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Sample records for predicting clinical response

  1. Predicting clinical responses in major depression using intrinsic functional connectivity.

    PubMed

    Qin, Jian; Shen, Hui; Zeng, Ling-Li; Jiang, Weixiong; Liu, Li; Hu, Dewen

    2015-08-19

    There has been increasing interest in multivariate pattern analysis (MVPA) as a means of distinguishing psychiatric patients from healthy controls using brain imaging. However, it remains unclear whether MVPA methods can accurately estimate the medication status of psychiatric patients. This study aims to develop an MVPA approach to accurately predict the antidepressant medication status of individuals with major depression on the basis of whole-brain resting-state functional connectivity MRI (rs-fcMRI). We investigated data from rs-fcMRI of 24 medication-naive depressed patients, 16 out of whom subsequently underwent antidepressant treatment and achieved clinical recovery, and 29 demographically similar controls. By training a linear support vector machine classifier and combining it with principal component analysis, the medication-naive patients were identified from the healthy controls with 100% accuracy. In addition, we found reliable correlations between MVPA prediction scores and clinical symptom severity. Moreover, the most discriminative functional connections were located within or across the cerebellum and default mode, affective, and sensorimotor networks, indicating that these networks may play important roles in major depression. Most importantly, only ∼30% of these discriminative connections were normalized in clinically recovered patients after antidepressant treatment. The current study may not only show the feasibility of estimating medication status by MVPA of whole-brain rs-fcMRI data in major depression but also shed new light on the pathological mechanism of this disorder. PMID:26164454

  2. Early treatment response predicted subsequent clinical response in patients with schizophrenia taking paliperidone extended-release.

    PubMed

    Yeh, En-Chi; Huang, Ming-Chyi; Tsai, Chang-Jer; Chen, Chun-Tse; Chen, Kuan-Yu; Chiu, Chih-Chiang

    2015-11-30

    This 6-week open-labeled study investigated whether early treatment response in patients receiving paliperidone extended-release (paliperidone ER) can facilitate prediction of responses at Week 6. Patients with schizophrenia or schizoaffective disorder were administered 9mg/day of paliperidone ER during the first 2 weeks, after which the dose was adjusted clinically. They were assessed on Days 0, 4, 7, 14, 28, and 42 by the Positive and Negative Syndrome Scale (PANSS). The serum concentrations of 9-hydroxyrisperidone were examined on Days 14 and 42. Among the 41 patients enrolled, 26 were classified as responders (≧50% improvement on total PANSS scores at Week 6). In the receiver-operator curves (ROC) analyses, the changes in total PANSS scores at Week 2 appeared to show more accurate predictability compared to Day 4 and Day 7. At Week 6, no significant correlation was observed between blood 9-hydroxyrisperidone concentration and the total score or changes of PANSS scores. The results suggest that early treatment response to paliperidone ER, particularly at Week 2, can serve as a suitable outcome predictor at Week 6. Using 9mg/day paliperidone ER as an initial dose for schizophrenia treatment exhibited relatively favorable tolerability and feasibility. PMID:26319696

  3. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.

    PubMed

    Gao, Hui; Korn, Joshua M; Ferretti, Stéphane; Monahan, John E; Wang, Youzhen; Singh, Mallika; Zhang, Chao; Schnell, Christian; Yang, Guizhi; Zhang, Yun; Balbin, O Alejandro; Barbe, Stéphanie; Cai, Hongbo; Casey, Fergal; Chatterjee, Susmita; Chiang, Derek Y; Chuai, Shannon; Cogan, Shawn M; Collins, Scott D; Dammassa, Ernesta; Ebel, Nicolas; Embry, Millicent; Green, John; Kauffmann, Audrey; Kowal, Colleen; Leary, Rebecca J; Lehar, Joseph; Liang, Ying; Loo, Alice; Lorenzana, Edward; Robert McDonald, E; McLaughlin, Margaret E; Merkin, Jason; Meyer, Ronald; Naylor, Tara L; Patawaran, Montesa; Reddy, Anupama; Röelli, Claudia; Ruddy, David A; Salangsang, Fernando; Santacroce, Francesca; Singh, Angad P; Tang, Yan; Tinetto, Walter; Tobler, Sonja; Velazquez, Roberto; Venkatesan, Kavitha; Von Arx, Fabian; Wang, Hui Qin; Wang, Zongyao; Wiesmann, Marion; Wyss, Daniel; Xu, Fiona; Bitter, Hans; Atadja, Peter; Lees, Emma; Hofmann, Francesco; Li, En; Keen, Nicholas; Cozens, Robert; Jensen, Michael Rugaard; Pryer, Nancy K; Williams, Juliet A; Sellers, William R

    2015-11-01

    Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses. PMID:26479923

  4. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures.

    PubMed

    Yu, Kun-Hsing; Levine, Douglas A; Zhang, Hui; Chan, Daniel W; Zhang, Zhen; Snyder, Michael

    2016-08-01

    Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P < 0.0001). We further built a least absolute shrinkage and selection operator (LASSO)-Cox proportional hazards model that stratified patients into early relapse and late relapse groups (P = 0.00013). The top proteomic features indicative of platinum response were involved in ATP synthesis pathways and Ran GTPase binding. Overall, we demonstrated that proteomic profiles of ovarian serous carcinoma patients predicted platinum drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers. PMID:27312948

  5. Pharmacogenomics of Methotrexate Membrane Transport Pathway: Can Clinical Response to Methotrexate in Rheumatoid Arthritis Be Predicted?

    PubMed Central

    Lima, Aurea; Bernardes, Miguel; Azevedo, Rita; Medeiros, Rui; Seabra, Vitor

    2015-01-01

    Background: Methotrexate (MTX) is widely used for rheumatoid arthritis (RA) treatment. Single nucleotide polymorphisms (SNPs) could be used as predictors of patients’ therapeutic outcome variability. Therefore, this study aims to evaluate the influence of SNPs in genes encoding for MTX membrane transport proteins in order to predict clinical response to MTX. Methods: Clinicopathological data from 233 RA patients treated with MTX were collected, clinical response defined, and patients genotyped for 23 SNPs. Genotype and haplotype analyses were performed using multivariate methods and a genetic risk index (GRI) for non-response was created. Results: Increased risk for non-response was associated to SLC22A11 rs11231809 T carriers; ABCC1 rs246240 G carriers; ABCC1 rs3784864 G carriers; CGG haplotype for ABCC1 rs35592, rs2074087 and rs3784864; and CGG haplotype for ABCC1 rs35592, rs246240 and rs3784864. GRI demonstrated that patients with Index 3 were 16-fold more likely to be non-responders than those with Index 1. Conclusions: This study revealed that SLC22A11 and ABCC1 may be important to identify those patients who will not benefit from MTX treatment, highlighting the relevance in translating these results to clinical practice. However, further validation by independent studies is needed to develop the field of personalized medicine to predict clinical response to MTX treatment. PMID:26086825

