Science.gov

Sample records for predicts inferior survival

  1. Radiographic tips on predicting inferior alveolar nerve exposure.

    PubMed

    Beirne, O Ross; Hujoel, Philippe

    2012-09-01

    The study included 230 patients (60% female) with a total of 423 wisdom tooth extractions. The patients were treated by 2 oral surgeons between July 1998 and July 2002 in the Oral and Maxillofacial Surgery Unit of the Massachusetts General Hospital in Boston, Massachusetts. The authors reported that the extraction was inspected for evidence of inferior alveolar nerve (IAN) exposure under direct vision using a headlight. Each tooth was inspected for the presence of any of the following 5 radiographic signs: No IAN exposures occurred when all 5 radiographic signs were absent. Based on this study, where 189 M3 had such a radiographic presentation, we can conclude that the upper limit of the 95% confidence interval for the IAN exposure is 1.6%. None of the 5 diagnostic markers, when used in isolation, had adequate sensitivity and specificity to accurately predict an IAN nerve exposure in a clinical setting. Copyright © 2012. Published by Mosby, Inc. All rights reserved.

  2. Predictions Shape Confidence in Right Inferior Frontal Gyrus.

    PubMed

    Sherman, Maxine T; Seth, Anil K; Kanai, Ryota

    2016-10-05

    It is clear that prior expectations shape perceptual decision-making, yet their contribution to the construction of subjective decision confidence remains largely unexplored. We recorded fMRI data while participants made perceptual decisions and confidence judgments, manipulating perceptual prior expectations while controlling for potential confounds of attention. Results show that subjective confidence increases as expectations increasingly support the decision, and that this relationship is associated with BOLD activity in right inferior frontal gyrus (rIFG). Specifically, rIFG is sensitive to the discrepancy between expectation and decision (mismatch), and higher mismatch responses are associated with lower decision confidence. Connectivity analyses revealed expectancy information to be represented in bilateral orbitofrontal cortex and sensory signals to be represented in intracalcarine sulcus. Together, our results indicate that predictive information is integrated into subjective confidence in rIFG, and reveal an occipital-frontal network that constructs confidence from top-down and bottom-up signals. This interpretation was further supported by exploratory findings that the white matter density of right orbitofrontal cortex negatively predicted its respective contribution to the construction of confidence. Our findings advance our understanding of the neural basis of subjective perceptual processes by revealing an occipitofrontal functional network that integrates prior beliefs into the construction of confidence.

  3. Study duration for three-arm non-inferiority survival trials designed for accrual by cohorts.

    PubMed

    Wu, Ying; Li, Yiqun; Hou, Yan; Li, Kang; Zhou, Xiaohua

    2016-03-17

    Study planning is particularly complex for survival trials because it usually involves an accrual period and a continued observation period after accrual closure. The three-arm clinical trial design, which includes a test treatment, an active reference, and a placebo control, is the gold standard design for the assessment of non-inferiority. The existing statistical methods of calculating minimal sample size for non-inferiority trials with three-arm design and survival-type endpoints cannot take into consideration the accrual rate of patients to the trial, the length of accrual period, the length of continued observation period after accrual closure, and unbalanced allocation of the total sample size. The purpose of this paper is to develop a statistical method, which allows for all these sources of variability for planning non-inferiority trials with the gold standard design for censored, exponentially distributed time-to-event data. The proposed method is based on the assumption of exponentially distributed failure times and a non-inferiority test formulated in terms of the retention of effect hypotheses. It can be used to calculate the duration of accrual required to assure a desired power for non-inferiority trials with active and placebo control. We illustrate the use of the method by considering a randomized, active- and placebo-controlled trial in depression associated with Parkinson's disease. We then explore the validity of the proposed method by simulation studies. An R-language program for the implementation of the proposed algorithm is provided as supplementary material. © The Author(s) 2016.

  4. More Lake States Tree Survival Predictions

    Treesearch

    Roland G. Buchman; Ellen L. Lentz

    1984-01-01

    Species coefficients are reported for predicting individual tree survival for nine Lake States species, supplementing a previous report for 10 species. Tree attributes are diameter growth rate and diameter at breast height. Regional and local performances are summarized.

  5. [Cardiac factors predictive of 10-year survival after coronary surgery].

    PubMed

    Fournial, G; Fourcade, J; Roux, D; Garcia, O; Sauer, M; Glock, Y

    1999-07-01

    Although the predictive factors of postoperative mortality after coronary artery surgery are well known, those predictive of long-term survival have received less attention. This study reviews the outcome of a group of 480 patients between 50 and 65 years of age, operated between 1984 and 1986. The patients were classified in two groups according to the presence or absence of internal mammary artery bypass grafts: Group I (304 patients with saphenous vein bypass grafts alone) and group II (176 patients with an internal mammary artery +/- saphenous vein bypass grafts). The long-term results were assessed according to 3 criteria: isolated cardiac mortality: cardiac mortality associated with a repeat revascularisation procedure and cardiac mortality associated with reoperation or recurrence of angina. Cardiac survival at 10 years was significantly better after internal mammary-LAD bypass: 91.4% (CI 87.1-95.1) than after saphenous vein bypass grafting alone: 79.6% (CI 74.8-84.4) (p = 0.012). Univariate analysis identified the following poor predictive factors: three vessel disease (p = 0.03), preoperative left ventricular dysfunction with an ejection fraction inferior to 45% (p = 0.0001), incomplete revascularisation (p = 0.0003), use of venous bypass graft alone (p < 0.014) and perioperative infarction (p = 0.0254). For each criterion of survival (cardiac isolated or associated with a new revascularisation and/or recurrence of angina), multivariate analysis identified three independent predictive factors of long-term extramortality: not using internal mammary artery-LAD bypass graft, incomplete revascularisation and preoperative hypertension. This study confirms the beneficial effects of internal mammary-LAD artery grafting on long-term survival after coronary artery surgery, and also demonstrates the prejudicial effects of hypertension.

  6. Survival Regression Modeling Strategies in CVD Prediction

    PubMed Central

    Barkhordari, Mahnaz; Padyab, Mojgan; Sardarinia, Mahsa; Hadaegh, Farzad; Azizi, Fereidoun; Bozorgmanesh, Mohammadreza

    2016-01-01

    Background A fundamental part of prevention is prediction. Potential predictors are the sine qua non of prediction models. However, whether incorporating novel predictors to prediction models could be directly translated to added predictive value remains an area of dispute. The difference between the predictive power of a predictive model with (enhanced model) and without (baseline model) a certain predictor is generally regarded as an indicator of the predictive value added by that predictor. Indices such as discrimination and calibration have long been used in this regard. Recently, the use of added predictive value has been suggested while comparing the predictive performances of the predictive models with and without novel biomarkers. Objectives User-friendly statistical software capable of implementing novel statistical procedures is conspicuously lacking. This shortcoming has restricted implementation of such novel model assessment methods. We aimed to construct Stata commands to help researchers obtain the aforementioned statistical indices. Materials and Methods We have written Stata commands that are intended to help researchers obtain the following. 1, Nam-D’Agostino X2 goodness of fit test; 2, Cut point-free and cut point-based net reclassification improvement index (NRI), relative absolute integrated discriminatory improvement index (IDI), and survival-based regression analyses. We applied the commands to real data on women participating in the Tehran lipid and glucose study (TLGS) to examine if information relating to a family history of premature cardiovascular disease (CVD), waist circumference, and fasting plasma glucose can improve predictive performance of Framingham’s general CVD risk algorithm. Results The command is adpredsurv for survival models. Conclusions Herein we have described the Stata package “adpredsurv” for calculation of the Nam-D’Agostino X2 goodness of fit test as well as cut point-free and cut point-based NRI, relative

  7. Predicting survival time for cold exposure

    NASA Astrophysics Data System (ADS)

    Tikuisis, Peter

    1995-06-01

    The prediction of survival time (ST) for cold exposure is speculative as reliable controlled data of deep hypothermia are unavailable. At best, guidance can be obtained from case histories of accidental exposure. This study describes the development of a mathematical model for the prediction of ST under sedentary conditions in the cold. The model is based on steady-state heat conduction in a single cylinder comprised of a core and two concentric annular shells representing the fat plus skin and the clothing plus still boundary layer, respectively. The ambient condition can be either air or water; the distinction is made by assigning different values of insulation to the still boundary layer. Metabolic heat production ( M) is comprised of resting and shivering components with the latter predicted by temperature signals from the core and skin. Where the cold exposure is too severe for M to balance heat loss, ST is largely determined by the rate of heat loss from the body. Where a balance occurs, ST is governed by the endurance time for shivering. End of survival is marked by the deep core temperature reaching a value of 30° C. The model was calibrated against survival data of cold water (0 to 20° C) immersion and then applied to cold air exposure. A sampling of ST predictions for the nude exposure of an average healthy male in relatively calm air (1 km/h wind speed) are the following: 1.8, 2.5, 4.1, 9.0, and >24 h for -30, -20, -10, 0, and 10° C, respectively. With two layers of loose clothing (average thickness of 1 mm each) in a 5 km/h wind, STs are 4.0, 5.6, 8.6, 15.4, and >24 h for -50, -40, -30, -20, and -10° C. The predicted STs must be weighted against the extrapolative nature of the model. At present, it would be prudent to use the predictions in a relative sense, that is, to compare or rank-order predicted STs for various combinations of ambient conditions and clothing protection.

  8. Renal cell carcinoma with inferior vena cava involvement: Prognostic effect of tumor thrombus consistency on cancer specific survival.

    PubMed

    Mager, Rene; Daneshmand, Siamak; Evans, Christopher P; Palou, Joan; Martínez-Salamanca, Juan I; Master, Viraj A; McKiernan, James M; Libertino, John A; Haferkamp, Axel; Haferkamp, Axel; Capitanio, Umberto; Carballido, Joaquín A; Chantada, Venancio; Chromecki, Thomas; Ciancio, Gaetano; Daneshmand, Siamak; Evans, Christopher P; Gontero, Paolo; González, Javier; Hohenfellner, Markus; Huang, William C; Koppie, Theresa M; Libertino, John A; Espinós, Estefanía Linares; Lorentz, Adam; Martínez-Salamanca, Juan I; Master, Viraj A; McKiernan, James M; Montorsi, Francesco; Novara, Giacomo; O'Malley, Padraic; Pahernik, Sascha; Palou, Joan; Moreno, José Luis Pontones; Pruthi, Raj S; Faba, Oscar Rodriguez; Russo, Paul; Scherr, Douglas S; Shariat, Shahrokh F; Spahn, Martin; Terrone, Carlo; Tilki, Derya; Vázquez-Martul, Dario; Donoso, Cesar Vera; Vergho, Daniel; Wallen, Eric M; Zigeuner, Richard

    2016-11-01

    Renal cell carcinoma forming a venous tumor thrombus (VTT) in the inferior vena cava (IVC) has a poor prognosis. Recent investigations have been focused on prognostic markers of survival. Thrombus consistency (TC) has been proposed to be of significant value but yet there are conflicting data. The aim of this study is to test the effect of IVC VTT consistency on cancer specific survival (CSS) in a multi-institutional cohort. The records of 413 patients collected by the International Renal Cell Carcinoma-Venous Thrombus Consortium were retrospectively analyzed. All patients underwent radical nephrectomy and tumor thrombectomy. Kaplan-Meier estimate and Cox regression analyses investigated the impact of TC on CSS in addition to established clinicopathological predictors. VTT was solid in 225 patients and friable in 188 patients. Median CSS was 50 months in solid and 45 months in friable VTT. TC showed no significant association with metastatic spread, pT stage, perinephric fat invasion, and higher Fuhrman grade. Survival analysis and Cox regression rejected TC as prognostic marker for CSS. In the largest cohort published so far, TC seems not to be independently associated with survival in RCC patients and should therefore not be included in risk stratification models. J. Surg. Oncol. 2016;114:764-768. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  9. Digital versus conventional panoramic radiography in predicting inferior alveolar nerve injury after mandibular third molar removal.

    PubMed

    Szalma, József; Lempel, Edina; Jeges, Sára; Olasz, Lajos

    2012-03-01

    The aim of the study was to compare the accuracy of conventional and digital panoramic radiography (OPG) in relation to 4 specific high-risk signs (interruption of the superior cortical line, diversion, narrowing of the canal, and dark band of the root), which would indicate a close anatomic relationship between third molar roots and the inferior alveolar canal.Four hundred mandibular third molar surgical removals after conventional and 272 after digital radiographs were evaluated in the study. The association between postoperative inferior alveolar nerve (IAN) paresthesia and the presence of any preoperative high-risk signs in the OPG was investigated. Bivariate and multivariate logistic regression analyses were completed to compare the accuracy of conventional and digital radiographic techniques detecting high-risk signs predicting possible IAN paresthesia.Digital OPG results showed significantly higher sensitivity in diversion (P = 0.014) and narrowing (P < 0.002) of the canal, whereas the specificity of these signs was significantly lower (P < 0.001 and P = 0.035). The likelihood ratio analysis and multivariate logistic regression analysis did not prove the significant difference between digital and conventional imaging according to the examined high-risk signs. Positive predictive values of the signs were found in conventional radiography between 3.6% and 10.9%, whereas in the digital images, it ranged from 2.9% to 7.9%.The results of this study failed to prove significant difference between the accuracy of digital and conventional OPG for predicting IAN paresthesia, whereas low positive predictive values indicate both imaging techniques as inadequate screening methods for predicting IAN paresthesia after mandibular third molar removal.

  10. The left inferior parietal lobe represents stored hand-postures for object use and action prediction

    PubMed Central

    van Elk, Michiel

    2014-01-01

    Action semantics enables us to plan actions with objects and to predict others' object-directed actions as well. Previous studies have suggested that action semantics are represented in a fronto-parietal action network that has also been implicated to play a role in action observation. In the present fMRI study it was investigated how activity within this network changes as a function of the predictability of an action involving multiple objects and requiring the use of action semantics. Participants performed an action prediction task in which they were required to anticipate the use of a centrally presented object that could be moved to an associated target object (e.g., hammer—nail). The availability of actor information (i.e., presenting a hand grasping the central object) and the number of possible target objects (i.e., 0, 1, or 2 target objects) were independently manipulated, resulting in different levels of predictability. It was found that making an action prediction based on actor information resulted in an increased activation in the extrastriate body area (EBA) and the fronto-parietal action observation network (AON). Predicting actions involving a target object resulted in increased activation in the bilateral IPL and frontal motor areas. Within the AON, activity in the left inferior parietal lobe (IPL) and the left premotor cortex (PMC) increased as a function of the level of action predictability. Together these findings suggest that the left IPL represents stored hand-postures that can be used for planning object-directed actions and for predicting other's actions as well. PMID:24795681

  11. The left inferior parietal lobe represents stored hand-postures for object use and action prediction.

    PubMed

    van Elk, Michiel

    2014-01-01

    Action semantics enables us to plan actions with objects and to predict others' object-directed actions as well. Previous studies have suggested that action semantics are represented in a fronto-parietal action network that has also been implicated to play a role in action observation. In the present fMRI study it was investigated how activity within this network changes as a function of the predictability of an action involving multiple objects and requiring the use of action semantics. Participants performed an action prediction task in which they were required to anticipate the use of a centrally presented object that could be moved to an associated target object (e.g., hammer-nail). The availability of actor information (i.e., presenting a hand grasping the central object) and the number of possible target objects (i.e., 0, 1, or 2 target objects) were independently manipulated, resulting in different levels of predictability. It was found that making an action prediction based on actor information resulted in an increased activation in the extrastriate body area (EBA) and the fronto-parietal action observation network (AON). Predicting actions involving a target object resulted in increased activation in the bilateral IPL and frontal motor areas. Within the AON, activity in the left inferior parietal lobe (IPL) and the left premotor cortex (PMC) increased as a function of the level of action predictability. Together these findings suggest that the left IPL represents stored hand-postures that can be used for planning object-directed actions and for predicting other's actions as well.

  12. Predicting goals in action episodes attenuates BOLD response in inferior frontal and occipitotemporal cortex.

    PubMed

    Wurm, Moritz F; Hrkać, Mari; Morikawa, Yuka; Schubotz, Ricarda I

    2014-11-01

    Actions are usually made of several action steps gearing towards an overarching goal. During observation of such action episodes the overarching action goal becomes more and more clear and upcoming action steps can be predicted with increasing precision. To tap this process, the present fMRI study investigated the dynamic changes of neural activity during the observation of distinct action steps that cohere by an overarching goal. Our hypotheses specifically addressed the role of the inferior frontal gyrus (IFG), a region assumed to be a key hub for integration functions during action processing, as well as the role of regions involved in action perception (often referred to as action observation network or AON) that should benefit from the predictability of forthcoming action steps. Participants watched separate action steps that formed a coherent action goal or not (factor goal coherence) and were performed by a single actor or not (factor actor coherence). Independent of actor coherence, neural activity in IFG and occipitotemporal cortex decreased as a function of goal predictability during the unfolding of goal-coherent episodes. In addition, we identified a network (precuneus, dorsolateral prefrontal and orbitofrontal cortex, angular gyrus, and middle temporal gyrus) that showed increased activity for goal coherence. We conclude that IFG fosters the integration of action steps to build overarching goals. Identifying the unifying goal of an action episode allows anticipation, and thus efficient processing, of forthcoming action steps. To this end, past action steps of the action episode are buffered and recollected with recourse to episodic memory.

  13. Ebola Blood Test May Help Predict Survival Chances

    MedlinePlus

    ... page: https://medlineplus.gov/news/fullstory_163165.html Ebola Blood Test May Help Predict Survival Chances Findings ... help determine a person's chance of surviving an Ebola infection, researchers say. "It is not just defining ...

  14. Ultrasound measurement of inferior vena cava collapse predicts propofol-induced hypotension.

    PubMed

    Au, Arthur K; Steinberg, Dean; Thom, Christopher; Shirazi, Maziar; Papanagnou, Dimitrios; Ku, Bon S; Fields, J Matthew

    2016-06-01

    Hypotension is a common side effect of propofol, but there are no reliable methods to determine which patients are at risk for significant propofol-induced hypotension (PIH). Ultrasound has been used to estimate volume status by visualization of inferior vena cava (IVC) collapse. This study explores whether IVC assessment by ultrasound can assist in predicting which patients may experience significant hypotension. This was a prospective observational study conducted in the operating suite of an urban community hospital. A convenience sample of consenting adults planned to receive propofol for induction of anesthesia during scheduled surgical procedures were enrolled. Bedside ultrasound was used to measure maximum (IVCmax) and minimum (IVCmin) IVC diameters. IVC-CI was calculated as [(IVCmax-IVCmin)/IVCmax × 100%]. The primary outcome was significant hypotension defined as systolic blood pressure (BP) below 90mmHg and/or administration of a vasopressor to increase BP during surgery. The study sample comprised 40 patients who met inclusion criteria. Mean age was 55years, (95%CI, 49-60) with 53% female. 55% of patients had significant hypotension after propofol administration. 76% of patients with IVC-CI≥50% had significant hypotension compared to 39% with IVC-CI<50%, P=.02. IVC-CI≥50% had a specificity of 77.27% (95%CI, 64.29%-90.26%) and sensitivity of 66.67% (95%CI, 52.06%-81.28%) in predicting PIH. The odds ratio for PIH in patients with IVC-CI≥50% was 6.9 (95%CI, 1.7-27.5). Patients with IVC-CI≥50% were more likely to develop significant hypotension from propofol. IVC ultrasound may be a useful tool to predict which patients are at increased risk for PIH. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Inferior mesenteric artery lymph node metastasis in rectal cancer treated with neoadjuvant chemoradiotherapy: Incidence, prediction and prognostic impact.

    PubMed

    Sun, Y; Chi, P; Lin, H; Lu, X; Huang, Y; Xu, Z; Huang, S; Wang, X

    2017-01-01

    To assess the effect of neoadjuvant chemoradiotherapy (nCRT) on inferior mesenteric artery (IMA) nodal metastasis and identify predictors for IMA nodal metastasis in locally advanced rectal cancer (LARC) after nCRT. Propensity score matching of 1167 patients with LARC was performed. Clinicopathological predictors and survival rates were analyzed using univariate and multivariate analyses. Compared to surgery alone, nCRT reduced the incidence of IMA nodal metastasis (before matching, 4.8% vs 9.1%, p = 0.004; after matching, 4.3% vs 10.1%, p = 0.002). Logistic regression analysis revealed that poorly differentiated (OR = 5.955, p < 0.001), tumors located above the peritoneal reflection (OR = 3.513, p = 0.005), and preoperative CEA levels ≧10 ng/ml (OR = 4.774, p = 0.005) were associated with IMA nodal metastasis. Time intervals to surgery ≧6 weeks were associated with fewer IMA nodal metastasis (OR = 0.274, p = 0.009).Over a median 40-month follow-up, the 3-year overall survival and disease-free survival rates were 63.0% and 43.1% in IMA-positive patients, respectively, which were significantly lower than the corresponding 89.0% and 82.4% rates in IMA-negative patients. Cox regression analysis revealed that IMA nodal metastasis was independently associated with unfavorable 3-year DFS. nCRT reduced the incidence of IMA node metastasis. Tumors located above the peritoneal reflection, poorly differentiated, and higher preoperative CEA levels were associated with IMA nodal metastasis after nCRT. IMA lymph node dissection is beneficial to certain patients with IMA nodal metastases, and the oncologic benefit may be improved if IMA nodal metastasis can be predicted. Copyright © 2016 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

  16. Accuracy of survival prediction by palliative radiation oncologists

    SciTech Connect

    Chow, Edward . E-mail: Edward.Chow@sw.ca; Davis, Lori; Panzarella, Tony; Hayter, Charles; Szumacher, Ewa; Loblaw, Andrew; Wong, Rebecca; Danjoux, Cyril

    2005-03-01

    Purpose: To examine the accuracy of survival prediction by palliative radiation oncologists. Methods and materials: After consultation of cancer patients with metastatic disease for referral of palliative radiotherapy, radiation oncologists estimated the survival of the patients. These were compared with the actual dates of death obtained from the Cancer Death Registry. The time to death from all causes was the outcome. The survival times were measured from the date of the first consultation at the palliative radiotherapy clinics. Results: Six radiation oncologists provided estimates for 739 patients. Of the 739 patients, 396 were men and 343 were women (median age, 69 years). The median survival of all patients was 15.9 weeks. The mean difference between the actual survival (AS) and the clinician predicted survival (i.e., actual survival minus clinician predicted survival) was -12.3 weeks (95% confidence interval, -15.0 to -9.5) for the entire population. The mean difference was -21.9 weeks when the actual survival was {<=}12 weeks, -19.2 weeks when the AS was 13-26 weeks, -9.7 weeks when the AS was 27-52 weeks, and +23.0 weeks when the AS was >52 weeks. Conclusion: In this study, the prediction of survival by radiation oncologists was inaccurate and tended to be overly optimistic.

  17. A K-nearest neighbors survival probability prediction method.

    PubMed

    Lowsky, D J; Ding, Y; Lee, D K K; McCulloch, C E; Ross, L F; Thistlethwaite, J R; Zenios, S A

    2013-05-30

    We introduce a nonparametric survival prediction method for right-censored data. The method generates a survival curve prediction by constructing a (weighted) Kaplan-Meier estimator using the outcomes of the K most similar training observations. Each observation has an associated set of covariates, and a metric on the covariate space is used to measure similarity between observations. We apply our method to a kidney transplantation data set to generate patient-specific distributions of graft survival and to a simulated data set in which the proportional hazards assumption is explicitly violated. We compare the performance of our method with the standard Cox model and the random survival forests method.

  18. Interrogating the Aged Striatum: Robust Survival of Grafted Dopamine Neurons in Aging Rats Produces Inferior Behavioral Recovery and Evidence of Impaired Integration

    PubMed Central

    Collier, Timothy J.; O’Malley, Jennifer; Rademacher, David J.; Stancati, Jennifer A.; Sisson, Kellie A.; Sortwell, Caryl E.; Paumier, Katrina L.; Gebremedhin, Kibrom G.; Steece-Collier, Kathy

    2015-01-01

    Advanced age is the primary risk factor for Parkinson disease (PD). In PD patients and rodent models of PD, advanced age is associated with inferior symptomatic benefit following intrastriatal grafting of embryonic dopamine (DA) neurons, a pattern believed to result from decreased survival and reinnervation provided by grafted neurons in the aged host. To help understand the capacity of the aged, parkinsonian striatum to be remodeled with new DA terminals, we used a grafting model and examined whether increasing the number of grafted DA neurons in aged rats would translate to enhanced behavioral recovery. Young (3 mo), middle-aged (15 mo), and aged (22 mo) parkinsonian rats were grafted with proportionately increasing numbers of embryonic ventral mesencephalic (VM) cells to evaluate whether the limitations of the graft environment in subjects of advancing age can be offset by increased numbers of transplanted neurons. Despite robust survival of grafted neurons in aged rats, reinnervation of striatal neurons remained inferior and amelioration of levodopa-induced dyskinesias (LID) was delayed or absent. This study demonstrates that: 1) counter to previous evidence, under certain conditions the aged striatum can support robust survival of grafted DA neurons; and 2) unknown factors associated with the aged striatum result in inferior integration of graft and host, and continue to present obstacles to full therapeutic efficacy of DA cell-based therapy in this model of aging. PMID:25771169

  19. Bacterial survival in turfgrass as predicted from the UV environment

    NASA Astrophysics Data System (ADS)

    Walter-Shea, Elizabeth; Yuen, Gary; Hubbard, Kenneth; Horst, Garald

    2002-01-01

    Phylloplane microorganism survival is presumably affected by ultraviolet radiation (UV) penetrating into plant canopies, but little field data exist relating microorganism population dynamics to canopy UV level. Recent advances in field measurements involving the use of biological dosimeters and miniature radiometers make possible data sets for use in assessing the impact of UV on phylloplane microbe survival. The objective of this study was to compare field survival of a bacterial species, applied to turfgrass as a biological disease control agent, with predicted survival based on the prevailing UV-B environment under natural and attenuated UV conditions. Derived survival curves and radiation penetration equations (based on radiometer and biodosimeter field measurements of UV-B transmittance) were applied to predict bacterial survival within a turfgrass canopy at different leaf area indices. Due to the range in UV levels within a canopy, as indicated by the maximum (sunfleck areas) and minimum (shaded areas) transmitted irradiance values, bacterial survival can vary; predicted bacterial survival based only on average light penetration tended to underestimate survival. Further study should address contributions due to microenvironmental effects (e.g., canopy temperature, leaf wetness, and canopy structure), the spatial distribution of bacterium leaf microsites and bacterium survival on leaf surfaces.

  20. High serum uric acid concentration predicts poor survival in patients with breast cancer.

    PubMed

    Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

    2017-08-26

    Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017. Published by Elsevier B.V.

  1. Survival prediction in Amyotrophic lateral sclerosis based on MRI measures and clinical characteristics.

    PubMed

    Schuster, Christina; Hardiman, Orla; Bede, Peter

    2017-04-17

    Amyotrophic lateral sclerosis (ALS) a highly heterogeneous neurodegenerative condition. Accurate diagnostic, monitoring and prognostic biomarkers are urgently needed both for individualised patient care and clinical trials. A multimodal magnetic resonance imaging study is presented, where MRI measures of ALS-associated brain regions are utilised to predict 18-month survival. A total of 60 ALS patients and 69 healthy controls were included in this study. 20% of the patient sample was utilised as an independent validation sample. Surface-based morphometry and diffusion tensor white matter parameters were used to identify anatomical patterns of neurodegeneration in 80% of the patient sample compared to healthy controls. Binary logistic ridge regressions were carried out to predict 18-month survival based on clinical measures alone, MRI features, and a combination of clinical and MRI data. Clinical indices included age at symptoms onset, site of disease onset, diagnostic delay from first symptom to diagnosis, and physical disability (ALSFRS-r). MRI features included the average cortical thickness of the precentral and paracentral gyri, the average fractional anisotropy, radial-, medial-, and axial diffusivity of the superior and inferior corona radiata, internal capsule, cerebral peduncles and the genu, body and splenium of the corpus callosum. Clinical data alone had a survival prediction accuracy of 66.67%, with 62.50% sensitivity and 70.84% specificity. MRI data alone resulted in a prediction accuracy of 77.08%, with 79.16% sensitivity and 75% specificity. The combination of clinical and MRI measures led to a survival prediction accuracy of 79.17%, with 75% sensitivity and 83.34% specificity. Quantitative MRI measures of ALS-specific brain regions enhance survival prediction in ALS and should be incorporated in future clinical trial designs.

  2. Prediction of Breast Cancer Survival Through Knowledge Discovery in Databases

    PubMed Central

    Afshar, Hadi Lotfnezhad; Ahmadi, Maryam; Roudbari, Masoud; Sadoughi, Farahnaz

    2015-01-01

    The collection of large volumes of medical data has offered an opportunity to develop prediction models for survival by the medical research community. Medical researchers who seek to discover and extract hidden patterns and relationships among large number of variables use knowledge discovery in databases (KDD) to predict the outcome of a disease. The study was conducted to develop predictive models and discover relationships between certain predictor variables and survival in the context of breast cancer. This study is Cross sectional. After data preparation, data of 22,763 female patients, mean age 59.4 years, stored in the Surveillance Epidemiology and End Results (SEER) breast cancer dataset were analyzed anonymously. IBM SPSS Statistics 16, Access 2003 and Excel 2003 were used in the data preparation and IBM SPSS Modeler 14.2 was used in the model design. Support Vector Machine (SVM) model outperformed other models in the prediction of breast cancer survival. Analysis showed SVM model detected ten important predictor variables contributing mostly to prediction of breast cancer survival. Among important variables, behavior of tumor as the most important variable and stage of malignancy as the least important variable were identified. In current study, applying of the knowledge discovery method in the breast cancer dataset predicted the survival condition of breast cancer patients with high confidence and identified the most important variables participating in breast cancer survival. PMID:25946945

  3. High expression of cholesterol biosynthesis genes is associated with resistance to statin treatment and inferior survival in breast cancer

    PubMed Central

    Kimbung, Siker; Lettiero, Barbara; Feldt, Maria; Bosch, Ana; Borgquist, Signe

    2016-01-01

    There is sufficient evidence that statins have a protective role against breast cancer proliferation and recurrence, but treatment predictive biomarkers are lacking. Breast cancer cell lines displaying diverse sensitivity to atorvastatin were subjected to global transcriptional profiling and genes significantly altered by statin treatment were identified. Atorvastatin treatment strongly inhibited proliferation in estrogen receptor (ER) negative cell lines and a commensurate response was also evident on the genome-wide transcriptional scale, with ER negative cells displaying a robust deregulation of genes involved in the regulation of cell cycle progression and apoptosis. Interestingly, atorvastatin upregulated genes involved in the cholesterol biosynthesis pathway in all cell lines, irrespective of sensitivity to statin treatment. However, the level of pathway induction; measured as the fold change in transcript levels, was inversely correlated to the effect of statin treatment on cell growth. High expression of cholesterol biosynthesis genes before treatment was associated with resistance to statin therapy in cell lines and clinical biopsies. Furthermore, high expression of cholesterol biosynthesis genes was independently prognostic for a shorter recurrence-free and overall survival, especially among ER positive tumors. Dysregulation of cholesterol biosynthesis is therefore predictive for both sensitivity to anti-cancer statin therapy and prognosis following primary breast cancer diagnosis. PMID:27458152

  4. Acylcarnitines profile best predicts survival in horses with atypical myopathy.

    PubMed

    Boemer, François; Detilleux, Johann; Cello, Christophe; Amory, Hélène; Marcillaud-Pitel, Christel; Richard, Eric; van Galen, Gaby; van Loon, Gunther; Lefère, Laurence; Votion, Dominique-Marie

    2017-01-01

    Equine atypical myopathy (AM) is caused by hypoglycin A intoxication and is characterized by a high fatality rate. Predictive estimation of survival in AM horses is necessary to prevent unnecessary suffering of animals that are unlikely to survive and to focus supportive therapy on horses with a possible favourable prognosis of survival. We hypothesized that outcome may be predicted early in the course of disease based on the assumption that the acylcarnitine profile reflects the derangement of muscle energetics. We developed a statistical model to prognosticate the risk of death of diseased animals and found that estimation of outcome may be drawn from three acylcarnitines (C2, C10:2 and C18 -carnitines) with a high sensitivity and specificity. The calculation of the prognosis of survival makes it possible to distinguish the horses that will survive from those that will die despite severe signs of acute rhabdomyolysis in both groups.

  5. Relapsed or Refractory Double-Expressor and Double-Hit Lymphomas Have Inferior Progression-Free Survival After Autologous Stem-Cell Transplantation.

    PubMed

    Herrera, Alex F; Mei, Matthew; Low, Lawrence; Kim, Haesook T; Griffin, Gabriel K; Song, Joo Y; Merryman, Reid W; Bedell, Victoria; Pak, Christine; Sun, Heather; Paris, Tanya; Stiller, Tracey; Brown, Jennifer R; Budde, Lihua E; Chan, Wing C; Chen, Robert; Davids, Matthew S; Freedman, Arnold S; Fisher, David C; Jacobsen, Eric D; Jacobson, Caron A; LaCasce, Ann S; Murata-Collins, Joyce; Nademanee, Auayporn P; Palmer, Joycelynne M; Pihan, German A; Pillai, Raju; Popplewell, Leslie; Siddiqi, Tanya; Sohani, Aliyah R; Zain, Jasmine; Rosen, Steven T; Kwak, Larry W; Weinstock, David M; Forman, Stephen J; Weisenburger, Dennis D; Kim, Young; Rodig, Scott J; Krishnan, Amrita; Armand, Philippe

    2017-01-01

    Purpose Double-hit lymphomas (DHLs) and double-expressor lymphomas (DELs) are subtypes of diffuse large B-cell lymphoma (DLBCL) associated with poor outcomes after standard chemoimmunotherapy. Data are limited regarding outcomes of patients with relapsed or refractory (rel/ref) DEL or DHL who undergo autologous stem-cell transplantation (ASCT). We retrospectively studied the prognostic impact of DEL and DHL status on ASCT outcomes in patients with rel/ref DLBCL. Methods Patients with chemotherapy-sensitive rel/ref DLBCL who underwent ASCT at two institutions and in whom archival tumor material was available were enrolled. Immunohistochemistry for MYC, BCL2, and BCL6 and fluorescence in situ hybridization (FISH) for MYC were performed. In cases with MYC rearrangement or copy gain, FISH for BCL2 and BCL6 was also performed. Results A total of 117 patients were included; 44% had DEL and 10% had DHL. DEL and DHL were associated with inferior progression-free survival (PFS), and DHL was associated with poorer overall survival (OS). The 4-year PFS in patients with DEL compared with those with non-DEL was 48% versus 59% ( P = .049), and the 4-year OS was 56% versus 67% ( P = .10); 4-year PFS in patients with DHL compared with those with non-DHL was 28% versus 57% ( P = .013), and 4-year OS was 25% versus 61% ( P = .002). The few patients with concurrent DEL and DHL had a poor outcome (4-year PFS, 0%). In multivariable models, DEL and DHL were independently associated with inferior PFS, whereas DHL and partial response ( v complete response) at transplant were associated with inferior OS. Conclusion DEL and DHL are both associated with inferior outcomes after ASCT in patients with rel/ref DLBCL. Although ASCT remains a potentially curative approach, these patients, particularly those with DHL, are a high-risk subset who should be targeted for investigational strategies other than standard ASCT.

  6. Relapsed or Refractory Double-Expressor and Double-Hit Lymphomas Have Inferior Progression-Free Survival After Autologous Stem-Cell Transplantation

    PubMed Central

    Herrera, Alex F.; Mei, Matthew; Low, Lawrence; Kim, Haesook T.; Griffin, Gabriel K.; Song, Joo Y.; Merryman, Reid W.; Bedell, Victoria; Pak, Christine; Sun, Heather; Paris, Tanya; Stiller, Tracey; Brown, Jennifer R.; Budde, Lihua E.; Chan, Wing C.; Chen, Robert; Davids, Matthew S.; Freedman, Arnold S.; Fisher, David C.; Jacobsen, Eric D.; Jacobson, Caron A.; LaCasce, Ann S.; Murata-Collins, Joyce; Nademanee, Auayporn P.; Palmer, Joycelynne M.; Pihan, German A.; Pillai, Raju; Popplewell, Leslie; Siddiqi, Tanya; Sohani, Aliyah R.; Zain, Jasmine; Rosen, Steven T.; Kwak, Larry W.; Weinstock, David M.; Forman, Stephen J.; Weisenburger, Dennis D.; Kim, Young; Rodig, Scott J.; Krishnan, Amrita

    2017-01-01

    Purpose Double-hit lymphomas (DHLs) and double-expressor lymphomas (DELs) are subtypes of diffuse large B-cell lymphoma (DLBCL) associated with poor outcomes after standard chemoimmunotherapy. Data are limited regarding outcomes of patients with relapsed or refractory (rel/ref) DEL or DHL who undergo autologous stem-cell transplantation (ASCT). We retrospectively studied the prognostic impact of DEL and DHL status on ASCT outcomes in patients with rel/ref DLBCL. Methods Patients with chemotherapy-sensitive rel/ref DLBCL who underwent ASCT at two institutions and in whom archival tumor material was available were enrolled. Immunohistochemistry for MYC, BCL2, and BCL6 and fluorescence in situ hybridization (FISH) for MYC were performed. In cases with MYC rearrangement or copy gain, FISH for BCL2 and BCL6 was also performed. Results A total of 117 patients were included; 44% had DEL and 10% had DHL. DEL and DHL were associated with inferior progression-free survival (PFS), and DHL was associated with poorer overall survival (OS). The 4-year PFS in patients with DEL compared with those with non-DEL was 48% versus 59% (P = .049), and the 4-year OS was 56% versus 67% (P = .10); 4-year PFS in patients with DHL compared with those with non-DHL was 28% versus 57% (P = .013), and 4-year OS was 25% versus 61% (P = .002). The few patients with concurrent DEL and DHL had a poor outcome (4-year PFS, 0%). In multivariable models, DEL and DHL were independently associated with inferior PFS, whereas DHL and partial response (v complete response) at transplant were associated with inferior OS. Conclusion DEL and DHL are both associated with inferior outcomes after ASCT in patients with rel/ref DLBCL. Although ASCT remains a potentially curative approach, these patients, particularly those with DHL, are a high-risk subset who should be targeted for investigational strategies other than standard ASCT. PMID:28034071

  7. Landmark Risk Prediction of Residual Life for Breast Cancer Survival

    PubMed Central

    Parast, Layla; Cai, Tianxi

    2013-01-01

    The importance of developing personalized risk prediction estimates has become increasingly evident in recent years. In general, patient populations may be heterogenous and represent a mixture of different unknown subtypes of disease. When the source of this heterogeneity and resulting subtypes of disease are unknown, accurate prediction of survival may be difficult. However, in certain disease settings the onset time of an observable short term event may be highly associated with these unknown subtypes of disease and thus may be useful in predicting long term survival. One approach to incorporate short term event information along with baseline markers for the prediction of long term survival is through a landmark Cox model, which assumes a proportional hazards model for the residual life at a given landmark point. In this paper, we use this modeling framework to develop procedures to assess how a patient’s long term survival trajectory may change over time given good short term outcome indications along with prognosis based on baseline markers. We first propose time-varying accuracy measures to quantify the predictive performance of landmark prediction rules for residual life and provide resampling-based procedures to make inference about such accuracy measures. Simulation studies show that the proposed procedures perform well in finite samples. Throughout, we illustrate our proposed procedures using a breast cancer dataset with information on time to metastasis and time to death. In addition to baseline clinical markers available for each patient, a chromosome instability genetic score, denoted by CIN25, is also available for each patient and has been shown to be predictive of survival for various types of cancer. We provide procedures to evaluate the incremental value of CIN25 for the prediction of residual life and examine how the residual life profile changes over time. This allows us to identify an informative landmark point, t0, such that accurate risk

  8. Genetic mutational profiling analysis of T cell acute lymphoblastic leukemia reveal mutant FBXW7 as a prognostic indicator for inferior survival.

    PubMed

    Yuan, Lan; Lu, Ling; Yang, Yongchen; Sun, Hengjuan; Chen, Xi; Huang, Yi; Wang, Xingjuan; Zou, Lin; Bao, Liming

    2015-11-01

    T cell acute lymphoblastic leukemia (T-ALL) is an aggressive neoplasm for which there are currently no adequate biomarkers for developing risk-adapted therapeutic regimens to improve the treatment outcome. In this prospective study of 83 Chinese patients (54 children and 29 adults) with de novo T-ALL, we analyzed mutations in 11 T-ALL genes: NOTCH1, FBXW7, PHF6, PTEN, N-RAS, K-RAS, WT1, IL7R, PIK3CA, PIK3RA, and AKT1. NOTCH1 mutations were identified in 51.9 and 37.9 % of pediatric and adult patients, respectively, and these patients showed improved overall survival (OS) and event-free survival (EFS). The FBXW7 mutant was present in 25.9 and 6.9 % of pediatric and adult patients, respectively, and was associated with inferior OS and EFS in pediatric T-ALL. Multivariate analysis revealed that mutant FBXW7 was an independent prognostic indicator for inferior EFS (hazard ratio [HR] 4.38; 95 % confidence interval [CI] 1.15-16.71; p = 0.03) and tended to be associated with reduced OS (HR 2.81; 95 % CI 0.91-8.69; p = 0.074) in pediatric T-ALL. Mutant PHF6 was present in 13 and 20.7 % of our childhood and adult cohorts, respectively, while PTEN mutations were noted in 11.1 % of the pediatric patients. PTEN and NOTCH1 mutations were almost mutually exclusive, while IL7R and WT1 mutations were rare in pediatric T-ALL and PTPN11 and AKT1 mutations were infrequent in adult T-ALL. This study revealed differences in the mutational profiles of pediatric and adult T-ALL and suggests mutant FBXW7 as an independent prognostic indicator for inferior survival in pediatric T-ALL.

  9. Prediction of patient survival in cases of acute paraquat poisoning.

    PubMed

    Hong, Sae-Yong; Lee, Ji-Sung; Sun, In O; Lee, Kwang-Young; Gil, Hyo-Wook

    2014-01-01

    Paraquat concentration-time data have been used to predict the clinical outcome following ingestion. However, these studies have included only small populations, although paraquat poisoning has a very high mortality rate. The purpose of this study was to develop a simple and reliable model to predict survival according to the time interval post-ingestion in patients with acute paraquat poisoning. Data were retrospectively collected for patients who were admitted with paraquat poisoning to Soonchunhyang University Choenan Hospital between January 2005 and December 2012. Plasma paraquat levels were measured using high-performance liquid chromatography. To validate the model we developed, we used external data from 788 subjects admitted to the Presbyterian Medical Center, Jeonju, Korea, between January 2007 and December 2012. Two thousand one hundred thirty six patients were included in this study. The overall survival rate was 44% (939/2136). The probability of survival for any specified time and concentration could be predicted as (exp(logit))/(1+exp(logit)), where logit = 1.3544+[-3.4688 × log10(plasma paraquat μg/M[Formula: see text])]+[-2.3169 × log10(hours since ingestion)]. The external validation study showed that our model was highly accurate for the prediction of survival (C statics 0.964; 95% CI [0.952-0.975]). We have developed a model that is effective for predicting survival after paraquat intoxication.

  10. Predicting venous insufficiency in flaps raised on the deep inferior epigastric system using computed tomography (CT) angiography.

    PubMed

    Wagels, M; Pillay, R; Saylor, A; Vrtik, L; Senewiratne, S

    2015-12-01

    Computed Tomography Angiogram (CTA) has become a routine part of pre-operative assessment of vascular anatomy and design in perforator flaps. We conducted a retrospective cohort study of flap raised on the deep inferior epigastric system (DIES) at our institution in order to identify CTA signs that might predict venous congestion in these flaps. 98 consecutive patients who had 124 DIES flaps raised from 2008 to 2012 were studied. Of these 124 flaps, four (3.2%) developed venous congestion. Our results showed that a Superficial Inferior Epigastric Vein (SIEV) that is larger than the DIEV at origin is highly predictive of congestion (5.2 vs 3.5 mm, p = 0.007). The findings of an axial non-arborising superficial system (96.7% vs 0, p < 0.001), without connection to deep system perforators (38.1 vs 88.8%, p < 0.001) and a type I pedicle were also predictive (75 vs 64.2%, p = 0.22). These results show the importance of CTAs as a pre-operative study for the identification of risk factors for venous compromise, and their use should prompt a robust discussion of the risk of flap failure with patients, and contingency planning to augment venous drainage with the superficial system if required. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  11. Predicting survival and morbidity-free survival to very old age

    PubMed Central

    Witteman, Jacqueline C. M.; Franco, Oscar H.; Stricker, Bruno H. C.; Breteler, Monique M. B.; Hofman, Albert; Tiemeier, Henning

    2010-01-01

    As life expectancy continually increases, it is imperative to identify determinants of survival to the extreme end of the lifespan and more importantly to identify factors that increase the chance of survival free of major morbidities. As such, the current study assessed 45 common disease factors as predictors of survival and morbidity-free survival to age 85 years. Within the Rotterdam Study, a population-based cohort, we evaluated morbidity-free participants who were able to attain age 85 within the study duration (n = 2,008). Risk factors were assessed at baseline (1990–1993), and mortality and morbidities were then collected continuously until mortality or the occurrence of their 85th birthday (average time of 7.9 years). Risk factors included demographic and lifestyle variables, health and morbidity indicators and physiological makers. Major morbidities examined included dementia, cancer, cerebrovascular accident, heart failure and myocardial infarction. Logistic regression analyses demonstrated that many of the variables were independently predictive for survival and for morbidity-free ageing to 85 years. These included being female, absence of left ventricular abnormalities, stable body weight, unimpaired instrumental activities of daily living, lower C-RP levels and higher levels of femoral neck bone mineral density and albumin. Relative to non-survival, predictors were stronger for morbidity-free survival than for total survival or survival with morbidity. This suggests that lifespan and healthy survival to older age can be relatively well predicted. Understanding predictors of a long and healthy lifespan is vital for developing primary and secondary preventions to help improve the quality of life of older adults and for reducing the financial burden of the rapidly escalating ageing population. PMID:20514522

  12. Predicting survival in potentially curable lung cancer patients.

    PubMed

    Win, Thida; Sharples, Linda; Groves, Ashley M; Ritchie, Andrew J; Wells, Francis C; Laroche, Clare M

    2008-01-01

    Lung cancer is the most common cause of cancer death with unchanged mortality for 50 years. Only localized nonsmall-cell lung cancer (NSCLC) is curable. In these patients it is essential to accurately predict survival to help identify those that will benefit from treatment and those at risk of relapse. Despite needing this clinical information, prospective data are lacking. We therefore prospectively identified prognostic factors in patients with potentially curable lung cancer. Over 2 years, 110 consecutive patients with confirmed localized NSCLC (stages 1-3A) were recruited from a single tertiary center. Prognostic factors investigated included age, gender, body mass index (BMI), performance status, comorbidity, disease stage, quality of life, and respiratory physiology. Patients were followed up for 3-5 years and mortality recorded. The data were analyzed using survival analysis methods. Twenty-eight patients died within 1 year, 15 patients died within 2 years, and 11 patients died within 3 years postsurgery. Kaplan-Meier survival estimates show a survival rate of 51% at 3 years. Factors significantly (p < 0.05) associated with poor overall survival were age at assessment, diabetes, serum albumin, peak VO(2) max, shuttle walk distance, and predicted postoperative transfer factor. In multiple-variable survival models, the strongest predictors of survival overall were diabetes and shuttle walk distance. The results show that potentially curable lung cancer patients should not be discriminated against with respect to weight and smoking history. Careful attention is required when managing patients with diabetes. Respiratory physiologic measurements were of limited value in predicting long-term survival after lung cancer surgery.

  13. Comparing Three Data Mining Methods to Predict Kidney Transplant Survival

    PubMed Central

    Shahmoradi, Leila; Langarizadeh, Mostafa; Pourmand, Gholamreza; fard, Ziba Aghsaei; Borhani, Alireza

    2016-01-01

    Introduction: One of the most important complications of post-transplant is rejection. Analyzing survival is one of the areas of medical prognosis and data mining, as an effective approach, has the capacity of analyzing and estimating outcomes in advance through discovering appropriate models among data. The present study aims at comparing the effectiveness of C5.0 algorithms, neural network and C&RTree to predict kidney transplant survival before transplant. Method: To detect factors effective in predicting transplant survival, information needs analysis was performed via a researcher-made questionnaire. A checklist was prepared and data of 513 kidney disease patient files were extracted from Sina Urology Research Center. Following CRISP methodology for data mining, IBM SPSS Modeler 14.2, C5.0, C&RTree algorithms and neural network were used. Results: Body Mass Index (BMI), cause of renal dysfunction and duration of dialysis were evaluated in all three models as the most effective factors in transplant survival. C5.0 algorithm with the highest validity (96.77%) was the first in estimating kidney transplant survival in patients followed by C&RTree (83.7%) and neural network (79.5%) models. Conclusion: Among the three models, C5.0 algorithm was the top model with high validity that confirms its strength in predicting survival. The most effective kidney transplant survival factors were detected in this study; therefore, duration of transplant survival (year) can be determined considering the regulations set for a new sample with specific characteristics. PMID:28163356

  14. Predicting survival in pulmonary arterial hypertension in the UK.

    PubMed

    Lee, Wai-Ting Nicola; Ling, Yi; Sheares, Karen K; Pepke-Zaba, Joanna; Peacock, Andrew John; Johnson, Martin Keith

    2012-09-01

    Contemporary prognostic equations in pulmonary arterial hypertension (PAH) derived from US and French cohorts may not perform as well in the UK as a locally derived scoring scheme. The aim of the study was to develop and validate a UK risk score to predict prognosis in PAH. Baseline mortality predictors identified by multivariate Cox analysis in 182 incident PAH patients were used to derive the Scottish composite score (SCS). Its prognostic performance in an independent UK cohort was compared with the French registry and Pulmonary Hypertension Connection (PHC) registry equations using Brier scores (BS). The SCS based on age, sex, aetiology, right atrial pressure, cardiac output and 6-min walk distance predicted survival in the validation cohort (hazard ratio (HR) 1.7 per point increase; p<0.001) and provided further prognostic stratification in World Health Organization (WHO) functional class III patients (HR 1.8 per point increase; p<0.001). It was more accurate than the French registry equation in predicting 1-yr survival (BS: 0.092 versus 0.146; p=0.001) and 2-yr survival (0.131 versus 0.255; p<0.001). There was no significant difference in BS between the SCS and PHC registry equation. The SCS predicts survival and can be used to supplement WHO functional class in prognostication.

  15. Landmark risk prediction of residual life for breast cancer survival.

    PubMed

    Parast, Layla; Cai, Tianxi

    2013-09-10

    The importance of developing personalized risk prediction estimates has become increasingly evident in recent years. In general, patient populations may be heterogenous and represent a mixture of different unknown subtypes of disease. When the source of this heterogeneity and resulting subtypes of disease are unknown, accurate prediction of survival may be difficult. However, in certain disease settings, the onset time of an observable short-term event may be highly associated with these unknown subtypes of disease and thus may be useful in predicting long-term survival. One approach to incorporate short-term event information along with baseline markers for the prediction of long-term survival is through a landmark Cox model, which assumes a proportional hazards model for the residual life at a given landmark point. In this paper, we use this modeling framework to develop procedures to assess how a patient's long-term survival trajectory may change over time given good short-term outcome indications along with prognosis on the basis of baseline markers. We first propose time-varying accuracy measures to quantify the predictive performance of landmark prediction rules for residual life and provide resampling-based procedures to make inference about such accuracy measures. Simulation studies show that the proposed procedures perform well in finite samples. Throughout, we illustrate our proposed procedures by using a breast cancer dataset with information on time to metastasis and time to death. In addition to baseline clinical markers available for each patient, a chromosome instability genetic score, denoted by CIN25, is also available for each patient and has been shown to be predictive of survival for various types of cancer. We provide procedures to evaluate the incremental value of CIN25 for the prediction of residual life and examine how the residual life profile changes over time. This allows us to identify an informative landmark point, t(0) , such that

  16. Long-term follow-up of patients receiving allogeneic stem cell transplant for chronic lymphocytic leukaemia: mixed T-cell chimerism is associated with high relapse risk and inferior survival.

    PubMed

    Thompson, Philip A; Stingo, Francesco; Keating, Michael J; Wierda, William G; O'Brien, Susan M; Estrov, Zeev; Ledesma, Celina; Rezvani, Katayoun; Qazilbash, Muzaffar; Shah, Nina; Parmar, Simrit; Popat, Uday; Anderlini, Paolo; Yago, Nieto; Ciurea, Stefan O; Kebriaei, Partow; Champlin, Richard; Shpall, Elizabeth J; Hosing, Chitra M

    2017-05-01

    There is limited information regarding the immunological predictors of post-allogeneic stem cell transplant (alloSCT) outcome in chronic lymphocytic leukaemia (CLL), such as mixed T-cell chimerism. We analysed 143 consecutive patients with relapsed/refractory CLL, transplanted between 2000 and 2012, to determine the prognostic relevance of mixed chimerism post-alloSCT and the ability of post-transplant immunomodulation to treat relapse. Mixed T-cell chimerism occurred in 50% of patients at 3 months and 43% at 6 months post-alloSCT; upon 3- and 6-month landmark analysis, this was associated with inferior progression-free survival (PFS) [Hazard ratio (HR) 1·93, P = 0·003 and HR 2·58, P < 0·001] and survival (HR 1·66, P = 0·05 and HR 2·17, P < 0·001), independent of baseline patient characteristics, and a lower rate of grade II-IV acute graft-versus-host disease (GHVD) (16% vs. 52%, P < 0·001). Thirty-three patients were treated with immunomodulation for relapse post-alloSCT (immunosuppression withdrawal, n = 6, donor lymphocyte infusion, n = 27); 17 achieved complete response (CR), which predicted superior PFS (53 months vs. 10 months, P < 0·001) and survival (117 months vs. 30 months, P = 0·006). Relapsed patients with mixed chimerism had inferior response to immunomodulation; conversion to full donor chimerism was highly correlated both with CR and with the development of severe acute GVHD, which was fatal in 3/8 patients. Novel therapeutic strategies are required for patients with mixed T-cell chimerism post-alloSCT for CLL. © 2017 John Wiley & Sons Ltd.

  17. Repetition Suppression in the Left Inferior Frontal Gyrus Predicts Tone Learning Performance.

    PubMed

    Asaridou, Salomi S; Takashima, Atsuko; Dediu, Dan; Hagoort, Peter; McQueen, James M

    2016-06-01

    Do individuals differ in how efficiently they process non-native sounds? To what extent do these differences relate to individual variability in sound-learning aptitude? We addressed these questions by assessing the sound-learning abilities of Dutch native speakers as they were trained on non-native tone contrasts. We used fMRI repetition suppression to the non-native tones to measure participants' neuronal processing efficiency before and after training. Although all participants improved in tone identification with training, there was large individual variability in learning performance. A repetition suppression effect to tone was found in the bilateral inferior frontal gyri (IFGs) before training. No whole-brain effect was found after training; a region-of-interest analysis, however, showed that, after training, repetition suppression to tone in the left IFG correlated positively with learning. That is, individuals who were better in learning the non-native tones showed larger repetition suppression in this area. Crucially, this was true even before training. These findings add to existing evidence that the left IFG plays an important role in sound learning and indicate that individual differences in learning aptitude stem from differences in the neuronal efficiency with which non-native sounds are processed.

  18. A computational method for predicting inferior vena cava filter performance on a patient-specific basis.

    PubMed

    Aycock, Kenneth I; Campbell, Robert L; Manning, Keefe B; Sastry, Shankar P; Shontz, Suzanne M; Lynch, Frank C; Craven, Brent A

    2014-08-01

    A computational methodology for simulating virtual inferior vena cava (IVC) filter placement and IVC hemodynamics was developed and demonstrated in two patient-specific IVC geometries: a left-sided IVC and an IVC with a retroaortic left renal vein. An inverse analysis was performed to obtain the approximate in vivo stress state for each patient vein using nonlinear finite element analysis (FEA). Contact modeling was then used to simulate IVC filter placement. Contact area, contact normal force, and maximum vein displacements were higher in the retroaortic IVC than in the left-sided IVC (144 mm(2), 0.47 N, and 1.49 mm versus 68 mm(2), 0.22 N, and 1.01 mm, respectively). Hemodynamics were simulated using computational fluid dynamics (CFD), with four cases for each patient-specific vein: (1) IVC only, (2) IVC with a placed filter, (3) IVC with a placed filter and model embolus, all at resting flow conditions, and (4) IVC with a placed filter and model embolus at exercise flow conditions. Significant hemodynamic differences were observed between the two patient IVCs, with the development of a right-sided jet, larger flow recirculation regions, and lower maximum flow velocities in the left-sided IVC. These results support further investigation of IVC filter placement and hemodynamics on a patient-specific basis.

  19. Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival Prediction

    PubMed Central

    Auslander, Noam; Wagner, Allon; Oberhardt, Matthew; Ruppin, Eytan

    2016-01-01

    Altered cellular metabolism is an important characteristic and driver of cancer. Surprisingly, however, we find here that aggregating individual gene expression using canonical metabolic pathways fails to enhance the classification of noncancerous vs. cancerous tissues and the prediction of cancer patient survival. This supports the notion that metabolic alterations in cancer rewire cellular metabolism through unconventional pathways. Here we present MCF (Metabolic classifier and feature generator), which incorporates gene expression measurements into a human metabolic network to infer new cancer-mediated pathway compositions that enhance cancer vs. adjacent noncancerous tissue classification across five different cancer types. MCF outperforms standard classifiers based on individual gene expression and on canonical human curated metabolic pathways. It successfully builds robust classifiers integrating different datasets of the same cancer type. Reassuringly, the MCF pathways identified lead to metabolites known to be associated with the pertaining specific cancer types. Aggregating gene expression through MCF pathways leads to markedly better predictions of breast cancer patients’ survival in an independent cohort than using the canonical human metabolic pathways (C-index = 0.69 vs. 0.52, respectively). Notably, the survival predictive power of individual MCF pathways strongly correlates with their power in predicting cancer vs. noncancerous samples. The more predictive composite pathways identified via MCF are hence more likely to capture key metabolic alterations occurring in cancer than the canonical pathways characterizing healthy human metabolism. PMID:27673682

  20. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    PubMed Central

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

  1. Predicting the survival of diabetes using neural network

    NASA Astrophysics Data System (ADS)

    Mamuda, Mamman; Sathasivam, Saratha

    2017-08-01

    Data mining techniques at the present time are used in predicting diseases of health care industries. Neural Network is one among the prevailing method in data mining techniques of an intelligent field for predicting diseases in health care industries. This paper presents a study on the prediction of the survival of diabetes diseases using different learning algorithms from the supervised learning algorithms of neural network. Three learning algorithms are considered in this study: (i) The levenberg-marquardt learning algorithm (ii) The Bayesian regulation learning algorithm and (iii) The scaled conjugate gradient learning algorithm. The network is trained using the Pima Indian Diabetes Dataset with the help of MATLAB R2014(a) software. The performance of each algorithm is further discussed through regression analysis. The prediction accuracy of the best algorithm is further computed to validate the accurate prediction

  2. A clinical tool for predicting survival in ALS

    PubMed Central

    Knibb, Jonathan A; Keren, Noa; Kulka, Anna; Leigh, P Nigel; Martin, Sarah; Shaw, Christopher E; Tsuda, Miho; Al-Chalabi, Ammar

    2016-01-01

    Background Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis. Methods 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval. Findings Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median. Interpretation A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors. PMID:27378085

  3. Predicting functional decline and survival in amyotrophic lateral sclerosis.

    PubMed

    Ong, Mei-Lyn; Tan, Pei Fang; Holbrook, Joanna D

    2017-01-01

    Better predictors of amyotrophic lateral sclerosis disease course could enable smaller and more targeted clinical trials. Partially to address this aim, the Prize for Life foundation collected de-identified records from amyotrophic lateral sclerosis sufferers who participated in clinical trials of investigational drugs and made them available to researchers in the PRO-ACT database. In this study, time series data from PRO-ACT subjects were fitted to exponential models. Binary classes for decline in the total score of amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) (fast/slow progression) and survival (high/low death risk) were derived. Data was segregated into training and test sets via cross validation. Learning algorithms were applied to the demographic, clinical and laboratory parameters in the training set to predict ALSFRS-R decline and the derived fast/slow progression and high/low death risk categories. The performance of predictive models was assessed by cross-validation in the test set using Receiver Operator Curves and root mean squared errors. A model created using a boosting algorithm containing the decline in four parameters (weight, alkaline phosphatase, albumin and creatine kinase) post baseline, was able to predict functional decline class (fast or slow) with fair accuracy (AUC = 0.82). However similar approaches to build a predictive model for decline class by baseline subject characteristics were not successful. In contrast, baseline values of total bilirubin, gamma glutamyltransferase, urine specific gravity and ALSFRS-R item score-climbing stairs were sufficient to predict survival class. Using combinations of small numbers of variables it was possible to predict classes of functional decline and survival across the 1-2 year timeframe available in PRO-ACT. These findings may have utility for design of future ALS clinical trials.

  4. Predicting functional decline and survival in amyotrophic lateral sclerosis

    PubMed Central

    Ong, Mei-Lyn; Tan, Pei Fang

    2017-01-01

    Background Better predictors of amyotrophic lateral sclerosis disease course could enable smaller and more targeted clinical trials. Partially to address this aim, the Prize for Life foundation collected de-identified records from amyotrophic lateral sclerosis sufferers who participated in clinical trials of investigational drugs and made them available to researchers in the PRO-ACT database. Methods In this study, time series data from PRO-ACT subjects were fitted to exponential models. Binary classes for decline in the total score of amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) (fast/slow progression) and survival (high/low death risk) were derived. Data was segregated into training and test sets via cross validation. Learning algorithms were applied to the demographic, clinical and laboratory parameters in the training set to predict ALSFRS-R decline and the derived fast/slow progression and high/low death risk categories. The performance of predictive models was assessed by cross-validation in the test set using Receiver Operator Curves and root mean squared errors. Results A model created using a boosting algorithm containing the decline in four parameters (weight, alkaline phosphatase, albumin and creatine kinase) post baseline, was able to predict functional decline class (fast or slow) with fair accuracy (AUC = 0.82). However similar approaches to build a predictive model for decline class by baseline subject characteristics were not successful. In contrast, baseline values of total bilirubin, gamma glutamyltransferase, urine specific gravity and ALSFRS-R item score—climbing stairs were sufficient to predict survival class. Conclusions Using combinations of small numbers of variables it was possible to predict classes of functional decline and survival across the 1–2 year timeframe available in PRO-ACT. These findings may have utility for design of future ALS clinical trials. PMID:28406915

  5. Subliminal enhancement of predictive effects during syntactic processing in the left inferior frontal gyrus: an MEG study

    PubMed Central

    Iijima, Kazuki; Sakai, Kuniyoshi L.

    2014-01-01

    Predictive syntactic processing plays an essential role in language comprehension. In our previous study using Japanese object-verb (OV) sentences, we showed that the left inferior frontal gyrus (IFG) responses to a verb increased at 120–140 ms after the verb onset, indicating predictive effects caused by a preceding object. To further elucidate the automaticity of the predictive effects in the present magnetoencephalography study, we examined whether a subliminally presented verb (“subliminal verb”) enhanced the predictive effects on the sentence-final verb (“target verb”) unconsciously, i.e., without awareness. By presenting a subliminal verb after the object, enhanced predictive effects on the target verb would be detected in the OV sentences when the transitivity of the target verb matched with that of the subliminal verb (“congruent condition”), because the subliminal verb just after the object could determine the grammaticality of the sentence. For the OV sentences under the congruent condition, we observed significantly increased left IFG responses at 140–160 ms after the target verb onset. In contrast, responses in the precuneus and midcingulate cortex (MCC) were significantly reduced for the OV sentences under the congruent condition at 110–140 and 280–300 ms, respectively. By using partial Granger causality analyses for the OV sentences under the congruent condition, we revealed a bidirectional interaction between the left IFG and MCC at 60–160 ms, as well as a significant influence from the MCC to the precuneus. These results indicate that a top-down influence from the left IFG to the MCC, and then to the precuneus, is critical in syntactic decisions, whereas the MCC shares its task-set information with the left IFG to achieve automatic and predictive processes of syntax. PMID:25404899

  6. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

    PubMed

    Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

    2015-09-30

    To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a

  7. Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

    PubMed Central

    Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

    2015-01-01

    To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a

  8. Integrated Cox's model for predicting survival time of glioblastoma multiforme.

    PubMed

    Ai, Zhibing; Li, Longti; Fu, Rui; Lu, Jing-Min; He, Jing-Dong; Li, Sen

    2017-04-01

    Glioblastoma multiforme is the most common primary brain tumor and is highly lethal. This study aims to figure out signatures for predicting the survival time of patients with glioblastoma multiforme. Clinical information, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism array data of patients with glioblastoma multiforme were retrieved from The Cancer Genome Atlas. Patients were separated into two groups by using 1 year as a cutoff, and a logistic regression model was used to figure out any variables that can predict whether the patient was able to live longer than 1 year. Furthermore, Cox's model was used to find out features that were correlated with the survival time. Finally, a Cox model integrated the significant clinical variables, messenger RNA expression, microRNA expression, and single-nucleotide polymorphism was built. Although the classification method failed, signatures of clinical features, messenger RNA expression levels, and microRNA expression levels were figured out by using Cox's model. However, no single-nucleotide polymorphisms related to prognosis were found. The selected clinical features were age at initial diagnosis, Karnofsky score, and race, all of which had been suggested to correlate with survival time. Both of the two significant microRNAs, microRNA-221 and microRNA-222, were targeted to p27(Kip1) protein, which implied the important role of p27(Kip1) on the prognosis of glioblastoma multiforme patients. Our results suggested that survival modeling was more suitable than classification to figure out prognostic biomarkers for patients with glioblastoma multiforme. An integrated model containing clinical features, messenger RNA levels, and microRNA expression levels was built, which has the potential to be used in clinics and thus to improve the survival status of glioblastoma multiforme patients.

  9. Pre-transplant weight loss predicts inferior outcome after allogeneic stem cell transplantation in patients with myelodysplastic syndrome.

    PubMed

    Radujkovic, Aleksandar; Becker, Natalia; Benner, Axel; Penack, Olaf; Platzbecker, Uwe; Stölzel, Friedrich; Bornhäuser, Martin; Hegenbart, Ute; Ho, Anthony D; Dreger, Peter; Luft, Thomas

    2015-10-27

    Allogeneic stem cell transplantation (alloSCT) represents a curative therapeutic option for patients with myelodysplastic syndrome (MDS), but relapse and non-relapse mortality (NRM) limit treatment efficacy. Based on our previous observation in acute myeloid leukemia we investigated the impact of pre-transplant weight loss on post-transplant outcome in MDS patients. A total of 111 patients diagnosed with MDS according to WHO criteria transplanted between 2000 and 2012 in three different transplant centers were included into the analysis. Data on weight loss were collected from medical records prior to conditioning therapy and 3-6 months earlier. Patient, disease and transplant characteristics did not differ between patients with weight loss (2-5%, n = 17; > 5%, n = 17) and those without (n = 77). In a mixed effect model, weight loss was associated with higher risk MDS (p = 0.046). In multivariable analyses, pre-transplant weight loss exceeding 5% was associated with a higher incidence of relapse (p < 0.001) and NRM (p = 0.007). Pre-transplant weight loss of 2-5% and > 5% were independent predictors of worse disease-free (p = 0.023 and p < 0.001, respectively) and overall survival (p = 0.043 and p < 0.001, respectively). Our retrospective study suggests that MDS patients losing weight prior to alloSCT have an inferior outcome after transplantation. Prospective studies addressing pre-transplant nutritional interventions are highly warranted.

  10. Survival Predictions of Ceramic Crowns Using Statistical Fracture Mechanics.

    PubMed

    Nasrin, S; Katsube, N; Seghi, R R; Rokhlin, S I

    2017-01-01

    This work establishes a survival probability methodology for interface-initiated fatigue failures of monolithic ceramic crowns under simulated masticatory loading. A complete 3-dimensional (3D) finite element analysis model of a minimally reduced molar crown was developed using commercially available hardware and software. Estimates of material surface flaw distributions and fatigue parameters for 3 reinforced glass-ceramics (fluormica [FM], leucite [LR], and lithium disilicate [LD]) and a dense sintered yttrium-stabilized zirconia (YZ) were obtained from the literature and incorporated into the model. Utilizing the proposed fracture mechanics-based model, crown survival probability as a function of loading cycles was obtained from simulations performed on the 4 ceramic materials utilizing identical crown geometries and loading conditions. The weaker ceramic materials (FM and LR) resulted in lower survival rates than the more recently developed higher-strength ceramic materials (LD and YZ). The simulated 10-y survival rate of crowns fabricated from YZ was only slightly better than those fabricated from LD. In addition, 2 of the model crown systems (FM and LD) were expanded to determine regional-dependent failure probabilities. This analysis predicted that the LD-based crowns were more likely to fail from fractures initiating from margin areas, whereas the FM-based crowns showed a slightly higher probability of failure from fractures initiating from the occlusal table below the contact areas. These 2 predicted fracture initiation locations have some agreement with reported fractographic analyses of failed crowns. In this model, we considered the maximum tensile stress tangential to the interfacial surface, as opposed to the more universally reported maximum principal stress, because it more directly impacts crack propagation. While the accuracy of these predictions needs to be experimentally verified, the model can provide a fundamental understanding of the

  11. The flatness index of inferior vena cava is useful in predicting hypovolemic shock in severe multiple-injury patients.

    PubMed

    Li, Yang; Zhang, Lian-yang; Wang, Yi; Zhang, Wei-guo

    2013-12-01

    Computed tomography (CT) signs of hypovolemic shock have been reported previously. Whether these signs can be used to clinically predict hypovolemic shock remains unclear. To investigate the predictive value of CT signs for hypovolemic shock in severe multiple-injury patients. The clinical and multi-slice spiral CT (MSCT) data from 63 severe multiple-injury patients admitted to our trauma center from January 2008 to December 2011 were reviewed. The caliber of the inferior vena cava (IVC) and abdominal aorta, and mean CT value of the abdominal organs in both the early and the delayed phases were measured. The patients were divided into two groups, a shock group (n = 34) and a stable group (n = 29), based on the occurrence of hypovolemic shock within 24 h after the CT scan. Receiver operating characteristic curve (ROC) analysis was performed to assess the predictive accuracy of these signs for hypovolemic shock. The shock group, compared to the stable group, had a higher Injury Severity Score (30 ± 8 vs. 22 ± 6, respectively, p < 0.001), shock index (1.17 ± 0.37 vs. 0.96 ± 0.33, respectively, p = 0.019), and lactate level (3.27 ± 0.69 mmol/L vs. 2.56 ± 0.89 mmol/L, respectively, p = 0.001). Among all the CT signs, the flatness index of IVC had the largest area under the curve (0.833) in ROC analysis, with sensitivity of 73.5% and specificity of 86.2%, higher than traditional indices and other CT signs. The optimal diagnostic cutoff value for the flatness index of IVC was 3.02. MSCT can provide useful information for predicting hyovolemic shock in severe multiple-injury patients. An IVC flatness index > 3.02 suggests the presence of hypovolemic shock in severe multiple-injury patients. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Decrease in 1-year Kidney Graft Size Predicts Inferior Outcomes After Deceased Donor Kidney Transplantation.

    PubMed

    Černe, Senka; Arnol, Miha; Kandus, Aljoša; Buturović-Ponikvar, Jadranka

    2016-08-01

    Longest bipolar length of the kidney graft is routinely measured for ultrasonographic assessment of graft size (GS), although the value of the graft length remains unclear. In a single-center, observational study involving 319 deceased-donor kidney transplant recipients, we assessed variations in absolute and adjusted GS (corrected for body surface area) between 1 and 12 months after transplantation ([INCREMENT]GS1m→12m). We tested whether variations in GS during the first year were predictive of the composite outcome of a reduction of 50% or more in the estimated glomerular filtration rate or end-stage graft failure. At 1 year after transplantation, 121 patients (38%) had a decrease in GS ([INCREMENT]GS1m→12m <0), and 198 patients (62%) had an increase in GS ([INCREMENT]GS1m→12m ≥0). After a median follow-up of 53 months, 41 patients with a decrease in GS reached the composite outcome as compared with 12 patients with an increase in GS (34% and 6%, respectively; P < 0.001). Areas under the receiver operating characteristics curves of absolute and adjusted [INCREMENT]GS1m→12m for composite outcome were 0.81 (95% confidence interval [95% CI], 0.74-0.88) and 0.78 (95% CI, 0.70-0.86), respectively. In multivariate analysis, the risk of the composite outcome was significantly higher among patients with a decrease in GS during the first year after transplantation (hazard ratio, 4.55; 95% CI, 2.35-8.81; P < 0.001). A decrease in kidney GS during the first year after transplantation, as compared with an increase in GS, is a powerful predictor of subsequent graft dysfunction or end-stage graft failure.

