fully clarified. In this meta-analysis, Hazard Ratio (HR) and 95% confidence interval (CI) for overall-survival (OS) were chosen to evaluate the prognostic impact of SRSF2 mutations and to compare SRSF2 mutations to those with wild-type. A total of 2056 patients from 12 studies were obtained. The pooled HRs for OSsuggested that patients with MDS had a poorer prognosis (HR = 1.780, 95% CI (1.410-2.249)), while analysis on SRSF2 mutations revealed no significant effect on the prognosis of CMML patients (HR = 1.091, 95% CI (0.925-1.286)). The frequency of SRSF2 mutations was found to be 11.5% and 39.8% in patients with MDS and CMML, respectively. This meta-analysis suggests that SRSF2 has a poor prognosis in patients with MDS, but no prognosis impact on patients with CMML. In conclusion, SRSF2 mutations were significantly related to the shorter OS in patients with MDS which may consider as an adverse prognostic risk factor. Whereas, analysis did not show any prognostic effect on OS of CMML patients with SRSF2 mutations.

EXPLORING FUNCTIONAL CONNECTIVITY IN FMRI VIA CLUSTERING.

PubMed

Venkataraman, Archana; Van Dijk, Koene R A; Buckner, Randy L; Golland, Polina

2009-04-01

In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering algorithms as alternatives to the commonly used Seed-Based Analysis. To enable clustering of the entire brain volume, we use the Nyström Method to approximate the necessary spectral decompositions. We apply K-Means, Spectral Clustering and Seed-Based Analysis to resting-state fMRI data collected from 45 healthy young adults. Without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via Seed-Based Analysis. Our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.

Hot Spot and Whole-Tumor Enumeration of CD8+ Tumor-Infiltrating Lymphocytes Utilizing Digital Image Analysis Is Prognostic in Triple-Negative Breast Cancer.

PubMed

McIntire, Patrick J; Irshaid, Lina; Liu, Yifang; Chen, Zhengming; Menken, Faith; Nowak, Eugene; Shin, Sandra J; Ginter, Paula S

2018-05-07

CD8 + tumor-infiltrating lymphocytes (TILs) have emerged as a prognostic indicator in triple-negative breast cancer (TNBC). There is debate surrounding the prognostic value of hot spots for CD8 + TIL enumeration. We compared hot spot versus whole-tumor CD8 + TIL enumeration in prognosticating TNBC using immunohistochemistry on whole tissue sections and quantification by digital image analysis (Halo imaging analysis software; Indica Labs, Corrales, NM). A wide range of clinically relevant hot spot sizes was evaluated. CD8 + TIL enumeration was independently statistically significant for all hot spot sizes and whole-tumor annotations for disease-free survival by multivariate analysis. A 10× objective (2.2 mm diameter) hot spot was found to correlate significantly with overall survival (P = .04), while the remaining hot spots and whole-tumor CD8 + TIL enumeration did not (P > .05). Statistical significance was not demonstrated when comparing between hot spots and whole-tumor annotations, as the groups had overlapping confidence intervals. CD8 + TIL hot spot enumeration is equivalent to whole-tumor enumeration for prognostication in TNBC and may serve as a good alternative methodology in future studies and clinical practice. Copyright © 2018 Elsevier Inc. All rights reserved.

Compressible fluids with Maxwell-type equations, the minimal coupling with electromagnetic field and the Stefan–Boltzmann law

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendes, Albert C.R., E-mail: albert@fisica.ufjf.br; Takakura, Flavio I., E-mail: takakura@fisica.ufjf.br; Abreu, Everton M.C., E-mail: evertonabreu@ufrrj.br

In this work we have obtained a higher-derivative Lagrangian for a charged fluid coupled with the electromagnetic fluid and the Dirac’s constraints analysis was discussed. A set of first-class constraints fixed by noncovariant gauge condition were obtained. The path integral formalism was used to obtain the partition function for the corresponding higher-derivative Hamiltonian and the Faddeev–Popov ansatz was used to construct an effective Lagrangian. Through the partition function, a Stefan–Boltzmann type law was obtained. - Highlights: • Higher-derivative Lagrangian for a charged fluid. • Electromagnetic coupling and Dirac’s constraint analysis. • Partition function through path integral formalism. • Stefan–Boltzmann-kind lawmore » through the partition function.« less

New Linear Partitioning Models Based on Experimental Water: Supercritical CO2 Partitioning Data of Selected Organic Compounds.

PubMed

Burant, Aniela; Thompson, Christopher; Lowry, Gregory V; Karamalidis, Athanasios K

2016-05-17

Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch-reactor system with dual spectroscopic detectors: a near-infrared spectrometer for measuring the organic analyte in the CO2 phase and a UV detector for quantifying the analyte in the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly parameter linear free-energy relationship and to develop five new linear free-energy relationships for predicting water-sc-CO2 partitioning coefficients. A total of four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than does the model built for the entire data set.

New Linear Partitioning Models Based on Experimental Water: Supercritical CO 2 Partitioning Data of Selected Organic Compounds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burant, Aniela; Thompson, Christopher; Lowry, Gregory V.

2016-05-17

Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch reactor system with dual spectroscopic detectors: a near infrared spectrometer for measuring the organic analyte in the CO2 phase, and a UV detector for quantifying the analyte inmore » the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly-parameter linear free energy relationship and to develop five new linear free energy relationships for predicting water-sc-CO2 partitioning coefficients. Four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than the model built for the entire dataset.« less

Positive matrix factorization of PM2.5 - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

PubMed

Xie, M; Barsanti, K C; Hannigan, M P; Dutton, S J; Vedal, S

2013-01-01

Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in n alkanes, fluoranthene in PAHs) had higher total concentrations (gas + particle phase) and lower particle-phase fractions. The total SVOC concentrations were analyzed using positive matrix factorization (PMF). Then the results were compared with source apportionment results where only particle-phase SVOC concentrations were used (particle only-based study; Xie et al., 2013). For the particle only-based PMF analysis, the factors primarily associated with primary or secondary sources ( n alkane, EC/sterane and inorganic ion factors) exhibit similar contribution time series ( r = 0.92-0.98) with their corresponding factors ( n alkane, sterane and nitrate+sulfate factors) in the current work. Three other factors (light n alkane/PAH, PAH and summer/odd n alkane factors) are linked with pollution sources influenced by atmospheric processes (e.g. G/P partitioning, photochemical reaction), and were less correlated ( r = 0.69-0.84) with their corresponding factors (light SVOC, PAH and bulk carbon factors) in the current work, suggesting that the source apportionment results derived from particle-only SVOC data could be affected by atmospheric processes. PMF analysis was also performed on three temperature-stratified subsets of the total SVOC data, representing ambient sampling during cold (daily average temperature < 10 °C), warm (≥ 10 °C and ≤ 20 °C) and hot (> 20 °C) periods. Unlike the particle only-based study, in this work the factor characterized by the low molecular weight (MW) compounds (light SVOC factor) exhibited strong correlations ( r = 0.82-0.98) between the full data set and each sub-data set solution, indicating that the impacts of G/P partitioning on receptor-based source apportionment could be eliminated by using total SVOC concentrations.

Survival analysis of platinum-refractory patients with advanced esophageal cancer treated with docetaxel or best supportive care alone: a retrospective study.