  6. Biomarkers for predicting clinical response to immunosuppressive therapy in aplastic anemia.

    PubMed

    Narita, Atsushi; Kojima, Seiji

    2016-08-01

    The decision to select hematopoietic stem cell transplantation (HSCT) or immunosuppressive therapy (IST) as initial therapy in acquired aplastic anemia (AA) is currently based on patient age and the availability of a human leukocyte antigen (HLA)-matched donor. Although IST is a promising treatment option, the ability to predict its long-term outcomes remains poor due to refractoriness, relapses, and the risk of clonal evolution. Several predictive biomarkers for response to IST have been posited, including age, gender, pre-treatment blood cell counts, cytokines, gene mutations, paroxysmal nocturnal hemoglobinuria (PNH), and telomere length (TL). While previous studies have provided substantial biological insights into the utility of IST, the prognostic power of the reported biomarkers is currently insufficient to contribute to clinical decision making. Recently, a large retrospective analysis proposed the combination of minor PNH clones and TL as an efficient predictor of IST response. Identification of a reliable predictor would provide a useful tool for determining the most appropriate treatment choice for AA patients, including up-front HSCT from HLA-matched unrelated donor. The present review summarizes studies evaluating the utility of biomarkers in predicting the clinical response to IST of patients with AA, and provides a baseline for prospective studies aimed at validating previously reported biomarkers. PMID:27091471

  7. Clinical application of fluctuation dissipation theory - Prediction of heart rate response to spontaneous breathing trial

    NASA Astrophysics Data System (ADS)

    Niestemski, Liang R.; Chen, Man; Prevost, Robert; McRae, Michael; Cholleti, Sharath; Najarro, Gabriel; Buchman, Timothy G.; Deem, Michael W.

    2013-03-01

    Contrary to the traditional view of the healthy physiological state as being a single static state, variation in physiologic variables has more recently been suggested to be a key component of the healthy state. Indeed, aging and disease are characterized by a loss of such variability. We apply the conceptual framework of fluctuation-dissipation theory (FDT) to predict the response to a common clinical intervention from historical fluctuations in physiologic time series data. The non-equilibrium FDT relates the response of a system to a perturbation to natural fluctuations in the stationary state of the system. We seek to understand with the FDT a common clinical perturbation, the spontaneous breathing trial (SBT), in which mechanical ventilation is briefly suspended while the patient breathes freely for a period of time. As a stress upon the heart of the patient, the SBT can be characterized as a perturbation of heart rate dynamics. A non-equilibrium, but steady-state FDT allows us to predict the heart rate recovery after the SBT stress. We show that the responses of groups of similar patients to the spontaneous breathing trial can be predicted by this approach. This mathematical framework may serve as part of the basis for personalized critical care.

  8. Clinical Parameters Predicting Pathologic Tumor Response After Preoperative Chemoradiotherapy for Rectal Cancer

    SciTech Connect

    Yoon, Sang Min; Kim, Dae Yong Kim, Tae Hyun; Jung, Kyung Hae; Chang, Hee Jin; Koom, Woong Sub; Lim, Seok-Byung; Choi, Hyo Seong; Jeong, Seung-Yong; Park, Jae-Gahb

    2007-11-15

    Purpose: To identify pretreatment clinical parameters that could predict pathologic tumor response to preoperative chemoradiotherapy (CRT) for rectal cancer. Methods and Materials: The study involved 351 patients who underwent preoperative CRT followed by surgery between October 2001 and July 2006. Tumor responses to preoperative CRT were assessed in terms of tumor downstaging and tumor regression. Statistical analyses were performed to identify clinical factors associated with pathologic tumor response. Results: Tumor downstaging (defined as ypT2 or less) was observed in 167 patients (47.6%), whereas tumor regression (defined as Dworak's Regression Grades 3 or 4) was observed in 103 patients (29.3%) and complete regression in 51 patients (14.5%). Multivariate analysis found that predictors of downstaging were pretreatment hemoglobin level (p = 0.045), cN0 classification (p < 0.001), and serum carcinoembryonic antigen (CEA) level (p < 0.001), that predictors of tumor regression were cN0 classification (p = 0.044) and CEA level (p < 0.001), and that the predictor of complete regression was CEA level (p = 0.004). Conclusions: The data suggest that pretreatment CEA level is the most important clinical predictor of pathologic tumor response. It may be of benefit in the selection of treatment options as well as the assessment of individual prognosis.

  9. Future clinical uses of neurophysiological biomarkers to predict and monitor treatment response for schizophrenia

    PubMed Central

    Light, Gregory A.; Swerdlow, Neal R.

    2015-01-01

    Advances in psychiatric neuroscience have transformed our understanding of impaired and spared brain functions in psychotic illnesses. Despite substantial progress, few if any laboratory tests have graduated to clinics to inform diagnoses, guide treatments, and monitor treatment response. Providers must rely on careful behavioral observation and interview techniques to make inferences about patients’ inner experiences and then secondary deductions about impacted neural systems. Development of more effective treatments has also been hindered by a lack of translational quantitative biomarkers that can span the brain–behavior–treatment knowledge gap. Here, we describe an example of a simple, low-cost, and translatable electroencephalography (EEG) measure that offers promise for improving our understanding and treatment of psychotic illnesses: mismatch negativity (MMN). MMN is sensitive to and/or predicts response to some pharmacologic and non-pharmacologic interventions and accounts for substantial portions of variance in clinical, cognitive, and psychosocial functioning in schizophrenia. This measure has recently been validated for use in large-scale multisite clinical studies of schizophrenia. Lastly, MMN greatly improves our ability to forecast which individuals at high clinical risk actually develop a psychotic illness. These attributes suggest that MMN can contribute to personalized biomarker-guided treatment strategies aimed at ameliorating or even preventing the onset of psychosis. PMID:25752648

  10. Can a Clinical Test of Reaction Time Predict a Functional Head-Protective Response?

    PubMed Central

    ECKNER, JAMES T.; LIPPS, DAVID B.; KIM, HOGENE; RICHARDSON, JAMES K.; ASHTON-MILLER, JAMES A.

    2015-01-01

    Purpose Reaction time is commonly prolonged after a sport-related concussion. Besides being a marker for injury, a rapid reaction time is necessary for protective maneuvers that can reduce the frequency and severity of additional head impacts. The purpose of this study was to determine whether a clinical test of simple visuomotor reaction time predicted the time taken to raise the hands to protect the head from a rapidly approaching ball. Methods Twenty-six healthy adult participants recruited from campus and community recreation and exercise facilities completed two experimental protocols during a single session: a manual visuomotor simple reaction time test (RTclin) and a sport-related head-protective response (RTsprt). RTclin measured the time required to catch a thin vertically oriented device on its release by the tester and was calculated from the distance the device fell before being arrested. RTsprt measured the time required to raise the hands from waist level to block a foam tennis ball fired toward the subject’s face from an air cannon and was determined using an optoelectronic camera system. A correlation coefficient was calculated between RTclin and RTsprt, with linear regression used to assess for effect modification by other covariates. Results A strong positive correlation was found between RTclin and RTsprt (r = 0.725, P < 0.001) independent of age, gender, height, or weight. Conclusions RTclin is predictive of a functional sport-related head-protective response. To our knowledge, this is the first demonstration of a clinical test predicting the ability to protect the head in a simulated sport environment. This correlation with a functional head-protective response is a relevant consideration for the potential use of RTclin as part of a multifaceted concussion assessment program. PMID:20689458

  11. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer.