  13. Machine learning models in breast cancer survival prediction.

    PubMed

    Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

    2016-01-01

    Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

  14. Ex Vivo Perfusion Characteristics of Donation After Cardiac Death Kidneys Predict Long-Term Graft Survival.

    PubMed

    Sevinc, M; Stamp, S; Ling, J; Carter, N; Talbot, D; Sheerin, N

    2016-12-01

    Ex vivo perfusion is used in our unit for kidneys donated after cardiac death (DCD). Perfusion flow index (PFI), resistance, and perfusate glutathione S-transferase (GST) can be measured to assess graft viability. We assessed whether measurements taken during perfusion could predict long-term outcome after transplantation. All DCD kidney transplants performed from 2002 to 2014 were included in this study. The exclusion criteria were: incomplete data, kidneys not machine perfused, kidneys perfused in continuous mode, and dual transplantation. There were 155 kidney transplantations included in the final analysis. Demographic data, ischemia times, donor hypertension, graft function, survival and machine perfusion parameters after 3 hours were analyzed. Each perfusion parameter was divided into 3 groups as high, medium, and low. Estimated glomerular filtration rate was calculated at 12 months and then yearly after transplantation. There was a significant association between graft survival and PFI and GST (P values, .020 and .022, respectively). PFI was the only independent parameter to predict graft survival. A low PFI during ex vivo hypothermic perfusion is associated with inferior graft survival after DCD kidney transplantation. We propose that PFI is a measure of the health of the graft vasculature and that a low PFI indicates vascular disease and therefore predicts a worse long-term outcome. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Survival model construction guided by fit and predictive strength.

    PubMed

    Chauvel, Cécile; O'Quigley, John

    2016-10-05

    Survival model construction can be guided by goodness-of-fit techniques as well as measures of predictive strength. Here, we aim to bring together these distinct techniques within the context of a single framework. The goal is how to best characterize and code the effects of the variables, in particular time dependencies, when taken either singly or in combination with other related covariates. Simple graphical techniques can provide an immediate visual indication as to the goodness-of-fit but, in cases of departure from model assumptions, will point in the direction of a more involved and richer alternative model. These techniques appear to be intuitive. This intuition is backed up by formal theorems that underlie the process of building richer models from simpler ones. Measures of predictive strength are used in conjunction with these goodness-of-fit techniques and, again, formal theorems show that these measures can be used to help identify models closest to the unknown non-proportional hazards mechanism that we can suppose generates the observations. Illustrations from studies in breast cancer show how these tools can be of help in guiding the practical problem of efficient model construction for survival data.

  16. Factors predicting survival in ALS: a multicenter Italian study.

    PubMed

    Calvo, Andrea; Moglia, Cristina; Lunetta, Christian; Marinou, Kalliopi; Ticozzi, Nicola; Ferrante, Gianluca Drago; Scialo, Carlo; Sorarù, Gianni; Trojsi, Francesca; Conte, Amelia; Falzone, Yuri M; Tortelli, Rosanna; Russo, Massimo; Chiò, Adriano; Sansone, Valeria Ada; Mora, Gabriele; Silani, Vincenzo; Volanti, Paolo; Caponnetto, Claudia; Querin, Giorgia; Monsurrò, Maria Rosaria; Sabatelli, Mario; Riva, Nilo; Logroscino, Giancarlo; Messina, Sonia; Fini, Nicola; Mandrioli, Jessica

    2017-01-01

    The aim of this multicenter, retrospective study is to investigate the role of clinical characteristics and therapeutic intervention on ALS prognosis. The study included patients diagnosed from January 1, 2009 to December 31, 2013 in 13 Italian referral centers for ALS located in 10 Italian regions. Caring neurologists collected a detailed phenotypic profile and follow-up data until death into an electronic database. One center collected also data from a population-based registry for ALS. 2648 incident cases were collected. The median survival time from onset to death/tracheostomy was 44 months (SE 1.18, CI 42-46). According to univariate analysis, factors related to survival from onset to death/tracheostomy were: age at onset, diagnostic delay, site of onset, phenotype, degree of certainty at diagnosis according to revised El Escorial criteria (R-EEC), presence/absence of dementia, BMI at diagnosis, patients' provenance. In the multivariate analysis, age at onset, diagnostic delay, phenotypes but not site of onset, presence/absence of dementia, BMI, riluzole use, R-EEC criteria were independent prognostic factors of survival in ALS. We compared patients from an ALS Registry with patients from tertiary centers; the latter ones were younger, less frequently bulbar, but more frequently familial and definite at diagnosis. Our large, multicenter study demonstrated the role of some clinical and demographic factors on ALS survival, and showed some interesting differences between referral centers' patients and the general ALS population. These results can be helpful for clinical practice, in clinical trial design and to validate new tools to predict disease progression.

  17. Does Respiratory Variation in Inferior Vena Cava Diameter Predict Fluid Responsiveness: A Systematic Review and Meta-Analysis.

    PubMed

    Long, Elliot; Oakley, Ed; Duke, Trevor; Babl, Franz E

    2017-05-01

    The aim of fluid resuscitation is to increase stroke volume, yet this effect is observed in only 50% of patients. Prediction of fluid responsiveness may allow fluid resuscitation to be administered to those most likely to benefit. The aim of this study was to systematically review the test characteristics of respiratory variation in inferior vena cava (IVC) diameter as a predictor of fluid responsiveness in patients with acute circulatory failure. Electronic searches combined with reference review of identified studies. Prospective observational studies of all patient groups and ages that used a recognized reference standard, stratified participants into fluid responders and fluid non-responders, and used summary statistics to describe their results were selected for inclusion. Study design, size, setting, patient population, use of mechanical ventilation and tidal volume, definition of fluid responsiveness, fluid challenge strategy, and summary statistics were abstracted. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) domains. Seventeen studies involving 533 patients were included, in whom 253 (47%) were fluid responders. The pooled sensitivity and specificity for a positive IVC ultrasound as a predictor of fluid responsiveness were 0.63 (95% confidence interval [CI]: 0.56-0.69) and 0.73 (95% CI: 0.67-0.78), respectively, with a pooled area under the receiver operating characteristic curve of 0.79 (standard error 0.05). In subgroup analysis, respiratory variation in IVC diameter was a better predictor of fluid responsiveness in mechanically ventilated patients. Respiratory variation in IVC diameter has limited ability to predict fluid responsiveness, particularly in spontaneously ventilating patients. A negative test cannot be used to rule out fluid responsiveness. Clinical context should be taken into account when using IVC ultrasound to help make treatment decisions.

  18. Cardiovascular CT in the diagnosis of pericardial constriction: predictive value of inferior vena cava cross-sectional area.

    PubMed

    Hanneman, Kate; Thavendiranathan, Paaladinesh; Nguyen, Elsie T; Moshonov, Hadas; Paul, Narinder S; Wintersperger, Bernd J; Crean, Andrew M

    2014-01-01

    The diagnosis of pericardial constriction remains challenging. We sought to evaluate the predictive value of cardiovascular CT-based measurements of inferior vena cava (IVC) parameters in the diagnosis of pericardial constriction. Forty-two consecutive patients referred for assessment of pericardial constriction by 64-slice CT were evaluated. The diagnosis of pericardial constriction was confirmed by clinical history, echocardiography, cardiac catheterization, intraoperative findings, histopathology, or a combination. Diameter and cross-sectional area of the suprahepatic IVC and cross-sectional area of the aorta were measured on a single-axial CT image at the level of the esophageal hiatus. Maximum pericardial thickness was measured. Logistic regression and receiver operating curve analyses were performed. Twenty-two patients had pericardial constriction. Mean age of the 42 patients was 57.1 ± 16.4 years, 57.1% were men. IVC diameter, IVC area, the ratio of IVC to aortic area, and pericardial thickness were all significantly greater in patients with constriction than in patients without (P < .05 for all). IVC-to-aortic area ratio had the highest odds ratio (51; 95% CI, 2.8-922) for the prediction of constriction and remained a significant predictor in multivariable analysis. In nested models, IVC-to-aortic area ratio had incremental value over pericardial thickness for the diagnosis of constriction. IVC-to-aortic area ratio discriminated between patients with and without constriction with an area under the curve of 0.88 on receiver operating curve analysis, with a value ≥ 1.6 having a sensitivity and specificity of 95% and 76%, respectively. Interobserver agreement for IVC-to-aortic area ratio was excellent (intraclass correlation coefficient, 0.98). Assessment of IVC-to-aortic area ratio on CT aids with the diagnosis of pericardial constriction and has independent and incremental value over pericardial thickness alone. Crown Copyright © 2014. Published by

  19. Diagnostic value of panoramic radiography in predicting inferior alveolar nerve injury after mandibular third molar extraction: a meta-analysis.

    PubMed

    Liu, W; Yin, W; Zhang, R; Li, J; Zheng, Y

    2015-06-01

    The aim of this study was to evaluate the predictive value of panoramic radiography on inferior alveolar nerve (IAN) injury after extraction of the mandibular third molar. Relevant studies up to 1 June 2014 that discussed the association of panoramic radiography signs and post-mandibular third molar extraction IAN injury were systematically retrieved from the databases of PubMed, Embase, Springerlink, Web of Science and Cochrane library. The effect size of pooled sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR) and diagnostic odds ratio (DOR) with their 95% confidence intervals (CI) were statistically analysed with Meta-disc 1.4 software. Nine articles were included in this meta-analysis. The pooled estimates of sensitivity and specificity were 0.56 (95% CI: 0.50-0.61) and 0.86 (95% CI: 0.84-0.87), respectively. The overall PLR was 3.46 (95% CI: 2.02-5.92) and overall NLR was 0.58 (95% CI: 0.45-0.73). The pooled estimate of DOR was 6.49 (95% CI: 2.92-14.44). The area under the summary receiver operating characteristic curve was 0.7143 ± 0.0604. The meta-analysis indicated that interpretation of panoramic radiography based on darkening of the root had a high specificity in predicting IAN injury after mandibular third molar extraction. However, the ability of this panoramic radiography marker to detect true positive IAN injury was not satisfactory. © 2015 Australian Dental Association.

  20. Predictive role of corneal Q-value differences between nasal–temporal and superior–inferior quadrants in orthokeratology lens decentration

    PubMed Central

    Li, Juan; Yang, Cheng; Xie, Wenjuan; Zhang, Guanrong; Li, Xue; Wang, Shujun; Yang, Xiaohong; Zeng, Jin

    2017-01-01

    Abstract Background: To investigate the association between pretreatment corneal parameters and orthokeratology lens decentration. Methods: This retrospective study included a total of 108 eyes in 60 myopia patients, who were divided into a lens-decentration and a control group. Various pretreatment corneal parameters were analyzed by receiver operating characteristic curves (ROC curves), including corneal horizontal and vertical curvatures, diopter, corneal eccentricity (E-value), asphericity (Q-value), diameter, and astigmatism, to establish a reliable predictive model for orthokeratology lens decentration. Results: The temporal and inferior quadrants are preferential sides for lens decentration, which was associated with the occurrence of complications such as ghosting and corneal epithelial staining. By further analysis, we revealed lower corneal horizontal curvature and much higher corneal Q-value differences between the nasal–temporal and superior–inferior quadrants in the lens-decentration group compared to the control group (P < 0.05). ROC curve analysis showed that the sum of Q-value differences between the nasal–temporal and superior–inferior quadrants was more sensitive than any other corneal parameters in predicting lens decentration, with an area under the curve of 0.778 and a truncation point of 0.3 (P < 0.001). Conclusion: The sum of pretreatment corneal Q-value differences between nasal–temporal and superior–inferior quadrants is a convenient and reliable predictor for orthokeratology lens decentration. PMID:28079814

  1. Interoceptive Ability Predicts Survival on a London Trading Floor.

    PubMed

    Kandasamy, Narayanan; Garfinkel, Sarah N; Page, Lionel; Hardy, Ben; Critchley, Hugo D; Gurnell, Mark; Coates, John M

    2016-09-19

    Interoception is the sensing of physiological signals originating inside the body, such as hunger, pain and heart rate. People with greater sensitivity to interoceptive signals, as measured by, for example, tests of heart beat detection, perform better in laboratory studies of risky decision-making. However, there has been little field work to determine if interoceptive sensitivity contributes to success in real-world, high-stakes risk taking. Here, we report on a study in which we quantified heartbeat detection skills in a group of financial traders working on a London trading floor. We found that traders are better able to perceive their own heartbeats than matched controls from the non-trading population. Moreover, the interoceptive ability of traders predicted their relative profitability, and strikingly, how long they survived in the financial markets. Our results suggest that signals from the body - the gut feelings of financial lore - contribute to success in the markets.

  2. Interoceptive Ability Predicts Survival on a London Trading Floor

    PubMed Central

    Kandasamy, Narayanan; Garfinkel, Sarah N.; Page, Lionel; Hardy, Ben; Critchley, Hugo D.; Gurnell, Mark; Coates, John M.

    2016-01-01

    Interoception is the sensing of physiological signals originating inside the body, such as hunger, pain and heart rate. People with greater sensitivity to interoceptive signals, as measured by, for example, tests of heart beat detection, perform better in laboratory studies of risky decision-making. However, there has been little field work to determine if interoceptive sensitivity contributes to success in real-world, high-stakes risk taking. Here, we report on a study in which we quantified heartbeat detection skills in a group of financial traders working on a London trading floor. We found that traders are better able to perceive their own heartbeats than matched controls from the non-trading population. Moreover, the interoceptive ability of traders predicted their relative profitability, and strikingly, how long they survived in the financial markets. Our results suggest that signals from the body - the gut feelings of financial lore - contribute to success in the markets. PMID:27641692

  3. Can Pre-Retrieval Computed Tomography Predict the Difficult Removal of an Implementing an Inferior Vena Cava Filter?

    PubMed Central

    Hong, Shinho; Park, Keun-Myoung; Jeon, Yong Sun; Cho, Soon Gu; Hong, Kee Chun; Shin, Woo Young; Choe, Yun-Mee

    2016-01-01

    Purpose: Implementing an inferior vena cava (IVC) filter is a relatively safe procedure but potential negative long-term effects. The complications for filter retrieval have been noted. We examined filter characteristics on pre-retrieval computed tomography (CT) that were associated with complicated retrieval (CR) of IVC filters. Materials and Methods: A retrospective review of IVC filter retrievals between January 2008 and June 2014 was performed to identify patients who had undergone a pre-retrieval CT for IVC filter retrieval. CR was defined as the use of nonstandard techniques, procedural time over 30 min, filter fractures, filter tip incorporation into the IVC wall, and retrieval failure. Pre-retrieval CT images were evaluated for tilt angle in the mediolateral and anteroposterior directions, tip embedding into the IVC wall, degree of filter strut perforation, and distance of the filter tip from the nearest renal vein. Results: Of seventy-six patients, twenty-four patients (31.6%) with CRs and 56 patients (73.7%) with non-CR were evaluated for pre-retrieval CT. For IVC filter retrieval with a dwelling time of over 45 days, a tilt of over 15 degrees, the appearance of tip embedding and grade 2 perforation were associated with CR on multivariate analysis. However, for IVC filter retrievals with a dwelling time of less than 45 days, there were no factors associated with CR. Conclusion: Pre-retrieval CTs may be more effective for IVC filters with a dwelling time of over 45 days. Therefore, a pre-retrieval CT may be helpful in predicting CR of IVC filters with long dwelling times. PMID:28042557

  4. Long-term survival of patients with hepatocellular carcinoma with inferior vena cava tumor thrombus treated with sorafenib combined with transarterial chemoembolization: report of two cases and literature review

    PubMed Central

    Gao, Heng-Jun; Xu, Li; Zhang, Yao-Jun; Chen, Min-Shan

    2014-01-01

    The prognosis of hepatocellular carcinoma (HCC) with tumor thrombus formation in the main vasculature is extremely poor. Sorafenib combined with transarterial chemoembolization is a novel treatment approach for advanced HCC. In this study, we report two HCC patients with inferior vena cava tumor thrombus who underwent the combination treatment. The overall survival times for these two patients were 44 months and 35 months, respectively. Our report suggests that sorafenib combined with transarterial chemoembolization may be a viable choice for patients with advanced HCC even with inferior vena cava tumor thrombus. Further studies are required to verify the efficacy and safety of this combination therapy for patients with advanced HCC with inferior vena cava tumor thrombus. PMID:24325788

  5. A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study.

    PubMed

    Yoo, Kyung Don; Noh, Junhyug; Lee, Hajeong; Kim, Dong Ki; Lim, Chun Soo; Kim, Young Hoon; Lee, Jung Pyo; Kim, Gunhee; Kim, Yon Su

    2017-08-21

    Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, to build new prediction models of graft survival that included immunological factors, as well as known recipient and donor variables. Graft survival was estimated from a retrospective analysis of the data from a multicenter cohort of 3,117 kidney transplant recipients. We evaluated the predictive power of ensemble learning algorithms (survival decision tree, bagging, random forest, and ridge and lasso) and compared outcomes to those of conventional models (decision tree and Cox regression). Using a conventional decision tree model, the 3-month serum creatinine level post-transplant (cut-off, 1.65 mg/dl) predicted a graft failure rate of 77.8% (index of concordance, 0.71). Using a survival decision tree model increased the index of concordance to 0.80, with the episode of acute rejection during the first year post-transplant being associated with a 4.27-fold increase in the risk of graft failure. Our study revealed that early acute rejection in the first year is associated with a substantially increased risk of graft failure. Machine learning methods may provide versatile and feasible tools for forecasting graft survival.

  6. Sensitivity, Specificity, Predictive Values, and Accuracy of Three Diagnostic Tests to Predict Inferior Alveolar Nerve Blockade Failure in Symptomatic Irreversible Pulpitis.

    PubMed

    Chavarría-Bolaños, Daniel; Rodríguez-Wong, Laura; Noguera-González, Danny; Esparza-Villalpando, Vicente; Montero-Aguilar, Mauricio; Pozos-Guillén, Amaury

    2017-01-01

    The inferior alveolar nerve block (IANB) is the most common anesthetic technique used on mandibular teeth during root canal treatment. Its success in the presence of preoperative inflammation is still controversial. The aim of this study was to evaluate the sensitivity, specificity, predictive values, and accuracy of three diagnostic tests used to predict IANB failure in symptomatic irreversible pulpitis (SIP). A cross-sectional study was carried out on the mandibular molars of 53 patients with SIP. All patients received a single cartridge of mepivacaine 2% with 1 : 100000 epinephrine using the IANB technique. Three diagnostic clinical tests were performed to detect anesthetic failure. Anesthetic failure was defined as a positive painful response to any of the three tests. Sensitivity, specificity, predictive values, accuracy, and ROC curves were calculated and compared and significant differences were analyzed. IANB failure was determined in 71.7% of the patients. The sensitivity scores for the three tests (lip numbness, the cold stimuli test, and responsiveness during endodontic access) were 0.03, 0.35, and 0.55, respectively, and the specificity score was determined as 1 for all of the tests. Clinically, none of the evaluated tests demonstrated a high enough accuracy (0.30, 0.53, and 0.68 for lip numbness, the cold stimuli test, and responsiveness during endodontic access, resp.). A comparison of the areas under the curve in the ROC analyses showed statistically significant differences between the three tests (p < 0.05). None of the analyzed tests demonstrated a high enough accuracy to be considered a reliable diagnostic tool for the prediction of anesthetic failure.

  7. Sensitivity, Specificity, Predictive Values, and Accuracy of Three Diagnostic Tests to Predict Inferior Alveolar Nerve Blockade Failure in Symptomatic Irreversible Pulpitis

    PubMed Central

    Rodríguez-Wong, Laura; Noguera-González, Danny; Esparza-Villalpando, Vicente; Montero-Aguilar, Mauricio

    2017-01-01

    Introduction The inferior alveolar nerve block (IANB) is the most common anesthetic technique used on mandibular teeth during root canal treatment. Its success in the presence of preoperative inflammation is still controversial. The aim of this study was to evaluate the sensitivity, specificity, predictive values, and accuracy of three diagnostic tests used to predict IANB failure in symptomatic irreversible pulpitis (SIP). Methodology A cross-sectional study was carried out on the mandibular molars of 53 patients with SIP. All patients received a single cartridge of mepivacaine 2% with 1 : 100000 epinephrine using the IANB technique. Three diagnostic clinical tests were performed to detect anesthetic failure. Anesthetic failure was defined as a positive painful response to any of the three tests. Sensitivity, specificity, predictive values, accuracy, and ROC curves were calculated and compared and significant differences were analyzed. Results IANB failure was determined in 71.7% of the patients. The sensitivity scores for the three tests (lip numbness, the cold stimuli test, and responsiveness during endodontic access) were 0.03, 0.35, and 0.55, respectively, and the specificity score was determined as 1 for all of the tests. Clinically, none of the evaluated tests demonstrated a high enough accuracy (0.30, 0.53, and 0.68 for lip numbness, the cold stimuli test, and responsiveness during endodontic access, resp.). A comparison of the areas under the curve in the ROC analyses showed statistically significant differences between the three tests (p < 0.05). Conclusion None of the analyzed tests demonstrated a high enough accuracy to be considered a reliable diagnostic tool for the prediction of anesthetic failure. PMID:28694714

  8. Loss of H3K27 tri-methylation is a diagnostic marker for malignant peripheral nerve sheath tumors and an indicator for an inferior survival.

    PubMed

    Cleven, Arjen H G; Sannaa, Ghadah A Al; Briaire-de Bruijn, Inge; Ingram, Davis R; van de Rijn, Matt; Rubin, Brian P; de Vries, Maurits W; Watson, Kelsey L; Torres, Kelia E; Wang, Wei-Lien; van Duinen, Sjoerd G; Hogendoorn, Pancras C W; Lazar, Alexander J; Bovée, Judith V M G

    2016-06-01

    Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas that can show overlapping features with benign neurofibromas as well as high-grade sarcomas. Additional diagnostic markers are needed to aid in this often challenging differential diagnosis. Recently mutations in two critical components of the polycomb repressor 2 (PRC2) complex, SUZ12 and EED, were reported to occur specifically in MPNSTs while such mutations are absent in neurofibromas, both in the setting of neurofibromatosis (NF) and sporadic cases. Furthermore, both SUZ12 and EED mutations in MPNSTs were associated with loss of H3K27 tri-methylation, a downstream target of PRC2. Therefore, we tested whether H3K27me3 immunohistochemistry is useful as a diagnostic and prognostic marker for MPNSTs. We performed H3K27me3 immunohistochemistry in 162 primary MPNSTs, 97 neurofibromas and 341 other tumors using tissue microarray. We observed loss of H3K27me3 in 34% (55/162) of all MPNSTs while expression was retained in all neurofibromas including atypical (n=8) and plexiform subtypes (n=24). Within other tumors we detected loss of H3K27me3 in only 7% (24/341). Surprisingly, 60% (9/15) of synovial sarcomas and 38% (3/8) of fibrosarcomatous dermatofibrosarcoma protuberans (DFSP) showed loss of H3K27 trimethylation. Only 1 out of 44 schwannomas showed loss of H3K27me3 and all 4 perineuriomas showed intact H3K27me3. Furthermore, MPNSTs with loss of H3K27 tri-methylation showed inferior survival compared with MPNSTs with intact H3K27 tri-methylation, which was validated in two independent cohorts. Our results indicate that H3K27me3 immunohistochemistry is useful as a diagnostic marker, in which loss of H3K27me3 favors MPNST above neurofibroma. However, H3K27me3 immunohistochemistry is not suitable to distinguish MPNST from its morphological mimicker synovial sarcoma or fibrosarcomatous DFSP. Since loss of H3K27 tri-methylation was related to poorer survival in MPNST, chromatin modification mediated

  9. Accuracy of predictive ability measures for survival models.

    PubMed

    Flandre, Philippe; Deutsch, Reena; O'Quigley, John

    2017-09-10

    One aspect of an analysis of survival data based on the proportional hazards model that has been receiving increasing attention is that of the predictive ability or explained variation of the model. A number of contending measures have been suggested, including one measure, R(2) (β), which has been proposed given its several desirable properties, including its capacity to accommodate time-dependent covariates, a major feature of the model and one that gives rise to great generality. A thorough study of the properties of available measures, including the aforementioned measure, has been carried out recently. In that work, the authors used bootstrap techniques, particularly complex in the setting of censored data, in order to obtain estimates of precision. The motivation of this work is to provide analytical expressions of precision, in particular confidence interval estimates for R(2) (β). We use Taylor series approximations with and without local linearizing transforms. We also consider a very simple expression based on the Fisher's transformation. This latter approach has two great advantages. It is very easy and quick to calculate, and secondly, it can be obtained for any of the methods given in the recent review. A large simulation study is carried out to investigate the properties of the different methods. Finally, three well-known datasets in breast cancer, lymphoma and lung cancer research are given as illustrations. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  10. Survival outcomes scores (SOFT, BAR, and Pedi-SOFT) are accurate in predicting post-liver transplant survival in adolescents.

    PubMed

    Conjeevaram Selvakumar, Praveen Kumar; Maksimak, Brian; Hanouneh, Ibrahim; Youssef, Dalia H; Lopez, Rocio; Alkhouri, Naim

    2016-09-01

    SOFT and BAR scores utilize recipient, donor, and graft factors to predict the 3-month survival after LT in adults (≥18 years). Recently, Pedi-SOFT score was developed to predict 3-month survival after LT in young children (≤12 years). These scoring systems have not been studied in adolescent patients (13-17 years). We evaluated the accuracy of these scoring systems in predicting the 3-month post-LT survival in adolescents through a retrospective analysis of data from UNOS of patients aged 13-17 years who received LT between 03/01/2002 and 12/31/2012. Recipients of combined organ transplants, donation after cardiac death, or living donor graft were excluded. A total of 711 adolescent LT recipients were included with a mean age of 15.2±1.4 years. A total of 100 patients died post-LT including 33 within 3 months. SOFT, BAR, and Pedi-SOFT scores were all found to be good predictors of 3-month post-transplant survival outcome with areas under the ROC curve of 0.81, 0.80, and 0.81, respectively. All three scores provided good accuracy for predicting 3-month survival post-LT in adolescents and may help clinical decision making to optimize survival rate and organ utilization. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Survival outcomes following liver transplantation (SOFT) score: a novel method to predict patient survival following liver transplantation.

    PubMed

    Rana, A; Hardy, M A; Halazun, K J; Woodland, D C; Ratner, L E; Samstein, B; Guarrera, J V; Brown, R S; Emond, J C

    2008-12-01

    It is critical to balance waitlist mortality against posttransplant mortality. Our objective was to devise a scoring system that predicts recipient survival at 3 months following liver transplantation to complement MELD-predicted waitlist mortality. Univariate and multivariate analysis on 21,673 liver transplant recipients identified independent recipient and donor risk factors for posttransplant mortality. A retrospective analysis conducted on 30,321 waitlisted candidates reevaluated the predictive ability of the Model for End-Stage Liver Disease (MELD) score. We identified 13 recipient factors, 4 donor factors and 2 operative factors (warm and cold ischemia) as significant predictors of recipient mortality following liver transplantation at 3 months. The Survival Outcomes Following Liver Transplant (SOFT) Score utilized 18 risk factors (excluding warm ischemia) to successfully predict 3-month recipient survival following liver transplantation. This analysis represents a study of waitlisted candidates and transplant recipients of liver allografts after the MELD score was implemented. Unlike MELD, the SOFT score can accurately predict 3-month survival following liver transplantation. The most significant risk factors were previous transplantation and life support pretransplant. The SOFT score can help clinicians determine in real time which candidates should be transplanted with which allografts. Combined with MELD, SOFT can better quantify survival benefit for individual transplant procedures.

  12. The accuracy of clinicians' predictions of survival in advanced cancer: a review.

    PubMed

    Cheon, Stephanie; Agarwal, Arnav; Popovic, Marko; Milakovic, Milica; Lam, Michael; Fu, Wayne; DiGiovanni, Julia; Lam, Henry; Lechner, Breanne; Pulenzas, Natalie; Chow, Ronald; Chow, Edward

    2016-01-01

    The process of formulating an accurate survival prediction is often difficult but important, as it influences the decisions of clinicians, patients, and their families. The current article aims to review the accuracy of clinicians' predictions of survival (CPS) in advanced cancer patients. A literature search of Cochrane CENTRAL, EMBASE, and MEDLINE was conducted to identify studies that reported clinicians' prediction of survival in advanced cancer patients. Studies were included if the subjects consisted of advanced cancer patients and the data reported on the ability of clinicians to predict survival, with both estimated and observed survival data present. Studies reporting on the ability of biological and molecular markers to predict survival were excluded. Fifteen studies that met the inclusion and exclusion criteria were identified. Clinicians in five studies underestimated patients' survival (estimated to observed survival ratio between 0.5 and 0.92). In contrast, 12 studies reported clinicians' overestimation of survival (ratio between 1.06 and 6). CPS in advanced cancer patients is often inaccurate and overestimated. Given these findings, clinicians should be aware of their tendency to be overoptimistic. Further investigation of predictive patient and clinician characteristics is warranted to improve clinicians' ability to predict survival.

  13. Camouflage predicts survival in ground-nesting birds

    PubMed Central

    Troscianko, Jolyon; Wilson-Aggarwal, Jared; Stevens, Martin; Spottiswoode, Claire N.

    2016-01-01

    Evading detection by predators is crucial for survival. Camouflage is therefore a widespread adaptation, but despite substantial research effort our understanding of different camouflage strategies has relied predominantly on artificial systems and on experiments disregarding how camouflage is perceived by predators. Here we show for the first time in a natural system, that survival probability of wild animals is directly related to their level of camouflage as perceived by the visual systems of their main predators. Ground-nesting plovers and coursers flee as threats approach, and their clutches were more likely to survive when their egg contrast matched their surrounds. In nightjars – which remain motionless as threats approach – clutch survival depended on plumage pattern matching between the incubating bird and its surrounds. Our findings highlight the importance of pattern and luminance based camouflage properties, and the effectiveness of modern techniques in capturing the adaptive properties of visual phenotypes. PMID:26822039

  14. Predicting survival time for metastatic castration resistant prostate cancer: An iterative imputation approach

    PubMed Central

    Deng, Detian; Du, Yu; Ji, Zhicheng; Rao, Karthik; Wu, Zhenke; Zhu, Yuxin; Coley, R. Yates

    2016-01-01

    In this paper, we present our winning method for survival time prediction in the 2015 Prostate Cancer DREAM Challenge, a recent crowdsourced competition focused on risk and survival time predictions for patients with metastatic castration-resistant prostate cancer (mCRPC). We are interested in using a patient's covariates to predict his or her time until death after initiating standard therapy. We propose an iterative algorithm to multiply impute right-censored survival times and use ensemble learning methods to characterize the dependence of these imputed survival times on possibly many covariates. We show that by iterating over imputation and ensemble learning steps, we guide imputation with patient covariates and, subsequently, optimize the accuracy of survival time prediction. This method is generally applicable to time-to-event prediction problems in the presence of right-censoring. We demonstrate the proposed method's performance with training and validation results from the DREAM Challenge and compare its accuracy with existing methods. PMID:28299176

  15. Metabolic tumor volume of primary tumor predicts survival better than T classification in the larynx preservation approach.

    PubMed

    Miyabe, Junji; Hanamoto, Atsushi; Tatsumi, Mitsuaki; Hamasaki, Toshimitsu; Takenaka, Yukinori; Nakahara, Susumu; Kishikawa, Toshihiro; Suzuki, Motoyuki; Takemoto, Norihiko; Michiba, Takahiro; Yoshioka, Yasuo; Isohashi, Fumiaki; Konishi, Koji; Ogawa, Kazuhiko; Hatazawa, Jun; Inohara, Hidenori

    2017-10-01

    We aimed to determine whether pretreatment metabolic tumor volume of the primary tumor (T-MTV) or T classification would be a better predictor of laryngectomy-free survival (LFS) and overall survival (OS) after chemoradiotherapy in patients with locally advanced laryngeal or hypopharyngeal cancer requiring total laryngectomy. We analyzed 85 patients using a Cox proportional hazards model and evaluated its usefulness by Akaike's information criterion. A T-MTV cut-off value was determined by time-dependent receiver operating characteristic curve analysis. Interobserver reliability for measuring T-MTV was estimated by the intraclass correlation coefficient (ICC). After adjustment for covariables, T-MTV, irrespective of whether a continuous or dichotomized variable, and T classification remained independent predictors of LFS and OS. Large T-MTV (>28.7 mL) was associated with inferior LFS (hazard ratio [HR], 4.16; 95% confidence interval [CI], 1.97-8.70; P = 0.0003) and inferior OS (HR, 3.18; 95% CI, 1.47-6.69; P = 0.004) compared with small T-MTV (≤28.7 mL). The T-MTV model outperformed the T classification model in predicting LFS and OS (P = 0.007 and 0.01, respectively). Three-year LFS and OS rates for patients with small versus large T-MTV were 68% vs 9% (P < 0.0001) and 77% vs 25% (P < 0.0001), respectively, whereas those for patients with T2-T3 versus T4a were 61% vs 31% (P = 0.003) and 71% vs 48% (P = 0.10), respectively. ICC was 0.99 (95% CI, 0.99-1.00). Given the excellent interobserver reliability, T-MTV is better than T classification to identify patients who would benefit from the larynx preservation approach. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  16. IGFBP2 expression predicts IDH-mutant glioma patient survival.

    PubMed

    Huang, Lin Eric; Cohen, Adam L; Colman, Howard; Jensen, Randy L; Fults, Daniel W; Couldwell, William T

    2017-01-03

    Mutations of the isocitrate dehydrogenase (IDH) 1 and 2 genes occur in ~80% of lower-grade (WHO grade II and grade III) gliomas. Mutant IDH produces (R)-2-hydroxyglutarate, which induces DNA hypermethylation and presumably drives tumorigenesis. Interestingly, IDH mutations are associated with improved survival in glioma patients, but the underlying mechanism for the difference in survival remains unclear. Through comparative analyses of 286 cases of IDH-wildtype and IDH-mutant lower-grade glioma from a TCGA data set, we report that IDH-mutant gliomas have increased expression of tumor-suppressor genes (NF1, PTEN, and PIK3R1) and decreased expression of oncogenes(AKT2, ARAF, ERBB2, FGFR3, and PDGFRB) and glioma progression genes (FOXM1, IGFBP2, and WWTR1) compared with IDH-wildtype gliomas. Furthermore, each of these genes is prognostic in overall gliomas; however, within the IDH-mutant group, none remains prognostic except IGFBP2 (encodinginsulin-like growth factor binding protein 2). Through validation in an independent cohort, we show that patients with low IGFBP2 expressiondisplay a clear advantage in overall and disease-free survival, whereas those with high IGFBP2 expressionhave worse median survival than IDH-wildtype patients. These observations hold true across different histological and molecular subtypes of lower-grade glioma. We propose therefore that an unexpected biological consequence of IDH mutations in glioma is to ameliorate patient survival by promoting tumor-suppressor signaling while inhibiting that of oncogenes, particularly IGFBP2.

  17. Usefulness of ultrasonographic measurement of the diameter of the inferior vena cava to predict responsiveness to intravascular fluid administration in patients with cancer

    PubMed Central

    Arredondo-Armenta, Juan M.; Guevara-García, Humberto; Barragán-Dessavre, Mireya; García-Guillén, Francisco J.; Sánchez-Hurtado, Luis A.; Córdova-Sánchez, Bertha; Bautista-Ocampo, Andoreni R.; Herrera-Gómez, Angel; Meneses-García, Abelardo

    2016-01-01

    We conducted an observational, longitudinal prospective study in which we measured the diameters of the inferior vena cava (IVC) of 47 patients using ultrasonography. The aim of our study was to assess the state of blood volume and to determine the percentage of patients who responded to intravascular volume expansion. Only 17 patients (36%) responded to fluid management. A higher number of responding patients had cardiovascular failure compared with nonresponders (82% vs. 50%, P = 0.03). Among the patients with cardiovascular failure, the probability of finding responders was 4.6 times higher than that of not finding responders (odds ratio, 4.66; 95% confidence interval, 1.10–19.6; P = 0.04). No significant difference was observed in the mortality rate between the two groups (11% vs. 23%, P = 0.46). In conclusion, responding to intravascular volume expansion had no impact on patient survival in the intensive care unit. PMID:27695165

  18. Comparison between respiratory changes in the inferior vena cava diameter and pulse pressure variation to predict fluid responsiveness in postoperative patients.

    PubMed

    de Oliveira, Olivia Haun; Freitas, Flávio Geraldo Rezende de; Ladeira, Renata Teixeira; Fischer, Claudio Henrique; Bafi, Antônio Tonete; Azevedo, Luciano Cesar Pontes; Machado, Flávia Ribeiro

    2016-08-01

    The objective of our study was to assess the reliability of the distensibility index of the inferior vena cava (dIVC) as a predictor of fluid responsiveness in postoperative, mechanically ventilated patients and compare its accuracy with that of the pulse pressure variation (PPV) measurement. We included postoperative mechanically ventilated and sedated patients who underwent volume expansion with 500mL of crystalloids over 15minutes. A response to fluid infusion was defined as a 15% increase in the left ventricular outflow tract velocity time integral according to transthoracic echocardiography. The inferior vena cava diameters were recorded by a subcostal view using the M-mode and the PPV by automatic calculation. The receiver operating characteristic (ROC) curves were generated for the baseline dIVC and PPV. Twenty patients were included. The area under the ROC curve for dIVC was 0.84 (95% confidence interval, 0.63-1.0), and the best cutoff value was 16% (sensitivity, 67%; specificity, 100%). The area under the ROC curve for PPV was 0.92 (95% confidence interval, 0.76-1.0), and the best cutoff was 12.4% (sensitivity, 89%; specificity, 100%). A noninferiority test showed that dIVC cannot replace PPV to predict fluid responsiveness (P=.28). The individual PPV discriminative properties for predicting fluid responsiveness in postoperative patients seemed superior to those of dIVC. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. IGFBP2 expression predicts IDH-mutant glioma patient survival

    PubMed Central

    Huang, Lin Eric; Cohen, Adam L.; Colman, Howard; Jensen, Randy L.; Fults, Daniel W.; Couldwell, William T.

    2017-01-01

    Mutations of the isocitrate dehydrogenase (IDH) 1 and 2 genes occur in ~80% of lower-grade (WHO grade II and grade III) gliomas. Mutant IDH produces (R)-2-hydroxyglutarate, which induces DNA hypermethylation and presumably drives tumorigenesis. Interestingly, IDH mutations are associated with improved survival in glioma patients, but the underlying mechanism for the difference in survival remains unclear. Through comparative analyses of 286 cases of IDH-wildtype and IDH-mutant lower-grade glioma from a TCGA data set, we report that IDH-mutant gliomas have increased expression of tumor-suppressor genes (NF1, PTEN, and PIK3R1) and decreased expression of oncogenes(AKT2, ARAF, ERBB2, FGFR3, and PDGFRB) and glioma progression genes (FOXM1, IGFBP2, and WWTR1) compared with IDH-wildtype gliomas. Furthermore, each of these genes is prognostic in overall gliomas; however, within the IDH-mutant group, none remains prognostic except IGFBP2 (encodinginsulin-like growth factor binding protein 2). Through validation in an independent cohort, we show that patients with low IGFBP2 expressiondisplay a clear advantage in overall and disease-free survival, whereas those with high IGFBP2 expressionhave worse median survival than IDH-wildtype patients. These observations hold true across different histological and molecular subtypes of lower-grade glioma. We propose therefore that an unexpected biological consequence of IDH mutations in glioma is to ameliorate patient survival by promoting tumor-suppressor signaling while inhibiting that of oncogenes, particularly IGFBP2. PMID:27852048

  20. [Systemic lupus erythematosus. 2. Factors of predictive significance for survival].

    PubMed

    Halberg, P; Bendixen, G; Fugleberg, S; Jørgensen, F; Kriegbaum, N J; Lorenzen, I; Müller, K; Olesen, K M; Rasmussen, E; Ullman, S

    1991-06-10

    Sixty-one of 173 patients with systemic lupus erythematosus followed for a mean of 13.9 years had severe infections which influenced their survival more than could be accounted for by the mortality (20 per cent) caused by the infections. Patients with infections had more SLE manifestations than patients without infections, and they died of lupus manifestations more often than patients without infections. Patients who went into a permanent remission and patients who died of lupus differed most markedly by the rates of infection. The rate of infection was increased more than tenfold in patients treated with high dosages of glucocorticoid compared with patients who received low dosages. Treatment with cytostatics influenced the rate of infections to a moderate degree. Nephropathy also influenced survival but half of the patients with nephropathy maintained a normal plasma creatinine in spite of the long observation period. 16 per cent of the patients with nephropathy died of kidney failure or are receiving chronic hemodialysis.

  1. Application of Artificial Neural Network in Predicting the Survival Rate of Gastric Cancer Patients

    PubMed Central

    Biglarian, A; Hajizadeh, E; Kazemnejad, A; Zali, MR

    2011-01-01

    Background: The aim of this study was to predict the survival rate of Iranian gastric cancer patients using the Cox proportional hazard and artificial neural network models as well as comparing the ability of these approaches in predicting the survival of these patients. Methods: In this historical cohort study, the data gathered from 436 registered gastric cancer patients who have had surgery between 2002 and 2007 at the Taleghani Hospital (a referral center for gastrointestinal cancers), Tehran, Iran, to predict the survival time using Cox proportional hazard and artificial neural network techniques. Results: The estimated one-year, two-year, three-year, four-year and five-year survival rates of the patients were 77.9%, 53.1%, 40.8%, 32.0%, and 17.4%, respectively. The Cox regression analysis revealed that the age at diagnosis, high-risk behaviors, extent of wall penetration, distant metastasis and tumor stage were significantly associated with the survival rate of the patients. The true prediction of neural network was 83.1%, and for Cox regression model, 75.0%. Conclusion: The present study shows that neural network model is a more powerful statistical tool in predicting the survival rate of the gastric cancer patients compared to Cox proportional hazard regression model. Therefore, this model recommended for the predicting the survival rate of these patients. PMID:23113076

  2. Alcohol abstinence in patients surviving an episode of alcoholic hepatitis: Prediction and impact on long-term survival.

    PubMed

    Altamirano, José; López-Pelayo, Hugo; Michelena, Javier; Jones, Patricia D; Ortega, Lluisa; Ginès, Pere; Caballería, Juan; Gual, Antoni; Bataller, Ramón; Lligoña, Anna

    2017-06-23

    Alcoholic hepatitis (AH) is the most severe form of alcoholic liver disease. Most studies have focused on short-term prognosis, while factors associated with long-term survival are largely unknown. 1) to determine the impact of complete abstinence from alcohol on long-term survival and 2) to identify prognostic factors at admission capable of predicting abstinence during long-term follow-up in patients with AH. One hundred and forty-two patients with biopsy-proven AH that survived the first episode were included. Demographic, psychiatric and biochemical variables at admission and drinking status during follow-up were obtained. Cox regression, logistic regression and classification and regression trees (CART) analyses were used for statistical analysis. Overall mortality was 38% with a median follow-up of 55 months. During follow-up, complete abstinence was reported in 39% and was associated with better long-term survival (HR 0.53; p=0.03). After adjustment for baseline prognostic scoring systems (MELD and ABIC scores), complete abstinence was independently associated with survival (p<0.05). Age and lack of prior alcoholism treatments were independently associated with complete abstinence (p<0.001 and p=0.02, respectively) during follow-up. CART analysis generated a simple and practical algorithm based-on the combination of prior alcoholism treatments and age. Using CART analysis we stratified 2 subgroups of patients with high (65%) and low (26-29%) rates of complete abstinence after an episode of AH. Complete abstinence after an episode of AH positively impacts long-term survival. The combination of 2 variables easily obtained at admission might be useful to predict long-term abstinence after an episode of AH. Strategies aimed at promoting alcohol abstinence in these patients are mandatory. This article is protected by copyright. All rights reserved. © 2017 by the American Association for the Study of Liver Diseases.

  3. Sarcopenia predicts survival outcomes among patients with urothelial carcinoma of the upper urinary tract undergoing radical nephroureterectomy: a retrospective multi-institution study.

    PubMed

    Ishihara, Hiroki; Kondo, Tsunenori; Omae, Kenji; Takagi, Toshio; Iizuka, Junpei; Kobayashi, Hirohito; Hashimoto, Yasunobu; Tanabe, Kazunari

    2017-02-01

    We aimed to evaluate the effect of sarcopenia, a condition of low muscle mass, on the survival among patients who were undergoing radical nephroureterectomy (RNU) for urothelial carcinoma of the upper urinary tract (UCUT). We retrospectively reviewed consecutive patients with UCUT (cT[any]N0M0) who underwent RNU between 2003 and 2013 at our department and its affiliated institutions. Preoperative computed tomography images were used to calculate each patient's skeletal muscle index, an indicator of whole-body muscle mass. Sarcopenia was defined according to the sex-specific consensus definitions, based on the patient's skeletal muscle and body mass indexes. We analyzed the relapse-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS) after RNU to identify factors that predicted patient survival. A total of 137 patients were included, and 90 patients (65.7 %) were diagnosed with sarcopenia. Compared to the non-sarcopenic patients, the sarcopenic patients had a significant inferior 5-year RFS (48.8 vs. 79.6 %, p = 0.0002), CSS (57.1 vs. 92.6 %, p < 0.0001), and OS (48.2 vs. 90.6 %, p < 0.0001). Multivariate analyses revealed that sarcopenia was an independent predictor of shorter RFS, CSS, and OS (all, p < 0.0001). Sarcopenia was an independent predictor of survival among patients with UCUT who were undergoing RNU.

  4. A simple lifestyle score predicts survival in healthy elderly men.

    PubMed

    Spencer, Carole A; Jamrozik, Konrad; Norman, Paul E; Lawrence-Brown, Michael

    2005-06-01

    Although improvements in life expectancy have been attributed in part to the adoption of a more prudent lifestyle, few studies have examined the association of lifestyle with survival, using several lifestyle factors simultaneously, in a healthy elderly population. We investigated the association of health related behaviors with mortality in 7989 men aged 65 to 83 years participating in a population-based trial in Perth, Western Australia, by calculating a lifestyle score as a simple tally of how many of eight prudent behaviors each individual followed. Invitations to screening produced a corrected response of 70.5%. Out of a possible score of 8, 46% of men had a score of less than 5. Within 5 years, a total of 703 men (9%) had died from any cause. The hazard ratio in men with a low lifestyle score was 1.3 [95% confidence interval (CI): 1.1-1.5] compared with men with a score of 5 or more. Lifestyle remains an important predictor of mortality even in old age. Survival in older men without a history of cardiovascular disease can potentially be enhanced by promoting a healthy lifestyle.

  5. Platelet serotonin level predicts survival in amyotrophic lateral sclerosis.

    PubMed

    Dupuis, Luc; Spreux-Varoquaux, Odile; Bensimon, Gilbert; Jullien, Philippe; Lacomblez, Lucette; Salachas, François; Bruneteau, Gaëlle; Pradat, Pierre-François; Loeffler, Jean-Philippe; Meininger, Vincent

    2010-10-13

    Amyotrophic lateral sclerosis (ALS) is a life-threatening neurodegenerative disease involving upper and lower motor neurons loss. Clinical features are highly variable among patients and there are currently few known disease-modifying factors underlying this heterogeneity. Serotonin is involved in a range of functions altered in ALS, including motor neuron excitability and energy metabolism. However, whether serotoninergic activity represents a disease modifier of ALS natural history remains unknown. Platelet and plasma unconjugated concentrations of serotonin and plasma 5-HIAA, the major serotonin metabolite, levels were measured using HPLC with coulometric detection in a cohort of 85 patients with ALS all followed-up until death and compared to a control group of 29 subjects. Platelet serotonin levels were significantly decreased in ALS patients. Platelet serotonin levels did not correlate with disease duration but were positively correlated with survival of the patients. Univariate Cox model analysis showed a 57% decreased risk of death for patients with platelet serotonin levels in the normal range relative to patients with abnormally low platelet serotonin (p = 0.0195). This protective effect remained significant after adjustment with age, gender or site of onset in multivariate analysis. Plasma unconjugated serotonin and 5-HIAA levels were unchanged in ALS patients compared to controls and did not correlate with clinical parameters. The positive correlation between platelet serotonin levels and survival strongly suggests that serotonin influences the course of ALS disease.

  6. Predicting survival of pancreatic cancer patients treated with gemcitabine using longitudinal tumour size data.

    PubMed

    Wendling, Thierry; Mistry, Hitesh; Ogungbenro, Kayode; Aarons, Leon

    2016-05-01

    Measures derived from longitudinal tumour size data have been increasingly utilised to predict survival of patients with solid tumours. The aim of this study was to examine the prognostic value of such measures for patients with metastatic pancreatic cancer undergoing gemcitabine therapy. The control data from two Phase III studies were retrospectively used to develop (271 patients) and validate (398 patients) survival models. Firstly, 31 baseline variables were screened from the training set using penalised Cox regression. Secondly, tumour shrinkage metrics were interpolated for each patient by hierarchical modelling of the tumour size time-series. Subsequently, survival models were built by applying two approaches: the first aimed at incorporating model-derived tumour size metrics in a parametric model, and the second simply aimed at identifying empirical factors using Cox regression. Finally, the performance of the models in predicting patient survival was evaluated on the validation set. Depending on the modelling approach applied, albumin, body surface area, neutrophil, baseline tumour size and tumour shrinkage measures were identified as potential prognostic factors. The distributional assumption on survival times appeared to affect the identification of risk factors but not the ability to describe the training data. The two survival modelling approaches performed similarly in predicting the validation data. A parametric model that incorporates model-derived tumour shrinkage metrics in addition to other baseline variables could predict reasonably well survival of patients with metastatic pancreatic cancer. However, the predictive performance was not significantly better than a simple Cox model that incorporates only baseline characteristics.

  7. Body Composition Predicts Survival in Patients with Hepatocellular Carcinoma Treated with Transarterial Chemoembolization.

    PubMed

    Parikh, Neehar D; Zhang, Peng; Singal, Amit G; Derstine, Brian A; Krishnamurthy, Venkat; Barman, Pranab; Waljee, Akbar K; Su, Grace L

    2017-06-01

    The prognosis of patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) is often uncertain. We aimed to utilize analytic morphomics, a high-throughput imaging analysis, to assess if body composition is predictive of post-TACE survival. We included patients from a single center (Ann Arbor VA) who had TACE as the primary treatment for HCC and had a pre-treatment CT scans. Univariate analysis and multivariate conditional inference tree analysis were utilized to identify the morphomic characteristics predictive of one-year survival. were validated in an external cohort (University of Michigan Health System) of HCC patients who underwent TACE as their primary treatment. In the 75 patients in the derivation cohort, median survival was 439 (IQR: 377-685) days from receipt of TACE, with 1-year survival of 61%. Visceral fat density (VFD) was the only morphomic factor predictive of overall and 1-year survival (p<0.001). Patients with VFD above the 56th percentile had a 1-year survival of 39% vs. 78% for those below the 56th percentile. VFD also correlated with 1-year survival in the external validation cohort (44% vs. 72%, p<0.001). In a secondary analysis, patients with higher VFD were significantly more likely to experience hepatic decompensation after TACE (p<0.001). VFD served as an objective predictor of mortality in patients undergoing TACE, possibly through its ability to predict hepatic decompensation. VFD may serve as a radiographic biomarker in predicting TACE outcomes.

  8. Predicting long-term graft survival in adult kidney transplant recipients.

    PubMed

    Pinsky, Brett W; Lentine, Krista L; Ercole, Patrick R; Salvalaggio, Paolo R; Burroughs, Thomas E; Schnitzler, Mark A

    2012-07-01

    The ability to accurately predict a population's long-term survival has important implications for quantifying the benefits of transplantation. To identify a model that can accurately predict a kidney transplant population's long-term graft survival, we retrospectively studied the United Network of Organ Sharing data from 13,111 kidney-only transplants completed in 1988- 1989. Nineteen-year death-censored graft survival (DCGS) projections were calculated and compared with the population's actual graft survival. The projection curves were created using a two-part estimation model that (1) fits a Kaplan-Meier survival curve immediately after transplant (Part A) and (2) uses truncated observational data to model a survival function for long-term projection (Part B). Projection curves were examined using varying amounts of time to fit both parts of the model. The accuracy of the projection curve was determined by examining whether predicted survival fell within the 95% confidence interval for the 19-year Kaplan-Meier survival, and the sample size needed to detect the difference in projected versus observed survival in a clinical trial. The 19-year DCGS was 40.7% (39.8-41.6%). Excellent predictability (41.3%) can be achieved when Part A is fit for three years and Part B is projected using two additional years of data. Using less than five total years of data tended to overestimate the population's long-term survival, accurate prediction of long-term DCGS is possible, but requires attention to the quantity data used in the projection method.

  9. Tumor RNA disruption predicts survival benefit from breast cancer chemotherapy.

    PubMed

    Parissenti, Amadeo M; Guo, Baoqing; Pritzker, Laura B; Pritzker, Kenneth P H; Wang, Xiaohui; Zhu, Mu; Shepherd, Lois E; Trudeau, Maureen E

    2015-08-01

    In a prior substudy of the CAN-NCIC-MA.22 clinical trial (ClinicalTrials.gov identifier NCT00066443), we observed that neoadjuvant chemotherapy reduced tumor RNA integrity in breast cancer patients, a phenomenon we term "RNA disruption." The purpose of the current study was to assess in the full patient cohort the relationship between mid-treatment tumor RNA disruption and both pCR post-treatment and, subsequently, disease-free survival (DFS) up to 108 months post-treatment. To meet these objectives, we developed the RNA disruption assay (RDA) to quantify RNA disruption and stratify it into 3 response zones of clinical importance. Zone 1 is a level of RNA disruption inadequate for pathologic complete response (pCR); Zone 2 is an intermediate level, while Zone 3 has high RNA disruption. The same RNA disruption cut points developed for pCR response were then utilized for DFS. Tumor RDA identified >fourfold more chemotherapy non-responders than did clinical response by calipers. pCR responders were clustered in RDA Zone 3, irrespective of tumor subtype. DFS was about 2-fold greater for patients with tumors in Zone 3 compared to Zone 1 patients. Kaplan-Meier survival curves corroborated these findings that high tumor RNA disruption was associated with increased DFS. DFS values for patients in zone 3 that did not achieve a pCR were similar to that of pCR recipients across tumor subtypes, including patients with hormone receptor positive tumors that seldom achieve a pCR. RDA appears superior to pCR as a chemotherapy response biomarker, supporting the prospect of its use in response-guided chemotherapy.

  10. Facial morphology predicts male fitness and rank but not survival in Second World War Finnish soldiers

    PubMed Central

    Loehr, John; O'Hara, Robert B.

    2013-01-01

    We investigated fitness, military rank and survival of facial phenotypes in large-scale warfare using 795 Finnish soldiers who fought in the Winter War (1939–1940). We measured facial width-to-height ratio—a trait known to predict aggressive behaviour in males—and assessed whether facial morphology could predict survival, lifetime reproductive success (LRS) and social status. We found no difference in survival along the phenotypic gradient, however, wider-faced individuals had greater LRS, but achieved a lower military rank. PMID:23658003

  11. Facial morphology predicts male fitness and rank but not survival in Second World War Finnish soldiers.

    PubMed

    Loehr, John; O'Hara, Robert B

    2013-08-23

    We investigated fitness, military rank and survival of facial phenotypes in large-scale warfare using 795 Finnish soldiers who fought in the Winter War (1939-1940). We measured facial width-to-height ratio-a trait known to predict aggressive behaviour in males-and assessed whether facial morphology could predict survival, lifetime reproductive success (LRS) and social status. We found no difference in survival along the phenotypic gradient, however, wider-faced individuals had greater LRS, but achieved a lower military rank.

  12. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science

    PubMed Central

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

  13. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    PubMed

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

  14. Predicting response and survival in chemotherapy-treated triple-negative breast cancer

    PubMed Central

    Prat, A; Lluch, A; Albanell, J; Barry, W T; Fan, C; Chacón, J I; Parker, J S; Calvo, L; Plazaola, A; Arcusa, A; Seguí-Palmer, M A; Burgues, O; Ribelles, N; Rodriguez-Lescure, A; Guerrero, A; Ruiz-Borrego, M; Munarriz, B; López, J A; Adamo, B; Cheang, M C U; Li, Y; Hu, Z; Gulley, M L; Vidal, M J; Pitcher, B N; Liu, M C; Citron, M L; Ellis, M J; Mardis, E; Vickery, T; Hudis, C A; Winer, E P; Carey, L A; Caballero, R; Carrasco, E; Martín, M; Perou, C M; Alba, E

    2014-01-01

    Background: In this study, we evaluated the ability of gene expression profiles to predict chemotherapy response and survival in triple-negative breast cancer (TNBC). Methods: Gene expression and clinical–pathological data were evaluated in five independent cohorts, including three randomised clinical trials for a total of 1055 patients with TNBC, basal-like disease (BLBC) or both. Previously defined intrinsic molecular subtype and a proliferation signature were determined and tested. Each signature was tested using multivariable logistic regression models (for pCR (pathological complete response)) and Cox models (for survival). Within TNBC, interactions between each signature and the basal-like subtype (vs other subtypes) for predicting either pCR or survival were investigated. Results: Within TNBC, all intrinsic subtypes were identified but BLBC predominated (55–81%). Significant associations between genomic signatures and response and survival after chemotherapy were only identified within BLBC and not within TNBC as a whole. In particular, high expression of a previously identified proliferation signature, or low expression of the luminal A signature, was found independently associated with pCR and improved survival following chemotherapy across different cohorts. Significant interaction tests were only obtained between each signature and the BLBC subtype for prediction of chemotherapy response or survival. Conclusions: The proliferation signature predicts response and improved survival after chemotherapy, but only within BLBC. This highlights the clinical implications of TNBC heterogeneity, and suggests that future clinical trials focused on this phenotypic subtype should consider stratifying patients as having BLBC or not. PMID:25101563

  15. Respiratory Muscle Strength as a Predictive Biomarker for Survival in Amyotrophic Lateral Sclerosis.

    PubMed

    Polkey, Michael I; Lyall, Rebecca A; Yang, Ke; Johnson, Erin; Leigh, P Nigel; Moxham, John

    2017-01-01

    Biomarkers for survival in amyotrophic lateral sclerosis (ALS) would facilitate the development of novel drugs. Although respiratory muscle weakness is a known predictor of poor prognosis, a comprehensive comparison of different tests is lacking. To compare the predictive power of invasive and noninvasive respiratory muscle strength assessments for survival or ventilator-free survival, up to 3 years. From a previously published report respiratory muscle strength measurements were available for 78 patients with ALS. Time to death and/or ventilation were ascertained. Receiver operating characteristic analysis was used to determine the cutoff point of each parameter. Each respiratory muscle strength assessment individually achieved statistical significance for prediction of survival or ventilator-free survival. In multivariate analysis sniff trans-diaphragmatic and esophageal pressure, twitch trans-diaphragmatic pressure (Tw Pdi), age, and maximal static expiratory mouth pressure were significant predictors of ventilation-free survival and Tw Pdi and maximal static expiratory mouth pressure for absolute survival. Although all measures had good specificity, there were differing sensitivities. All cutoff points for the VC were greater than 80% of normal, except for prediction of 3-month outcomes. Sequential data showed a linear decline for direct measures of respiratory muscle strength, whereas VC showed little to no decline until 12 months before death/ventilation. The most powerful biomarker for mortality stratification was Tw Pdi, but the predictive power of sniff nasal inspiratory pressure was also excellent. A VC within normal range suggested a good prognosis at 3 months but was of little other value.

  16. A simple protein-energy wasting score predicts survival in maintenance hemodialysis patients.

    PubMed

    Moreau-Gaudry, Xavier; Jean, Guillaume; Genet, Leslie; Lataillade, Dominique; Legrand, Eric; Kuentz, François; Fouque, Denis

    2014-11-01

    Nutritional status is a powerful predictor of survival in maintenance hemodialysis patients but remains challenging to assess. We defined a new Protein Energy Wasting (PEW) score based on the nomenclature proposed by the International Society of Renal Nutrition and Metabolism in 2008. This score, graded from 0 (worse) to 4 (best) was derived from 4 body nutrition compartments: serum albumin, body mass index, a normalized serum creatinine value, and protein intake as assessed by nPNA. We applied this score to 1443 patients from the ARNOS prospective dialysis cohort and provide survival data from 2005 until 2008. Patients survival at 3.5 year. Survival ranged from 84%-69% according to the protein-energy wasting score. There was a clear-cut reduction in survival (5%-7%; P < 0.01) for each unit decrement in the score grade. There was a 99% survival at 1 year for patients with the score of 4. In addition, the 6-month variation of this PEW score also strongly predicted patients' survival (P < 0.01). A new simple and easy-to-get PEW score predicts survival in maintenance hemodialysis patients. Furthermore, increase of this nutritional score over time also indicates survival improvement, and may help to better identify subgroups of patients with a high mortality rate, in which nutrition support should be enforced. Copyright © 2014 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  17. Cardiopulmonary bypass (CPB) has no significant impact on survival in patients undergoing nephrectomy and level III-IV inferior vena cava thrombectomy; a multi-institutional analysis

    PubMed Central

    Dall'Era, Marc A.; Durbin-Johnson, Blythe; Carballido, Joaquín A.; Chandrasekar, Thenappan; Chromecki, Thomas; Ciancio, Gaetano; Daneshmand, Siamak; Gontero, Paolo; Gonzalez, Javier; Haferkamp, Axel; Hohenfellner, Markus; Huang, William C.; Espinós, Estefania Linares; Mandel, Philipp; Martinez-Salamanca, Juan I.; Master, Viraj A.; McKiernan, James M.; Montorsi, Francesco; Novara, Giacomo; Pahernik, Sascha; Palou, Juan; Pruthi, Raj S.; Rodriguez-Faba, Oscar; Russo, Paul; Scherr, Douglas S.; Shariat, Shahrokh F.; Spahn, Martin; Terrone, Carlo; Vergho, Daniel; Wallen, Eric M.; Xylinas, Evanguelos; Zigeuner, Richard; Libertino, John A.; Evans, Christopher P.

    2016-01-01

    Purpose The impact of cardiopulmonary bypass (CPB) usage in level III-IV tumor thrombectomy on surgical and oncologic outcomes is unknown. We sought to determine the impact of cardiopulmonary bypass (CPB) on overall and cancer specific survival, as well as surgical complication rates, and immediate outcomes in patients undergoing nephrectomy and level III-IV tumor thrombectomy with or without CPB. Patients and Methods We retrospectively analyzed 362 patients with RCC and with level III or IV tumor thrombus from 1992 to 2012 in 22 US and European centers. Cox proportional hazards models were used to compare overall and cancer-specific survival between patients with and without CPB. Perioperative mortality and complications rates were assessed using logistic regression analyses. Results The median overall survival was 24.6 months in non-CPB patients and 26.6 months in CPB patients. Overall survival and cancer-specific survival (CSS) did not differ significantly in both groups, neither in univariate analysis nor when adjusting for known risk factors. In multivariate analysis, no significant differences were seen in hospital LOS, Clavien 1-4 complication rate, intraoperative or 30 day mortality, and CSS between both groups. Limitations include the retrospective nature of the study. Conclusions In our multi-institutional analysis, the use of cardiopulmonary bypass did not significantly impact cancer specific survival or overall survival in patients undergoing nephrectomy and level III or IV tumor thrombectomy. Neither approach was independently associated with increased mortality in the multivariate analysis. Higher surgical complications were not independently associated with the use of CPB. PMID:25797392

  18. Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models.

    PubMed

    Yousefi, Safoora; Amrollahi, Fatemeh; Amgad, Mohamed; Dong, Chengliang; Lewis, Joshua E; Song, Congzheng; Gutman, David A; Halani, Sameer H; Vega, Jose Enrique Velazquez; Brat, Daniel J; Cooper, Lee A D

    2017-09-15

    Translating the vast data generated by genomic platforms into accurate predictions of clinical outcomes is a fundamental challenge in genomic medicine. Many prediction methods face limitations in learning from the high-dimensional profiles generated by these platforms, and rely on experts to hand-select a small number of features for training prediction models. In this paper, we demonstrate how deep learning and Bayesian optimization methods that have been remarkably successful in general high-dimensional prediction tasks can be adapted to the problem of predicting cancer outcomes. We perform an extensive comparison of Bayesian optimized deep survival models and other state of the art machine learning methods for survival analysis, and describe a framework for interpreting deep survival models using a risk backpropagation technique. Finally, we illustrate that deep survival models can successfully transfer information across diseases to improve prognostic accuracy. We provide an open-source software implementation of this framework called SurvivalNet that enables automatic training, evaluation and interpretation of deep survival models.

  19. Characterization of wafer charging mechanisms and oxide survival prediction methodology

    SciTech Connect

    Lukaszek, W.; Dixon, W.; Vella, M.; Messick, C.; Reno, S.; Shideler, J.

    1994-04-01

    Unipolar, EEPROM-based peak potential sensors and current sensors have been used to characterize the I-V relationship of charging transients which devices normally experience during the course of ion implantation. The results indicate that the charging sources may appear to behave like current-sources or voltage-sources, depending on the impedance of the load. This behavior may be understood in terms of plasma concepts. The ability to empirically characterize the I-V characteristics of charging sources using the CHARM-2 monitor wafers opens the way for prediction of failure rates of oxides subjected to specific processes, if the oxide Q{sub bd} distributions are known.

  20. The radiosensitivity index predicts for overall survival in glioblastoma

    PubMed Central

    Ahmed, Kamran A.; Chinnaiyan, Prakash; Fulp, William J.; Eschrich, Steven; Torres-Roca, Javier F.; Caudell, Jimmy J.

    2015-01-01

    We have previously developed a multigene expression model of tumor radiosensitivity (RSI) with clinical validation in multiple cohorts and disease sites. We hypothesized RSI would identify glioblastoma patients who would respond to radiation and predict treatment outcomes. Clinical and array based gene expression (Affymetrix HT Human Genome U133 Array Plate Set) level 2 data was downloaded from the cancer genome atlas (TCGA). A total of 270 patients were identified for the analysis: 214 who underwent radiotherapy and temozolomide and 56 who did not undergo radiotherapy. Median follow-up for the entire cohort was 9.1 months (range: 0.04–92.2 months). Patients who did not receive radiotherapy were more likely to be older (p < 0.001) and of poorer performance status (p < 0.001). On multivariate analysis, RSI is an independent predictor of OS (HR = 1.64, 95% CI 1.08–2.5; p = 0.02). Furthermore, on subset analysis, radiosensitive patients had significantly improved OS in the patients with high MGMT expression (unmethylated MGMT), 1 year OS 84.1% vs. 53.7% (p = 0.005). This observation held on MVA (HR = 1.94, 95% CI 1.19–3.31; p = 0.008), suggesting that RT has a larger therapeutic impact in these patients. In conclusion, RSI predicts for OS in glioblastoma. These data further confirm the value of RSI as a disease-site independent biomarker. PMID:26451615

  1. The radiosensitivity index predicts for overall survival in glioblastoma.

    PubMed

    Ahmed, Kamran A; Chinnaiyan, Prakash; Fulp, William J; Eschrich, Steven; Torres-Roca, Javier F; Caudell, Jimmy J

    2015-10-27

    We have previously developed a multigene expression model of tumor radiosensitivity (RSI) with clinical validation in multiple cohorts and disease sites. We hypothesized RSI would identify glioblastoma patients who would respond to radiation and predict treatment outcomes. Clinical and array based gene expression (Affymetrix HT Human Genome U133 Array Plate Set) level 2 data was downloaded from the cancer genome atlas (TCGA). A total of 270 patients were identified for the analysis: 214 who underwent radiotherapy and temozolomide and 56 who did not undergo radiotherapy. Median follow-up for the entire cohort was 9.1 months (range: 0.04-92.2 months). Patients who did not receive radiotherapy were more likely to be older (p < 0.001) and of poorer performance status (p < 0.001). On multivariate analysis, RSI is an independent predictor of OS (HR = 1.64, 95% CI 1.08-2.5; p = 0.02). Furthermore, on subset analysis, radiosensitive patients had significantly improved OS in the patients with high MGMT expression (unmethylated MGMT), 1 year OS 84.1% vs. 53.7% (p = 0.005). This observation held on MVA (HR = 1.94, 95% CI 1.19-3.31; p = 0.008), suggesting that RT has a larger therapeutic impact in these patients. In conclusion, RSI predicts for OS in glioblastoma. These data further confirm the value of RSI as a disease-site independent biomarker.

  2. Evaluation of parametric models by the prediction error in colorectal cancer survival analysis

    PubMed Central

    Baghestani, Ahmad Reza; Gohari, Mahmood Reza; Orooji, Arezoo; Pourhoseingholi, Mohamad Amin; Zali, Mohammad Reza

    2015-01-01

    Aim: The aim of this study is to determine the factors influencing predicted survival time for patients with colorectal cancer (CRC) using parametric models and select the best model by predicting error’s technique. Background: Survival models are statistical techniques to estimate or predict the overall time up to specific events. Prediction is important in medical science and the accuracy of prediction is determined by a measurement, generally based on loss functions, called prediction error. Patients and methods: A total of 600 colorectal cancer patients who admitted to the Cancer Registry Center of Gastroenterology and Liver Disease Research Center, Taleghani Hospital, Tehran, were followed at least for 5 years and have completed selected information for this study. Body Mass Index (BMI), Sex, family history of CRC, tumor site, stage of disease and histology of tumor included in the analysis. The survival time was compared by the Log-rank test and multivariate analysis was carried out using parametric models including Log normal, Weibull and Log logistic regression. For selecting the best model, the prediction error by apparent loss was used. Results: Log rank test showed a better survival for females, BMI more than 25, patients with early stage at diagnosis and patients with colon tumor site. Prediction error by apparent loss was estimated and indicated that Weibull model was the best one for multivariate analysis. BMI and Stage were independent prognostic factors, according to Weibull model. Conclusion: In this study, according to prediction error Weibull regression showed a better fit. Prediction error would be a criterion to select the best model with the ability to make predictions of prognostic factors in survival analysis. PMID:26328040

  3. Unbiased Prediction and Feature Selection in High-Dimensional Survival Regression

    PubMed Central

    Laimighofer, Michael; Krumsiek, Jan; Theis, Fabian J.

    2016-01-01

    Abstract With widespread availability of omics profiling techniques, the analysis and interpretation of high-dimensional omics data, for example, for biomarkers, is becoming an increasingly important part of clinical medicine because such datasets constitute a promising resource for predicting survival outcomes. However, early experience has shown that biomarkers often generalize poorly. Thus, it is crucial that models are not overfitted and give accurate results with new data. In addition, reliable detection of multivariate biomarkers with high predictive power (feature selection) is of particular interest in clinical settings. We present an approach that addresses both aspects in high-dimensional survival models. Within a nested cross-validation (CV), we fit a survival model, evaluate a dataset in an unbiased fashion, and select features with the best predictive power by applying a weighted combination of CV runs. We evaluate our approach using simulated toy data, as well as three breast cancer datasets, to predict the survival of breast cancer patients after treatment. In all datasets, we achieve more reliable estimation of predictive power for unseen cases and better predictive performance compared to the standard CoxLasso model. Taken together, we present a comprehensive and flexible framework for survival models, including performance estimation, final feature selection, and final model construction. The proposed algorithm is implemented in an open source R package (SurvRank) available on CRAN. PMID:26894327

  4. Significance of bioindicators to predict survival in irradiated minipigs

    PubMed Central

    Moroni, Maria; Port, Matthias; Koch, Amory; Gulani, Jatinder; Meineke, Viktor; Abend, Michael

    2014-01-01

    The minipig is emerging as a potential alternative non-rodent animal model. Several biological markers e.g. blood counts, laboratory parameter and clinical signs have been proposed for rapid triage of radiation victims. Here, we focus on the significance of bio-indicators for prediction of survivors after irradiation and compared it with human data; relationship between these biomarkers and radiation dose is not part of this study. Male Gottingen minipigs (age 4–5 months, weight 9–10 kg) were irradiated (or sham-irradiated) bilaterally with gamma-photons (Cobalt-60, 0.5–0.6 Gy/min) in the dose range of 1.6 – 12 Gy. Peripheral blood cell counts, laboratory parameters, and clinical symptoms were collected up to 10 days after irradiation and analyzed using logistic regression analysis and calculating ROC curves. In moribund pigs parameters such as decreased lymphocyte/granulocyte counts, increased C-reactive protein, alkaline phosphatase values as well as increased citrulline values and body temperature significantly (p<0.002 up to p<0.0001) discriminated non-survivors from survivors with high precision (ROC ≥ 0.8), but most predictive within the first three days after exposure was a combination of decreased lymphocyte counts and increased body temperature observed as early as 3 h after radiation exposure (ROC: 0.93–0.96, p<0.0001). Sham-irradiated animals (corresponding to “worried wells”) could be easily discriminated from dying pigs, thus pointing to the diagnostic significance of our analysis. These data corroborate with earlier findings performed on human radiation victims suffering from severe hematological syndrome and provide further evidence for the suitability of the minipig model as a potential alternative non-rodent animal model. PMID:24776906

  5. Anthrax Vaccine Induced Antibodies Provide Cross-Species Prediction of Survival to Aerosol Challenge

    PubMed Central

    Fay, Michael P.; Follmann, Dean A.; Lynn, Freyja; Schiffer, Jarad M.; Stark, Greg; Kohberge, Robert; Quinn, Conrad P.; Nuzum, Edwin O.