PubMed

Moriwaki, T; Kajiwara, T; Matsumoto, T; Suzuki, H; Hiroshima, Y; Matsuda, K; Hirai, S; Yamamoto, Y; Yamada, T; Sugaya, A; Kobayashi, M; Endo, S; Ishige, K; Nishina, T; Hyodo, I

2014-01-01

The survival benefit of second-line chemotherapy with docetaxel in platinum-refractory patients with advanced esophageal cancer (AEC) remains unclear. A retrospective analysis of AEC patients with Eastern Cooperative Oncology Group performance status (PS)≤2 was performed, and major organ functions were preserved, who determined to receive docetaxel or best supportive care (BSC) alone after failure of platinum-based chemotherapy. The post-progression survival (PPS), defined as survival time after disease progression following platinum-based chemotherapy, was analyzed by multivariate Cox regression analysis using factors identified as significant in univariate analysis of various 20 characteristics (age, sex, PS, primary tumor location, etc) including Glasgow prognostic score (GPS), which is a well-known prognostic factor in many malignant tumors. Sixty-six and 45 patients were determined to receive docetaxel and BSC between January 2007 and December 2011, respectively. The median PPS was 5.4 months (95% confidence interval [CI] 4.8-6.0) in the docetaxel group and 3.3 months (95% CI 2.5-4.0) in the BSC group (hazard ratio [HR] 0.56, 95% CI 0.38-0.84, P=0.005). Univariate analysis revealed six significant factors: treatment, PS, GPS, number of metastatic organs, liver metastasis, and bone metastasis. Multivariate analysis including these significant factors revealed three independent prognostic factors: docetaxel treatment (HR 0.62, 95% CI 0.39-0.99, P=0.043), better GPS (HR 0.61, 95% CI 0.46-0.81, P=0.001), and no bone metastasis (HR 0.31, 95% CI 0.15-0.68, P=0.003). There was a trend for PPS in favor of the docetaxel group compared with patients who refused docetaxel treatment in the BSC group (adjusted HR 0.61, 95% CI 0.29-1.29, P=0.20). Docetaxel treatment may have prolonged survival in platinum-refractory patients with AEC. © 2014 International Society for Diseases of the Esophagus.

An Integrated Prognostic Classifier for Stage I Lung Adenocarcinoma based on mRNA, microRNA and DNA Methylation Biomarkers

PubMed Central

Robles, Ana I.; Arai, Eri; Mathé, Ewy A.; Okayama, Hirokazu; Schetter, Aaron J.; Brown, Derek; Petersen, David; Bowman, Elise D.; Noro, Rintaro; Welsh, Judith A.; Edelman, Daniel C.; Stevenson, Holly S.; Wang, Yonghong; Tsuchiya, Naoto; Kohno, Takashi; Skaug, Vidar; Mollerup, Steen; Haugen, Aage; Meltzer, Paul S.; Yokota, Jun; Kanai, Yae

2015-01-01

Introduction Up to 30% Stage I lung cancer patients suffer recurrence within 5 years of curative surgery. We sought to improve existing protein-coding gene and microRNA expression prognostic classifiers by incorporating epigenetic biomarkers. Methods Genome-wide screening of DNA methylation and pyrosequencing analysis of HOXA9 promoter methylation were performed in two independently collected cohorts of Stage I lung adenocarcinoma. The prognostic value of HOXA9 promoter methylation alone and in combination with mRNA and miRNA biomarkers was assessed by Cox regression and Kaplan-Meier survival analysis in both cohorts. Results Promoters of genes marked by Polycomb in Embryonic Stem Cells were methylated de novo in tumors and identified patients with poor prognosis. The HOXA9 locus was methylated de novo in Stage I tumors (P < 0.0005). High HOXA9 promoter methylation was associated with worse cancer-specific survival (Hazard Ratio [HR], 2.6; P = 0.02) and recurrence-free survival (HR, 3.0; P = 0.01), and identified high-risk patients in stratified analysis of Stage IA and IB. Four protein-coding gene (XPO1, BRCA1, HIF1α, DLC1), miR-21 expression and HOXA9 promoter methylation were each independently associated with outcome (HR, 2.8; P = 0.002; HR, 2.3; P = 0.01; and HR, 2.4; P = 0.005, respectively), and, when combined, identified high-risk, therapy naïve, Stage I patients (HR, 10.2; P = 3x10−5). All associations were confirmed in two independently collected cohorts. Conclusion A prognostic classifier comprising three types of genomic and epigenomic data may help guide the postoperative management of Stage I lung cancer patients at high risk of recurrence. PMID:26134223

Genomic and protein expression profiling identifies CDK6 as novel independent prognostic marker in medulloblastoma.

PubMed

Mendrzyk, Frank; Radlwimmer, Bernhard; Joos, Stefan; Kokocinski, Felix; Benner, Axel; Stange, Daniel E; Neben, Kai; Fiegler, Heike; Carter, Nigel P; Reifenberger, Guido; Korshunov, Andrey; Lichter, Peter

2005-12-01

Medulloblastoma is the most common malignant brain tumor in children. Despite multimodal aggressive treatment, nearly half of the patients die as a result of this tumor. Identification of molecular markers for prognosis and development of novel pathogenesis-based therapies depends crucially on a better understanding of medulloblastoma pathomechanisms. We performed genome-wide analysis of DNA copy number imbalances in 47 medulloblastomas using comparative genomic hybridization to large insert DNA microarrays (matrix-CGH). The expression of selected candidate genes identified by matrix-CGH was analyzed immunohistochemically on tissue microarrays representing medulloblastomas from 189 clinically well-documented patients. To identify novel prognostic markers, genomic findings and protein expression data were correlated to patient survival. Matrix-CGH analysis revealed frequent DNA copy number alterations of several novel candidate regions. Among these, gains at 17q23.2-qter (P < .01) and losses at 17p13.1 to 17p13.3 (P = .04) were significantly correlated to poor prognosis. Within 17q23.2-qter and 7q21.2, two of the most frequently gained chromosomal regions, confined amplicons were identified that contained the PPM1D and CDK6 genes, respectively. Immunohistochemistry revealed strong expression of PPM1D in 148 (88%) of 168 and CDK6 in 50 (30%) of 169 medulloblastomas. Overexpression of CDK6 correlated significantly with poor prognosis (P < .01) and represented an independent prognostic marker of overall survival on multivariate analysis (P = .02). We identified CDK6 as a novel molecular marker that can be determined by immunohistochemistry on routinely processed tissue specimens and may facilitate the prognostic assessment of medulloblastoma patients. Furthermore, increased protein-levels of PPM1D and CDK6 may link the TP53 and RB1 tumor suppressor pathways to medulloblastoma pathomechanisms.

Developing QSPR model of gas/particle partition coefficients of neutral poly-/perfluoroalkyl substances

NASA Astrophysics Data System (ADS)

Yuan, Quan; Ma, Guangcai; Xu, Ting; Serge, Bakire; Yu, Haiying; Chen, Jianrong; Lin, Hongjun

2016-10-01

Poly-/perfluoroalkyl substances (PFASs) are a class of synthetic fluorinated organic substances that raise increasing concern because of their environmental persistence, bioaccumulation and widespread presence in various environment media and organisms. PFASs can be released into the atmosphere through both direct and indirect sources, and the gas/particle partition coefficient (KP) is an important parameter that helps us to understand their atmospheric behavior. In this study, we developed a temperature-dependent predictive model for log KP of PFASs and analyzed the molecular mechanism that governs their partitioning equilibrium between gas phase and particle phase. All theoretical computation was carried out at B3LYP/6-31G (d, p) level based on neutral molecular structures by Gaussian 09 program package. The regression model has a good statistical performance and robustness. The application domain has also been defined according to OECD guidance. The mechanism analysis shows that electrostatic interaction and dispersion interaction play the most important role in the partitioning equilibrium. The developed model can be used to predict log KP values of neutral fluorotelomer alcohols and perfluor sulfonamides/sulfonamidoethanols with different substitutions at nitrogen atoms, providing basic data for their ecological risk assessment.

On factors structuring the flatfish assemblage in the southern North Sea

NASA Astrophysics Data System (ADS)

Piet, G. J.; Pfisterer, A. B.; Rijnsdorp, A. D.

1998-09-01

Ten species of flatfish were studied to see to what extent interspecific competition influences their diet or spatial distribution and whether the potential of these flatfish species to avoid interspecific competition through resource partitioning is constrained by specific morphological characteristics. For this, seven morphological characteristics were measured, diet composition was determined from gut content analyses and overlap in distribution was determined from the co-occurrence in trawl hauls. Canonical correspondence analysis revealed the morphological characteristics that were most strongly correlated with the diet composition. Based on these findings the mouth gape was considered to be the most important morphological constraint affecting the choice of food. Two resource dimensions were distinguished along which interspecific competition can act on the flatfish assemblage: the trophic dimension (diet composition) and the spatial dimension (distribution). Resource partitioning was observed along both dimensions separately and, more importantly, the degree of resource partitioning along the two dimensions was negatively correlated. Especially the latter was considered strong circumstantial evidence that interspecific competition is a major factor structuring the flatfish assemblage. Resource partitioning along the two resource dimensions increased with decreasing mouth gape, suggesting that interspecific competition mainly acts on the small-mouthed fish, i.e. juveniles.