    PubMed

    Xia, Shu; Kohli, Manish; Du, Meijun; Dittmar, Rachel L; Lee, Adam; Nandy, Debashis; Yuan, Tiezheng; Guo, Yongchen; Wang, Yuan; Tschannen, Michael R; Worthey, Elizabeth; Jacob, Howard; See, William; Kilari, Deepak; Wang, Xuexia; Hovey, Raymond L; Huang, Chiang-Ching; Wang, Liang

    2015-06-30

    Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer. PMID:25915538

  12. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

    PubMed Central

    Du, Meijun; Dittmar, Rachel L.; Lee, Adam; Nandy, Debashis; Yuan, Tiezheng; Guo, Yongchen; Wang, Yuan; Tschannen, Michael R.; Worthey, Elizabeth; Jacob, Howard; See, William; Kilari, Deepak; Wang, Xuexia; Hovey, Raymond L.; Huang, Chiang-Ching; Wang, Liang

    2015-01-01

    Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer. PMID:25915538

  13. Empirically and Clinically Useful Decision Making in Psychotherapy: Differential Predictions with Treatment Response Models

    ERIC Educational Resources Information Center

    Lutz, Wolfgang; Saunders, Stephen M.; Leon, Scott C.; Martinovich, Zoran; Kosfelder, Joachim; Schulte, Dietmar; Grawe, Klaus; Tholen, Sven

    2006-01-01

    In the delivery of clinical services, outcomes monitoring (i.e., repeated assessments of a patient's response to treatment) can be used to support clinical decision making (i.e., recurrent revisions of outcome expectations on the basis of that response). Outcomes monitoring can be particularly useful in the context of established practice research…

  14. Mucosal Immune Responses Predict Clinical Outcomes during Influenza Infection Independently of Age and Viral Load

    PubMed Central

    Oshansky, Christine M.; Gartland, Andrew J.; Wong, Sook-San; Jeevan, Trushar; Wang, David; Roddam, Philippa L.; Caniza, Miguela A.; Hertz, Tomer; DeVincenzo, John P.; Webby, Richard J.

    2014-01-01

    Rationale: Children are an at-risk population for developing complications following influenza infection, but immunologic correlates of disease severity are not understood. We hypothesized that innate cellular immune responses at the site of infection would correlate with disease outcome. Objectives: To test the immunologic basis of severe illness during natural influenza virus infection of children and adults at the site of infection. Methods: An observational cohort study with longitudinal sampling of peripheral and mucosal sites in 84 naturally influenza-infected individuals, including infants. Cellular responses, viral loads, and cytokines were quantified from nasal lavages and blood, and correlated to clinical severity. Measurements and Main Results: We show for the first time that although viral loads in children and adults were similar, innate responses in the airways were stronger in children and varied considerably between plasma and site of infection. Adjusting for age and viral load, an innate immune profile characterized by increased nasal lavage monocyte chemotactic protein-3, IFN-α2, and plasma IL-10 levels at enrollment predicted progression to severe disease. Increased plasma IL-10, monocyte chemotactic protein-3, and IL-6 levels predicted hospitalization. This inflammatory cytokine production correlated significantly with monocyte localization from the blood to the site of infection, with conventional monocytes positively correlating with inflammation. Increased frequencies of CD14lo monocytes were in the airways of participants with lower inflammatory cytokine levels. Conclusions: An innate profile was identified that correlated with disease progression independent of viral dynamics and age. The airways and blood displayed dramatically different immune profiles emphasizing the importance of cellular migration and localized immune phenotypes. PMID:24308446

  15. Population pharmacokinetic–pharmacodynamic modelling in oncology: a tool for predicting clinical response

    PubMed Central

    Bender, Brendan C; Schindler, Emilie; Friberg, Lena E

    2015-01-01

    In oncology trials, overall survival (OS) is considered the most reliable and preferred endpoint to evaluate the benefit of drug treatment. Other relevant variables are also collected from patients for a given drug and its indication, and it is important to characterize the dynamic effects and links between these variables in order to improve the speed and efficiency of clinical oncology drug development. However, the drug-induced effects and causal relationships are often difficult to interpret because of temporal differences. To address this, population pharmacokinetic–pharmacodynamic (PKPD) modelling and parametric time-to-event (TTE) models are becoming more frequently applied. Population PKPD and TTE models allow for exploration towards describing the data, understanding the disease and drug action over time, investigating relevance of biomarkers, quantifying patient variability and in designing successful trials. In addition, development of models characterizing both desired and adverse effects in a modelling framework support exploration of risk-benefit of different dosing schedules. In this review, we have summarized population PKPD modelling analyses describing tumour, tumour marker and biomarker responses, as well as adverse effects, from anticancer drug treatment data. Various model-based metrics used to drive PD response and predict OS for oncology drugs and their indications are also discussed. PMID:24134068

  16. Clinical validity: Combinatorial pharmacogenomics predicts antidepressant responses and healthcare utilizations better than single gene phenotypes.

    PubMed

    Altar, C A; Carhart, J M; Allen, J D; Hall-Flavin, D K; Dechairo, B M; Winner, J G

    2015-10-01

    In four previous studies, a combinatorial multigene pharmacogenomic test (GeneSight) predicted those patients whose antidepressant treatment for major depressive disorder resulted in poorer efficacy and increased health-care resource utilizations. Here, we extended the analysis of clinical validity to the combined data from these studies. We also compared the outcome predictions of the combinatorial use of allelic variations in genes for four cytochrome P450 (CYP) enzymes (CYP2D6, CYP2C19, CYP2C9 and CYP1A2), the serotonin transporter (SLC6A4) and serotonin 2A receptor (HTR2A) with the outcome predictions for the very same subjects using traditional, single-gene analysis. Depression scores were measured at baseline and 8-10 weeks later for the 119 fully blinded subjects who received treatment as usual (TAU) with antidepressant standard of care, without the benefit of pharmacogenomic medication guidance. For another 96 TAU subjects, health-care utilizations were recorded in a 1-year, retrospective chart review. All subjects were genotyped after the clinical study period, and phenotype subgroups were created among those who had been prescribed a GeneSight panel medication that is a substrate for either CYP enzyme or serotonin effector protein. On the basis of medications prescribed for each subject at baseline, the combinatorial pharmacogenomic (CPGx™) GeneSight method categorized each subject into either a green ('use as directed'), yellow ('use with caution') or red category ('use with increased caution and with more frequent monitoring') phenotype, whereas the single-gene method categorized the same subjects with the traditional phenotype (for example, poor, intermediate, extensive or ultrarapid CYP metabolizer). The GeneSight combinatorial categorization approach discriminated and predicted poorer outcomes for red category patients prescribed medications metabolized by CYP2D6, CYP2C19 and CYP1A2 (P=0.0034, P=0.04 and P=0.03, respectively), whereas the single

  17. Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures.