    2013-01-01

    Because clinical trials to assess the efficacy of vaccines against anthrax are not ethical or feasible, licensure for new anthrax vaccines will likely involve the Food and Drug Administration’s “Animal Rule,” a set of regulations that allow approval of products based on efficacy data only in animals combined with immunogenicity and safety data in animals and humans. US government sponsored animal studies have shown anthrax vaccine efficacy in a variety of settings. We examined data from 21 of those studies to determine if an immunological bridge based on lethal toxin neutralization activity assay (TNA) can predict survival against an inhalation anthrax challenge within and across species and genera. The 21 studies were classified into 11 different settings, each of which had the same animal species, vaccine type and formulation, vaccination schedule, time of TNA measurement, and challenge time. Logistic regression models determined the contribution of vaccine dilution dose and TNA on prediction of survival. For most settings, logistic models using only TNA explained more than 75% of the survival effect of the models with dose additionally included. Cross species survival predictions using TNA were compared to the actual survival and shown to have good agreement (Cohen’s κ ranged from 0.55 to 0.78). In one study design, cynomolgus macaque data predicted 78.6% survival in rhesus macaques (actual survival 83.0%) and 72.6% in rabbits (actual survival, 64.6%). These data add support for the use of TNA as an immunological bridge between species to extrapolate data in animals to predict anthrax vaccine effectiveness in humans. PMID:22972844

  6. SU-F-R-04: Radiomics for Survival Prediction in Glioblastoma (GBM)

    SciTech Connect

    Zhang, H; Molitoris, J; Bhooshan, N; Choi, W; Lu, W; Mehta, M; D’Souza, W; Tan, S; Giacomelli, I; Scartoni, D; Gzell, C

    2016-06-15

    Purpose: To develop a quantitative radiomics approach for survival prediction of glioblastoma (GBM) patients treated with chemoradiotherapy (CRT). Methods: 28 GBM patients who received CRT at our institution were retrospectively studied. 255 radiomic features were extracted from 3 gadolinium-enhanced T1 weighted MRIs for 2 regions of interest (ROIs) (the surgical cavity and its surrounding enhancement rim). The 3 MRIs were at pre-treatment, 1-month and 3-month post-CRT. The imaging features comprehensively quantified the intensity, spatial variation (texture), geometric property and their spatial-temporal changes for the 2 ROIs. 3 demographics features (age, race, gender) and 12 clinical parameters (KPS, extent of resection, whether concurrent temozolomide was adjusted/stopped and radiotherapy related information) were also included. 4 Machine learning models (logistic regression (LR), support vector machine (SVM), decision tree (DT), neural network (NN)) were applied to predict overall survival (OS) and progression-free survival (PFS). The number of cases and percentage of cases predicted correctly were collected and AUC (area under the receiver operating characteristic (ROC) curve) were determined after leave-one-out cross-validation. Results: From univariate analysis, 27 features (1 demographic, 1 clinical and 25 imaging) were statistically significant (p<0.05) for both OS and PFS. Two sets of features (each contained 24 features) were algorithmically selected from all features to predict OS and PFS. High prediction accuracy of OS was achieved by using NN (96%, 27 of 28 cases were correctly predicted, AUC = 0.99), LR (93%, 26 of 28 cases were correctly predicted, AUC = 0.95) and SVM (93%, 26 of 28 cases were correctly predicted, AUC = 0.90). When predicting PFS, NN obtained the highest prediction accuracy (89%, 25 of 28 cases were correctly predicted, AUC = 0.92). Conclusion: Radiomics approach combined with patients’ demographics and clinical parameters can

  7. For prediction of elder survival by a Gompertz model, number dead is preferable to number alive.

    PubMed

    Easton, Dexter M; Hirsch, Henry R

    2008-12-01

    The standard Gompertz equation for human survival fits very poorly the survival data of the very old (age 85 and above), who appear to survive better than predicted. An alternative Gompertz model based on the number of individuals who have died, rather than the number that are alive, at each age, tracks the data more accurately. The alternative model is based on the same differential equation as in the usual Gompertz model. The standard model describes the accelerated exponential decay of the number alive, whereas the alternative, heretofore unutilized model describes the decelerated exponential growth of the number dead. The alternative model is complementary to the standard and, together, the two Gompertz formulations allow accurate prediction of survival of the older as well as the younger mature members of the population.

  8. A Model-Free Machine Learning Method for Risk Classification and Survival Probability Prediction.

    PubMed

    Geng, Yuan; Lu, Wenbin; Zhang, Hao Helen

    2014-01-01

    Risk classification and survival probability prediction are two major goals in survival data analysis since they play an important role in patients' risk stratification, long-term diagnosis, and treatment selection. In this article, we propose a new model-free machine learning framework for risk classification and survival probability prediction based on weighted support vector machines. The new procedure does not require any specific parametric or semiparametric model assumption on data, and is therefore capable of capturing nonlinear covariate effects. We use numerous simulation examples to demonstrate finite sample performance of the proposed method under various settings. Applications to a glioma tumor data and a breast cancer gene expression survival data are shown to illustrate the new methodology in real data analysis.

  9. Accuracy of Inferior Vena Cava Ultrasound for Predicting Dehydration in Children with Acute Diarrhea in Resource-Limited Settings

    PubMed Central

    Modi, Payal; Glavis-Bloom, Justin; Nasrin, Sabiha; Guy, Allysia; Rege, Soham; Noble, Vicki E.; Alam, Nur H.; Levine, Adam C.

    2016-01-01

    Introduction Although dehydration from diarrhea is a leading cause of morbidity and mortality in children under five, existing methods of assessing dehydration status in children have limited accuracy. Objective To assess the accuracy of point-of-care ultrasound measurement of the aorta-to-IVC ratio as a predictor of dehydration in children. Methods A prospective cohort study of children under five years with acute diarrhea was conducted in the rehydration unit of the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). Ultrasound measurements of aorta-to-IVC ratio and dehydrated weight were obtained on patient arrival. Percent weight change was monitored during rehydration to classify children as having “some dehydration” with weight change 3–9% or “severe dehydration” with weight change > 9%. Logistic regression analysis and Receiver-Operator Characteristic (ROC) curves were used to evaluate the accuracy of aorta-to-IVC ratio as a predictor of dehydration severity. Results 850 children were enrolled, of which 771 were included in the final analysis. Aorta to IVC ratio was a significant predictor of the percent dehydration in children with acute diarrhea, with each 1-point increase in the aorta to IVC ratio predicting a 1.1% increase in the percent dehydration of the child. However, the area under the ROC curve (0.60), sensitivity (67%), and specificity (49%), for predicting severe dehydration were all poor. Conclusions Point-of-care ultrasound of the aorta-to-IVC ratio was statistically associated with volume status, but was not accurate enough to be used as an independent screening tool for dehydration in children under five years presenting with acute diarrhea in a resource-limited setting. PMID:26766306

  10. A Comparative Analysis of Survival Prediction Using PRESERVE and RESP Scores.

    PubMed

    Kang, Hye-Rin; Kim, Dong Jung; Lee, Jinwoo; Cho, Young-Jae; Kim, Jun Sung; Lee, Sang-Min; Lee, Jae-Ho; Jheon, Sanghoon; Lee, Choon-Taek; Lee, Yeon Joo

    2017-09-01

    Venovenous (VV) extracorporeal membrane oxygenation (ECMO) can be a life-saving therapy for patients with severe acute lung failure refractory to conventional therapy. The respiratory ECMO survival prediction (RESP) score and the predicting death for severe acute respiratory distress syndrome on VV-ECMO (PRESERVE) score were created to predict survival at the time of initiation of ECMO. This study aimed to validate both of these scores externally and to compare their predictive accuracies in patients with non-Western acute respiratory distress syndrome (ARDS). In this retrospective cohort study, we reviewed and extracted data from electronic medical records of consecutive adult ARDS patients who were treated with VV-ECMO from 2007 to 2015. The PRESERVE and RESP scores were calculated for each patient. The outcomes of interest were inhospital and 6-month survival. In all, 99 patients were included. The mean age of the patients was 54 years, and male patients constituted 70% of the cohort. The inhospital and 6-month survival rates were 23% and 22%, respectively. Receiver-operating characteristics curve analysis of the PRESERVE and RESP scores showed area under the curve values of 0.64 and 0.69, respectively (p = 0.53), for inhospital survival. The receiver-operating characteristics areas under the curve for 6-month survival were 0.66 and 0.69, respectively (p = 0.68). The prognostic accuracies of the PRESERVE and RESP scores were thus similar. Both PRESERVE and RESP scores are useful for predicting survival in Asian ARDS patients, and both scores had similar prognostic accuracies in our Korean ARDS cohort. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  11. Introduction of a prediction model to assigning periodontal prognosis based on survival rates.

    PubMed

    Martinez-Canut, Pedro; Alcaraz, Jaime; Alcaraz, Jaime; Alvarez-Novoa, Pablo; Alvarez-Novoa, Carmen; Marcos, Ana; Noguerol, Blas; Noguerol, Fernando; Zabalegui, Ion

    2017-09-04

    To develop a prediction model for tooth loss due to periodontal disease (TLPD) in patients following periodontal maintenance (PM), and assess its performance using a multicentre approach. A multilevel analysis of eleven predictors of TLPD in 500 patients following PM was carried out to calculate the probability of TLPD. This algorithm was applied to three different TLPD samples (369 teeth) gathered retrospectively by nine periodontist, associating several intervals of probability with the corresponding survival rates, based on significant differences in the mean survival rates. The reproducibility of these associations was assessed in each sample (One-way ANOVA and pair-wise comparison with Bonferroni corrections). The model presented high specificity and moderate sensitivity, with optimal calibration and discrimination measurements. Seven intervals of probability were associated with seven survival rates and these associations contained close to 80% of the cases: the probability predicted the survival rate at this percentage. The model performed well in the three samples, since the mean survival rates of each association were significantly different within each sample, while no significant differences between the samples were found in pair-wise comparisons of means. This model might be useful for predicting survival rates in different TLPD samples This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  12. A priori Prediction of Neoadjuvant Chemotherapy Response and Survival in Breast Cancer Patients using Quantitative Ultrasound

    NASA Astrophysics Data System (ADS)

    Tadayyon, Hadi; Sannachi, Lakshmanan; Gangeh, Mehrdad J.; Kim, Christina; Ghandi, Sonal; Trudeau, Maureen; Pritchard, Kathleen; Tran, William T.; Slodkowska, Elzbieta; Sadeghi-Naini, Ali; Czarnota, Gregory J.

    2017-04-01

    Quantitative ultrasound (QUS) can probe tissue structure and analyze tumour characteristics. Using a 6-MHz ultrasound system, radiofrequency data were acquired from 56 locally advanced breast cancer patients prior to their neoadjuvant chemotherapy (NAC) and QUS texture features were computed from regions of interest in tumour cores and their margins as potential predictive and prognostic indicators. Breast tumour molecular features were also collected and used for analysis. A multiparametric QUS model was constructed, which demonstrated a response prediction accuracy of 88% and ability to predict patient 5-year survival rates (p = 0.01). QUS features demonstrated superior performance in comparison to molecular markers and the combination of QUS and molecular markers did not improve response prediction. This study demonstrates, for the first time, that non-invasive QUS features in the core and margin of breast tumours can indicate breast cancer response to neoadjuvant chemotherapy (NAC) and predict five-year recurrence-free survival.

  13. A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

    SciTech Connect

    Oberije, Cary; De Ruysscher, Dirk; Houben, Ruud; Heuvel, Michel van de; Uyterlinde, Wilma; Deasy, Joseph O.; Belderbos, Jose; Dingemans, Anne-Marie C.; Rimner, Andreas; Din, Shaun; Lambin, Philippe

    2015-07-15

    Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

  14. A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

    PubMed Central

    Oberije, Cary; De Ruysscher, Dirk; Houben, Ruud; van de Heuvel, Michel; Uyterlinde, Wilma; Deasy, Joseph O.; Belderbos, Jose; Dingemans, Anne-Marie C.; Rimner, Andreas; Din, Shaun; Lambin, Philippe

    2016-01-01

    Purpose Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient’s survival probability (www.predictcancer.org). The data set can be downloaded at https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048. Conclusions The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system. PMID:25936599

  15. Melanoma sentinel node biopsy and prediction models for relapse and overall survival

    PubMed Central

    Mitra, A; Conway, C; Walker, C; Cook, M; Powell, B; Lobo, S; Chan, M; Kissin, M; Layer, G; Smallwood, J; Ottensmeier, C; Stanley, P; Peach, H; Chong, H; Elliott, F; Iles, M M; Nsengimana, J; Barrett, J H; Bishop, D T; Newton-Bishop, J A

    2010-01-01

    Background: To optimise predictive models for sentinal node biopsy (SNB) positivity, relapse and survival, using clinico-pathological characteristics and osteopontin gene expression in primary melanomas. Methods: A comparison of the clinico-pathological characteristics of SNB positive and negative cases was carried out in 561 melanoma patients. In 199 patients, gene expression in formalin-fixed primary tumours was studied using Illumina's DASL assay. A cross validation approach was used to test prognostic predictive models and receiver operating characteristic curves were produced. Results: Independent predictors of SNB positivity were Breslow thickness, mitotic count and tumour site. Osteopontin expression best predicted SNB positivity (P=2.4 × 10−7), remaining significant in multivariable analysis. Osteopontin expression, combined with thickness, mitotic count and site, gave the best area under the curve (AUC) to predict SNB positivity (72.6%). Independent predictors of relapse-free survival were SNB status, thickness, site, ulceration and vessel invasion, whereas only SNB status and thickness predicted overall survival. Using clinico-pathological features (thickness, mitotic count, ulceration, vessel invasion, site, age and sex) gave a better AUC to predict relapse (71.0%) and survival (70.0%) than SNB status alone (57.0, 55.0%). In patients with gene expression data, the SNB status combined with the clinico-pathological features produced the best prediction of relapse (72.7%) and survival (69.0%), which was not increased further with osteopontin expression (72.7, 68.0%). Conclusion: Use of these models should be tested in other data sets in order to improve predictive and prognostic data for patients. PMID:20859289

  16. Is the ACLS score a valid prediction rule for survival after cardiac arrest?

    PubMed

    Haukoos, Jason S; Lewis, Roger J; Stratton, Samuel J; Niemann, James T

    2003-06-01

    The ACLS (advanced cardiac life support) Score was previously developed to predict survival from out-of-hospital cardiac arrest. Whether the arrest was witnessed, initial cardiac rhythm, performance of bystander cardiopulmonary resuscitation (CPR), and the response time of the paramedic unit were determined to be predictive of survival. However, the ACLS Score has not been validated in other emergency medical services systems. The purpose of this study was to externally validate the ACLS Score in one patient population. This was a retrospective cohort study performed at an urban county teaching hospital. The study population consisted of consecutive adult patients treated for out-of-hospital, nontraumatic cardiac arrest, and transported to the authors' institution between November 1, 1994, and September 30, 2001. Patient records for all cardiac arrests during the study period were reviewed. Study variables included witnessed arrest, initial arrest rhythm, bystander CPR, paramedic response time, and survival to hospital discharge. Predicted probability of survival to hospital discharge was calculated for each patient using the ACLS Score. The overall predicted and observed survival rates were compared using Flora's Z score. The Hosmer-Lemeshow test was used to evaluate the model's goodness-of-fit over a range of survival probabilities. Of 754 cardiac arrest patients enrolled in the study period, 575 (76%) patients had documentation that allowed scoring using the ACLS Score. Twenty-five (4%) patients survived to hospital discharge. The predicted number of survivors based on the ACLS Score was 104 (18%), yielding a Flora's Z statistic of -4.46 (p < 0.0001). After categorizing predicted survival probabilities into four categories, the resulting Hosmer-Lemeshow statistic was 210 (p < 10(-6)). Both goodness-of-fit statistics demonstrated extremely poor fit of the model. A receiver operating characteristic (ROC) curve was created, yielding an area under the ROC curve of 0

  17. A METHOD TO PREDICT AND UNDERSTAND FISH SURVIVAL UNDER DYNAMIC CHEMICAL STRESS USING STANDARD ECOTOXICITY DATA

    PubMed Central

    Ashauer, Roman; Thorbek, Pernille; Warinton, Jacqui S; Wheeler, James R; Maund, Steve

    2013-01-01

    The authors present a method to predict fish survival under exposure to fluctuating concentrations and repeated pulses of a chemical stressor. The method is based on toxicokinetic-toxicodynamic modeling using the general unified threshold model of survival (GUTS) and calibrated using raw data from standard fish acute toxicity tests. The model was validated by predicting fry survival in a fish early life stage test. Application of the model was demonstrated by using Forum for Co-ordination of Pesticide Fate Models and Their Use surface water (FOCUS-SW) exposure patterns as model input and predicting the survival of fish over 485 d. Exposure patterns were also multiplied by factors of five and 10 to achieve higher exposure concentrations for fish survival predictions. Furthermore, the authors quantified how far the exposure profiles were below the onset of mortality by finding the corresponding exposure multiplication factor for each scenario. The authors calculated organism recovery times as additional characteristic of toxicity as well as number of peaks, interval length between peaks, and mean duration as additional characteristics of the exposure pattern. The authors also calculated which of the exposure patterns had the smallest and largest inherent potential toxicity. Sensitivity of the model to parameter changes depends on the exposure pattern and differs between GUTS individual tolerance and GUTS stochastic death. Possible uses of the additional information gained from modeling to inform risk assessment are discussed. Environ. Toxicol. Chem. 2013;32:954–965. © 2013 SETAC PMID:23365017

  18. Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

    PubMed

    van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

    2017-01-01

    Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

  19. Overall Survival in Spine Myeloma Metastases: Difficulties in Predicting With Prognostic Scores.

    PubMed

    Amelot, Aymeric; Cristini, Joseph; Salaud, Céline; Moles, Alexis; Hamel, Olivier; Moreau, Philippe; Bord, Eric; Buffenoir, Kevin

    2017-03-15

    Fifty-one patients with spinal multiple myeloma (MM) metastases were operated and followed between January 2004 and July 2014. The aim of this study was to consider the efficiency of surgical prognosis scores in the management of spinal metastases myelomas. The spine is the most common site of bone metastases in MM. Surgery in spine metastases MM is a matter of debate and its impact on the increase of a patient's survival time is not clear. Several surgical survival scores have been developed to determine the best treatment in these patients. We studied 51 patients operated for spinal MM metastases between January 2004 and July 2014. We determined the Tokuhashi and Tomita survival scores and compared them with documented patient survivals. The two scores were also compared with the International Staging System (ISS). Median survival (MS) was 108 months [standard deviation (SD) 62] for ISS I, 132.2 (SD 40) for ISS II, and 45.5 months (SD 16.3) for ISS III (P = 0.09). According to Tokuhashi survival score, 21 patients (41.2%) will survive <6 months, 6 (11.8%) 6 to 12 months, and 24 (47%) >12 months. According to Tomita et al., 50 patients (98%) will survive >49.9 months and 1 patient (2%) <15 months. Regardless of the ISS grade prognosis, Tokuhashi survival score, and to a lesser extent Tomita score, underestimated the actual survival very significantly [P < 0.0001, Log Rank (Mantel-Cox)]. We suggest that spine surgical prognosis scores are not accurate and are not able to predict the survival of patients with spine myeloma metastases. Spine surgeons have to be guided not by the initial ISS stage but rather by spinal instability and neurological status. N/A.

  20. Low Serum Vitamin D Levels Are Associated With Inferior Survival in Follicular Lymphoma: A Prospective Evaluation in SWOG and LYSA Studies

    PubMed Central

    Kelly, Jennifer L.; Salles, Gilles; Goldman, Bryan; Fisher, Richard I.; Brice, Pauline; Press, Oliver; Casasnovas, Olivier; Maloney, David G.; Soubeyran, Pierre; Rimsza, Lisa; Haioun, Corinne; Xerri, Luc; LeBlanc, Michael; Tilly, Hervé; Friedberg, Jonathan W.

    2015-01-01

    Purpose Recent literature reports a potential association between high vitamin D and improved lymphoma prognosis. We evaluated the impact of pretreatment vitamin D on follicular lymphoma (FL) outcome. Patients and Methods SWOG participants were previously untreated patients with FL enrolled onto SWOG clinical trials (S9800, S9911, or S0016) involving CHOP chemotherapy plus an anti-CD20 antibody (rituximab or iodine-131 tositumomab) between 1998 and 2008. Participants included in our second independent cohort were also previously untreated patients with FL enrolled onto the Lymphoma Study Association (LYSA) PRIMA trial of rituximab plus chemotherapy (randomly assigned to rituximab maintenance v observation) between 2004 and 2007. Using the gold-standard liquid chromatography–tandem mass spectrometry method, 25-hydroxyvitamin D was measured in stored baseline serum samples. The primary end point was progression-free survival (PFS). Results After a median follow-up of 5.4 years, the adjusted PFS and overall survival hazard ratios for the SWOG cohort were 1.97 (95% CI, 1.10 to 3.53) and 4.16 (95% CI, 1.66 to 10.44), respectively, for those who were vitamin D deficient (< 20 ng/mL; 15% of cohort). After a median follow-up of 6.6 years, the adjusted PFS and overall survival hazard ratios for the LYSA cohort were 1.50 (95% CI, 0.93 to 2.42) and 1.92 (95% CI, 0.72 to 5.13), respectively, for those who were vitamin D deficient (< 10 ng/mL; 25% of cohort). Conclusion Although statistical significance was not reached in the LYSA cohort, the consistent estimates of association between low vitamin D levels and FL outcomes in two independent cohorts suggests that serum vitamin D might be the first potentially modifiable factor to be associated with FL survival. Further investigation is needed to determine the effects of vitamin D supplementation in this clinical setting. PMID:25823738

  1. Low Serum Vitamin D Levels Are Associated With Inferior Survival in Follicular Lymphoma: A Prospective Evaluation in SWOG and LYSA Studies.

    PubMed

    Kelly, Jennifer L; Salles, Gilles; Goldman, Bryan; Fisher, Richard I; Brice, Pauline; Press, Oliver; Casasnovas, Olivier; Maloney, David G; Soubeyran, Pierre; Rimsza, Lisa; Haioun, Corinne; Xerri, Luc; LeBlanc, Michael; Tilly, Hervé; Friedberg, Jonathan W

    2015-05-01

    Recent literature reports a potential association between high vitamin D and improved lymphoma prognosis. We evaluated the impact of pretreatment vitamin D on follicular lymphoma (FL) outcome. SWOG participants were previously untreated patients with FL enrolled onto SWOG clinical trials (S9800, S9911, or S0016) involving CHOP chemotherapy plus an anti-CD20 antibody (rituximab or iodine-131 tositumomab) between 1998 and 2008. Participants included in our second independent cohort were also previously untreated patients with FL enrolled onto the Lymphoma Study Association (LYSA) PRIMA trial of rituximab plus chemotherapy (randomly assigned to rituximab maintenance v observation) between 2004 and 2007. Using the gold-standard liquid chromatography-tandem mass spectrometry method, 25-hydroxyvitamin D was measured in stored baseline serum samples. The primary end point was progression-free survival (PFS). After a median follow-up of 5.4 years, the adjusted PFS and overall survival hazard ratios for the SWOG cohort were 1.97 (95% CI, 1.10 to 3.53) and 4.16 (95% CI, 1.66 to 10.44), respectively, for those who were vitamin D deficient (< 20 ng/mL; 15% of cohort). After a median follow-up of 6.6 years, the adjusted PFS and overall survival hazard ratios for the LYSA cohort were 1.50 (95% CI, 0.93 to 2.42) and 1.92 (95% CI, 0.72 to 5.13), respectively, for those who were vitamin D deficient (< 10 ng/mL; 25% of cohort). Although statistical significance was not reached in the LYSA cohort, the consistent estimates of association between low vitamin D levels and FL outcomes in two independent cohorts suggests that serum vitamin D might be the first potentially modifiable factor to be associated with FL survival. Further investigation is needed to determine the effects of vitamin D supplementation in this clinical setting. © 2015 by American Society of Clinical Oncology.

  2. Systematic review of FDG-PET prediction of complete pathological response and survival in rectal cancer.

    PubMed

    Memon, Sameer; Lynch, A Craig; Akhurst, Timothy; Ngan, Samuel Y; Warrier, Satish K; Michael, Michael; Heriot, Alexander G

    2014-10-01

    Advances in the management of rectal cancer have resulted in an increased application of multimodal therapy with the aim of tailoring therapy to individual patients. Complete pathological response (pCR) is associated with improved survival and may be potentially managed without radical surgical resection. Over the last decade, there has been increasing interest in the ability of functional imaging to predict complete response to treatment. The aim of this review was to assess the role of (18)F-flurordeoxyglucose positron emission tomography (FDG-PET) in prediction of pCR and prognosis in resectable locally advanced rectal cancer. A search of the MEDLINE and Embase databases was conducted, and a systematic review of the literature investigating positron emission tomography (PET) in the prediction of pCR and survival in rectal cancer was performed. Seventeen series assessing PET prediction of pCR were included in the review. Seven series assessed postchemoradiation SUVmax, which was significantly different between response groups in all six studies that assessed this. Nine series assessed the response index (RI) for SUVmax, which was significantly different between response groups in seven series. Thirteen studies investigated PET response for prediction of survival. Metabolic complete response assessed by SUV2max or visual response and RISUVmax showed strong associations with disease-free survival (DFS) and overall survival (OS). SUV2max and RISUVmax appear to be useful FDG-PET markers for prediction of pCR and these parameters also show strong associations with DFS and OS. FDG-PET may have a role in outcome prediction in patients with advanced rectal cancer.

  3. Reactive oxygen species-associated molecular signature predicts survival in patients with sepsis.

    PubMed

    Bime, Christian; Zhou, Tong; Wang, Ting; Slepian, Marvin J; Garcia, Joe G N; Hecker, Louise

    2016-06-01

    Sepsis-related multiple organ dysfunction syndrome is a leading cause of death in intensive care units. There is overwhelming evidence that oxidative stress plays a significant role in the pathogenesis of sepsis-associated multiple organ failure; however, reactive oxygen species (ROS)-associated biomarkers and/or diagnostics that define mortality or predict survival in sepsis are lacking. Lung or peripheral blood gene expression analysis has gained increasing recognition as a potential prognostic and/or diagnostic tool. The objective of this study was to identify ROS-associated biomarkers predictive of survival in patients with sepsis. In-silico analyses of expression profiles allowed the identification of a 21-gene ROS-associated molecular signature that predicts survival in sepsis patients. Importantly, this signature performed well in a validation cohort consisting of sepsis patients aggregated from distinct patient populations recruited from different sites. Our signature outperforms randomly generated signatures of the same signature gene size. Our findings further validate the critical role of ROSs in the pathogenesis of sepsis and provide a novel gene signature that predicts survival in sepsis patients. These results also highlight the utility of peripheral blood molecular signatures as biomarkers for predicting mortality risk in patients with sepsis, which could facilitate the development of personalized therapies.

  4. Predicting the survival rate of mouse embryonic stem cells cryopreserved in alginate beads.

    PubMed

    Sambu, S; Xu, X; Ye, H; Cui, Z F

    2011-11-01

    Stem cell cryopreservation in three-dimensional (3D) scaffolds may offer better protection to cells leading to higher survival rates. However, it introduces heterogeneity in cryoprotective agent (CPA) concentrations, durations of exposure to CPA, and freezing and thawing rate within constructs. This paper applies a mathematical model which couples the mass transport of dimethyl sulphoxide (DMSO) in a cell-seeded spherical construct and cell membrane transport into mouse embryonic stem cells (mESCs) to predict overall cell survival rate (CSR) based on CPA equilibrium exposure times (t(E)) and concentrations. The effect of freeze-concentration is also considered. To enable such a prediction, a contour plot was constructed using experimental data obtained in cryopreservation of cell suspensions with DMSO at a cooling rate of 1 degrees C/min. Thereafter, the diffusion in the alginate bead and the membrane transport of CPA was numerically simulated. Results were mapped onto the survival rate contours yielding 'predicted' CSR. The effects of loading time, hindrance, construct radius, and CPA concentration on predicted CSR were examined. From these results, an operation window with upper and lower t(E) of 12-19 min (for 0.6 mm radius beads and 1.4 M DMSO) yielded an overall viability of 60 per cent. The model predictions and the best experimental cryopreservation results with encapsulated mESCs were in agreement. Hence, optimization based on post-thaw CSR can accelerate the identification of cryopreservation protocols and parameters for maximizing cell survival.

  5. Reactive oxygen species–associated molecular signature predicts survival in patients with sepsis

    PubMed Central

    Zhou, Tong; Wang, Ting; Slepian, Marvin J.; Garcia, Joe G. N.; Hecker, Louise

    2016-01-01

    Abstract Sepsis-related multiple organ dysfunction syndrome is a leading cause of death in intensive care units. There is overwhelming evidence that oxidative stress plays a significant role in the pathogenesis of sepsis-associated multiple organ failure; however, reactive oxygen species (ROS)–associated biomarkers and/or diagnostics that define mortality or predict survival in sepsis are lacking. Lung or peripheral blood gene expression analysis has gained increasing recognition as a potential prognostic and/or diagnostic tool. The objective of this study was to identify ROS-associated biomarkers predictive of survival in patients with sepsis. In-silico analyses of expression profiles allowed the identification of a 21-gene ROS-associated molecular signature that predicts survival in sepsis patients. Importantly, this signature performed well in a validation cohort consisting of sepsis patients aggregated from distinct patient populations recruited from different sites. Our signature outperforms randomly generated signatures of the same signature gene size. Our findings further validate the critical role of ROSs in the pathogenesis of sepsis and provide a novel gene signature that predicts survival in sepsis patients. These results also highlight the utility of peripheral blood molecular signatures as biomarkers for predicting mortality risk in patients with sepsis, which could facilitate the development of personalized therapies. PMID:27252846

  6. The value of surrogate endpoints for predicting real-world survival across five cancer types.

    PubMed

    Shafrin, Jason; Brookmeyer, Ron; Peneva, Desi; Park, Jinhee; Zhang, Jie; Figlin, Robert A; Lakdawalla, Darius N

    2016-01-01

    It is unclear how well different outcome measures in randomized controlled trials (RCTs) perform in predicting real-world cancer survival. We assess the ability of RCT overall survival (OS) and surrogate endpoints - progression-free survival (PFS) and time to progression (TTP) - to predict real-world OS across five cancers. We identified 20 treatments and 31 indications for breast, colorectal, lung, ovarian, and pancreatic cancer that had a phase III RCT reporting median OS and median PFS or TTP. Median real-world OS was determined using a Kaplan-Meier estimator applied to patients in the Surveillance and Epidemiology End Results (SEER)-Medicare database (1991-2010). Performance of RCT OS and PFS/TTP in predicting real-world OS was measured using t-tests, median absolute prediction error, and R(2) from linear regressions. Among 72,600 SEER-Medicare patients similar to RCT participants, median survival was 5.9 months for trial surrogates, 14.1 months for trial OS, and 13.4 months for real-world OS. For this sample, regression models using clinical trial OS and trial surrogates as independent variables predicted real-world OS significantly better than models using surrogates alone (P = 0.026). Among all real-world patients using sample treatments (N = 309,182), however, adding trial OS did not improve predictive power over predictions based on surrogates alone (P = 0.194). Results were qualitatively similar using median absolute prediction error and R(2) metrics. Among the five tumor types investigated, trial OS and surrogates were each independently valuable in predicting real-world OS outcomes for patients similar to trial participants. In broader real-world populations, however, trial OS added little incremental value over surrogates alone.

  7. The ratio of absolute lymphocyte count at interim of therapy to absolute lymphocyte count at diagnosis predicts survival in childhood B-lineage acute lymphoblastic leukemia.

    PubMed

    Cheng, Yuping; Luo, Zebin; Yang, Shilong; Jia, Ming; Zhao, Haizhao; Xu, Weiqun; Tang, Yongmin

    2015-02-01

    Absolute lymphocyte count (ALC) after therapy has been reported to be an independent prognostic factor for clinical outcome in leukemia. This study mainly analyzed ALC at interim of therapy on day 22 (ALC-22) and the ratio of ALC-22 to ALC at diagnosis (ALC-0) on the impact of survival and the relation of ALC to lymphocyte subsets in 119 pediatric B-lineage acute lymphoblastic leukemia (B-ALL) patients. Univariate analysis revealed that ALC-22/ALC-0 ratio <10% was significantly associated with inferior overall survival (OS) (hazard ratio (HR)=12.24, P=0.0014) and event-free survival (EFS) (HR=3.3, P=0.0046). In multivariate analysis, ALC-22/ALC-0 ratio remained an independent prognostic factor for OS (HR=6.92, P=0.0181) and EFS (HR=2.78, P=0.0329) after adjusting for age, white blood cell (WBC) count and minimal residual disease (MRD) status. A Spearman correlation test showed that CD3+ T cells had a negative correlation with ALC-0 (r=-0.7204, P<0.0001) and a positive correlation with ALC-22 (r=0.5061, P=0.0071). These data suggest that ALC-22/ALC-0 ratio may serve as a more effective biomarker to predict survival in pediatric B-ALL and ALC is mainly associated with CD3+ T cells.

  8. Successful validation of a survival prediction model in patients with metastases in the spinal column

    SciTech Connect

    Chow, Edward . E-mail: Edward.Chow@sw.ca; Harris, Kristin; Fung, Kinwah

    2006-08-01

    Purpose: The Dutch Bone Metastases Study Group developed a survival prediction model in patients with symptomatic spinal bone metastases to guide the treating physician. The objective of this study was to validate the Dutch model and compare with our previously developed survival model at the Rapid Response Radiotherapy Program (RRRP model). Methods and Materials: The following prognostic factors were extracted from a prospective database in an outpatient palliative radiotherapy clinic: Karnofsky Performance Scores (KPS), primary cancer site, and visceral involvement for the Dutch model; primary cancer site, site of metastases, KPS, fatigue, appetite, and shortness of breath scores in the Edmonton Symptom Assessment Scale for the RRRP model. Patients were assigned scores according to each model. The survival probabilities were generated and calibration was performed for each model. Results: A total of 231 patients with spinal bone metastases from 1999 and 2002 were included in the analysis. The survival probabilities were similar to those in the original models. The calibration comparing actual survival with predicted survival from the Dutch and RRRP models gave R{sup 2} values of 0.90 and 0.86, respectively. Conclusion: The two models were successfully validated. The Dutch model using three clinical prognostic factors was easier to administer.

  9. Several microRNAs could predict survival in patients with hepatitis B-related liver cancer

    PubMed Central

    Zhen, Ye; Xinghui, Zhao; Chao, Wu; Yi, Zhao; Jinwen, Chen; Ruifang, Gao; Chao, Zhang; Min, Zhao; Chunlei, Guo; Yan, Fang; Lingfang, Du; Long, Shen; Wenzhi, Shen; Xiaohe, Luo; Rong, Xiang

    2017-01-01

    MicroRNAs as biomarkers play an important role in the tumorigenesis process, including hepatocellular carcinomas (HCCs). In this paper, we used The Cancer Genome Atlas (TCGA) database to mine hepatitis B-related liver cancer microRNAs that could predict survival in patients with hepatitis B-related liver cancer. There were 93 cases of HBV-HCC and 49 cases of adjacent normal controls included in the study. Kaplan–Meier survival analysis of a liver cancer group versus a normal control group of differentially expressed genes identified eight genes with statistical significance. Compared with the normal liver cell line, hepatocellular carcinoma cell lines had high expression of 8 microRNAs, albeit at different levels. A Cox proportional hazards regression model for multivariate analysis showed that four genes had a significant difference. We established classification models to distinguish short survival time and long survival time of liver cancers. Eight genes (mir9-3, mir10b, mir31, mir519c, mir522, mir3660, mir4784, and mir6883) were identified could predict survival in patients with HBV-HCC. There was a significant correlation between mir10b and mir31 and clinical stages (p < 0.05). A random forests model effectively estimated patient survival times. PMID:28322348

  10. Changes in clinical and physiologic variables predict survival in idiopathic pulmonary fibrosis.

    PubMed

    Collard, Harold R; King, Talmadge E; Bartelson, Becki Bucher; Vourlekis, Jason S; Schwarz, Marvin I; Brown, Kevin K

    2003-09-01

    There is significant heterogeneity in survival time among patients with idiopathic pulmonary fibrosis. Studies of baseline clinical and physiologic variables as predictors of survival time have reported inconsistent results. We evaluated the predictive value of changes in clinical and physiologic variables over time for survival time in 81 patients with biopsy-proven idiopathic pulmonary fibrosis. Six-month changes in dyspnea score, total lung capacity, thoracic gas volume, FVC, FEV1, diffusing capacity of carbon monoxide, partial pressure of arterial oxygen, oxygen saturation, and alveolar-arterial oxygen gradient were predictive of survival time even after adjustment for baseline values. Analyses were repeated on 51 patients with 12-month change data. Twelve-month changes in dyspnea score, total lung capacity, FVC, partial pressure of arterial oxygen, oxygen saturation, and alveolar-arterial oxygen gradient were predictive of survival time after adjustment for baseline values. Evaluation of changes in clinical and physiological variables over 6 and 12 months may provide clinicians with more accurate prognostic information than baseline values alone.

  11. Survival Outcomes Following Pediatric Liver Transplantation (Pedi-SOFT) Score: A Novel Predictive Index.

    PubMed

    Rana, A; Pallister, Z S; Guiteau, J J; Cotton, R T; Halazun, K; Nalty, C C; Khaderi, S A; O'Mahony, C A; Goss, J A

    2015-07-01

    A prognostic index to predict survival after liver transplantation could address several clinical needs. Here, we devised a scoring system that predicts recipient survival after pediatric liver transplantation. We used univariate and multivariate analysis on 4565 pediatric liver transplant recipients data and identified independent recipient and donor risk factors for posttransplant mortality at 3 months. Multiple imputation was used to account for missing variables. We identified five factors as significant predictors of recipient mortality after pediatric liver transplantation: two previous transplants (OR 5.88, CI 2.88-12.01), one previous transplant (OR 2.54, CI 1.75-3.68), life support (OR 3.68, CI 2.39-5.67), renal insufficiency (OR 2.66, CI 1.84-3.84), recipient weight under 6 kilograms (OR 1.67, CI 1.12-2.36) and cadaveric technical variant allograft (OR 1.38, CI 1.03-1.83). The Survival Outcomes Following Pediatric Liver Transplant score assigns weighted risk points to each of these factors in a scoring system to predict 3-month recipient survival after liver transplantation with a C-statistic of 0.74. Although quite accurate when compared with other posttransplant survival models, we would not advocate individual clinical application of the index. © Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons.

  12. Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques.

    PubMed

    Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L; Bilello, Michel; O'Rourke, Donald M; Davatzikos, Christos

    2016-03-01

    MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood-brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. © The Author(s) 2015. 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.

  13. Incremental shuttle walk test distance and autonomic dysfunction predict survival in pulmonary arterial hypertension.

    PubMed

    Billings, Catherine G; Hurdman, Judith A; Condliffe, Robin; Elliot, Charlie A; Smith, Ian A; Austin, Matthew; Armstrong, Iain J; Hamilton, Neil; Charalampopoulos, Athanasios; Sabroe, Ian; Swift, Andrew J; Rothman, Alexander M; Wild, Jim M; Lawrie, Allan; Waterhouse, Judith C; Kiely, David G

    2017-08-01

    To ensure effective monitoring of pulmonary arterial hypertension (PAH), a simple, reliable assessment of exercise capacity applicable over a range of disease severity is needed. The aim of this study was to assess the ability of the incremental shuttle walk test (ISWT) to correlate with disease severity, measure sensitivity to change, and predict survival in PAH. We enrolled 418 treatment-naïve patients with PAH with baseline ISWT within 3 months of cardiac catheterization. Clinical validity and prognostic value of ISWT distance were assessed at baseline and 1 year. ISWT distance was found to correlate at baseline with World Health Organization functional class, Borg score, and hemodynamics without a ceiling effect (all p < 0.001). Walking distance at baseline and after treatment predicted survival; the area under the receiver operating characteristic curve for ability of ISWT distance to predict mortality was 0.655 (95% confidence interval 0.553-0.757; p = 0.004) at baseline and 0.737 (95% confidence interval 0.643-0.827; p < 0.001) at 1 year after initiation of treatment. Change in ISWT distance also predicted survival (p = 0.04). Heart rate (HR) and systolic blood pressure (SBP) parameters reflecting autonomic response to exercise (highest HR, change in HR, HR recovery at 1 minute >18 beats/min, highest SBP, change in SBP, and 3-minute SBP ratio) were significant predictors of survival (all p < 0.05). In patients with PAH, the ISWT is simple to perform, allows assessment of maximal exercise capacity, is sensitive to treatment effect, predicts outcome, and has no ceiling effect. Also, measures of autonomic function made post-exercise predict survival in PAH. Copyright © 2017. Published by Elsevier Inc.

  14. Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

    PubMed Central

    Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M.; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V.; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L.; Bilello, Michel; O'Rourke, Donald M.; Davatzikos, Christos

    2016-01-01

    Background MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). Methods One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Results Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. Conclusions By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood–brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. PMID:26188015

  15. DWCox: A density-weighted Cox model for outlier-robust prediction of prostate cancer survival

    PubMed Central

    Xiao, Jinfeng; Wang, Sheng; Shang, Jingbo; Lin, Henry; Xin, Doris; Ren, Xiang; Han, Jiawei; Peng, Jian

    2016-01-01

    Reliable predictions on the risk and survival time of prostate cancer patients based on their clinical records can help guide their treatment and provide hints about the disease mechanism. The Cox regression is currently a commonly accepted approach for such tasks in clinical applications. More complex methods, like ensemble approaches, have the potential of reaching better prediction accuracy at the cost of increased training difficulty and worse result interpretability. Better performance on a specific data set may also be obtained by extensive manual exploration in the data space, but such developed models are subject to overfitting and usually not directly applicable to a different data set. We propose DWCox, a density-weighted Cox model that has improved robustness against outliers and thus can provide more accurate predictions of prostate cancer survival. DWCox assigns weights to the training data according to their local kernel density in the feature space, and incorporates those weights into the partial likelihood function. A linear regression is then used to predict the actual survival times from the predicted risks. In the 2015 Prostate Cancer DREAM Challenge, DWCox obtained the best average ranking in prediction accuracy on the risk and survival time. The success of DWCox is remarkable given that it is one of the smallest and most interpretable models submitted to the challenge. In simulations, DWCox performed consistently better than a standard Cox model when the training data contained many sparsely distributed outliers. Although developed for prostate cancer patients, DWCox can be easily re-trained and applied to other survival analysis problems. DWCox is implemented in R and can be downloaded from https://github.com/JinfengXiao/DWCox. PMID:28299178

  16. Comparison of Elixhauser and Charlson Methods for Predicting Oral Cancer Survival

    PubMed Central

    Chang, Heng-Jui; Chen, Po-Chun; Yang, Ching-Chieh; Su, Yu-Chieh; Lee, Ching-Chih

    2016-01-01

    Abstract Cancer survival correlates not only with the features of primary malignancy but also with the degree of underlying comorbidities. Of the multiple methods used for evaluating the impact of comorbidities on survival, the Charlson and Elixhauser methods are most common. This study compared these 2 comorbidity measures for predicting survival in oral cancer patients. Using the Taiwan National Health Insurance claims data (2008–2011), we acquired data regarding patients’ characteristics, comorbidities, and survival from 3583 oral cancer patients. Comorbidity was classified according to both the Charlson comorbidity and Elixhauser comorbidity based on the International Classification of Diseases, 9th Revision. The Elixhauser comorbidity score and Charlson comorbidity score were also calculated. The prediction of survival was determined using measures of discrimination, including the Akaike information criterion and Harrell C (C-statistic). The mean age of the study cohort was 52 ± 10 years, and 94.9% of the patients were male. The median follow-up time was 30.1 months, and the 3-year overall survival was 61.6%. Elixhauser comorbidity method added higher discrimination, compared with the Charlson comorbidity method (Harrell C, 0.677 vs 0.651). Furthermore, the Elixhauser comorbidity score outperformed the Charlson comorbidity score in continuous variable (Harrell C, 0.654 vs 0.646) and category (Harrell C, 0.658 vs 0.645). The Elixhauser method is a superior comorbidity risk-adjustment model for oral cancer survival prediction. Utilization of the Elixhauser comorbidity method may be encouraged for risk adjustment in oral cancer study. PMID:26886653

  17. Predicting potential survival benefit of renal transplantation in patients with chronic kidney disease

    PubMed Central

    van Walraven, Carl; Austin, Peter C.; Knoll, Greg

    2010-01-01

    Background To facilitate decision-making about treatment options for patients with end-stage renal disease considering kidney transplantation, we sought to develop an index for clinical prediction of risk for death. Methods We derived and validated a multivariable survival model predicting time to death in 169 393 patients with end-stage renal disease who were eligible for transplantation. We modified the model into a simple point-system index. Results Deaths occurred in 23.5% of the cohort. Twelve variables independently predicted death: age, race, cause of kidney failure, body mass index, comorbid disease, smoking, employment status, serum albumin level, year of first renal replacement therapy, kidney transplantation, time to transplant wait-listing and time on the wait list. The index separated patients into 26 groups having significantly unique five-year survival, ranging from 97.8% in the lowest-risk group to 24.7% in the highest-risk group. The index score was discriminative, with a concordance probability of 0.746 (95% CI 0.741–0.751). Observed survival in the derivation and validation cohorts was similar for each level of index score in 93.9% of patients. Interpretation Our prognostic index uses commonly available information to predict mortality accurately in patients with end-stage renal disease. This index could provide valuable quantitative data on survival for clinicians and patients to use when deciding whether to pursue transplantation or remain on dialysis. PMID:20351122

  18. Native cardiac reserve predicts survival in acute post infarction heart failure in mice

    PubMed Central

    Täng, Margareta Scharin; Råmunddal, Truls; Lindbom, Malin; Omerovic, Elmir

    2007-01-01

    Cardiac reserve can be used to predict survival and outcome in patients with heart failure. The aim of this study was to investigate if native cardiac reserve could predict survival after myocardial infarction (MI) in mice. Method We investigated 27 healthy C57Bl6 mice (♂10–12 weeks old) with echocardiography using a high-frequency 15-MHz linear transducer. Investigations were performed both at rest and after pharmacological stress induced by dobutamine (1 μg/g body weight i.p.). The day after the echocardiography examination, a large MI was induced by ligation of the left anterior descending (LAD) coronary artery for evaluation of mortality rate. Results Two weeks after induction of MI, 7 mice were alive (26%). Evaluation of the difference between the surviving and deceased animals showed that the survivors had a better native ability to increase systolic performance (ΔLVESd -1.86 vs -1.28mm p = 0.02) upon dobutamine challenge, resulting in a better cardiac reserve (ΔFS 37 vs 25% p = 0.02 and ΔCO 0.27 vs -0.10 ml/min p = 0.02) and a better chronotropic reserve (ΔR-R interval -68 vs -19 ms p < 0.01). A positive relationship was found between ability to survive and both cardiac (p < 0.05) and chronotropic reserve (p < 0.05) when the mice were divided into three groups: survivors, surviving < 7 days, and surviving < 1 day. Conclusion We conclude that before MI induction the surviving animals had a better cardiac function compared with the deceased. This indicates that native cardiac and chronotropic reserve may be an important determinant and predictor of survival in the setting of large MI and post-infarction heart failure. PMID:18053159

  19. Deep Learning based multi-omics integration robustly predicts survival in liver cancer.

    PubMed

    Chaudhary, Kumardeep; Poirion, Olivier B; Lu, Liangqun; Garmire, Lana X

    2017-10-05

    Identifying robust survival subgroups of hepatocellular carcinoma (HCC) will significantly improve patient care. Currently, endeavor of integrating multi-omics data to explicitly predict HCC survival from multiple patient cohorts is lacking. To fill in this gap, we present a deep learning (DL) based model on HCC that robustly differentiates survival subpopulations of patients in six cohorts. We build the DL based, survival-sensitive model on 360 HCC patients' data using RNA-seq, miRNA-seq and methylation data from TCGA, which predicts prognosis as good as an alternative model where genomics and clinical data are both considered. This DL based model provides two optimal subgroups of patients with significant survival differences (P=7.13e-6) and good model fitness (C-index=0.68). More aggressive subtype is associated with frequent TP53 inactivation mutations, higher expression of stemness markers (KRT19, EPCAM) and tumor marker BIRC5, and activated Wnt and Akt signaling pathways. We validated this multi-omics model on five external datasets of various omics types: LIRI-JP cohort (n=230, C-index=0.75), NCI cohort (n=221, C-index=0.67), Chinese cohort (n=166, C-index=0.69), E-TABM-36 cohort (n=40, C-index=0.77), and Hawaiian cohort (n=27, C-index=0.82). This is the first study to employ deep learning to identify multi-omics features linked to the differential survival of HCC patients. Given its robustness over multiple cohorts, we expect this workflow to be useful at predicting HCC prognosis prediction. Copyright ©2017, American Association for Cancer Research.

  20. Dynamic model for predicting survival of mature larvae of Tribolium confusum during facility heat treatments.

    PubMed

    Boina, Dhana Raj; Subramanyam, Bhadriraju; Alavi, Sajid

    2008-06-01

    Structural heat treatment, a viable alternative to methyl bromide fumigation, involves raising the ambient temperature of food-processing facilities between 50 and 60 degrees C by using gas, electric, or steam heaters, and holding these elevated temperatures for 24 h or longer to kill stored-product insects. A dynamic model was developed to predict survival of mature larvae, which is the most heat-tolerant stage of the confused flour beetle, Tribolium confusum (Jacquelin du Val), at elevated temperatures between 46 and 60 degrees C. The model is based on two nonlinear relationships: 1) logarithmic survival of T. confusum mature larvae as a function of time, and 2) logarithmic reduction in larval survival as a function of temperature. The dynamic model was validated with nine independent data sets collected during actual facility heat treatments conducted on two separate occasions at the Kansas State University pilot flour and feed mills. The rate of increase of temperature over time varied among the nine locations where mature larvae of T. confusum were exposed, and the approximate heating rates during the entire heat treatment ranged from 1.1 to 13.2 degrees C/h. The absolute deviation in the predicted number of larvae surviving the heat treatment was within 3-7% of the actual observed data. Comparison of the absolute deviation in the time taken for equivalent larval survival showed that the model predictions were within 2-6% of the observed data. The dynamic model can be used to predict survival of mature larvae of T. confusum during heat treatments of food-processing facilities based on time-dependent temperature profiles obtained at any given location.

  1. Predicting patient survival after deceased donor kidney transplantation using flexible parametric modelling.

    PubMed

    Li, Bernadette; Cairns, John A; Robb, Matthew L; Johnson, Rachel J; Watson, Christopher J E; Forsythe, John L; Oniscu, Gabriel C; Ravanan, Rommel; Dudley, Christopher; Roderick, Paul; Metcalfe, Wendy; Tomson, Charles R; Bradley, J Andrew

    2016-05-25

    The influence of donor and recipient factors on outcomes following kidney transplantation is commonly analysed using Cox regression models, but this approach is not useful for predicting long-term survival beyond observed data. We demonstrate the application of a flexible parametric approach to fit a model that can be extrapolated for the purpose of predicting mean patient survival. The primary motivation for this analysis is to develop a predictive model to estimate post-transplant survival based on individual patient characteristics to inform the design of alternative approaches to allocating deceased donor kidneys to those on the transplant waiting list in the United Kingdom. We analysed data from over 12,000 recipients of deceased donor kidney or combined kidney and pancreas transplants between 2003 and 2012. We fitted a flexible parametric model incorporating restricted cubic splines to characterise the baseline hazard function and explored a range of covariates including recipient, donor and transplant-related factors. Multivariable analysis showed the risk of death increased with recipient and donor age, diabetic nephropathy as the recipient's primary renal diagnosis and donor hypertension. The risk of death was lower in female recipients, patients with polycystic kidney disease and recipients of pre-emptive transplants. The final model was used to extrapolate survival curves in order to calculate mean survival times for patients with specific characteristics. The use of flexible parametric modelling techniques allowed us to address some of the limitations of both the Cox regression approach and of standard parametric models when the goal is to predict long-term survival.

  2. High Pretreatment D-Dimer Levels Correlate with Adverse Clinical Features and Predict Poor Survival in Patients with Natural Killer/T-Cell Lymphoma.

    PubMed

    Bi, Xi-wen; Wang, Liang; Zhang, Wen-wen; Sun, Peng; Yan, Shu-mei; Liu, Pan-pan; Li, Zhi-ming; Jiang, Wen-qi

    2016-01-01

    Pretreatment plasma D-dimer levels have been reported to predict survival in several types of malignancies. The aim of this study was to evaluate the prognostic value of D-dimer levels in patients with newly diagnosed natural killer/T-cell lymphoma (NKTCL). The cut-off value of D-dimer to predict survival was set as 1.2 μg/mL based on the receiver operating curve analysis. Patients with a D-dimer level ≥ 1.2 μg/mL had significantly more adverse clinical features, including poor performance status, advanced stage diseases, B symptoms, elevated serum lactic dehydrogenase levels, involvement of regional lymph nodes, more extranodal diseases, and higher International Prognostic Index and natural killer/T-cell lymphoma prognostic index scores. A D-dimer level ≥ 1.2 μg/mL was significantly associated with inferior 3-year overall survival (OS, 13.0 vs. 68.5%, P < 0.001). In the multivariate analysis, a D-dimer level ≥ 1.2 μg/mL remained an independent predictor for worse OS (HR: 3.13, 95% CI: 1.47-6.68, P = 0.003) after adjusting for other confounding prognostic factors. Among patients with Ann Arbor stage I-II diseases, those with a D-dimer level ≥ 1.2 μg/mL had a significantly worse survival than those with a D-dimer level < 1.2 μg/mL (3 year-OS: 76.2 vs. 22.2%, P < 0.001). Survival of early-stage patients with a high D-dimer level was similar to that of the advanced-stage patients. In conclusion, pretreatment plasma D-dimer level may serve as a simple but effective predictor of prognosis in patients with NKTCL.

  3. Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic

    PubMed Central

    Wang, Ming; Long, Qi

    2016-01-01

    Summary Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c–statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy are assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations. PMID:26756274

  4. Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic.

    PubMed

    Wang, Ming; Long, Qi

    2016-09-01

    Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c-statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy is assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations.

  5. Predicting survival in malignant pleural effusion: development and validation of the LENT prognostic score.

    PubMed

    Clive, Amelia O; Kahan, Brennan C; Hooper, Clare E; Bhatnagar, Rahul; Morley, Anna J; Zahan-Evans, Natalie; Bintcliffe, Oliver J; Boshuizen, Rogier C; Fysh, Edward T H; Tobin, Claire L; Medford, Andrew R L; Harvey, John E; van den Heuvel, Michel M; Lee, Y C Gary; Maskell, Nick A

    2014-12-01

    Malignant pleural effusion (MPE) causes debilitating breathlessness and predicting survival is challenging. This study aimed to obtain contemporary data on survival by underlying tumour type in patients with MPE, identify prognostic indicators of overall survival and develop and validate a prognostic scoring system. Three large international cohorts of patients with MPE were used to calculate survival by cell type (univariable Cox model). The prognostic value of 14 predefined variables was evaluated in the most complete data set (multivariable Cox model). A clinical prognostic scoring system was then developed and validated. Based on the results of the international data and the multivariable survival analysis, the LENT prognostic score (pleural fluid lactate dehydrogenase, Eastern Cooperative Oncology Group (ECOG) performance score (PS), neutrophil-to-lymphocyte ratio and tumour type) was developed and subsequently validated using an independent data set. Risk stratifying patients into low-risk, moderate-risk and high-risk groups gave median (IQR) survivals of 319 days (228-549; n=43), 130 days (47-467; n=129) and 44 days (22-77; n=31), respectively. Only 65% (20/31) of patients with a high-risk LENT score survived 1 month from diagnosis and just 3% (1/31) survived 6 months. Analysis of the area under the receiver operating curve revealed the LENT score to be superior at predicting survival compared with ECOG PS at 1 month (0.77 vs 0.66, p<0.01), 3 months (0.84 vs 0.75, p<0.01) and 6 months (0.85 vs 0.76, p<0.01). The LENT scoring system is the first validated prognostic score in MPE, which predicts survival with significantly better accuracy than ECOG PS alone. This may aid clinical decision making in this diverse patient population. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  6. Serum alkaline phosphatase predicts survival outcomes in patients with skeletal metastatic nasopharyngeal carcinoma.

    PubMed

    Jin, Ying; Yuan, Mei-Qin; Chen, Jun-Qing; Zhang, Yi-Ping

    2015-04-01

    Bone metastasis is frequently associated with nasopharyngeal carcinoma. The diagnosis and follow-up of bone metastatic patients usually relies on skeletal X-ray and bone scintigraphy, which are time-consuming and costly. This study aimed to evaluate whether serum alkaline phosphatase offers clinical value in predicting the clinical response and survival outcome for skeletal metastatic nasopharyngeal carcinoma. Serum alkaline phosphatase was measured at baseline and then before each cycle of treatment in 416 nasopharyngeal carcinoma patients with bone metastasis. The correlations between the pre-treatment and post-treatment alkaline phosphatase levels and the treatment efficacy were analyzed using the chi-square test. Survival was analyzed using the Kaplan-Meier method and then compared using the log-rank test. Patients with elevated pre-treatment alkaline phosphatase (>110 IU/L) had significantly worse progression-free survival (P<0.001) and overall survival (P<0.001) than those with a normal level of this marker (≤110 IU/L). Patients with elevated post-treatment alkaline phosphatase had worse progression-free survival (P<0.001) and overall survival (P<0.001) compared with those with a normal level. Patients with normal pre-treatment and post-treatment alkaline phosphatase showed the most favorable prognosis. The Cox multivariate analysis revealed that only the pre-treatment and post-treatment alkaline phosphatase levels were independent prognostic factors for progression-free survival (HR ϝ 1.656, P<0.001; HR ϝ 2.226, P<0.001) and for overall survival (HR ϝ 1.794, P<0.001; HR ϝ 2.657, P<0.001). Serum alkaline phosphatase appears to be a significant independent prognostic index in patients with skeletal metastatic nasopharyngeal carcinoma, which could reflect the short-term treatment response of palliative chemotherapy and the long-term survival outcomes.

  7. Functional cardiovascular reserve predicts survival pre-kidney and post-kidney transplantation.

    PubMed

    Ting, Stephen M S; Iqbal, Hasan; Kanji, Hemali; Hamborg, Thomas; Aldridge, Nicolas; Krishnan, Nithya; Imray, Chris H E; Banerjee, Prithwish; Bland, Rosemary; Higgins, Robert; Zehnder, Daniel

    2014-01-01

    Exercise intolerance is an important comorbidity in patients with CKD. Anaerobic threshold (AT) determines the upper limits of aerobic exercise and is a measure of cardiovascular reserve. This study investigated the prognostic capacity of AT on survival in patients with advanced CKD and the effect of kidney transplantation on survival in those with reduced cardiovascular reserve. Using cardiopulmonary exercise testing, cardiovascular reserve was evaluated in 240 patients who were waitlisted for kidney transplantation between 2008 and 2010, and patients were followed for ≤5 years. Survival time was the primary endpoint. Cumulative survival for the entire cohort was 72.6% (24 deaths), with cardiovascular events being the most common cause of death (54.2%). According to Kaplan-Meier estimates, patients with AT <40% of predicted peak VO2 had a significantly reduced 5-year cumulative overall survival rate compared with those with AT ≥40% (P<0.001). Regarding the cohort with AT <40%, patients who underwent kidney transplantation (6 deaths) had significantly better survival compared with nontransplanted patients (17 deaths) (hazard ratio, 4.48; 95% confidence interval, 1.78 to 11.38; P=0.002). Survival did not differ significantly among patients with AT ≥40%, with one death in the nontransplanted group and no deaths in the transplanted group. In summary, this is the first prospective study to demonstrate a significant association of AT, as the objective index of cardiovascular reserve, with survival in patients with advanced CKD. High-risk patients with reduced cardiovascular reserve had a better survival rate after receiving a kidney transplant.

  8. Lung Cancer Survival Prediction using Ensemble Data Mining on Seer Data

    DOE PAGES

    Agrawal, Ankit; Misra, Sanchit; Narayanan, Ramanathan; ...

    2012-01-01

    We analyze the lung cancer data available from the SEER program with the aim of developing accurate survival prediction models for lung cancer. Carefully designed preprocessing steps resulted in removal/modification/splitting of several attributes, and 2 of the 11 derived attributes were found to have significant predictive power. Several supervised classification methods were used on the preprocessed data along with various data mining optimizations and validations. In our experiments, ensemble voting of five decision tree based classifiers and meta-classifiers was found to result in the best prediction performance in terms of accuracy and area under the ROC curve. We have developedmore » an on-line lung cancer outcome calculator for estimating the risk of mortality after 6 months, 9 months, 1 year, 2 year and 5 years of diagnosis, for which a smaller non-redundant subset of 13 attributes was carefully selected using attribute selection techniques, while trying to retain the predictive power of the original set of attributes. Further, ensemble voting models were also created for predicting conditional survival outcome for lung cancer (estimating risk of mortality after 5 years of diagnosis, given that the patient has already survived for a period of time), and included in the calculator. The on-line lung cancer outcome calculator developed as a result of this study is available at http://info.eecs.northwestern.edu:8080/LungCancerOutcomeCalculator/.« less

  9. Immune function and adjustment style: do they predict survival in breast cancer?

    PubMed

    Osborne, Richard H; Sali, Avni; Aaronson, Neil K; Elsworth, Gerald R; Mdzewski, Bogdan; Sinclair, Andrew J

    2004-03-01

    The aim of this study was to investigate the role of immune status and psychosocial factors in survival from early breast cancer (N=61). Baseline assessments included lymphocyte number and function, natural killer cell activity (NKA), plasma cortisol and prolactin level. Psychosocial measures included anxiety, depression and mental adjustment to cancer and social support. Length of follow-up was 6.1-7.9 years with 14 (23%) breast cancer deaths. In Cox proportional hazards models adjusting for lymph node status two parameters predicted longer survival, low NKA (HR 29 per LLU, p=0.003) and minimizing the illness adjustment (HR 0.64 per scale point, p=0.012). These data provide little evidence for a psychoneuroimmunological mechanism in the survival from breast cancer. While this study is limited due to small sample size, and therefore the possibility of inflated estimates, longer survival in those minimizing the illness is a finding consistent with recent studies; however, the counter-intuitive finding that high NKA predicts shorter survival may be a marker for current disease or response to treatments. Copyright 2003 John Wiley & Sons, Ltd.

  10. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird

    PubMed Central

    Milenkaya, Olga; Catlin, Daniel H.; Legge, Sarah; Walters, Jeffrey R.

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage) such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous interpretation of

  11. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

    PubMed

    Milenkaya, Olga; Catlin, Daniel H; Legge, Sarah; Walters, Jeffrey R

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage) such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous interpretation of

  12. Upper Extremity Pulse Pressure Predicts Amputation-Free Survival after Lower Extremity Bypass.

    PubMed

    Wise, Eric S; Wergin, Justine E; Mace, Eric H; Kallos, Justiss A; Muhlestein, Whitney E; Shelburne, Nicholas J; Hocking, Kyle M; Brophy, Colleen M; Guzman, Raul J

    2017-07-01

    Increased pulse pressure reflects pathologic arterial stiffening and predicts cardiovascular events and mortality. The effect of pulse pressure on outcomes in lower extremity bypass patients remains unknown. We thus investigated whether preoperative pulse pressure could predict amputation-free survival in patients undergoing lower extremity bypass for atherosclerotic occlusive disease. An institutional database identified 240 included patients undergoing lower extremity bypass from 2005 to 2014. Preoperative demographics, cardiovascular risk factors, operative factors, and systolic and diastolic blood pressures were recorded, and compared between patients with pulse pressures above and below 80 mm Hg. Factors were analyzed in bi- and multivariable models to assess independent predictors of amputation-free survival. Kaplan-Meier analysis was performed to evaluate the temporal effect of pulse pressure ≥80 mm Hg on amputation-free survival. Patients with a pulse pressure ≥80 mm Hg were older, male, and had higher systolic and lower diastolic pressures. Patients with pulse pressure <80 mm Hg demonstrated a survival advantage on Kaplan-Meier analysis at six months (log-rank P = 0.003) and one year (P = 0.005) postoperatively. In multivariable analysis, independent risk factors for decreased amputation-free survival at six months included nonwhite race, tissue loss, infrapopliteal target, and preoperative pulse pressure ≥80 mm Hg (hazard ratio 2.60; P = 0.02), while only tissue loss and pulse pressure ≥80 mm Hg (hazard ratio 2.30, P = 0.02) remained predictive at one year. Increased pulse pressure is independently associated with decreased amputation-free survival in patients undergoing lower extremity bypass. Further efforts to understand the relationship between increased arterial stiffness and poor outcomes in these patients are needed.

  13. Predictive validity of neuropsychiatric subgroups on nursing home placement and survival in patients with Alzheimer disease.

    PubMed

    Tun, Saw-Myo; Murman, Daniel L; Long, Heidi L; Colenda, Christopher C; von Eye, Alexander

    2007-04-01

    The aim of the study was to conceptualize neuropsychiatric symptoms in patients with Alzheimer disease as distinct symptom profiles with differential disease outcomes. Two outcomes of interest in the study were nursing home placement and survival. Cluster analysis was used to categorize 122 patients with Alzheimer disease based on their neuropsychiatric symptoms as assessed by the Neuropsychiatric Inventory. Both the presence as well as the severity and frequency of symptoms were considered. After identification of the subgroups, the predictive validity of the categorization was tested on time to nursing home placement and time to death over a three-year period. Cox proportional hazard models were used to perform survival analysis. Important covariates such as severity of cognitive and functional impairments, comorbid medical conditions, presence of parkinsonism, and marital status were adjusted at baseline. Based on the presence of neuropsychiatric symptoms, three subgroups were identified: minimally symptomatic, highly symptomatic, and affective/apathetic. Over a three-year period, the highly symptomatic group had an increased risk of nursing home placement. In addition, the rates of survival were significantly lower for the highly symptomatic and the affective/apathetic subgroups. Based on the severity and frequency of symptoms, two-cluster and four-cluster solutions were produced. The groupings based on severity and frequency of symptoms predicted significant differential outcomes in survival and nursing home placement. Neuropsychiatric subgroups were able to predict differential outcomes and identify those with an increased risk for a worse prognosis. The findings were discussed through their research and clinical implications.

  14. Development of a Summarized Health Index (SHI) for Use in Predicting Survival in Sea Turtles

    PubMed Central

    Li, Tsung-Hsien; Chang, Chao-Chin; Cheng, I-Jiunn; Lin, Suen-Chuain

    2015-01-01

    Veterinary care plays an influential role in sea turtle rehabilitation, especially in endangered species. Physiological characteristics, hematological and plasma biochemistry profiles, are useful references for clinical management in animals, especially when animals are during the convalescence period. In this study, these factors associated with sea turtle surviving were analyzed. The blood samples were collected when sea turtles remained alive, and then animals were followed up for surviving status. The results indicated that significantly negative correlation was found between buoyancy disorders (BD) and sea turtle surviving (p < 0.05). Furthermore, non-surviving sea turtles had significantly higher levels of aspartate aminotranspherase (AST), creatinine kinase (CK), creatinine and uric acid (UA) than surviving sea turtles (all p < 0.05). After further analysis by multiple logistic regression model, only factors of BD, creatinine and UA were included in the equation for calculating summarized health index (SHI) for each individual. Through evaluation by receiver operating characteristic (ROC) curve, the result indicated that the area under curve was 0.920 ± 0.037, and a cut-off SHI value of 2.5244 showed 80.0% sensitivity and 86.7% specificity in predicting survival. Therefore, the developed SHI could be a useful index to evaluate health status of sea turtles and to improve veterinary care at rehabilitation facilities. PMID:25803431

  15. Development of a Summarized Health Index (SHI) for use in predicting survival in sea turtles.

    PubMed

    Li, Tsung-Hsien; Chang, Chao-Chin; Cheng, I-Jiunn; Lin, Suen-Chuain

    2015-01-01

    Veterinary care plays an influential role in sea turtle rehabilitation, especially in endangered species. Physiological characteristics, hematological and plasma biochemistry profiles, are useful references for clinical management in animals, especially when animals are during the convalescence period. In this study, these factors associated with sea turtle surviving were analyzed. The blood samples were collected when sea turtles remained alive, and then animals were followed up for surviving status. The results indicated that significantly negative correlation was found between buoyancy disorders (BD) and sea turtle surviving (p < 0.05). Furthermore, non-surviving sea turtles had significantly higher levels of aspartate aminotranspherase (AST), creatinine kinase (CK), creatinine and uric acid (UA) than surviving sea turtles (all p < 0.05). After further analysis by multiple logistic regression model, only factors of BD, creatinine and UA were included in the equation for calculating summarized health index (SHI) for each individual. Through evaluation by receiver operating characteristic (ROC) curve, the result indicated that the area under curve was 0.920 ± 0.037, and a cut-off SHI value of 2.5244 showed 80.0% sensitivity and 86.7% specificity in predicting survival. Therefore, the developed SHI could be a useful index to evaluate health status of sea turtles and to improve veterinary care at rehabilitation facilities.

  16. A simple model for predicting survival of angler-caught and released largemouth bass

    USGS Publications Warehouse

    Wilde, G.R.; Pope, K.L.

    2008-01-01

    We conducted a controlled experiment in the laboratory to assess the influence of anatomical hooking location and water temperature on survival of angler-caught and released largemouth bass Micropterus salmoides. Survival was 98% (58 of 59 fish) among fish that were hand-hooked within the oral cavity (including the gills), whereas survival was 66% (33 of 50 fish) among fish that were hand-hooked in the esophagus. Survival of hooked fish was not significantly influenced by water temperature (7-27??C) or the hooking location X water temperature interaction. We combined our results with prior research to develop a predictive model of largemouth bass survival, which was 98.3% (SD = 1.87%) for fish hooked in the oral cavity and 55.0% (SD = 9.70%) for fish hooked in the esophagus. The model is valid for water temperatures ranging from 7??C to 27??C and allows one to estimate, with known precision, the survival of angler-caught and released largemouth bass without the need for controlled studies or for holding fish in pens or cages to assess delayed mortality. ?? Copyright by the American Fisheries Society 2008.

  17. Comparison of slow and forced vital capacities on ability to predict survival in ALS.

    PubMed

    Pinto, Susana; de Carvalho, Mamede

    2017-07-25

    Slow (SVC) and forced (FVC) vital capacities are the most used pulmonary function tests in amyotrophic lateral sclerosis (ALS). It is unknown if they equally predict survival in ALS. The aim of the present study was to compare both measures in predicting survival in this disease. Consecutive definite/probable ALS patients (2000-2014) in whom respiratory tests were performed at baseline and four months later were included. All patients were evaluated with the revised ALS functional rating scale (ALSFRS-R), respiratory (RofALSFRS-R), bulbar (ALSFRSb), upper and lower limb subscores, SVC, FVC, maximal inspiratory (MIP) and expiratory (MEP) pressures. King's functional staging system was applied retrospectively. Survival analysis was carried out by univariate Kaplan-Meier log-rank test. Multivariate Cox proportional hazards model determined significant independent variables. We included 469 patients (270 males; mean onset age 61.0 ± 11.5 years; mean disease duration from first symptoms to first visit: 15.8 ± 16.1months; 329 spinal and 140 bulbar onset). FVC and SVC were strongly correlated (r(2) = 0.981, p < 0.001). Significant survival prognostic variables (Kaplan-Meier analyses) were onset region, age, disease duration, ALSFRS-R, ALSFRSb, RofALSFRS-R, ALSFRS-R decay, SVC, FVC, MIP, MEP and King's staging (p ≤ 0.01). Final Cox model including the significant variables showed similar results for FVC and SVC (p < 0.001). Moreover, 1% decrease in either predicted values increased death probability by 1.02. FVC and SVC are inter-changeable in predicting survival in ALS.

  18. Survival prediction model of children with diffuse intrinsic pontine glioma based on clinical and radiological criteria.

    PubMed

    Jansen, Marc H; Veldhuijzen van Zanten, Sophie E; Sanchez Aliaga, Esther; Heymans, Martijn W; Warmuth-Metz, Monika; Hargrave, Darren; van der Hoeven, Erica J; Gidding, Corrie E; de Bont, Eveline S; Eshghi, Omid S; Reddingius, Roel; Peeters, Cacha M; Schouten-van Meeteren, Antoinette Y N; Gooskens, Rob H J; Granzen, Bernd; Paardekooper, Gabriel M; Janssens, Geert O; Noske, David P; Barkhof, Frederik; Kramm, Christof M; Vandertop, W Peter; Kaspers, Gertjan J; van Vuurden, Dannis G

    2015-01-01

    Although diffuse intrinsic pontine glioma (DIPG) carries the worst prognosis of all pediatric brain tumors, studies on prognostic factors in DIPG are sparse. To control for confounding variables in DIPG studies, which generally include relatively small patient numbers, a survival prediction tool is needed. A multicenter retrospective cohort study was performed in the Netherlands, the UK, and Germany with central review of clinical data and MRI scans of children with DIPG. Cox proportional hazards with backward regression was used to select prognostic variables (P < .05) to predict the accumulated 12-month risk of death. These predictors were transformed into a practical risk score. The model's performance was validated by bootstrapping techniques. A total of 316 patients were included. The median overall survival was 10 months. Multivariate Cox analysis yielded 5 prognostic variables of which the coefficients were included in the risk score. Age ≤3 years, longer symptom duration at diagnosis, and use of oral and intravenous chemotherapy were favorable predictors, while ring enhancement on MRI at diagnosis was an unfavorable predictor. With increasing risk score categories, overall survival decreased significantly. The model can distinguish between patients with very short, average, and increased overall survival (medians of 7.0, 9.7, and 13.7 mo, respectively). The area under the receiver operating characteristic curve was 0.68. We developed a DIPG survival prediction tool that can be used to predict the outcome of patients and for stratification in trials. Validation of the model is needed in a prospective cohort. © The Author(s) 2014. 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.