Trophic niche partitioning of littoral fish species from the rocky intertidal of Helgoland, Germany

NASA Astrophysics Data System (ADS)

Hielscher, N. N.; Malzahn, A. M.; Diekmann, R.; Aberle, N.

2015-12-01

During a 3-year field study, interspecific and interannual differences in the trophic ecology of littoral fish species were investigated in the rocky intertidal of Helgoland island (North Sea). We investigated trophic niche partitioning of common coexisting littoral fish species based on a multi-tracer approach using stable isotope and fatty acids in order to show differences and similarities in resource use and feeding modes. The results of the dual-tracer approach showed clear trophic niche partitioning of the five target fish species, the goldsinny wrasse Ctenolabrus rupestris, the sand goby Pomatoschistus minutus, the painted goby Pomatoschistus pictus, the short-spined sea scorpion Myoxocephalus scorpius and the long-spined sea scorpion Taurulus bubalis. Both stable isotopes and fatty acids showed distinct differences in the trophic ecology of the studied fish species. However, the combined use of the two techniques added an additional resolution on the interannual scale. The sand goby P. minutus showed the largest trophic plasticity with a pronounced variability between years. The present data analysis provides valuable information on trophic niche partitioning of fish species in the littoral zones of Helgoland and on complex benthic food webs in general.

Prognostic role of tumor-infiltrating lymphocytes in gastric cancer: a meta-analysis

PubMed Central

Shao, Yingjie; Xu, Bin; Chen, Lujun; Zhou, Qi; Hu, Wenwei; Zhang, Dachuan; Wu, Changping; Tao, Min; Zhu, Yibei; Jiang, Jingting

2017-01-01

Background In patients with gastric cancer, the prognostic value of tumor-infiltrating lymphocytes (TILs) is still controversial. A meta-analysis was performed to evaluate the prognostic value of TILs in gastric cancer. Materials and methods We identify studies from PubMed, Embase and the Cochrane Library to assess the prognostic effect of TILs in patients with gastric cancer. Fixed-effects models or random-effects models were used estimate the pooled hazard ratios (HRs) for overall survival (OS) and disease-free survival (DFS), which depend on the heterogeneity. Results A total of 31 observational studies including 4,185 patients were enrolled. For TILs subsets, the amount of CD8+, FOXP3+, CD3+, CD57+, CD20+, CD45RO+, Granzyme B+ and T-bet+ lymphocytes was significantly associated with improved survival (P < 0.05); moreover, the amount of CD3+ TILs in intra-tumoral compartment (IT) was the most significant prognostic marker (pooled HR = 0.52; 95% CI = 0.43–0.63; P < 0.001). However, CD4+ TILs was not statistically associated with patients’ survival. FOXP3+ TILs showed bidirectional prognostic roles which had positive effect in IT (pooled HR = 1.57; 95% CI = 1.04–2.37; P = 0.033) and negative effect in extra-tumoral compartment (ET) (pooled HR = 0.76; 95% CI = 0.60–0.96; P = 0.022). Conclusions This meta-analysis suggests that some TIL subsets could serve as prognostic biomarkers in gastric cancer. High-quality randomized controlled trials are needed to decide if these TILs could serve as targets for immunotherapy in gastric cancer. PMID:28915679

Cell-Free DNA in Metastatic Colorectal Cancer: A Systematic Review and Meta-Analysis.

PubMed

Spindler, Karen-Lise G; Boysen, Anders K; Pallisgård, Niels; Johansen, Julia S; Tabernero, Josep; Sørensen, Morten M; Jensen, Benny V; Hansen, Torben F; Sefrioui, David; Andersen, Rikke F; Brandslund, Ivan; Jakobsen, Anders

2017-09-01

Circulating DNA can be detected and quantified in the blood of cancer patients and used for detection of tumor-specific genetic alterations. The clinical utility has been intensively investigated for the past 10 years. The majority of reports focus on analyzing the clinical potential of tumor-specific mutations, whereas the use of total cell-free DNA (cfDNA) quantification is somehow controversial and sparsely described in the literature, but holds important clinical information in itself. The purpose of the present report was to present a systematic review and meta-analysis of the prognostic value of total cfDNA in patients with metastatic colorectal cancer (mCRC) treated with chemotherapy. In addition, we report on the overall performance of cfDNA as source for KRAS mutation detection. A systematic literature search of PubMed and Embase was performed by two independent investigators. Eligibility criteria were (a) total cfDNA analysis, (b) mCRC, and (c) prognostic value during palliative treatment. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were followed, and meta-analysis applied on both aggregate data extraction and individual patients' data. Ten eligible cohorts were identified, including a total of 1,076 patients. Seven studies used quantitative polymerase chain reaction methods, two BEAMing [beads, emulsification, amplification, and magnetics] technology, and one study digital droplet polymerase chain reaction. The baseline levels of cfDNA was similar in the presented studies, and all studies reported a clear prognostic value in favor of patients with lowest levels of baseline cfDNA. A meta-analysis revealed a combined estimate of favorable overall survival hazard ratio (HR) in patients with levels below the median cfDNA (HR = 2.39, 95% confidence interval 2.03-2.82, p  < .0001). The total cfDNA levels are high in patients with mCRC and bear strong prognostic information, which should be tested prospectively by using a predefined cut-off value based on normal values in healthy cohorts. Finally, the potential use of cfDNA for detection of tumor-specific mutations was emphasized in a large individual patients' data meta-analysis. Reliable prognostic markers could help to guide patients and treating physicians regarding the relevance and choice of systemic therapy. Small fragments of circulating cell-free DNA (cfDNA) can be measured in a simple blood sample. This report presents the first meta-analysis of the prognostic value of total cfDNA measurement in patients with metastatic colorectal cancer. Data from 1,076 patients confirmed that patients with the lowest pre-treatment levels of cfDNA had a significantly higher chance of longer survival than those with higher levels. Cell-free DNA analysis can also be used for detection of tumor-specific mutations, and hold potential as a valuable tool in colorectal cancer treatment. © AlphaMed Press 2017.

Diagnosis-Specific Prognostic Factors, Indexes, and Treatment Outcomes for Patients With Newly Diagnosed Brain Metastases: A Multi-Institutional Analysis of 4,259 Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sperduto, Paul W., E-mail: psperduto@mropa.co; Chao, Samuel T.; Sneed, Penny K.

2010-07-01

Purpose: Controversy endures regarding the optimal treatment of patients with brain metastases (BMs). Debate persists, despite many randomized trials, perhaps because BM patients are a heterogeneous population. The purpose of the present study was to identify significant diagnosis-specific prognostic factors and indexes (Diagnosis-Specific Graded Prognostic Assessment [DS-GPA]). Methods and Materials: A retrospective database of 5,067 patients treated for BMs between 1985 and 2007 was generated from 11 institutions. After exclusion of the patients with recurrent BMs or incomplete data, 4,259 patients with newly diagnosed BMs remained eligible for analysis. Univariate and multivariate analyses of the prognostic factors and outcomes bymore » primary site and treatment were performed. The significant prognostic factors were determined and used to define the DS-GPA prognostic indexes. The DS-GPA scores were calculated and correlated with the outcomes, stratified by diagnosis and treatment. Results: The significant prognostic factors varied by diagnosis. For non-small-cell lung cancer and small-cell lung cancer, the significant prognostic factors were Karnofsky performance status, age, presence of extracranial metastases, and number of BMs, confirming the original GPA for these diagnoses. For melanoma and renal cell cancer, the significant prognostic factors were Karnofsky performance status and the number of BMs. For breast and gastrointestinal cancer, the only significant prognostic factor was the Karnofsky performance status. Two new DS-GPA indexes were thus designed for breast/gastrointestinal cancer and melanoma/renal cell carcinoma. The median survival by GPA score, diagnosis, and treatment were determined. Conclusion: The prognostic factors for BM patients varied by diagnosis. The original GPA was confirmed for non-small-cell lung cancer and small-cell lung cancer. New DS-GPA indexes were determined for other histologic types and correlated with the outcome, and statistical separation between the groups was confirmed. These data should be considered in the design of future randomized trials and in clinical decision-making.« less

A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose; Kulkarni, Chetan; Biswas, Gautam; Saha, Sankalita; Goebel, Kai

2011-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Towards A Model-Based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan S.; Biswas, Gautam; Goebel, Kai

2012-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Prognostic Implications of Monosomies in Patients With Multiple Myeloma.