    PubMed

    Ye, Zheng; Rae, Charlotte L; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle-Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R; Maxwell, Helen; Sahakian, Barbara J; Barker, Roger A; Robbins, Trevor W; Rowe, James B

    2016-03-01

    Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double-blind randomized three-way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion-weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave-one-out cross-validation (LOOCV) to predict patients' responses in terms of improved stopping efficiency. We identified two optimal models: (1) a "clinical" model that predicted the response of an individual patient with 77-79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion-weighted imaging scan; and (2) a "mechanistic" model that explained the behavioral response with 85% accuracy for each drug, using drug-induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. PMID:26757216

  18. New Perspectives on Predictive Biomarkers of Tumor Response and Their Clinical Application in Preoperative Chemoradiation Therapy for Rectal Cancer.

    PubMed

    Kim, Nam Kyu; Hur, Hyuk

    2015-11-01

    Preoperative chemoradiation therapy (CRT) is the standard treatment for patients with locally advanced rectal cancer (LARC) and can improve local control and survival outcomes. However, the responses of individual tumors to CRT are not uniform and vary widely, from complete response to disease progression. Patients with resistant tumors can be exposed to irradiation and chemotherapy that are both expensive and at times toxic without benefit. In contrast, about 60% of tumors show tumor regression and T and N down-staging. Furthermore, a pathologic complete response (pCR), which is characterized by sterilization of all tumor cells, leads to an excellent prognosis and is observed in approximately 10-30% of cases. This variety in tumor response has lead to an increased need to develop a model predictive of responses to CRT in order to identify patients who will benefit from this multimodal treatment. Endoscopy, magnetic resonance imaging, positron emission tomography, serum carcinoembryonic antigen, and molecular biomarkers analyzed using immunohistochemistry and gene expression profiling are the most commonly used predictive models in preoperative CRT. Such modalities guide clinicians in choosing the best possible treatment options and the extent of surgery for each individual patient. However, there are still controversies regarding study outcomes, and a nomogram of combined models of future trends is needed to better predict patient response. The aim of this article was to review currently available tools for predicting tumor response after preoperative CRT in rectal cancer and to explore their applicability in clinical practice for tailored treatment. PMID:26446626

  19. New Perspectives on Predictive Biomarkers of Tumor Response and Their Clinical Application in Preoperative Chemoradiation Therapy for Rectal Cancer

    PubMed Central

    Hur, Hyuk

    2015-01-01

    Preoperative chemoradiation therapy (CRT) is the standard treatment for patients with locally advanced rectal cancer (LARC) and can improve local control and survival outcomes. However, the responses of individual tumors to CRT are not uniform and vary widely, from complete response to disease progression. Patients with resistant tumors can be exposed to irradiation and chemotherapy that are both expensive and at times toxic without benefit. In contrast, about 60% of tumors show tumor regression and T and N down-staging. Furthermore, a pathologic complete response (pCR), which is characterized by sterilization of all tumor cells, leads to an excellent prognosis and is observed in approximately 10-30% of cases. This variety in tumor response has lead to an increased need to develop a model predictive of responses to CRT in order to identify patients who will benefit from this multimodal treatment. Endoscopy, magnetic resonance imaging, positron emission tomography, serum carcinoembryonic antigen, and molecular biomarkers analyzed using immunohistochemistry and gene expression profiling are the most commonly used predictive models in preoperative CRT. Such modalities guide clinicians in choosing the best possible treatment options and the extent of surgery for each individual patient. However, there are still controversies regarding study outcomes, and a nomogram of combined models of future trends is needed to better predict patient response. The aim of this article was to review currently available tools for predicting tumor response after preoperative CRT in rectal cancer and to explore their applicability in clinical practice for tailored treatment. PMID:26446626

  20. Neurobiological markers predicting treatment response in anxiety disorders: A systematic review and implications for clinical application.

    PubMed

    Lueken, Ulrike; Zierhut, Kathrin C; Hahn, Tim; Straube, Benjamin; Kircher, Tilo; Reif, Andreas; Richter, Jan; Hamm, Alfons; Wittchen, Hans-Ulrich; Domschke, Katharina

    2016-07-01

    Anxiety disorders constitute the largest group of mental disorders with a high individual and societal burden. Neurobiological markers of treatment response bear potential to improve response rates by informing stratified medicine approaches. A systematic review was performed on the current evidence of the predictive value of genetic, neuroimaging and other physiological markers for treatment response (pharmacological and/or psychotherapeutic treatment) in anxiety disorders. Studies published until March 2015 were selected through search in PubMed, Web of Science, PsycINFO, Embase, and CENTRAL. Sixty studies were included, among them 27 on genetic, 17 on neuroimaging and 16 on other markers. Preliminary evidence was found for the functional 5-HTTLPR/rs25531 genotypes, anterior cingulate cortex function and cardiovascular flexibility to modulate treatment outcome. Studies varied considerably in methodological quality. Application of more stringent study methodology, predictions on the individual patient level and cross-validation in independent samples are recommended to set the next stage of biomarker research and to avoid flawed conclusions in the emerging field of "Mental Health Predictomics". PMID:27168345

  1. The use of computational models to predict response to HIV therapy for clinical cases in Romania

    PubMed Central

    Revell, Andrew D; Ene, Luminiţa; Duiculescu, Dan; Wang, Dechao; Youle, Mike; Pozniak, Anton; Montaner, Julio; Larder, Brendan A

    2012-01-01

    Introduction A major challenge in Romania is the optimisation of antiretroviral therapy for the many HIV-infected adults with, on average, a decade of treatment experience. The RDI has developed computational models that predict virological response to therapy but these require a genotype, which is not routinely available in Romania. Moreover the models, which were trained without any Romanian data, have proved most accurate for patients from the healthcare settings that contributed the training data. Here we develop and test a novel model that does not require a genotype, with test data from Romania. Methods A random forest (RF) model was developed to predict the probability of the HIV viral load (VL) being reduced to <50 copies/ml following therapy change. The input variables were baseline VL, CD4 count, treatment history and time to follow-up. The model was developed with 3188 treatment changes episodes (TCEs) from North America, Western Europe and Australia. The model’s predictions for 100 independent TCEs from the RDI database were compared to those of a model trained with the same data plus genotypes and then tested using 39 TCEs from Romania in terms of the area under the ROC curve (AUC). Results When tested with the 100 independent RDI TCEs, the AUC values for the models with and without genotypes were 0.88 and 0.86 respectively. For the 39 Romanian TCEs the AUC was 0.60. However, when 14 cases with viral loads that may have been between 50 and 400 copies were removed, the AUC increased to 0.83. Discussion Despite having been trained without data from Romania, the model predicted treatment responses in treatment-experienced Romanian patients with clade F virus accurately without the need for a genotype. The results suggest that this approach might be generalisable and useful in helping design optimal salvage regimens for treatment-experienced patients in countries with limited resources where genotyping is not always available. PMID:24432257

  2. Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson's disease with clinical and neuroimaging measures

    PubMed Central

    Ye, Zheng; Rae, Charlotte L.; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Rodríguez, Patricia Vázquez; Coyle‐Gilchrist, Ian; Regenthal, Ralf; Altena, Ellemarije; Housden, Charlotte R.; Maxwell, Helen; Sahakian, Barbara J.; Barker, Roger A.; Robbins, Trevor W.