  19. HSP70 mediates survival in apoptotic cells—Boolean network prediction and experimental validation

    PubMed Central

    Vasaikar, Suhas V.; Ghosh, Sourish; Narain, Priyam; Basu, Anirban; Gomes, James

    2015-01-01

    Neuronal stress or injury results in the activation of proteins, which regulate the balance between survival and apoptosis. However, the complex mechanism of cell signaling involving cell death and survival, activated in response to cellular stress is not yet completely understood. To bring more clarity about these mechanisms, a Boolean network was constructed that represented the apoptotic pathway in neuronal cells. FasL and neurotrophic growth factor (NGF) were considered as inputs in the absence and presence of heat shock proteins known to shift the balance toward survival by rescuing pro-apoptotic cells. The probabilities of survival, DNA repair and apoptosis as cellular fates, in the presence of either the growth factor or FasL, revealed a survival bias encoded in the network. Boolean predictions tested by measuring the mRNA level of caspase-3, caspase-8, and BAX in neuronal Neuro2a (N2a) cell line with NGF and FasL as external input, showed positive correlation with the observed experimental results for survival and apoptotic states. It was observed that HSP70 contributed more toward rescuing cells from apoptosis in comparison to HSP27, HSP40, and HSP90. Overexpression of HSP70 in N2a transfected cells showed reversal of cellular fate from FasL-induced apoptosis to survival. Further, the pro-survival role of the proteins BCL2, IAP, cFLIP, and NFκB determined by vertex perturbation analysis was experimentally validated through protein inhibition experiments using EM20-25, Embelin and Wedelolactone, which resulted in 1.27-, 1.26-, and 1.46-fold increase in apoptosis of N2a cells. The existence of a one-to-one correspondence between cellular fates and attractor states shows that Boolean networks may be employed with confidence in qualitative analytical studies of biological networks. PMID:26379495

  20. HSP70 mediates survival in apoptotic cells-Boolean network prediction and experimental validation.

    PubMed

    Vasaikar, Suhas V; Ghosh, Sourish; Narain, Priyam; Basu, Anirban; Gomes, James

    2015-01-01

    Neuronal stress or injury results in the activation of proteins, which regulate the balance between survival and apoptosis. However, the complex mechanism of cell signaling involving cell death and survival, activated in response to cellular stress is not yet completely understood. To bring more clarity about these mechanisms, a Boolean network was constructed that represented the apoptotic pathway in neuronal cells. FasL and neurotrophic growth factor (NGF) were considered as inputs in the absence and presence of heat shock proteins known to shift the balance toward survival by rescuing pro-apoptotic cells. The probabilities of survival, DNA repair and apoptosis as cellular fates, in the presence of either the growth factor or FasL, revealed a survival bias encoded in the network. Boolean predictions tested by measuring the mRNA level of caspase-3, caspase-8, and BAX in neuronal Neuro2a (N2a) cell line with NGF and FasL as external input, showed positive correlation with the observed experimental results for survival and apoptotic states. It was observed that HSP70 contributed more toward rescuing cells from apoptosis in comparison to HSP27, HSP40, and HSP90. Overexpression of HSP70 in N2a transfected cells showed reversal of cellular fate from FasL-induced apoptosis to survival. Further, the pro-survival role of the proteins BCL2, IAP, cFLIP, and NFκB determined by vertex perturbation analysis was experimentally validated through protein inhibition experiments using EM20-25, Embelin and Wedelolactone, which resulted in 1.27-, 1.26-, and 1.46-fold increase in apoptosis of N2a cells. The existence of a one-to-one correspondence between cellular fates and attractor states shows that Boolean networks may be employed with confidence in qualitative analytical studies of biological networks.

  1. PTP4A3 Independently Predicts Metastasis and Survival in Upper Tract Urothelial Carcinoma Treated with Radical Nephroureterectomy.

    PubMed

    Yeh, Hsin-Chih; Li, Ching-Chia; Huang, Chun-Nung; Hour, Tzyh-Chyuan; Yeh, Bi-Wen; Li, Wei-Ming; Liang, Peir-In; Chang, Lin-Li; Li, Chien-Feng; Wu, Wen-Jeng

    2015-11-01

    Increasing evidence has shown that protein tyrosine phosphatases have dominant roles in setting the levels of tyrosine phosphorylation and promoting oncogenic processes. PTP4A3 has been implicated in cancer metastasis but to our knowledge the role of PTP4A3 in upper tract urothelial carcinoma is unknown. The aim of this study was to investigate the association of PTP4A3 with disease characteristics, distant metastasis and prognosis of upper tract urothelial carcinoma. The importance of PTP4A3 was initially examined in paired normal urothelium, noninvasive upper tract urothelial carcinoma, invasive upper tract urothelial carcinoma and nodal metastatic tissue. The PTP4A3 transcript level was assessed in another 20 upper tract urothelial carcinoma samples by real-time reverse transcriptase-polymerase chain reaction. PTP4A3 protein expression was determined by immunohistochemistry using the H-score in 340 upper tract urothelial carcinoma samples. It was further correlated with clinicopathological factors, and disease specific and metastasis-free survival. The expression of PTP4A3 significantly increased from normal urothelium, noninvasive upper tract urothelial carcinoma and invasive upper tract urothelial carcinoma to nodal metastatic tissue (p <0.001). The PTP4A3 transcript level was also markedly up-regulated in higher stage upper tract urothelial carcinoma (p = 0.002). Over expression of PTP4A3 protein was significantly associated with advanced pT status, nodal metastasis, lymphovascular invasion and perineural invasion (each p <0.001) as well as with inferior disease specific and metastasis-free survival on multivariate analysis (each p <0.0001). In addition, it predicted metastasis in patients with pTa, pT1 and pT2 upper tract urothelial carcinoma. Results imply that PTP4A3 has a role in the carcinogenesis of upper tract urothelial carcinoma. PTP4A3 over expression independently predicted the metastasis and outcome of upper tract urothelial carcinoma, which was

  2. Midregional pro-atrial natriuretic peptide and procalcitonin improve survival prediction in VAP.

    PubMed

    Boeck, L; Eggimann, P; Smyrnios, N; Pargger, H; Thakkar, N; Siegemund, M; Marsch, S; Rakic, J; Tamm, M; Stolz, D

    2011-03-01

    Ventilator-associated pneumonia (VAP) affects mortality, morbidity and cost of critical care. Reliable risk estimation might improve end-of-life decisions, resource allocation and outcome. Several scoring systems for survival prediction have been established and optimised over the last decades. Recently, new biomarkers have gained interest in the prognostic field. We assessed whether midregional pro-atrial natriuretic peptide (MR-proANP) and procalcitonin (PCT) improve the predictive value of the Simplified Acute Physiologic Score (SAPS) II and Sequential Related Organ Failure Assessment (SOFA) in VAP. Specified end-points of a prospective multinational trial including 101 patients with VAP were analysed. Death <28 days after VAP onset was the primary end-point. MR-proANP and PCT were elevated at the onset of VAP in nonsurvivors compared with survivors (p = 0.003 and p = 0.017, respectively) and their slope of decline differed significantly (p = 0.018 and p = 0.039, respectively). Patients with the highest MR-proANP quartile at VAP onset were at increased risk for death (log rank p = 0.013). In a logistic regression model, MR-proANP was identified as the best predictor of survival. Adding MR-proANP and PCT to SAPS II and SOFA improved their predictive properties (area under the curve 0.895 and 0.880). We conclude that the combination of two biomarkers, MR-proANP and PCT, improve survival prediction of clinical severity scores in VAP.

  3. Imbalanced learning for clinical survival group prediction of brain tumor patients

    NASA Astrophysics Data System (ADS)

    Zhou, Mu; Hall, Lawrence O.; Goldgof, Dmitry B.; Gillies, Robert J.; Gatenby, Robert A.

    2015-03-01

    Accurate computer-aided prediction of survival time for brain tumor patients requires a thorough understanding of clinical data, since it provides useful prior knowledge for learning models. However, to simplify the learning process, traditional settings often assume datasets with equally distributed classes, which clearly does not reflect a typical distribution. In this paper, we investigate the problem of mining knowledge from an imbalanced dataset (i.e., a skewed distribution) to predict survival time. In particular, we propose an algorithmic framework to predict survival groups of brain tumor patients using multi-modality MRI data. Both an imbalanced distribution and classifier design are jointly considered: 1) We used the Synthetic Minority Over-sampling Technique to compensate for the imbalanced distribution; 2) A predictive linear regression model was adopted to learn a pair of class-specific dictionaries, which were derived from reformulated balanced data. We tested the proposed framework using a dataset of 42 patients with Glioblastoma Multiforme (GBM) tumors whose scans were obtained from the cancer genome atlas (TCGA). Experimental results showed that the proposed method achieved 95.24% accuracy.

  4. Survival prediction of trauma patients: a study on US National Trauma Data Bank.

    PubMed

    Sefrioui, I; Amadini, R; Mauro, J; El Fallahi, A; Gabbrielli, M

    2017-02-22

    Exceptional circumstances like major incidents or natural disasters may cause a huge number of victims that might not be immediately and simultaneously saved. In these cases it is important to define priorities avoiding to waste time and resources for not savable victims. Trauma and Injury Severity Score (TRISS) methodology is the well-known and standard system usually used by practitioners to predict the survival probability of trauma patients. However, practitioners have noted that the accuracy of TRISS predictions is unacceptable especially for severely injured patients. Thus, alternative methods should be proposed. In this work we evaluate different approaches for predicting whether a patient will survive or not according to simple and easily measurable observations. We conducted a rigorous, comparative study based on the most important prediction techniques using real clinical data of the US National Trauma Data Bank. Empirical results show that well-known Machine Learning classifiers can outperform the TRISS methodology. Based on our findings, we can say that the best approach we evaluated is Random Forest: it has the best accuracy, the best area under the curve, and k-statistic, as well as the second-best sensitivity and specificity. It has also a good calibration curve. Furthermore, its performance monotonically increases as the dataset size grows, meaning that it can be very effective to exploit incoming knowledge. Considering the whole dataset, it is always better than TRISS. Finally, we implemented a new tool to compute the survival of victims. This will help medical practitioners to obtain a better accuracy than the TRISS tools. Random Forests may be a good candidate solution for improving the predictions on survival upon the standard TRISS methodology.

  5. Gene signatures of drug resistance predict patient survival in colorectal cancer

    PubMed Central

    Zheng, Y; Zhou, J; Tong, Y

    2015-01-01

    Different combinations of 5-fluorouracil (5-FU), oxaliplatin, irinotecan and other newly developed agents have been used to treat colorectal cancer. Despite the advent of new treatment regimens, the 5-year survival rate for metastatic colorectal cancer remains low (~10%). Knowing the drug sensitivity of a given tumor for a particular agent could significantly impact decision making and treatment planning. Biomarkers are proven to be successful in characterizing patients into different response groups. Using survival prediction analysis, we have identified three independent gene signatures, which are associated with sensitivity of colorectal cancer cells to 5-FU, oxaliplatin or irinotecan. On the basis of the three gene signatures, three score systems were developed to stratify patients from sensitive to resistance. These score systems exhibited robustness in stratify patients in two independent clinical studies. Patients with high scores in all three drugs exhibited the lowest survival. PMID:25179828

  6. Percentage of smudge cells on routine blood smear predicts survival in chronic lymphocytic leukemia.

    PubMed

    Nowakowski, Grzegorz S; Hoyer, James D; Shanafelt, Tait D; Zent, Clive S; Call, Timothy G; Bone, Nancy D; Laplant, Betsy; Dewald, Gordon W; Tschumper, Renee C; Jelinek, Diane F; Witzig, Thomas E; Kay, Neil E

    2009-04-10

    Smudge cells are ruptured chronic lymphocytic leukemia (CLL) cells appearing on the blood smears of CLL patients. Our recent findings suggest that the number of smudge cells may have important biologic correlations rather than being only an artifact of slide preparation. In this study, we evaluated whether the smudge cell percentage on a blood smear predicted survival of CLL patients. We calculated smudge cell percentages (ratio of smudged to intact cells plus smudged lymphocytes) on archived blood smears from a cohort of previously untreated patients with predominantly early-stage CLL enrolled onto a prospective observational study. The relationship between percentage of smudge cells, patient survival, and other prognostic factors was explored. Between 1994 and 2002, 108 patients were enrolled onto the study and had archived blood smears available for review; 80% of patients had Rai stage 0 or I disease. The median smudge cell percentage was 28% (range, 1% to 75%). The percentage of smudge cells was lower in CD38(+) versus CD38(-) patients (P = .019) and in Zap70-positive versus Zap70-negative patients (P = .028). Smudge cell percentage as a continuous variable was associated with prolonged survival (P = .042). The 10-year survival rate was 50% for patients with 30% or less smudge cells compared with 80% for patients with more than 30% of smudge cells (P = .015). In multivariate analysis, the percentage of smudge cells was an independent predictor of overall survival. Percentage of smudge cells on blood smear is readily available and an independent factor predicting overall survival in CLL.

  7. Percentage of Smudge Cells on Routine Blood Smear Predicts Survival in Chronic Lymphocytic Leukemia

    PubMed Central

    Nowakowski, Grzegorz S.; Hoyer, James D.; Shanafelt, Tait D.; Zent, Clive S.; Call, Timothy G.; Bone, Nancy D.; LaPlant, Betsy; Dewald, Gordon W.; Tschumper, Renee C.; Jelinek, Diane F.; Witzig, Thomas E.; Kay, Neil E.

    2009-01-01

    Purpose Smudge cells are ruptured chronic lymphocytic leukemia (CLL) cells appearing on the blood smears of CLL patients. Our recent findings suggest that the number of smudge cells may have important biologic correlations rather than being only an artifact of slide preparation. In this study, we evaluated whether the smudge cell percentage on a blood smear predicted survival of CLL patients. Patients and Methods We calculated smudge cell percentages (ratio of smudged to intact cells plus smudged lymphocytes) on archived blood smears from a cohort of previously untreated patients with predominantly early-stage CLL enrolled onto a prospective observational study. The relationship between percentage of smudge cells, patient survival, and other prognostic factors was explored. Results Between 1994 and 2002, 108 patients were enrolled onto the study and had archived blood smears available for review; 80% of patients had Rai stage 0 or I disease. The median smudge cell percentage was 28% (range, 1% to 75%). The percentage of smudge cells was lower in CD38+ versus CD38– patients (P = .019) and in Zap70-positive versus Zap70-negative patients (P = .028). Smudge cell percentage as a continuous variable was associated with prolonged survival (P = .042). The 10-year survival rate was 50% for patients with 30% or less smudge cells compared with 80% for patients with more than 30% of smudge cells (P = .015). In multivariate analysis, the percentage of smudge cells was an independent predictor of overall survival. Conclusion Percentage of smudge cells on blood smear is readily available and an independent factor predicting overall survival in CLL. PMID:19255329

  8. Expression of Tiam1 predicts lymph node metastasis and poor survival of lung adenocarcinoma patients

    PubMed Central

    2014-01-01

    Background To assess the value of Tiam1 in predicting lymph node metastasis and survival after curative resection in patients with lung adenocarcinoma. Methods Immunohistochemical staining for Tiam1 was performed on 98 adenocarcinoma and 30 normal lung tissues. The association of Tiam1 protein expression with the clinicopathological characteristics and the prognosis of lung adenocarcinoma were subsequently assessed. Results Immunohistochemical analysis showed that 60 of 98 (61.22%) adenocarcinoma tissues showed high expression of Tiam1, and high Tiam1 expression was significantly associated with advanced TNM stage (P < 0.0005) and lymph node status (P < 0.0005) of lung adenocarcinoma. Moreover, the lung adenocarcinoma patients with low Tiam1 expression had higher overall survival than patients with high Tiam1 expression (log rank value = 10.805, P = 0.001). High expression of Tiam1 predicted poor overall survival of patients in stages I + II (P = 0.006). Furthermore, multivariate analysis indicated that high expression of Tiam1 protein was an independent prognostic factor for overall survival (P = 0.011) in patients with lung adenocarcinoma. Conclusion These findings suggest for the first time that Tiam1 expression may be beneficial in predicting lymph node metastasis and survival of patients with lung adenocarcinoma. A future study will investigate whether Tiam1 can serve as a novel therapeutic target in lung adenocarcinoma. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1377798917111123. PMID:24661909

  9. Expression of Tiam1 predicts lymph node metastasis and poor survival of lung adenocarcinoma patients.

    PubMed

    Liu, Shuguang; Li, Yumei; Qi, Wenjuan; Zhao, Yunfei; Huang, Aili; Sheng, Wenjie; Lei, Bin; Lin, Peixin; Zhu, Haili; Li, Wenxia; Shen, Hong

    2014-03-24

    To assess the value of Tiam1 in predicting lymph node metastasis and survival after curative resection in patients with lung adenocarcinoma. Immunohistochemical staining for Tiam1 was performed on 98 adenocarcinoma and 30 normal lung tissues. The association of Tiam1 protein expression with the clinicopathological characteristics and the prognosis of lung adenocarcinoma were subsequently assessed. Immunohistochemical analysis showed that 60 of 98 (61.22%) adenocarcinoma tissues showed high expression of Tiam1, and high Tiam1 expression was significantly associated with advanced TNM stage (P < 0.0005) and lymph node status (P < 0.0005) of lung adenocarcinoma. Moreover, the lung adenocarcinoma patients with low Tiam1 expression had higher overall survival than patients with high Tiam1 expression (log rank value = 10.805, P = 0.001). High expression of Tiam1 predicted poor overall survival of patients in stages I + II (P = 0.006). Furthermore, multivariate analysis indicated that high expression of Tiam1 protein was an independent prognostic factor for overall survival (P = 0.011) in patients with lung adenocarcinoma. These findings suggest for the first time that Tiam1 expression may be beneficial in predicting lymph node metastasis and survival of patients with lung adenocarcinoma. A future study will investigate whether Tiam1 can serve as a novel therapeutic target in lung adenocarcinoma. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1377798917111123.

  10. Classification of TP53 mutations and HPV predict survival in advanced larynx cancer.

    PubMed

    Scheel, Adam; Bellile, Emily; McHugh, Jonathan B; Walline, Heather M; Prince, Mark E; Urba, Susan; Wolf, Gregory T; Eisbruch, Avraham; Worden, Francis; Carey, Thomas E; Bradford, Carol

    2016-09-01

    Assess tumor suppressor p53 (TP53) functional mutations in the context of other biomarkers in advanced larynx cancer. Prospective analysis of pretreatment tumor TP53, human papillomavirus (HPV), Bcl-xL, and cyclin D1 status in stage III and IV larynx cancer patients in a clinical trial. TP53 exons 4 through 9 from 58 tumors were sequenced. Mutations were grouped using three classifications based on their expected function. Each functional group was analyzed for response to induction chemotherapy, time to surgery, survival, HPV status, p16INK4a, Bcl-xl, and cyclin D1 expression. TP53 mutations were found in 22 of 58 (37.9%) patients with advanced larynx cancer, including missense mutations in 13 of 58 (22.4%) patients, nonsense mutations in four of 58 (6.9%), and deletions in five of 58 (8.6%). High-risk HPV was found in 20 of 52 (38.5%) tumors. A classification based on Evolutionary Action score of p53 (EAp53) distinguished missense mutations with high risk for decreased survival from low-risk mutations (P = 0.0315). A model including this TP53 classification, HPV status, cyclin D1, and Bcl-xL staining significantly predicts survival (P = 0.0017). EAp53 functional classification of TP53 mutants and biomarkers predict survival in advanced larynx cancer. NA. Laryngoscope, 126:E292-E299, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

  11. Longitudinal Temporal and Probabilistic Prediction of Survival in a Cohort of Patients With Advanced Cancer

    PubMed Central

    Perez-Cruz, Pedro E.; dos Santos, Renata; Silva, Thiago Buosi; Crovador, Camila Souza; Nascimento, Maria Salete de Angelis; Hall, Stacy; Fajardo, Julieta; Bruera, Eduardo; Hui, David

    2014-01-01

    Context Survival prognostication is important during end-of-life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized. Objectives To examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches. Methods Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at day −14 (baseline) with accuracy at each time point using a test of proportions. Results 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 (4, 20) days. Temporal CPS had low accuracy (10–40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (p<.05 at each time point) but decreased close to death. Conclusion Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary. PMID:24746583

  12. Longitudinal temporal and probabilistic prediction of survival in a cohort of patients with advanced cancer.

    PubMed

    Perez-Cruz, Pedro E; Dos Santos, Renata; Silva, Thiago Buosi; Crovador, Camila Souza; Nascimento, Maria Salete de Angelis; Hall, Stacy; Fajardo, Julieta; Bruera, Eduardo; Hui, David

    2014-11-01

    Survival prognostication is important during the end of life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized. The aims of the study were to examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches. Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at Day -14 (baseline) with accuracy at each time point using a test of proportions. A total of 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 days (4-20 days). Temporal CPS had low accuracy (10%-40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (P < .05 at each time point) but decreased close to death. Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary. Copyright © 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  13. Corticosterone levels predict survival probabilities of Galapagos marine iguanas during El Nino events.

    PubMed

    Romero, L M; Wikelski, M

    2001-06-19

    Plasma levels of corticosterone are often used as a measure of "stress" in wild animal populations. However, we lack conclusive evidence that different stress levels reflect different survival probabilities between populations. Galápagos marine iguanas offer an ideal test case because island populations are affected differently by recurring El Niño famine events, and population-level survival can be quantified by counting iguanas locally. We surveyed corticosterone levels in six populations during the 1998 El Niño famine and the 1999 La Niña feast period. Iguanas had higher baseline and handling stress-induced corticosterone concentrations during famine than feast conditions. Corticosterone levels differed between islands and predicted survival through an El Niño period. However, among individuals, baseline corticosterone was only elevated when body condition dropped below a critical threshold. Thus, the population-level corticosterone response was variable but nevertheless predicted overall population health. Our results lend support to the use of corticosterone as a rapid quantitative predictor of survival in wild animal populations.

  14. Nestling telomere shortening, but not telomere length, reflects developmental stress and predicts survival in wild birds

    PubMed Central

    Boonekamp, Jelle J.; Mulder, G. A.; Salomons, H. Martijn; Dijkstra, Cor; Verhulst, Simon

    2014-01-01

    Developmental stressors often have long-term fitness consequences, but linking offspring traits to fitness prospects has remained a challenge. Telomere length predicts mortality in adult birds, and may provide a link between developmental conditions and fitness prospects. Here, we examine the effects of manipulated brood size on growth, telomere dynamics and post-fledging survival in free-living jackdaws. Nestlings in enlarged broods achieved lower mass and lost 21% more telomere repeats relative to nestlings in reduced broods, showing that developmental stress accelerates telomere shortening. Adult telomere length was positively correlated with their telomere length as nestling (r = 0.83). Thus, an advantage of long telomeres in nestlings is carried through to adulthood. Nestling telomere shortening predicted post-fledging survival and recruitment independent of manipulation and fledgling mass. This effect was strong, with a threefold difference in recruitment probability over the telomere shortening range. By contrast, absolute telomere length was neither affected by brood size manipulation nor related to survival. We conclude that telomere loss, but not absolute telomere length, links developmental conditions to subsequent survival and suggest that telomere shortening may provide a key to unravelling the physiological causes of developmental effects on fitness. PMID:24789893

  15. Reduction in predicted survival times in cold water due to wind and waves.

    PubMed

    Power, Jonathan; Simões Ré, António; Barwood, Martin; Tikuisis, Peter; Tipton, Michael

    2015-07-01

    Recent marine accidents have called into question the level of protection provided by immersion suits in real (harsh) life situations. Two immersion suit studies, one dry and the other with 500 mL of water underneath the suit, were conducted in cold water with 10-12 males in each to test body heat loss under three environmental conditions: calm, as mandated for immersion suit certification, and two combinations of wind plus waves to simulate conditions typically found offshore. In both studies mean skin heat loss was higher in wind and waves vs. calm; deep body temperature and oxygen consumption were not different. Mean survival time predictions exceeded 36 h for all conditions in the first study but were markedly less in the second in both calm and wind and waves. Immersion suit protection and consequential predicted survival times under realistic environmental conditions and with leakage are reduced relative to calm conditions. Copyright © 2015. Published by Elsevier Ltd.

  16. Dynamic predictions with time-dependent covariates in survival analysis using joint modeling and landmarking.

    PubMed

    Rizopoulos, Dimitris; Molenberghs, Geert; Lesaffre, Emmanuel M E H

    2017-08-09

    A key question in clinical practice is accurate prediction of patient prognosis. To this end, nowadays, physicians have at their disposal a variety of tests and biomarkers to aid them in optimizing medical care. These tests are often performed on a regular basis in order to closely follow the progression of the disease. In this setting, it is of interest to optimally utilize the recorded information and provide medically relevant summary measures, such as survival probabilities, which will aid in decision making. In this work, we present and compare two statistical techniques that provide dynamically updated estimates of survival probabilities, namely landmark analysis and joint models for longitudinal and time-to-event data. Special attention is given to the functional form linking the longitudinal and event time processes, and to measures of discrimination and calibration in the context of dynamic prediction. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. The Geriatric Nutritional Risk Index Predicts Survival in Elderly Esophageal Squamous Cell Carcinoma Patients with Radiotherapy

    PubMed Central

    Wang, Kunlun; Liu, Yang; You, Jie; Cui, Han; Zhu, Yiwei; Yuan, Ling

    2016-01-01

    The impact of nutritional status on survival among elderly esophageal squamous cell carcinoma (ESCC) patients undergoing radiotherapy is unclear. In this study, we aimed at validating the performance of the geriatric nutritional risk index (GNRI) in predicting overall survival time in elderly ESCC patients with radiotherapy. A retrospective cohort study was conducted on 239 ESCC patients aged 60 and over admitted consecutively from January 2008 to November 2014 in the Department of Radiotherapy, Henan Tumor Hospital (Affiliated Tumor Hospital of Zhengzhou University), Zhengzhou, Henan, China. All patients were subjected to nutritional screening using GNRI, and were followed for the occurrence of lymphatic node metastasis, radiation complication and mortality. The Kaplan–Meier method with Log-rank test was used to estimate survival curves. Univariable Cox regression analysis was used to identify variables associated with overall survival time. Among the 239 patients, 184 patients (76.9%) took no nutritional risk, 32 patients (13.4%) took moderate risk of malnutrition, and 23 patients (9.7%) took a high risk of malnutrition. Univariable Cox regression showed that both high nutritional risk group and moderate nutritional risk group were significantly less likely to survive than no nutritional risk patients (hazard ratio (HR) = 1.688, 95% confidence interval (CI) = 1.019–2.798 for moderate risk group, and HR = 2.699, 95% CI = 1.512–4.819 for high risk group, respectively). The GNRI is an independent prognostic factor for overall survival time in elderly ESCC patients with radiotherapy. A GNRI ≤98 can be suggested as an indicator of surviving less. PMID:27196126

  18. Cognitive performance and functional status are the major factors predicting survival of centenarians in Poland.

    PubMed

    Mossakowska, Malgorzata; Broczek, Katarzyna; Wieczorowska-Tobis, Katarzyna; Klich-Rączka, Alicja; Jonas, Marta; Pawlik-Pachucka, Eliza; Safranow, Krzysztof; Kuznicki, Jacek; Puzianowska-Kuznicka, Monika

    2014-10-01

    Clinical and biochemical predictors of extreme longevity would be useful in geriatric practice but have still not been clearly defined. To identify the best nongenetic predictors of survival in centenarians, we examined 340 individuals aged 100+ years. A detailed questionnaire was completed, and comprehensive geriatric assessment and blood analyses were performed. Survival of study participants was checked annually over the period of 10 years. In the univariate Cox proportional hazards model, a longer survival of centenarians was correlated with a higher adjusted Mini-Mental State Examination (MMSE(adj)) score (p < .000001), higher Activities of Daily Living (ADL) and adjusted Instrumental Activities of Daily Living (IADL(adj)) scores (p < .000001 and p = .00008, respectively), and younger age at the time of testing (p = .005). Blood pressure, lipid profile, and C-reactive protein and hemoglobin concentrations were not associated with survival. Multivariate analysis including age, sex, and the MMSE(adj) and ADL scores showed that both MMSE(adj) and ADL predicted survival (HR = 0.978 per each MMSE(adj) point, 95% CI: 0.964-0.993, p = .004; HR = 0.900 per each ADL point, 95% CI: 0.842-0.962, p = .002, respectively). In multivariate analysis with the ADL score substituted by the IADL(adj) score, the only predictor of survival was MMSE(adj) (HR = 0.973 per each MMSE(adj) point, 95% CI: 0.958-0.988, p = .0006). Cognitive and functional performances are predictors of survival in centenarians. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. A hemocyte gene expression signature correlated with predictive capacity of oysters to survive Vibrio infections

    PubMed Central

    2012-01-01

    Background The complex balance between environmental and host factors is an important determinant of susceptibility to infection. Disturbances of this equilibrium may result in multifactorial diseases as illustrated by the summer mortality syndrome, a worldwide and complex phenomenon that affects the oysters, Crassostrea gigas. The summer mortality syndrome reveals a physiological intolerance making this oyster species susceptible to diseases. Exploration of genetic basis governing the oyster resistance or susceptibility to infections is thus a major goal for understanding field mortality events. In this context, we used high-throughput genomic approaches to identify genetic traits that may characterize inherent survival capacities in C. gigas. Results Using digital gene expression (DGE), we analyzed the transcriptomes of hemocytes (immunocompetent cells) of oysters able or not able to survive infections by Vibrio species shown to be involved in summer mortalities. Hemocytes were nonlethally collected from oysters before Vibrio experimental infection, and two DGE libraries were generated from individuals that survived or did not survive. Exploration of DGE data and microfluidic qPCR analyses at individual level showed an extraordinary polymorphism in gene expressions, but also a set of hemocyte-expressed genes whose basal mRNA levels discriminate oyster capacity to survive infections by the pathogenic V. splendidus LGP32. Finally, we identified a signature of 14 genes that predicted oyster survival capacity. Their expressions are likely driven by distinct transcriptional regulation processes associated or not associated to gene copy number variation (CNV). Conclusions We provide here for the first time in oyster a gene expression survival signature that represents a useful tool for understanding mortality events and for assessing genetic traits of interest for disease resistance selection programs. PMID:22708697

  20. A prediction model of survival for patients with bone metastasis from uterine cervical cancer

    PubMed Central

    2016-01-01

    Objective The aim of the study was to establish a predictive model of survival period after bone metastasis from cervical cancer. Methods A total of 54 patients with bone metastasis from cervical cancer were included in the study. Data at the time of bone metastasis diagnosis, which included presence of extraskeletal metastasis, performance status, history of any previous radiation or chemotherapy, the number of bone metastases, onset period, and treatment were collected. Survival data were analyzed using Kaplan-Meier method and Cox proportional hazards model. Results The median survival period after diagnosis of bone metastasis was 22 weeks (5 months). The 26- and 52-week survival rates after bone metastasis were 36.5% and 15.4%, respectively. Cox regression analysis showed that extraskeletal metastasis (hazard ratio [HR], 6.1; 95% CI, 2.2 to 16.6), performance status of 3 to 4 (HR, 7.8; 95% CI, 3.3 to 18.2), previous radiation or chemotherapy (HR, 3.3; 95% CI, 1.4 to 7.8), multiple bone metastases (HR, 1.9; 95% CI, 1.0 to 3.5), and a bone metastasis-free interval of <12 months (HR, 2.5; 95% CI, 1.2 to 5.3) were significantly and independently related to poor survival. A prognostic score was calculated by adding the number of each significant factor. The 26-week survival rates after diagnosis of bone metastasis were 70.1% in the group with a score ≤2, 46.7% in the group with a score of 3, and 12.5% in the group with a score ≥4 (p<0.001). Conclusion This scoring system provided useful prognostic information on survival of patients with bone metastasis of cervical cancer. PMID:27550401

  1. Glycated Albumin Predicts Long-term Survival in Patients Undergoing Hemodialysis

    PubMed Central

    Lu, Chien-Lin; Ma, Wen-Ya; Lin, Yuh-Feng; Shyu, Jia-Fwu; Wang, Yuan-Hung; Liu, Yueh-Min; Wu, Chia-Chao; Lu, Kuo-Cheng

    2016-01-01

    Background: In patients with advanced renal dysfunction undergoing maintenance hemodialysis, glycated albumin (GA) levels may be more representative of blood glucose levels than hemoglobin A1C levels. The aim of this study was to determine the predictive power of GA levels on long-term survival in hemodialysis patients. Methods: A total of 176 patients with a mean age of 68.2 years were enrolled. The median duration of follow-up was 51.0 months. Receiver-operating characteristic curve analysis was utilized to determine the optimal cutoff value. We examined the cumulative survival rate by Kaplan-Meier estimates and the influence of known survival factors with the multivariate Cox proportional-hazard regression model. Results: In the whole patient group, cumulative survival in the low GA group was better than in the high GA group (p=0.030), with more prominence in those aged <70 years (p=0.029). In subgroup analysis, both diabetic (DM) and non-DM patients with low GA had a better cumulative survival compared with those with high GA. The risk of mortality increased by 3.0% for each 1% increase in serum GA level in all patients undergoing hemodialysis. Conclusions: In addition to serving as a glycemic control marker, GA levels may be useful for evaluating the risk of death in both DM and non-DM patients on hemodialysis. PMID:27226780

  2. Identifying endpoints to predict the influence of immunosuppression on long-term kidney graft survival.

    PubMed

    Srinivas, Titte R; Oppenheimer, Federico

    2015-07-01

    Identifying a short-term endpoint for use in clinical trials that accurately reflects the influence of specific immunosuppressive regimens on long-term kidney graft survival is challenging. The number, timing, type (T-cell-mediated or antibody mediated), and severity of biopsy-proven acute rejection (BPAR) episodes in terms of histological changes and functional impact are highly influential for graft prognosis, and a crude measure of overall acute rejection incidence alone is unlikely to be a robust predictor of graft outcome. A series of studies has shown remarkably consistent results in terms of the cutoff point for one-yr renal function which predicts poor long-term graft survival, indicating that a threshold of 50 mL/min/1.73 m(2) is likely to be appropriate. Estimated glomerular filtration rate at one yr post-transplant discriminates effectively among immunosuppressive regimens with regard to graft survival, primarily calcineurin inhibitor reduction strategies. Several other factors that can affect graft survival, such as pathological changes in the graft, may be partly influenced by the immunosuppressive regimen, but the contribution of drug therapy is difficult to define. A combined approach in which both treated BPAR and renal function at one yr are used to assess novel immunosuppressive regimens appears to be promising as the emphasis shifts toward sustaining kidney allograft survival over the long term. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  3. MRI and thallium-201 SPECT in the prediction of survival in glioma.

    PubMed

    Vos, Maaike J; Berkhof, Johannes; Hoekstra, Otto S; Bosma, Ingeborg; Sizoo, Eefje M; Heimans, Jan J; Reijneveld, Jaap C; Sanchez, Esther; Lagerwaard, Frank J; Buter, Jan; Noske, David P; Postma, Tjeerd J

    2012-06-01

    This paper aims to study the value of MRI and Thallium 201 ((201)Tl) single-photon emission computed tomography (SPECT) in the prediction of overall survival (OS) in glioma patients treated with temozolomide (TMZ) and to evaluate timing of radiological follow-up. We included patients treated with TMZ chemoradiotherapy for newly diagnosed glioblastoma multiforme (GBM) and with TMZ for recurrent glioma. MRIs and (201)Tl SPECTs were obtained at regular intervals. The value of both imaging modalities in predicting OS was examined using Cox regression analyses. Altogether, 138 MRIs and 113 (201)Tl SPECTs in 46 patients were performed. Both imaging modalities were strongly related to OS (P ≤ 0.02). In newly diagnosed GBM patients, the last follow-up MRI (i.e., after six adjuvant TMZ courses) and SPECT (i.e., after three adjuvant TMZ courses) were the strongest predictors of OS (P = 0.01). In recurrent glioma patients, baseline measurements appeared to be the most predictive of OS (P < 0.01). The addition of one imaging modality to the other did not contribute to the prediction of OS. Both MRI and (201)Tl SPECT are valuable in the prediction of OS. It is adequate to restrict to one of both modalities in the radiological follow-up during treatment. In the primary GBM setting, MRI after six adjuvant TMZ courses contributes significantly to the prediction of survival. In the recurrent glioma setting, baseline MRI appears to be a powerful predictor of survival, whereas follow-up MRIs during TMZ seem to be of little additional value.

  4. Validation of a Predictive Model for Survival in Metastatic Cancer Patients Attending an Outpatient Palliative Radiotherapy Clinic

    SciTech Connect

    Chow, Edward Abdolell, Mohamed; Panzarella, Tony; Harris, Kristin; Bezjak, Andrea; Warde, Padraig; Tannock, Ian

    2009-01-01

    Purpose: To validate a predictive model for survival of patients attending a palliative radiotherapy clinic. Methods and Materials: We described previously a model that had good predictive value for survival of patients referred during 1999 (1). The six prognostic factors (primary cancer site, site of metastases, Karnofsky performance score, and the fatigue, appetite and shortness-of-breath items from the Edmonton Symptom Assessment Scale) identified in this training set were extracted from the prospective database for the year 2000. We generated a partial score whereby each prognostic factor was assigned a value proportional to its prognostic weight. The sum of the partial scores for each patient was used to construct a survival prediction score (SPS). Patients were also grouped according to the number of these risk factors (NRF) that they possessed. The probability of survival at 3, 6, and 12 months was generated. The models were evaluated for their ability to predict survival in this validation set with appropriate statistical tests. Results: The median survival and survival probabilities of the training and validation sets were similar when separated into three groups using both SPS and NRF methods. There was no statistical difference in the performance of the SPS and NRF methods in survival prediction. Conclusion: Both the SPS and NRF models for predicting survival in patients referred for palliative radiotherapy have been validated. The NRF model is preferred because it is simpler and avoids the need to remember the weightings among the prognostic factors.

  5. Management of hepatocellular carcinoma: Predictive value of immunohistochemical markers for postoperative survival

    PubMed Central

    Niu, Zhao-Shan; Niu, Xiao-Jun; Wang, Mei

    2015-01-01

    Hepatocellular carcinoma (HCC) accounts for over 90% of all primary liver cancers. With an ever increasing incidence trend year by year, it has become the third most common cause of death from cancer worldwide. Hepatic resection is generally considered to be one of the most effective therapies for HCC patients, however, there is a high risk of recurrence in postoperative HCC. In clinical practice, there exists an urgent need for valid prognostic markers to identify patients with prognosis, hence the importance of studies on prognostic markers in improving the prediction of HCC prognosis. This review focuses on the most promising immunohistochemical prognostic markers in predicting the postoperative survival of HCC patients. PMID:25624992

  6. Supervised Wavelet Method to Predict Patient Survival from Gene Expression Data

    PubMed Central

    Farhadian, Maryam; Lisboa, Paulo J. G.; Moghimbeigi, Abbas; Mahjub, Hossein

    2014-01-01

    In microarray studies, the number of samples is relatively small compared to the number of genes per sample. An important aspect of microarray studies is the prediction of patient survival based on their gene expression profile. This naturally calls for the use of a dimension reduction procedure together with the survival prediction model. In this study, a new method based on combining wavelet approximation coefficients and Cox regression was presented. The proposed method was compared with supervised principal component and supervised partial least squares methods. The different fitted Cox models based on supervised wavelet approximation coefficients, the top number of supervised principal components, and partial least squares components were applied to the data. The results showed that the prediction performance of the Cox model based on supervised wavelet feature extraction was superior to the supervised principal components and partial least squares components. The results suggested the possibility of developing new tools based on wavelets for the dimensionally reduction of microarray data sets in the context of survival analysis. PMID:25538955

  7. Sample size considerations of prediction-validation methods in high-dimensional data for survival outcomes.

    PubMed

    Pang, Herbert; Jung, Sin-Ho

    2013-04-01

    A variety of prediction methods are used to relate high-dimensional genome data with a clinical outcome using a prediction model. Once a prediction model is developed from a data set, it should be validated using a resampling method or an independent data set. Although the existing prediction methods have been intensively evaluated by many investigators, there has not been a comprehensive study investigating the performance of the validation methods, especially with a survival clinical outcome. Understanding the properties of the various validation methods can allow researchers to perform more powerful validations while controlling for type I error. In addition, sample size calculation strategy based on these validation methods is lacking. We conduct extensive simulations to examine the statistical properties of these validation strategies. In both simulations and a real data example, we have found that 10-fold cross-validation with permutation gave the best power while controlling type I error close to the nominal level. Based on this, we have also developed a sample size calculation method that will be used to design a validation study with a user-chosen combination of prediction. Microarray and genome-wide association studies data are used as illustrations. The power calculation method in this presentation can be used for the design of any biomedical studies involving high-dimensional data and survival outcomes.

  8. Sample Size Considerations of Prediction-Validation Methods in High-Dimensional Data for Survival Outcomes

    PubMed Central

    Pang, Herbert; Jung, Sin-Ho

    2013-01-01

    A variety of prediction methods are used to relate high-dimensional genome data with a clinical outcome using a prediction model. Once a prediction model is developed from a data set, it should be validated using a resampling method or an independent data set. Although the existing prediction methods have been intensively evaluated by many investigators, there has not been a comprehensive study investigating the performance of the validation methods, especially with a survival clinical outcome. Understanding the properties of the various validation methods can allow researchers to perform more powerful validations while controlling for type I error. In addition, sample size calculation strategy based on these validation methods is lacking. We conduct extensive simulations to examine the statistical properties of these validation strategies. In both simulations and a real data example, we have found that 10-fold cross-validation with permutation gave the best power while controlling type I error close to the nominal level. Based on this, we have also developed a sample size calculation method that will be used to design a validation study with a user-chosen combination of prediction. Microarray and genome-wide association studies data are used as illustrations. The power calculation method in this presentation can be used for the design of any biomedical studies involving high-dimensional data and survival outcomes. PMID:23471879

  9. A new approach: role of data mining in prediction of survival of burn patients.

    PubMed

    Patil, Bankat Madhavrao; Joshi, Ramesh C; Toshniwal, Durga; Biradar, Siddeshwar

    2011-12-01

    The prediction of burn patient survivability is a difficult problem to investigate till present times. In present study a prediction Model for patients with burns was built, and its capability to accurately predict the survivability was assessed. We have compared different data mining techniques to asses the performance of various algorithms based on the different measures used in the analysis of information pertaining to medical domain. Obtained results were evaluated for correctness with the help of registered medical practitioners. The dataset was collected from SRT (Swami Ramanand Tirth) Hospital in India, which is one of the Asia's largest rural hospitals. Dataset contains records of 180 patients mainly suffering from burn injuries collected during period from the year 2002 to 2006. Features contain patients' age, sex and percentage of burn received for eight different parts of the body. Prediction models have been developed through rigorous comparative study of important and relevant data mining classification techniques namely, navie bayes, decision tree, support vector machine and back propagation. Performance comparison was also carried out for measuring unbiased estimate of the prediction models using 10-fold cross-validation method. Using the analysis of obtained results, we show that Navie bayes is the best predictor with an accuracy of 97.78% on the holdout samples, further, both the decision tree and support vector machine (SVM) techniques demonstrated an accuracy of 96.12%, and back propagation technique resulted in achieving accuracy of 95%.

  10. An Easy Tool to Predict Survival in Patients Receiving Radiation Therapy for Painful Bone Metastases

    SciTech Connect

    Westhoff, Paulien G.; Graeff, Alexander de; Monninkhof, Evelyn M.; Bollen, Laurens; Dijkstra, Sander P.; Steen-Banasik, Elzbieta M. van der; Vulpen, Marco van; Leer, Jan Willem H.; Marijnen, Corrie A.; Linden, Yvette M. van der

    2014-11-15

    Purpose: Patients with bone metastases have a widely varying survival. A reliable estimation of survival is needed for appropriate treatment strategies. Our goal was to assess the value of simple prognostic factors, namely, patient and tumor characteristics, Karnofsky performance status (KPS), and patient-reported scores of pain and quality of life, to predict survival in patients with painful bone metastases. Methods and Materials: In the Dutch Bone Metastasis Study, 1157 patients were treated with radiation therapy for painful bone metastases. At randomization, physicians determined the KPS; patients rated general health on a visual analogue scale (VAS-gh), valuation of life on a verbal rating scale (VRS-vl) and pain intensity. To assess the predictive value of the variables, we used multivariate Cox proportional hazard analyses and C-statistics for discriminative value. Of the final model, calibration was assessed. External validation was performed on a dataset of 934 patients who were treated with radiation therapy for vertebral metastases. Results: Patients had mainly breast (39%), prostate (23%), or lung cancer (25%). After a maximum of 142 weeks' follow-up, 74% of patients had died. The best predictive model included sex, primary tumor, visceral metastases, KPS, VAS-gh, and VRS-vl (C-statistic = 0.72, 95% CI = 0.70-0.74). A reduced model, with only KPS and primary tumor, showed comparable discriminative capacity (C-statistic = 0.71, 95% CI = 0.69-0.72). External validation showed a C-statistic of 0.72 (95% CI = 0.70-0.73). Calibration of the derivation and the validation dataset showed underestimation of survival. Conclusion: In predicting survival in patients with painful bone metastases, KPS combined with primary tumor was comparable to a more complex model. Considering the amount of variables in complex models and the additional burden on patients, the simple model is preferred for daily use. In addition, a risk table for survival is provided.

  11. External validation of a 5-year survival prediction model after elective abdominal aortic aneurysm repair.

    PubMed

    DeMartino, Randall R; Huang, Ying; Mandrekar, Jay; Goodney, Philip P; Oderich, Gustavo S; Kalra, Manju; Bower, Thomas C; Cronenwett, Jack L; Gloviczki, Peter

    2017-08-11

    The benefit of prophylactic repair of abdominal aortic aneurysms (AAAs) is based on the risk of rupture exceeding the risk of death from other comorbidities. The purpose of this study was to validate a 5-year survival prediction model for patients undergoing elective repair of asymptomatic AAA <6.5 cm to assist in optimal selection of patients. All patients undergoing elective repair for asymptomatic AAA <6.5 cm (open or endovascular) from 2002 to 2011 were identified from a single institutional database (validation group). We assessed the ability of a prior published Vascular Study Group of New England (VSGNE) model (derivation group) to predict survival in our cohort. The model was assessed for discrimination (concordance index), calibration (calibration slope and calibration in the large), and goodness of fit (score test). The VSGNE derivation group consisted of 2367 patients (70% endovascular). Major factors associated with survival in the derivation group were age, coronary disease, chronic obstructive pulmonary disease, renal function, and antiplatelet and statin medication use. Our validation group consisted of 1038 patients (59% endovascular). The validation group was slightly older (74 vs 72 years; P < .01) and had a higher proportion of men (76% vs 68%; P < .01). In addition, the derivation group had higher rates of advanced cardiac disease, chronic obstructive pulmonary disease, and baseline creatinine concentration (1.2 vs 1.1 mg/dL; P < .01). Despite slight differences in preoperative patient factors, 5-year survival was similar between validation and derivation groups (75% vs 77%; P = .33). The concordance index of the validation group was identical between derivation and validation groups at 0.659 (95% confidence interval, 0.63-0.69). Our validation calibration in the large value was 1.02 (P = .62, closer to 1 indicating better calibration), calibration slope of 0.84 (95% confidence interval, 0.71-0.97), and score test of P = .57 (>.05

  12. Massive blood transfusion after the first cut in liver transplantation predicts renal outcome and survival.

    PubMed

    Reichert, Benedikt; Kaltenborn, Alexander; Becker, Thomas; Schiffer, Mario; Klempnauer, Jürgen; Schrem, Harald

    2014-04-01

    Transfusion requirements of blood products may provide useful prognostic factors for the prediction of short-term patient mortality and renal outcome after liver transplantation. Two hundred ninety-one consecutive liver transplants in adults were analysed retrospectively. Combined and living-related liver transplants were excluded. The amount of transfused packed red blood cells (PRBC) and units of platelets (UP) within the first 48 h were investigated as prognostic factors to predict short-term patient mortality and renal outcome. Receiver operating characteristic (ROC) curve analysis with area under the curve (AUC), Hosmer-Lemeshow tests and Brier scores were used to calculate overall model correctness, model calibration and accuracy of prognostic factors. Cut-off values were determined with the best Youden index. The potential clinical usefulness of PRBC as a prognostic factor to predict 30-day mortality (cut-off 17.5 units) and post-transplant haemodialysis (cut-off 12.5 units) could be demonstrated with AUCs >0.7 (0.712 and 0.794, respectively). Hosmer-Lemeshow test results and Brier scores indicated good overall model correctness, model calibration and accuracy. The UP proved as an equally clinically useful prognostic factor to predict end-stage renal disease (cut-off 3.5 units; AUC = 0.763). The association of cut-off levels of PRBC with patient survival (p < 0.001, log-rank test) and dialysis-free survival (p < 0.001, log-rank test) was significant (cut-off levels 17.5 and 12.5 units, respectively) as well as the association of UP with dialysis-free survival (p < 0.001, log-rank test) (cut-off level 3.5 units). The impressive discriminative power of these simple prognostic factors for the prediction of outcome after liver transplantation emphasizes the relevance of strategies to avoid excessive transfusion requirements.

  13. MRE11 and ATM Expression Levels Predict Rectal Cancer Survival and Their Association with Radiotherapy Response

    PubMed Central

    Revoltar, Maxine; Lim, Stephanie H.; Tut, Thein-Ga; Abubakar, Askar; Henderson, Chris J.; Chua, Wei; Ng, Weng; Lee, Mark; De Souza, Paul; Morgan, Matthew; Lee, C. Soon; Shin, Joo-Shik

    2016-01-01

    Background Aberrant expression of DNA repair proteins is associated with poor survival in cancer patients. We investigated the combined expression of MRE11 and ATM as a predictive marker of response to radiotherapy in rectal cancer. Methods MRE11 and ATM expression were examined in tumor samples from 262 rectal cancer patients who underwent surgery for rectal cancer, including a sub-cohort of 54 patients who were treated with neoadjuvant radiotherapy. The relationship between expression of the two-protein panel and tumor regression grade (TRG) was assessed by Mann–Whitney U test and receiver operating characteristics area under curve (ROC-AUC) analysis. The association between expression of the two-protein panel and clinicopathologic variables and survival was examined by Kaplan-Meier methods and Cox regression analysis. Results A high score for two-protein combined expression in the tumor center (TC) was significantly associated with worse disease-free survival (DFS) (P = 0.035) and overall survival (OS) (P = 0.003) in the whole cohort, and with DFS (P = 0.028) and OS (P = 0.024) in the neoadjuvant subgroup (n = 54). In multivariate analysis, the two-protein combination panel (HR = 2.178, 95% CI 1.115–4.256, P = 0.023) and perineural invasion (HR = 2.183, 95% CI 1.222–3.899, P = 0.008) were significantly associated with DFS. Using ROC-AUC analysis of good versus poor histological tumor response among patients treated preoperatively with radiotherapy, the average ROC-AUC was 0.745 for the combined panel, 0.618 for ATM alone, and 0.711 for MRE11 alone. Conclusions The MRE11/ATM two-protein panel developed in this study may have clinical value as a predictive marker of tumor response to neoadjuvant radiotherapy, and a prognostic marker for disease-free and overall survival. PMID:27930716

  14. Sunitinib-induced hypothyroidism predicts progression-free survival in metastatic renal cell carcinoma patients.

    PubMed

    Buda-Nowak, Anna; Kucharz, Jakub; Dumnicka, Paulina; Kuzniewski, Marek; Herman, Roman Maria; Zygulska, Aneta L; Kusnierz-Cabala, Beata

    2017-04-01

    Sunitinib is a tyrosine kinase inhibitor (TKI) used in treatment of metastatic renal cell carcinoma (mRCC), gastrointestinal stromal tumors and pancreatic neuroendocrine tumors. One of the most common side effects related to sunitinib is hypothyroidism. Recent trials suggest correlation between the incidence of hypothyroidism and treatment outcome in patients treated with TKI. This study evaluates whether development of hypothyroidism is a predictive marker of progression-free survival (PFS) in patients with mRCC treated with sunitinib. Twenty-seven patients diagnosed with clear cell mRCC, after nephrectomy and in 'good' or 'intermediate' MSKCC risk prognostic group, were included in the study. All patients received sunitinib as a first-line treatment on a standard schedule (initial dose 50 mg/day, 4 weeks on, 2 weeks off). The thyroid-stimulating hormone serum levels were obtained at the baseline and every 12 weeks of treatment. In statistic analyses, we used Kaplan-Meier method for assessment of progression-free survival; for comparison of survival, we used log-rank test. In our study, the incidence of hypothyroidism was 44%. The patients who had developed hypothyroidism had better median PFS to patients with normal thyroid function 28,3 months [95% (CI) 20.4-36.2 months] versus 9.8 months (6.4-13.1 months). In survival analysis, we perceive that thyroid dysfunction is a predictive factor of a progression-free survival (PFS). In the unified group of patients, the development of hypothyroidism during treatment with sunitinib is a positive marker for PFS. During that treatment, thyroid function should be evaluated regularly.

  15. MRE11 and ATM Expression Levels Predict Rectal Cancer Survival and Their Association with Radiotherapy Response.

    PubMed

    Ho, Vincent; Chung, Liping; Revoltar, Maxine; Lim, Stephanie H; Tut, Thein-Ga; Abubakar, Askar; Henderson, Chris J; Chua, Wei; Ng, Weng; Lee, Mark; De Souza, Paul; Morgan, Matthew; Lee, C Soon; Shin, Joo-Shik

    2016-01-01

    Aberrant expression of DNA repair proteins is associated with poor survival in cancer patients. We investigated the combined expression of MRE11 and ATM as a predictive marker of response to radiotherapy in rectal cancer. MRE11 and ATM expression were examined in tumor samples from 262 rectal cancer patients who underwent surgery for rectal cancer, including a sub-cohort of 54 patients who were treated with neoadjuvant radiotherapy. The relationship between expression of the two-protein panel and tumor regression grade (TRG) was assessed by Mann-Whitney U test and receiver operating characteristics area under curve (ROC-AUC) analysis. The association between expression of the two-protein panel and clinicopathologic variables and survival was examined by Kaplan-Meier methods and Cox regression analysis. A high score for two-protein combined expression in the tumor center (TC) was significantly associated with worse disease-free survival (DFS) (P = 0.035) and overall survival (OS) (P = 0.003) in the whole cohort, and with DFS (P = 0.028) and OS (P = 0.024) in the neoadjuvant subgroup (n = 54). In multivariate analysis, the two-protein combination panel (HR = 2.178, 95% CI 1.115-4.256, P = 0.023) and perineural invasion (HR = 2.183, 95% CI 1.222-3.899, P = 0.008) were significantly associated with DFS. Using ROC-AUC analysis of good versus poor histological tumor response among patients treated preoperatively with radiotherapy, the average ROC-AUC was 0.745 for the combined panel, 0.618 for ATM alone, and 0.711 for MRE11 alone. The MRE11/ATM two-protein panel developed in this study may have clinical value as a predictive marker of tumor response to neoadjuvant radiotherapy, and a prognostic marker for disease-free and overall survival.

  16. B7-H3 Overexpression Predicts Poor Survival of Cancer Patients: A Meta-Analysis.

    PubMed

    Ye, Zhimeng; Zheng, Zhuojun; Li, Xiaodong; Zhu, Yuandong; Zhong, Zhaoping; Peng, Linrui; Wu, Yanyan

    2016-01-01

    B7-H3 exhibits altered expression in various cancers. However, the correlation between B7-H3 expression and prognosis of cancer patients remains controversial. Therefore, we elicit a meta-analysis to investigate the potential value of B7-H3 in the prognostic prediction in human cancers. We searched PubMed (last update by June 15th, 2016) to identify studies assessing the effect of B7-H3 on survival of cancer patients. Hazard ratios (HRs) for overall survival (OS), recurrence free survival (RFS) and progression-free survival (PFS) from individual studies were calculated and pooled by using a random-effect or fix-effect model, and heterogeneity and publication bias analyses were also performed. Data from 24 observational studies consisting of 4141 patients were summarized. An elevated baseline B7-H3 was significantly correlated with poor OS (pooled HR = 2.09; 95% CI =1.60-2.74; P < 0.001). Differences across subgroups of tumor type (P = 0.324), year of publication (P = 0.431), ethnicity (P = 0.940), source of HR (P = 0.145), analysis type (P = 0.178) and sample size (P = 0.909) were not significant. Furthermore, high B7-H3 expression also predicted a significantly poor RFS (pooled HR = 1.39; 95% CI = 1.11-1.75; P = 0.004) but not PFS. This meta-analysis clarifies that elevated B7-H3 expression is significantly associated with poor survival in cancer patients. © 2016 The Author(s) Published by S. Karger AG, Basel.

  17. The BMP inhibitor DAND5 in serum predicts poor survival in breast cancer

    PubMed Central

    Huang, Sheng; Huang, Naisi; Li, Shan; Shao, Zhiming; Wu, Jiong

    2016-01-01

    Background & Aims Breast cancer (BC) is prevalent worldwide malignant cancer. Improvements in timely and effective diagnosis and prediction are needed. As reported, secreted DAND5 is contributed to BC metastasis. We aim to assess whether DAND5 in peripheral blood serum could determine BC-specific mortality. Methods We used immunohistochemistry staining to detect DAND5 expression in our BC tissue array including 250 samples. Angiogenesis assay and xenograft mice model were used to examine the secreted DAND5 function in BC progression. Serum concentration of DAND5 was examined by ELISA in 1730 BC patients. Kaplan-Meier and adjusted Cox proportional hazards models were utilized to analyze the prognosis and survival of BC patients. Results Tissue array results showed that positive DAND5 staining cases displayed a higher likelihood of occurrence of disease events (HR=5.494; 95% CI: 1.008-2.353; P=0.048) in univariate analysis and remained the same trend in multivariate analysis (HR=2.537; 95% CI: 1.056-6.096; P=0.037). DAND5 positive patients exerted generally poor DFS (P=0.041) in the Kaplan-Meier survival analysis. Furthermore, secreted DAND5 promoted tumor growth and angiogenesis in vitro and in vivo. In addition, positive DAND5 in BC patients serum was associated with increased risk of disease events occurrence (univariate: HR=1.58; 95% CI: 1.206-2.070; P=0.001; multivariate: HR=1.4; 95% CI: 1.003-1.954; P=0.048) in univariate and multivariate survival analysis. In the Kaplan-Meier analysis, serum DAND5 positively correlated with poor DFS (P=0.001) and DDFS (P=0.002). Conclusions DAND5 was correlated with poor survival and could serve as an easily detectable serum biomarker to predict the survival of breast cancer. PMID:26908452

  18. Radiation therapy for nasopharyngeal carcinoma: the predictive value of interim survival assessment.

    PubMed

    Toya, Ryo; Murakami, Ryuji; Saito, Tetsuo; Murakami, Daizo; Matsuyama, Tomohiko; Baba, Yuji; Nishimura, Ryuichi; Hirai, Toshinori; Semba, Akiko; Yumoto, Eiji; Yamashita, Yasuyuki; Oya, Natsuo

    2016-09-01

    Pretreatment characteristics are suggested as predictive and/or prognostic factors for nasopharyngeal carcinoma (NPC); however, individual tumor radiosensitivities have previously not been considered. As boost planning is recommended for NPC, we performed interim assessments of magnetic resonance (MR) images for boost planning and retrospectively evaluated their predictive value for the survival of NPC patients. Radiation therapy via elective nodal irradiation (median dose: 39.6 Gy) with/without chemotherapy was used to treat 63 NPC patients. Boost irradiation (median total dose: 70 Gy) was performed based on the interim assessment. The largest lymph node (LN) was measured on MR images acquired at the time of interim assessment. The site of first failure was local in 8 (12.7%), regional in 7 (11.1%), and distant in 12 patients (19.0%). All 7 patients with regional failure harbored LNs ≥15 mm at interim assessment. We divided the 63 patients into two groups based on LN size [large (≥15 mm), n = 10 and small (<15 mm), n = 53]. Univariate analysis showed that 5-year overall survival (OS) and cause-specific survival (CSS) rates for large LNs were significantly lower than for small LNs (OS: 12.5% vs 70.5%, P < 0.001 and CSS: 25.0% vs 80.0%, P < 0.001). Multivariate analysis showed that large LNs were a significantly unfavorable factor for both OS (hazard ratio = 4.543, P = 0.002) and CSS (hazard ratio = 6.020, P = 0.001). The results suggest that LN size at interim assessment could predict survival in NPC patients.

  19. Early stridor onset and stridor treatment predict survival in 136 patients with MSA.

    PubMed

    Giannini, Giulia; Calandra-Buonaura, Giovanna; Mastrolilli, Francesca; Righini, Matteo; Bacchi-Reggiani, Maria Letizia; Cecere, Annagrazia; Barletta, Giorgio; Guaraldi, Pietro; Provini, Federica; Cortelli, Pietro

    2016-09-27

    To evaluate the predictive value of stridor and its latency of onset and to investigate the role of stridor treatment in a cohort of patients with multiple system atrophy (MSA) referred to a tertiary center. We retrospectively identified patients diagnosed with MSA referred to our department beginning in 1991 and evaluated at least yearly during the disease course. Stridor was defined as present when confirmed by a whole night video-polysomnography and as early if presenting within 3 years of disease onset. Survival data, from disease onset to time of death, were calculated with Kaplan-Meier curves. Predictors were identified in univariate and multivariable Cox regression analyses. We included 136 patients with MSA; 113 were deceased at the time of study. Stridor was diagnosed in 42 patients, and 22 presented early stridor onset. Twelve of the 31 patients treated for stridor received tracheostomy, and 19 received continuous positive airway pressure. Overall survival did not differ between patients with and without stridor, while patients with early stridor onset had a worse prognosis than those developing this symptom later. In the stridor subgroup, early stridor onset was an unfavorable survival predictor. Stridor treatment was significantly associated with survival in our population. The Kaplan-Meier curve did not reveal significant differences in survival between the 2 treatments even though there was a trend toward longer disease duration in patients receiving tracheostomy. Our results demonstrated that early stridor onset is an independent predictor for shorter survival and that tracheostomy could control stridor, influencing disease duration. © 2016 American Academy of Neurology.

  20. The PROPKD Score: A New Algorithm to Predict Renal Survival in Autosomal Dominant Polycystic Kidney Disease.

    PubMed

    Cornec-Le Gall, Emilie; Audrézet, Marie-Pierre; Rousseau, Annick; Hourmant, Maryvonne; Renaudineau, Eric; Charasse, Christophe; Morin, Marie-Pascale; Moal, Marie-Christine; Dantal, Jacques; Wehbe, Bassem; Perrichot, Régine; Frouget, Thierry; Vigneau, Cécile; Potier, Jérôme; Jousset, Philippe; Guillodo, Marie-Paule; Siohan, Pascale; Terki, Nazim; Sawadogo, Théophile; Legrand, Didier; Menoyo-Calonge, Victorio; Benarbia, Seddik; Besnier, Dominique; Longuet, Hélène; Férec, Claude; Le Meur, Yannick

    2016-03-01

    The course of autosomal dominant polycystic kidney disease (ADPKD) varies among individuals, with some reaching ESRD before 40 years of age and others never requiring RRT. In this study, we developed a prognostic model to predict renal outcomes in patients with ADPKD on the basis of genetic and clinical data. We conducted a cross-sectional study of 1341 patients from the Genkyst cohort and evaluated the influence of clinical and genetic factors on renal survival. Multivariate survival analysis identified four variables that were significantly associated with age at ESRD onset, and a scoring system from 0 to 9 was developed as follows: being male: 1 point; hypertension before 35 years of age: 2 points; first urologic event before 35 years of age: 2 points; PKD2 mutation: 0 points; nontruncating PKD1 mutation: 2 points; and truncating PKD1 mutation: 4 points. Three risk categories were subsequently defined as low risk (0-3 points), intermediate risk (4-6 points), and high risk (7-9 points) of progression to ESRD, with corresponding median ages for ESRD onset of 70.6, 56.9, and 49 years, respectively. Whereas a score ≤3 eliminates evolution to ESRD before 60 years of age with a negative predictive value of 81.4%, a score >6 forecasts ESRD onset before 60 years of age with a positive predictive value of 90.9%. This new prognostic score accurately predicts renal outcomes in patients with ADPKD and may enable the personalization of therapeutic management of ADPKD.

  1. Validation of two predictive models for survival in pulmonary arterial hypertension.

    PubMed

    Sitbon, Olivier; Benza, Raymond L; Badesch, David B; Barst, Robyn J; Elliott, C Gregory; Gressin, Virginie; Lemarié, Jean-Christophe; Miller, Dave P; Muros-Le Rouzic, Erwan; Simonneau, Gérald; Frost, Adaani E; Farber, Harrison W; Humbert, Marc; McGoon, Michael D

    2015-07-01

    The French Pulmonary Hypertension Network (FPHN) registry and the Registry to Evaluate Early And Long-term Pulmonary Arterial Hypertension Disease Management (REVEAL) have developed predictive models for survival in pulmonary arterial hypertension (PAH). In this collaboration, we assess the external validity (or generalisability) of the FPHN ItinérAIR-HTAP predictive equation and the REVEAL risk score calculator. Validation cohorts approximated the eligibility criteria defined for each model. The REVEAL cohort comprised 292 treatment-naïve, adult patients diagnosed <1 year prior to enrolment with idiopathic, familial or anorexigen-induced PAH. The FPHN cohort comprised 1737 patients with group 1 PAH. Application of FPHN parameters to REVEAL and REVEAL risk scores to FPHN demonstrated estimated hazard ratios that were consistent between studies and had high probabilities of concordance (hazard ratios of 0.72, 95% CI 0.64-0.80, and 0.73, 95% CI 0.70-0.77, respectively). The REVEAL risk score calculator and FPHN ItinérAIR-HTAP predictive equation showed good discrimination and calibration for prediction of survival in the FPHN and REVEAL cohorts, respectively, suggesting prognostic generalisability in geographically different PAH populations. Once prospectively validated, these may become valuable tools in clinical practice.

  2. Preoperative Body Mass Index, Blood Albumin and Triglycerides Predict Survival for Patients with Gastric Cancer.

    PubMed

    Liu, Bin Zheng; Tao, Lin; Chen, Yun Zhao; Li, Xu Zhe; Dong, Yu Ling; Ma, Ya Jing; Li, Shu Gang; Li, Feng; Zhang, Wen Jie

    2016-01-01

    Gastric cancer (GC) is common and its prognosis is often poor due to difficulties in early diagnosis and optimal treatment strategies. TNM staging system is useful in predicting prognosis but only possible after surgery. Therefore, it is desirable to investigate prognostic factors/markers that may predict prognosis before surgery by which helps appropriate management decisions preoperatively. A total of 320 GC patients were consecutively recruited from 2004 to 2013 and followed up for 127 months (10.6 years) after surgery. These patients' were examined for body mass index (BMI) and blood levels of albumin, triglyceride, total cholesterol, low density lipoprotein cholesterol (LDL-C), and high density lipoprotein cholesterol (HDL-C). Kaplan-Meier method and log rank test were used to analyze long-term survival using the above potential risk markers. We first employed medians of these variables to reveal maximal potentials of the above prognostic predictors. Three major findings were obtained: (1) Preoperative BMI was positively correlated with albumin (r = 0.144, P<0.05) and triglyceride (r = 0.365, P<0.01), but negatively correlated with TNM staging (r = -0.265, P<0.05). Preoperative albumin levels were positively correlated with triglyceride (r = 0.173, P<0.05) but again, negatively correlated with TNM staging (r = -0.137, P<0.05); (2) Poor survival was observed in GC patients with lower levels of BMI (P = 0.028), albumin (P = 0.004), and triglyceride (P = 0.043), respectively. Receiver operating characteristic (ROC) curve analyses suggested BMI, albumin and triglyceride to have survival-predictor powers similar to TNM system; and (3) Cox multi-factorial analyses demonstrated that age (P = 0.049), BMI (P = 0.016), cell differentiation (P = 0.001), and TNM staging (P = 0.011) were independent overall survival-predictors for GC patients. Preoperative BMI, albumin, and triglyceride levels are capable of predicting survival for GC patients superior to postoperative TNM

  3. Preoperative Body Mass Index, Blood Albumin and Triglycerides Predict Survival for Patients with Gastric Cancer

    PubMed Central

    Liu, Bin Zheng; Tao, Lin; Chen, Yun Zhao; Li, Xu Zhe; Dong, Yu Ling; Ma, Ya Jing; Li, Shu Gang; Li, Feng; Zhang, Wen Jie

    2016-01-01

    Background Gastric cancer (GC) is common and its prognosis is often poor due to difficulties in early diagnosis and optimal treatment strategies. TNM staging system is useful in predicting prognosis but only possible after surgery. Therefore, it is desirable to investigate prognostic factors/markers that may predict prognosis before surgery by which helps appropriate management decisions preoperatively. Methods A total of 320 GC patients were consecutively recruited from 2004 to 2013 and followed up for 127 months (10.6 years) after surgery. These patients’ were examined for body mass index (BMI) and blood levels of albumin, triglyceride, total cholesterol, low density lipoprotein cholesterol (LDL-C), and high density lipoprotein cholesterol (HDL-C). Kaplan-Meier method and log rank test were used to analyze long-term survival using the above potential risk markers. We first employed medians of these variables to reveal maximal potentials of the above prognostic predictors. Results Three major findings were obtained: (1) Preoperative BMI was positively correlated with albumin (r = 0.144, P<0.05) and triglyceride (r = 0.365, P<0.01), but negatively correlated with TNM staging (r = -0.265, P<0.05). Preoperative albumin levels were positively correlated with triglyceride (r = 0.173, P<0.05) but again, negatively correlated with TNM staging (r = -0.137, P<0.05); (2) Poor survival was observed in GC patients with lower levels of BMI (P = 0.028), albumin (P = 0.004), and triglyceride (P = 0.043), respectively. Receiver operating characteristic (ROC) curve analyses suggested BMI, albumin and triglyceride to have survival-predictor powers similar to TNM system; and (3) Cox multi-factorial analyses demonstrated that age (P = 0.049), BMI (P = 0.016), cell differentiation (P = 0.001), and TNM staging (P = 0.011) were independent overall survival-predictors for GC patients. Conclusions Preoperative BMI, albumin, and triglyceride levels are capable of predicting survival for

  4. Usefulness of ST-segment elevation in the inferior leads in predicting ventricular septal rupture in patients with anterior wall acute myocardial infarction.

    PubMed

    Hayashi, Takahiro; Hirano, Yutaka; Takai, Hiroyuki; Kimura, Akio; Taniguchi, Mitsugu; Kurooka, Atsuhiro; Ishikawa, Kinji

    2005-10-15

    The ventricular septum receives its blood supply from the septal perforators of the left anterior descending (LAD) coronary artery and the right coronary artery. However, when the LAD artery extends to the inferior wall, beyond the apex (so-called wrapped LAD), the ventricular septum near the apex receives blood supply only from the LAD artery. As a consequence, ventricular septal rupture (VSR) would seem more likely in myocardial infarction with occlusion of this type of LAD artery. To test this hypothesis, we compared electrocardiographic findings in 21 patients who had anterior acute myocardial infarction that was complicated by VSR with those in 275 patients who had acute myocardial infarction that was not complicated by VSR. We observed ST-segment elevation in all inferior leads (II, III, and aVF) in addition to anterior leads in 42.9% of patients (9 of 21) who had VSR but in only 3.6% of those (10 of 275) who did not have VSR. Abnormal Q waves appeared in all 3 inferior leads in 44.4% of patients (8 of 18) who had VSR but in only 4.0% of those (10 of 250) who did not have VSR. Thus, the incidence of ST-segment elevation and abnormal Q waves in the inferior leads was significantly (p <0.001) greater in the VSR group. In addition, multivariate analysis of patient characteristics, including advanced age, female gender, and coronary morphology, showed VSR to be significantly correlated with ST-segment elevation (odds ratio 16.93, 95% confidence interval 4.13 to 69.30) and abnormal Q waves (odds ratio 13.64, 95% confidence interval 3.16 to 58.79) in the 3 inferior leads. In conclusion, these electrocardiographic findings can be useful predictors of complication by VSR.

  5. Predicting the graft survival for heart-lung transplantation patients: an integrated data mining methodology.

    PubMed

    Oztekin, Asil; Delen, Dursun; Kong, Zhenyu James

    2009-12-01

    Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for

  6. Predictive parameters of survival in hemodialysis patients with restless leg syndrome.

    PubMed

    Stolic, Radojica V; Trajkovic, Goran Z; Jekic, Djole; Sovtic, Sasa R; Jovanovic, Aleksandar N; Stolic, Dragica Z; Stanojevic-Pirkovic, Marijana S; Djordjevic, Zorana

    2014-09-01

    Restless leg syndrome (RLS) affects the quality of life and survival in patients on hemodialysis (HD). The aim of this study was to determine the characteristics and survival parameters in patients on HD with RLS. This study was a non-randomized clinical study involving 204 patients on HD, of whom 71 were female and 133 were male. Symptoms of RLS were defined as positive responses to four questions comprising the criteria of RLS. We recorded the outcome of treatment, biochemical analyses, demographic, sexual, anthropometric and clinical characteristics in all study patients. Patients with RLS who completed the study had a significantly higher body mass index and lower intima-media thickness and flow through the arteriovenous fistula. Among patients with RLS who died, there were more smokers as well as higher incidences of cardiovascular disease and diabetes mellitus. Among patients with RLS who survived, there were a greater number of patients with preserved diuresis and receiving erythropoietin therapy. Patients who completed the study had significantly higher levels of hemoglobin, creatinine, serum iron and transferrin saturation. Diabetes mellitus (B = 1.802; P = 0.002) and low Kt/V (B = -5.218; P = 0.001) were major predictive parameters for survival.