PubMed

Shin, Sang-Yong; Eom, Hyeon-Seok; Sohn, Ji Yeon; Lee, Hyewon; Park, Boram; Joo, Jungnam; Jang, Ja-Hyun; Lee, Mi-Na; Kim, Jung Kwon; Kong, Sun-Young

2017-03-01

Cytogenetic analysis aides in risk stratification for patients with multiple myeloma (MM). Although several cytogenetic aberrations have been reported to be prognostic, less is known about the association between the presence of monosomies and prognosis. The present study evaluated the prevalence and prognostic implications of monosomies in patients with MM. Karyotypes were determined using conventional cytogenetics and fluorescence in situ hybridization (FISH). The prognostic effect of monosomies was evaluated by comparison with the clinical factors in MM patients with normal karyotypes. Karyotypes were successfully determined in 167 of the 170 patients with MM. Of these 167 patients, 52 (31.1%) had abnormal karyotypes. Univariable analyses showed that a normal karyotype, hypodiploidy, monosomies of chromosomes 13 and 16, deletion or monosomy of 13q14, and loss of X detected by metaphase analysis were each associated with reduced progression-free survival (P < .05 for each). Univariable analyses showed that a normal karyotype, hypodiploidy, monosomies of chromosomes 13 and 16, deletion or monosomy of 13q14 detected by metaphase analysis and FISH-determined RB1 (13q)/TP53 (17p) deletion were each associated with reduced overall survival (P < .05 for each). Multivariable analysis showed that hypodiploidy detected by metaphase analysis was independently prognostic of shorter progression-free survival (P < .05 for each) and that hypodiploidy, monosomy 16, and loss of Y chromosome and FISH-determined TP53 (17p) deletion were associated with reduced overall survival (P < .05 for each). In addition to known cytogenetic abnormalities, such as monosomy 13, hypodiploidy, and TP53 (17p) deletion, monosomy 16 and loss of the Y chromosome have adverse prognostic implications in patients with MM. Copyright © 2016 Elsevier Inc. All rights reserved.

Transitions in Prognostic Awareness Among Terminally Ill Cancer Patients in Their Last 6 Months of Life Examined by Multi-State Markov Modeling.

PubMed

Hsiu Chen, Chen; Wen, Fur-Hsing; Hou, Ming-Mo; Hsieh, Chia-Hsun; Chou, Wen-Chi; Chen, Jen-Shi; Chang, Wen-Cheng; Tang, Siew Tzuh

2017-09-01

Developing accurate prognostic awareness, a cornerstone of preference-based end-of-life (EOL) care decision-making, is a dynamic process involving more prognostic-awareness states than knowing or not knowing. Understanding the transition probabilities and time spent in each prognostic-awareness state can help clinicians identify trigger points for facilitating transitions toward accurate prognostic awareness. We examined transition probabilities in distinct prognostic-awareness states between consecutive time points in 247 cancer patients' last 6 months and estimated the time spent in each state. Prognostic awareness was categorized into four states: (a) unknown and not wanting to know, state 1; (b) unknown but wanting to know, state 2; (c) inaccurate awareness, state 3; and (d) accurate awareness, state 4. Transitional probabilities were examined by multistate Markov modeling. Initially, 59.5% of patients had accurate prognostic awareness, whereas the probabilities of being in states 1-3 were 8.1%, 17.4%, and 15.0%, respectively. Patients' prognostic awareness generally remained unchanged (probabilities of remaining in the same state: 45.5%-92.9%). If prognostic awareness changed, it tended to shift toward higher prognostic-awareness states (probabilities of shifting to state 4 were 23.2%-36.6% for patients initially in states 1-3, followed by probabilities of shifting to state 3 for those in states 1 and 2 [9.8%-10.1%]). Patients were estimated to spend 1.29, 0.42, 0.68, and 3.61 months in states 1-4, respectively, in their last 6 months. Terminally ill cancer patients' prognostic awareness generally remained unchanged, with a tendency to become more aware of their prognosis. Health care professionals should facilitate patients' transitions toward accurate prognostic awareness in a timely manner to promote preference-based EOL decisions. Terminally ill Taiwanese cancer patients' prognostic awareness generally remained stable, with a tendency toward developing higher states of awareness. Health care professionals should appropriately assess patients' readiness for prognostic information and respect patients' reluctance to confront their poor prognosis if they are not ready to know, but sensitively coach them to cultivate their accurate prognostic awareness, provide desired and understandable prognostic information for those who are ready to know, and give direct and honest prognostic information to clarify any misunderstandings for those with inaccurate awareness, thus ensuring that they develop accurate and realistic prognostic knowledge in time to make end-of-life care decisions. © AlphaMed Press 2017.

Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data

PubMed Central

Goldstein, Theodore; Paull, Evan O.; Ellis, Matthew J.; Stuart, Joshua M.

2013-01-01

High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes. How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care – which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the “activitome,” help connect genomic events to clinical factors in order to predict the drivers of poor outcome. PMID:23430023

Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Sankararaman, Shankar

2013-01-01

Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

Does tumor size have its prognostic role in colorectal cancer? Re-evaluating its value in colorectal adenocarcinoma with different macroscopic growth pattern.

PubMed

Dai, Weixing; Li, Yaqi; Meng, Xianke; Cai, Sanjun; Li, Qingguo; Cai, Guoxiang

2017-09-01

Few previous studies have taken the growth pattern into consideration when analyzing the prognostic value of tumor size in colorectal cancer (CRC). We sought to reveal the prognostic role of tumor size in different macroscopic growth patterns of CRC. Using Cancer Center datasets, we identified 4057 cases with colorectal adenocarcinoma treated with curative resection. Macroscopic growth patterns of tumors were classified into three types: infiltrative, ulcerative and expansive types based on tumor gross appearance. Univariate and multivariate Cox regression analyses were performed to evaluate the prognostic factors for overall survival (OS) and disease-free survival (DFS). In whole cohort, tumor size was an independent factor for OS (HR 1.10, 95%CI 1.04-1.16, p < 0.001). Subgroup analysis based on macroscopic growth pattern suggested that tumor size was an independent factor for OS both in the infiltrative (HR 1.37, 95%CI 1.12-1.66, p = 0.002) group and ulcerative group (HR 1.08, 95%CI 1.00-1.16, p = 0.044) and tumor size (HR 1.22, 95%CI 1.06-1.40, p = 0.004) was found as an independent factor for DFS only in infiltrative group. Tumor size is an independent factor for OS and DFS in patients with colorectal adenocarcinoma of infiltrative type, while only for OS in patients of ulcerative type. Copyright © 2017. Published by Elsevier Ltd.

Serum lactate dehydrogenase with a systemic inflammation score is useful for predicting response and survival in patients with newly diagnosed diffuse large B-cell lymphoma.

PubMed

Jung, Sung-Hoon; Yang, Deok-Hwan; Ahn, Jae-Sook; Kim, Yeo-Kyeoung; Kim, Hyeoung-Joon; Lee, Je-Jung

2015-01-01

We evaluated the relationship between serum lactate dehydrogenase (LDH) level with systemic inflammation score and survival in 213 patients with diffuse large B-cell lymphoma (DLBCL) receiving R-CHOP chemotherapy. The patients were classified into 3 groups based on LDH with the Glasgow Prognostic Score (L-GPS). A score of 2 was assigned to patients with elevated C-reactive protein, hypoalbuminemia and elevated LDH, a score of 1 to those with one or two abnormalities and a score of 0 to those with no abnormality. In multivariate analysis, independent poor prognostic factors for progression-free survival were L-GPS 2 [hazard ratio (HR) 5.415, p = 0.001], Eastern Cooperative Oncology Group performance status (ECOG PS) ≥2 (HR 3.504, p = 0.001) and bulky lesion (HR 2.030, p = 0.039). Independent poor prognostic factors for overall survival were L-GPS 2 (HR 5.898, p = 0.001) and ECOG PS ≥2 (HR 3.525, p = 0.001). The overall response rate for the R-CHOP chemotherapy decreased according to the L-GPS; it was 96.7% at L-GPS 0, 87% at L-GPS 1 and 75% at L-GPS 2 (p = 0.009). L-GPS based on systemic inflammatory indicators may be a useful clinical prognostic indicator for survival, and predicts the response for R-CHOP chemotherapy in patients with newly diagnosed DLBCL. © 2014 S. Karger AG, Basel.