    2016-01-01

    Abstract Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral performance and brain activity. We reassessed the behavioral efficacy of these drugs in a larger cohort and developed predictive models to identify patient responders. We used a double‐blind randomized three‐way crossover design to investigate stopping efficiency in 34 patients with idiopathic Parkinson's disease after 40 mg atomoxetine, 30 mg citalopram, or placebo. Diffusion‐weighted and functional imaging measured microstructural properties and regional brain activations, respectively. We confirmed that Parkinson's disease impairs response inhibition. Overall, drug effects on response inhibition varied substantially across patients at both behavioral and brain activity levels. We therefore built binary classifiers with leave‐one‐out cross‐validation (LOOCV) to predict patients’ responses in terms of improved stopping efficiency. We identified two optimal models: (1) a “clinical” model that predicted the response of an individual patient with 77–79% accuracy for atomoxetine and citalopram, using clinically available information including age, cognitive status, and levodopa equivalent dose, and a simple diffusion‐weighted imaging scan; and (2) a “mechanistic” model that explained the behavioral response with 85% accuracy for each drug, using drug‐induced changes of brain activations in the striatum and presupplementary motor area from functional imaging. These data support growing evidence for the role of noradrenaline and serotonin in inhibitory control. Although noradrenergic and serotonergic drugs have highly variable effects in patients with Parkinson's disease, the individual patient's response to each drug can be predicted using a pattern of clinical and neuroimaging features. Hum Brain Mapp 37:1026–1037

  3. Near-Infrared Spectroscopy in Schizophrenia: A Possible Biomarker for Predicting Clinical Outcome and Treatment Response

    PubMed Central

    Koike, Shinsuke; Nishimura, Yukika; Takizawa, Ryu; Yahata, Noriaki; Kasai, Kiyoto

    2013-01-01

    Functional near-infrared spectroscopy (fNIRS) is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions) compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography), fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and non-invasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an fNIRS community

  4. Can a physician predict the clinical response to first-line immunomodulatory treatment in relapsing–remitting multiple sclerosis?

    PubMed Central

    Mezei, Zsolt; Bereczki, Daniel; Racz, Lilla; Csiba, Laszlo; Csepany, Tünde

    2012-01-01

    Background Decreased relapse rate and slower disease progression have been reported with long-term use of immunomodulatory treatments (IMTs, interferon beta or glatiramer acetate) in relapsing–remitting multiple sclerosis. There are, however, patients who do not respond to such treatments, and they can be potential candidates for alternative therapeutic approaches. Objective To identify clinical factors as possible predictors of poor long-term response. Methods A 9-year prospective, continuous follow-up at a single center in Hungary to assess clinical efficacy of IMT. Results In a patient group of 81 subjects with mean IMT duration of 54 ± 33 months, treatment efficacy expressed as annual relapse rate and change in clinical severity from baseline did not depend on the specific IMT (any of the interferon betas or glatiramer acetate), and on mono- or multifocal features of the initial appearance of the disease. Responders had shorter disease duration and milder clinical signs at the initiation of treatment. Relapse-rate reduction in the initial 2 years of treatment predicted clinical efficacy in subsequent years. Conclusion Based on these observations, we suggest that a 2-year trial period is sufficient to decide on the efficacy of a specific IMT. For those with insufficient relapse reduction in the first 2 years of treatment, a different IMT or other therapeutic approaches should be recommended. PMID:23118540

  5. A Personalized BEST: Characterization of Latent Clinical Classes of Nonischemic Heart Failure That Predict Outcomes and Response to Bucindolol

    PubMed Central

    Kao, David P.; Wagner, Brandie D.; Robertson, Alastair D.; Bristow, Michael R.; Lowes, Brian D.

    2012-01-01

    Background Heart failure patients with reduced ejection fraction (HFREF) are heterogenous, and our ability to identify patients likely to respond to therapy is limited. We present a method of identifying disease subtypes using high-dimensional clinical phenotyping and latent class analysis that may be useful in personalizing prognosis and treatment in HFREF. Methods A total of 1121 patients with nonischemic HFREF from the β-blocker Evaluation of Survival Trial were categorized according to 27 clinical features. Latent class analysis was used to generate two latent class models, LCM A and B, to identify HFREF subtypes. LCM A consisted of features associated with HF pathogenesis, whereas LCM B consisted of markers of HF progression and severity. The Seattle Heart Failure Model (SHFM) Score was also calculated for all patients. Mortality, improvement in left ventricular ejection fraction (LVEF) defined as an increase in LVEF ≥5% and a final LVEF of 35% after 12 months, and effect of bucindolol on both outcomes were compared across HFREF subtypes. Performance of models that included a combination of LCM subtypes and SHFM scores towards predicting mortality and LVEF response was estimated and subsequently validated using leave-one-out cross-validation and data from the Multicenter Oral Carvedilol Heart Failure Assessment Trial. Results A total of 6 subtypes were identified using LCM A and 5 subtypes using LCM B. Several subtypes resembled familiar clinical phenotypes. Prognosis, improvement in LVEF, and the effect of bucindolol treatment differed significantly between subtypes. Prediction improved with addition of both latent class models to SHFM for both 1-year mortality and LVEF response outcomes. Conclusions The combination of high-dimensional phenotyping and latent class analysis identifies subtypes of HFREF with implications for prognosis and response to specific therapies that may provide insight into mechanisms of disease. These subtypes may facilitate

  6. Prediction of clinical and endoscopic responses to anti-tumor necrosis factor-α antibodies in ulcerative colitis.

    PubMed

    Morita, Yukihiro; Bamba, Shigeki; Takahashi, Kenichiro; Imaeda, Hirotsugu; Nishida, Atsushi; Inatomi, Osamu; Sasaki, Masaya; Tsujikawa, Tomoyuki; Sugimoto, Mitsushige; Andoh, Akira

    2016-08-01

    Objective In patients with ulcerative colitis (UC), the relationship between the initial endoscopic findings and the response to anti-tumor necrosis factor (TNF)-α antibodies remains unclear. We herein evaluated the potential of endoscopic assessment using the ulcerative colitis endoscopic index of severity (UCEIS) to predict the response to anti-TNF-α antibodies. Methods We enrolled 64 patients with UC undergoing anti-TNF-α maintenance therapy with infliximab (IFX) or adalimumab (ADA) between April 2010 and March 2015. Anti-TNF-α trough levels were determined by ELISA. Endoscopic disease activity was assessed using the UCEIS. Results The clinical response rate at 8 weeks was 77.4% for IFX and 66.7% for ADA. Serum albumin levels were significantly higher and the UCEIS bleeding descriptor before treatment was significantly lower in the responders than in the non-responders (p < 0.05 each). The CRP levels at 2 weeks were significantly lower in the responders (p < 0.001). The serum albumin levels before treatment were significantly higher and the UCEIS erosions and ulcers descriptor was significantly lower in the mucosal healing group than in the non-mucosal healing group (p < 0.05 each). A significant and negative correlation between the trough levels of anti-TNF-α antibodies and the UCEIS descriptors was observed. The trough levels of anti-TNF-α antibodies to achieve mucosal healing were 2.7 μg/mL for IFX and 10.3 μg/mL for ADA. Conclusions The UCEIS score, as well as some clinical markers (serum albumin and CRP levels), is useful for the prediction of the treatment outcome of UC patients in response to anti-TNF-α antibodies. PMID:26888161