  7. Modelling Circulating Tumour Cells for Personalised Survival Prediction in Metastatic Breast Cancer

    PubMed Central

    2015-01-01

    Ductal carcinoma is one of the most common cancers among women, and the main cause of death is the formation of metastases. The development of metastases is caused by cancer cells that migrate from the primary tumour site (the mammary duct) through the blood vessels and extravasating they initiate metastasis. Here, we propose a multi-compartment model which mimics the dynamics of tumoural cells in the mammary duct, in the circulatory system and in the bone. Through a branching process model, we describe the relation between the survival times and the four markers mainly involved in metastatic breast cancer (EPCAM, CD47, CD44 and MET). In particular, the model takes into account the gene expression profile of circulating tumour cells to predict personalised survival probability. We also include the administration of drugs as bisphosphonates, which reduce the formation of circulating tumour cells and their survival in the blood vessels, in order to analyse the dynamic changes induced by the therapy. We analyse the effects of circulating tumour cells on the progression of the disease providing a quantitative measure of the cell driver mutations needed for invading the bone tissue. Our model allows to design intervention scenarios that alter the patient-specific survival probability by modifying the populations of circulating tumour cells and it could be extended to other cancer metastasis dynamics. PMID:25978366

  8. ROCK I Has More Accurate Prognostic Value than MET in Predicting Patient Survival in Colorectal Cancer.

    PubMed

    Li, Jian; Bharadwaj, Shruthi S; Guzman, Grace; Vishnubhotla, Ramana; Glover, Sarah C

    2015-06-01

    Colorectal cancer remains the second leading cause of death in the United States despite improvements in incidence rates and advancements in screening. The present study evaluated the prognostic value of two tumor markers, MET and ROCK I, which have been noted in other cancers to provide more accurate prognoses of patient outcomes than tumor staging alone. We constructed a tissue microarray from surgical specimens of adenocarcinomas from 108 colorectal cancer patients. Using immunohistochemistry, we examined the expression levels of tumor markers MET and ROCK I, with a pathologist blinded to patient identities and clinical outcomes providing the scoring of MET and ROCK I expression. We then used retrospective analysis of patients' survival data to provide correlations with expression levels of MET and ROCK I. Both MET and ROCK I were significantly over-expressed in colorectal cancer tissues, relative to the unaffected adjacent mucosa. Kaplan-Meier survival analysis revealed that patients' 5-year survival was inversely correlated with levels of expression of ROCK I. In contrast, MET was less strongly correlated with five-year survival. ROCK I provides better efficacy in predicting patient outcomes, compared to either tumor staging or MET expression. As a result, ROCK I may provide a less invasive method of assessing patient prognoses and directing therapeutic interventions. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  9. The histopathologic type predicts survival of patients with ampullary carcinoma after resection: A meta-analysis.

    PubMed

    Zhou, Yanming; Li, Dianqi; Wu, Lupeng; Si, Xiaoying

    The results of studies on the prognostic value of histopathologic differentiation of the intestinal and pancreatobiliary types of ampullary carcinoma after resection are conflicting. A meta-analysis was undertaken to investigate this issue. A systematic literature search was performed to identify articles published from January 2000 to August 2016. Data were pooled for meta-analysis using Review Manager 5.3. Twenty three retrospective studies involving a total of 2234 patients were identified for inclusion, of whom 1021 (45.7%) had intestinal type tumors and 899 (40.2%) had pancreaticobiliary type tumors. Patients with the pancreaticobiliary type had high rates of poor tumor differentiation (P < 0.001), lymph node metastasis (P < 0.001), vascular invasion (P < 0.001), perineural invasion (P < 0.001), and positive resection margins (P = 0.004), as compared with those with the intestinal type. The pancreaticobiliary type predicted a worse overall survival (hazard ratio [HR] 1.84, 95% CI 1.49-2.27; P < 0.001) and disease-free survival (HR 1.93, 95% CI 1.23-3.01; P = 0.004). The histopathologic type has major impact on survival in patients with ampullary carcinoma after resection, and the pancreaticobiliary type reflects a more aggressive tumor biology and is associated with worse survival. Copyright © 2017 IAP and EPC. Published by Elsevier B.V. All rights reserved.

  10. Survival Outcomes and Predictive Factors for Female Urethral Cancer: Long-term Experience with Korean Patients.

    PubMed

    Kang, Minyong; Jeong, Chang Wook; Kwak, Cheol; Kim, Hyeon Hoe; Ku, Ja Hyeon

    2015-08-01

    The aim of this study was to evaluate female urethral cancer (UCa) patients treated and followed-up during a time period spanning more than 20 yr at single institution in Korea. We reviewed medical records of 21 consecutive patients diagnosed with female UCa at our institution between 1991 and 2012. After exclusion of two patients due to undefined histology, we examined clinicopathological variables, as well as survival outcomes of 19 patients with female UCa. A Cox proportional hazards ratio model was used to identify significant predictors of prognosis according to variables. The median age at diagnosis was 59 yr, and the median follow-up duration was 87.0 months. The most common initial symptoms were voiding symptoms and blood spotting. The median tumor size was 3.4 cm, and 55% of patients had lesions involving the entire urethra. The most common histologic type was adenocarcinoma, and the second most common type was urothelial carcinoma. Fourteen patients underwent surgery, and 7 of these patients received adjuvant radiation or systemic chemotherapy. Eleven patients experienced tumor recurrence after primary therapy. Patients with high stage disease, advanced T stage (≥T3), and positive lymph nodes had worse survival outcomes compared to their counterparts. Particularly, lymph node positivity and advanced T stage were significant predictive factors for all survival outcomes. Tumor location was the only significant predictor for recurrence-free survival. Although our study included a small number of patients, it conveys valuable information about this rare female urologic malignancy in a Korean population.

  11. ['Lung age' predicts post-operative complications and survival in lung cancer patients].

    PubMed

    Haruki, Tomohiro; Nakamura, Hiroshige; Taniguchi, Yuji; Miwa, Ken; Adachi, Yoshin; Fujioka, Shinji

    2010-08-01

    The Japanese Respiratory Society (JRS) recently proposed 'lung age' as an easily understood concept of respiratory function. In this study, we evaluated whether 'lung age' could be a useful predictor of post-operative respiratory complications and survival patients with lung cancer treated surgically. The study recruited 308 patients who underwent surgery for primary non-small cell lung cancer. All patients had pre-operative pulmonary function testing. 'Lung age' was determined using the methods advocated by the JRS. Based on the difference between real age' (R) and 'lung age' (L), patients were classified into five groups: group A: R-L > 15 (n = 37), B: 5 < R-L < or = 15 (n = 50), C: -5 < or = R-L < or = 5 (n = 73), D: -15 < or = R-L < -5 (n = 54), E: -15 > R-L (n = 94). Clinicopathological factors, post-operative respiratory complications and survival were compared between the groups. Gender, smoking status and index, histology, operative approach and FEV1 were significantly associated with the group classification. The incidence of complications was significantly higher in group E compared with other groups (p < 0.01). Multivariate analysis showed that the group classification by 'lung age' was an independent predictor of postoperative respiratory complications (p = 0.02). Overall survival differed significantly between the groups (p = 0.03). 'Lung age' could be useful for the prediction of post-operative respiratory complications and survival in patients with lung cancer treated surgically.

  12. Elevated Omentin Serum Levels Predict Long-Term Survival in Critically Ill Patients

    PubMed Central

    Luedde, Mark; Benz, Fabian; Niedeggen, Jennifer; Vucur, Mihael; Hippe, Hans-Joerg; Spehlmann, Martina E.; Schueller, Florian; Loosen, Sven; Frey, Norbert; Trautwein, Christian; Koch, Alexander; Luedde, Tom; Tacke, Frank

    2016-01-01

    Introduction. Omentin, a recently described adipokine, was shown to be involved in the pathophysiology of inflammatory and infectious diseases. However, its role in critical illness and sepsis is currently unknown. Materials and Methods. Omentin serum concentrations were measured in 117 ICU-patients (84 with septic and 33 with nonseptic disease etiology) admitted to the medical ICU. Results were compared with 50 healthy controls. Results. Omentin serum levels of critically ill patients at admission to the ICU or after 72 hours of ICU treatment were similar compared to healthy controls. Moreover, circulating omentin levels were independent of sepsis and etiology of critical illness. Notably, serum concentrations of omentin could not be linked to concentrations of inflammatory cytokines or routinely used sepsis markers. While serum levels of omentin were not predictive for short term survival during ICU treatment, low omentin concentrations were an independent predictor of patients' overall survival. Omentin levels strongly correlated with that of other adipokines (e.g., leptin receptor or adiponectin), which have also been identified as prognostic markers in critical illness. Conclusions. Although circulating omentin levels did not differ between ICU-patients and controls, elevated omentin levels were predictive for an impaired patients' long term survival. PMID:27867249

  13. Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression.

    PubMed

    Goli, Shahrbanoo; Mahjub, Hossein; Faradmal, Javad; Mashayekhi, Hoda; Soltanian, Ali-Reza

    2016-01-01

    The Support Vector Regression (SVR) model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC) dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model.

  14. Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression

    PubMed Central

    Goli, Shahrbanoo; Faradmal, Javad; Mashayekhi, Hoda; Soltanian, Ali-Reza

    2016-01-01

    The Support Vector Regression (SVR) model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC) dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model. PMID:27882074

  15. Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer

    PubMed Central

    Jiang, Mengjie; Li, Dan; Jiang, Ting; Hong, Zhongwu; Wang, Fan; Li, Shuguang

    2016-01-01

    Background The features related to the prognosis of patients with mucinous breast cancer (MBC) remain controversial. We aimed to explore the prognostic factors of MBC and develop a nomogram for predicting survival outcomes. Methods The Surveillance, Epidemiology, and End Results (SEER) database was searched to identify 139611 women with resectable breast cancer from 1990 to 2007. Survival curves were generated using Kaplan-Meier methods. The 5-year and 10-year cancer-specific survival (CSS) rates were calculated using the Life-Table method. Based on Cox models, a nomogram was constructed to predict the probabilities of CSS for an individual patient. The competing risk regression model was used to analyse the specific survival of patients with MBC. Results There were 136569 (97.82%) infiltrative ductal cancer (IDC) patients and 3042 (2.18%) MBC patients. Patients with MBC had less lymph node involvement, a higher frequency of well-differentiated lesions, and more estrogen receptor (ER)-positive tumors. Patients with MBC had significantly higher 5 and10-year CSS rates (98.23 and 96.03%, respectively) than patients with IDC (91.44 and 85.48%, respectively). Univariate and multivariate analyses showed that MBC was an independent factor for better prognosis. As for patients with MBC, the event of death caused by another disease exceeded the event of death caused by breast cancer. A competing risk regression model further showed that lymph node involvement, poorly differentiated grade and advanced T-classification were independent factors of poor prognosis in patients with MBC. The Nomogram can accurately predict CSS with a high C-index (0.816). Risk scores developed from the nomogram can more accurately predict the prognosis of patients with MBC (C-index = 0.789) than the traditional TNM system (C-index = 0.704, P< 0.001). Conclusions Patients with MBC have a better prognosis than patients with IDC. Nomograms could help clinicians make more informed decisions in

  16. Predicting Survival of De Novo Metastatic Breast Cancer in Asian Women: Systematic Review and Validation Study

    PubMed Central

    Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G. M.; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M.

    2014-01-01

    Background In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. Materials and Methods We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). Results We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48–0.53) to 0.63 (95% CI, 0.60–0.66). Conclusion The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making. PMID:24695692

  17. Gene Expression-Based Survival Prediction in Lung Adenocarcinoma: A Multi-Site, Blinded Validation Study

    PubMed Central

    Shedden, Kerby; Taylor, Jeremy M.G.; Enkemann, Steve A.; Tsao, Ming S.; Yeatman, Timothy J.; Gerald, William L.; Eschrich, Steve; Jurisica, Igor; Venkatraman, Seshan E.; Meyerson, Matthew; Kuick, Rork; Dobbin, Kevin K.; Lively, Tracy; Jacobson, James W.; Beer, David G.; Giordano, Thomas J.; Misek, David E.; Chang, Andrew C.; Zhu, Chang Qi; Strumpf, Dan; Hanash, Samir; Shepherd, Francis A.; Ding, Kuyue; Seymour, Lesley; Naoki, Katsuhiko; Pennell, Nathan; Weir, Barbara; Verhaak, Roel; Ladd-Acosta, Christine; Golub, Todd; Gruidl, Mike; Szoke, Janos; Zakowski, Maureen; Rusch, Valerie; Kris, Mark; Viale, Agnes; Motoi, Noriko; Travis, William; Sharma, Anupama

    2009-01-01

    Although prognostic gene expression signatures for survival in early stage lung cancer have been proposed, for clinical application it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) can be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas. PMID:18641660

  18. Cervical cancer survival prediction using hybrid of SMOTE, CART and smooth support vector machine

    NASA Astrophysics Data System (ADS)

    Purnami, S. W.; Khasanah, P. M.; Sumartini, S. H.; Chosuvivatwong, V.; Sriplung, H.

    2016-04-01

    According to the WHO, every two minutes there is one patient who died from cervical cancer. The high mortality rate is due to the lack of awareness of women for early detection. There are several factors that supposedly influence the survival of cervical cancer patients, including age, anemia status, stage, type of treatment, complications and secondary disease. This study wants to classify/predict cervical cancer survival based on those factors. Various classifications methods: classification and regression tree (CART), smooth support vector machine (SSVM), three order spline SSVM (TSSVM) were used. Since the data of cervical cancer are imbalanced, synthetic minority oversampling technique (SMOTE) is used for handling imbalanced dataset. Performances of these methods are evaluated using accuracy, sensitivity and specificity. Results of this study show that balancing data using SMOTE as preprocessing can improve performance of classification. The SMOTE-SSVM method provided better result than SMOTE-TSSVM and SMOTE-CART.

  19. EPH/ephrin profile and EPHB2 expression predicts patient survival in breast cancer

    PubMed Central

    Husa, Anna-Maria; Magić, Željana; Larsson, Malin; Fornander, Tommy; Pérez-Tenorio, Gizeh

    2016-01-01

    The EPH and ephrins function as both receptor and ligands and the output on their complex signaling is currently investigated in cancer. Previous work shows that some EPH family members have clinical value in breast cancer, suggesting that this family could be a source of novel clinical targets. Here we quantified the mRNA expression levels of EPH receptors and their ligands, ephrins, in 65 node positive breast cancer samples by RT-PCR with TaqMan® Micro Fluidics Cards Microarray. Upon hierarchical clustering of the mRNA expression levels, we identified a subgroup of patients with high expression, and poor clinical outcome. EPHA2, EPHA4, EFNB1, EFNB2, EPHB2 and EPHB6 were significantly correlated with the cluster groups and particularly EPHB2 was an independent prognostic factor in multivariate analysis and in four public databases. The EPHB2 protein expression was also analyzed by immunohistochemistry in paraffin embedded material (cohort 2). EPHB2 was detected in the membrane and cytoplasmic cell compartments and there was an inverse correlation between membranous and cytoplasmic EPHB2. Membranous EPHB2 predicted longer breast cancer survival in both univariate and multivariate analysis while cytoplasmic EPHB2 indicated shorter breast cancer survival in univariate analysis. Concluding: the EPH/EFN cluster analysis revealed that high EPH/EFN mRNA expression is an independent prognostic factor for poor survival. Especially EPHB2 predicted poor breast cancer survival in several materials and EPHB2 protein expression has also prognostic value depending on cell localization. PMID:26870995

  20. A gene expression inflammatory signature specifically predicts multiple myeloma evolution and patients survival

    PubMed Central

    Botta, C; Di Martino, M T; Ciliberto, D; Cucè, M; Correale, P; Rossi, M; Tagliaferri, P; Tassone, P

    2016-01-01

    Multiple myeloma (MM) is closely dependent on cross-talk between malignant plasma cells and cellular components of the inflammatory/immunosuppressive bone marrow milieu, which promotes disease progression, drug resistance, neo-angiogenesis, bone destruction and immune-impairment. We investigated the relevance of inflammatory genes in predicting disease evolution and patient survival. A bioinformatics study by Ingenuity Pathway Analysis on gene expression profiling dataset of monoclonal gammopathy of undetermined significance, smoldering and symptomatic-MM, identified inflammatory and cytokine/chemokine pathways as the most progressively affected during disease evolution. We then selected 20 candidate genes involved in B-cell inflammation and we investigated their role in predicting clinical outcome, through univariate and multivariate analyses (log-rank test, logistic regression and Cox-regression model). We defined an 8-genes signature (IL8, IL10, IL17A, CCL3, CCL5, VEGFA, EBI3 and NOS2) identifying each condition (MGUS/smoldering/symptomatic-MM) with 84% accuracy. Moreover, six genes (IFNG, IL2, LTA, CCL2, VEGFA, CCL3) were found independently correlated with patients' survival. Patients whose MM cells expressed high levels of Th1 cytokines (IFNG/LTA/IL2/CCL2) and low levels of CCL3 and VEGFA, experienced the longest survival. On these six genes, we built a prognostic risk score that was validated in three additional independent datasets. In this study, we provide proof-of-concept that inflammation has a critical role in MM patient progression and survival. The inflammatory-gene prognostic signature validated in different datasets clearly indicates novel opportunities for personalized anti-MM treatment. PMID:27983725

  1. Predicting the Survival Time for Bladder Cancer Using an Additive Hazards Model in Microarray Data

    PubMed Central

    TAPAK, Leili; MAHJUB, Hossein; SADEGHIFAR, Majid; SAIDIJAM, Massoud; POOROLAJAL, Jalal

    2016-01-01

    Background: One substantial part of microarray studies is to predict patients’ survival based on their gene expression profile. Variable selection techniques are powerful tools to handle high dimensionality in analysis of microarray data. However, these techniques have not been investigated in competing risks setting. This study aimed to investigate the performance of four sparse variable selection methods in estimating the survival time. Methods: The data included 1381 gene expression measurements and clinical information from 301 patients with bladder cancer operated in the years 1987 to 2000 in hospitals in Denmark, Sweden, Spain, France, and England. Four methods of the least absolute shrinkage and selection operator, smoothly clipped absolute deviation, the smooth integration of counting and absolute deviation and elastic net were utilized for simultaneous variable selection and estimation under an additive hazards model. The criteria of area under ROC curve, Brier score and c-index were used to compare the methods. Results: The median follow-up time for all patients was 47 months. The elastic net approach was indicated to outperform other methods. The elastic net had the lowest integrated Brier score (0.137±0.07) and the greatest median of the over-time AUC and C-index (0.803±0.06 and 0.779±0.13, respectively). Five out of 19 selected genes by the elastic net were significant (P<0.05) under an additive hazards model. It was indicated that the expression of RTN4, SON, IGF1R and CDC20 decrease the survival time, while the expression of SMARCAD1 increase it. Conclusion: The elastic net had higher capability than the other methods for the prediction of survival time in patients with bladder cancer in the presence of competing risks base on additive hazards model. PMID:27114989

  2. Expression profiles of loneliness-associated genes for survival prediction in cancer patients.

    PubMed

    You, Liang-Fu; Yeh, Jia-Rong; Su, Mu-Chun

    2014-01-01

    Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high- lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness- associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

  3. Histopathologic features predict survival in diffuse pleural malignant mesothelioma on pleural biopsies.

    PubMed

    Habougit, Cyril; Trombert-Paviot, Béatrice; Karpathiou, Georgia; Casteillo, François; Bayle-Bleuez, Sophie; Fournel, Pierre; Vergnon, Jean-Michel; Tiffet, Olivier; Péoc'h, Michel; Forest, Fabien

    2017-03-27

    Malignant pleural mesothelioma is a rare tumor with a poor prognosis. The only universally recognized pathological prognostic factor is histopathological subtype with a shorter survival in non-epithelioid subtypes. Recently, a grading of epithelioid mesothelioma on surgical resection has been proposed. The aim of our work is to assess the prognostic role of several histopathological factors on a retrospective cohort of 116 patients diagnosed as a pleural mesothelioma for more than 95% of patients on pleural biopsy. Our work shows that mitotic count <3/10 HPF (p < 0.0001), the lack of necrosis (p = 0.0379), mild nuclear atypia (p = 0.0054), the lack of atypical mitoses (p = 0.0265), a nucleoli size <3 μm (p = 0.0139), and a nucleoli absent or visible at 200× or higher magnification (p = 0.0170) are significantly associated with a better median overall survival in epithelioid mesothelioma. The presence of atypical mitoses was found to be related to a worse median survival in non-epithelioid mesothelioma. Mitotic count, necrosis, nuclear atypia, and nucleoli size are not associated with overall survival in non-epithelioid mesothelioma. Our work highlights that histopathological prognostic factors can be assessed on pleural biopsies and can predict reliably median overall survival. This is of interest in order to define subgroups of patients who could benefit of different therapies and select patients who could benefit of surgical excision.

  4. Tumor Response and Survival Predicted by Post-Therapy FDG-PET/CT in Anal Cancer

    SciTech Connect

    Schwarz, Julie K.; Siegel, Barry A.; Dehdashti, Farrokh; Myerson, Robert J.; Fleshman, James W.; Grigsby, Perry W.

    2008-05-01

    Purpose: To evaluate the response to therapy for anal carcinoma using post-therapy imaging with positron emission tomography (PET)/computed tomography and F-18 fluorodeoxyglucose (FDG) and to compare the metabolic response with patient outcome. Patients and Methods: This was a prospective cohort study of 53 consecutive patients with anal cancer. All patients underwent pre- and post-treatment whole-body FDG-PET/computed tomography. Patients had been treated with external beam radiotherapy and concurrent chemotherapy. Whole-body FDG-PET was performed 0.9-5.4 months (mean, 2.1) after therapy completion. Results: The post-therapy PET scan did not show any abnormal FDG uptake (complete metabolic response) in 44 patients. Persistent abnormal FDG uptake (partial metabolic response) was found in the anal tumor in 9 patients. The 2-year cause-specific survival rate was 94% for patients with a complete vs. 39% for patients with a partial metabolic response in the anal tumor (p = 0.0008). The 2-year progression-free survival rate was 95% for patients with a complete vs. 22% for patients with a partial metabolic response in the anal tumor (p < 0.0001). A Cox proportional hazards model of survival outcome indicated that a complete metabolic response was the most significant predictor of progression-free survival in our patient population (p = 0.0003). Conclusions: A partial metabolic response in the anal tumor as determined by post-therapy FDG-PET is predictive of significantly decreased progression-free and cause-specific survival after chemoradiotherapy for anal cancer.

  5. Key Comorbid Conditions that Are Predictive of Survival among Hemodialysis Patients

    PubMed Central

    Bragg-Gresham, Jennifer; Gillespie, Brenda W.; Tentori, Francesca; Pisoni, Ronald L.; Tighiouart, Hocine; Levey, Andrew S.; Port, Friedrich K.

    2009-01-01

    Background and objectives: Abstracting information about comorbid illnesses from the medical record can be time-consuming, particularly when a large number of conditions are under consideration. We sought to determine which conditions are most prognostic and whether comorbidity continues to contribute to a survival model once laboratory and clinical parameters have been accounted for. Design, setting, participants, & measurements: Comorbidity data were abstracted from the medical records of Dialysis Outcomes and Practice Pattern Study (DOPPS) I, II, and III participants using a standardized questionnaire. Models that were composed of different combinations of comorbid conditions and case-mix factors were compared for explained variance (R2) and discrimination (c statistic). Results: Seventeen comorbid conditions account for 96% of the total explained variance that would result if 45 comorbidities that were expected to be predictive of survival were added to a demographics-adjusted survival model. These conditions together had more discriminatory power (c statistic 0.67) than age alone (0.63) or serum albumin (0.60) and were equivalent to a combination of routine laboratory and clinical parameters (0.67). The strength of association of the individual comorbidities lessened when laboratory/clinical parameters were added, but all remained significant. The total R2 of a model adjusted for demographics and laboratory/clinical parameters increased from 0.13 to 0.17 upon addition of comorbidity. Conclusions: A relatively small list of comorbid conditions provides equivalent discrimination and explained variance for survival as a more extensive characterization of comorbidity. Comorbidity adds to the survival model a modest amount of independent prognostic information that cannot be substituted by clinical/laboratory parameters. PMID:19808231

  6. Low platelet counts after liver transplantation predict early posttransplant survival: the 60-5 criterion.

    PubMed

    Lesurtel, Mickaël; Raptis, Dimitri A; Melloul, Emmanuel; Schlegel, Andrea; Oberkofler, Christian; El-Badry, Ashraf Mohammad; Weber, Annina; Mueller, Nicolas; Dutkowski, Philipp; Clavien, Pierre-Alain

    2014-02-01

    Platelets play a critical role in liver injury and regeneration. Thrombocytopenia is associated with increases in postoperative complications after partial hepatectomy, but it is unknown whether platelet counts could also predict outcomes after transplantation, a procedure that is often performed in thrombocytopenic patients. Therefore, the aim of this study was to evaluate whether platelet counts could be indicators of short- and long-term outcomes after liver transplantation (LT). Two hundred fifty-seven consecutive LT recipients (January 2003-December 2011) from our prospective database were analyzed. Preoperative and daily postoperative platelet counts were recorded until postoperative day 7 (POD7). Univariate and multivariate analyses were performed to assess whether low perioperative platelet counts were a risk factor for postoperative complications and graft and patient survival. The median pretransplant platelet count was 88 × 10(9) /L [interquartile range (IQR) = 58-127 × 10(9) /L]. The lowest platelet counts occurred on POD3: the median was 56 × 10(9) /L (IQR = 41-86 × 10(9) /L). Patients with low platelet counts on POD5 had higher rates of severe (grade IIIb/IV) complications [39% versus 29%, odds ratio (OR) = 1.09 (95% CI = 1.1-3.3), P = 0.02] and 90-day mortality [16% versus 8%, OR = 2.25 (95% CI = 1.0-5.0), P = 0.05]. In the multivariate analysis, POD5 platelet counts < 60 × 10(9) /L were identified as an independent risk factor for grade IIIb/IV complications [OR = 1.96 (95% CI = 1.07-3.56), P = 0.03)], graft survival [hazard ratio (HR) = 2.0 (95% CI = 1.1-3.6), P = 0.03)], and patient survival [HR = 2.2 (95% CI = 1.1-4.6), P = 0.03)]. The predictive value of platelet counts for graft and patient survival was lost in patients who survived 90 days. In conclusion, after LT, platelet counts < 60 × 10(9) /L on POD5 (the 60-5 criterion) are an independent factor associated

  7. MRD parameters using immunophenotypic detection methods are highly reliable in predicting survival in acute myeloid leukaemia.

    PubMed

    Feller, N; van der Pol, M A; van Stijn, A; Weijers, G W D; Westra, A H; Evertse, B W; Ossenkoppele, G J; Schuurhuis, G J

    2004-08-01

    Outgrowth of minimal residual disease (MRD) in acute myeloid leukaemia (AML) is responsible for the occurrence of relapses. MRD can be quantified by immunophenotyping on a flow cytometer using the expression of leukaemia-associated phenotypes. MRD was monitored in follow-up samples taken from bone marrow (BM) of 72 patients after three different cycles of chemotherapy and from autologous peripheral blood stem cell (PBSC) products. The MRD% in BM after the first cycle (n=51), second cycle (n=52) and third cycle (n=30), as well as in PBSC products (n=39) strongly correlated with relapse-free survival. At a cutoff level of 1% after the first cycle and median cutoff levels of 0.14% after the second, 0.11% after the third cycle and 0.13% for PBSC products, the relative risk of relapse was a factor 6.1, 3.4, 7.2 and 5.7, respectively, higher for patients in the high MRD group. Also, absolute MRD cell number/ml was highly predictive of the clinical outcome. After the treatment has ended, an increase of MRD% predicted forthcoming relapses, with MRD assessment intervals of < or =3 months. In conclusion, MRD parameter assessment at different stages of disease is highly reliable in predicting survival and forthcoming relapses in AML.

  8. Survival prediction in patients undergoing radionuclide therapy based on intratumoral somatostatin-receptor heterogeneity

    PubMed Central

    Ilhan, Harun; Higuchi, Takahiro; Buck, Andreas K.; Lehner, Sebastian; Bartenstein, Peter; Bengel, Frank; Schatka, Imke; Muegge, Dirk O.; Papp, László; Zsótér, Norbert; Große-Ophoff, Tobias; Essler, Markus; Bundschuh, Ralph A.

    2017-01-01

    The NETTER-1 trial demonstrated significantly improved progression-free survival (PFS) for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET) emphasizing the high demand for response prediction in appropriate candidates. In this multicenter study, we aimed to elucidate the prognostic value of tumor heterogeneity as assessed by somatostatin receptor (SSTR)-PET/CT. 141 patients with SSTR-expressing tumors were analyzed obtaining SSTR-PET/CT before PRRT (1-6 cycles, 177Lu somatostatin analog). Using the Interview Fusion Workstation (Mediso), a total of 872 metastases were manually segmented. Conventional PET parameters as well as textural features representing intratumoral heterogeneity were computed. The prognostic ability for PFS and overall survival (OS) were examined. After performing Cox regression, independent parameters were determined by ROC analysis to obtain cut-off values to be used for Kaplan-Meier analysis. Within follow-up (median, 43.1 months), 75 patients showed disease progression (median, 22.2 m) and 54 patients died (median, 27.6 m). Cox analysis identified 8 statistically independent heterogeneity parameters for time-to-progression and time-to-death. Among them, the textural feature Entropy predicted both PFS and OS. Conventional PET parameters failed in response prediction. Imaging-based heterogeneity assessment provides prognostic information in PRRT candidates and outperformed conventional PET parameters. Its implementation in clinical practice can pave the way for individualized patient management. PMID:27705948

  9. Single portal pressure measurement predicts survival in cirrhotic patients with recent bleeding

    PubMed Central

    Patch, D; Armonis, A; Sabin, C; Christopoulou, K; Greenslade, L; McCormick, A; Dick, R; Burroughs, A

    1999-01-01

    Background—Height of portal pressure correlates with severity of alcoholic cirrhosis. Portal pressure indices are not however used routinely as predictors of survival. 
Aims—To examine the clinical value of a single portal pressure measurement in predicting outcome in cirrhotic patients who have bled. 
Methods—A series of 105 cirrhotic patients who consecutively underwent hepatic venous pressure measurement were investigated. The main cause of cirrhosis was alcoholic (64.8%) and prior to admission all patients had bled from varices. 
Results—During the follow up period (median 566 days, range 10-2555), 33 patients died, and 54 developed variceal haemorrhage. Applying Cox regression analysis, hepatic venous pressure gradient, bilirubin, prothrombin time, ascites, and previous long term endoscopic treatment were the only statistically independent predictors of survival, irrespective of cirrhotic aetiology. The predictive value of the pressure gradient was much higher if the measurement was taken within the first or the second week from the bleeding and there was no association after 15 days. A hepatic venous pressure gradient of at least 16 mm Hg appeared to identify patients with a greatly increased risk of dying. 
Conclusions—Indirectly measured portal pressure is an independent predictor of survival in patients with both alcoholic and non-alcoholic cirrhosis. In patients with a previous variceal bleeding episode this predictive value seems to be better if the measurement is taken within the first two weeks from the bleeding episode. A greater use of this technique is recommended for the prognostic assessment and management of patients with chronic liver disease. 

 Keywords: chronic liver disease; alcoholic cirrhosis; portal pressure PMID:9895388

  10. Review and evaluation of performance measures for survival prediction models in external validation settings.

    PubMed

    Rahman, M Shafiqur; Ambler, Gareth; Choodari-Oskooei, Babak; Omar, Rumana Z

    2017-04-18

    When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell's concordance measure which tended to increase as censoring increased. We recommend that Uno's concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller's measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston's D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive accuracy curves. In addition, we recommend to investigate the characteristics

  11. Predictive factors for survival and score application in liver retransplantation for hepatitis C recurrence.

    PubMed

    Song, Alice Tung Wan; Sobesky, Rodolphe; Vinaixa, Carmen; Dumortier, Jérôme; Radenne, Sylvie; Durand, François; Calmus, Yvon; Rousseau, Géraldine; Latournerie, Marianne; Feray, Cyrille; Delvart, Valérie; Roche, Bruno; Haim-Boukobza, Stéphanie; Roque-Afonso, Anne-Marie; Castaing, Denis; Abdala, Edson; D'Albuquerque, Luiz Augusto Carneiro; Duclos-Vallée, Jean-Charles; Berenguer, Marina; Samuel, Didier

    2016-05-14

    To identify risk factors associated with survival in patients retransplanted for hepatitis C virus (HCV) recurrence and to apply a survival score to this population. We retrospectively identified 108 patients retransplanted for HCV recurrence in eight European liver transplantation centers (seven in France, one in Spain). Data collection comprised clinical and laboratory variables, including virological and antiviral treatment data. We then analyzed the factors associated with survival in this population. A recently published score that predicts survival in retransplantation in patients with hepatitis C was applied. Because there are currently no uniform recommendations regarding selection of the best candidates for retransplantation in this setting, we also described the clinical characteristics of 164 patients not retransplanted, with F3, F4, or fibrosing cholestatic hepatitis (FCH) post-first graft presenting with hepatic decompensation. Overall retransplantation patient survival rates were 55%, 47%, and 43% at 3, 5, and 10 years, respectively. Patients who were retransplanted for advanced cirrhosis had survival rates of 59%, 52%, and 49% at 3, 5, and 10 years, while those retransplanted for FCH had survival rates of 34%, 29%, and 11%, respectively. Under multivariate analysis, and adjusting for the center effect and the occurrence of FCH, factors associated with better survival after retransplantation were: negative HCV viremia before retransplantation, antiviral therapy after retransplantation, non-genotype 1, a Model for End-stage Liver Disease (MELD) score < 25 when replaced on the waiting list, and a retransplantation donor age < 60 years. Although the numbers were small, in the context of the new antivirals era, we showed that outcomes in patients who underwent retransplantation with undetectable HCV viremia did not depend on donor age and MELD score. The Andrés score was applied to 102 patients for whom all score variables were available, producing a

  12. The MITOS system predicts long-term survival in amyotrophic lateral sclerosis.

    PubMed

    Tramacere, Irene; Dalla Bella, Eleonora; Chiò, Adriano; Mora, Gabriele; Filippini, Graziella; Lauria, Giuseppe

    2015-11-01

    The choice of adequate proxy for long-term survival, the ultimate outcome in randomised clinical trials (RCT) assessing disease-modifying treatments for amyotrophic lateral sclerosis (ALS), is a key issue. The intrinsic limitations of the ALS Functional Rating Scale-Revised (ALSFRS-R), including non-linearity, multidimensionality and floor-effect, have emerged and its usefulness argued. The ALS Milano-Torino staging (ALS-MITOS) system was proposed as a novel tool to measure the progression of ALS and overcome these limitations. This study was performed to validate the ALS-MITOS as a 6-month proxy of survival in 200 ALS patients followed up to 18 months. Analyses were performed on data from the recombinant human erythropoietin RCT that failed to demonstrate differences between groups for both primary and secondary outcomes. The ALS-MITOS system is composed of four key domains included in the ALSFRS-R scale (walking/self-care, swallowing, communicating and breathing), each with a threshold reflecting the loss of function in the specific ALSFRS-R subscores. Sensitivity, specificity and the area under the curve of the receiver operating characteristic curves of the ALS-MITOS system stages and ALSFRS-R decline at 6 months were calculated and compared with the primary outcome (survival, tracheotomy or >23-hour non-invasive ventilation) at 12 and 18 months Predicted probabilities of the ALS-MITO system at 6 months for any event at 12 and 18 months were computed through logistic regression models. Disease progression from baseline to 6 months as defined by the ALS-MITOS system predicted death, tracheotomy or >23-hour non-invasive ventilation at 12 months with 82% sensitivity (95% CI 71% to 93%, n=37/45) and 63% specificity (95% CI 55% to 71%, n=92/146), and at 18 months with 71% sensitivity (95% CI 61% to 82%, n=50/70) and 68% specificity (95% CI 60% to 77%, n=76/111). The analysis of ALS-MITOS and ALSFRS-R progression at 6-month follow-up showed that the best cut-off to

  13. Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

    PubMed

    Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

    2017-10-01

    Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (P<.001). Learning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe

  14. Survival prediction models for estimating the benefit of post-operative radiation therapy for gallbladder cancer and lung cancer.

    PubMed

    Kalpathy-Cramer, Jayashree; Hersh, William; Kim, Jong Song; Thomas, Charles R; Wang, Samuel J

    2008-11-06

    The role of post-operative radiotherapy (PORT) is still controversial for some cancer sites. In the absence of large randomized controlled trials, survival prediction models can help estimate the predicted benefit of PORT for specific settings. The purpose of this study was to compare the performance of two types of prediction models for estimating the benefit of PORT for 2 cancer sites. Using data from the Surveillance, Epidemiology, and End Results database, we constructed prediction models for gallbladder (GB) cancer and non-small cell lung cancer (NSMLC), using Cox proportional hazards and Random Survival Forests. We compared validation measures for discrimination and found that both the CPH and RSF models had comparable C-indices. For GB cancer, PORT was associated with improved survival for node positive patients, and for NSCLC, PORT was associated with a survival benefit for patients with N2 disease.

  15. FDG-PET predicts survival in recurrent high-grade gliomas treated with bevacizumab and irinotecan

    PubMed Central

    Colavolpe, Cécile; Chinot, Olivier; Metellus, Philippe; Mancini, Julien; Barrie, Maryline; Bequet-Boucard, Céline; Tabouret, Emeline; Mundler, Olivier; Figarella-Branger, Dominique; Guedj, Eric

    2012-01-01

    Prognosis of recurrent high-grade glioma (HGG) is poor, although bevacizumab has been documented in that context. This study aimed to determine the independent prognostic value of fluorodeoxyglucose (FDG)-PET on progression-free survival (PFS) and overall survival (OS) of recurrent HGG after combined treatment with bevacizumab and irinotecan, compared with other documented prognostic variables. Twenty-five adult patients with histologically proven HGG were included at recurrence. Brain FDG-PET imaging was performed within 6 weeks of starting chemotherapy with bevacizumab and irinotecan. Response based on MRI was assessed every 2 months according to revised assessment in Neuro-Oncology (RANO) criteria. Median PFS and OS were 4 months (range, 0.9–10.4 months) and 7.2 months (range, 1.2–41.7 months), respectively. At 6 months, PFS and OS rate were 16.0% and 72.0%. FDG uptake was the most powerful predictor of both PFS and OS, using either univariate or multivariate analysis, among all variables tested: histological grade, Karnofsky performance status, steroid intake, and number of previous treatments. Moreover, FDG uptake was also prognostic of response to bevacizumab-based therapy. This study provides the first evidence that pretreatment FDG-PET can serve as an imaging biomarker in recurrent HGG for predicting survival following anti-angiogenic therapy with bevacizumab. PMID:22379188

  16. Serum MicroRNA-122 Predicts Survival in Patients with Liver Cirrhosis

    PubMed Central

    Waidmann, Oliver; Köberle, Verena; Brunner, Friederike; Zeuzem, Stefan

    2012-01-01

    Background Liver cirrhosis is associated with high morbidity and mortality. MicroRNAs (miRs) circulating in the blood are an emerging new class of biomarkers. In particular, the serum level of the liver-specific miR-122 might be a clinically useful new parameter in patients with acute or chronic liver disease. Aim Here we investigated if the serum level of miR-122 might be a prognostic parameter in patients with liver cirrhosis. Methods 107 patients with liver cirrhosis in the test cohort and 143 patients in the validation cohort were prospectively enrolled into the present study. RNA was extracted from the sera obtained at the time of study enrollment and the level of miR-122 was assessed. Serum miR-122 levels were assessed by quantitative reverse-transcription PCR (RT-PCR) and were compared to overall survival time and to different complications of liver cirrhosis. Results Serum miR-122 levels were reduced in patients with hepatic decompensation in comparison to patients with compensated liver disease. Patients with ascites, spontaneous bacterial peritonitis and hepatorenal syndrome had significantly lower miR-122 levels than patients without these complications. Multivariate Cox regression analysis revealed that the miR-122 serum levels were associated with survival independently from the MELD score, sex and age. Conclusions Serum miR-122 is a new independent marker for prediction of survival of patients with liver cirrhosis. PMID:23029162

  17. Early toxicity predicts long-term survival in high-grade glioma

    PubMed Central

    Lawrence, Y R; Wang, M; Dicker, A P; Andrews, D; Curran, W J; Michalski, J M; Souhami, L; Yung, W-Ka; Mehta, M

    2011-01-01

    Background: Patients with high-grade gliomas are treated with surgery followed by chemoradiation. The risk factors and implications of neurological side effects are not known. Methods: Acute and late ⩾ grade 3 neurological toxicities (NTs) were analysed among 2761 patients from 14 RTOG trials accrued from 1983 to 2003. The association between acute and late toxicity was analysed using a stepwise logistic regression model. The association between the occurrence of acute NT and survival was analysed as an independent variable. Results: There were 2610 analysable patients (86% glioblastoma, 10% anaplastic astrocytoma). All received a systemic agent during radiation (83% chemotherapy, 17% biological agents). Median radiation dose was 60 Gy. There were 182 acute and 83 late NT events. On univariate analysis, older age, poor performance status, aggressive surgery, pre-existing neurological dysfunction, poor mental status and twice-daily radiation were associated with increased acute NT. In a stepwise logistic regression model the occurrence of acute NT was significantly associated with late NT (OR=2.40; 95% CI=1.2–4.8; P=0.014). The occurrence of acute NT predicted poorer overall survival, independent of recursive partitioning analysis class (median 7.8 vs 11.8 months). Interpretation: Acute NT is significantly associated with both late NT and overall survival. PMID:21487410

  18. Postchemoradiotherapy Positron Emission Tomography Predicts Pathologic Response and Survival in Patients With Esophageal Cancer

    SciTech Connect

    Jayachandran, Priya; Pai, Reetesh K.; Quon, Andrew; Graves, Edward; Krakow, Trevor E.; La, Trang; Loo, Billy W.; Koong, Albert C.; Chang, Daniel T.

    2012-10-01

    Purpose: To correlate the prechemoradiotherapy (CRT) and post-CRT metabolic tumor volume (MTV) on positron emission tomography (PET) scanning with the pathologic response and survival in patients receiving preoperative CRT for esophageal cancer. Materials and Methods: The medical records of 37 patients with histologically confirmed Stage I-IVA esophageal cancer treated with CRT with or without surgical resection were reviewed. Of the 37 patients, 21 received preoperative CRT (57%) and 16 received definitive CRT (43%). All patients had a pre-CRT and 32 had a post-CRT PET scan. The MTV was measured on the pre-CRT PET and post-CRT PET scan, respectively, using a minimum standardized uptake value (SUV) threshold x, where x = 2, 2.5, 3, or the SUV maximum Multiplication-Sign 50%. The total glycolytic activity (TGA{sub x}) was defined as the mean SUV Multiplication-Sign MTV{sub x}. The MTV ratio was defined as the pre-CRT PET MTV/post-CRT MTV. The SUV ratio was defined similarly. A single pathologist scored the pathologic response using a tumor regression grade (TRG) scale. Results: The median follow-up was 1.5 years (range, 0.4-4.9). No significant correlation was found between any parameters on the pre-CRT PET scan and the TRG or overall survival (OS). Multiple post-CRT MTV values and post-TGA values correlated with the TRG and OS; however, the MTV{sub 2.5Post} and TGA{sub 2.5Post} had the greatest correlation. The MTV{sub 2} ratio correlated with OS. The maximum SUV on either the pre-CRT and post-CRT PET scans or the maximum SUV ratio did not correlate with the TRG or OS. Patients treated preoperatively had survival similar compared with those treated definitively with a good PET response (p = 0.97) and significantly better than that of patients treated definitively with a poor PET response (p < 0.0001). Conclusion: The maximum SUV was not a predictive or prognostic parameter. The MTV{sub 2.5} and TGA{sub 2.5} were useful markers for predicting the response and

  19. The PROPKD Score: A New Algorithm to Predict Renal Survival in Autosomal Dominant Polycystic Kidney Disease

    PubMed Central

    Cornec-Le Gall, Emilie; Audrézet, Marie-Pierre; Rousseau, Annick; Hourmant, Maryvonne; Renaudineau, Eric; Charasse, Christophe; Morin, Marie-Pascale; Moal, Marie-Christine; Dantal, Jacques; Wehbe, Bassem; Perrichot, Régine; Frouget, Thierry; Vigneau, Cécile; Potier, Jérôme; Jousset, Philippe; Guillodo, Marie-Paule; Siohan, Pascale; Terki, Nazim; Sawadogo, Théophile; Legrand, Didier; Menoyo-Calonge, Victorio; Benarbia, Seddik; Besnier, Dominique; Longuet, Hélène; Férec, Claude

    2016-01-01

    The course of autosomal dominant polycystic kidney disease (ADPKD) varies among individuals, with some reaching ESRD before 40 years of age and others never requiring RRT. In this study, we developed a prognostic model to predict renal outcomes in patients with ADPKD on the basis of genetic and clinical data. We conducted a cross-sectional study of 1341 patients from the Genkyst cohort and evaluated the influence of clinical and genetic factors on renal survival. Multivariate survival analysis identified four variables that were significantly associated with age at ESRD onset, and a scoring system from 0 to 9 was developed as follows: being male: 1 point; hypertension before 35 years of age: 2 points; first urologic event before 35 years of age: 2 points; PKD2 mutation: 0 points; nontruncating PKD1 mutation: 2 points; and truncating PKD1 mutation: 4 points. Three risk categories were subsequently defined as low risk (0–3 points), intermediate risk (4–6 points), and high risk (7–9 points) of progression to ESRD, with corresponding median ages for ESRD onset of 70.6, 56.9, and 49 years, respectively. Whereas a score ≤3 eliminates evolution to ESRD before 60 years of age with a negative predictive value of 81.4%, a score >6 forecasts ESRD onset before 60 years of age with a positive predictive value of 90.9%. This new prognostic score accurately predicts renal outcomes in patients with ADPKD and may enable the personalization of therapeutic management of ADPKD. PMID:26150605

  20. Apoptosis in cervical squamous carcinoma: predictive value for survival following radiotherapy

    PubMed Central

    Paxton, J; Bolger, B; Armour, A; Symonds, R; Mao, J; Burnett, R

    2000-01-01

    Background—Apoptosis, or programmed cell death, can be induced by radiotherapy. The extent of apoptosis in a tumour before treatment may have important implications for response to radiotherapy and long term survival. Aim—To examine the extent of apoptosis in tumour tissue from patients with squamous carcinoma of the cervix before radiotherapy, and to correlate this with response to treatment and prognosis. Methods—The percentage of apoptotic cells was assessed in 146 carcinomas of the cervix from patients scheduled to receive radiotherapy. The CAS 200 static image analysis system was used to count the number of tumour nuclei per high power field, while the numbers of apoptotic cells in the same field were visualised simultaneously on the image analyser and recorded manually. Results—The median apoptotic level was 0.73%. Patients were divided into two groups around the median. There was no statistically significant difference in outcome between the two groups as determined by long term survival following radiotherapy. Conclusions—The CAS 200 static image analyser system can be used to assist in the rapid semiautomated assessment of apoptosis in conventionally prepared tissue. The results suggest that the apoptotic state of a tumour before treatment is of no value in predicting response to radiotherapy and subsequent prognosis. Tumour stage, size, and BrdU labelling index, as a measure of proliferation rate, remain the most important prognostic factors in terms of predicting local tumour control. Key Words: apoptosis • uterine cervix • squamous cell carcinoma PMID:10823138

  1. The use of the Oxford classification of IgA nephropathy to predict renal survival.

    PubMed

    Alamartine, Eric; Sauron, Catherine; Laurent, Blandine; Sury, Aurore; Seffert, Aline; Mariat, Christophe

    2011-10-01

    A new classification for IgA nephropathy was recently proposed, namely the Oxford classification. It established specific pathologic features that predict the risk of progression of renal disease. This classification needs validation in different patient populations. We propose a retrospective study to evaluate the predictive value of the Oxford classification on renal survival defined by doubling creatinine or end-stage renal disease in patients with IgA nephropathy. We included 183 patients with primary IgA nephropathy diagnosed between 1994 and 2005. Mean follow-up time was 77 months. Doubling creatinine occurred in 20% of the patients, and end-stage renal disease occurred in 16%. The biopsies were revisited to apply the Oxford classification. The influence of pathologic features on renal survival was analyzed in univariate and multivariate models. In univariate time-dependent analyses, tubular atrophy/interstitial fibrosis, segmental glomerulosclerosis, and endocapillary hypercellularity strongly impacted doubling creatinine or end-stage renal disease. On the contrary, mesangial hypercellularity was not associated with renal outcome. In the multivariate model, only estimated GFR at baseline was a risk factor, pathologic lesions having no independent influence. We confirm the usefulness of the Oxford classification to establish the renal prognosis of patients with IgA nephropathy, although renal function at baseline seems to be of a greater importance than pathologic lesions.

  2. Do Conflict Resolution and Recovery Predict the Survival of Adolescents' Romantic Relationships?

    PubMed Central

    Ha, Thao; Overbeek, Geertjan; Lichtwarck-Aschoff, Anna; Engels, Rutger C. M. E.

    2013-01-01

    Numerous studies have shown that being able to resolve and recover from conflicts is of key importance for relationship satisfaction and stability in adults. Less is known about the importance of these relationship dynamics in adolescent romantic relationships. Therefore, this study investigated whether conflict resolution and recovery predict breakups in middle adolescent couples. Couples who are able to resolve and recover from conflict were expected to demonstrate a lower probability of breaking up. In total, 80 adolescent couples (M age = 15.48, SD = 1.16) participated in a 4-wave prospective questionnaire and observational study, with one year between measurements. In addition to self-report measures, adolescents were observed in real-time during conflicts with their partners. Multilevel Proportional Hazard analyses revealed that, contrary to the hypothesis, conflict resolution and conflict recovery did not predict the likelihood of breakup. Survival differences were not attributable to conflict resolution or conflict recovery. More research is needed to consider the unique relationship factors of adolescent romantic relationships to determine why some relationships survive while others do not. PMID:23613960

  3. Biomarkers Predicting Survival of Sepsis Patients Treated with Continuous Renal Replacement Therapy

    PubMed Central

    Lee, Jeong Ho; Kim, Ha Yeon; Bae, Eun Hui; Kim, Soo Wan

    2017-01-01

    The present study investigated the prognostic factors predicting survival of patients with sepsis and acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT). This retrospective observational study included 165 sepsis patients treated with CRRT. The patients were divided into two groups; the survivor group (n=73, 44.2%) vs. the nonsurvivor group (n=92, 55.8%). AKI was defined by the 2012 Kidney Disease: Improving Global Outcomes Clinical Practice Guidelines. We analyzed medical histories, clinical characteristics and laboratory findings of the enrolled patients when they started CRRT. In addition, we performed binary logistic regression and cox regression analysis. In the survivor group, urine output during the first day was significantly higher compared with the nonsurvivor group (55.7±66.3 vs. 26.6±46.4, p=0.001). Patients with urine output <30 mL/hour during the 1st day showed worse outcomes than ≥30 mL/hour in the logistic regression (hazard ratio 2.464, 95% confidence interval 1.152-5.271, p=0.020) and the cox regression analysis (hazard ratio 1.935, 95% confidence interval 1.147-3.263, p=0.013). In conclusion, urine output may predict survival of septic AKI patients undergoing CRRT. In these patients, urine output <30 mL/hour during the first day was the strongest risk factor for in-hospital mortality. PMID:28184340

  4. Overexpression of Rho GDP-dissociation inhibitor alpha predicts poor survival in oral squamous cell carcinoma.

    PubMed

    Chiang, Wei-Fan; Ho, Hsu-Chueh; Chang, Hua-Yuan; Chiu, Chien-Chih; Chen, Yuh-Ling; Hour, Tzyh-Chyuan; Chuang, Shu-Ju; Wu, Yu-Jen; Chen, Hau-Ren; Chen, Jen-Hao; Liu, Shyun-Yeu; Lu, Chin-Li; Chen, Jeff Yi-Fu

    2011-06-01

    Oral cancer has emerged as one of the fastest growing malignancies in Taiwan. However, biomarkers that reliably predict clinical outcomes have yet to be identified. This study was aimed to identify tumor-associated proteins that could be prognostic biomarkers for oral cancer. We compared the protein expression between oral squamous cell carcinoma (OSCC) tissues and adjacent non-cancerous matched tissues (NCMTs) by proteomics. We found that Rho GDP-dissociation inhibitor alpha (RhoGDIα) was differentially expressed in frozen cancerous samples and OSCC cell lines but not in NCMTs. Furthermore, our results indicated that RhoGDIα was selectively upregulated in 78 OSCC tissue sections (p<0.001), and this high expression was significantly correlated with increased tumor size (p<0.05) and poor overall survival (p<0.01). There was a trend that RhoGDIα expression was localized in the cytoplasm of cancer cells but was localized in the plasma membrane of NCMTs. Finally, expression of RhoGDIα was validated to be an independent prognostic indicator for overall survival (p<0.01). These results have identified a novel biomarker that may be useful for prediction of poor prognosis in OSCC patients.

  5. Molecular classification and survival prediction in human gliomas based on proteome analysis.

    PubMed

    Iwadate, Yasuo; Sakaida, Tsukasa; Hiwasa, Takaki; Nagai, Yuichiro; Ishikura, Hiroshi; Takiguchi, Masaki; Yamaura, Akira

    2004-04-01

    The biological features of gliomas, which are characterized by highly heterogeneous biological aggressiveness even in the same histological category, would be precisely described by global gene expression data at the protein level. We investigated whether proteome analysis based on two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry can identify differences in protein expression between high- and low-grade glioma tissues. Proteome profiling patterns were compared in 85 tissue samples: 52 glioblastoma multiforme, 13 anaplastic astrocytomas, 10 atrocytomas, and 10 normal brain tissues. We could completely distinguish the normal brain tissues from glioma tissues by cluster analysis based on the proteome profiling patterns. Proteome-based clustering significantly correlated with the patient survival, and we could identify a biologically distinct subset of astrocytomas with aggressive nature. Discriminant analysis extracted a set of 37 proteins differentially expressed based on histological grading. Among them, many of the proteins that were increased in high-grade gliomas were categorized as signal transduction proteins, including small G-proteins. Immunohistochemical analysis confirmed the expression of identified proteins in glioma tissues. The present study shows that proteome analysis is useful to develop a novel system for the prediction of biological aggressiveness of gliomas. The proteins identified here could be novel biomarkers for survival prediction and rational targets for antiglioma therapy.

  6. ras and p53 in the prediction of survival in Dukes' stage B colorectal carcinoma

    PubMed Central

    Bennett, M A; Kay, E W; Mulcahy, H; O'Flaherty, L; O'Donoghue, D P; Leader, M; Croke, D T

    1995-01-01

    Aims—To determine possible associations between p53 allelic deletion, c-Ki-ras mutational activation, immunohistochemical detection of p53 and ras proteins, various clinicopathological variables, and patient outcome in 168 Dukes' stage B colorectal carcinomas. Methods—Allelic deletion at the p53 tumour suppressor gene locus was detected using polymerase chain reaction (PCR) based loss of heterozygosity (LOH) assays. Overexpressed proteins were detected using the CM1 polyclonal antibody. A PCR based assay was used to detect the presence of activating mutations at codon 12 of c-Ki-ras. Immunostaining was carried out using a monoclonal antibody to p21ras. Results—p53 LOH, CM1 immunostaining, c-Ki-ras mutational activation, and p21ras immunostaining were not predictive of survival by logrank analysis. Multivariate analysis using Cox regression did not predict survival in this group of tumours. Conclusions—Aberrations in ras and p53 are unlikely to play an important role in the subdivision of patients with Dukes' stage B colorectal carcinoma into more accurate prognostic strata. It is possible that later genetic events are more important in conferring a specific phenotype on the resultant Dukes' stage B tumour. Images PMID:16696029

  7. Do conflict resolution and recovery predict the survival of adolescents' romantic relationships?

    PubMed

    Ha, Thao; Overbeek, Geertjan; Lichtwarck-Aschoff, Anna; Engels, Rutger C M E

    2013-01-01

    Numerous studies have shown that being able to resolve and recover from conflicts is of key importance for relationship satisfaction and stability in adults. Less is known about the importance of these relationship dynamics in adolescent romantic relationships. Therefore, this study investigated whether conflict resolution and recovery predict breakups in middle adolescent couples. Couples who are able to resolve and recover from conflict were expected to demonstrate a lower probability of breaking up. In total, 80 adolescent couples (M age = 15.48, SD = 1.16) participated in a 4-wave prospective questionnaire and observational study, with one year between measurements. In addition to self-report measures, adolescents were observed in real-time during conflicts with their partners. Multilevel Proportional Hazard analyses revealed that, contrary to the hypothesis, conflict resolution and conflict recovery did not predict the likelihood of breakup. Survival differences were not attributable to conflict resolution or conflict recovery. More research is needed to consider the unique relationship factors of adolescent romantic relationships to determine why some relationships survive while others do not.

  8. The Use of the Oxford Classification of IgA Nephropathy to Predict Renal Survival

    PubMed Central

    Sauron, Catherine; Laurent, Blandine; Sury, Aurore; Seffert, Aline; Mariat, Christophe

    2011-01-01

    Summary Background and objectives A new classification for IgA nephropathy was recently proposed, namely the Oxford classification. It established specific pathologic features that predict the risk of progression of renal disease. This classification needs validation in different patient populations. We propose a retrospective study to evaluate the predictive value of the Oxford classification on renal survival defined by doubling creatinine or end-stage renal disease in patients with IgA nephropathy. Design, setting, participants, & measurements We included 183 patients with primary IgA nephropathy diagnosed between 1994 and 2005. Mean follow-up time was 77 months. Doubling creatinine occurred in 20% of the patients, and end-stage renal disease occurred in 16%. The biopsies were revisited to apply the Oxford classification. The influence of pathologic features on renal survival was analyzed in univariate and multivariate models. Results In univariate time-dependent analyses, tubular atrophy/interstitial fibrosis, segmental glomerulosclerosis, and endocapillary hypercellularity strongly impacted doubling creatinine or end-stage renal disease. On the contrary, mesangial hypercellularity was not associated with renal outcome. In the multivariate model, only estimated GFR at baseline was a risk factor, pathologic lesions having no independent influence. Conclusions We confirm the usefulness of the Oxford classification to establish the renal prognosis of patients with IgA nephropathy, although renal function at baseline seems to be of a greater importance than pathologic lesions. PMID:21885791

  9. A MAP3k1 SNP Predicts Survival of Gastric Cancer in a Chinese Population

    PubMed Central

    Gu, Dongying; Shen, Lili; Wang, Meilin; Xu, Zhi; Gong, Weida; Tang, Cuiju; Gao, Jinglong; Chen, Jinfei; Zhang, Zhengdong

    2014-01-01

    Objectives Genome-wide association studies (GWAS) have demonstrated that the single nucleotide polymorphism (SNP) MAP3K1 rs889312 is a genetic susceptibility marker significantly associated with a risk of hormone-related tumors such as breast cancer. Considering steroid hormone-mediated signaling pathways have an important role in the progression of gastric cancer, we hypothesized that MAP3K1 rs889312 may be associated with survival outcomes in gastric cancer. The purpose of this study was to test this hypothesis. Methods We genotyped MAP3K1 rs889312 using TaqMan in 884 gastric cancer patients who received subtotal or total gastrectomy. Kaplan-Meier survival analysis and Cox proportional hazard regression were used to analyze the association between MAP3K1 rs889312 genotypes and survival outcomes of gastric cancer. Results Our findings reveal that the rs889312 heterozygous AC genotype was significantly associated with an increased rate of mortality among patients with diffuse-type gastric cancer (log-rank P = 0.028 for AC versus AA/CC, hazard ratio [HR] = 1.32, 95% confidence interval [CI] = 1.03–1.69), compared to those carrying the homozygous variant genotypes (AA/CC). Additionally, univariate and multivariate Cox regression analysis demonstrate that rs889312 polymorphism was an independent risk factor for poor survival in these patients. Conclusions In conclusion, we demonstrate that MAP3K1 rs889312 is closely correlated with outcome among diffuse-type gastric cancer. This raises the possibility for rs889312 polymorphisms to be used as an independent indicator for predicting the prognosis of diffuse-type gastric cancer within the Chinese population. PMID:24759887

  10. Clinical Score Predicting Long-Term Survival after Repeat Resection for Recurrent Adrenocortical Carcinoma

    PubMed Central

    Tran, Thuy B; Maithel, Shishir K; Pawlik, Timothy M; Wang, Tracy S; Hatzaras, Ioannis; Phay, John E; Fields, Ryan C; Weber, Sharon M; Sicklick, Jason K; Yopp, Adam C; Duh, Quan-Yang; Solorzano, Carmen C; Votanopoulos, Konstantinos I; Poultsides, George A

    2017-01-01

    BACKGROUND Adrenocortical carcinoma (ACC) is an aggressive malignancy typically resistant to chemotherapy and radiation. Surgery, even in the setting of locally recurrent or metastatic disease, remains the only potentially curative option. However, the subset of patients who will benefit from repeat resection in this setting remains ill defined. The objective of this study was to propose a prognostic clinical score that facilitates selection of patients for repeat resection of recurrent ACC. STUDY DESIGN Patients who underwent curative-intent repeat resection for recurrent ACC at 1 of 13 academic medical centers participating in the US ACC Study Group were identified. End points included morbidity, mortality, and overall survival. RESULTS Fifty-six patients underwent repeat curative-intent resection for recurrent ACC (representing 21% of 265 patients who underwent resection for primary ACC) from 1997 to 2014. Median age was 52 years. Sites of resected recurrence included locoregional only (54%), lung only (14%), liver only (12%), combined locoregional and lung (4%), combined liver and lung (4%), and other distant sites (12%). Thirty-day morbidity and mortality rates were 40% and 5.4%, respectively. Cox regression analysis revealed that the presence of multifocal recurrence, disease-free interval <12 months, and extrapulmonary distant metastases were independent predictors of poor survival. A clinical score consisting of 1-point each for the 3 variables demonstrated good discrimination in predicting survival after repeat resection (5-year: 72% for 0 points, 32% for 1 point, 0% for 2 or 3 points; p = 0.0006, area under the curve = 0.78). CONCLUSIONS Long-term survival after repeat resection for recurrent ACC is feasible when 2 of the following factors are present: solitary tumor, disease-free interval >12 months, and locoregional or pulmonary recurrence. PMID:27618748

  11. Prediction of the survival and functional ability of severe stroke patients after ICU therapeutic intervention

    PubMed Central

    Riachy, Moussa; Sfeir, Frida; Sleilaty, Ghassan; Hage-Chahine, Samer; Dabar, Georges; Bazerbachi, Taha; Aoun-Bacha, Zeina; Khayat, Georges; Koussa, Salam

    2008-01-01

    Background This study evaluated the benefits and impact of ICU therapeutic interventions on the survival and functional ability of severe cerebrovascular accident (CVA) patients. Methods Sixty-two ICU patients suffering from severe ischemic/haemorrhagic stroke were evaluated for CVA severity using APACHE II and the Glasgow coma scale (GCS). Survival was determined using Kaplan-Meier survival tables and survival prediction factors were determined by Cox multivariate analysis. Functional ability was assessed using the stroke impact scale (SIS-16) and Karnofsky score. Risk factors, life support techniques and neurosurgical interventions were recorded. One year post-CVA dependency was investigated using multivariate analysis based on linear regression. Results The study cohort constituted 6% of all CVA (37.8% haemorrhagic/62.2% ischemic) admissions. Patient mean(SD) age was 65.8(12.3) years with a 1:1 male: female ratio. During the study period 16 patients had died within the ICU and seven in the year following hospital release. The mean(SD) APACHE II score at hospital admission was 14.9(6.0) and ICU mean duration of stay was 11.2(15.4) days. Mechanical ventilation was required in 37.1% of cases. Risk ratios were; GCS at admission 0.8(0.14), (p = 0.024), APACHE II 1.11(0.11), (p = 0.05) and duration of mechanical ventilation 1.07(0.07), (p = 0.046). Linear coefficients were: type of CVA – haemorrhagic versus ischemic: -18.95(4.58) (p = 0.007), GCS at hospital admission: -6.83(1.08), (p = 0.001), and duration of hospital stay -0.38(0.14), (p = 0.40). Conclusion To ensure a better prognosis CVA patients require ICU therapeutic interventions. However, as we have shown, where tests can determine the worst affected patients with a poor vital and functional outcome should treatment be withheld? PMID:18582387

  12. Mutation spectrum of TP53 gene predicts clinicopathological features and survival of gastric cancer

    PubMed Central

    Tahara, Tomomitsu; Shibata, Tomoyuki; Okamoto, Yasuyuki; Yamazaki, Jumpei; Kawamura, Tomohiko; Horiguchi, Noriyuki; Okubo, Masaaki; Nakano, Naoko; Ishizuka, Takamitsu; Nagasaka, Mitsuo; Nakagawa, Yoshihito; Ohmiya, Naoki

    2016-01-01

    Background and aim TP53 gene is frequently mutated in gastric cancer (GC), but the relationship with clinicopathological features and prognosis is conflicting. Here, we screened TP53 mutation spectrum of 214 GC patients in relation to their clinicopathological features and prognosis. Results TP53 nonsilent mutations were detected in 80 cases (37.4%), being frequently occurred as C:G to T:A single nucleotide transitions at 5′-CpG-3′ sites. TP53 mutations occurred more frequently in differentiated histologic type than in undifferentiated type in the early stage (48.6% vs. 7%, P=0.0006), while the mutations correlated with venous invasion among advanced stage (47.7% vs. 20.7%, P=0.04). Subset of GC with TP53 hot spot mutations (R175, G245, R248, R273, R282) presented significantly worse overall survival and recurrence free survival compared to others (both P=0.001). Methods Matched biopsies from GC and adjacent tissues from 214 patients were used for the experiment. All coding regions of TP53 gene (exon2 to exon11) were examined using Sanger sequencing. Conclusion Our data suggest that GC with TP53 mutations seems to develop as differentiated histologic type and show aggressive biological behavior such as venous invasion. Moreover, our data emphasizes the importance of discriminating TP53 hot spot mutations (R175, G245, R248, R273, R282) to predict worse overall survival and recurrence free survival of GC patients. PMID:27323394

  13. Organism activity levels predict marine invertebrate survival during ancient global change extinctions.

    PubMed

    Clapham, Matthew E

    2017-04-01

    Multistressor global change, the combined influence of ocean warming, acidification, and deoxygenation, poses a serious threat to marine organisms. Experimental studies imply that organisms with higher levels of activity should be more resilient, but testing this prediction and understanding organism vulnerability at a global scale, over evolutionary timescales, and in natural ecosystems remain challenging. The fossil record, which contains multiple extinctions triggered by multistressor global change, is ideally suited for testing hypotheses at broad geographic, taxonomic, and temporal scales. Here, I assess the importance of activity level for survival of well-skeletonized benthic marine invertebrates over a 100-million-year-long interval (Permian to Jurassic periods) containing four global change extinctions, including the end-Permian and end-Triassic mass extinctions. More active organisms, based on a semiquantitative score incorporating feeding and motility, were significantly more likely to survive during three of the four extinction events (Guadalupian, end-Permian, and end-Triassic). In contrast, activity was not an important control on survival during nonextinction intervals. Both the end-Permian and end-Triassic mass extinctions also triggered abrupt shifts to increased dominance by more active organisms. Although mean activity gradually returned toward pre-extinction values, the net result was a permanent ratcheting of ecosystem-wide activity to higher levels. Selectivity patterns during ancient global change extinctions confirm the hypothesis that higher activity, a proxy for respiratory physiology, is a fundamental control on survival, although the roles of specific physiological traits (such as extracellular pCO2 or aerobic scope) cannot be distinguished. Modern marine ecosystems are dominated by more active organisms, in part because of selectivity ratcheting during these ancient extinctions, so on average may be less vulnerable to global change

  14. A nomogram for predicting survival of nasopharyngeal carcinoma patients with metachronous metastasis

    PubMed Central

    Zeng, Zixun; Shen, Lujun; Wang, Yue; Shi, Feng; Chen, Chen; Wu, Ming; Bai, Yutong; Pan, Changchuan; Xia, Yunfei; Wu, Peihong; Li, Wang

    2016-01-01

    Abstract Patients with metachronous metastatic nasopharyngeal carcinoma (NPC) differ significantly in survival outcomes. The aim of this study is to build a clinically practical nomogram incorporating known tumor prognostic factors to predict survival for metastatic NPC patients in epidemic areas. A total of 860 patients with metachronous metastatic nasopharyngeal carcinoma were analyzed retrospectively. Variables assessed were age, gender, body mass index, Karnofsky Performance Status (KPS), Union for International Cancer Control (UICC) T and N stages, World Health Organization (WHO) histology type, serum lactate dehydrogenase (sLDH) level, serum Epstein–Barr virus (EBV) level, treatment modality, specific metastatic location (lung/liver/bone), number of metastatic location(s) (isolated vs multiple), and number of metastatic lesion(s) in metastatic location(s) (single vs multiple). The independent prognostic factors for overall survival (OS) by Cox-regression model were utilized to build the nomogram. Independent prognostic factors for OS of metastatic NPC patients included age, UICC N stage, KPS, sLDH, number of metastatic locations, number of metastatic lesions, involvement of liver metastasis, and involvement of bone metastasis. Calibration of the final model suggested a c-index of 0.68 (95% confidence interval [CI], 0.65–0.69). Based on the total point (TP) by nomogram, we further subdivided the study cohort into 4 groups. Group 1 (TP < 320, 208 patients) had the lowest risk of dying. Discrimination was visualized by the differences in survival between these 4 groups (group 2/group 1: hazard ratio [HR] = 1.61, 95%CI: 1.24–2.09; group 3/group 1: HR = 2.20, 95%CI: 1.69–2.86; and group 4/group 1: HR = 3.66, 95%CI: 2.82–4.75). The developed nomogram can help guide the prognostication of patients with metachronous metastatic NPC in epidemic areas. PMID:27399084

  15. The Need for New Donor Stratification to Predict Graft Survival in Deceased Donor Kidney Transplantation.

    PubMed

    Yang, Shin Seok; Yang, Jaeseok; Ahn, Curie; Min, Sang Il; Ha, Jongwon; Kim, Sung Joo; Park, Jae Berm

    2017-05-01

    The aim of this study was to determine whether stratification of deceased donors by the United Network for Organ Sharing (UNOS) criteria negatively impacts graft survival. We retrospectively reviewed deceased donor and recipient pretransplant variables of kidney transplantations that occurred between February 1995 and December 2009. We compared clinical outcomes between standard criteria donors (SCDs) and expanded criteria donors (ECDs). The deceased donors consisted of 369 patients. A total of 494 transplant recipients were enrolled in this study. Mean age was 41.7±11.4 year (range 18-69) and 273 patients (55.4%) were male. Mean duration of follow-up was 8.8±4.9 years. The recipients from ECD kidneys were 63 patients (12.8%). The overall mean cold ischemia time was 5.7±3.2 hours. Estimated glomerular filtration rate at 1, 2, and 3 years after transplantation were significantly lower in ECD transplants (1 year, 62.2±17.6 vs. 51.0±16.4, p<0.001; 2 year, 62.2±17.6 vs. 51.0±16.4, p=0.001; 3 year, 60.9±23.5 vs. 54.1±18.7, p=0.047). In multivariate analysis, donor age (≥40 years) was an independent risk factor for graft failure. In Kaplan-Meier analyses, there was no significant difference in death-censored graft survival (Log rank test, p>0.05), although patient survival was lower in ECDs than SCDs (Log rank test, p=0.011). Our data demonstrate that stratification by the UNOS criteria does not predict graft survival. In order to expand the donor pool, new criteria for standard/expanded donors need to be modified by regional differences.

  16. Systemic Inflammatory Response and Elevated Tumour Markers Predict Worse Survival in Resectable Pancreatic Ductal Adenocarcinoma

    PubMed Central

    Salmiheimo, Aino; Mustonen, Harri; Stenman, Ulf-Håkan; Puolakkainen, Pauli; Kemppainen, Esko; Seppänen, Hanna; Haglund, Caj

    2016-01-01

    Background Estimation of the prognosis of resectable pancreatic ductal adenocarcinoma (PDAC) currently relies on tumour-related factors such as resection margins and on lymph-node ratio (LNR) both inconveniently available only postoperatively. Our aim was to assess the accuracy of preoperative laboratory data in predicting PDAC prognosis. Methods Collection of laboratory and clinical data was retrospective from 265 consecutive patients undergoing surgery for PDAC at Helsinki University Hospital. Cancer-specific survival assessment utilized Kaplan-Meier analysis, and independent associations between factors were by the Cox regression model. Results During follow-up, 76% of the patients died of PDAC, with a median survival time of 19.6 months. In univariate analysis, CRP, albumin, CEA, and CA19-9 were significantly associated with postoperative cancer-specific survival. In multivariate analysis, taking into account age, gender, LNR, resection margins, tumour status, and adjuvant chemotherapy, the preoperative biomarkers independently associated with adverse prognosis were hypoalbuminemia (< 36 g/L, hazard ratio (HR) 1.56, 95% confidence interval (CI) 1.10–2.19, p = 0.011), elevated CRP (> 5 mg/L, HR 1.44, 95% CI 1.03–2.02, p = 0.036), CEA (> 5 μg/L, HR 1.60, 95% CI 1.07–2.53, p = 0.047), and CA19-9 (≥555 kU/L, HR 1.91, 95% CI 1.18–3.08, p = 0.008). Conclusion For patients with resectable PDAC, preoperative CRP, along with albumin and tumour markers, is useful for predicting prognosis. PMID:27632196

  17. Factors predicting survival in chronic lymphocytic leukemia patients developing Richter syndrome transformation into Hodgkin lymphoma.