A novel prognostic six-CpG signature in glioblastomas.

PubMed

Yin, An-An; Lu, Nan; Etcheverry, Amandine; Aubry, Marc; Barnholtz-Sloan, Jill; Zhang, Lu-Hua; Mosser, Jean; Zhang, Wei; Zhang, Xiang; Liu, Yu-He; He, Ya-Long

2018-03-01

We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM). A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation. An integrative analysis of multidimensional TCGA data was performed to molecularly characterize different risk tumors. The six-CpG risk-score signature robustly predicted overall survival (OS) in all discovery and validation cohorts and in a treatment-independent manner. It also predicted progression-free survival (PFS) in available patients. The multimarker epigenetic signature was demonstrated as an independent prognosticator and had better performance than known molecular indicators such as glioma-CpG island methylator phenotype (G-CIMP) and proneural subtype. The defined risk subgroups were molecularly distinct; high-risk tumors were biologically more aggressive with concordant activation of proangiogenic signaling at multimolecular levels. Accordingly, we observed better OS benefits of bevacizumab-contained therapy to high-risk patients in independent sets, supporting its implication in guiding usage of antiangiogenic therapy. Finally, the six-CpG signature refined the risk classification based on G-CIMP and MGMT methylation status. The novel six-CpG signature is a robust and independent prognostic indicator for GBMs and is of promising value to improve personalized management. © 2018 John Wiley & Sons Ltd.

Abbreviation of the Follow-Up NIH Stroke Scale Using Factor Analysis

PubMed Central

Raza, Syed Ali; Frankel, Michael R.; Rangaraju, Srikant

2017-01-01

Background The NIH Stroke Scale (NIHSS) is a 15-item measure of stroke-related neurologic deficits that, when measured at 24 h, is highly predictive of long-term functional outcome. We hypothesized that a simplified 24-h scale that incorporates the most predictive components of the NIHSS can retain prognostic accuracy and have improved interrater reliability. Methods In a post hoc analysis of the Interventional Management of Stroke-3 (IMS-3) trial, we performed principal component (PC) analysis to resolve the 24-h NIHSS into PCs. In the PCs that explained the largest proportions of variance, key variables were identified. Using these key variables, the prognostic accuracies (area under the curve [AUC]) for good outcome (3-month modified Rankin Scale [mRS] 0–2) and poor outcome (mRS 5–6) of various abbreviated NIHSS iterations were compared with the total 24-h NIHSS. The results were validated in the NINDS intravenous tissue plasminogen activator (NINDS-TPA) study cohort. Based on previously published data, interrater reliability of the abbreviated 24-h NIHSS (aNIHSS) was compared to the total 24-h NIHSS. Results In 545 IMS-3 participants, 2 PCs explained 60.8% of variance in the 24-h NIHSS. The key variables in PC1 included neglect, arm and leg weakness; while PC2 included level-of-consciousness (LOC) questions, LOC commands, and aphasia. A 3-variable aNIHSS (aphasia, neglect, arm weakness) retained excellent prognostic accuracy for good outcome (AUC = 0.90) as compared to the total 24-h NIHSS (AUC = 0.91), and it was more predictive (p < 0.001) than the baseline NIHSS (AUC = 0.73). The prognostic accuracy of the aNIHSS for good outcome was validated in the NINDS-TPA trial cohort (aNIHSS: AUC = 0.89 vs. total 24-h NIHSS: 0.92). An aNIHSS >9 predicted very poor outcomes (mRS 0–2: 0%, mRS 4–6: 98.5%). The estimated interrater reliability of the aNIHSS was higher than that of the total 24-h NIHSS across 6 published datasets (mean weighted kappa 0.80 vs. 0.73, p < 0.001). Conclusions At 24 h following ischemic stroke, aphasia, neglect, and arm weakness are the most prognostically relevant neurologic findings. The aNIHSS appears to have excellent prognostic accuracy with higher reliability and may be clinically useful. PMID:28968607

Tobacco, Marijuana, and Alcohol Use in University Students: A Cluster Analysis

ERIC Educational Resources Information Center

Primack, Brian A.; Kim, Kevin H.; Shensa, Ariel; Sidani, Jaime E.; Barnett, Tracey E.; Switzer, Galen E.

2012-01-01

Objective: Segmentation of populations may facilitate development of targeted substance abuse prevention programs. The authors aimed to partition a national sample of university students according to profiles based on substance use. Participants: The authors used 2008-2009 data from the National College Health Assessment from the American College…

A functional language approach in high-speed digital simulation

NASA Technical Reports Server (NTRS)

Ercegovac, M. D.; Lu, S.-L.

1983-01-01

A functional programming approach for a multi-microprocessor architecture is presented. The language, based on Backus FP, its intermediate form and the translation process are discussed and illustrated with an example. The approach allows performance analysis to be performed at a high level as an aid in program partitioning.

Validated Test Method 1316: Liquid-Solid Partitioning as a Function of Liquid-to-Solid Ratio in Solid Materials Using a Parallel Batch Procedure

EPA Pesticide Factsheets

Describes procedures written based on the assumption that they will be performed by analysts who are formally trained in at least the basic principles of chemical analysis and in the use of the subject technology.

Prognostic value of combined preoperative fibrinogen and neutrophil–lymphocyte ratio in patients with hepatocellular carcinoma after liver transplantation

PubMed Central

Chen, Mao-Gen; Wang, Xiao-Ping; Ju, Wei-Qiang; Zhao, Qiang; Wu, Lin-Wei; Ren, Qing-Qi; Guo, Zhi-Yong; Wang, Dong-Ping; Zhu, Xiao-Feng; Ma, Yi; He, Xiao-Shun

2017-01-01

Objectives Elevated plasma fibrinogen (Fib) correlated with patient's prognosis in several solid tumors. However, few studies have illuminated the relationship between preoperative Fib and prognosis of HCC after liver transplantation. We aimed to clarify the prognostic value of Fib and whether the prognostic accuracy can be enhanced by the combination of Fib and neutrophil–lymphocyte ratio (NLR). Results Fib was correlated with Child-pugh stage, alpha-fetoprotein (AFP), size of largest tumor, macro- and micro-vascular invasion. Univariate analysis showed preoperative Fib, AFP, NLR, size of largest tumor, tumor number, macro- and micro- vascular invasion were significantly associated with disease-free survival (DFS) and overall survival (OS) in HCC patients with liver transplantation. After multivariate analysis, only Fib and macro-vascular invasion were independently correlated with DFS and OS. Survival analysis showed that preoperative Fib > 2.345 g/L predicted poor prognosis of patients HCC after liver transplantation. Preoperative Fib showed prognostic value in various subgroups of HCC. Furthermore, the predictive range was expanded by the combination of Fib and NLR. Materials and Methods Data were collected retrospectively from 130 HCC patients who underwent liver transplantation. Preoperative Fib, NLR and clinicopathologic variables were analyzed. The survival analysis was performed by the Kaplan-Meier method, and compared by the log-rank test. Univariate and multivariate analyses were performed to identify the prognostic factors for DFS and OS. Conclusions Preoperative Fib is an independent effective predictor of prognosis for HCC patients, higher levels of Fib predict poorer outcomes and the combination of Fib and NLR enlarges the prognostic accuracy of testing. PMID:27935864

Dominant partition method. [based on a wave function formalism

NASA Technical Reports Server (NTRS)

Dixon, R. M.; Redish, E. F.

1979-01-01

By use of the L'Huillier, Redish, and Tandy (LRT) wave function formalism, a partially connected method, the dominant partition method (DPM) is developed for obtaining few body reductions of the many body problem in the LRT and Bencze, Redish, and Sloan (BRS) formalisms. The DPM maps the many body problem to a fewer body one by using the criterion that the truncated formalism must be such that consistency with the full Schroedinger equation is preserved. The DPM is based on a class of new forms for the irreducible cluster potential, which is introduced in the LRT formalism. Connectivity is maintained with respect to all partitions containing a given partition, which is referred to as the dominant partition. Degrees of freedom corresponding to the breakup of one or more of the clusters of the dominant partition are treated in a disconnected manner. This approach for simplifying the complicated BRS equations is appropriate for physical problems where a few body reaction mechanism prevails.