  7. Cultural Responsivity in Clinical Psychology Graduate Students: A Developmental Approach to the Prediction of Learning

    ERIC Educational Resources Information Center

    Berrin, Sebastian Everett

    2010-01-01

    This study used a mixed-method approach to examine students' experiences in multicultural training and their opinions about various aspects of their course(s). A developmental model of learning was employed to analyze results. More specifically, this study explored the relationship between clinical psychology doctoral students' self-reported…

  8. A Personalized Approach to Biological Therapy Using Prediction of Clinical Response Based on MRP8/14 Serum Complex Levels in Rheumatoid Arthritis Patients

    PubMed Central

    Nair, S. C.; Welsing, P. M. J.; Choi, I. Y. K.; Roth, J.; Holzinger, D.; Bijlsma, J. W. J.; van Laar, J. M.; Gerlag, D. M.; Lafeber, F. P. J. G.; Tak, P. P.

    2016-01-01

    Objectives Measurement of MRP8/14 serum levels has shown potential in predicting clinical response to different biological agents in rheumatoid arthritis (RA). We aimed to develop a treatment algorithm based on a prediction score using MRP8/14 measurements and clinical parameters predictive for response to different biological agents. Methods Baseline serum levels of MRP8/14 were measured in 170 patients starting treatment with infliximab, adalimumab or rituximab. We used logistic regression analysis to develop a predictive score for clinical response at 16 weeks. MRP8/14 levels along with clinical variables at baseline were investigated. We also investigated how the predictive effect of MRP8/14 was modified by drug type. A treatment algorithm was developed based on categorizing the expected response per drug type as high, intermediate or low for each patient and optimal treatment was defined. Finally, we present the utility of using this treatment algorithm in clinical practice. Results The probability of response increased with higher baseline MRP8/14 complex levels (OR = 1.39), differentially between the TNF-blockers and rituximab (OR of interaction term = 0.78), and also increased with higher DAS28 at baseline (OR = 1.28). Rheumatoid factor positivity, functional disability (a higher HAQ), and previous use of a TNF-inhibitor decreased the probability of response. Based on the treatment algorithm 80 patients would have been recommended for anti-TNF treatment, 8 for rituximab, 13 for another biological treatment (other than TNFi or rituximab) and for 69 no recommendation was made. The predicted response rates matched the observed response in the cohort well. On group level the predicted response based on the algorithm resulted in a modest 10% higher response rate in our cohort with much higher differences in response probability in individual patients treated contrary to treatment recommendation. Conclusions Prediction of response using MRP8/14 levels along with

  9. Systolic pressure response to voluntary apnea predicts sympathetic tone in obstructive sleep apnea as a clinically useful index.

    PubMed

    Jouett, Noah P; Hardisty, Janelle M; Mason, J Ryan; Niv, Dorene; Romano, James J; Watenpaugh, Donald E; Burk, John R; Smith, Michael L

    2016-01-01

    The present investigation tested the hypotheses that systolic arterial pressure (SAP) responses to voluntary apnea (a) serve as a surrogate of sympathetic nerve activity (SNA), (b) can distinguish Obstructive Sleep Apnea (OSA) patients from control subjects and (c) can document autonomic effects of treatment. 9 OSA and 10 control subjects were recruited in a laboratory study; 44 OSA subjects and 78 control subjects were recruited in a clinical study; and 21 untreated OSA subjects and 14 well-treated OSA subjects were recruited into a treatment study. Each subject performed hypoxic and room air voluntary apneas in triplicate. Muscle SNA (MSNA) and continuous AP were measured during each apnea in the laboratory study, while systolic arterial pressure (SAP) responses were measured continuously and by standard auscultation in the clinical and treatment studies. OSA subjects exhibited increased mean arterial pressure (MAP), SAP and MSNA responses to hypoxic apnea (all P<0.01) and the SAP response highly correlated with the MSNA response (R(2)=0.72, P<0.001). Clinical assessment confirmed that OSA subjects exhibited markedly elevated SAP responses (P<0.01), while treated OSA subjects had a decreased SAP response to apnea (P<0.04) compared to poorly treated subjects. These data indicate that (a) OSA subjects exhibit increased pressor and MSNA responses to apnea, and that (b) voluntary apnea may be a clinically useful assessment tool of autonomic dysregulation and treatment efficacy in OSA. PMID:26774324

  10. Activation of c-Jun predicts a poor response to sorafenib in hepatocellular carcinoma: Preliminary Clinical Evidence

    PubMed Central

    Chen, Wei; Xiao, Weikai; Zhang, Kunsong; Yin, Xiaoyu; Lai, Jiaming; Liang, Lijian; Chen, Dong

    2016-01-01

    We determined the mitogen-activated protein kinase (MAPK) gene expression profile of acquired resistance in sorafenib-sensitive hepatocellular carcinoma (HCC) cells and aimed to identify c-Jun as an important molecule mediating the efficacy of sorafenib. Differences in gene expression of the MAPK signaling between untreated and sorafenib-treated HCC cell lines were investigated using real-time polymerase chain reaction array. Western blot and real-time PCR further evaluated the expression of c-Jun. Pathological specimens from 50 patients with advanced HCC were collected to measure p-c-Jun expression. Sorafenib-resistant HCC cells demonstrated greater levels of basal c-Jun mRNA and protein compared with sorafenib-sensitive HCC cells. Sorafenib activated p-c-Jun in a dose- and time-dependent manner in PLC/PRF/5 and MHCC97H cell lines. Decreased expression levels of 6 genes after sorafenib treatment suggested a robust inhibitory impact of sorafenib on MAPK signaling in HCC cells. c-Jun and p-c-Jun expression levels were inversely correlated with the efficacy of sorafenib; a high expression level of p-c-Jun was associated with resistance to sorafenib and poor overall survival in patients with clinical HCC. p-c-Jun may act as a biomarker for predicting responses of sorafenib treatment, thus advocating targeting of JNK/c-Jun signaling as an optimal therapeutic strategy in a subset of HCC. PMID:26964667

  11. Early Clinical Response after 2 Weeks of Sorafenib Therapy Predicts Outcomes and Anti-Tumor Response in Patients with Advanced Hepatocellular Carcinoma

    PubMed Central

    Kuzuya, Teiji; Ishigami, Masatoshi; Ishizu, Yoji; Honda, Takashi; Hayashi, Kazuhiko; Katano, Yoshiaki; Hirooka, Yoshiki; Ishikawa, Tetsuya; Nakano, Isao; Goto, Hidemi