    PubMed

    Mauro, Francesca Romana; Galieni, Piero; Tedeschi, Alessandra; Laurenti, Luca; Del Poeta, Giovanni; Reda, Gianluigi; Motta, Marina; Gozzetti, Alessandro; Murru, Roberta; Caputo, Maria Denise; Campanelli, Melissa; Frustaci, Anna Maria; Innocenti, Idanna; Raponi, Sara; Guarini, Anna; Morabito, Fortunato; Foà, Robin; Gentile, Massimo

    2017-03-10

    We hereby report the clinical and biologic features of 33 of 4680 (0.7%) patients with chronic lymphocytic leukemia (CLL), managed at 10 Italian centers, who developed Hodgkin lymphoma (HL), a rare variant of Richter syndrome. The median age at CLL and at HL diagnosis were 61 years (range 41-80) and 70 years (range 46-82), respectively, with a median interval from CLL to the diagnosis of HL of 90 months (range 0-258). In 3 cases, CLL and HL were diagnosed simultaneously. Hl was characterized by advanced stage in 79% of cases, International Prognostic Score (IPS) ≥4 in 50%, extranodal involvement in 39%, B symptoms in 70%. Prior treatment for CLL had been received by 82% of patients and included fludarabine in 67%. Coexistence of CLL and HL was detected in the same bioptic tissue in 87% of cases. The most common administered treatment was the ABVD regimen given to 22 patients (66.6%). The complete response (CR) rate after ABVD was 68%, and was influenced by the IPS (p=.03) and interval from the last CLL treatment (p=.057). Survival from HL was also influenced by the IPS (p=.006) and time from the last CLL treatment (p=.047). The achievement of CR with ABVD was the only significant and independent factor predicting survival (p=.037). Taken together, our results show that the IPS and the interval from the prior CLL treatment influence the likelihood of achieving CR after ABVD, which is the most important factor predicting survival of patients with CLL developing HL. This article is protected by copyright. All rights reserved.

  18. Systemic Inflammatory Response and Elevated Tumour Markers Predict Worse Survival in Resectable Pancreatic Ductal Adenocarcinoma.

    PubMed

    Salmiheimo, Aino; Mustonen, Harri; Stenman, Ulf-Håkan; Puolakkainen, Pauli; Kemppainen, Esko; Seppänen, Hanna; Haglund, Caj

    2016-01-01

    Estimation of the prognosis of resectable pancreatic ductal adenocarcinoma (PDAC) currently relies on tumour-related factors such as resection margins and on lymph-node ratio (LNR) both inconveniently available only postoperatively. Our aim was to assess the accuracy of preoperative laboratory data in predicting PDAC prognosis. Collection of laboratory and clinical data was retrospective from 265 consecutive patients undergoing surgery for PDAC at Helsinki University Hospital. Cancer-specific survival assessment utilized Kaplan-Meier analysis, and independent associations between factors were by the Cox regression model. During follow-up, 76% of the patients died of PDAC, with a median survival time of 19.6 months. In univariate analysis, CRP, albumin, CEA, and CA19-9 were significantly associated with postoperative cancer-specific survival. In multivariate analysis, taking into account age, gender, LNR, resection margins, tumour status, and adjuvant chemotherapy, the preoperative biomarkers independently associated with adverse prognosis were hypoalbuminemia (< 36 g/L, hazard ratio (HR) 1.56, 95% confidence interval (CI) 1.10-2.19, p = 0.011), elevated CRP (> 5 mg/L, HR 1.44, 95% CI 1.03-2.02, p = 0.036), CEA (> 5 μg/L, HR 1.60, 95% CI 1.07-2.53, p = 0.047), and CA19-9 (≥555 kU/L, HR 1.91, 95% CI 1.18-3.08, p = 0.008). For patients with resectable PDAC, preoperative CRP, along with albumin and tumour markers, is useful for predicting prognosis.

  19. A Simple Risk Model to Predict Survival in Patients With Carcinoma of Unknown Primary Origin.

    PubMed

    Huang, Chen-Yang; Lu, Chang-Hsien; Yang, Chan-Keng; Hsu, Hung-Chih; Kuo, Yung-Chia; Huang, Wen-Kuan; Chen, Jen-Shi; Lin, Yung-Chang; Chia-Yen, Hung; Shen, Wen-Chi; Chang, Pei-Hung; Yeh, Kun-Yun; Hung, Yu-Shin; Chou, Wen-Chi

    2015-11-01

    Carcinoma of unknown primary origin (CUP) is characterized by diverse histological subtypes and clinical presentations, ranging from clinically indolent to frankly aggressive behaviors. This study aimed to identify prognostic factors of CUP and to develop a simple risk model to predict survival in a cohort of Asian patients.We retrospectively reviewed 190 patients diagnosed with CUP between 2007 and 2012 at a single medical center in Taiwan. The clinicopathological parameters and outcomes of our cohort were analyzed. A risk model was developed using multivariate logistic regression and a prognostic score was generated.The prognostic score was calculated based on 3 independent prognostic variables: the Eastern Cooperative Oncology Group (ECOG) scale (0 points if the score was 1, 2 points if it was 2-4), visceral organ involvement (0 points if no involvement, 1 point if involved), and the neutrophil-to-lymphocyte ratio (0 points if ≤3, 1 point if >3). Patients were stratified into good (score 0), intermediate (score 1-2), and poor (score 3-4) prognostic groups based on the risk model. The median survival (95% confidence interval) was 1086 days (500-1617, n = 42), 305 days (237-372, n = 75), and 64 days (44-84, n = 73) for the good, intermediate, and poor prognostic groups, respectively. The c-statistics using the risk model and ECOG scale for the outcome of 1-year mortality were 0.80 and 0.70 (P = 0.038), respectively.In this study, we developed a simple risk model that accurately predicted survival in patients with CUP. This scoring system may be used to help patients and clinicians determine appropriate treatments.

  20. Use of Nonclonal Serum Immunoglobulin Free Light Chains to Predict Overall Survival in the General Population

    PubMed Central

    Dispenzieri, Angela; Katzmann, Jerry A.; Kyle, Robert A.; Larson, Dirk R.; Therneau, Terry M.; Colby, Colin L.; Clark, Raynell J.; Mead, Graham P.; Kumar, Shaji; Melton, L. Joseph; Rajkumar, S. Vincent

    2012-01-01

    Objective To determine whether the free light chain (FLC) assay provides prognostic information relevant to the general population. Methods After excluding persons with a known plasma cell disorder, we studied 15,859 Olmsted County, Minnesota, residents 50 years or older in whom unmasked data and samples for FLC testing were available. Baseline information was obtained between March 13, 1995, and November 21, 2003, and follow-up status and cause of death were identified through June 30, 2009. The κ and λ FLC sum (Σ FLC) was evaluated for its ability to predict overall survival. Specific causes of death were also investigated. Results In 158,003 person-years of follow-up, 4348 individuals died. A high Σ FLC was significantly predictive of worse overall survival; the risk ratio for death for those with the highest decile of Σ FLC (ie, ≥4.72 mg/dL) was 4.4 (95% confidence interval, 4.1-4.7) relative to the remaining study participants. Multivariate analyses demonstrated that this excess risk of death was independent of age, sex, and renal insufficiency, with a corrected risk ratio of 2.1 (95% confidence interval, 1.9-2.2). The increased mortality was not restricted to any particular cause of death because the observed-to-expected risk of death from most causes was significantly higher among those individuals with an antecedent Σ FLC of 4.72 mg/dL or higher, which is near the upper limit of normal for the test. Conclusion A nonclonal elevation of Σ FLC is a significant predictor of worse overall survival in the general population of persons without plasma cell disorders. PMID:22677072

  1. Donor Chimerism Early after Reduced-intensity Conditioning Hematopoietic Stem Cell Transplantation Predicts Relapse and Survival

    PubMed Central

    Koreth, John; Kim, Haesook T.; Nikiforow, Sarah; Milford, Edgar L.; Armand, Philippe; Cutler, Corey; Glotzbecker, Brett; Ho, Vincent T.; Antin, Joseph H.; Soiffer, Robert J.; Ritz, Jerome; Alyea, Edwin P.

    2015-01-01

    The impact of early donor cell chimerism on outcomes of T-replete reduced-intensity conditioning (RIC) hematopoietic stem cell transplantation (HSCT) is ill-defined. We evaluated day 30 (D30) and 100 (D100) total donor cell chimerism after RIC HSCT undertaken between 2002 and 2010 at our institution, excluding patients who died or relapsed before D30. When available, donor T-cell chimerism was also assessed. The primary outcome was overall survival (OS). Secondary outcomes included progression-free survival (PFS), relapse and non-relapse mortality (NRM). 688 patients with hematologic malignancies (48% myeloid; 52% lymphoid) and a median age of 57 years (range, 18-74) undergoing RIC HSCT with T-replete donor grafts (97% peripheral blood; 92% HLA-matched) and median follow-up of 58.2 months (range, 12.6-120.7) were evaluated. In multivariable analysis total donor cell and T-cell chimerism at D30 and D100 each predicted RIC HSCT outcomes, with D100 total donor cell chimerism most predictive. D100 total donor cell chimerism <90% was associated with increased relapse (HR 2.54, 95% CI 1.83-3.51, p<0.0001), impaired PFS (HR 2.01, 95% CI 1.53-2.65, p<0.0001) and worse OS (1.50, 95% CI 1.11-2.04, p=0.009), but not NRM (HR 0.76; 95% CI 0.44-2.27, p=0.33). There was no additional utility of incorporating sustained D30-D100 total donor cell chimerism, or T-cell chimerism. Low donor chimerism early after RIC HSCT is an independent risk factor for relapse and impaired survival. Donor chimerism assessment early after RIC HSCT can prognosticate for long-term outcomes and help identify high-risk patient cohorts that may benefit from additional therapeutic interventions. PMID:24907627

  2. A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme.

    PubMed

    Lao, Jiangwei; Chen, Yinsheng; Li, Zhi-Cheng; Li, Qihua; Zhang, Ji; Liu, Jing; Zhai, Guangtao

    2017-09-04

    Traditional radiomics models mainly rely on explicitly-designed handcrafted features from medical images. This paper aimed to investigate if deep features extracted via transfer learning can generate radiomics signatures for prediction of overall survival (OS) in patients with Glioblastoma Multiforme (GBM). This study comprised a discovery data set of 75 patients and an independent validation data set of 37 patients. A total of 1403 handcrafted features and 98304 deep features were extracted from preoperative multi-modality MR images. After feature selection, a six-deep-feature signature was constructed by using the least absolute shrinkage and selection operator (LASSO) Cox regression model. A radiomics nomogram was further presented by combining the signature and clinical risk factors such as age and Karnofsky Performance Score. Compared with traditional risk factors, the proposed signature achieved better performance for prediction of OS (C-index = 0.710, 95% CI: 0.588, 0.932) and significant stratification of patients into prognostically distinct groups (P < 0.001, HR = 5.128, 95% CI: 2.029, 12.960). The combined model achieved improved predictive performance (C-index = 0.739). Our study demonstrates that transfer learning-based deep features are able to generate prognostic imaging signature for OS prediction and patient stratification for GBM, indicating the potential of deep imaging feature-based biomarker in preoperative care of GBM patients.

  3. A prospective, multicenter cohort study to validate a simple performance status-based survival prediction system for oncologists.

    PubMed

    Yamada, Takeshi; Morita, Tatsuya; Maeda, Isseki; Inoue, Satoshi; Ikenaga, Masayuki; Matsumoto, Yoshihisa; Baba, Mika; Sekine, Ryuichi; Yamaguchi, Takashi; Hirohashi, Takeshi; Tajima, Tsukasa; Tatara, Ryohei; Watanabe, Hiroaki; Otani, Hiroyuki; Takigawa, Chizuko; Matsuda, Yoshinobu; Ono, Shigeki; Ozawa, Taketoshi; Yamamoto, Ryo; Shishido, Hideki; Yamamoto, Naoki

    2017-04-15

    Survival prediction systems such as the Palliative Prognostic Index (PPI), which includes the Palliative Performance Scale (PPS), are used to estimate survival for terminally ill patients. Oncologists are, however, less familiar with the PPS in comparison with the Eastern Cooperative Oncology Group (ECOG) performance status (PS). This study was designed to validate a simple survival prediction system for oncologists, the Performance Status-Based Palliative Prognostic Index (PS-PPI), which is a modified form of the PPI based on the ECOG PS. This multicenter, prospective cohort study enrolled all consecutive patients who were referred to 58 palliative care services in Japan. The primary responsible physicians rated the variables required to calculate the PS-PPI and the PPI. Patient survival in these risk groups was compared, and the sensitivity and specificity of the PS-PPI and the PPI were evaluated. Patients were subclassified as patients receiving care from in-hospital palliative care teams, palliative care units, or home-based palliative care services. Subsets of patients receiving chemotherapy were also analyzed. This study included 2346 patients. Survival predictions based on the PPI and the PS-PPI differed significantly among the 3 risk groups (P < .001). The PS-PPI was more sensitive, whereas the PPI was more specific. All areas under the receiver operating characteristic curves of both indices were >0.78 for predicting survival at all times, from 3 weeks to 180 days. In predicting the prognosis of patients with advanced cancer, the PS-PPI was as accurate as the PPI. The PS-PPI was useful for short- and long-term survival prediction and for the prediction of survival for patients undergoing chemotherapy. Cancer 2017;123:1442-1452. © 2016 American Cancer Society. © 2016 American Cancer Society.

  4. Development of a model to predict breast cancer survival using data from the National Cancer Data Base.

    PubMed

    Asare, Elliot A; Liu, Lei; Hess, Kenneth R; Gordon, Elisa J; Paruch, Jennifer L; Palis, Bryan; Dahlke, Allison R; McCabe, Ryan; Cohen, Mark E; Winchester, David P; Bilimoria, Karl Y

    2016-02-01

    With the large amounts of data on patient, tumor, and treatment factors available to clinicians, it has become critically important to harness this information to guide clinicians in discussing a patient's prognosis. However, no widely accepted survival calculator is available that uses national data and includes multiple prognostic factors. Our objective was to develop a model for predicting survival among patients diagnosed with breast cancer using the National Cancer Data Base (NCDB) to serve as a prototype for the Commission on Cancer's "Cancer Survival Prognostic Calculator." A retrospective cohort of patients diagnosed with breast cancer (2003-2006) in the NCDB was included. A multivariable Cox proportional hazards regression model to predict overall survival was developed. Model discrimination by 10-fold internal cross-validation and calibration was assessed. There were 296,284 patients for model development and internal validation. The c-index for the 10-fold cross-validation ranged from 0.779 to 0.788 after inclusion of all available pertinent prognostic factors. A plot of the observed versus predicted 5 year overall survival showed minimal deviation from the reference line. This breast cancer survival prognostic model to be used as a prototype for building the Commission on Cancer's "Cancer Survival Prognostic Calculator" will offer patients and clinicians an objective opportunity to estimate personalized long-term survival based on patient demographic characteristics, tumor factors, and treatment delivered. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. The platelet-to-lymphocyte ratio predicts poor survival in patients with huge hepatocellular carcinoma that received transarterial chemoembolization.

    PubMed

    Xue, Tong-Chun; Jia, Qing-An; Ge, Ning-Ling; Zhang, Bo-Heng; Wang, Yan-Hong; Ren, Zheng-Gang; Ye, Sheng-Long

    2015-08-01

    Inflammation is particularly strong in huge hepatocellular carcinoma (HCC). However, it is unclear whether the platelet-to-lymphocyte ratio (PLR), as an inflammatory-related marker, can predict survival of patients with huge HCC. In this study, we enrolled 291 patients with huge HCC (diameter over 10 cm) who were undergoing repeated transarterial chemoembolization (TACE) at our institute. The baseline PLR was calculated from complete serum blood counts before the first chemoembolization. We found that a baseline PLR cutoff value over 150 best predicted huge HCC survival. The 12, 24, and 36 months survival rates in the high PLR group (22.6, 8.1, and 4.1 %, respectively) were significantly lower than in the low PLR group (35.6, 22.4, and 14 %, respectively). Thus, a significant difference was found in overall survival (log-rank test, p < 0.0001). Univariate analyses indicated a high PLR (p < 0.0001) was predictor of poor survival, and multivariate Cox analyses further showed that a high PLR (p = 0.002) was an independent factor that predicted worse survival. In conclusion, for patients with huge HCC, a high baseline PLR is a useful predictor of poor survival in patients undergoing chemoembolization. Additional anti-inflammatory or anti-platelet treatments, in combination with TACE, may improve survival in HCC patients with high PLR.

  6. AFP mRNA Detected in Bone Marrow by Real-Time Quantitative RT-PCR Analysis Predicts Survival and Recurrence After Curative Hepatectomy for Hepatocellular Carcinoma

    PubMed Central

    Kamiyama, Toshiya; Takahashi, Masato; Nakagawa, Takahito; Nakanishi, Kazuaki; Kamachi, Hirofumi; Suzuki, Tomomi; Shimamura, Tsuyoshi; Taniguchi, Masahiko; Ozaki, Michitaka; Matsushita, Michiaki; Furukawa, Hiroyuki; Todo, Satoru

    2006-01-01

    Objective: To determine whether detection of hepatocellular carcinoma (HCC) cells by real-time quantitative RT-PCR targeting of alpha-fetoprotein mRNA (AFP mRNA) before or after curative hepatectomy predicts HCC recurrence and patient survival. Summary Background Data: The presence of cancer cells in peripheral blood and/or bone marrow in patients with malignant disease has been reported to correlate with outcome. Methods: Between July 2000 and June 2005, 136 consecutive HCC patients underwent primary curative hepatectomy. Bone marrow aspirated preoperatively, and peripheral blood samples collected before and after operation were subjected to real-time quantitative RT-PCR analysis using AFP mRNA as a target molecule. Median follow-up was 23 months (range, 6–54 months). Patient survival (PS), disease-free survival (DFS), and clinicopathologic features were compared between patients with positive and negative AFP mRNA. Results: Twenty-four patients died (22 from HCC). HCC recurred in 66 patients (hepatic in 37 [56.1%]; hepatic and remote in 17 [25.8%], and remote alone in 12 [18.2%]). Bone marrow was positive for AFP mRNA in 38 patients (27.9%) and negative in 98 (72.1%). One- and 3-year PS was 96.6% and 91.4%, respectively, with negative AFP mRNA versus 86.2% and 55.5%, respectively, with positive AFP mRNA (P < 0.0001). One- and 3-year DFS were 73.2% and 44.8%, respectively, with negative AFP mRNA versus 54.5% and 25.8%, respectively, with positive AFP mRNA (P = 0.0399). Portal vascular invasion, tumor size, multiple tumors, and tumor differentiation correlated with inferior PS and DFS on univariate analysis. On multivariate analysis, positive AFP mRNA was the most important risk factor for PS (P = 0.001) and DFS (P = 0.0165). In addition, positive AFP mRNA in peripheral blood after operation tended to predict reduced DFS. Conclusion: AFP mRNA in the bone marrow and systemic circulation during the perioperative period predicts patient survival and recurrence after

  7. Predicting Survival from Telomere Length versus Conventional Predictors: A Multinational Population-Based Cohort Study

    PubMed Central

    Glei, Dana A.; Goldman, Noreen; Risques, Rosa Ana; Rehkopf, David H.; Dow, William H.; Rosero-Bixby, Luis; Weinstein, Maxine

    2016-01-01

    Telomere length has generated substantial interest as a potential predictor of aging-related diseases and mortality. Some studies have reported significant associations, but few have tested its ability to discriminate between decedents and survivors compared with a broad range of well-established predictors that include both biomarkers and commonly collected self-reported data. Our aim here was to quantify the prognostic value of leukocyte telomere length relative to age, sex, and 19 other variables for predicting five-year mortality among older persons in three countries. We used data from nationally representative surveys in Costa Rica (N = 923, aged 61+), Taiwan (N = 976, aged 54+), and the U.S. (N = 2672, aged 60+). Our study used a prospective cohort design with all-cause mortality during five years post-exam as the outcome. We fit Cox hazards models separately by country, and assessed the discriminatory ability of each predictor. Age was, by far, the single best predictor of all-cause mortality, whereas leukocyte telomere length was only somewhat better than random chance in terms of discriminating between decedents and survivors. After adjustment for age and sex, telomere length ranked between 15th and 17th (out of 20), and its incremental contribution was small; nine self-reported variables (e.g., mobility, global self-assessed health status, limitations with activities of daily living, smoking status), a cognitive assessment, and three biological markers (C-reactive protein, serum creatinine, and glycosylated hemoglobin) were more powerful predictors of mortality in all three countries. Results were similar for cause-specific models (i.e., mortality from cardiovascular disease, cancer, and all other causes combined). Leukocyte telomere length had a statistically discernible, but weak, association with mortality, but it did not predict survival as well as age or many other self-reported variables. Although telomere length may eventually help scientists

  8. Time to lowest postoperative carcinoembryonic antigen level is predictive on survival outcome in rectal cancer

    PubMed Central

    Yu, Huichuan; Luo, Yanxin; Wang, Xiaolin; Bai, Liangliang; Huang, Pinzhu; Wang, Lei; Huang, Meijin; Deng, Yanhong; Wang, Jianping

    2016-01-01

    This study was to investigate whether the time to the lowest postoperative CEA can predict cancer survival. We enrolled 155 rectal cancer patients in this retrospective and longitudinal cohort study. Deepness of response (DpR) of CEA refers to the relative change of the lowest postoperative CEA level from baseline, and time to DpR (TTDpR) refers to the time from surgery to the lowest postoperative CEA level. The median of TTDpR and DpR was 4.5 (range, 3.0–18.0) weeks and −67% (range, −99% to 114%) respectively. Patients with TTDpR 4.5 weeks. Using TTDpR as a continuous variable, the HR of DFS and OS was 1.13 (95% CI 1.06–1.22, P = 0.001) and 1.17 (95% CI 1.07–1.29, P = 0.001) respectively. On multivariate analysis, the predictive value of prolonged TTDpR remained [adjusted HRs: 1.12 (95% CI 1.03–1.21, P = 0.006) and 1.17 (95% CI 1.06–1.28, P = 0.001)]. These findings remained significant in patients with normal preoperative CEA. Our results showed prolonged TTDpR of CEA independently predicted unfavorable survival outcomes, regardless of whether preoperative CEA was elevated or not. PMID:27658525

  9. Distance in cancer gene expression from stem cells predicts patient survival

    PubMed Central

    Zehir, Ahmet; Gönen, Mithat; Moreira, Andre L.; Downey, Robert J.; Michor, Franziska

    2017-01-01

    The degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis. Here we utilized mRNA expression data from 4,413 patient samples with 7 diverse cancer histologies to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors. We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells orients cancers in a clinically coherent fashion. For all histologies analyzed (including carcinomas, sarcomas, and hematologic malignancies), patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. We also found that the genes in all undifferentiated cancers of diverse histologies that were most differentially expressed were associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes. Thus, a stem cell-oriented phylogeny of cancers allows for the derivation of a novel cancer gene expression signature found in all undifferentiated forms of diverse cancer histologies, that is competitive in predicting overall survival in cancer patients compared to previously published prediction models, and is coherent in that gene expression was associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes associated with regulation of

  10. Distance in cancer gene expression from stem cells predicts patient survival.

    PubMed

    Riester, Markus; Wu, Hua-Jun; Zehir, Ahmet; Gönen, Mithat; Moreira, Andre L; Downey, Robert J; Michor, Franziska

    2017-01-01

    The degree of histologic cellular differentiation of a cancer has been associated with prognosis but is subjectively assessed. We hypothesized that information about tumor differentiation of individual cancers could be derived objectively from cancer gene expression data, and would allow creation of a cancer phylogenetic framework that would correlate with clinical, histologic and molecular characteristics of the cancers, as well as predict prognosis. Here we utilized mRNA expression data from 4,413 patient samples with 7 diverse cancer histologies to explore the utility of ordering samples by their distance in gene expression from that of stem cells. A differentiation baseline was obtained by including expression data of human embryonic stem cells (hESC) and human mesenchymal stem cells (hMSC) for solid tumors, and of hESC and CD34+ cells for liquid tumors. We found that the correlation distance (the degree of similarity) between the gene expression profile of a tumor sample and that of stem cells orients cancers in a clinically coherent fashion. For all histologies analyzed (including carcinomas, sarcomas, and hematologic malignancies), patients with cancers with gene expression patterns most similar to that of stem cells had poorer overall survival. We also found that the genes in all undifferentiated cancers of diverse histologies that were most differentially expressed were associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes. Thus, a stem cell-oriented phylogeny of cancers allows for the derivation of a novel cancer gene expression signature found in all undifferentiated forms of diverse cancer histologies, that is competitive in predicting overall survival in cancer patients compared to previously published prediction models, and is coherent in that gene expression was associated with up-regulation of specific oncogenes and down-regulation of specific tumor suppressor genes associated with regulation of

  11. Low preoperative albumin-globulin score predicts favorable survival in esophageal squamous cell carcinoma

    PubMed Central

    Wang, Zhi-qiang; Wang, De-shen; Wang, Yun; Zhang, Dong-sheng; Wang, Feng-hua; Fu, Jian-hua; Xu, Rui-hua; Li, Yu-hong

    2016-01-01

    This study retrospectively investigated the prognostic significance of the preoperative albumin-globulin score (AGS) and albumin/globulin ratio (AGR) in esophageal squamous cell carcinoma (ESCC). A cohort of 458 newly diagnosed ESCC patients who underwent radical esophagectomy in Sun Yat-sen University Cancer Center (Guangzhou, China) between January 2006 and December 2010 were selected into this study. The optimal cut-off value was identified to be 45.6 g/L, 26.9 g/L and 1.30 for albumin (ALB), globulin (GLB) and AGR in terms of survival, respectively. Patients with low ALB levels (< 45.6 g/L) and high GLB levels (≥ 26.9 g/L) were assigned an AGS of 2, those with only one of the two abnormalities were assigned an AGS of 1, and those with neither of the two abnormalities were assigned an AGS of 0. Univariate survival analysis showed that low AGS (0) was significantly associated with favorable disease free survival (DFS) [hazard ratio (HR), 0.635; 95% confidence interval (CI), 0.441–0.914; P = 0.015] and overall survival (OS) (HR, 0.578; 95% CI, 0.387–0.862; P = 0.007), and it remained an independent predictor for OS (HR, 0.630; 95% CI, 0.418–0.952; P = 0.028), but not for DFS (HR, 0.697; 95% CI, 0.479–1.061; P = 0.060) in multivariate models. High AGR (≥ 1.30) was also correlated with favorable DFS (HR, 0.626; 95% CI, 0.430–0.910; P = 0.014) and OS (HR, 0.622; 95% CI, 0.422–0.916; P = 0.016) in univariate analysis, but it failed to be an independent prognostic indicator for DFS (HR, 0.730; 95% CI, 0.494–1.078; P = 0.114) or OS (HR, 0.759; 95% CI, 0.507–1.137; P = 0.181) by multivariate analysis. Low preoperative AGS could serve as a valuable and convenient biochemical marker to predict favorable long-term survival in ESCC patients. PMID:27105522

  12. Nomograms to Predict Recurrence-Free and Overall Survival After Curative Resection of Adrenocortical Carcinoma

    PubMed Central

    Kim, Yuhree; Margonis, Georgios A.; Prescott, Jason D.; Tran, Thuy B.; Postlewait, Lauren M.; Maithel, Shishir K.; Wang, Tracy S.; Evans, Douglas B.; Hatzaras, Ioannis; Shenoy, Rivfka; Phay, John E.; Keplinger, Kara; Fields, Ryan C.; Jin, Linda X.; Weber, Sharon M.; Salem, Ahmed I.; Sicklick, Jason K.; Gad, Shady; Yopp, Adam C.; Mansour, John C.; Duh, Quan-Yang; Seiser, Natalie; Solorzano, Carmen C.; Kiernan, Colleen M.; Votanopoulos, Konstantinos I.; Levine, Edward A.; Poultsides, George A.; Pawlik, Timothy M.

    2016-01-01

    IMPORTANCE Adrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined. OBJECTIVES To define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction. DESIGN, SETTING, AND PARTICIPANTS Nomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015. MAIN OUTCOMES AND MEASURES The discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves. RESULTS In total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63–5.70; P < .001), positive nodal status (HR, 4.78; 95% CI, 1.47–15.50; P = .01), stage III/IV (HR, 1.80; 95% CI, 0.95–3.39; P = .07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27–4.48; P = .01), and capsular invasion (HR, 1.96; 95% CI, 1.02–3.74; P = .04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00–3.17; P = .05), positive

  13. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers

    PubMed Central

    Anand, Sanya; Sebra, Robert; Catalina Camacho, Sandra; Garnar-Wortzel, Leopold; Nair, Navya; Moshier, Erin; Wooten, Melissa; Uzilov, Andrew; Chen, Rong; Prasad-Hayes, Monica; Zakashansky, Konstantin; Beddoe, Ann Marie; Schadt, Eric; Dottino, Peter; Martignetti, John A.

    2015-01-01

    Background High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools. Methods and Findings Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival. Conclusions Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic

  14. A new survival status prediction system for severe trauma patients based on a multiple classifier system.

    PubMed

    Sanz, José; Paternain, Daniel; Galar, Mikel; Fernandez, Javier; Reyero, Diego; Belzunegui, Tomás

    2017-04-01

    Severe trauma patients are those who have several injuries implying a death risk. Prediction systems consider the severity of these injuries to predict whether the patients are likely to survive or not. These systems allow one to objectively compare the quality of the emergency services of trauma centres across different hospitals. However, even the most accurate existing prediction systems are based on the usage of a single model. The aim of this paper is to combine several models to make the prediction, since this methodology usually improves the performance of single models. The two currently used prediction systems by the Hospital of Navarre, which are based on logistic regression models, besides the C4.5 decision tree are combined to conform our proposed multiple classifier system. The quality of the method is tested using the major trauma registry of Navarre, which stores information of 462 trauma patients. A 10x10-fold cross-validation model is applied using as performance measures the specificity, sensitivity and the geometric mean between the two former ones. The results are supported by the usage of the Mann-Whitney's U statistical test. The proposed method provides 0.8908, 0.6703 and 0.7661 for sensitivity, specificity and geometric mean, respectively. It slightly decreases the sensitivity of the currently used systems but it notably increases the specificity, which implies a large enhancement on the geometric mean. The same behaviour is found when it is compared versus four classical ensemble approaches and the random forest. The statistical analysis supports the quality of our proposal, since the obtained p-values are less than 0.01 in all the cases. The obtained results show that the multiple classifier systems is the best choice among the considered methods to obtain a trade-off between sensitivity and specificity. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. PREDICTIVE MODEL FOR SURVIVAL AND GROWTH OF SALMONELLA TYPHIMURIUM DT104 ON CHICKEN SKIN DURING TEMPERATURE ABUSE

    USDA-ARS?s Scientific Manuscript database

    To better predict risk of Salmonella infection from chicken subjected to temperature abuse, a study was undertaken to develop a predictive model for survival and growth of Salmonella Typhimurium DT104 on chicken skin with native micro flora. For model development, chicken skin portions were inocula...

  16. Oxygenation predicts radiation response and survival in patients with cervix cancer.

    PubMed

    Fyles, A W; Milosevic, M; Wong, R; Kavanagh, M C; Pintilie, M; Sun, A; Chapman, W; Levin, W; Manchul, L; Keane, T J; Hill, R P

    1998-08-01

    Hypoxia appears to be an important factor in predicting tumor relapse following radiation therapy. This study measured oxygenation prior to treatment in patients with cervix cancer using a polarographic oxygen electrode to determine if oxygenation was an important prognostic factor with regard to tumor control and survival. Between May 1994 and June 1997, 74 eligible patients with cervix cancer were entered into an ongoing prospective study of tumor oxygenation prior to primary radiation therapy. All patients were evaluated with an Eppendorf oxygen electrode during examination under anesthesia. Oxygenation data are presented as the hypoxic proportion, defined as the percentage of pO2 readings of <5 mm Hg (abbreviated as HP5). The HP5 ranged from 2 to 99% with a median of 52%. With a median follow-up of 1.2 years, the disease-free survival (DFS) rate was 69% for patients with HP5 of < or =50% compared with 34% for those with HP5 of >50% (log-rank P = 0.02). Tumor size above and below the median of 5 cm was also significantly related to DFS (P = 0.0003) and patients with bulky hypoxic tumors had a significantly lower DFS (12% at 2 years) than either bulky oxygenated or non-bulky oxygenated or hypoxic tumors (65%, P = 0.0001). Hypoxia and tumor size are significant adverse prognostic factors in a univariate analysis of disease-free survival in patients with cervix cancer. A high risk group of patients with bulky hypoxic tumors have a significantly higher probability of relapse and death.

  17. High expression of TIG3 predicts poor survival in patients with primary glioblastoma.

    PubMed

    Wang, Hongxiang; Xu, Hanchong; Xu, Tao; Tan, Cong; Jiang, Mei; Chen, Yihong; Hu, Xinyu; Zhou, Jinxu; Shen, Junyan; Qin, Rong; Hu, Daiyu; Huang, Qilin; Wang, Min; Wang, Lian; Duan, Dongxia; Yan, Yong; Chen, Juxiang

    2017-06-01

    TIG3 (tazarotene-induced gene 3) has been reported to suppress the progression of several malignancies, where this gene is universally downregulated. However, the expression of TIG3 in primary glioblastoma and its relevance to patient's prognosis have not been elaborated. Thus, this study was aimed to evaluate TIG3 expression level in primary glioblastoma and investigate the prognostic value of TIG3 for patients. The Cancer Genome Atlas database was first utilized to analyze the expression and prognostic potential of TIG3 in 528 glioblastoma cases. Compared with control group, glioblastoma showed significantly elevated TIG3 expression (p < 0.001). Log-rank analysis revealed that higher expression of TIG3 was associated with shorter overall survival (358vs 383 days, p = 0.039). Furthermore, TIG3 protein expression detected by immunohistochemistry confirmed positive correlation of TIG3 expression and glioma grade and upregulation of TIG3 in our cohort of 101 primary glioblastoma patients compared to 16 normal brains. Finally, Kaplan-Meier analysis and Cox regression analysis identified high TIG3 expression as an independent risk factor for overall survival of primary glioblastoma patients (overall survival, 10 vs 13 months, p = 0.033; hazard ratio = 1.542, p = 0.046). Together, this study indicated that increased expression of TIG3 in primary glioblastoma is a novel biomarker for predicting poor outcome of patients. We then hypothesize that TIG3 may function in a different pattern in glioblastoma.

  18. Using cross-validation to evaluate predictive accuracy of survival risk classifiers based on high-dimensional data.

    PubMed

    Simon, Richard M; Subramanian, Jyothi; Li, Ming-Chung; Menezes, Supriya

    2011-05-01

    Developments in whole genome biotechnology have stimulated statistical focus on prediction methods. We review here methodology for classifying patients into survival risk groups and for using cross-validation to evaluate such classifications. Measures of discrimination for survival risk models include separation of survival curves, time-dependent ROC curves and Harrell's concordance index. For high-dimensional data applications, however, computing these measures as re-substitution statistics on the same data used for model development results in highly biased estimates. Most developments in methodology for survival risk modeling with high-dimensional data have utilized separate test data sets for model evaluation. Cross-validation has sometimes been used for optimization of tuning parameters. In many applications, however, the data available are too limited for effective division into training and test sets and consequently authors have often either reported re-substitution statistics or analyzed their data using binary classification methods in order to utilize familiar cross-validation. In this article we have tried to indicate how to utilize cross-validation for the evaluation of survival risk models; specifically how to compute cross-validated estimates of survival distributions for predicted risk groups and how to compute cross-validated time-dependent ROC curves. We have also discussed evaluation of the statistical significance of a survival risk model and evaluation of whether high-dimensional genomic data adds predictive accuracy to a model based on standard covariates alone.

  19. The Prognostic Nutritional Index Predicts Survival and Identifies Aggressiveness of Gastric Cancer.

    PubMed

    Eo, Wan Kyu; Chang, Hye Jung; Suh, Jungho; Ahn, Jin; Shin, Jeong; Hur, Joon-Young; Kim, Gou Young; Lee, Sookyung; Park, Sora; Lee, Sanghun

    2015-01-01

    Nutritional status has been associated with long-term outcomes in cancer patients. The prognostic nutritional index (PNI) is calculated by serum albumin concentration and absolute lymphocyte count, and it may be a surrogate biomarker for nutritional status and possibly predicts overall survival (OS) of gastric cancer. We evaluated the value of the PNI as a predictor for disease-free survival (DFS) in addition to OS in a cohort of 314 gastric cancer patients who underwent curative surgical resection. There were 77 patients in PNI-low group (PNI ≤ 47.3) and 237 patients in PNI-high group (PNI > 47.3). With a median follow-up of 36.5 mo, 5-yr DFS rates in PNI-low group and PNI-high group were 63.5% and 83.6% and 5-yr OS rates in PNI-low group and PNI-high group were 63.5% and 88.4%, respectively (DFS, P < 0.0001; OS, P < 0.0001). In the multivariate analysis, the only predictors for DFS were PNI, tumor-node-metastasis (TNM) stage, and perineural invasion, whereas the only predictors for OS were PNI, age, TNM stage, and perineural invasion. In addition, the PNI was independent of various inflammatory markers. In conclusion, the PNI is an independent prognostic factor for both DFS and OS, and provides additional prognostic information beyond pathologic parameters.

  20. LncRNA Expression Discriminates Karyotype and Predicts Survival in B-lymphoblastic Leukemia

    PubMed Central

    Fernando, Thilini R.; Rodriguez-Malave, Norma I.; Waters, Ella V.; Yan, Weihong; Casero, David; Basso, Giuseppe; Pigazzi, Martina; Rao, Dinesh S.

    2015-01-01

    Long non-coding RNAs (lncRNAs) have been found to play a role in gene regulation with dysregulated expression in various cancers. The precise role that lncRNA expression plays in the pathogenesis of B-acute lymphoblastic leukemia (B-ALL) is unknown. Therefore, unbiased microarray profiling was performed on human B-ALL specimens and it was determined that lncRNA expression correlates with cytogenetic abnormalities, which was confirmed by RT-qPCR in a large set of B-ALL cases. Importantly, high expression of BALR-2 correlated with poor overall survival and diminished response to prednisone treatment. In line with a function for this lncRNA in regulating cell survival, BALR-2 knockdown led to reduced proliferation, increased apoptosis, and increased sensitivity to prednisolone treatment. Conversely, overexpression of BALR-2 led to increased cell growth and resistance to prednisone treatment. Interestingly, BALR-2 expression was repressed by prednisolone treatment and its knockdown led to upregulation of the glucocorticoid response pathway in both human and mouse B-cells. Together, these findings indicate that BALR-2 plays a functional role in the pathogenesis and/or clinical responsiveness of B-ALL and that altering the levels of particular lncRNAs may provide a future direction for therapeutic development. Implications lncRNA expression has the potential to segregate the common subtypes of B-ALL, predict the cytogenetic subtype, and indicate prognosis. PMID:25681502

  1. BINNING SOMATIC MUTATIONS BASED ON BIOLOGICAL KNOWLEDGE FOR PREDICTING SURVIVAL: AN APPLICATION IN RENAL CELL CARCINOMA

    PubMed Central

    Kim, Dokyoon; Li, Ruowang; Dudek, Scott M.; Wallace, John R.; Ritchie, Marylyn D.

    2014-01-01

    Enormous efforts of whole exome and genome sequencing from hundreds to thousands of patients have provided the landscape of somatic genomic alterations in many cancer types to distinguish between driver mutations and passenger mutations. Driver mutations show strong associations with cancer clinical outcomes such as survival. However, due to the heterogeneity of tumors, somatic mutation profiles are exceptionally sparse whereas other types of genomic data such as miRNA or gene expression contain much more complete data for all genomic features with quantitative values measured in each patient. To overcome the extreme sparseness of somatic mutation profiles and allow for the discovery of combinations of somatic mutations that may predict cancer clinical outcomes, here we propose a new approach for binning somatic mutations based on existing biological knowledge. Through the analysis using renal cell carcinoma dataset from The Cancer Genome Atlas (TCGA), we identified combinations of somatic mutation burden based on pathways, protein families, evolutionary conversed regions, and regulatory regions associated with survival. Due to the nature of heterogeneity in cancer, using a binning strategy for somatic mutation profiles based on biological knowledge will be valuable for improved prognostic biomarkers and potentially for tailoring therapeutic strategies by identifying combinations of driver mutations. PMID:25592572

  2. Centromere and kinetochore gene misexpression predicts cancer patient survival and response to radiotherapy and chemotherapy

    PubMed Central

    Zhang, Weiguo; Mao, Jian-Hua; Zhu, Wei; Jain, Anshu K.; Liu, Ke; Brown, James B.; Karpen, Gary H.

    2016-01-01

    Chromosomal instability (CIN) is a hallmark of cancer that contributes to tumour heterogeneity and other malignant properties. Aberrant centromere and kinetochore function causes CIN through chromosome missegregation, leading to aneuploidy, rearrangements and micronucleus formation. Here we develop a Centromere and kinetochore gene Expression Score (CES) signature that quantifies the centromere and kinetochore gene misexpression in cancers. High CES values correlate with increased levels of genomic instability and several specific adverse tumour properties, and prognosticate poor patient survival for breast and lung cancers, especially early-stage tumours. They also signify high levels of genomic instability that sensitize cancer cells to additional genotoxicity. Thus, the CES signature forecasts patient response to adjuvant chemotherapy or radiotherapy. Our results demonstrate the prognostic and predictive power of the CES, suggest a role for centromere misregulation in cancer progression, and support the idea that tumours with extremely high CIN are less tolerant to specific genotoxic therapies. PMID:27577169

  3. Natural variation of macrophage activation as disease-relevant phenotype predictive of inflammation and cancer survival.

    PubMed

    Buscher, Konrad; Ehinger, Erik; Gupta, Pritha; Pramod, Akula Bala; Wolf, Dennis; Tweet, George; Pan, Calvin; Mills, Charles D; Lusis, Aldons J; Ley, Klaus

    2017-07-24

    Although mouse models exist for many immune-based diseases, the clinical translation remains challenging. Most basic and translational studies utilize only a single inbred mouse strain. However, basal and diseased immune states in humans show vast inter-individual variability. Here, focusing on macrophage responses to lipopolysaccharide (LPS), we use the hybrid mouse diversity panel (HMDP) of 83 inbred strains as a surrogate for human natural immune variation. Since conventional bioinformatics fail to analyse a population spectrum, we highlight how gene signatures for LPS responsiveness can be derived based on an Interleukin-12β and arginase expression ratio. Compared to published signatures, these gene markers are more robust to identify susceptibility or resilience to several macrophage-related disorders in humans, including survival prediction across many tumours. This study highlights natural activation diversity as a disease-relevant dimension in macrophage biology, and suggests the HMDP as a viable tool to increase translatability of mouse data to clinical settings.

  4. Thymidylate Synthase 1 (TS1) in Situ Protein Expression Predicts the Survival of Ewing/PNET

    PubMed Central

    Bui, Marilyn M.; Zheng, Zhong; Antonia, Scott; Bepler, Gerold

    2013-01-01

    TS1, RRM1 and ERCC1, which are crucial for DNA synthesis and repair and have shown prognostic and predictive value in carcinomas, were investigated in Ewing/PNET. The tissue microarray consisting of 31 archived Ewing/PNET samples was subjected to immunohistochemistry based on immunofluorescence combined with automated quantitative analysis (AQUA) to assess in situ expression. AQUA score was analyzed with various clinicopathological data. TS1 was immunoreactive in the nucleus and cytoplasm, while RRM1 and ERCC1 were nuclear. High TS1 expression, not RRM1 and ERCC1, was associated with long overall survival (p value = 0.057). Thus in situ TS1 protein expression in Ewing/PNET is a prognostic marker. PMID:21043562

  5. Wolbachia infections that reduce immature insect survival: Predicted impacts on population replacement

    PubMed Central

    2011-01-01

    Background The evolutionary success of Wolbachia bacteria, infections of which are widespread in invertebrates, is largely attributed to an ability to manipulate host reproduction without imposing substantial fitness costs. Here, we describe a stage-structured model with deterministic immature lifestages and a stochastic adult female lifestage. Simulations were conducted to better understand Wolbachia invasions into uninfected host populations. The model includes conventional Wolbachia parameters (the level of cytoplasmic incompatibility, maternal inheritance, the relative fecundity of infected females, and the initial Wolbachia infection frequency) and a new parameter termed relative larval viability (RLV), which is the survival of infected larvae relative to uninfected larvae. Results The results predict the RLV parameter to be the most important determinant for Wolbachia invasion and establishment. Specifically, the fitness of infected immature hosts must be close to equal to that of uninfected hosts before population replacement can occur. Furthermore, minute decreases in RLV inhibit the invasion of Wolbachia despite high levels of cytoplasmic incompatibility, maternal inheritance, and low adult fitness costs. Conclusions The model described here takes a novel approach to understanding the spread of Wolbachia through a population with explicit dynamics. By combining a stochastic female adult lifestage and deterministic immature/adult male lifestages, the model predicts that even those Wolbachia infections that cause minor decreases in immature survival are unlikely to invade and spread within the host population. The results are discussed in relation to recent theoretical and empirical studies of natural population replacement events and proposed applied research, which would use Wolbachia as a tool to manipulate insect populations. PMID:21975225

  6. Body Composition Features Predict Overall Survival in Patients With Hepatocellular Carcinoma

    PubMed Central

    Singal, Amit G; Zhang, Peng; Waljee, Akbar K; Ananthakrishnan, Lakshmi; Parikh, Neehar D; Sharma, Pratima; Barman, Pranab; Krishnamurthy, Venkataramu; Wang, Lu; Wang, Stewart C; Su, Grace L

    2016-01-01

    Objectives: Existing prognostic models for patients with hepatocellular carcinoma (HCC) have limitations. Analytic morphomics, a novel process to measure body composition using computational image-processing algorithms, may offer further prognostic information. The aim of this study was to develop and validate a prognostic model for HCC patients using body composition features and objective clinical information. Methods: Using computed tomography scans from a cohort of HCC patients at the VA Ann Arbor Healthcare System between January 2006 and December 2013, we developed a prognostic model using analytic morphomics and routine clinical data based on multivariate Cox regression and regularization methods. We assessed model performance using C-statistics and validated predicted survival probabilities. We validated model performance in an external cohort of HCC patients from Parkland Hospital, a safety-net health system in Dallas County. Results: The derivation cohort consisted of 204 HCC patients (20.1% Barcelona Clinic Liver Cancer classification (BCLC) 0/A), and the validation cohort had 225 patients (22.2% BCLC 0/A). The analytic morphomics model had good prognostic accuracy in the derivation cohort (C-statistic 0.80, 95% confidence interval (CI) 0.71–0.89) and external validation cohort (C-statistic 0.75, 95% CI 0.68–0.82). The accuracy of the analytic morphomics model was significantly higher than that of TNM and BCLC staging systems in derivation (P<0.001 for both) and validation (P<0.001 for both) cohorts. For calibration, mean absolute errors in predicted 1-year survival probabilities were 5.3% (90% quantile of 7.5%) and 7.6% (90% quantile of 12.5%) in the derivation and validation cohorts, respectively. Conclusion: Body composition features, combined with readily available clinical data, can provide valuable prognostic information for patients with newly diagnosed HCC. PMID:27228403

  7. Tumour thickness predicts cervical nodal metastases and survival in early oral tongue cancer.

    PubMed

    O-charoenrat, P; Pillai, G; Patel, S; Fisher, C; Archer, D; Eccles, S; Rhys-Evans, P

    2003-06-01

    Squamous cell carcinoma (SCC) of the oral tongue is characterized by a high propensity for cervical nodal metastasis, which affects the probability of regional control and survival. Until now, elective treatment of the clinically negative neck in early lesions (T(1-2)) of the oral tongue cancer remains controversial. This study attempted to identify predictive factor(s) for cervical nodal metastasis and treatment outcomes in patients with early stage SCC of the oral tongue treated primarily by surgery. Fifty patients with previously untreated Stage I/II primary tongue carcinomas with available archival specimens treated at the Royal Marsden Hospital between 1981 and 1998 were reviewed. Clinico-pathological features including age, gender, alcohol and tobacco consumption, tumour location, histological grade, tumour-stromal border, growth pattern, tumour thickness, and clinical stage were evaluated and the correlations with cervical metastases and outcome analysis were determined. The overall occult nodal metastatic rate was 40% (20/50). Tumour thickness exceeding 5 mm was statistically significantly correlated with cervical metastases (P = 0.003; relative risk = 2.429). No statistical correlation was observed between other clinico-pathological parameters and nodal metastasis. With a median follow-up of 98 months, 5-year actuarial overall, disease-specific (DSS), and relapse-free survival were 65.71, 67.77, and 68.18%, respectively. Univariate analysis for DSS showed poorer outcomes for patients with age > 60 years (P = 0.0423) and tumour thickness > 5 mm (P = 0.0067). The effect of tumour thickness was maintained (P = 0.005) on multivariate analysis. The present study indicates that the thickness of primary tumour has a strong predictive value for occult cervical metastasis and poor outcomes in patients with Stage I/II oral tongue SCC. Thus, elective neck treatment (surgery or irradiation) is indicated for tumours exceeding 5 mm thickness. Copyright 2003 Elsevier

  8. Circulating Tumor Cell Phenotype Predicts Recurrence and Survival in Pancreatic Adenocarcinoma

    PubMed Central

    Poruk, Katherine E.; Valero, Vicente; Saunders, Tyler; Blackford, Amanda L.; Griffin, James F.; Poling, Justin; Hruban, Ralph H.; Anders, Robert A.; Herman, Joseph; Zheng, Lei; Rasheed, Zeshaan A.; Laheru, Daniel A.; Ahuja, Nita; Weiss, Matthew J.; Cameron, John L.; Goggins, Michael; Iacobuzio-Donahue, Christine A.; Wood, Laura D.; Wolfgang, Christopher L.

    2016-01-01

    Objective We assessed circulating tumor cells (CTCs) with epithelial and mesenchymal phenotypes as a potential prognostic biomarker for patients with pancreatic adenocarcinoma (PDAC). Background PDAC is the fourth leading cause of cancer death in the United States. There is an urgent need to develop biomarkers that predict patient prognosis and allow for better treatment stratification. Methods Peripheral and portal blood samples were obtained from 50 patients with PDAC before surgical resection and filtered using the Isolation by Size of Epithelial Tumor cells method. CTCs were identified by immunofluorescence using commercially available antibodies to cytokeratin, vimentin, and CD45. Results Thirty-nine patients (78%) had epithelial CTCs that expressed cytokeratin but not CD45. Twenty-six (67%) of the 39 patients had CTCs which also expressed vimentin, a mesenchymal marker. No patients had cytokeratin-negative and vimentin-positive CTCs. The presence of cytokeratin-positive CTCs (P < 0.01), but not mesenchymal-like CTCs (P = 0.39), was associated with poorer survival. The presence of cytokeratin-positive CTCs remained a significant independent predictor of survival by multi-variable analysis after accounting for other prognostic factors (P < 0.01). The detection of CTCs expressing both vimentin and cytokeratin was predictive of recurrence (P = 0.01). Among patients with cancer recurrence, those with vimentin-positive and cytokeratin-expressing CTCs had decreased median time to recurrence compared with patients without CTCs (P = 0.02). Conclusions CTCs are an exciting potential strategy for understanding the biology of metastases, and provide prognostic utility for PDAC patients. CTCs exist as heterogeneous populations, and assessment should include phenotypic identification tailored to characterize cells based on epithelial and mesenchymal markers. PMID:26756760

  9. Albumin concentrations plus neutrophil lymphocyte ratios for predicting overall survival after curative resection for gastric cancer

    PubMed Central

    Sun, Xiaowei; Wang, Juncheng; Liu, Jianjun; Chen, Shangxiang; Liu, Xuechao

    2016-01-01

    Background In patients with gastric cancer (GC), survival is poor, given the late diagnosis. Risk-stratifying these patients earlier could help improve care. We determined whether combining preoperative albumin concentration and the neutrophil lymphocyte ratio (COA-NLR) could predict overall survival (OS) better than other prognostic indexes. Methods We calculated the COA-NLR and other prognostic indexes with data obtained within 1 week before surgery in a retrospective analysis of patients with GC undergoing curative resection between September 2000 and November 2012. Patients with concentrations of hypoalbuminemia above 35 g/L and an NLR value of 2.3 or higher were given a score of 2. Patients with one of these conditions or neither were allocated scores of 1 or 0, respectively. Patients were monitored until July 2014. Results OS in the 873 eligible patients was 44.9% in patients with a COA-NLR score of 0, 29.8% in patients with a score of 1, and 20.3% in patients with a score of 2 (P<0.001). The COA-NLR score was independently associated with OS (hazard ratio, 1.35; 95% confidence interval, 1.12 to 1.63; P=0.002). Moreover, the area under the receiver operating characteristics curve was 0.62 for the COA-NLR, which was significantly higher (<0.001) than that of the NLR ratio (0.60), the Glasgow prognostic score (0.58), and the platelet lymphocyte ratio (0.54). The COA-NLR was especially accurate for patients with stage I–II GC and the three values (0, 1, and 2) divided patients into subgroups more accurately than did the other indexes (area under the curve value: 0.66, P<0.001). Conclusion The preoperative COA-NLR index is useful for predicting postoperative OS in patients with GC and can be used to guide targeted therapy. PMID:27536130

  10. Inferior vestibular neuritis.

    PubMed

    Kim, Ji-Soo; Kim, Hyo Jung

    2012-08-01

    Vestibular neuritis (VN) mostly involves the superior portion of the vestibular nerve and labyrinth. This study aimed to describe the clinical features of VN involving the inferior vestibular labyrinth and its afferents only. Of the 703 patients with a diagnosis of VN or labyrinthitis at Seoul National University Bundang Hospital from 2004 to 2010, we retrospectively recruited 9 patients (6 women, age range 15-75) with a diagnosis of isolated inferior VN. Diagnosis of isolated inferior VN was based on torsional downbeating spontaneous nystagmus, abnormal head-impulse test (HIT) for the posterior semicircular canal (PC), and abnormal cervical vestibular-evoked myogenic potentials (VEMP) in the presence of normally functioning horizontal and anterior semicircular canals, as determined by normal HIT and bithermal caloric tests. All patients presented with acute vertigo with nausea, vomiting, and imbalance. Three patients also had tinnitus and hearing loss in the involved side. The rotation axis of torsional downbeating spontaneous nystagmus was best aligned with that of the involved PC. HIT was also positive only for the involved PC. Cervical VEMP was abnormal in seven patients, and ocular VEMP was normal in all four patients tested. Ocular torsion and subjective visual vertical tests were mostly within the normal range. Since isolated inferior VN lacks the typical findings of much more prevalent superior VN, it may be mistaken for a central vestibular disorder. Recognition of this rare disorder may help avoid unnecessary workups in patients with acute vestibulopathy.

  11. Inferiority is compex

    NASA Astrophysics Data System (ADS)

    Wade, Jess

    2017-07-01

    In Inferior: How Science Got Women Wrong and the New Research That's Rewriting the Story, author Angela Saini puts forward the idea that bad science has been used to endorse the cultural prejudice that women are both biologically and psychologically second rate to men.

  12. Predictive Capability of Near-Infrared Fluorescence Angiography in Submental Perforator Flap Survival

    PubMed Central

    Matsui, Aya; Lee, Bernard T.; Winer, Joshua H.; Laurence, Rita G.; Frangioni, John V.

    2010-01-01

    Background Perforator flaps have become increasingly popular in reconstructive surgery as patients experience less donor-site morbidity than with conventional musculocutaneous flaps. Previously, our laboratory described the intraoperative use of near-infrared (NIR) fluorescence angiography for patient-specific perforator-flap design. This study evaluates the predictive capability of NIR fluorescence angiography for flap survival in submental flap reconstruction. Methods NIR angiography was performed using indocyanine green at 0, 0.5, 24, 48, and 72 h post-surgery after flap creation in 12 pigs. A single perforator artery was preserved during flap creation based on location (central or non-central) and dominance (dominant or non-dominant). Venous drainage, arterial perfusion, and perfused area as percentage of total flap were analyzed. Clinical assessments of perfusion were compared with those made using NIR imaging and histology. Results Use of NIR fluorescence angiography immediately after flap creation accurately predicted areas of perfusion at 72 h (p = 0.0013), compared to the initial clinical assessment (p = 0.3085). Identification of necrosis by histology at 72 h correlated with NIR findings of insufficient arterial perfusion immediately after flap creation. No statistically significant differences in perfusion metrics were detected based on location or dominance of the preserved perforator; however, flaps containing central perforators had a higher percent perfused area than those with non-central perforators. Conclusions The use of NIR angiography immediately after flap creation can predict areas of perfusion at 72 h. This predictive capability may permit intraoperative revision of compromised flaps that have a high likelihood of failure. PMID:21042109

  13. Transaminase Activity Predicts Survival in Patients with Head and Neck Cancer

    PubMed Central

    Takenaka, Yukinori; Takemoto, Norihiko; Yasui, Toshimichi; Yamamoto, Yoshifumi; Uno, Atsuhiko; Miyabe, Haruka; Ashida, Naoki; Shimizu, Kotaro; Nakahara, Susumu; Hanamoto, Atshushi; Fukusumi, Takahito; Michiba, Takahiro; Cho, Hironori; Yamamoto, Masashi; Inohara, Hidenori

    2016-01-01

    Various serum biomarkers have been developed for predicting head and neck squamous cell carcinoma (HNSCC) prognosis. However, none of them have been proven to be clinically significant. A recent study reported that the ratio of aspartate aminotransaminase (AST) to alanine aminotransaminase (ALT) had a prognostic effect on non-metastatic cancers. This study aimed to examine the effect of the AST/ALT ratio on the survival of patients with HNSCC. Clinical data of 356 patients with locoregionally advanced HNSCC were collected. The effect of the AST/ALT ratio on overall survival was analyzed using a Cox proportional hazard model. Moreover, recursive partitioning analysis (RPA) was used to divide the patients into groups on the basis of the clinical stage and AST/ALT ratio. The prognostic ability of this grouping was validated using an independent data set (N = 167). The AST/ALT ratio ranged from 0.42 to 4.30 (median, 1.42) and was a prognostic factor for overall survival that was independent of age, primary sites, and tumor stage (hazard ratio: 1.36, confidence interval: 1.08−1.68, P = 0.010). RPA divided patients with stage IVA into the following two subgroups: high AST/ALT (≥2.3) and low AST/ALT (<2.3) subgroups. The 5-year survival rate for patients with stage III, stage IVA with a low AST/ALT ratio, stage IVA with a high AST/ALT ratio, and stage IVB were 64.8%, 49.2%, 28.6%, and 33.3%, respectively (p < 0.001). Compared with the low AST/ALT group, the adjusted hazard ratio for death was 2.17 for high AST/ALT group (confidence interval: 1.02–.22 P = 0.045). The AST/ALT ratio was demonstrated to be a prognostic factor of HNSCC. The ratio subdivided patients with stage IVA into low- and high-risk groups. Moreover, intensified treatment for the high-risk group may be considered. PMID:27732629

  14. A novel molecular and clinical staging model to predict survival for patients with esophageal squamous cell carcinoma

    PubMed Central

    Zhao, Jun; Wei, Min; Zhu, Xinghua; He, Qi; Ling, Tianlong; Chen, Xiaoyan; Cao, Ziang; Zhang, Yixin; Liu, Lei; Shi, Minxin

    2016-01-01

    Current prognostic factors fail to accurately determine prognosis for patients with esophageal squamous cell carcinoma (ESCC) after surgery. Here, we constructed a survival prediction model for prognostication in patients with ESCC. Candidate molecular biomarkers were extracted from the Gene Expression Omnibus (GEO), and Cox regression analysis was performed to determine significant prognostic factors. The survival prediction model was constructed based on cluster and discriminant analyses in a training cohort (N=205), and validated in a test cohort (N=207). The survival prediction model consisting of two genes (UBE2C and MGP) and two clinicopathological factors (tumor stage and grade) was developed. This model could be used to accurately categorize patients into three groups in the test cohort. Both disease-free survival and overall survival differed among the diverse groups (P<0.05). In summary, we have developed and validated a predictive model that is based on two gene markers in conjunction with two clinicopathological variables, and which can accurately predict outcomes for ESCC patients after surgery. PMID:27556859

  15. Pretreatment Evaluation of Microcirculation by Dynamic Contrast-Enhanced Magnetic Resonance Imaging Predicts Survival in Primary Rectal Cancer Patients

    SciTech Connect

    DeVries, Alexander Friedrich; Piringer, Gudrun; Kremser, Christian; Judmaier, Werner; Saely, Christoph Hubert; Lukas, Peter; Öfner, Dietmar

    2014-12-01

    Purpose: To investigate the prognostic value of the perfusion index (PI), a microcirculatory parameter estimated from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which integrates information on both flow and permeability, to predict overall survival and disease-free survival in patients with primary rectal cancer. Methods and Materials: A total of 83 patients with stage cT3 rectal cancer requiring neoadjuvant chemoradiation were investigated with DCE-MRI before start of therapy. Contrast-enhanced dynamic T{sub 1} mapping was obtained, and a simple data analysis strategy based on the calculation of the maximum slope of the tissue concentration–time curve divided by the maximum of the arterial input function was used as a measure of tumor microcirculation (PI), which integrates information on both flow and permeability. Results: In 39 patients (47.0%), T downstaging (ypT0-2) was observed. During a mean (±SD) follow-up period of 71 ± 29 months, 58 patients (69.9%) survived, and disease-free survival was achieved in 45 patients (54.2%). The mean PI (PImean) averaged over the group of nonresponders was significantly higher than for responders. Additionally, higher PImean in age- and gender-adjusted analyses was strongly predictive of therapy nonresponse. Most importantly, PImean strongly and significantly predicted disease-free survival (unadjusted hazard ratio [HR], 1.85 [ 95% confidence interval, 1.35-2.54; P<.001)]; HR adjusted for age and sex, 1.81 [1.30-2.51]; P<.001) as well as overall survival (unadjusted HR 1.42 [1.02-1.99], P=.040; HR adjusted for age and sex, 1.43 [1.03-1.98]; P=.034). Conclusions: This analysis identifies PImean as a novel biomarker that is predictive for therapy response, disease-free survival, and overall survival in patients with primary locally advanced rectal cancer.

  16. A Transcriptional Fingerprint of Estrogen in Human Breast Cancer Predicts Patient Survival12

    PubMed Central

    Yu, Jianjun; Yu, Jindan; Cordero, Kevin E; Johnson, Michael D; Ghosh, Debashis; Rae, James M; Chinnaiyan, Arul M; Lippman, Marc E

    2008-01-01

    Estrogen signaling plays an essential role in breast cancer progression, and estrogen receptor (ER) status has long been a marker of hormone responsiveness. However, ER status alone has been an incomplete predictor of endocrine therapy, as some ER+ tumors, nevertheless, have poor prognosis. Here we sought to use expression profiling of ER+ breast cancer cells to screen for a robust estrogen-regulated gene signature that may serve as a better indicator of cancer outcome. We identified 532 estrogen-induced genes and further developed a 73-gene signature that best separated a training set of 286 primary breast carcinomas into prognostic subtypes by stepwise cross-validation. Notably, this signature predicts clinical outcome in over 10 patient cohorts as well as their respective ER+ subcohorts. Further, this signature separates patients who have received endocrine therapy into two prognostic subgroups, suggesting its specificity as a measure of estrogen signaling, and thus hormone sensitivity. The 73-gene signature also provides additional predictive value for patient survival, independent of other clinical parameters, and outperforms other previously reported molecular outcome signatures. Taken together, these data demonstrate the power of using cell culture systems to screen for robust gene signatures of clinical relevance. PMID:18231641

  17. 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

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

    SciTech Connect

    Wang, Pin; Wang, Yunshan; Hang, Bo; Zou, Xiaoping; Mao, Jian-Hua

    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 network 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.

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

    PubMed Central

    Hang, Bo; Zou, Xiaoping; Mao, Jian-Hua

    2016-01-01

    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 network 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. PMID:27419373

  20. High relative density of lymphatic vessels predicts poor survival in tongue squamous cell carcinoma.

    PubMed

    Seppälä, Miia; Pohjola, Konsta; Laranne, Jussi; Rautiainen, Markus; Huhtala, Heini; Renkonen, Risto; Lemström, Karl; Paavonen, Timo; Toppila-Salmi, Sanna

    2016-12-01

    Tongue cancer has a poor prognosis due to its early metastasis via lymphatic vessels. The present study aimed at evaluating lymphatic vessel density, relative density of lymphatic vessel, and diameter of lymphatic vessels and its predictive role in tongue cancer. Paraffin-embedded tongue and lymph node specimens (n = 113) were stained immunohistochemically with a polyclonal antibody von Willebrand factor, recognizing blood and lymphatic endothelium and with a monoclonal antibody podoplanin, recognizing lymphatic endothelium. The relative density of lymphatic vessels was counted by dividing the mean number of lymphatic vessels per microscopic field (podoplanin) by the mean number of all vessels (vWf) per microscopic field. The high relative density of lymphatic vessels (≥80 %) was associated with poor prognosis in tongue cancer. The relative density of lymphatic vessels predicted poor prognosis in the group of primary tumor size T1-T2 and in the group of non-metastatic cancer. The lymphatic vessel density and diameter of lymphatic vessels were not associated with tongue cancer survival. The relative density of lymphatic vessels might have clinically relevant prognostic impact. Further studies with increased number of patients are needed.

  1. Comparison of the RTS and ISS scores on prediction of survival chances in multiple trauma patients.

    PubMed

    Akhavan Akbari, G; Mohammadian, A

    2012-01-01

    Trauma represents the third cause of death after cardio vascular disease and tumors. Also in Iran, road accidents are one of the leading causes of death. Rapid evaluation of trauma severity and prediction of prognosis and mortality rate and probability of survival and rapid treatment of patients is necessary. One of the useful instruments for this is ISS and RTS scoring systems. This study evaluated 70 multi trauma patients in Fatemi trauma center affiliated to Ardabil University of medical science. This study was prospective study populations were 70 trauma patients admitted in Fatemi trauma center. During the II month, and patients data was collected by clinical evaluating of patients and follow up them and arranged as a questionnaire then related findings were evaluated by SPSS software. The average age of patients was 37.6±23.5 years and minimum and maximum age was 1 and 85 years. The most common involved group was 10-19 years (13 men and 1 woman). 81.4% of patients (57 cases were male) and 18.6% were female (13 cases). The most common causes of trauma was car accident with 64.2% frequency (43 cases) and then motorcycle accident with 16.4% frequency (11 cases) and all injured patient due to motorcycle accident compose the age group less than 40 years old. Also car accident had the highest frequency in both gender. Other causes of trauma were fall down with 13.5% frequency (9 cases) and under debris 5.9% (4 cases). Also from 70 studied patients, 67 cases (95.7%) had blunt trauma and 3 cases (4.3%) had penetrating trauma. The most penetrating trauma occurs in ages less than 50 years and was in the range of 30-50 years. The average RTS and ISS was 10.67±1.45 and 18.11±8.64, high and low scores of ISS existed in all age groups but a low score of RTS was highest in the children age group. The average length of ICU stay was 12.14±11.11 days. Overall mortality was 15.7 (11 cases). In this study, by the ISS increasing, the mortality rate also increased. But there

  2. Impact of tumour volume on prediction of progression-free survival in sinonasal cancer

    PubMed Central

    Hennersdorf, Florian; Mauz, Paul-Stefan; Adam, Patrick; Welz, Stefan; Sievert, Anne; Ernemann, Ulrike; Bisdas, Sotirios

    2015-01-01

    Background The present study aimed to analyse potential prognostic factors, with emphasis on tumour volume, in determining progression free survival (PFS) for malignancies of the nasal cavity and the paranasal sinuses. Patients and methods Retrospective analysis of 106 patients with primary sinonasal malignancies treated and followed-up between March 2006 and October 2012. Possible predictive parameters for PFS were entered into univariate and multivariate Cox regression analysis. Kaplan-Meier curve analysis included age, sex, baseline tumour volume (based on MR imaging), histology type, TNM stage and prognostic groups according to the American Joint Committee on Cancer (AJCC) classification. Receiver operating characteristic (ROC) curve analysis concerning the predictive value of tumour volume for recurrence was also conducted. Results The main histological subgroup consisted of epithelial tumours (77%). The majority of the patients (68%) showed advanced tumour burden (AJCC stage III–IV). Lymph node involvement was present in 18 cases. The mean tumour volume was 26.6 ± 21.2 cm3. The median PFS for all patients was 24.9 months (range: 2.5–84.5 months). The ROC curve analysis for the tumour volume showed 58.1% sensitivity and 75.4% specificity for predicting recurrence. Tumour volume, AJCC staging, T- and N- stage were significant predictors in the univariate analysis. Positive lymph node status and tumour volume remained significant and independent predictors in the multivariate analysis. Conclusions Radiological tumour volume proofed to be a statistically reliable predictor of PFS. In the multivariate analysis, T-, N- and overall AJCC staging did not show significant prognostic value. PMID:26401135

  3. Model predicting survival/exitus after traumatic brain injury: biomarker S100B 24h.

    PubMed

    Gonzćlez-Mao, M C; Repáraz-Andrade, A; Del Campo-Pérez, V; Alvarez-García, E; Vara-Perez, C; Andrade-Olivié, M A

    2011-01-01

    The enigma of Traumatic Brain Injury (TBI), reflected in recent scientific literature, is its uncertain consequences, variability of the final prognosis with apparently similar TBI, necessity for peripheral biomarkers, and more specific predictive models. To study the relationship between serum S100B and survival in TBI patients in various serious situations; the S100B level in patients without traumatic pathology or associated tumour, subjected to stressful situations such as neurological intensive care unit (NICU) stay; the possible overestimation caused by extracerebral liberation in TBI patients and associated polytraumatism; the predictive cutoffs to determine the most sensitive and specific chronology; and achieve a predictive prognostic model. Patients admitted to the NICU within 6 hours after TBI were selected. We measured: a) clinical: exitus yes/no; age and gender, traumatic mechanism, polytraumatism yes/no, GCS score, unconsciousness duration, amnesia duration, neurological focality, and surgical interventions; b) radiological: CT scan for radiological lesions; c) biochemical: serum SB100B at 6, 24, 48 and 72 hours after TBI and drug abuse detected in the urine; d) GOS on hospital discharge. N: 149 TBI patients, independent of polytraumatism, mean serum S100B at 6, 24, 48, and 72 hours: 2.1, 1.3, 1.2, and 0.6 microg/L, respectively; N: 124 without associated polytraumatism, S100B at 6, 24, 48, and 72 hours: 2.0, 1.4, 1.3, and 0.6 microg/L; N: 50 control I S100B 24 hours: 0.17 microg/L (0.04 - 0.56) and 25 healthy subjects S100B 0.057 microg/L (0.02-0.094). Significantly higher S100B levels are observed on exitus, with excellent TBI prognosis and evolution performance. Hospital stay in the NICU produces significant increases in S100B compared to healthy subjects, without invalidating it as a biomarker. Polytraumatism associated to TBI does not significantly alter S100B levels. S100B at 24 hours > or = 0.90 microg/L appears to predict unfavourable TBI

  4. A Mycobacterium avium subsp. paratuberculosis Predicted Serine Protease Is Associated with Acid Stress and Intraphagosomal Survival

    PubMed Central

    Kugadas, Abirami; Lamont, Elise A.; Bannantine, John P.; Shoyama, Fernanda M.; Brenner, Evan; Janagama, Harish K.; Sreevatsan, Srinand

    2016-01-01

    The ability to maintain intra-cellular pH is crucial for bacteria and other microbes to survive in diverse environments, particularly those that undergo fluctuations in pH. Mechanisms of acid resistance remain poorly understood in mycobacteria. Although, studies investigating acid stress in M. tuberculosis are gaining traction, few center on Mycobacterium avium subsp. paratuberculosis (MAP), the etiological agent of chronic enteritis in ruminants. We identified a MAP acid stress response network involved in macrophage infection. The central node of this network was MAP0403, a predicted serine protease that shared an 86% amino acid identity with MarP in M. tuberculosis. Previous studies confirmed MarP as a serine protease integral to maintaining intra-bacterial pH and survival in acid in vitro and in vivo. We show that MAP0403 is upregulated in infected macrophages and MAC-T cells that coincided with phagosome acidification. Treatment of mammalian cells with bafilomcyin A1, a potent inhibitor of phagosomal vATPases, diminished MAP0403 transcription. MAP0403 expression was also noted in acidic medium. A surrogate host, M. smegmatis mc2 155, was designed to express MAP0403 and when exposed to either macrophages or in vitro acid stress had increased bacterial cell viability, which corresponds to maintenance of intra-bacterial pH in acidic (pH = 5) conditions, compared to the parent strain. These data suggest that MAP0403 may be the equivalent of MarP in MAP. Future studies confirming MAP0403 as a serine protease and exploring its structure and possible substrates are warranted. PMID:27597934

  5. Texture analysis for survival prediction of pancreatic ductal adenocarcinoma patients with neoadjuvant chemotherapy

    NASA Astrophysics Data System (ADS)

    Chakraborty, Jayasree; Langdon-Embry, Liana; Escalon, Joanna G.; Allen, Peter J.; Lowery, Maeve A.; O'Reilly, Eileen M.; Do, Richard K. G.; Simpson, Amber L.