Quantification and significance of diffuse myocardial fibrosis and diastolic dysfunction in childhood hypertrophic cardiomyopathy.

PubMed

Hussain, Tarique; Dragulescu, Andreea; Benson, Lee; Yoo, Shi-Joon; Meng, Howard; Windram, Jonathan; Wong, Derek; Greiser, Andreas; Friedberg, Mark; Mertens, Luc; Seed, Michael; Redington, Andrew; Grosse-Wortmann, Lars

2015-06-01

The purpose of this study was to evaluate the presence of diffuse myocardial fibrosis in children and adolescents with hypertrophic cardiomyopathy (HCM) and to assess associations with echocardiographic and clinical parameters of disease. While a common end point in adults with HCM, it is unclear whether diffuse myocardial fibrosis occurs early in the disease. Cardiac magnetic resonance (CMR) estimation of myocardial post-contrast longitudinal relaxation time (T1) is an increasingly used method to estimate diffuse fibrosis. T1 measurements were taken using standard multi-breath-hold spoiled gradient echo phase-sensitive inversion-recovery CMR before and 15 min after the injection of gadolinium. The tissue-blood partition coefficient was calculated as a function of the ratio of T1 change of myocardium compared with blood. An echocardiogram and blood brain natriuretic peptide (BNP) levels were obtained on the day of the CMR. Twelve controls (mean age 12.8 years; 7 male) and 28 patients with HCM (mean age 12.8 years; 21 male) participated. The partition coefficient for both septal (0.27 ± 0.17 vs. 0.13 ± 0.09; p = 0.03) and lateral walls (0.22 ± 0.09 vs. 0.07 ± 0.10; p < 0.001) was increased in patients compared with controls. Eight patients had overt areas of late gadolinium enhancement (LGE). These patients did not show increased partition coefficient compared with those without LGE (0.27 ± 0.15 vs. 0.27 ± 0.19 and 0.22 ± 0.09 vs. 0.22 ± 0.09; p = 0.95 and 0.98, respectively). However, patients who were symptomatic (dyspnea, arrhythmia and/or chest pain) had higher lateral wall partition coefficient than asymptomatic HCM patients (0.27 ± 0.08 vs. 0.17 ± 0.08; p = 0.006). Similarly, patients with raised BNP (>100 pg/ml) had raised lateral wall coefficients (0.27 ± 0.07 vs. 0.20 ± 0.07; p = 0.03), as did those with traditional risk factors for sudden death (0.27 ± 0.06 vs. 0.18 ± 0.08; p = 0.007). Diffuse fibrosis, measured by the partition coefficient technique, is demonstrable in children and adolescents with HCM. Markers of fibrosis show an association with symptoms and raised serum BNP. Further study of the prognostic implication of this technique in young patients with HCM is warranted.

GPU Accelerated Prognostics

NASA Technical Reports Server (NTRS)

Gorospe, George E., Jr.; Daigle, Matthew J.; Sankararaman, Shankar; Kulkarni, Chetan S.; Ng, Eley

2017-01-01

Prognostic methods enable operators and maintainers to predict the future performance for critical systems. However, these methods can be computationally expensive and may need to be performed each time new information about the system becomes available. In light of these computational requirements, we have investigated the application of graphics processing units (GPUs) as a computational platform for real-time prognostics. Recent advances in GPU technology have reduced cost and increased the computational capability of these highly parallel processing units, making them more attractive for the deployment of prognostic software. We present a survey of model-based prognostic algorithms with considerations for leveraging the parallel architecture of the GPU and a case study of GPU-accelerated battery prognostics with computational performance results.

Review and Analysis of Algorithmic Approaches Developed for Prognostics on CMAPSS Dataset

DTIC Science & Technology

2014-12-23

publications for benchmarking prognostics algorithms. The turbofan degradation datasets have received over seven thousand unique downloads in the last five...approaches that researchers have taken to implement prognostics using these turbofan datasets. Some unique characteristics of these datasets are also...Description of the five turbofan degradation datasets available from NASA repository. Datasets #Fault Modes #Conditions #Train Units #Test Units

Prognostics and health management system for hydropower plant based on fog computing and docker container

NASA Astrophysics Data System (ADS)

Xiao, Jian; Zhang, Mingqiang; Tian, Haiping; Huang, Bo; Fu, Wenlong

2018-02-01

In this paper, a novel prognostics and health management system architecture for hydropower plant equipment was proposed based on fog computing and Docker container. We employed the fog node to improve the real-time processing ability of improving the cloud architecture-based prognostics and health management system and overcome the problems of long delay time, network congestion and so on. Then Storm-based stream processing of fog node was present and could calculate the health index in the edge of network. Moreover, the distributed micros-service and Docker container architecture of hydropower plants equipment prognostics and health management was also proposed. Using the micro service architecture proposed in this paper, the hydropower unit can achieve the goal of the business intercommunication and seamless integration of different equipment and different manufacturers. Finally a real application case is given in this paper.

Stability Analysis of Distributed Engine Control Systems Under Communication Packet Drop (Postprint)

DTIC Science & Technology

2008-07-01

use, modify, reproduce, release, perform, display, or disclose the work. 14. ABSTRACT Currently, Full Authority Digital Engine Control ( FADEC ...based on a centralized architecture framework is being widely used for gas turbine engine control. However, current FADEC is not able to meet the...system (DEC). FADEC based on Distributed Control Systems (DCS) offers modularity, improved control systems prognostics and fault tolerance along with

On Applying the Prognostic Performance Metrics

NASA Technical Reports Server (NTRS)

Saxena, Abhinav; Celaya, Jose; Saha, Bhaskar; Saha, Sankalita; Goebel, Kai

2009-01-01

Prognostics performance evaluation has gained significant attention in the past few years. As prognostics technology matures and more sophisticated methods for prognostic uncertainty management are developed, a standardized methodology for performance evaluation becomes extremely important to guide improvement efforts in a constructive manner. This paper is in continuation of previous efforts where several new evaluation metrics tailored for prognostics were introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. Several shortcomings identified, while applying these metrics to a variety of real applications, are also summarized along with discussions that attempt to alleviate these problems. Further, these metrics have been enhanced to include the capability of incorporating probability distribution information from prognostic algorithms as opposed to evaluation based on point estimates only. Several methods have been suggested and guidelines have been provided to help choose one method over another based on probability distribution characteristics. These approaches also offer a convenient and intuitive visualization of algorithm performance with respect to some of these new metrics like prognostic horizon and alpha-lambda performance, and also quantify the corresponding performance while incorporating the uncertainty information.

Temperature-mortality relationship in dairy cattle in France based on an iso-hygro-thermal partition of the territory

NASA Astrophysics Data System (ADS)

Morignat, Eric; Gay, Emilie; Vinard, Jean-Luc; Calavas, Didier; Hénaux, Viviane

2017-11-01

The issue of global warming and more specifically its health impact on populations is increasingly concerning. The aim of our study was to evaluate the impact of temperature on dairy cattle mortality in France during the warm season (April-August). We therefore devised and implemented a spatial partitioning method to divide France into areas in which weather conditions were homogeneous, combining a multiple factor analysis with a clustering method using both weather and spatial data. We then used time-series regressions (2001-2008) to model the relationship between temperature humidity index (an index representing the temperature corrected by the relative humidity) and dairy cattle mortality within these areas. We found a significant effect of heat on dairy cattle mortality, but also an effect of cooler temperatures (to a lesser extent in some areas), which leads to a U-shaped relationship in the studied areas. Our partitioning approach based on weather criteria, associated with classic clustering methods, may contribute to better estimating temperature effects, a critical issue for animal health and welfare. Beyond the interest of its use in animal health, this approach can also be of interest in several situations in the frame of human health.

Partitioning of organic carbon among density fractions in surface sediments of Fiordland, New Zealand

NASA Astrophysics Data System (ADS)

Cui, Xingqian; Bianchi, Thomas S.; Hutchings, Jack A.; Savage, Candida; Curtis, Jason H.