    2015-01-01

    Background & Aims We evaluated the relationship between the early clinical response after 2 weeks of sorafenib therapy and the outcomes and anti-tumor response in patients with advanced hepatocellular carcinoma. Methods Fifty-seven patients who had intrahepatic hypervascular hepatocellular carcinoma and Child-Pugh (CP) class A disease at baseline were enrolled in this prospective, multicenter, observational, non-interventional study. As an early clinical response after 2 weeks of sorafenib therapy, changes in intra-tumor blood flow on contrast-enhanced computed tomography (CE-CT), alpha-fetoprotein (AFP) levels, and remnant liver function were investigated. Results After 2 weeks of sorafenib therapy, there were 26 patients (45.6%) without disappearance of arterial tumor enhancement on CE-CT, 15 patients (26.3%) with an AFP ratio of >1.2, and seven patients (12.3%) with two or more increments in the CP score. Multivariate analysis showed that the absence of disappearance of arterial tumor enhancement on CE-CT, AFP ratio of >1.2, and two or more increments in the CP score after 2 weeks of sorafenib therapy were significant and independent predictors of worse survival. Upon scoring these three variables as "poor prognostic factors", patients with poor prognostic score 4, 3 or 2 (n = 17) had significantly worse outcomes and a significantly higher progressive disease (PD) rate based on modified Response Evaluation Criteria in Solid Tumors at 6 weeks after sorafenib therapy than those with poor prognostic score 1 or 0 (n = 40) (median overall survival: 194 days vs. 378 days; p = 0.0010, PD rate: 70.6% vs. 20.0%; p = 0.0003, respectively). Conclusions Changes in intra-tumor blood flow on CE-CT, AFP levels, and remnant liver function after 2 weeks of sorafenib therapy may be useful for predicting the outcomes and anti-tumor response to sorafenib in patients with advanced hepatocellular carcinoma. PMID:26421430

  12. Clinical course, costs and predictive factors for response to treatment in carpal tunnel syndrome: the PALMS study protocol

    PubMed Central

    2014-01-01

    Background Carpal tunnel syndrome (CTS) is the most common neuropathy of the upper limb and a significant contributor to hand functional impairment and disability. Effective treatment options include conservative and surgical interventions, however it is not possible at present to predict the outcome of treatment. The primary aim of this study is to identify which baseline clinical factors predict a good outcome from conservative treatment (by injection) or surgery in patients diagnosed with carpal tunnel syndrome. Secondary aims are to describe the clinical course and progression of CTS, and to describe and predict the UK cost of CTS to the individual, National Health Service (NHS) and society over a two year period. Methods/Design In this prospective observational cohort study patients presenting with clinical signs and symptoms typical of CTS and in whom the diagnosis is confirmed by nerve conduction studies are invited to participate. Data on putative predictive factors are collected at baseline and follow-up through patient questionnaires and include standardised measures of symptom severity, hand function, psychological and physical health, comorbidity and quality of life. Resource use and cost over the 2 year period such as prescribed medications, NHS and private healthcare contacts are also collected through patient self-report at 6, 12, 18 and 24 months. The primary outcome used to classify treatment success or failures will be a 5-point global assessment of change. Secondary outcomes include changes in clinical symptoms, functioning, psychological health, quality of life and resource use. A multivariable model of factors which predict outcome and cost will be developed. Discussion This prospective cohort study will provide important data on the clinical course and UK costs of CTS over a two-year period and begin to identify predictive factors for treatment success from conservative and surgical interventions. PMID:24507749

  13. Prediction of Response to Treatment in a Randomized Clinical Trial of Couple Therapy: A 2-Year Follow-Up

    ERIC Educational Resources Information Center

    Baucom, Brian R.; Atkins, David C.; Simpson, Lorelei E.; Christensen, Andrew

    2009-01-01

    Many studies have examined pretreatment predictors of immediate posttreatment outcome, but few studies have examined prediction of long-term treatment response to couple therapies. Four groups of predictors (demographic, intrapersonal, communication, and other interpersonal) and 2 moderators (pretreatment severity and type of therapy) were…

  14. Tumor-associated gastroparesis with esophageal carcinoma. Use of intravenous metoclopramide during radionuclide gastric emptying studies to predict clinical response

    SciTech Connect

    Choe, A.I.; Ziessman, H.A.; Fleischer, D.E.

    1989-07-01

    This case report describes a patient with esophageal carcinoma and tumor-associated gastroparesis. The radionuclide gastric emptying study diagnosed very delayed liquid and solid gastric emptying. Metoclopramide was administered intravenously during the study and was able to predict a good response to oral therapy.

  15. Expression of Heat Shock Protein 27 in Melanoma Metastases Is Associated with Overall Response to Bevacizumab Monotherapy: Analyses of Predictive Markers in a Clinical Phase II Study

    PubMed Central

    Schuster, Cornelia; Akslen, Lars A.; Straume, Oddbjørn

    2016-01-01

    The aim of this study was to identify potential predictive biomarkers in 35 patients with metastatic melanoma treated with anti-angiogenic bevacizumab monotherapy in a clinical phase II study. The immunohistochemical expression of various angiogenic factors in tissues from primary melanomas and metastases as well as their concentration in blood samples were examined. Strong expression of Heat Shock Protein 27 (HSP27) in metastases correlated significantly with complete or partial response to bevacizumab (p = 0.044). Furthermore, clinical benefit, i.e., complete or partial response or stable disease for at least 6 months, was more frequent in patients with strong expression of HSP27 in primary tumors (p = 0.046). Tissue expression of vascular endothelial growth factor (VEGF-A), its splicing variant VEGF165b or basic fibroblast growth factor (bFGF) did not correlate with response, and the concentration of HSP27, VEGF-A or bFGF measured in blood samples before treatment did not show predictive value. Further, microvessel density, proliferating microvessel density and presence of glomeruloid microvascular proliferations were assessed in sections of primary tumors and metastases. Microvessel density in primary melanomas was significantly higher in patients with clinical benefit than in non-responders (p = 0.042). In conclusion, our findings suggest that strong HSP27 expression in melanoma metastases predicts response to bevacizumab treatment. Trial Registration ClinicalTrials.gov NCT00139360 PMID:27166673

  16. Prediction of therapeutic response in steroid-treated pulmonary sarcoidosis. Evaluation of clinical parameters, bronchoalveolar lavage, gallium-67 lung scanning, and serum angiotensin-converting enzyme levels

    SciTech Connect

    Hollinger, W.M.; Staton, G.W. Jr.; Fajman, W.A.; Gilman, M.J.; Pine, J.R.; Check, I.J.

    1985-07-01

    To find a pretreatment predictor of steroid responsiveness in pulmonary sarcoidosis the authors studied 21 patients before and after steroid treatment by clinical evaluation, pulmonary function tests, bronchoalveolar lavage (BAL), gallium-67 lung scan, and serum angiotensin-converting enzyme (SACE) level. Although clinical score, forced vital capacity (FVC), BAL percent lymphocytes (% lymphs), quantitated gallium-67 lung uptake, and SACE levels all improved with therapy, only the pretreatment BAL % lymphs correlated with the improvement in FVC (r = 0.47, p less than 0.05). Pretreatment BAL % lymphs of greater than or equal to 35% predicted improvement in FVC of 10/11 patients, whereas among 10 patients with BAL % lymphs less than 35%, 5 patients improved and 5 deteriorated. Clinical score, pulmonary function parameters, quantitated gallium-67 lung uptake, and SACE level used alone, in combination with BAL % lymphs or in combination with each other, did not improve this predictive value. The authors conclude that steroid therapy improves a number of clinical and laboratory parameters in sarcoidosis, but only the pretreatment BAL % lymphs are useful in predicting therapeutic responsiveness.