    2016-03-01

    Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death in the United States. The five-year survival rate for all stages is approximately 6%, and approximately 2% when presenting with distant disease.1 Only 10-20% of all patients present with resectable disease, but recurrence rates are high with only 5 to 15% remaining free of disease at 5 years. At this time, we are unable to distinguish between resectable PDAC patients with occult metastatic disease from those with potentially curable disease. Early classification of these tumor types may eventually lead to changes in initial management including the use of neoadjuvant chemotherapy or radiation, or in the choice of postoperative adjuvant treatments. Texture analysis is an emerging methodology in oncologic imaging for quantitatively assessing tumor heterogeneity that could potentially aid in the stratification of these patients. The present study derives several texture-based features from CT images of PDAC patients, acquired prior to neoadjuvant chemotherapy, and analyzes their performance, individually as well as in combination, as prognostic markers. A fuzzy minimum redundancy maximum relevance method with leave-one-image-out technique is included to select discriminating features from the set of extracted features. With a naive Bayes classifier, the proposed method predicts the 5-year overall survival of PDAC patients prior to neoadjuvant therapy and achieves the best results in terms of the area under the receiver operating characteristic curve of 0:858 and accuracy of 83:0% with four-fold cross-validation techniques.

  6. Overweight and obesity predict better overall survival rates in cancer patients with distant metastases.

    PubMed

    Tsang, Ngan Ming; Pai, Ping Ching; Chuang, Chi Cheng; Chuang, Wen Ching; Tseng, Chen Kan; Chang, Kai Ping; Yen, Tzu Chen; Lin, Jen Der; Chang, Joseph Tung Chieh

    2016-04-01

    Recent studies conducted in patients with chronic diseases have reported an inverse association between body mass index (BMI) and mortality. However, the question as to whether BMI may predict prognosis in patients with metastatic cancer remains open. We therefore designed the current retrospective study to investigate the potential association between BMI and overall survival (OS) in patients with distant metastases (DM) and a favorable performance status. Between 2000 and 2012, a total of 4010 cancer patients with DM who required radiotherapy (RT) and had their BMI measured at the initiation of RT were identified. The relation between BMI and OS was examined by univariate and multivariable analysis. The median OS time was 3.23 months (range: 0.1-122.17) for underweight patients, 6.08 months (range: 0.03-149.46) for normal-weight patients, 7.99 months (range: 0.07-158.01) for overweight patients, and 12.49 months (range, 0.2-164.1) for obese patients (log-rank: P < 0.001). Compared with normal-weight patients, both obese (HR = 0.676; 95% P < 0.001) and overweight individuals (HR = 0.84; P < 0.001) had a reduced risk of all-cause mortality in multivariable analysis. Conversely, underweight patients had a significantly higher risk of death from all causes (HR = 1.41; P < 0.001). Overweight and obesity are independent predictors of better OS in metastatic patients with a good performance status. Increased BMI may play a role to identify metastatic patients with superior survival outcome and exhibit a potential to encourage aggressive management in those patients even with metastases. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  7. Novel Inflammation-Based Prognostic Score for Predicting Survival in Patients with Metastatic Urothelial Carcinoma

    PubMed Central

    Su, Yu-Li; Hsieh, Meng-Che; Chiang, Po-Hui; Sung, Ming-Tse; Lan, Jui; Luo, Hao-Lun; Huang, Chun-Chieh; Huang, Cheng-Hua; Tang, Yeh; Rau, Kun-Ming

    2017-01-01

    Purpose We developed a novel inflammation-based model (NPS), which consisted of a neutrophil to lymphocyte ratio (NLR) and platelet count (PC), for assessing the prognostic role in patients with metastatic urothelial carcinoma (UC). Materials and Methods We performed a retrospective analysis of patients with metastatic UC who underwent systemic chemotherapy between January 1997 and December 2014 in Kaohsiung Chang Gung Memorial Hospital. The defined cutoff values for the NLR and PC were 3.0 and 400 × 103/μL, respectively. Patients were scored 1 for either an elevated NLR or PC, and 0 otherwise. The NPS was calculated by summing the scores, ranging from 0 to 2. The primary endpoint was overall survival (OS) by using Kaplan–Meier analysis. Multivariate Cox regression analysis was used to identify the independent prognostic factors for OS. Results In total, 256 metastatic UC patients were enrolled. Univariate analysis revealed that patients with either a high NLR or PC had a significantly shorter survival rate compared with those with a low NLR (P = .001) or PC (P < .0001). The median OS in patients with NPS 0, 1, and 2 was 19.0, 12.8, and 9.3 months, respectively (P < .0001). Multivariate analysis revealed that NPS, along with the histologic variant, liver metastasis, age, and white cell count, was an independent factor facilitating OS prediction (hazard ratio 1.64, 95% confidence interval 1.20–2.24, P = .002). Conclusion The NLR and PC are independent prognostic factors for OS in patients with metastatic UC. The NPS model has excellent discriminant ability for OS. PMID:28076369

  8. Plasma matrix metalloproteinase 1 improves the detection and survival prediction of esophageal squamous cell carcinoma

    PubMed Central

    Chen, Yu-Kuei; Tung, Chun-Wei; Lee, Jui-Ying; Hung, Yi-Chun; Lee, Chien-Hung; Chou, Shah-Hwa; Lin, Hung-Shun; Wu, Ming-Tsang; Wu, I-Chen

    2016-01-01

    This study aimed to identify noninvasive protein markers capable of detecting the presence and prognosis of esophageal squamous-cell carcinoma (ESCC). Analyzing microarray expression data collected from 17-pair ESCC specimens, we identified one protein, matrix metalloproteinase-1 (MMP1), as a possibly useful marker. Plasma MMP1 was then measured by enzyme-linked immunosorbent assay (ELISA) in 210 ESCC patients and 197 healthy controls. ESCC patients had higher mean levels of MMP1 than controls (8.7 ± 7.5 vs. 6.7 ± 4.9 ng/mL, p < 0.0001). Using the highest quartile level (9.67 ng/mL) as cut-off, we found a 9.0-fold risk of ESCC in those with higher plasma MMP1 after adjusting for covariates (95% confidence interval = 2.2, 36.0). Heavy smokers and heavy drinkers with higher plasma MMP1 had 61.4- and 31.0 times the risk, respectively, than non-users with lower MMP1. In the survival analysis, compared to those with MMP1 ≤ 9.67 ng/mL, ESCC patients with MMP1 > 9.67 ng/mL had a 48% increase in the risk of ESCC death (adjusted hazard ratio = 1.48; 95% CI = 1.04–2.10). In conclusion, plasma MMP1 may serve as a noninvasive marker of detecting the presence and predicting the survival of ESCC. PMID:27436512

  9. Is time to recurrence after hysterectomy predictive of survival in patients with early stage endometrial carcinoma?

    PubMed

    Robbins, Jared R; Yechieli, Raphael; Laser, Benjamin; Mahan, Meredith; Rasool, Nabila; Elshaikh, Mohamed A

    2012-10-01

    To determine the prognostic significance of time to recurrence (TTR) on overall survival (OS) and disease-specific survival (DSS) following recurrence in patients with stage I-II uterine endometrioid carcinoma. After IRB approval, we retrospectively identified 57 patients with recurrent endometrioid carcinoma who were initially treated for FIGO 1988 stages I-II between 1987 and 2009. The Kaplan-Meier approach and Cox regression analysis were used to estimate OS and DSS following recurrence and identify factors impacting outcomes. Median follow-up times were 54.8 months from hysterectomy and 19.8 months after recurrence. Median time to recurrence was 20.2 months. Twenty-eight (47%) patients had a recurrence<18 months after hysterectomy and 29 (53%) had a recurrence≥18 months. Both groups were evenly matched regarding initial pathological features and adjuvant treatments. The median OS and DSS in patients with TTR<18 months was shorter than those with TTR≥18 months, but not statistically significant (p=0.216). TTR did not impact outcomes after loco-regional recurrence, but for extrapelvic recurrence, a shorter TTR resulted in worse OS and DSS (p=0.03). On multivariate analysis, isolated loco-regional recurrence (HR 0.28, p=0.001) and salvage radiation therapy (HR 0.47, p=0.045) were statistically significant independent predictors of longer OS following recurrence. TTR as a continuous variable or dichotomized was not predictive of OS or DSS. In our study, the prognostic impact of time to recurrence was less important than the site of recurrence. While not prognostic for the entire cohort or for patients with loco-regional recurrence, TTR<18 months was associated with shorter OS and DSS after extrapelvic recurrence. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. Circulating tumor cells predict survival benefit from chemotherapy in patients with lung cancer

    PubMed Central

    Jiang, Han-Ling; Pan, Hong-Ming; Han, Wei-Dong

    2016-01-01

    Background This meta-analysis was to explore the clinical significance of circulating tumor cells (CTCs) in predicting the tumor response to chemotherapy and prognosis of patients with lung cancer. Methods We searched PubMed, Embase, Cochrane Database, Web of Science and reference lists of relevant articles. Our meta-analysis was performed by Stata software, version 12.0, with a random effects model. Risk ratio (RR), hazard ratio (HR) and 95% confidence intervals (CI) were used as effect measures. Results 8 studies, including 453 patients, were eligible for analyses. We showed that the disease control rate (DCR) in CTCs-negative patients was significantly higher than CTCs-positive patients at baseline (RR = 2.56, 95%CI [1.36, 4.82], p < 0.05) and during chemotherapy (RR = 9.08, CI [3.44, 23.98], p < 0.001). Patients who converted form CTC-negative to positive or persistently positive during chemotherapy had a worse disease progression than those with CTC-positive to negative or persistently negative (RR = 8.52, CI [1.66, 43.83], p < 0.05). Detection of CTCs at baseline and during chemotherapy also indicated poor overall survival (OS) (baseline: HR = 3.43, CI [2.21, 5.33], p<0.001; during chemotherapy: HR = 3.16, CI [2.23, 4.48], p < 0.001) and progression-free survival (PFS) (baseline: HR = 3.16, 95%CI [2.23, 4.48], p < 0.001; during chemotherapy: HR = 3.78, CI [2.33, 6.13], p < 0.001). Conclusions Detection of CTCs in peripheral blood indicates poor tumor response to chemotherapy and poor prognosis in patients with lung cancer. PMID:27588489

  11. NanOx, a new model to predict cell survival in the context of particle therapy

    NASA Astrophysics Data System (ADS)

    Cunha, M.; Monini, C.; Testa, E.; Beuve, M.

    2017-02-01

    Particle therapy is increasingly attractive for the treatment of tumors and the number of facilities offering it is rising worldwide. Due to the well-known enhanced effectiveness of ions, it is of utmost importance to plan treatments with great care to ensure tumor killing and healthy tissues sparing. Hence, the accurate quantification of the relative biological effectiveness (RBE) of ions, used in the calculation of the biological dose, is critical. Nevertheless, the RBE is a complex function of many parameters and its determination requires modeling. The approaches currently used have allowed particle therapy to thrive, but still show some shortcomings. We present herein a short description of a new theoretical framework, NanOx, to calculate cell survival in the context of particle therapy. It gathers principles from existing approaches, while addressing some of their weaknesses. NanOx is a multiscale model that takes the stochastic nature of radiation at nanometric and micrometric scales fully into account, integrating also the chemical aspects of radiation-matter interaction. The latter are included in the model by means of a chemical specific energy, determined from the production of reactive chemical species induced by irradiation. Such a production represents the accumulation of oxidative stress and sublethal damage in the cell, potentially generating non-local lethal events in NanOx. The complementary local lethal events occur in a very localized region and can, alone, lead to cell death. Both these classes of events contribute to cell death. The comparison between experimental data and model predictions for the V79 cell line show a good agreement. In particular, the dependence of the typical shoulders of cell survival curves on linear energy transfer are well described, but also the effectiveness of different ions, including the overkill effect. These results required the adjustment of a number of parameters compatible with the application of the model in

  12. Prognostic factors predictive of survival and local recurrence for extremity soft tissue sarcoma.

    PubMed Central

    Singer, S; Corson, J M; Gonin, R; Labow, B; Eberlein, T J

    1994-01-01

    OBJECTIVE: The authors sought to identify prognostic factors in the management of extremity soft tissue sarcoma. SUMMARY BACKGROUND DATA: The surgical management of soft tissue sarcoma has evolved because of advances in therapy, resulting in increased limb preservation and quality of life. However, identifying a subset of patients most likely to benefit from adjuvant chemotherapy has been difficult to achieve. METHODS: A retrospective analysis of a prospective data base of 182 patients with extremity sarcomas from 1970 to 1992 was performed. RESULTS: A histologic diagnosis of Ewing's sarcoma, synovial sarcoma, and angiosarcoma was associated with a 13-fold increased risk of death compared with liposarcoma, fibrosarcoma, and malignant peripheral nerve sheath histologic types after having adjusted for the other prognostic factors (p < 0.001). In addition to histologic type, high-grade sarcomas (p = 0.018), sarcomas greater than 10 cm in size (p = 0.006), and age at diagnosis (p = 0.016) were found to be important prognostic factors for survival but not for local recurrence. For the first time to their knowledge, the authors showed that mean mitotic activity has prognostic value after having adjusted for other prognostic factors, such as grade (p = 0.005). The only prognostic factors predictive for local recurrence were whether the patient presented with locally recurrent disease (p = 0.0001) or had microscopically positive margins (p = 0.052). CONCLUSIONS: The use of mitotic activity along with grade, size, histologic type, and age at diagnosis is prognostic for survival in extremity soft tissue sarcoma. The use of an objective pathologic feature, such as mean mitotic activity, is also useful in selecting patients for future systemic neoadjuvant or adjuvant trials and primary therapy. PMID:8129487

  13. Predicting survival for well-differentiated liposarcoma: the importance of tumor location.

    PubMed

    Smith, Caitlin A; Martinez, Steve R; Tseng, Warren H; Tamurian, Robert M; Bold, Richard J; Borys, Dariusz; Canter, Robert J

    2012-06-01

    Although well-differentiated liposarcoma (WD Lipo) is a low grade neoplasm with a negligible risk of metastatic disease, it can be locally aggressive. We hypothesized that survival for WD Lipo varies significantly based on tumor location. We identified 1266 patients with WD Lipo in the Surveillance, Epidemiology, and End Results database from 1988-2004. After excluding patients diagnosed by autopsy only, those lacking histologic confirmation, those lacking data on tumor location, and those with metastatic disease or unknown staging information, we arrived at a final study cohort of 1130 patients. Clinical, pathologic, and treatment variables were analyzed for their association with overall survival (OS) and disease-specific survival (DSS) using Kaplan-Meier analysis and Cox proportional hazards multivariate models. Mean age was 61 y (± 14.6), 72.2% were white, and 60.4% were male. Eighty-one percent of patients were treated with surgical therapy alone, 4.6% were treated with radiotherapy (RT) alone, and 12.9% were treated with both surgery and RT. Extremity location was most common (41.6%), followed by trunk (29%), retroperitoneal/intra-abdominal (RIA, 21.6%), thorax (4.2%), and head/neck (3.6%). With a median follow-up of 45 mo, median OS was 115 mo (95% confidence interval [CI] 92-138 mo) for RIA tumors compared to not reached for other tumor locations (P = 0.002). On multivariate analysis, increasing age and RIA location both predicted worse OS and DSS while tumor size, race, sex, receipt of RT, and Surveillance, Epidemiology, and End Results (SEER) stage did not. Tumor size became a significant predictor of worse DSS, but not OS, only when site, SEER stage, and extent of resection were removed from the multivariate model. Non-RIA locations, including extremity, experienced statistically similar OS, but 5-y DSS for trunk location was intermediate [92.3%, (95% CI 88.5%-96.1%) compared with 98.0% (95% CI, 96.2%-99.8%) for extremity and 86.6 (95% CI 81

  14. NUCLEAR EGFR PROTEIN EXPRESSION PREDICTS POOR SURVIVAL IN EARLY STAGE NON-SMALL CELL LUNG CANCER

    PubMed Central

    Traynor, Anne M.; Weigel, Tracey L.; Oettel, Kurt R.; Yang, David T.; Zhang, Chong; Kim, KyungMann; Salgia, Ravi; Iida, Mari; Brand, Toni M.; Hoang, Tien; Campbell, Toby C.; Hernan, Hilary R.; Wheeler, Deric L.

    2013-01-01

    Introduction Nuclear EGFR (nEGFR) has been identified in various human tumor tissues, including cancers of the breast, ovary, oropharynx, and esophagus, and has predicted poor patient outcomes. We sought to determine if protein expression of nEGFR is prognostic in early stage non-small cell lung cancer (NSCLC). Methods Resected stage I and II NSCLC specimens were evaluated for nEGFR protein expression using immunohistochemistry (IHC). Cases with at least one replicate core containing ≥5% of tumor cells demonstrating strong dot-like nucleolar EGFR expression were scored as nEGFR positive. Results Twenty-three (26.1% of the population) of 88 resected specimens stained positively for nEGFR. Nuclear EGFR protein expression was associated with higher disease stage (45.5% of stage II vs. 14.5% of stage I; p=0.023), histology (41.7% in squamous cell carcinoma vs. 17.1% in adenocarcinoma; p=0.028), shorter progression-free survival (PFS) (median PFS 8.7 months [95% CI 5.1–10.7 mo] for nEGFR positive vs. 14.5 months [95% CI 9.5–17.4 mo] for nEGFR negative; hazard ratio (HR) of 1.89 [95% CI 1.15–3.10]; p=0.011), and shorter overall survival (OS) (median OS 14.1 months [95% CI 10.3–22.7 mo] for nEGFR positive vs. 23.4 months [95% CI 20.1–29.4 mo] for nEGFR negative; HR of 1.83 [95% CI 1.12–2.99]; p=0.014). Conclusions Expression of nEGFR protein was associated with higher stage and squamous cell histology, and predicted shorter PFS and OS, in this patient cohort. Nuclear EGFR serves as a useful independent prognostic variable and as a potential therapeutic target in NSCLC. PMID:23628526

  15. Consciousness levels one week after admission to a palliative care unit improve survival prediction in advanced cancer patients.

    PubMed

    Tsai, Jaw-Shiun; Chen, Chao-Hsien; Wu, Chih-Hsun; Chiu, Tai-Yuan; Morita, Tatsuya; Chang, Chin-Hao; Hung, Shou-Hung; Lee, Ya-Ping; Chen, Ching-Yu

    2015-02-01

    Consciousness is an important factor of survival prediction in advanced cancer patients. However, effects on survival of changes over time in consciousness in advanced cancer patients have not been fully explored. This study evaluated changes in consciousness after admission to a palliative care unit and their correlation with prognosis in terminal cancer patients. This is a prospective observational study. From a palliative care unit in Taiwan, 531 cancer patients (51.8% male) were recruited. Consciousness status was assessed at admission and one week afterwards and recorded as normal or impaired. The mean age was 65.28±13.59 years, and the average survival time was 23.41±37.69 days. Patients with normal consciousness at admission (n=317) had better survival than those with impaired consciousness at admission (n=214): (17.0 days versus 6.0 days, p<0.001). In the analysis on survival within one week after admission, those with normal consciousness at admission had a higher percentage of survival than the impaired (78.9% versus 44.3%, p<0.001). Patients were further classified into four groups according to consciousness levels: (1) normal at admission and one week afterwards, (2) impaired at admission but normal one week afterwards, (3) normal at admission but impaired one week afterwards, and (4) impaired both at admission and one week afterwards. The former two groups had significantly better survival than the latter two groups: (median survival counted from day 7 after admission), 25.5, 27.0, 7.0, and 7.0 days, respectively. Consciousness levels one week after admission should be integrated into survival prediction in advanced cancer patients.

  16. Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study

    PubMed Central

    Ganly, Ian; Amit, Moran; Kou, Lei; Palmer, Frank L.; Migliacci, Jocelyn; Katabi, Nora; Yu, Changhong; Kattan, Michael W.; Binenbaum, Yoav; Sharma, Kanika; Naomi, Ramer; Abib, Agbetoba; Miles, Brett; Yang, Xinjie; Lei, Delin; Bjoerndal, Kristine; Godballe, Christian; Mücke, Thomas; Wolff, Klaus-Dietrich; Fliss, Dan; Eckardt, André M.; Chiara, Copelli; Sesenna, Enrico; Ali, Safina; Czerwonka, Lukas; Goldstein, David P.; Gil, Ziv; Patel, Snehal G.

    2016-01-01

    Background Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome. Methods ACC patients managed at 10 international centers were identified. Patient, tumor, and treatment characteristics were recorded and an international collaborative dataset created. Multivariable competing risk models were then built to predict the 10 year recurrence free probability (RFP), distant recurrence free probability (DRFP), overall survival (OS) and cancer specific mortality (CSM). All predictors of interest were added in the starting full models before selection, including age, gender, tumor site, clinical T stage, perineural invasion, margin status, pathologic N-status, and M-status. Stepdown method was used in model selection to choose predictive variables. An external dataset of 99 patients from 2 other institutions was used to validate the nomograms. Findings Of 438 ACC patients, 27.2% (119/438) died from ACC and 38.8% (170/438) died of other causes. Median follow-up was 56 months (range 1–306). The nomogram for OS had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N-status and M-status) with a concordance index (CI) of 0.71. The nomogram for CSM had the same variables, except margin status, with a concordance index (CI) of 0.70. The nomogram for RFP had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N status and perineural invasion) (CI 0.66). The nomogram for DRFP had 6 variables (gender, clinical T stage, tumor site, pathologic N-status, perineural invasion and margin status) (CI 0.64). Concordance index for the external validation set were 0.76, 0.72, 0.67 and 0.70 respectively. Interpretation Using an international collaborative database we have created the first nomograms which

  17. Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study.

    PubMed

    Ganly, Ian; Amit, Moran; Kou, Lei; Palmer, Frank L; Migliacci, Jocelyn; Katabi, Nora; Yu, Changhong; Kattan, Michael W; Binenbaum, Yoav; Sharma, Kanika; Naomi, Ramer; Abib, Agbetoba; Miles, Brett; Yang, Xinjie; Lei, Delin; Bjoerndal, Kristine; Godballe, Christian; Mücke, Thomas; Wolff, Klaus-Dietrich; Fliss, Dan; Eckardt, André M; Chiara, Copelli; Sesenna, Enrico; Ali, Safina; Czerwonka, Lukas; Goldstein, David P; Gil, Ziv; Patel, Snehal G

    2015-12-01

    Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome. ACC patients managed at 10 international centers were identified. Patient, tumor, and treatment characteristics were recorded and an international collaborative dataset created. Multivariable competing risk models were then built to predict the 10 year recurrence free probability (RFP), distant recurrence free probability (DRFP), overall survival (OS) and cancer specific mortality (CSM). All predictors of interest were added in the starting full models before selection, including age, gender, tumor site, clinical T stage, perineural invasion, margin status, pathologic N-status, and M-status. Stepdown method was used in model selection to choose predictive variables. An external dataset of 99 patients from 2 other institutions was used to validate the nomograms. Of 438 ACC patients, 27.2% (119/438) died from ACC and 38.8% (170/438) died of other causes. Median follow-up was 56 months (range 1-306). The nomogram for OS had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N-status and M-status) with a concordance index (CI) of 0.71. The nomogram for CSM had the same variables, except margin status, with a concordance index (CI) of 0.70. The nomogram for RFP had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N status and perineural invasion) (CI 0.66). The nomogram for DRFP had 6 variables (gender, clinical T stage, tumor site, pathologic N-status, perineural invasion and margin status) (CI 0.64). Concordance index for the external validation set were 0.76, 0.72, 0.67 and 0.70 respectively. Using an international collaborative database we have created the first nomograms which estimate outcome in individual patients with ACC

  18. Cardiac Dysautonomia Predicts Long-Term Survival in Hereditary Transthyretin Amyloidosis After Liver Transplantation.

    PubMed

    Algalarrondo, Vincent; Antonini, Teresa; Théaudin, Marie; Chemla, Denis; Benmalek, Anouar; Lacroix, Catherine; Castaing, Denis; Cauquil, Cécile; Dinanian, Sylvie; Eliahou, Ludivine; Samuel, Didier; Adams, David; Le Guludec, Dominique; Slama, Michel S; Rouzet, François

    2016-12-01

    This study sought to compare techniques evaluating cardiac dysautonomia and predicting the risk of death of patients with hereditary transthyretin amyloidosis (mATTR) after liver transplantation (LT). mATTR is a multisystemic disease involving mainly the heart and the peripheral nervous system. LT is the reference treatment, and pre-operative detection of high-risk patients is critical. Cardiovascular dysautonomia is commonly encountered in ATTR and may affect patient outcome, although it is not known yet which technique should be used in the field to evaluate it. In a series of 215 consecutive mATTR patients who underwent LT, cardiac dysautonomia was assessed by a dedicated clinical score, time-domain heart rate variability, (123)-meta-iodobenzylguanidine heart/mediastinum ((123)-MIBG H/M) ratio on scintigraphy, and heart rate response to atropine (HRRA). Patient median age was 43 years, 62% were male and 69% carried the Val30Met mutation. Cardiac dysautonomia was documented by at least 1 technique for all patients but 6 (97%). In univariate analysis, clinical score, (123)-MIBG H/M ratio and HRRA were associated with mortality but not heart rate variability. The (123)-MIBG H/M ratio and HRRA had greater area under the curve (AUC) of receiver-operating characteristic curves than clinical score and heart rate variability (AUC: 0.787, 0.748, 0.656, and 0.523, respectively). Multivariate score models were then built using the following variables: New York Heart Association functional class, interventricular septum thickness, and either (123-)MIBG H/M ratio (SMIBG) or HRRA (Satropine). AUC of SMIBG and Satropine were greater than AUC of univariate models, although nonsignificantly (AUC: 0.798 and 0.799, respectively). Predictive powers of SMIBG, Satropine, and a reference clinical model (AUC: 0.785) were similar. Evaluation of cardiac dysautonomia is a valuable addition for predicting survival of mATTR patients following LT. Among the different techniques that

  19. Lung function predicts survival in a cohort of asbestos cement workers.

    PubMed

    Moshammer, H; Neuberger, Manfred

    2009-01-01

    To study the predictive power of respiratory screening examinations a cohort of asbestos workers was followed from active work in an asbestos cement plant until death. From a cohort with data on individual exposure since first employment 309 workers who had a preventive medical examination in 1989/1990 were observed until death or the end of 2006. The impact of asbestos exposure (fibre years) and of smoking history on lung function was examined by linear regression, on specific causes of death and total mortality by Cox regression. The prognostic value of lung function, chest X-ray, and various clinical findings regarding total mortality was also examined by Cox regression. Lung function proved to be the best predictor of survival apart from current smoking. Depending on the lung function variable an impairment by the interquartile range resulted in a hazard ratio of 1.5-1.6 while for current smokers it was 2.3. An increase of 70 fibre years (interquartile range) led to a hazard ratio of only 1.1. Lung function was influenced by asbestos exposure, current (but not former) smoking, and by pathological X-ray findings. The risk for pleural mesothelioma was dominated by time since first exposure to crocydolite in the pipe factory while the risk for bronchial cancer increased with smoking and total fibre years. An unexpected finding was an increase of gastric cancer in asbestos cement workers. Lung function decrease predicts risk of premature death better than exposure history and regular spirometry should therefore be offered as primary screening to all former asbestos workers. In workers with a history of high cumulative exposure or rapid lung function decrease or radiological signs (diffuse pleural thickening or small irregular opacities) more sensitive techniques (high resolution computer tomography) need to be applied. All smokers with a history of asbestos exposure should be given free smoking cessation therapy to prevent premature death and lung cancer in

  20. Fetuin A/nutritional status predicts cardiovascular outcomes and survival in hemodialysis patients.

    PubMed

    Chen, Hung-Yuan; Chiu, Yen-Ling; Hsu, Shih-Ping; Pai, Mei-Fen; Yang, Ju-Yeh; Peng, Yu-Sen

    2014-01-01

    Fetuin A - a predictor of cardiovascular (CV) outcomes in dialysis patients - is correlated with over-nutrition in the general population. Whether fetuin A and nutritional status interact with each other to alter CV outcomes and survival in hemodialysis (HD) patients remains unknown. We performed a prospective study on 388 prevalent HD patients. We used the geriatric nutritional risk index (GNRI) for the evaluation of nutritional status. Study outcomes included the occurrence of CV event, CV death, and all-cause mortality during follow-up; interactions between parameters for predicting outcomes were assessed by the interaction terms in a Cox regression model. Overall, 131 patients experienced CV events and 92 patients died, with 51 CV deaths. HD patients with higher fetuin A levels had lower numbers of CV events (adjusted hazard ratio [HR], 0.9; 0.81-0.99) and all-cause mortality (adjusted HR, 0.97; 0.91-0.99). However, patients with higher GNRI had lower all-cause mortality (adjusted HR, 0.79; 0.51-0.98, for every 10-unit increase). Fetuin A levels and GNRI showed a significant interaction in the prediction of CV events (adjusted HR, 1.01; 1.008-1.02) but not for all-cause or CV mortality. In patients with poor nutritional status, higher fetuin A levels were associated with fewer CV events; however, in contrast, in subjects with better nutritional status, higher fetuin A levels appeared to lead to a higher number of CV events. Fetuin A showed a remarkable interaction with nutritional status in evaluating the risks of CV morbidities in prevalent HD patients. © 2014 S. Karger AG, Basel.

  1. What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study

    PubMed Central

    Goldman, Noreen; Glei, Dana A; Weinstein, Maxine

    2016-01-01

    Despite myriad efforts among social scientists, epidemiologists, and clinicians to identify variables with strong linkages to mortality, few researchers have evaluated statistically the relative strength of a comprehensive set of predictors of survival. Here, we determine the strongest predictors of five-year mortality in four national, prospective studies of older adults. We analyze nationally representative surveys of older adults in four countries with similar levels of life expectancy: England (n = 6113, ages 52+), the US (n = 2023, ages 50+), Costa Rica (n = 2694, ages 60+), and Taiwan (n = 1032, ages 53+). Each survey includes a broad set of demographic, social, health, and biological variables that have been shown previously to predict mortality. We rank 57 predictors, 25 of which are available in all four countries, net of age and sex. We use the area under the receiver operating characteristic curve and assess robustness with additional discrimination measures. We demonstrate consistent findings across four countries with different cultural traditions, levels of economic development, and epidemiological transitions. Self-reported measures of instrumental activities of daily living limitations, mobility limitations, and overall self-assessed health are among the top predictors in all four samples. C-reactive protein, additional inflammatory markers, homocysteine, serum albumin, three performance assessments (gait speed, grip strength, and chair stands), and exercise frequency also discriminate well between decedents and survivors when these measures are available. We identify several promising candidates that could improve mortality prediction for both population-based and clinical populations. Better prognostic tools are likely to provide researchers with new insights into the behavioral and biological pathways that underlie social stratification in health and may allow physicians to have more informed discussions with patients about end-of-life treatment

  2. SIRT1 and c-Myc Promote Liver Tumor Cell Survival and Predict Poor Survival of Human Hepatocellular Carcinomas

    PubMed Central

    Jang, Kyu Yun; Noh, Sang Jae; Lehwald, Nadja; Tao, Guo-Zhong; Bellovin, David I.; Park, Ho Sung; Moon, Woo Sung; Felsher, Dean W.; Sylvester, Karl G.

    2012-01-01

    The increased expression of SIRT1 has recently been identified in numerous human tumors and a possible correlation with c-Myc oncogene has been proposed. However, it remains unclear whether SIRT1 functions as an oncogene or tumor suppressor. We sought to elucidate the role of SIRT1 in liver cancer under the influence of c-Myc and to determine the prognostic significance of SIRT1 and c-Myc expression in human hepatocellular carcinoma. The effect of either over-expression or knock down of SIRT1 on cell proliferation and survival was evaluated in both mouse and human liver cancer cells. Nicotinamide, an inhibitor of SIRT1, was also evaluated for its effects on liver tumorigenesis. The prognostic significance of the immunohistochemical detection of SIRT1 and c-Myc was evaluated in 154 hepatocellular carcinoma patients. SIRT1 and c-Myc regulate each other via a positive feedback loop and act synergistically to promote hepatocellular proliferation in both mice and human liver tumor cells. Tumor growth was significantly inhibited by nicotinamide in vivo and in vitro. In human hepatocellular carcinoma, SIRT1 expression positively correlated with c-Myc, Ki67 and p53 expression, as well as high á-fetoprotein level. Moreover, the expression of SIRT1, c-Myc and p53 were independent prognostic indicators of hepatocellular carcinoma. In conclusion, this study demonstrates that SIRT1 expression supports liver tumorigenesis and is closely correlated with oncogenic c-MYC expression. In addition, both SIRT1 and c-Myc may be useful prognostic indicators of hepatocellular carcinoma and SIRT1 targeted therapy may be beneficial in the treatment of hepatocellular carcinoma. PMID:23024800

  3. Convergent RANK- and c-Met-mediated signaling components predict survival of patients with prostate cancer: an interracial comparative study.

    PubMed

    Hu, Peizhen; Chung, Leland W K; Berel, Dror; Frierson, Henry F; Yang, Hua; Liu, Chunyan; Wang, Ruoxiang; Li, Qinlong; Rogatko, Andre; Zhau, Haiyen E

    2013-01-01

    We reported (PLoS One 6 (12):e28670, 2011) that the activation of c-Met signaling in RANKL-overexpressing bone metastatic LNCaP cell and xenograft models increased expression of RANK, RANKL, c-Met, and phosphorylated c-Met, and mediated downstream signaling. We confirmed the significance of the RANK-mediated signaling network in castration resistant clinical human prostate cancer (PC) tissues. In this report, we used a multispectral quantum dot labeling technique to label six RANK and c-Met convergent signaling pathway mediators simultaneously in formalin fixed paraffin embedded (FFPE) tissue specimens, quantify the intensity of each expression at the sub-cellular level, and investigated their potential utility as predictors of patient survival in Caucasian-American, African-American and Chinese men. We found that RANKL and neuropilin-1 (NRP-1) expression predicts survival of Caucasian-Americans with PC. A Gleason score ≥ 8 combined with nuclear p-c-Met expression predicts survival in African-American PC patients. Neuropilin-1, p-NF-κB p65 and VEGF are predictors for the overall survival of Chinese men with PC. These results collectively support interracial differences in cell signaling networks that can predict the survival of PC patients.

  4. Survival Prediction Model Using Clinico-Pathologic Characteristics for Nonsmall Cell Lung Cancer Patients After Curative Resection.

    PubMed

    Wu, Ching-Yang; Fu, Jui-Ying; Wu, Ching-Feng; Hsieh, Ming-Ju; Liu, Yun-Hen; Wu, Yi-Cheng; Yang, Cheng-Ta; Tsai, Ying-Huang

    2015-11-01

    The current TNM staging system did not provide disease relapse information. The aim of study was try to establish a predictive survival model for disease and overall survival in nonsmall cell lung cancer patients who presented as resectable disease and to develop a reference for follow-up imaging tool selection.From January 2005 to December 2011, 442 patients who initially presented as resectable disease (stages I-IIIa) and received anatomic resection and mediastinal lymph node dissection were included in the study.Medical charts were thoroughly reviewed and clinico-pathologic factors were collected and analyzed.Visceral pleural invasion, tumor size >5 cm, and postoperative adjuvant therapy were identified as risk factors for poorer disease-free survival. The 5-year disease-free survival from score 0 to 3 was 68.7%, 46.6%, 31.9%, and 26.1%, respectively. The disease relapse percentage for scores 0 to 3 were 26.49%, 50.61%, 65.05%, and 73.81%, respectively. For analysis of overall survival, age >60 years, tumor size >3 cm, and total metastatic lymph node ratio >0.05 were correlated to worse overall survival. Because greater age may be correlated with poor general condition, we re-scored risk factors that correlated to disease severity that ranging from 0 to 2. The 5-year overall survival range from score 0 to 2 was 56.3%, 43.1%, and 13.1%, respectively.Poor prognostic factors correlated to disease-free survival were tumor size >5 cm, visceral pleural invasion, and patients needing to receive postoperative adjuvant therapy. Disease-free survival of resectable nonsmall cell lung cancer patients and disease relapse can be stratified by these 3 factors. Chest tomography may be recommended for patients with 1 or more poor disease-free survival risk factors.

  5. Go/No Go task performance predicts cortical thickness in the caudal inferior frontal gyrus in young adults with and without ADHD.

    PubMed

    Newman, Erik; Jernigan, Terry L; Lisdahl, Krista M; Tamm, Leanne; Tapert, Susan F; Potkin, Steven G; Mathalon, Daniel; Molina, Brooke; Bjork, James; Castellanos, F Xavier; Swanson, James; Kuperman, Joshua M; Bartsch, Hauke; Chen, Chi-Hua; Dale, Anders M; Epstein, Jeffery N; Group, Mta Neuroimaging

    2016-09-01

    Response inhibition deficits are widely believed to be at the core of Attention-Deficit Hyperactivity Disorder (ADHD). Several studies have examined neural architectural correlates of ADHD, but research directly examining structural correlates of response inhibition is lacking. Here we examine the relationship between response inhibition as measured by a Go/No Go task, and cortical surface area and thickness of the caudal inferior frontal gyrus (cIFG), a region implicated in functional imaging studies of response inhibition, in a sample of 114 young adults with and without ADHD diagnosed initially during childhood. We used multiple linear regression models to test the hypothesis that Go/No Go performance would be associated with cIFG surface area or thickness. Results showed that poorer Go/No Go performance was associated with thicker cIFG cortex, and this effect was not mediated by ADHD status or history of substance use. However, independent of Go/No Go performance, persistence of ADHD symptoms and more frequent cannabis use were associated with thinner cIFG. Go/No Go performance was not associated with cortical surface area. The association between poor inhibitory functioning and thicker cIFG suggests that maturation of this region may differ in low performing participants. An independent association of persistent ADHD symptoms and frequent cannabis use with thinner cIFG cortex suggests that distinct neural mechanisms within this region may play a role in inhibitory function, broader ADHD symptomatology, and cannabis use. These results contribute to Research Domain Criteria (RDoC) by revealing novel associations between neural architectural phenotypes and basic neurobehavioral processes measured dimensionally.

  6. Loss of Cytoplasmic CDK1 Predicts Poor Survival in Human Lung Cancer and Confers Chemotherapeutic Resistance

    PubMed Central

    Zhang, Chunyu; Elkahloun, Abdel G.; Robertson, Matthew; Gills, Joell J.; Tsurutani, Junji; Shih, Joanna H.; Fukuoka, Junya; Hollander, M. Christine; Harris, Curtis C.; Travis, William D.; Jen, Jin; Dennis, Phillip A.

    2011-01-01

    The dismal lethality of lung cancer is due to late stage at diagnosis and inherent therapeutic resistance. The incorporation of targeted therapies has modestly improved clinical outcomes, but the identification of new targets could further improve clinical outcomes by guiding stratification of poor-risk early stage patients and individualizing therapeutic choices. We hypothesized that a sequential, combined microarray approach would be valuable to identify and validate new targets in lung cancer. We profiled gene expression signatures during lung epithelial cell immortalization and transformation, and showed that genes involved in mitosis were progressively enhanced in carcinogenesis. 28 genes were validated by immunoblotting and 4 genes were further evaluated in non-small cell lung cancer tissue microarrays. Although CDK1 was highly expressed in tumor tissues, its loss from the cytoplasm unexpectedly predicted poor survival and conferred resistance to chemotherapy in multiple cell lines, especially microtubule-directed agents. An analysis of expression of CDK1 and CDK1-associated genes in the NCI60 cell line database confirmed the broad association of these genes with chemotherapeutic responsiveness. These results have implications for personalizing lung cancer therapy and highlight the potential of combined approaches for biomarker discovery. PMID:21887332

  7. Geriatric assessment predicts survival and toxicities in elderly myeloma patients: an International Myeloma Working Group report

    PubMed Central

    Bringhen, Sara; Mateos, Maria-Victoria; Larocca, Alessandra; Facon, Thierry; Kumar, Shaji K.; Offidani, Massimo; McCarthy, Philip; Evangelista, Andrea; Lonial, Sagar; Zweegman, Sonja; Musto, Pellegrino; Terpos, Evangelos; Belch, Andrew; Hajek, Roman; Ludwig, Heinz; Stewart, A. Keith; Moreau, Philippe; Anderson, Kenneth; Einsele, Hermann; Durie, Brian G. M.; Dimopoulos, Meletios A.; Landgren, Ola; San Miguel, Jesus F.; Richardson, Paul; Sonneveld, Pieter; Rajkumar, S. Vincent

    2015-01-01

    We conducted a pooled analysis of 869 individual newly diagnosed elderly patient data from 3 prospective trials. At diagnosis, a geriatric assessment had been performed. An additive scoring system (range 0-5), based on age, comorbidities, and cognitive and physical conditions, was developed to identify 3 groups: fit (score = 0, 39%), intermediate fitness (score = 1, 31%), and frail (score ≥2, 30%). The 3-year overall survival was 84% in fit, 76% in intermediate-fitness (hazard ratio [HR], 1.61; P = .042), and 57% in frail (HR, 3.57; P < .001) patients. The cumulative incidence of grade ≥3 nonhematologic adverse events at 12 months was 22.2% in fit, 26.4% in intermediate-fitness (HR, 1.23; P = .217), and 34.0% in frail (HR, 1.74; P < .001) patients. The cumulative incidence of treatment discontinuation at 12 months was 16.5% in fit, 20.8% in intermediate-fitness (HR, 1.41; P = .052), and 31.2% in frail (HR, 2.21; P < .001) patients. Our frailty score predicts mortality and the risk of toxicity in elderly myeloma patients. The International Myeloma Working group proposes this score for the measurement of frailty in designing future clinical trials. These trials are registered at www.clinicaltrials.gov as #NCT01093136 (EMN01), #NCT01190787 (26866138MMY2069), and #NCT01346787 (IST-CAR-506). PMID:25628469

  8. Preoperative inflammation markers and IDH mutation status predict glioblastoma patient survival.

    PubMed

    Wang, Peng-Fei; Song, Hong-Wang; Cai, Hong-Qing; Kong, Ling-Wei; Yao, Kun; Jiang, Tao; Li, Shou-Wei; Yan, Chang-Xiang

    2017-02-09

    Recent studies suggest that inflammation response biomarkers are prognostic indicators of solid tumor outcomes. Here, we quantify the prognostic value of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) in glioblastomas (GBMs), taking into consideration the role of the isocitrate dehydrogenase (IDH) mutation status. We examined 141 primary glioblastomas (pGBMs) and 25 secondary glioblastomas (sGBMs). NLRs, PLRs, and LMRs were calculated before surgery. IDH mutations were detected immunohistochemically after tumor resection, and patients' clinical outcomes were analyzed after classification into GBM, pGBM, and IDH-wild type glioblastoma (IDH-wt GBM) groups. To make comparisons, we set cutoffs for NLR, PLR and LMR of 4.0, 175.0, and 3.7, respectively. In a multivariate analysis, both NLR (HR=1.712, 95% CI 1.026-2.858, p=0.040) and PLR (HR=2.051, 95% CI 1.288-3.267, p=0.002) had independent prognostic value. While a low NLR was associated with a better prognosis only in the IDH-wt GBM group, PLR was predictive of patient survival in the GBM, pGBM, and IDH-wt GBM groups. By contrast, LMR exhibited no prognostic value for any of the 3 types of GBM.

  9. A CpG-methylation-based assay to predict survival in clear cell renal cell carcinoma

    PubMed Central

    Wei, Jin-Huan; Haddad, Ahmed; Wu, Kai-Jie; Zhao, Hong-Wei; Kapur, Payal; Zhang, Zhi-Ling; Zhao, Liang-Yun; Chen, Zhen-Hua; Zhou, Yun-Yun; Zhou, Jian-Cheng; Wang, Bin; Yu, Yan-Hong; Cai, Mu-Yan; Xie, Dan; Liao, Bing; Li, Cai-Xia; Li, Pei-Xing; Wang, Zong-Ren; Zhou, Fang-Jian; Shi, Lei; Liu, Qing-Zuo; Gao, Zhen-Li; He, Da-Lin; Chen, Wei; Hsieh, Jer-Tsong; Li, Quan-Zhen; Margulis, Vitaly; Luo, Jun-Hang

    2015-01-01

    Clear cell renal cell carcinomas (ccRCCs) display divergent clinical behaviours. Molecular markers might improve risk stratification of ccRCC. Here we use, based on genome-wide CpG methylation profiling, a LASSO model to develop a five-CpG-based assay for ccRCC prognosis that can be used with formalin-fixed paraffin-embedded specimens. The five-CpG-based classifier was validated in three independent sets from China, United States and the Cancer Genome Atlas data set. The classifier predicts the overall survival of ccRCC patients (hazard ratio=2.96−4.82; P=3.9 × 10−6−2.2 × 10−9), independent of standard clinical prognostic factors. The five-CpG-based classifier successfully categorizes patients into high-risk and low-risk groups, with significant differences of clinical outcome in respective clinical stages and individual ‘stage, size, grade and necrosis' scores. Moreover, methylation at the five CpGs correlates with expression of five genes: PITX1, FOXE3, TWF2, EHBP1L1 and RIN1. Our five-CpG-based classifier is a practical and reliable prognostic tool for ccRCC that can add prognostic value to the staging system. PMID:26515236

  10. CD4⁺ follicular helper T cell infiltration predicts breast cancer survival.

    PubMed

    Gu-Trantien, Chunyan; Loi, Sherene; Garaud, Soizic; Equeter, Carole; Libin, Myriam; de Wind, Alexandre; Ravoet, Marie; Le Buanec, Hélène; Sibille, Catherine; Manfouo-Foutsop, Germain; Veys, Isabelle; Haibe-Kains, Benjamin; Singhal, Sandeep K; Michiels, Stefan; Rothé, Françoise; Salgado, Roberto; Duvillier, Hugues; Ignatiadis, Michail; Desmedt, Christine; Bron, Dominique; Larsimont, Denis; Piccart, Martine; Sotiriou, Christos; Willard-Gallo, Karen

    2013-07-01

    CD4⁺ T cells are critical regulators of immune responses, but their functional role in human breast cancer is relatively unknown. The goal of this study was to produce an image of CD4⁺ T cells infiltrating breast tumors using limited ex vivo manipulation to better understand the in vivo differences associated with patient prognosis. We performed comprehensive molecular profiling of infiltrating CD4⁺ T cells isolated from untreated invasive primary tumors and found that the infiltrating T cell subpopulations included follicular helper T (Tfh) cells, which have not previously been found in solid tumors, as well as Th1, Th2, and Th17 effector memory cells and Tregs. T cell signaling pathway alterations included a mixture of activation and suppression characterized by restricted cytokine/chemokine production, which inversely paralleled lymphoid infiltration levels and could be reproduced in activated donor CD4⁺ T cells treated with primary tumor supernatant. A comparison of extensively versus minimally infiltrated tumors showed that CXCL13-producing CD4⁺ Tfh cells distinguish extensive immune infiltrates, principally located in tertiary lymphoid structure germinal centers. An 8-gene Tfh signature, signifying organized antitumor immunity, robustly predicted survival or preoperative response to chemotherapy. Our identification of CD4⁺ Tfh cells in breast cancer suggests that they are an important immune element whose presence in the tumor is a prognostic factor.

  11. CD4+ follicular helper T cell infiltration predicts breast cancer survival

    PubMed Central

    Gu-Trantien, Chunyan; Loi, Sherene; Garaud, Soizic; Equeter, Carole; Libin, Myriam; de Wind, Alexandre; Ravoet, Marie; Le Buanec, Hélène; Sibille, Catherine; Manfouo-Foutsop, Germain; Veys, Isabelle; Haibe-Kains, Benjamin; Singhal, Sandeep K.; Michiels, Stefan; Rothé, Françoise; Salgado, Roberto; Duvillier, Hugues; Ignatiadis, Michail; Desmedt, Christine; Bron, Dominique; Larsimont, Denis; Piccart, Martine; Sotiriou, Christos; Willard-Gallo, Karen

    2013-01-01

    CD4+ T cells are critical regulators of immune responses, but their functional role in human breast cancer is relatively unknown. The goal of this study was to produce an image of CD4+ T cells infiltrating breast tumors using limited ex vivo manipulation to better understand the in vivo differences associated with patient prognosis. We performed comprehensive molecular profiling of infiltrating CD4+ T cells isolated from untreated invasive primary tumors and found that the infiltrating T cell subpopulations included follicular helper T (Tfh) cells, which have not previously been found in solid tumors, as well as Th1, Th2, and Th17 effector memory cells and Tregs. T cell signaling pathway alterations included a mixture of activation and suppression characterized by restricted cytokine/chemokine production, which inversely paralleled lymphoid infiltration levels and could be reproduced in activated donor CD4+ T cells treated with primary tumor supernatant. A comparison of extensively versus minimally infiltrated tumors showed that CXCL13-producing CD4+ Tfh cells distinguish extensive immune infiltrates, principally located in tertiary lymphoid structure germinal centers. An 8-gene Tfh signature, signifying organized antitumor immunity, robustly predicted survival or preoperative response to chemotherapy. Our identification of CD4+ Tfh cells in breast cancer suggests that they are an important immune element whose presence in the tumor is a prognostic factor. PMID:23778140

  12. Higher Levels of GATA3 Predict Better Survival in Women with Breast Cancer

    PubMed Central

    Yoon, Nam K.; Maresh, Erin L.; Shen, Dejun; Elshimali, Yahya; Apple, Sophia; Horvath, Steve; Mah, Vei; Bose, Shikha; Chia, David; Chang, Helena R.; Goodglick, Lee

    2010-01-01

    The GATA family members are zinc finger transcription factors involved in cell differentiation and proliferation. GATA3 in particular is necessary for mammary gland maturation, and its loss has been implicated in breast cancer development. Our goal was to validate the ability of GATA3 expression to predict survival in breast cancer patients. Protein expression of GATA3 was analyzed on a high density tissue microarray consisting of 242 cases of breast cancer. We associated GATA3 expression with patient outcomes and clinicopathological variables. Expression of GATA3 was significantly increased in breast cancer, in situ lesions, and hyperplastic tissue compared to normal breast tissue. GATA3 expression decreased with increasing tumor grade. Low GATA3 expression was a significant predictor of disease-related death in all patients, as well as in subgroups of estrogen receptor positive or low grade patients. Additionally, low GATA3 expression correlated with increased tumor size and estrogen and progesterone receptor negativity. GATA3 is an important predictor of disease outcome in breast cancer patients. This finding has been validated in a diverse set of populations. Thus, GATA3 expression has utility as a prognostic indicator in breast cancer. PMID:21078439

  13. Geriatric assessment predicts survival for older adults receiving induction chemotherapy for acute myelogenous leukemia.

    PubMed

    Klepin, Heidi D; Geiger, Ann M; Tooze, Janet A; Kritchevsky, Stephen B; Williamson, Jeff D; Pardee, Timothy S; Ellis, Leslie R; Powell, Bayard L

    2013-05-23

    We investigated the predictive value of geriatric assessment (GA) on overall survival (OS) for older adults with acute myelogenous leukemia (AML). Consecutive patients ≥ 60 years with newly diagnosed AML and planned intensive chemotherapy were enrolled at a single institution. Pretreatment GA included evaluation of cognition, depression, distress, physical function (PF) (self-reported and objectively measured), and comorbidity. Objective PF was assessed using the Short Physical Performance Battery (SPPB, timed 4-m walk, chair stands, standing balance) and grip strength. Cox proportional hazards models were fit for each GA measure as a predictor of OS. Among 74 patients, the mean age was 70 years, and 78.4% had an Eastern Cooperative Oncology Group (ECOG) score ≤ 1. OS was significantly shorter for participants who screened positive for impairment in cognition and objectively measured PF. Adjusting for age, gender, ECOG score, cytogenetic risk group, myelodysplastic syndrome, and hemoglobin, impaired cognition (Modified Mini-Mental State Exam < 77) and impaired objective PF (SPPB < 9) were associated with worse OS. GA methods, with a focus on cognitive and PF, improve risk stratification and may inform interventions to improve outcomes for older AML patients.

  14. Geriatric assessment predicts survival for older adults receiving induction chemotherapy for acute myelogenous leukemia

    PubMed Central

    Geiger, Ann M.; Tooze, Janet A.; Kritchevsky, Stephen B.; Williamson, Jeff D.; Pardee, Timothy S.; Ellis, Leslie R.; Powell, Bayard L.

    2013-01-01

    We investigated the predictive value of geriatric assessment (GA) on overall survival (OS) for older adults with acute myelogenous leukemia (AML). Consecutive patients ≥ 60 years with newly diagnosed AML and planned intensive chemotherapy were enrolled at a single institution. Pretreatment GA included evaluation of cognition, depression, distress, physical function (PF) (self-reported and objectively measured), and comorbidity. Objective PF was assessed using the Short Physical Performance Battery (SPPB, timed 4-m walk, chair stands, standing balance) and grip strength. Cox proportional hazards models were fit for each GA measure as a predictor of OS. Among 74 patients, the mean age was 70 years, and 78.4% had an Eastern Cooperative Oncology Group (ECOG) score ≤ 1. OS was significantly shorter for participants who screened positive for impairment in cognition and objectively measured PF. Adjusting for age, gender, ECOG score, cytogenetic risk group, myelodysplastic syndrome, and hemoglobin, impaired cognition (Modified Mini-Mental State Exam < 77) and impaired objective PF (SPPB < 9) were associated with worse OS. GA methods, with a focus on cognitive and PF, improve risk stratification and may inform interventions to improve outcomes for older AML patients. PMID:23550038

  15. A dynamic Bayesian network approach for time-specific survival probability prediction in patients after ventricular assist device implantation.

    PubMed

    Exarchos, Themis P; Rigas, George; Goletsis, Yorgos; Stefanou, Kostas; Jacobs, Steven; Trivella, Maria-Giovanna; Fotiadis, Dimitrios I

    2014-01-01

    In this work we present a decision support tool for the calculation of time-dependent survival probability for patients after ventricular assist device implantation. Two different models have been developed, a short term one which predicts survival for the first three months and a long term one that predicts survival for one year after implantation. In order to model the time dependencies between the different time slices of the problem, a dynamic Bayesian network (DBN) approach has been employed. DBNs order to capture the temporal events of the patient disease and the temporal data availability. High accuracy results have been reported for both models. The short and long term DBNs reached an accuracy of 96.97% and 93.55% respectively.

  16. Survival prediction in terminally ill cancer patients by clinical estimates, laboratory tests, and self-rated anxiety and depression.

    PubMed

    Gripp, Stephan; Moeller, Sibylle; Bölke, Edwin; Schmitt, Gerd; Matuschek, Christiane; Asgari, Sonja; Asgharzadeh, Farzin; Roth, Stephan; Budach, Wilfried; Franz, Matthias; Willers, Reinhardt

    2007-08-01

    To study how survival of palliative cancer patients relates to subjective prediction of survival, objective prognostic factors (PFs), and individual psychological coping. Survival was estimated according to three categories (< 1 month, 1 to 6 months, and > 6 months) by two physicians (A and B) and the institutional tumor board (C) for 216 patients recently referred for palliative radiotherapy. After 6 months, the accuracy of these estimates was assessed. The prognostic relevance of clinical symptoms, performance status, laboratory tests, and self-reported emotional distress (Hospital Anxiety and Depression Scale) was investigated. In 61%, 55%, and 63% of the patients, prognoses were correctly estimated by A, B, and C, respectively. kappa statistic showed fair agreement of the estimates, which proved to be overly optimistic. Accuracy of the three estimates did not improve with increasing professional experience. In particular, the survival of 96%, 71%, and 87% of patients who died in less than 1 month was overestimated by A, B, and C, respectively. On univariate analysis, 11 of 27 parameters significantly affected survival, namely performance status, primary cancer, fatigue, dyspnea, use of strong analgesics, brain metastases, leukocytosis, lactate dehydrogenase (LDH), depression, and anxiety. On multivariate analysis, colorectal and breast cancer had a favorable prognosis, whereas brain metastases, Karnofsky performance status less than 50%, strong analgesics, dyspnea, LDH, and leukocytosis were associated with a poor prognosis. This study revealed that physicians' survival estimates were unreliable, especially in the case of patients near death. Self-reported emotional distress and objective PFs may improve the accuracy of survival estimates.

  17. Two-step feature selection for predicting survival time of patients with metastatic castrate resistant prostate cancer

    PubMed Central

    Shiga, Motoki

    2016-01-01

    Metastatic castrate resistant prostate cancer (mCRPC) is the major cause of death in prostate cancer patients. Even though some options for treatment of mCRPC have been developed, the most effective therapies remain unclear. Thus finding key patient clinical variables related with mCRPC is an important issue for understanding the disease progression mechanism of mCRPC and clinical decision making for these patients. The Prostate Cancer DREAM Challenge is a crowd-based competition to tackle this essential challenge using new large clinical datasets. This paper proposes an effective procedure for predicting global risks and survival times of these patients, aimed at sub-challenge 1a and 1b of the Prostate Cancer DREAM challenge. The procedure implements a two-step feature selection procedure, which first implements sparse feature selection for numerical clinical variables and statistical hypothesis testing of differences between survival curves caused by categorical clinical variables, and then implements a forward feature selection to narrow the list of informative features. Using Cox’s proportional hazards model with these selected features, this method predicted global risk and survival time of patients using a linear model whose input is a median time computed from the hazard model. The challenge results demonstrated that the proposed procedure outperforms the state of the art model by correctly selecting more informative features on both the global risk prediction and the survival time prediction. PMID:27990267

  18. Stomach position in prediction of survival in left-sided congenital diaphragmatic hernia with or without fetoscopic endoluminal tracheal occlusion.

    PubMed

    Cordier, A-G; Jani, J C; Cannie, M M; Rodó, C; Fabietti, I; Persico, N; Saada, J; Carreras, E; Senat, M-V; Benachi, A

    2015-08-01

    To investigate the value of fetal stomach position in predicting postnatal outcome in left-sided congenital diaphragmatic hernia (CDH) with and without fetoscopic endoluminal tracheal occlusion (FETO). This was a retrospective review of CDH cases that were expectantly managed or treated with FETO, assessed from May 2008 to October 2013, in which we graded, on a scale of 1-4, stomach position on the four-chamber view of the heart with respect to thoracic structures. Logistic regression analysis was used to investigate the effect of management center (Paris, Brussels, Barcelona, Milan), stomach grading, observed-to-expected lung area-to-head circumference ratio (O/E-LHR), gestational age at delivery, birth weight in expectantly managed CDH, gestational ages at FETO and at removal and period of tracheal occlusion, on postnatal survival in CDH cases treated with FETO. We identified 67 expectantly managed CDH cases and 47 CDH cases that were treated with FETO. In expectantly managed CDH, stomach position and O/E-LHR predicted postnatal survival independently. In CDH treated with FETO, stomach position and gestational age at delivery predicted postnatal survival independently. In left-sided CDH with or without FETO, stomach position is predictive of postnatal survival. Copyright © 2014 ISUOG. Published by John Wiley & Sons Ltd.

  19. Tumor-Absorbed Dose Predicts Progression-Free Survival Following 131I-Tositumomab Radioimmunotherapy

    PubMed Central

    Dewaraja, Yuni K.; Schipper, Matthew J.; Shen, Jincheng; Smith, Lauren B.; Murgic, Jure; Savas, Hatice; Youssef, Ehab; Regan, Denise; Wilderman, Scott J.; Roberson, Peter L.; Kaminski, Mark S.; Avram, Anca M.

    2014-01-01

    The study aimed at identifying patient-specific dosimetric and nondosimetric factors predicting outcome of non-Hodgkin lymphoma patients after 131I-tositumomab radioimmunotherapy for potential use in treatment planning. Methods Tumor-absorbed dose measures were estimated for 130 tumors in 39 relapsed or refractory non-Hodgkin lymphoma patients by coupling SPECT/CT imaging with the Dose Planning Method (DPM) Monte Carlo code. Equivalent biologic effect was calculated to assess the biologic effects of nonuniform absorbed dose including the effects of the unlabeled antibody. Evaluated nondosimetric covariates included histology, presence of bulky disease, and prior treatment history. Tumor level outcome was based on volume shrinkage assessed on follow-up CT. Patient level outcome measures were overall response (OR), complete response (CR), and progression-free survival (PFS), determined from clinical assessments that included PET/CT. Results The estimated mean tumor-absorbed dose had a median value of 275 cGy (range, 94–711 cGy). A high correlation was observed between tracer-predicted and therapy-delivered mean tumor-absorbed doses (P < 0.001; r = 0.85). In univariate tumor-level analysis, tumor shrinkage correlated significantly with almost all of the evaluated dosimetric factors, including equivalent biologic effect. Regression analysis showed that OR, CR, and PFS were associated with the dosimetric factors and equivalent biologic effect. Both mean tumor-absorbed dose (P = 0.025) and equivalent biologic effect (P = 0.035) were significant predictors of PFS whereas none of the nondosimetric covariates were found to be statistically significant factors affecting PFS. The most important finding of the study was that in Kaplan–Meier curves stratified by mean dose, longer PFS was observed in patients receiving mean tumor-absorbed doses greater than 200 cGy than in those receiving 200 cGy or less (median PFS, 13.6 vs. 1.9 mo for the 2 dose groups; log-rank P < 0

  20. A Novel Inflammation-Based Stage (I Stage) Predicts Overall Survival of Patients with Nasopharyngeal Carcinoma

    PubMed Central

    Li, Jian-Pei; Chen, Shu-Lin; Liu, Xiao-Min; He, Xia; Xing, Shan; Liu, Yi-Jun; Lin, Yue-Hao; Liu, Wan-Li

    2016-01-01

    Recent studies have indicated that inflammation-based prognostic scores, such as the Glasgow Prognostic Score (GPS), modified GPS (mGPS) and C-reactive protein/Albumin (CRP/Alb) ratio, platelet–lymphocyte ratio (PLR), and neutrophil–lymphocyte ratio (NLR), have been reported to have prognostic value in patients with many types of cancer, including nasopharyngeal carcinoma (NPC). In this study, we proposed a novel inflammation-based stage, named I stage, for patients with NPC. A retrospective study of 409 newly-diagnosed cases of NPC was conducted. The prognostic factors (GPS, mGPS, CRP/Alb ratios, PLR, and NLR) were evaluated using univariate and multivariate analyses. Then, according to the results of the multivariate analyses, we proposed a I stage combination of independent risk factors (CRP/Alb ratio and PLR). The I stage was calculated as follows: patients with high levels of CRP/Alb ratio (>0.03) and PLR (>146.2) were defined as I2; patients with one or no abnormal values were defined as I1 or I0, respectively. The relationships between the I stage and clinicopathological variables and overall survival (OS) were evaluated. In addition, the discriminatory ability of the I stage with other inflammation-based prognostic scores was assessed using the AUCs (areas under the curves) analyzed by receiver operating characteristics (ROC) curves. The p value of <0.05 was considered to be significant. A total of 409 patients with NPC were enrolled in this study. Multivariate analyses revealed that only the CRP/Alb ratio (Hazard ratio (HR) = 2.093; 95% Confidence interval (CI): 1.222–3.587; p = 0.007) and PLR (HR: 2.003; 95% CI: 1.177–3.410; p = 0.010) were independent prognostic factors in patients with NPC. The five-year overall survival rates for patients with I0, I1, and I2 were 92.1% ± 2.9%, 83.3% ± 2.6%, and 63.1% ± 4.6%, respectively (p < 0.001). The I stage had a higher area under the curve value (0.670) compared with other systemic inflammation

  1. Child-Na score: a predictive model for survival in cirrhotic patients with symptomatic portal hypertension treated with TIPS.

    PubMed

    Chen, Hui; Bai, Ming; Qi, Xingshun; Liu, Lei; He, Chuangye; Yin, Zhanxin; Fan, Daiming; Han, Guohong

    2013-01-01

    Several models have been developed to predict survival in patients with cirrhosis undergoing TIPS; however, few of these models have gained widespread acceptance, especially in the era of covered stents. The aim of this study was to establish an evidence-based model for predicting survival after TIPS procedures. A total of 210 patients with cirrhosis treated with TIPS were considered in the study. We comprehensively investigated factors associated with one-year survival and developed a new predictive model using the Cox regression model. In the multivariate analysis, the Child-Pugh score and serum sodium levels were independent predictors of one-year survival. A new score incorporating serum sodium into the Child-Pugh score was developed: Child-Na score. We compared the predictive accuracy of Child-Na score with that of other scores; only the Child-Na and MELD-Na scores had adequate predictive ability in patients with serum Na levels <138 mmol/L. The best Child-Na cut-off score (15.5) differentiated two groups of patients with distinct prognoses (one-year cumulative survival rates of 80.6% and 45.5%); this finding was confirmed in a validation cohort (n = 86). In a subgroup analysis stratifying patients by indication for TIPS, the Child-Na score distinguished patients with different prognoses. Patients with variceal bleeding and a Child-Na score ≤15 had a better prognosis than patients with a score ≥16. Patients with refractory ascites and a Child-Na score ≥16 had a high risk of death after the TIPS procedures; caution should be used when treating these patients with TIPS.

  2. Precore/Core Region Mutations in Hepatitis B Virus DNA Predict Postoperative Survival in Hepatocellular Carcinoma

    PubMed Central

    Zhao, Yufei; Zhang, Lan; Zhao, Yue; Liu, Binghui; Guo, Zhanjun

    2015-01-01

    Hepatitis B virus (HBV) DNA is prone to mutations because of the proofreading deficiencies of HBV polymerase. We have identified hepatocellular carcinoma (HCC) survival-associated HBV mutations in the X protein region of HBV DNA. In the present study, we extend our research to assess HCC survival-associated HBV mutations in the HBV precore/core (PreC/C) region. The PreC/C region was amplified and sequenced and the HBV mutations were identified according to the NCBI database (http://www.ncbi.nlm.nih.gov/genome/5536). The relationships between the mutations in the PreC/C region and HCC survival were analyzed. Survival curves were generated using the Kaplan-Meier method, and comparisons between the curves were made using the log-rank test. Multivariate survival analysis was performed using a Cox proportional hazards model. After adjusting for clinical characteristics, the 1915, 2134, 2221, 2245 and 2288 mutational sites were identified as statistically significant independent predictors of HCC survival by multivariate survival analysis using a Cox proportional hazards model. In addition, the mutational site of 1896 was identified for its association with survival at a borderline significance level. A total of five mutations in the precore/core region were identified as independent predictors of postoperative survival in HCC patients. The analysis of HBV DNA mutations may help identify patient subgroups with poor prognosis and may help refine therapeutic decisions regarding HCC patients. PMID:26208136

  3. Precore/Core Region Mutations in Hepatitis B Virus DNA Predict Postoperative Survival in Hepatocellular Carcinoma.

    PubMed

    Xie, Ying; Liu, Shufeng; Zhao, Yufei; Zhang, Lan; Zhao, Yue; Liu, Binghui; Guo, Zhanjun

    2015-01-01

    Hepatitis B virus (HBV) DNA is prone to mutations because of the proofreading deficiencies of HBV polymerase. We have identified hepatocellular carcinoma (HCC) survival-associated HBV mutations in the X protein region of HBV DNA. In the present study, we extend our research to assess HCC survival-associated HBV mutations in the HBV precore/core (PreC/C) region. The PreC/C region was amplified and sequenced and the HBV mutations were identified according to the NCBI database (http://www.ncbi.nlm.nih.gov/genome/5536). The relationships between the mutations in the PreC/C region and HCC survival were analyzed. Survival curves were generated using the Kaplan-Meier method, and comparisons between the curves were made using the log-rank test. Multivariate survival analysis was performed using a Cox proportional hazards model. After adjusting for clinical characteristics, the 1915, 2134, 2221, 2245 and 2288 mutational sites were identified as statistically significant independent predictors of HCC survival by multivariate survival analysis using a Cox proportional hazards model. In addition, the mutational site of 1896 was identified for its association with survival at a borderline significance level. A total of five mutations in the precore/core region were identified as independent predictors of postoperative survival in HCC patients. The analysis of HBV DNA mutations may help identify patient subgroups with poor prognosis and may help refine therapeutic decisions regarding HCC patients.

  4. Clinical investigation survival prediction in high-grade gliomas by MRI perfusion before and during early stage of RT

    SciTech Connect

    Cao Yue . E-mail: yuecao@med.umich.edu; Tsien, Christina I.; Nagesh, Vijaya; Junck, Larry; Haken, Randall ten; Ross, Brian D.; Chenevert, Thomas L.; Lawrence, Theodore S.

    2006-03-01

    Purpose: To determine whether cerebral blood volume (CBV) and cerebral blood flow can predict the response of high-grade gliomas to radiotherapy (RT) by taking into account spatial heterogeneity and temporal changes in perfusion. Methods and Materials: Twenty-three patients with high-grade gliomas underwent conformal RT, with magnetic resonance imaging perfusion before and at Weeks 1-2 and 3-4 during RT. Tumor perfusion was classified as high, medium, or low. The prognostic values of pre-RT perfusion and the changes during RT for early prediction of tumor response to RT were evaluated. Results: The fractional high-CBV tumor volume before RT and the fluid-attenuated inversion recovery imaging tumor volume were identified as predictors for survival (p = 0.01). Changes in tumor CBV during the early treatment course also predicted for survival. Better survival was predicted by a decrease in the fractional low-CBV tumor volume at Week 1 of RT vs. before RT, a decrease in the fractional high-CBV tumor volume at Week 3 vs. Week 1 of RT, and a smaller pre-RT fluid-attenuated inversion recovery imaging tumor volume (p = 0.01). Conclusion: Early temporal changes during RT in heterogeneous regions of high and low perfusion in gliomas might predict for different physiologic responses to RT. This might also open the opportunity to identify tumor subvolumes that are radioresistant and might benefit from intensified RT.

  5. A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

    PubMed

    Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

    2015-01-01

    Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

  6. A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

    PubMed Central

    Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

    2015-01-01

    Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

  7. Isolated inferior mesenteric portal hypertension with giant inferior mesenteric vein and anomalous inferior mesenteric vein insertion

    PubMed Central

    Prasad, G. Raghavendra; Billa, Srikar; Bhandari, Pavaneel; Hussain, Aijaz

    2013-01-01

    Extrahepatic portal hypertension is not an uncommon disease in childhood, but isolated inferior mesenteric portal varices and lower gastrointestinal (GI) bleed have not been reported till date. A 4-year-old girl presented with lower GI bleed. Surgical exploration revealed extrahepatic portal vein obstruction with giant inferior mesenteric vein and colonic varices. Inferior mesenteric vein was joining the superior mesenteric vein. The child was treated successfully with inferior mesenteric – inferior vena caval anastomosis. The child was relieved of GI bleed during the follow-up. PMID:23798814

  8. Inferior vena cava filters.

    PubMed

    Duffett, L; Carrier, M

    2017-01-01

    Use of inferior vena cava (IVC) filters has increased dramatically in recent decades, despite a lack of evidence that their use has impacted venous thromboembolism (VTE)-related mortality. This increased use appears to be primarily driven by the insertion of retrievable filters for prophylactic indications. A growing body of evidence, however, suggests that IVC filters are frequently associated with clinically important adverse events, prompting a closer look at their role. We sought to narratively review the current evidence on the efficacy and safety of IVC filter placements. Inferior vena cava filters remain the only treatment option for patients with an acute (within 2-4 weeks) proximal deep vein thrombosis (DVT) or pulmonary embolism and an absolute contraindication to anticoagulation. In such patients, anticoagulation should be resumed and IVC filters removed as soon as the contraindication has passed. For all other indications, there is insufficient evidence to support the use of IVC filters and high-quality trials are required. In patients where an IVC filter remains, regular follow-up to reassess removal and screen for filter-related complications should occur. © 2016 International Society on Thrombosis and Haemostasis.

  9. Effect of PSCA gene polymorphisms on gastric cancer risk and survival prediction: A meta-analysis

    PubMed Central

    ZHANG, TAO; CHEN, YUAN-NENG; WANG, ZHEN; CHEN, JUN-QIANG; HUANG, SHI

    2012-01-01

    Previous studies have shown that two single-nucleotide polymorphisms (SNPs) in PSCA (rs2976392 and rs2294008) are associated with gastric cancer (GC), but the results are conflicting. Additionally, the prognostic value of PSCA gene polymorphisms for GC patients is unknown. We performed a meta-analysis using 9 eligible case-control studies to investigate the association between PSCA polymorphisms and GC risk, and additionally investigated the prognostic value of PSCA polymorphisms for GC patients with two eligible studies. The association was measured using random-effect or fixed-effect odds ratios (ORs) combined with 95% confidence intervals (CIs) according to the heterogeneity of the studies. We found that rs2294008 (dominant model: OR, 1.44; 95% CI, 1.16–1.79) and rs2976392 (dominant model: OR, 1.41; 95% CI, 0.98–2.04) polymorphisms were associated with increased risk of GC, although the association of rs2976392 was not statistically significant. For rs2294008, the associations were all consistently significant among the different subgroups stratified by ethnicity and tumor location, but not significant in intestinal or diffuse subtypes. For rs2976392, the associations were consistently significant for the intestinal, diffuse and non-cardia subtypes, but not significant for the cardia subtype. Furthermore, two eligible studies reported inverse results of PCSA in predicting the survival of GC patients (HR, 0.75; 95% CI, 0.59–0.96; and HR, 2.12; 95% CI, 1.22–3.69, respectively). In conclusion, PSCA gene polymorphisms are associated with increased risk of GC and are correlated with the prognosis of GC patients. Future studies are required to evaluate the molecular mechanisms of PSCA polymorphisms in GC and validate the prognostic value in a larger number of patients. PMID:23060941

  10. Preoperative interleukin-6 production by mononuclear blood cells predicts survival after radical surgery for colorectal carcinoma.