2016-03-01

Transport of particles plays a major role in redistributing organic carbon (OC) along coastal regions. In particular, the global importance of fjords as sites of carbon burial has recently been shown to be even more important than previously thought. In this study, we used six surface sediments from Fiordland, New Zealand, to investigate the transport of particles and OC based on density fractionation. Bulk, biomarker, and principle component analysis were applied to density fractions with ranges of <1.6, 1.6-2.0, 2.0-2.5, and >2.5 g cm-3. Our results found various patterns of OC partitioning at different locations along fjords, likely due to selective transport of higher density but smaller size particles along fjord head-to-mouth transects. We also found preferential leaching of certain biomarkers (e.g., lignin) over others (e.g., fatty acids) during the density fractionation procedure, which altered lignin-based degradation indices. Finally, our results indicated various patterns of OC partitioning on density fractions among different coastal systems. We further propose that a combination of particle size-density fractionation is needed to better understand transport and distribution of particles and OC.

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2015-12-01

Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

Prognostic value of baseline absolute lymphocyte concentration and neutrophil/lymphocyte ratio in dogs with newly diagnosed multi-centric lymphoma.

PubMed

Mutz, M; Boudreaux, B; Kearney, M; Stroda, K; Gaunt, S; Shiomitsu, K

2015-12-01

Canine multi-centric B-cell lymphoma shares similarities with diffuse large B-cell (Non-Hodgkin's) lymphoma (NHL) in people. In people with NHL, lymphopenia at diagnosis and first relapse and neutrophil/lymphocyte ratio (N:L) > 3.5 are negative prognostic factors for survival. The objective of this study was to determine if lymphocyte concentration at diagnosis and first relapse and N:L were prognostic for survival in dogs with newly diagnosed multi-centric lymphoma. Medical records of 77 dogs with multi-centric lymphoma treated with a CHOP-based chemotherapy protocol were retrospectively evaluated. Absolute lymphocyte concentration and N:L ratio at presentation of dogs pre-treated with steroids was not significantly different from dogs who had not received steroids. On multivariate analysis, only immunophenotype remained significant for progression-free survival (PFS), whereas no variables remained significant for ST. A prospective study of these haematologic variables is warranted to assess their true significance. © 2013 John Wiley & Sons Ltd.

Thymidylate synthase (TS) protein expression as a prognostic factor in advanced colorectal cancer: a comparison with TS mRNA expression.

PubMed

Nakagawa, Tateo; Shimada, Mitsuo; Kurita, Nobuhiro; Iwata, Takashi; Nishioka, Masanori; Yoshikawa, Kozo; Higashijima, Jun; Utsunomiya, Tohru

2012-06-01

The role of intratumoral thymidylate synthase (TS) mRNA or protein expression is still controversial and little has been reported regarding relation of them in colorectal cancer. Forty-six patients with advanced colorectal cancer who underwent surgical resection were included. TS mRNA expression was determined by the Danenberg tumor profile method based on laser-captured micro-dissection of the tumor cells. TS protein expression was evaluated using immunohistochemical staining. TS mRNA expression tended to relate TS protein expression. Statistical significance was not found in overall survival between the TS mRNA high group and low group regardless of performing adjuvant chemotherapy. The overall survival in the TS protein negative group was significantly higher than that in positive group in all and the patients without adjuvant chemotherapy. Multivariate analysis showed TS protein expression was as an independent prognostic factor. TS protein expression tends to be related TS mRNA expression and is an independent prognostic factor in advanced colorectal cancer.

Solute partitioning in multi-component γ/γ' Co–Ni-base superalloys with near-zero lattice misfit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meher, S.; Carroll, L. J.; Pollock, T. M.

The addition of nickel to cobalt-base alloys enables alloys with a near zero γ – γ' lattice misfit. The solute partitioning between ordered γ' precipitates and the disordered γ matrix have been investigated using atom probe tomography. Lastly, the unique shift in solute partitioning in these alloys, as compared to that in simpler Co-base alloys, derives from changes in site substitution of solutes as the relative amounts of Co and Ni change, highlighting new opportunities for the development of advanced tailored alloys.

Solute partitioning in multi-component γ/γ' Co–Ni-base superalloys with near-zero lattice misfit

DOE PAGES

Meher, S.; Carroll, L. J.; Pollock, T. M.; ...

2015-11-21

The addition of nickel to cobalt-base alloys enables alloys with a near zero γ – γ' lattice misfit. The solute partitioning between ordered γ' precipitates and the disordered γ matrix have been investigated using atom probe tomography. Lastly, the unique shift in solute partitioning in these alloys, as compared to that in simpler Co-base alloys, derives from changes in site substitution of solutes as the relative amounts of Co and Ni change, highlighting new opportunities for the development of advanced tailored alloys.

Short-course whole-brain radiotherapy (WBRT) for brain metastases due to small-cell lung cancer (SCLC).

PubMed

Bohlen, Guenther; Meyners, Thekla; Kieckebusch, Susanne; Lohynska, Radka; Veninga, Theo; Stalpers, Lukas J A; Schild, Steven E; Rades, Dirk

2010-04-01

Many patients with brain metastases due to SCLC have a poor survival prognosis. The most common treatment is whole-brain radiotherapy (WBRT). This retrospective study compares short-course WBRT with 5x4Gy in 1 week to standard WBRT with 10x3Gy in 2 weeks. Forty-four SCLC patients receiving WBRT with 5x4Gy were compared to 102 patients receiving 10x3Gy for survival (OS) and local (intracerebral) control (LC). Seven further potential prognostic factors were investigated: age, gender, Karnofsky Performance Score (KPS), number of brain metastases, extracerebral metastases, interval from tumor diagnosis to WBRT, RPA (Recursive Partitioning Analysis) class. After 5x4Gy, 12-month OS was 15%, versus 22% after 10x3Gy (p=0.69). On multivariate analysis, improved OS was associated with age or=70 (p<0.001), <4 brain metastases (p=0.011), and RPA class 1 (p<0.001). 12-month LC was 34% after 5x4Gy versus 25% after 10x3Gy (p=0.32). On multivariate analysis, improved LC was associated with KPS >or=70 (p<0.001), <4 brain metastases (p=0.027), and RPA class 1 (p<0.001). In patients with brain metastases due to SCLC, short-course WBRT with 5x4Gy provided similar outcomes as 10x3Gy and appears preferable, particularly for patients with poor estimated survival.

High pretreatment plasma D-dimer predicts poor survival of colorectal cancer: insight from a meta-analysis of observational studies

PubMed Central

Lu, Shao-Long; Ye, Zhi-Hua; Ling, Tong; Liang, Si-Yuan; Li, Hui; Tang, Xiao-Zhun; Xu, Yan-Song; Tang, Wei-Zhong

2017-01-01

D-dimer, one of the canonical markers of hypercoagulability, was reported to be a potential prognostic marker of colorectal cancer. However, an inconsistent conclusion existed in several published studies. Thus, we performed this meta-analysis to provide a comprehensive insight into the prognostic role for pretreatment D-dimer in colorectal cancer. Six databases (English: Pubmed, Embase and Web of Science; Chinese: CNKI, Wangfang and VIP) were utilized for the literature retrieval. Hazard ratio (HR) was pooled by Stata 12.0. A total of fifteen studies (2283 cases) corresponded to this meta-analysis and provided available data to evaluate the prognostic role of D-dimer for colorectal cancer. The pooled HR reached 2.167 (95%. CI (confidence interval): 1.672–2.809, P < 0.001) utilizing random effect model due to obvious heterogeneity among the included studies (I2: 73.3%; P < 0.001). To explore the heterogeneity among the studies, we conducted a sensitivity analysis and found a heterogeneous study. After removing it, the heterogeneity reduced substantially (I2: 0%; P = 0.549) and we obtained a more convincing result by fixed effect model (HR = 2.143, 95% CI = 1.922–2.390, P < 0.001, 14 studies with 2179 cases). In summary, high pretreatment plasma D-dimer predicts poor survival of colorectal cancer based on the current evidence. Further prospective researches are necessary to confirm the role of D-dimer in colorectal cancer. PMID:29113378

Methodological issues and recommendations for systematic reviews of prognostic studies: an example from cardiovascular disease.