    PubMed

    Clinchy, Birgitta; Fransson, Annelie; Druvefors, Bengt; Hellsten, Anna; Håkansson, Annika; Gustafsson, Bertil; Sjödahl, Rune; Håkansson, Leif

    2007-05-01

    Colorectal cancer is one of the most common forms of cancer in the Western world. Staging based on histopathology is currently the most accurate predictor of outcome after surgery. Colorectal cancer is curable if treated at an early stage (stage I-III). However, for tumors in stages II and III there is a great need for tests giving more accurate prognostic information defining the patient population in need of closer follow-up and/or adjuvant therapy. Furthermore, tests that provide prognostic information preoperatively could provide a guide both for preoperative oncologic treatment and the surgical procedure. Peripheral blood mononuclear cells (PBMCs) were isolated preoperatively, within a week before primary surgery, from 39 patients undergoing surgery for colorectal cancer. The PBMCs were cultured in vitro for 24 hours in the presence of autologous serum and lipopolysaccharide (LPS). Interleukin-6 (IL-6) production was measured with enzyme-linked immunosorbent assay (ELISA). Staging based on histopathology was performed in all patients. Patients were followed for at least 54 months. A production of >5000 pg/mL of IL-6 identified colorectal cancer patients with a poor prognosis. Eight out of 13 patients with >5000 pg/mL IL-6 died from cancer within the follow-up period, whereas no cancer-related deaths were recorded among 21 patients with 5000 pg/mL IL-6 or less. A multivariate Cox regression analysis, stratified for T- and N-stage, identified IL-6 production as an independent prognostic factor. IL-6 production in vitro by PBMC can predict survival after radical surgery for colorectal cancer. Copyright (c) 2007 American Cancer Society

  11. The cardio-renal-anaemia syndrome predicts survival in peritoneally dialyzed patients

    PubMed Central

    Zbroch, Edyta; Malyszko, Jacek; Mysliwiec, Michal; Iaina, Adrian

    2010-01-01

    Introduction Anaemia is one of the arms of the cardio-renal-anaemia syndrome (CRA) in chronic kidney disease (CKD) patients. The correction of anaemia was effective in the amelioration of both cardiac and renal failure. We studied the relationship between the severity of CRA syndrome in peritoneally dialyzed patients and their survival probability. Material and methods Fifty-six patients on peritoneal dialysis were followed for 1 year. Definition of the severity of the CRA in dialysis patients: cardiac arm – NYHA class I-IV = 1-4 points, renal arm – non-diabetic patients age < 65 =1 point, non-diabetic patients age>65 = 2 points, diabetic patients age < 65 = 3 points, diabetic patients age>65 = 4 points, anaemia arm – Hb 11-13 g/dl (male), 11-12 g/dl (female) = 1 point, Hb 10-11 g/dl = 2 points, Hb 9-10 g/dl = 3 points, Hb < 9 g/dl = 4 points. The severity score = cardiac + renal + anaemia arms score divided by 3 (maximum 4 points). Results A total of 10/56 patients (18%) died during the study. The median value for the severity score of the whole group was 1.69. In Kaplan-Meier analysis CRA severity score was strongly associated with mortality (p < 0.001). It also correlated with albumin, CRP, erythropoietin treatment, Hb and fasting glucose. In the multivariate regression analysis age, Hb, albumin, and presence of diabetes remained significant predictors of death. Conclusions The severity score of CRA syndrome in peritoneally dialyzed patients is an independent and very significant predictor of death. The patients with a high severity score had more hypoalbuminaemia, higher inflammation markers and higher prevalence of diabetes and chronic heart failure. Cardio-renal-anaemia syndrome severity scoring as defined by us could be an easy tool to predict outcome of dialysis patients. PMID:22371797

  12. MET FISH-positive status predicts short progression-free survival and overall survival after gefitinib treatment in lung adenocarcinoma with EGFR mutation.

    PubMed

    Noro, Rintaro; Seike, Masahiro; Zou, Fenfei; Soeno, Chie; Matsuda, Kuniko; Sugano, Teppei; Nishijima, Nobuhiko; Matsumoto, Masaru; Kitamura, Kazuhiro; Kosaihira, Seiji; Minegishi, Yuji; Yoshimura, Akinobu; Kubota, Kaoru; Gemma, Akihiko

    2015-02-06

    Lung adenocarcinoma patients with EGFR gene mutations have shown a dramatic response to gefitinib. However, drug resistance eventually emerges which limits the mean duration of response. With that in view, we examined the correlations between MET gene status as assessed by fluorescence in situ hybridization (FISH) with overall survival (OS) and progression-free survival (PFS) in adenocarcinoma patients with EGFR gene mutations who had received gefitinib therapy. We evaluated 35 lung cancer samples with EGFR mutation from adenocarcinoma patients who had received gefitinib. Gene copy numbers (GCNs) and amplification of MET gene before gefitinib therapy was examined by FISH. MET protein expression was also evaluated by immunohistochemistry (IHC). FISH assessment showed that of the 35 adenocarcinoma samples, 10 patients (29%) exhibited high polysomy (5 copies≦mean MET per cell) and 1 patient (3%) exhibited amplification (2≦MET gene (red)/CEP7q (green) per cell). IHC evaluation of MET protein expression could not confirm MET high polysomy status. The Eleven patients with MET FISH positivity had significantly shorter progression-free survival (PFS) and overall survival (OS) than the 24 patients who were MET FISH-negative (PFS: p = 0.001 and OS: p = 0.03). Median PFS and OS with MET FISH-positivity were 7.6 months and 16.8 months, respectively, whereas PFS and OS with MET FISH-negativity were 15.9 months and 33.0 months, respectively. Univariate analysis revealed that MET FISH-positivity was the most significant independent factor associated with a high risk of progression and death (hazard ratio, 3.83 (p = 0.0008) and 2.25 (p = 0.03), respectively). Using FISH analysis to detect high polysomy and amplification of MET gene may be useful in predicting shortened PFS and OS after Gefitinib treatment in lung adenocarcinoma. The correlation between MET gene status and clinical outcomes for EGFR-TKI should be further evaluated using large scale samples.

  13. A Clinical Decision Support Tool To Predict Survival in Cancer Patients beyond 120 Days after Palliative Chemotherapy

    PubMed Central

    Ng, Terence

    2012-01-01

    Abstract Background Palliative chemotherapy is often administered to terminally ill cancer patients to relieve symptoms. Yet, unnecessary use of chemotherapy can worsen patients' quality of life due to treatment-related toxicities. Thus, accurate prediction of survival in terminally ill patients can help clinicians decide on the most appropriate palliative care for these patients. However, studies have shown that clinicians often make imprecise predictions of survival in cancer patients. Hence, the purpose of this study was to create a clinical decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy. Materials and Methods Data were obtained from a retrospective study of 400 randomly selected terminally ill cancer patients in the National Cancer Centre Singapore (NCCS) from 2008 to 2009. After removing patients with missing data, there were 325 patients remaining for model development. Three classification algorithms, naive Bayes (NB), neural network (NN), and support vector machine (SVM) were used to create the models. A final model with the best prediction performance was then selected to develop the tool. Results The NN model had the best prediction performance. The accuracy, specificity, sensitivity, and area under the curve (AUC) of this model were 78%, 82%, 74%, and 0.857, respectively. Five patient attributes (albumin level, alanine transaminase level (ATL), absolute neutrophil count, Eastern Cooperative Oncology Group (ECOG) status, and number of metastatic sites) were included in the model. Conclusions A decision support tool to predict survival in cancer patients beyond 120 days after palliative chemotherapy was created. With further validation, this tool coupled with the professional judgment of clinicians can help improve patient care. PMID:22690950

  14. Magnetic resonance imaging predicts survival and occult metastasis in oral cancer: a dual-centre, retrospective study.

    PubMed

    Boland, Paul W; Watt-Smith, Steve R; Hopper, Colin; Golding, Stephen J

    2013-12-01

    The purpose of this study was to investigate the effectiveness of tumour variables measured on magnetic resonance imaging (MRI) to predict 2-year disease-related survival and occult cervical lymph node metastasis in oral carcinoma. In this retrospective, dual-centre study the volume and thickness of tumours were measured using archived MRI staging scans of 199 patients who had curative primary resection for histologically confirmed oral carcinoma. Tumour volume predicted survival when grouped using the median (3.0 cm(3), HR 3.41, p 0.005) and first and third quartiles (0.5 cm(3), HR 8.22, p 0.04; 8.0 cm(3), HR 18.6, p 0.005). Tumour thickness predicted survival using a median of 11.0 mm (HR 2.65, p 0.02). Volume predicted occult cervical lymph node metastasis using a median of 3.0 cm(3) (HR 5.02, p<0.001) and quartiles of 0.5 cm(3) (HR 6.92, p=0.01) and 8.0 cm(3) (HR 11.3, p 0.005); thickness predicted it using a median of 11.0 mm (HR 4.39, p 0.002) and quartiles of 4.0 mm (HR 4.33, p 0.06) and 16 mm (HR 11.9, p 0.003). The thickness and volume of tumour measured on MRI may predict 2-year disease-related survival and occult cervical lymph node metastasis in oral cancer.

  15. A Novel and Validated Inflammation-Based Score (IBS) Predicts Survival in Patients With Hepatocellular Carcinoma Following Curative Surgical Resection

    PubMed Central

    Fu, Yi-Peng; Ni, Xiao-Chun; Yi, Yong; Cai, Xiao-Yan; He, Hong-Wei; Wang, Jia-Xing; Lu, Zhu-Feng; Han, Xu; Cao, Ya; Zhou, Jian; Fan, Jia; Qiu, Shuang-Jian

    2016-01-01

    Abstract As chronic inflammation is involved in the pathogenesis and progression of hepatocellular carcinoma (HCC), we investigated the prognostic accuracy of a cluster of inflammatory scores, including the Glasgow Prognostic Score, modified Glasgow Prognostic Score, platelet to lymphocyte ratio, Prognostic Nutritional Index, Prognostic Index, and a novel Inflammation-Based Score (IBS) integrated preoperative and postoperative neutrophil to lymphocyte ratio in 2 independent cohorts. Further, we aimed to formulate an effective prognostic nomogram for HCC after hepatectomy. Prognostic value of inflammatory scores and Barcelona Clinic Liver Cancer (BCLC) stage were studied in a training cohort of 772 patients with HCC underwent hepatectomy. Independent predictors of survival identified in multivariate analysis were validated in an independent set of 349 patients with an overall similar clinical feature. In both training and validation cohorts, IBS, microscopic vascular invasion, and BCLC stage emerged as independent factors of overall survival (OS) and recurrence-free survival (RFS). The predictive capacity of the IBS in both OS and RFS appeared superior to that of the other inflammatory scores in terms of C-index. Additionally, the formulated nomogram comprised IBS resulted in more accurate prognostic prediction compared with BCLC stage alone. IBS is a novel and validated prognostic indicator of HCC after curative resection, and a robust HCC nomogram including IBS was developed to predict survival for patients after hepatectomy. PMID:26886627

  16. Changes in neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios during chemoradiation predict for survival and pathologic complete response in trimodality esophageal cancer patients

    PubMed Central

    Hyder, Jalal; Boggs, Drexell Hunter; Hanna, Andrew; Suntharalingam, Mohan

    2016-01-01

    Background Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) predict for survival in cancer patients. In patients receiving multimodality therapy, the effect of therapy on the NLR and PLR is not well understood. We evaluated changes in NLR and PLR among locally advanced esophageal cancer patients who received trimodality therapy. Methods We performed a retrospective analysis of nonmetastatic patients with esophageal cancer who received neoadjuvant chemoradiation therapy (CRT) followed by esophagectomy at our institution between March 2000 and April 2012. NLR and PLR values were obtained for the following time points (TPs): (I) at diagnosis before CRT; (II) after CRT but prior to surgery; and (III) after surgery. We evaluated changes in NLR and PLR using the difference and ratio between TPs. Overall survival (OS) was evaluated by Kaplan-Meier analysis. Univariate and multivariate Cox regression models were applied to evaluate the independent prognostic significance of NLR and PLR. Results This IRB-approved study included the records of 83 consecutive patients with stage II-IV esophageal cancer. The median age was 60 years, and median follow-up was 29.3 months. Patients were treated to a median prescription dose of 50.4 Gy (range, 50.4-56.4 Gy) in 28-33 fractions. Median NLR and PLR were 3.3 and 157.2, 12 and 645, and 11.5 and 391.7 at TPs 1, 2, and 3, respectively. On multivariate analysis, superior OS was associated with PLR ≥250 at TP3 (P=0.03), PLR decrease ≥609.2 between TP2 and TP3 (P=0.02), and PLR ratio (TP3/TP1) ≥1.08 (P=0.03). Inferior progression-free survival (PFS) was associated with NLR ≥36 at TP2 (P=0.0008), NLR increase ≥28.3 between TP1 and TP2 (P=0.0005), and PLR ratio (TP2/TP3) ≥0.38 (P=0.1). Pathologic complete response (PCR) was less likely for adenocarcinoma (AC) histology (P=0.03), NLR ≥10.6 at TP2 (P=0.04), and NLR increase ≥4.6 from TP1 to TP2 (P=0.03). Conclusions To our knowledge, this is the first

  17. Magnetic resonance imaging-detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience.

    PubMed

    Patel, Uday B; Taylor, Fiona; Blomqvist, Lennart; George, Christopher; Evans, Hywel; Tekkis, Paris; Quirke, Philip; Sebag-Montefiore, David; Moran, Brendan; Heald, Richard; Guthrie, Ashley; Bees, Nicola; Swift, Ian; Pennert, Kjell; Brown, Gina

    2011-10-01

    To assess magnetic resonance imaging (MRI) and pathologic staging after neoadjuvant therapy for rectal cancer in a prospectively enrolled, multicenter study. In a prospective cohort study, 111 patients who had rectal cancer treated by neoadjuvant therapy were assessed for response by MRI and pathology staging by T, N and circumferential resection margin (CRM) status. Tumor regression grade (TRG) was also assessed by MRI. Overall survival (OS) was estimated by using the Kaplan-Meier product-limit method, and Cox proportional hazards models were used to determine associations between staging of good and poor responders on MRI or pathology and survival outcomes after controlling for patient characteristics. On multivariate analysis, the MRI-assessed TRG (mrTRG) hazard ratios (HRs) were independently significant for survival (HR, 4.40; 95% CI, 1.65 to 11.7) and disease-free survival (DFS; HR, 3.28; 95% CI, 1.22 to 8.80). Five-year survival for poor mrTRG was 27% versus 72% (P = .001), and DFS for poor mrTRG was 31% versus 64% (P = .007). Preoperative MRI-predicted CRM independently predicted local recurrence (LR; HR, 4.25; 95% CI, 1.45 to 12.51). Five-year survival for poor post-treatment pathologic T stage (ypT) was 39% versus 76% (P = .001); DFS for the same was 38% versus 84% (P = .001); and LR for the same was 27% versus 6% (P = .018). The 5-year survival for involved pCRM was 30% versus 59% (P = .001); DFS, 28 versus 62% (P = .02); and LR, 56% versus 10% (P = .001). Pathology node status did not predict outcomes. MRI assessment of TRG and CRM are imaging markers that predict survival outcomes for good and poor responders and provide an opportunity for the multidisciplinary team to offer additional treatment options before planning definitive surgery. Postoperative histopathology assessment of ypT and CRM but not post-treatment N status were important postsurgical predictors of outcome.

  18. A Preoperative Nutritional Index for Predicting Cancer-Specific and Overall Survival in Chinese Patients With Laryngeal Cancer

    PubMed Central

    Fu, Yan; Chen, Shu-Wei; Chen, Shi-Qi; Ou-Yang, Dian; Liu, Wei-Wei; Song, Ming; Yang, An-Kui; Zhang, Quan

    2016-01-01

    Abstract Pinato prognostic nutritional index (PNI) adequately predicts long-term outcomes of various malignancies. However, its value in predicting outcomes in laryngeal squamous cell carcinoma (LSCC) is unknown. All patients newly diagnosed with LSCC presenting to the Department of Head and Neck Oncology at Sun Yat-sen University Cancer Center between January 1, 1990 and July 31, 2010 were eligible. The PNI was calculated as serum albumin (g/L) + 5 × total lymphocyte count/L. The Cutoff Finder software program was used to classify the patients into 3 groups for which the PNI score was at least 70% sensitive, at least 70% specific, or equivocal. Cancer-specific survival was estimated using the Kaplan–Meier method, and predictors were assessed with Cox regression analysis. Median time between surgery and PNI administration for the 975 eligible patients was 83 months. Index score groups were significantly associated with age, T stage, TNM stage, and type of surgery. Five-year CSS and OS were 57.3% and 56.6% in patients with PNI scores below 48.65 (low-probability of survival), 72.8% and 71.3% with scores between 48.65 and 56.93 (moderate-probability of survival), and 77.6% and 75.3% with scores above 56.93 (high-probability of survival); 10-year CSS and OS were 44.2% and 42.7%, 61.6% and 55.6%, 68.3% and 63.5%, respectively. The PNI score groups significantly predicted CSS and OS (P < 0.001). The PNI is an inexpensive and readily available score that predicted survival in patients with LSCC after curative laryngectomy. PMID:26986105

  19. Number of Negative Lymph Nodes Can Predict Survival after Postmastectomy Radiotherapy According to Different Breast Cancer Subtypes

    PubMed Central

    Wu, San-Gang; Peng, Fang; Zhou, Juan; Sun, Jia-Yuan; Li, Feng-Yan; Lin, Qin; Lin, Huan-Xin; Bao, Yong; He, Zhen-Yu

    2015-01-01

    Purpose: To assess the prognostic value of the number of negative lymph nodes (NLNs) in breast cancer patients with positive axillary lymph nodes after mastectomy and its predictive value for radiotherapy efficacy of different breast cancer subtypes (BCS). Methods: The records of 1,260 breast cancer patients with positive axillary lymph nodes who received mastectomy between January 1998 and December 2007 were reviewed. The prognostic impact and predictive value of the number of NLNs with respect to locoregional recurrence-free survival (LRFS), disease-free survival (DFS), and overall survival (OS) were analyzed. Results: The median follow-up time was 58 months, and 444 patients (35.2%) received postmastectomy radiotherapy (PMRT). Univariate and multivariate Cox survival analysis indicated the number of NLNs was an independent prognostic factor of LRFS, DFS, and OS. Patients with a higher number of NLNs had better survival. PMRT improved the LRFS of patients with ≤ 8 NLNs ( p < 0.001), while failing to improve the LRFS of patients with > 8 NLNs (p = 0.075). In patients with luminal A subtype, PMRT improved the LRFS, DFS, and OS of patients with ≤ 8 NLNs, but in patients with > 8 NLNs only the LRFS was improved. For patients with luminal B subtype, PMRT only improved the LRFS of patients with ≤ 8 NLNs. The number of NLNs had no predictive value for the efficacy with PMRT in Her2+ and triple-negative subtypes. Conclusions: The number of NLNs is a prognostic indicator in patients with node-positive breast cancer, and it can predict the efficacy of PMRT according to different BCS. PMID:25663944

  20. A novel systemic inflammation response index (SIRI) for predicting the survival of patients with pancreatic cancer after chemotherapy.

    PubMed

    Qi, Qi; Zhuang, Liping; Shen, Yehua; Geng, Yawen; Yu, Shulin; Chen, Hao; Liu, Luming; Meng, Zhiqiang; Wang, Peng; Chen, Zhen

    2016-07-15

    Predicting survival is uniquely difficult in patients with pancreatic cancer who receive chemotherapy. The authors developed a systemic inflammation response index (SIRI) based on peripheral neutrophil, monocyte, and lymphocyte counts and evaluated the ability of the SIRI to predict the survival of patients with pancreatic cancer who received chemotherapy. The SIRI was developed in a training set of 177 patients who had advanced pancreatic cancer and received palliative chemotherapy. The ability of the SIRI to predict a patient's survival after chemotherapy was validated in 2 independent cohorts (n = 397). Compared with patients who had an SIRI <1.8, patients in the training cohort who had an SIRI ≥1.8 had a shorter time to progression (TTP) (hazard ratio [HR], 2.348; 95% confidence interval, 1.559-3.535; P = .003) and shorter overall survival (OS) (HR, 2.789; 95% confidence interval, 1.897-4.121; P < .001). Comparable TTP and OS findings were observed in 2 independent validation cohorts. Multivariate analysis confirmed that the SIRI was an independent prognostic factor for both TTP and OS. In addition, compared with no change, an increase in the SIRI at week 8 was associated with poor TTP and OS, whereas a decrease in the SIRI was associated with improved outcomes. In addition, high SIRI scores were correlated with higher serum levels of interleukin 10, C-C motif chemokine ligand 17 (CCL17), CCL18, and CCL22 and with a shortened TTP. The SIRI can be used to predict the survival of patients with pancreatic adenocarcinomas who receive chemotherapy, potentially allowing clinicians to improve treatment outcomes by identifying candidates for aggressive therapy. Cancer 2016;122:2158-67. © 2016 American Cancer Society. © 2016 American Cancer Society.

  1. Molecular markers to complement sentinel node status in predicting survival in patients with high-risk locally invasive melanoma.

    PubMed

    Rowe, Casey J; Tang, Fiona; Hughes, Maria Celia B; Rodero, Mathieu P; Malt, Maryrose; Lambie, Duncan; Barbour, Andrew; Hayward, Nicholas K; Smithers, B Mark; Green, Adele C; Khosrotehrani, Kiarash

    2016-08-01

    Sentinel lymph node status is a major prognostic marker in locally invasive cutaneous melanoma. However, this procedure is not always feasible, requires advanced logistics and carries rare but significant morbidity. Previous studies have linked markers of tumour biology to patient survival. In this study, we aimed to combine the predictive value of established biomarkers in addition to clinical parameters as indicators of survival in addition to or instead of sentinel node biopsy in a cohort of high-risk melanoma patients. Patients with locally invasive melanomas undergoing sentinel lymph node biopsy were ascertained and prospectively followed. Information on mortality was validated through the National Death Index. Immunohistochemistry was used to analyse proteins previously reported to be associated with melanoma survival, namely Ki67, p16 and CD163. Evaluation and multivariate analyses according to REMARK criteria were used to generate models to predict disease-free and melanoma-specific survival. A total of 189 patients with available archival material of their primary tumour were analysed. Our study sample was representative of the entire cohort (N = 559). Average Breslow thickness was 2.5 mm. Thirty-two (17%) patients in the study sample died from melanoma during the follow-up period. A prognostic score was developed and was strongly predictive of survival, independent of sentinel node status. The score allowed classification of risk of melanoma death in sentinel node-negative patients. Combining clinicopathological factors and established biomarkers allows prediction of outcome in locally invasive melanoma and might be implemented in addition to or in cases when sentinel node biopsy cannot be performed. © 2016 UICC.

  2. Nomogram based on systemic inflammatory response markers predicting the survival of patients with resectable gastric cancer after D2 gastrectomy

    PubMed Central

    Chen, Shangxiang; Liu, Xuechao; Kong, Pengfei; Zhou, Zhiwei; Zhan, Youqing; Xu, Dazhi

    2016-01-01

    This study aimed to construct a nomogram to predict survival of patients with resectable gastric cancer (RGC) based on both clinicopathology characteristics and systemic inflammatory response markers (SIRMs). Of 3,452 RGC patients after D2 gastrectomy at the Sun Yat-sen University Cancer Center, 1058 patients who met the inclusion criterion were analyzed. The patients operated on from January 1, 2005 to December 31, 2009 were assigned to the training set (817 patients) to establish a nomogram, and the rest (241 patients) were selected as validation set. Based on the training set, seven independent risk factors were selected in the nomogram. The calibration curves for probability of 1-year, 3-year and 5-year overall survival (OS) showed satisfactory accordance between nomogram prediction and actual observation. When the metastatic lymph node stage (mLNS) is replaced by metastasis lymph node ratio (mLNR) in validation set, the C-index in predicting OS rise from 0.77 to 0.79, higher than that of 7th American Joint Committee on Cancer 7th (AJCC) staging system (0.70; p<0.001). In conclusions, the proposed nomogram which including mLNR and routine detected SIRMs resulted in optimal survival prediction for RGC patients after D2 gastrectomy. PMID:27121054

  3. Implementation of a rapid learning platform: Predicting 2-year survival in laryngeal carcinoma patients in a clinical setting

    PubMed Central

    Lustberg, Tim; Bailey, Michael; Thwaites, David I.; Miller, Alexis; Carolan, Martin; Holloway, Lois; Velazquez, Emmanuel Rios; Hoebers, Frank; Dekker, Andre

    2016-01-01

    Background and Purpose To improve quality and personalization of oncology health care, decision aid tools are needed to advise physicians and patients. The aim of this work is to demonstrate the clinical relevance of a survival prediction model as a first step to multi institutional rapid learning and compare this to a clinical trial dataset. Materials and Methods Data extraction and mining tools were used to collect uncurated input parameters from Illawarra Cancer Care Centre's (clinical cohort) oncology information system. Prognosis categories previously established from the Maastricht Radiation Oncology (training cohort) dataset, were applied to the clinical cohort and the radiotherapy only arm of the RTOG-9111 (trial cohort). Results Data mining identified 125 laryngeal carcinoma patients, ending up with 52 patients in the clinical cohort who were eligible to be evaluated by the model to predict 2-year survival and 177 for the trial cohort. The model was able to classify patients and predict survival in the clinical cohort, but for the trial cohort it failed to do so. Conclusions The technical infrastructure and model is able to support the prognosis prediction of laryngeal carcinoma patients in a clinical cohort. The model does not perform well for the highly selective patient population in the trial cohort. PMID:27095578

  4. Development and validation of a nomogram for predicting survival in patients with resected non-small-cell lung cancer.

    PubMed

    Liang, Wenhua; Zhang, Li; Jiang, Gening; Wang, Qun; Liu, Lunxu; Liu, Deruo; Wang, Zheng; Zhu, Zhihua; Deng, Qiuhua; Xiong, Xinguo; Shao, Wenlong; Shi, Xiaoshun; He, Jianxing

    2015-03-10

    A nomogram is a useful and convenient tool for individualized cancer prognoses. We sought to develop a clinical nomogram for predicting survival of patients with resected non-small-cell lung cancer (NSCLC). On the basis of data from a multi-institutional registry of 6,111 patients with resected NSCLC in China, we identified and integrated significant prognostic factors for survival to build a nomogram. The model was subjected to bootstrap internal validation and to external validation with a separate cohort of 2,148 patients from the International Association for the Study of Lung Cancer (IASLC) database. The predictive accuracy and discriminative ability were measured by concordance index (C-index) and risk group stratification. A total of 5,261 patients were included for analysis. Six independent prognostic factors were identified and entered into the nomogram. The calibration curves for probability of 1-, 3-, and 5-year overall survival (OS) showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram was higher than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (primary cohort, 0.71 v 0.68, respectively; P < .01; IASLC cohort, 0.67 v 0.64, respectively; P = .06). The stratification into different risk groups allowed significant distinction between survival curves within respective TNM categories. We established and validated a novel nomogram that can provide individual prediction of OS for patients with resected NSCLC. This practical prognostic model may help clinicians in decision making and design of clinical studies. © 2015 by American Society of Clinical Oncology.

  5. Predicting short-term survival after liver transplantation on eight score systems: a national report from China Liver Transplant Registry.

    PubMed

    Ling, Qi; Dai, Haojiang; Zhuang, Runzhou; Shen, Tian; Wang, Weilin; Xu, Xiao; Zheng, Shusen

    2017-02-13

    To compare the performance of eight score systems (MELD, uMELD, MELD-Na. iMELD, UKELD, MELD-AS, CTP, and mCTP) in predicting the post-transplant mortality, we analyzed the data of 6,014 adult cirrhotic patients who underwent liver transplantation between January 2003 and December 2010 from the China Liver Transplant Registry database. In hepatitis B virus (HBV) group, MELD, uMELD and MELD-AS showed good predictive accuracies at 3-month mortality after liver transplantation; by comparison with other five models, MELD presented the best ability in predicting 3-month, 6-month and 1-year mortality, showing a significantly better predictive ability than UKELD and iMELD. In hepatitis C virus and Alcohol groups, the predictive ability did not differ significantly between MELD and other models. Patient survivals in different MELD categories were of statistically significant difference. Among patients with MELD score >35, a new prognostic model based on serum creatinine, need for hemodialysis and moderate ascites could identify the sickest one. In conclusion, MELD is superior to other score systems in predicting short-term post-transplant survival in patients with HBV-related liver disease. Among patients with MELD score >35, a new prognostic model can identify the sickest patients who should be excluded from waiting list to prevent wasteful transplantation.

  6. Predicting short-term survival after liver transplantation on eight score systems: a national report from China Liver Transplant Registry

    PubMed Central

    Ling, Qi; Dai, Haojiang; Zhuang, Runzhou; Shen, Tian; Wang, Weilin; Xu, Xiao; Zheng, Shusen

    2017-01-01

    To compare the performance of eight score systems (MELD, uMELD, MELD-Na. iMELD, UKELD, MELD-AS, CTP, and mCTP) in predicting the post-transplant mortality, we analyzed the data of 6,014 adult cirrhotic patients who underwent liver transplantation between January 2003 and December 2010 from the China Liver Transplant Registry database. In hepatitis B virus (HBV) group, MELD, uMELD and MELD-AS showed good predictive accuracies at 3-month mortality after liver transplantation; by comparison with other five models, MELD presented the best ability in predicting 3-month, 6-month and 1-year mortality, showing a significantly better predictive ability than UKELD and iMELD. In hepatitis C virus and Alcohol groups, the predictive ability did not differ significantly between MELD and other models. Patient survivals in different MELD categories were of statistically significant difference. Among patients with MELD score >35, a new prognostic model based on serum creatinine, need for hemodialysis and moderate ascites could identify the sickest one. In conclusion, MELD is superior to other score systems in predicting short-term post-transplant survival in patients with HBV-related liver disease. Among patients with MELD score >35, a new prognostic model can identify the sickest patients who should be excluded from waiting list to prevent wasteful transplantation. PMID:28198820

  7. Validation of a predictive model for survival and growth of Salmonella Typhimurium DT104 on chicken skin for extrapolation to a previous history of frozen storage

    USDA-ARS?s Scientific Manuscript database

    A predictive model for survival and growth of Salmonella Typhimurium DT104 on chicken skin was evaluated for its ability to predict survival and growth of the same organism after frozen storage for 6 days at -20 C. Experimental methods used to collect data for model development were the same as tho...

  8. Levels of gemcitabine transport and metabolism proteins predict survival times of patients treated with gemcitabine for pancreatic adenocarcinoma.

    PubMed

    Maréchal, Raphaël; Bachet, Jean-Baptiste; Mackey, John R; Dalban, Cécile; Demetter, Pieter; Graham, Kathryn; Couvelard, Anne; Svrcek, Magali; Bardier-Dupas, Armelle; Hammel, Pascal; Sauvanet, Alain; Louvet, Christophe; Paye, François; Rougier, Philippe; Penna, Christophe; André, Thierry; Dumontet, Charles; Cass, Carol E; Jordheim, Lars Petter; Matera, Eva-Laure; Closset, Jean; Salmon, Isabelle; Devière, Jacques; Emile, Jean-François; Van Laethem, Jean-Luc

    2012-09-01

    Patients who undergo surgery for pancreatic ductal adenocarcinoma (PDAC) frequently receive adjuvant gemcitabine chemotherapy. Key determinants of gemcitabine cytotoxicity include the activities of the human equilibrative nucleoside transporter 1 (hENT1), deoxycytidine kinase (dCK), and ribonucleotide reductase subunit 1 (RRM1). We investigated whether tumor levels of these proteins were associated with efficacy of gemcitabine therapy following surgery. Sequential samples of resected PDACs were retrospectively collected from 434 patients at 5 centers; 142 patients did not receive adjuvant treatment (33%), 243 received adjuvant gemcitabine-based regimens (56%), and 49 received nongemcitabine regimens (11%). We measured protein levels of hENT1, dCK, and RRM1 by semiquantitative immunohistochemistry with tissue microarrays and investigated their relationship with patients' overall survival time. The median overall survival time of patients was 32.0 months. Among patients who did not receive adjuvant treatment, levels of hENT1, RRM1, and dCK were not associated with survival time. Among patients who received gemcitabine, high levels of hENT1 and dCK were significantly associated with longer survival time (hazard ratios of 0.34 [P < .0001] and 0.57 [P = .012], respectively). Interaction tests for gemcitabine administration and hENT1 and dCK status were statistically significant (P = .0007 and P = .016, respectively). On multivariate analysis of this population, hENT1 and dCK retained independent predictive values, and those patients with high levels of each protein had the longest survival times following adjuvant therapy with gemcitabine. High levels of hENT1 and dCK in PDAC predict longer survival times in patients treated with adjuvant gemcitabine. Copyright © 2012 AGA Institute. Published by Elsevier Inc. All rights reserved.

  9. Von Willebrand factor and alkaline phosphatase predict re-transplantation-free survival after the first liver transplantation

    PubMed Central

    Wannhoff, Andreas; Rauber, Conrad; Friedrich, Kilian; Rupp, Christian; Stremmel, Wolfgang; Weiss, Karl Heinz; Schemmer, Peter

    2016-01-01

    Background After liver transplantation (LT), there are liver-related, infectious and cardiovascular complications that contribute to reduced graft survival. These conditions are associated with an increase in the Von Willebrand factor antigen (VWF-Ag), which was previously correlated with survival in cirrhotic patients. Objective Evaluate VWF-Ag as a predictive marker of re-transplantation-free survival in patients after LT. Methods We measured VWF-Ag in patients after first LT and then followed them prospectively with regard to the primary endpoint, namely re-transplantation-free survival. Results There were 6 out of 80 patients who died or received re-LT during follow-up. In these patients, the median VWF-Ag was 510.6%, which was significantly higher (p = 0.001) than in the patients who were alive at the end of follow-up (with a median VWF-Ag = 186.8%). At a cut-off of 286.8%, VWF-Ag was significantly correlated with re-transplantation-free survival (p < 0.001). VWF-Ag was independently associated with re-transplantation-free survival in a multivariate analysis; as was alkaline phosphatase (ALP), but not the model of end-stage liver disease (MELD) score, donor age, nor cold ischemia time. A score combining VWF-Ag and ALP showed an impressive capability in the receiver operating characteristic (ROC) analysis (with area under the curve (AUC) = 0.958) to distinguish between patients with regard to the primary endpoint. Conclusions VWF-Ag is a non-invasive marker that can predict outcome in patients after LT. Its diagnostic performance increased when combined with ALP in a newly developed scoring system. PMID:28405326

  10. cN-II expression predicts survival in patients receiving gemcitabine for advanced non-small cell lung cancer.

    PubMed

    Sève, Pascal; Mackey, John R; Isaac, Sylvie; Trédan, Olivier; Souquet, Pierre Jean; Pérol, Maurice; Cass, Carol; Dumontet, Charles

    2005-09-01

    Resistance to gemcitabine is likely to be multifactorial and could involve a number of mechanisms involved in drug penetration, metabolism and targeting. In vitro studies of resistant human cell lines have confirmed that human equilibrative nucleoside transporter 1 (hENT1)-deficient cells display resistance to gemcitabine. Overexpression of certain nucleotidases, such as cN-II, has also been frequently shown in gemcitabine-resistant models. In this study, we applied immunohistochemical methods to assess the protein abundance of cN-II, hENT1, human concentrative nucleoside transporter 3 (hCNT3) and deoxycitidine kinase (dCK) in malignant cells in from 43 patients with treatment-naïve locally advanced or metastatic non-small cell lung cancer (NSCLC). All patients subsequently received gemcitabine-based chemotherapy. Response to chemotherapy, progression-free survival (PFS), and overall survival (OS) were correlated with abundance of these proteins. Among the 43 samples, only 7 (16%) expressed detectable hENT1, with a low percentage of positive cells, 18 expressed hCNT3 (42%), 36 (86%) expressed cN-II and 28 (66%) expressed dCK. In univariate analysis, only cN-II expression levels were correlated with overall survival. None of the parameters were correlated with freedom from progression survival nor with response. Patients with low levels of expression of cN-II (less than 40% positively stained cells) had worse overall survival than patients with higher levels of cN-II expression (6 months and 11 months, respectively). In a multivariate analysis taking into account age, sex, weight loss, stage and immunohistochemical results, cN-II was the only predictive factor associated with overall survival. This study suggests that cN-II nucleotidase expression levels identify subgroups of NSCLC patients with different outcomes under gemcitabine-based therapy. Larger prospective studies are warranted to confirm the predictive value of cN-II in these patients.

  11. Pretransplant Prediction of Posttransplant Survival for Liver Recipients with Benign End-Stage Liver Diseases: A Nonlinear Model

    PubMed Central

    Chen, Bo; Li, You Ping; Yan, Lu Nan; Wen, Tian Fu; Li, Bo

    2012-01-01

    Background The scarcity of grafts available necessitates a system that considers expected posttransplant survival, in addition to pretransplant mortality as estimated by the MELD. So far, however, conventional linear techniques have failed to achieve sufficient accuracy in posttransplant outcome prediction. In this study, we aim to develop a pretransplant predictive model for liver recipients' survival with benign end-stage liver diseases (BESLD) by a nonlinear method based on pretransplant characteristics, and compare its performance with a BESLD-specific prognostic model (MELD) and a general-illness severity model (the sequential organ failure assessment score, or SOFA score). Methodology/Principal Findings With retrospectively collected data on 360 recipients receiving deceased-donor transplantation for BESLD between February 1999 and August 2009 in the west China hospital of Sichuan university, we developed a multi-layer perceptron (MLP) network to predict one-year and two-year survival probability after transplantation. The performances of the MLP, SOFA, and MELD were assessed by measuring both calibration ability and discriminative power, with Hosmer-Lemeshow test and receiver operating characteristic analysis, respectively. By the forward stepwise selection, donor age and BMI; serum concentration of HB, Crea, ALB, TB, ALT, INR, Na+; presence of pretransplant diabetes; dialysis prior to transplantation, and microbiologically proven sepsis were identified to be the optimal input features. The MLP, employing 18 input neurons and 12 hidden neurons, yielded high predictive accuracy, with c-statistic of 0.91 (P<0.001) in one-year and 0.88 (P<0.001) in two-year prediction. The performances of SOFA and MELD were fairly poor in prognostic assessment, with c-statistics of 0.70 and 0.66, respectively, in one-year prediction, and 0.67 and 0.65 in two-year prediction. Conclusions/Significance The posttransplant prognosis is a multidimensional nonlinear problem, and the

  12. Polymorphisms in MicroRNA Binding Sites Predict Colorectal Cancer Survival

    PubMed Central

    Yang, Ying-Pi; Ting, Wen-Chien; Chen, Lu-Min; Lu, Te-Ling; Bao, Bo-Ying

    2017-01-01

    Background: MicroRNAs (miRNAs) mediate negative regulation of target genes through base pairing, and aberrant miRNA expression has been described in cancers. We hypothesized that single nucleotide polymorphisms (SNPs) within miRNA target sites might influence clinical outcomes in patients with colorectal cancer. Methods: Sixteen common SNPs within miRNA target sites were identified, and the association between these SNPs and overall survival was assessed in colorectal cancer patients using Kaplan-Meier analysis, Cox regression model, and survival tree analysis. Results: Survival tree analysis identified a higher-order genetic interaction profile consisting of the RPS6KB1 rs1051424 and ZNF839 rs11704 that was significantly associated with overall survival. The 5-year survival rates were 74.6%, 62.7%, and 57.1% for the low-, medium-, and high-risk genetic profiles, respectively (P = 0.006). The genetic interaction profile remained significant even after adjusting for potential risk factors. Additional in silico analysis provided evidence that rs1051424 and rs11704 affect RPS6KB1 and ZNF839 expressions, which in turn is significantly correlated with prognosis in colorectal cancer. Conclusion: Our results suggest that the genetic interaction profiles among SNPs within miRNA target sites might be prognostic markers for colorectal cancer survival. PMID:28138309

  13. X protein mutations in hepatitis B virus DNA predict postoperative survival in hepatocellular carcinoma.

    PubMed

    Xie, Ying; Liu, Shufeng; Zhao, Yue; Guo, Zhanjun; Xu, Jinsheng

    2014-10-01

    Hepatitis B virus (HBV) DNA is prone to mutations because of the proofreading deficiencies of HBV polymerase. The postoperative prognostic value of HBV mutations in HBV X protein (HBx) gene was assessed in HBV associated hepatocellular carcinoma (HCC) patients. The HBx gene was amplified and sequenced, the HBV mutations was identified according to NCBI database ( http://www.ncbi.nlm.nih.gov/genome/5536 ). The relationship between the HBV mutations and HCC survival was compared. Survival curves were generated using the Kaplan-Meier method, and comparisons between the curves were made using the log-rank test. Multivariate survival analysis was performed using a Cox proportional hazards model. After adjusting for clinical characteristics, the following eight mutational sites were identified as statistically significant independent predictors of HCC survival: 1383, 1461, 1485, 1544, 1613, 1653, 1719, and 1753. In addition, the following four mutational sites were identified for their association with survival at a border-line significance level: 1527, 1637, 1674, and 1762/1764. A total of 12 mutations in HBx gene region were identified as independent predictors of postoperative survival in HCC patients. The analysis of HBV DNA mutations may help identify patient subgroups with poor prognosis and may help refine therapeutic decisions regarding HCC patients.

  14. Karnofsky Performance Score Is Predictive of Survival After Palliative Irradiation of Metastatic Bile Duct Cancer.

    PubMed

    Rades, Dirk; Bolm, Louisa; Kaesmann, Lukas; Bartscht, Tobias

    2017-02-01

    Palliative irradiation is effective in alleviating symptoms in patients with metastatic cancer in general. However, little data exist regarding irradiation of metastatic bile duct cancer. Selection of the best regimen for such a patient should be based on their survival prognosis. This study included five patients irradiated for metastatic bile duct cancer and aimed to identify predictors of survival by analyzing six factors: age, gender, general condition (Karnofsky performance score), metastatic site receiving palliative irradiation, metastases outside irradiated sites and time between diagnosis of bile duct cancer and palliative irradiation. In the whole series, median survival was 3 months. Survival rates at 3 and 6 months were 40% and 40%, respectively. A Karnofsky performance score >70% had a borderline significant association with better survival (p=0.05). Karnofsky performance score was identified as predictor of survival and should be considered when assigning the radiation regimen to patients with metastatic bile duct cancer. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  15. Pulmonary Vascular Distensibility Predicts Pulmonary Hypertension Severity, Exercise Capacity, and Survival in Heart Failure

    PubMed Central

    Malhotra, Rajeev; Dhakal, Bishnu P.; Eisman, Aaron S.; Pappagianopoulos, Paul P.; Dress, Ashley; Weiner, Rory B.; Baggish, Aaron L.; Semigran, Marc J.; Lewis, Gregory D.

    2016-01-01

    Background Pulmonary vascular (PV) distensibility, defined as the percent increase in pulmonary vessel diameter per mmHg increase in pressure, permits the pulmonary arteries to increase in size to accommodate increased blood flow. We hypothesized that PV distensibility is abnormally low in patients with heart failure (HF) and serves as an important determinant of right ventricular performance and exercise capacity. Methods and Results Patients with HF and preserved ejection fraction (HFpEF, n=48), HF and reduced ejection fraction (HFrEF, n=55), pulmonary hypertension without left-heart failure (PAH, n=18), and control subjects (n=30) underwent cardiopulmonary exercise testing with invasive hemodynamic monitoring and first-pass radionuclide ventriculography. PV distensibility was derived from 1257 matched measurements (mean±SD, 8±2 per subject) of PA pressure, PA wedge pressure and cardiac output. PV distensibility was lowest in the PAH group (0.40±0.24% per mmHg) and intermediate in the HFpEF and HFrEF groups (0.92±0.39 and 0.84±0.33% per mmHg, respectively) compared to the control group (1.39±0.32% per mmHg, P<0.0001 for all three). PV distensibility was associated with change in RVEF (ρ=0.39, P<0.0001) with exercise and was an independent predictor of peak VO2. PV distensibility also predicted cardiovascular mortality independent of peak VO2 in HF patients (n=103, Cox HR 0.30, 95% CI 0.10–0.93, P=0.036). In a subset of HFrEF patients (n=26), 12 weeks of treatment with the pulmonary vasodilator sildenafil or placebo led to a 24.6% increase in PV distensibility (P=0.015) in the sildenafil group only. Conclusions PV distensibility is reduced in patients with HF and PAH and is closely related to RV systolic function during exercise, maximal exercise capacity, and survival. Furthermore, PV distensibility is modifiable with selective pulmonary vasodilator therapy and may represent an important target for therapy in selected HF patients with pulmonary

  16. Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

    PubMed

    Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

    2014-03-01

    This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case

  17. Social affiliation matters: both same-sex and opposite-sex relationships predict survival in wild female baboons

    PubMed Central

    Archie, Elizabeth A.; Tung, Jenny; Clark, Michael; Altmann, Jeanne; Alberts, Susan C.

    2014-01-01

    Social integration and support can have profound effects on human survival. The extent of this phenomenon in non-human animals is largely unknown, but such knowledge is important to understanding the evolution of both lifespan and sociality. Here, we report evidence that levels of affiliative social behaviour (i.e. ‘social connectedness’) with both same-sex and opposite-sex conspecifics predict adult survival in wild female baboons. In the Amboseli ecosystem in Kenya, adult female baboons that were socially connected to either adult males or adult females lived longer than females who were socially isolated from both sexes—females with strong connectedness to individuals of both sexes lived the longest. Female social connectedness to males was predicted by high dominance rank, indicating that males are a limited resource for females, and females compete for access to male social partners. To date, only a handful of animal studies have found that social relationships may affect survival. This study extends those findings by examining relationships to both sexes in by far the largest dataset yet examined for any animal. Our results support the idea that social effects on survival are evolutionarily conserved in social mammals. PMID:25209936

  18. Social affiliation matters: both same-sex and opposite-sex relationships predict survival in wild female baboons.

    PubMed

    Archie, Elizabeth A; Tung, Jenny; Clark, Michael; Altmann, Jeanne; Alberts, Susan C

    2014-10-22

    Social integration and support can have profound effects on human survival. The extent of this phenomenon in non-human animals is largely unknown, but such knowledge is important to understanding the evolution of both lifespan and sociality. Here, we report evidence that levels of affiliative social behaviour (i.e. 'social connectedness') with both same-sex and opposite-sex conspecifics predict adult survival in wild female baboons. In the Amboseli ecosystem in Kenya, adult female baboons that were socially connected to either adult males or adult females lived longer than females who were socially isolated from both sexes--females with strong connectedness to individuals of both sexes lived the longest. Female social connectedness to males was predicted by high dominance rank, indicating that males are a limited resource for females, and females compete for access to male social partners. To date, only a handful of animal studies have found that social relationships may affect survival. This study extends those findings by examining relationships to both sexes in by far the largest dataset yet examined for any animal. Our results support the idea that social effects on survival are evolutionarily conserved in social mammals. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  19. Corticosterone levels predict survival probabilities of Galápagos marine iguanas during El Niño events

    PubMed Central

    Romero, L. Michael; Wikelski, Martin

    2001-01-01

    Plasma levels of corticosterone are often used as a measure of “stress” in wild animal populations. However, we lack conclusive evidence that different stress levels reflect different survival probabilities between populations. Galápagos marine iguanas offer an ideal test case because island populations are affected differently by recurring El Niño famine events, and population-level survival can be quantified by counting iguanas locally. We surveyed corticosterone levels in six populations during the 1998 El Niño famine and the 1999 La Niña feast period. Iguanas had higher baseline and handling stress-induced corticosterone concentrations during famine than feast conditions. Corticosterone levels differed between islands and predicted survival through an El Niño period. However, among individuals, baseline corticosterone was only elevated when body condition dropped below a critical threshold. Thus, the population-level corticosterone response was variable but nevertheless predicted overall population health. Our results lend support to the use of corticosterone as a rapid quantitative predictor of survival in wild animal populations. PMID:11416210

  20. Predicting Structure-Function Relations and Survival following Surgical and Bronchoscopic Lung Volume Reduction Treatment of Emphysema

    PubMed Central

    Mondoñedo, Jarred R.

    2017-01-01

    Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (bLVR) are palliative treatments aimed at reducing hyperinflation in advanced emphysema. Previous work has evaluated functional improvements and survival advantage for these techniques, although their effects on the micromechanical environment in the lung have yet to be determined. Here, we introduce a computational model to simulate a force-based destruction of elastic networks representing emphysema progression, which we use to track the response to lung volume reduction via LVRS and bLVR. We find that (1) LVRS efficacy can be predicted based on pre-surgical network structure; (2) macroscopic functional improvements following bLVR are related to microscopic changes in mechanical force heterogeneity; and (3) both techniques improve aspects of survival and quality of life influenced by lung compliance, albeit while accelerating disease progression. Our model predictions yield unique insights into the microscopic origins underlying emphysema progression before and after lung volume reduction. PMID:28182686

  1. Predicting Structure-Function Relations and Survival following Surgical and Bronchoscopic Lung Volume Reduction Treatment of Emphysema.

    PubMed

    Mondoñedo, Jarred R; Suki, Béla

    2017-02-01

    Lung volume reduction surgery (LVRS) and bronchoscopic lung volume reduction (bLVR) are palliative treatments aimed at reducing hyperinflation in advanced emphysema. Previous work has evaluated functional improvements and survival advantage for these techniques, although their effects on the micromechanical environment in the lung have yet to be determined. Here, we introduce a computational model to simulate a force-based destruction of elastic networks representing emphysema progression, which we use to track the response to lung volume reduction via LVRS and bLVR. We find that (1) LVRS efficacy can be predicted based on pre-surgical network structure; (2) macroscopic functional improvements following bLVR are related to microscopic changes in mechanical force heterogeneity; and (3) both techniques improve aspects of survival and quality of life influenced by lung compliance, albeit while accelerating disease progression. Our model predictions yield unique insights into the microscopic origins underlying emphysema progression before and after lung volume reduction.

  2. Blood neutrophil-lymphocyte ratio predicts survival after hepatectomy for hepatocellular carcinoma: A propensity score-based analysis

    PubMed Central

    Yang, Hao-Jie; Guo, Zhe; Yang, Yu-Ting; Jiang, Jing-Hang; Qi, Ya-Peng; Li, Ji-Jia; Li, Le-Qun; Xiang, Bang-De

    2016-01-01

    AIM: To investigate whether an elevated preoperative neutrophil-to-lymphocyte ratio (NLR) can predict poor survival in patients with hepatocellular carcinoma (HCC). METHODS: We retrospectively reviewed 526 patients with HCC who underwent surgery between 2004 and 2011. RESULTS: Preoperative NLR ≥ 2.81 was an independent predictor of poor disease-free survival (DFS, P < 0.001) and overall survival (OS, P = 0.044). Compared with patients who showed a preoperative NLR < 2.81 and postoperative increase, patients who showed preoperative NLR ≥ 2.81 and postoperative decrease had worse survival (DFS, P < 0.001; OS, P < 0.001). Among patients with preoperative NLR ≥ 2.81, survival was significantly higher among those showing a postoperative decrease in NLR than among those showing an increase (DFS, P < 0.001; OS, P < 0.001). When elevated, alpha-fetoprotein (AFP) provided no prognostic information, and so preoperative NLR ≥ 2.81 may be a good complementary indicator of poor OS whenever AFP levels are low or high. CONCLUSION: Preoperative NLR ≥ 2.81 may be an indicator of poor DFS and OS in patients with HCC undergoing surgery. Preoperative NLR ≥ 2.81 may be a good complementary indicator of poor OS when elevated AFP levels provide no prognostic information. PMID:27275101

  3. External validation of a web-based prognostic tool for predicting survival for patients in hospice care.

    PubMed

    Miladinovic, Branko; Mhaskar, Rahul; Kumar, Ambuj; Kim, Sehwan; Schonwetter, Ronald; Djulbegovic, Benjamin

    2013-01-01

    Prognostat is an interactive Web-based prognostic tool for estimating hospice patient survival based on a patient's Palliative Performance Scale (PPS) score, age, gender, and cancer status. The tool was developed using data from 5,893 palliative care patients, which was collected at the Victoria Hospice in Victoria, British Columbia, Canada, beginning in 1994. This study externally validates Prognostat with a retrospective cohort of 590 hospice patients at LifePath Hospice and Palliative Care in Florida, USA. The criteria used to evaluate the prognostic performance were the Brier score, area under the receiver operating curve, discrimination slope, and Hosmer-Lemeshow goodness-of-fit test. Though the Kaplan-Meier curves show each PPS level to be distinct and significantly different, the findings reveal low agreement between observed survival in our cohort of patients and survival predicted by the prognostic tool. Before developing a new prognostic model, researchers are encouraged to update survival estimates obtained using Prognostat with the information from their cohort of patients. If it is to be useful to patients and clinicians, Prognostat needs to explicitly report patient risk scores and estimates of baseline survival.

  4. Graft and Patient Survival Outcomes of a Third Kidney Transplant

    PubMed Central

    Redfield, Robert R.; Gupta, Meera; Rodriguez, Eduardo; Wood, Alexander; Abt, Peter L.; Levine, Matthew H.

    2014-01-01

    Background The waiting time for deceased donor renal transplantation in the United States continues to grow. Retransplant candidates make up a small but growing percentage of the overall transplant waiting list and raise questions about the stewardship of scarce resources. The utility of renal transplantation among individuals with two prior renal transplants is not described in the literature and we thus sought to determine the survival benefit associated with a third kidney transplant (3KT). Methods Multivariable Cox regression models were created to determine characteristics associated with 3KT outcomes and the survival benefit of 3KT among recipients wait listed and transplanted within the United States between 1995 and 2009. Results 4,334 patients were waitlisted for a 3KT and 2,492 patients received a 3KT. In a multivariate analysis, 3KT demonstrated an overall patient survival benefit compared to the wait list (HR-0.379, CI=0.302-0.475 p<0.001) for those awaiting their first, second or third kidney transplants, although an inferior graft outcome compared to first kidney transplants. The time to survival benefit did not accrue until 8-months after transplant. Additionally we found that the duration of second graft survival was predictive of third graft survival, such that second graft survival beyond 5 years is associated with superior 3KT graft survival. Second graft loss in 30 days or less was not associated with inferior 3KT graft survival. Conclusion 3KT achieves a survival benefit over remaining on the wait list, although is associated with inferior graft outcomes compared to first kidney transplants. Graft survival of the second transplant beyond 5 years is associated with superior 3KT graft survival. PMID:25121473

  5. Predicting Fluid Responsiveness Using Bedside Ultrasound Measurements of the Inferior Vena Cava and Physician Gestalt in the Emergency Department of an Urban Public Hospital in Sub-Saharan Africa.

    PubMed

    Sawe, Hendry Robert; Haeffele, Cathryn; Mfinanga, Juma A; Mwafongo, Victor G; Reynolds, Teri A

    Bedside inferior vena cava (IVC) ultrasound has been proposed as a non-invasive measure of volume status. We compared ultrasound measurements of the caval index (CI) and physician gestalt to predict blood pressure response in patients requiring intravenous fluid resuscitation. This was a prospective study of adult emergency department patients requiring fluid resuscitation. A structured data sheet was used to record serial vital signs and the treating clinician's impression of patient volume status and cause of hypotension. Bedside ultrasound CI measurements were performed at baseline and after each 500mL of fluid. Receiver operating characteristic (ROC) curve analysis was performed to characterize the relationship between CI and Physician gestalt, and the change in mean arterial pressure (MAP). We enrolled 364 patients, 52% male, mean age 36 years. Indications for fluid resuscitation were haemorrhage (54%), dehydration (30%), and sepsis (17%). Receiver operating characteristic curve analysis found optimal CI cut-off values of 45%, 52% and 53% to predict a MAP rise of 5, 8 and 10 mmHg per litre of fluid, respectively. The sensitivity and specificity of CI of 50% for predicting a 10mmHg increase in MAP per litre were 88% (95%CI 81-93%) and 73% (95%CI 67-79%), respectively, area under the curve (AUC) = 0.85 (0.81-0.89). The sensitivity and specificity of physician gestalt estimate of volume depletion severity were 68% (95%CI 60-75%) and 86% (95%CI 80-90%), respectively, AUC = 0.83 (95% CI: 0.79-0.87). Those with a baseline CI ≥ 50% (51% of patients) had a 2.8-fold greater fluid responsiveness than those with a baseline CI<50% (p<0.0001). Ultrasound measurement of the CI can predict blood pressure response among patients requiring intravenous fluid resuscitation and may be useful in early identification of patients who will benefit most from volume resuscitation, and those who will likely require other interventions.

  6. Bilateral inferior petrosal sinus sampling

    PubMed Central

    Grossrubatscher, Erika; Dalino Ciaramella, Paolo; Boccardi, Edoardo

    2016-01-01

    Simultaneous bilateral inferior petrosal sinus sampling (BIPSS) plays a crucial role in the diagnostic work-up of Cushing’s syndrome. It is the most accurate procedure in the differential diagnosis of hypercortisolism of pituitary or ectopic origin, as compared with clinical, biochemical and imaging analyses, with a sensitivity and specificity of 88–100% and 67–100%, respectively. In the setting of hypercortisolemia, ACTH levels obtained from venous drainage of the pituitary are expected to be higher than the levels of peripheral blood, thus suggesting pituitary ACTH excess as the cause of hypercortisolism. Direct stimulation of the pituitary corticotroph with corticotrophin-releasing hormone enhances the sensitivity of the procedure. The procedure must be undertaken in the presence of hypercortisolemia, which suppresses both the basal and stimulated secretory activity of normal corticotrophic cells: ACTH measured in the sinus is, therefore, the result of the secretory activity of the tumor tissue. The poor accuracy in lateralization of BIPSS (positive predictive value of 50–70%) makes interpetrosal ACTH gradient alone not sufficient for the localization of the tumor. An accurate exploration of the gland is recommended if a tumor is not found in the predicted area. Despite the fact that BIPSS is an invasive procedure, the occurrence of adverse events is extremely rare, particularly if it is performed by experienced operators in referral centres. PMID:27352844

  7. Bilateral inferior petrosal sinus sampling.

    PubMed

    Zampetti, Benedetta; Grossrubatscher, Erika; Dalino Ciaramella, Paolo; Boccardi, Edoardo; Loli, Paola

    2016-07-01

    Simultaneous bilateral inferior petrosal sinus sampling (BIPSS) plays a crucial role in the diagnostic work-up of Cushing's syndrome. It is the most accurate procedure in the differential diagnosis of hypercortisolism of pituitary or ectopic origin, as compared with clinical, biochemical and imaging analyses, with a sensitivity and specificity of 88-100% and 67-100%, respectively. In the setting of hypercortisolemia, ACTH levels obtained from venous drainage of the pituitary are expected to be higher than the levels of peripheral blood, thus suggesting pituitary ACTH excess as the cause of hypercortisolism. Direct stimulation of the pituitary corticotroph with corticotrophin-releasing hormone enhances the sensitivity of the procedure. The procedure must be undertaken in the presence of hypercortisolemia, which suppresses both the basal and stimulated secretory activity of normal corticotrophic cells: ACTH measured in the sinus is, therefore, the result of the secretory activity of the tumor tissue. The poor accuracy in lateralization of BIPSS (positive predictive value of 50-70%) makes interpetrosal ACTH gradient alone not sufficient for the localization of the tumor. An accurate exploration of the gland is recommended if a tumor is not found in the predicted area. Despite the fact that BIPSS is an invasive procedure, the occurrence of adverse events is extremely rare, particularly if it is performed by experienced operators in referral centres.

  8. Nomograms Predicting Platinum Sensitivity, Progression-Free Survival, and Overall Survival Using Pretreatment Complete Blood Cell Counts in Epithelial Ovarian Cancer.

    PubMed

    Paik, E Sun; Sohn, Insuk; Baek, Sun-Young; Shim, Minhee; Choi, Hyun Jin; Kim, Tae-Joong; Choi, Chel Hun; Lee, Jeong-Won; Kim, Byoung-Gie; Lee, Yoo-Young; Bae, Duk-Soo

    2017-07-01

    This study was conducted to evaluate the prognostic significance of pre-treatment complete blood cell count (CBC), including white blood cell (WBC) differential, in epithelial ovarian cancer (EOC) patients with primary debulking surgery (PDS) and to develop nomograms for platinum sensitivity, progression-free survival (PFS), and overall survival (OS). We retrospectively reviewed the records of 757 patients with EOC whose primary treatment consisted of surgical debulking and chemotherapy at Samsung Medical Center from 2002 to 2012. We subsequently created nomograms for platinum sensitivity, 3-year PFS, and 5-year OS as prediction models for prognostic variables including age, stage, grade, cancer antigen 125 level, residual disease after PDS, and pre-treatment WBC differential counts. The models were then validated by 10-fold cross-validation (CV). In addition to stage and residual disease after PDS, which are known predictors, lymphocyte and monocyte count were found to be significant prognostic factors for platinum-sensitivity, platelet count for PFS, and neutrophil count for OS on multivariate analysis. The area under the curves of platinum sensitivity, 3-year PFS, and 5-year OS calculated by the 10-fold CV procedure were 0.7405, 0.8159, and 0.815, respectively. Prognostic factors including pre-treatment CBC were used to develop nomograms for platinum sensitivity, 3-year PFS, and 5-year OS of patients with EOC. These nomograms can be used to better estimate individual outcomes.

  9. Absolute Lymphocyte Count (ALC) after Induction Treatment Predicts Survival of Pediatric Patients with Acute Lymphoblastic Leukemia.

    PubMed

    Farkas, Tamas; Müller, Judit; Erdelyi, Daniel J; Csoka, Monika; Kovacs, Gabor T

    2017-01-30

    Absolute Lymphocyte Count (ALC) has been recently established as a prognostic factor of survival in pediatric Acute Lymphoblastic Leukemia (ALL). A retrospective analysis of 132 patients treated according the BFM - ALLIC 2002 protocol was performed in a single institution. A possible association between ALC values and Overall Survival (OS) or Event-Free Survival (EFS) was evaluated at multiple time points during induction chemotherapy. ALC higher than 350 cells/μL measured on the 33th day of induction was associated with better Overall- and Event-Free Survival in both Kaplan-Meier (OS 88.6% vs. 40%; p < 0.001 / EFS 81.6% vs. 30%; p < 0.001) and Cox regression (OS HR 8.77 (3.31-23.28); p < 0.001) and EFS HR 6.61 (2.79-15.63); p < 0.001) analyses. There was no association between survival and measured ALC values from earlier time points (day of diagnosis, days 8 and 15) of induction therapy. Patients with low ALC values tend to have higher risk (MR or HR groups) and a higher age at diagnosis (>10 years). With help of day 33 ALC values of 350 cells/μL cutoff it was possible to refine day 33 flow cytometry (FC) Minimal Residual Disease (MRD) results within the negative cohort: higher ALC values were significantly associated with better survival. ALC on day 33 (350 cells/μL) remained prognostic for OS and EFS in multivariate analysis after adjusting it for age, cytogenetics, immunophenotype and FC MRD of induction day 33. According to these findings ALC on day 33 of induction is a strong predictor of survival in pediatric ALL.

  10. Molecular stratification of metastatic melanoma using gene expression profiling: Prediction of survival outcome and benefit from molecular targeted therapy.

    PubMed

    Cirenajwis, Helena; Ekedahl, Henrik; Lauss, Martin; Harbst, Katja; Carneiro, Ana; Enoksson, Jens; Rosengren, Frida; Werner-Hartman, Linda; Törngren, Therese; Kvist, Anders; Fredlund, Erik; Bendahl, Pär-Ola; Jirström, Karin; Lundgren, Lotta; Howlin, Jillian; Borg, Åke; Gruvberger-Saal, Sofia K; Saal, Lao H; Nielsen, Kari; Ringnér, Markus; Tsao, Hensin; Olsson, Håkan; Ingvar, Christian; Staaf, Johan; Jönsson, Göran

    2015-05-20

    Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.

  11. Using weather indices to predict survival of winter wheat in a cool temperate environment.

    PubMed

    Hayhoe, H N; Lapen, D R; Andrews, C J

    2003-03-01

    Seven years of winter survival data for winter wheat ( Triticum aestivum L.) were collected on a loam soil located on the Central Experimental Farm at Ottawa, Ontario (45 degrees 23'N, 75 degrees 43'W). The site was low-lying and subject to frequent winter flooding and ice-sheet formation. Two cultivars, a soft white and a hard red winter wheat, were planted in September. Crop establishment was measured in late fall and the percentage survival was measured in April of the following year. Meteorological data, which were available from the nearby weather site, were used to develop a large set of monthly weather indices that were felt to be important for winter survival. The objective of the study was to use genetic selection algorithms and artificial neural networks to select a subset of critical weather factors and topographic features and to model winter survival. The six weather indices selected were the total rain depth for December (mm), the total rain depth for February (mm), the number of days of the month with snow on the ground for January, the extreme minimum observed daily air temperature for March ( degrees C), the number of days of the month with snow on the ground for March, and the number of days of April with a daily maximum air temperature greater than 0 degrees C. It was found 89% of the variation in winter survival could be explained by these six weather indices, the cultivar, elevation and plot location.

  12. Diagnosis of pseudoprogression using MRI perfusion in patients with glioblastoma multiforme may predict improved survival

    PubMed Central

    Gahramanov, Seymur; Varallyay, Csanad; Tyson, Rose Marie; Lacy, Cynthia; Fu, Rongwei; Netto, Joao Prola; Nasseri, Morad; White, Tricia; Woltjer, Randy L; Gultekin, Sakir Humayun; Neuwelt, Edward A

    2015-01-01

    SUMMARY Aims This retrospective study determined the survival of glioblastoma patients with or without pseudoprogression. Methods A total of 68 patients were included. Overall survival was compared between patients showing pseudoprogression (in most cases diagnosed using perfusion MRI with ferumoxytol) and in patients without pseudoprogession. MGMT methylation status was also analyzed in the pseudoprogression cases. Results Median survival in 24 (35.3%) patients with pseudoprogression was 34.7 months (95% CI: 20.3–54.1), and 13.4 months (95% CI: 11.1–19.5) in 44 (64.7%) patients without pseudoprogression (p < 0.0001). The longest survival was a median of 54.1 months in patients with combination of pseudoprogression and (MGMT) promoter methylation. Conclusion Pseudoprogression is associated with better outcome, especially if concurring with MGMT promoter methylation. Patients never diagnosed with pseudoprogression had poor survival. This study emphasizes the importance of differentiating tumor progression and pseudoprogression using perfusion MRI. PMID:25438810

  13. Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry.

    PubMed

    Gupta, Sunil; Tran, Truyen; Luo, Wei; Phung, Dinh; Kennedy, Richard Lee; Broad, Adam; Campbell, David; Kipp, David; Singh, Madhu; Khasraw, Mustafa; Matheson, Leigh; Ashley, David M; Venkatesh, Svetha

    2014-03-17

    Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes. A regional cancer centre in Australia. Disease-specific data from a purpose-built cancer registry (Evaluation of Cancer Outcomes (ECO)) from 869 patients were used to predict survival at 6, 12 and 24 months. The model was validated with data from a further 94 patients, and results compared to the assessment of five specialist oncologists. Machine-learning prediction using ECO data was compared with that using EAR and a model combining ECO and EAR data. Survival prediction accuracy in terms of the area under the receiver operating characteristic curve (AUC). The ECO model yielded AUCs of 0.87 (95% CI 0.848 to 0.890) at 6 months, 0.796 (95% CI 0.774 to 0.823) at 12 months and 0.764 (95% CI 0.737 to 0.789) at 24 months. Each was slightly better than the performance of the clinician panel. The model performed consistently across a range of cancers, including rare cancers. Combining ECO and EAR data yielded better prediction than the ECO-based model (AUCs ranging from 0.757 to 0.997 for 6 months, AUCs from 0.689 to 0.988 for 12 months and AUCs from 0.713 to 0.973 for 24 months). The best prediction was for genitourinary, head and neck, lung, skin, and upper gastrointestinal tumours. Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes. Importantly, the approach described made use of digital data that is already routinely collected but underexploited by clinical health systems.

  14. Quality of life predicts overall survival in women with platinum-resistant ovarian cancer: an AURELIA substudy.

    PubMed

    Roncolato, F T; Gibbs, E; Lee, C K; Asher, R; Davies, L C; Gebski, V J; Friedlander, M; Hilpert, F; Wenzel, L; Stockler, M R; King, M; Pujade-Lauraine, E

    2017-08-01

    Women with platinum-resistant ovarian cancer are a heterogeneous group whose median overall survival is 12 months. We hypothesized that their quality of life (QoL) scores would be prognostic. Data from AURELIA (n = 326), a randomized trial of chemotherapy with or without bevacizumab, were used to identify baseline QoL domains [EORTC (European Organisation for Research and Treatment of Cancer) QLQ-C30 and OV28] that were significantly associated with overall survival in multivariable Cox regression analyses. Patients were classified as having good, medium, or poor risk. Cutpoints were validated in an independent dataset, CARTAXHY (n = 136). Multivariable analyses of significant QoL domains on survival were adjusted for clinicopathological prognostic factors. The additional QoL information was assessed using C statistic. In AURELIA, all domains, except cognitive function, predicted overall survival in univariable analyses. Physical function (P < 0.001) and abdominal/gastrointestinal symptom (P < 0.001) scores remained significant in multivariable models. In high (score <67), medium (67-93), and low (>93) risk categories for physical function, median overall survival was 11.0, 14.7, and 19.3 months, respectively (P < 0.001). In CARTAXHY, median overall survival was 7.9, 16.2, and 23.9 months (P < 0.001), respectively. For high- (>44), medium- (13-44), and low- (<13) risk categories for abdominal/gastrointestinal symptoms, median overall survival was 11.9, 14.3, and 19.7 months in AURELIA (P < 0.001) and 10.5, 19.6, and 24.1 months in CARTAXHY (P = 0.02). Physical function (P = 0.02) and abdominal/gastrointestinal symptoms (P = 0.03) remained independent prognostic factors after adjustment for clinicopathological factors. The C statistic of the full model was 0.71. For QoL factors alone, patient factors alone and disease factors alone, the C statistics were 0.61, 0.61, and 0.67 respectively. Physical function and

  15. Pancreatectomy Predicts Improved Survival for Pancreatic Adenocarcinoma: Results of an Instrumental Variable Analysis

    PubMed Central

    McDowell, Bradley D.; Chapman, Cole G.; Smith, Brian J.; Button, Anna M.; Chrischilles, Elizabeth A.; Mezhir, James J.

    2014-01-01

    Background and Objective Pancreatic resection is the standard therapy for patients with stage I/II pancreatic ductal adenocarcinoma (PDA), yet many studies demonstrate low rates of resection. The objective of this study is to evaluate whether increasing resection rates would result in an increase in average survival in patients with stage I/II PDA. Methods SEER data were analyzed for patients with stage I/II pancreatic head cancers treated from 2004–2009. Pancreatectomy rates were examined within Health Service Areas (HSA) across 18 SEER regions. An instrumental variables (IV) analysis was performed, using HSA rates as an instrument, to determine the impact of increasing resection rates on survival. Results Pancreatectomy was performed in 4,322 of the 8,323 patients evaluated with stage I/II PDA (overall resection rate=51.9%). The resection rate across HSAs ranged from an average of 38.6% in the lowest quintile to 67.3% in the highest quintile. Median survival was improved in HSAs with higher resection rates. IV analysis revealed that, for patients whose treatment choices were influenced by the rates of resection in their geographic region, pancreatectomy was associated with a statistically significant increase in overall survival. Conclusions When controlling for confounders using IV analysis, pancreatectomy is associated with a statistically significant increase in survival for patients with resectable PDA. Based on these results, if resection rates were to increase in select patients, then average survival would also be expected to increase. It is important that this information be provided to physicians and patients so they can properly weigh the risks and advantages of pancreatectomy as treatment for PDA. PMID:24979599

  16. 139 Clinically Applicable and Biologically Validated MRI Radiomic Test Method Predicts Glioblastoma Genomic Landscape and Survival.

    PubMed

    Zinn, Pascal O; Singh, Sanjay K; Kotrotsou, Aikaterini; Zandi, Faramak; Thomas, Ginu; Hatami, Masumeh; Luedi, Markus M; Elakkad, Ahmed; Hassan, Islam; Gumin, Joy; Sulman, Erik P; Lang, Frederick F; Colen, Rivka R

    2016-08-01

    Imaging is the modality of choice for noninvasive characterization of biological tissue and organ systems; imaging serves as early diagnostic tool for most disease processes and is rapidly evolving, thus transforming the way we diagnose and follow patients over time. A vast number of cancer imaging characteristics have been correlated to underlying genomics; however, none have established causality. Therefore, our objectives were to test if there is a causal relationship between imaging and genomic information; and to develop a clinically relevant radiomic pipeline for glioblastoma molecular characterization. Functional validation was performed using a prototypic in vivo RNA-interference-based orthotopic xenograft mouse model. The automated pipeline collects 4800 MRI-derived texture features per tumor. Using univariate feature selection and boosted tree predictive modeling, a patient-specific genomic probability map was derived and patient survival predicted (The Cancer Genome Atlas/MD Anderson data sets). Data demonstrated a significant xenograft to human association (area under the curve [AUC] 84%, P < .001). Further, epidermal growth factor receptor amplification (AUC 86%, P < .0001), O-methylguanine-DNA-methyltransferase methylation/expression (AUC 92%, P = .001), glioblastoma molecular subgroups (AUC 88%, P = .001), and survival in 2 independent data sets (AUC 90%, P < .001) was predicted. Our results for the first time illustrate a causal relationship between imaging features and genomic tumor composition. We present a directly clinically applicable analytical imaging method termed Radiome Sequencing to allow for automated image analysis, prediction of key genomic events, and survival. This method is scalable and applicable to any type of medical imaging. Further, it allows for human-mouse matched coclinical trials, in-depth end point analysis, and upfront noninvasive high-resolution radiomics-based diagnostic, prognostic, and predictive biomarker development.

  17. A Three-Variable Model Predicts Short Survival in Patients With Newly Diagnosed Metastatic Renal Cell Carcinoma

    PubMed Central

    Syed, Mohsan Ali;