PubMed

Dretzke, Janine; Ensor, Joie; Bayliss, Sue; Hodgkinson, James; Lordkipanidzé, Marie; Riley, Richard D; Fitzmaurice, David; Moore, David

2014-12-03

Prognostic factors are associated with the risk of future health outcomes in individuals with a particular health condition. The prognostic ability of such factors is increasingly being assessed in both primary research and systematic reviews. Systematic review methodology in this area is continuing to evolve, reflected in variable approaches to key methodological aspects. The aim of this article was to (i) explore and compare the methodology of systematic reviews of prognostic factors undertaken for the same clinical question, (ii) to discuss implications for review findings, and (iii) to present recommendations on what might be considered to be 'good practice' approaches. The sample was comprised of eight systematic reviews addressing the same clinical question, namely whether 'aspirin resistance' (a potential prognostic factor) has prognostic utility relative to future vascular events in patients on aspirin therapy for secondary prevention. A detailed comparison of methods around study identification, study selection, quality assessment, approaches to analysis, and reporting of findings was undertaken and the implications discussed. These were summarised into key considerations that may be transferable to future systematic reviews of prognostic factors. Across systematic reviews addressing the same clinical question, there were considerable differences in the numbers of studies identified and overlap between included studies, which could only partially be explained by different study eligibility criteria. Incomplete reporting and differences in terminology within primary studies hampered study identification and selection process across reviews. Quality assessment was highly variable and only one systematic review considered a checklist for studies of prognostic questions. There was inconsistency between reviews in approaches towards analysis, synthesis, addressing heterogeneity and reporting of results. Different methodological approaches may ultimately affect the findings and interpretation of systematic reviews of prognostic research, with implications for clinical decision-making.

Covariance Partition Priors: A Bayesian Approach to Simultaneous Covariance Estimation for Longitudinal Data.

PubMed

Gaskins, J T; Daniels, M J

2016-01-02

The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.

Prognostic and predictive value of tumor-infiltrating lymphocytes in two phase III randomized adjuvant breast cancer trials

PubMed Central

Dieci, M. V.; Mathieu, M. C.; Guarneri, V.; Conte, P.; Delaloge, S.; Andre, F.; Goubar, A.

2015-01-01

Background Tumor-infiltrating lymphocytes (TILs) are emerging as strong prognostic factor for early breast cancer patients, especially in the triple-negative subtype. Here, we aim to validate previous findings on the prognostic role of TIL in the context of two randomized adjuvant trials and to investigate whether lymphocyte infiltrates can predict benefit from adjuvant anthracyclines. Patients and methods A total of 816 patients enrolled and treated at the Gustave Roussy in the context of two multicentric randomized trials comparing adjuvant anthracyclines versus no chemotherapy were included in the present analysis. Primary end point was overall survival (OS). Hematoxilin and eosin slides of primary tumors were retrieved and evaluated for the percentage of intratumoral (It) and stromal (Str) TIL. Each case was also defined as high-TIL or low-TIL breast cancer adopting previously validated cutoffs. Results TIL were assessable for 781 of 816 cases. High-TIL cases were more likely grade 3 and estrogen receptor (ER)-negative (P < 0.001). In multivariate analysis, both continuous It-TIL and Str-TIL were strong prognostic factors for OS [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.77–0.95 P = 0.003; HR 0.89, 95% CI 0.81–0.96, P = 0.005 for It-TIL and Str-TIL, respectively]. The prognostic effect of continuous TIL was limited to triple-negative and HER2-positive patients. Ten-year OS rates were: 89% and 68% for triple-negative high-TIL and low-TIL, respectively (HR 0.44, 95% CI 0.18–1.10, P = 0.07) and 78% and 57% for HER2-positive high-TIL versus low-TIL, respectively (HR 0.46, 95% CI 0.20–1.11, P = 0.08). Either continuous or binary TIL variables did not predict for the efficacy of anthracyclines. Test for interaction P value was not significant in the whole study population and in subgroups (ER+/HER2−, HER2+, ER−/HER2−). Conclusions We confirmed the prognostic role of TIL in triple-negative early breast cancer and suggested a prognostic impact in HER2+ patients as well. Basing on our data, TIL should not be used as a parameter to select patients for anthracyclines chemotherapy. PMID:25995301

Damage tolerance modeling and validation of a wireless sensory composite panel for a structural health monitoring system

NASA Astrophysics Data System (ADS)

Talagani, Mohamad R.; Abdi, Frank; Saravanos, Dimitris; Chrysohoidis, Nikos; Nikbin, Kamran; Ragalini, Rose; Rodov, Irena

2013-05-01

The paper proposes the diagnostic and prognostic modeling and test validation of a Wireless Integrated Strain Monitoring and Simulation System (WISMOS). The effort verifies a hardware and web based software tool that is able to evaluate and optimize sensorized aerospace composite structures for the purpose of Structural Health Monitoring (SHM). The tool is an extension of an existing suite of an SHM system, based on a diagnostic-prognostic system (DPS) methodology. The goal of the extended SHM-DPS is to apply multi-scale nonlinear physics-based Progressive Failure analyses to the "as-is" structural configuration to determine residual strength, remaining service life, and future inspection intervals and maintenance procedures. The DPS solution meets the JTI Green Regional Aircraft (GRA) goals towards low weight, durable and reliable commercial aircraft. It will take advantage of the currently developed methodologies within the European Clean sky JTI project WISMOS, with the capability to transmit, store and process strain data from a network of wireless sensors (e.g. strain gages, FBGA) and utilize a DPS-based methodology, based on multi scale progressive failure analysis (MS-PFA), to determine structural health and to advice with respect to condition based inspection and maintenance. As part of the validation of the Diagnostic and prognostic system, Carbon/Epoxy ASTM coupons were fabricated and tested to extract the mechanical properties. Subsequently two composite stiffened panels were manufactured, instrumented and tested under compressive loading: 1) an undamaged stiffened buckling panel; and 2) a damaged stiffened buckling panel including an initial diamond cut. Next numerical Finite element models of the two panels were developed and analyzed under test conditions using Multi-Scale Progressive Failure Analysis (an extension of FEM) to evaluate the damage/fracture evolution process, as well as the identification of contributing failure modes. The comparisons between predictions and test results were within 10% accuracy.

Prognostic significance of anaplasia and angiogenesis in childhood medulloblastoma: a pediatric oncology group study.

PubMed

Ozer, Erdener; Sarialioglu, Faik; Cetingoz, Riza; Yüceer, Nurullah; Cakmakci, Handan; Ozkal, Sermin; Olgun, Nur; Uysal, Kamer; Corapcioglu, Funda; Canda, Serefettin

2004-01-01

The purpose of this study was to investigate whether quantitative assessment of cytologic anaplasia and angiogenesis may predict the clinical prognosis in medulloblastoma and stratify the patients to avoid both undertreatment and overtreatment. Medulloblastomas from 23 patients belonging to the Pediatric Oncology Group were evaluated with respect to some prognostic variables, including histologic assessment of nodularity and desmoplasia, grading of anaplasia, measurement of nuclear size, mitotic cell count, quantification of angiogenesis, including vascular surface density (VSD) and microvessel number (NVES), and immunohistochemical scoring of vascular endothelial growth factor (VEGF) expression. Univariate and multivariate analyses for prognostic indicators for survival were performed. Univariate analysis revealed that extensive nodularity was a significant favorable prognostic factor, whereas the presence of anaplasia, increased nuclear size, mitotic rate, VSD, and NVES were significant unfavorable prognostic factors. Using multivariate analysis, increased nuclear size was found to be an independent unfavorable prognostic factor for survival. Neither the presence of desmoplasia nor VEGF expression was significantly related to patient survival. Although care must be taken not to overstate the importance of the results of this single-institution preliminary report, pathologic grading of medulloblastomas with respect to grading of anaplasia and quantification of nodularity, nuclear size, and microvessel profiles may be clinically useful for the treatment of medulloblastomas. Further validation of the independent prognostic significance of nuclear size in stratifying patients is required.

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2012-09-01

the Gerchberg-Saxton algorithm in the Fresnel diffraction regime, and is much more robust against image noise than the TIE-based method. For details...developed efficient coding with the software modules for the image registration, flat-filed correction , and phase retrievals. In addition, we...X, Liu H. 2010. Performance analysis of the attenuation-partition based iterative phase retrieval algorithm for in-line phase-contrast imaging