  17. Early epigenetic changes and DNA damage do not predict clinical response in an overlapping schedule of 5-azacytidine and entinostat in patients with myeloid malignancies

    PubMed Central

    Fandy, Tamer E.; Herman, James G.; Kerns, Patrick; Jiemjit, Anchalee; Sugar, Elizabeth A.; Choi, Si-Ho; Yang, Allen S.; Aucott, Timothy; Dauses, Tianna; Odchimar-Reissig, Rosalie; Licht, Jonathan; McConnell, Melanie J.; Nasrallah, Chris; Kim, Marianne K. H.; Zhang, Weijia; Sun, Yezou; Murgo, Anthony; Espinoza-Delgado, Igor; Oteiza, Katharine; Owoeye, Ibitayo; Silverman, Lewis R.; Carraway, Hetty E.

    2009-01-01

    Sequential administration of DNA methyltransferase (DNMT) inhibitors and histone deacetylase (HDAC) inhibitors has demonstrated clinical efficacy in patients with hematologic malignancies. However, the mechanism behind their clinical efficacy remains controversial. In this study, the methylation dynamics of 4 TSGs (p15INK4B, CDH-1, DAPK-1, and SOCS-1) were studied in sequential bone marrow samples from 30 patients with myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML) who completed a minimum of 4 cycles of therapy with 5-azacytidine and entinostat. Reversal of promoter methylation after therapy was observed in both clinical responders and nonresponders across all genes. There was no association between clinical response and either baseline methylation or methylation reversal in the bone marrow or purified CD34+ population, nor was there an association with change in gene expression. Transient global hypomethylation was observed in samples after treatment but was not associated with clinical response. Induction of histone H3/H4 acetylation and the DNA damage–associated variant histone γ-H2AX was observed in peripheral blood samples across all dose cohorts. In conclusion, methylation reversal of candidate TSGs during cycle 1 of therapy was not predictive of clinical response to combination “epigenetic” therapy. This trial is registered with http://www.clinicaltrials.gov under NCT00101179. PMID:19546476

  18. Integrating in vitro sensitivity and dose-response slope is predictive of clinical response to ABL kinase inhibitors in chronic myeloid leukemia.

    PubMed

    Vainstein, Vladimir; Eide, Christopher A; O'Hare, Thomas; Shukron, Ofir; Druker, Brian J

    2013-11-01

    BCR-ABL mutations result in clinical resistance to ABL tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML). Although in vitro 50% inhibitory concentration (IC(50)) values for specific mutations have been suggested to guide TKI choice in the clinic, the quantitative relationship between IC(50) and clinical response has never been demonstrated. We used Hill's equation for in vitro response of Ba/F3 cells transduced with various BCR-ABL mutants to determine IC(50) and the slope of the dose-response curve. We found that slope variability between mutants tracked with in vitro TKI resistance, provides particular additional interpretive value in cases where in vitro IC(50) and clinical response are disparate. Moreover, unlike IC(50) alone, higher inhibitory potential at peak concentration (IPP), which integrates IC(50), slope, and peak concentration (Cmax), correlated with improved complete cytogenetic response (CCyR) rates in CML patients treated with dasatinib. Our findings suggest a metric integrating in vitro and clinical data may provide an improved tool for BCR-ABL mutation-guided TKI selection. PMID:24062017

  19. Epidemiological and Clinical Baseline Characteristics as Predictive Biomarkers of Response to Anti-VEGF Treatment in Patients with Neovascular AMD

    PubMed Central

    López-Gálvez, Maria I.; Margaron, Philippe; Lambrou, George N.

    2016-01-01

    Purpose. To review the current literature investigating patient response to antivascular endothelial growth factor-A (VEGF) therapy in the treatment of neovascular age-related macular degeneration (nAMD) and to identify baseline characteristics that might predict response. Method. A literature search of the PubMed database was performed, using the keywords: AMD, anti-VEGF, biomarker, optical coherence tomography, treatment outcome, and predictor. The search was limited to articles published from 2006 to date. Exclusion criteria included phase 1 trials, case reports, studies focusing on indications other than nAMD, and oncology. Results. A total of 1467 articles were identified, of which 845 were excluded. Of the 622 remaining references, 47 met all the search criteria and were included in this review. Conclusion. Several baseline characteristics correlated with anti-VEGF treatment response, including best-corrected visual acuity, age, lesion size, and retinal thickness. The majority of factors were associated with disease duration, suggesting that longer disease duration before treatment results in worse treatment outcomes. This highlights the need for early treatment for patients with nAMD to gain optimal treatment outcomes. Many of the identified baseline characteristics are interconnected and cannot be evaluated in isolation; therefore multivariate analyses will be required to determine any specific relationship with treatment response. PMID:27073691

  20. Epidemiological and Clinical Baseline Characteristics as Predictive Biomarkers of Response to Anti-VEGF Treatment in Patients with Neovascular AMD.

    PubMed

    Tsilimbaris, Miltiadis K; López-Gálvez, Maria I; Gallego-Pinazo, Roberto; Margaron, Philippe; Lambrou, George N

    2016-01-01

    Purpose. To review the current literature investigating patient response to antivascular endothelial growth factor-A (VEGF) therapy in the treatment of neovascular age-related macular degeneration (nAMD) and to identify baseline characteristics that might predict response. Method. A literature search of the PubMed database was performed, using the keywords: AMD, anti-VEGF, biomarker, optical coherence tomography, treatment outcome, and predictor. The search was limited to articles published from 2006 to date. Exclusion criteria included phase 1 trials, case reports, studies focusing on indications other than nAMD, and oncology. Results. A total of 1467 articles were identified, of which 845 were excluded. Of the 622 remaining references, 47 met all the search criteria and were included in this review. Conclusion. Several baseline characteristics correlated with anti-VEGF treatment response, including best-corrected visual acuity, age, lesion size, and retinal thickness. The majority of factors were associated with disease duration, suggesting that longer disease duration before treatment results in worse treatment outcomes. This highlights the need for early treatment for patients with nAMD to gain optimal treatment outcomes. Many of the identified baseline characteristics are interconnected and cannot be evaluated in isolation; therefore multivariate analyses will be required to determine any specific relationship with treatment response. PMID:27073691

  1. Presence of Systemic Inflammatory Response Syndrome Predicts a Poor Clinical Outcome in Dogs with a Primary Hepatitis.

    PubMed

    Kilpatrick, Scott; Dreistadt, Margaret; Frowde, Polly; Powell, Roger; Milne, Elspeth; Smith, Sionagh; Morrison, Linda; Gow, Adam G; Handel, Ian; Mellanby, Richard J

    2016-01-01

    Primary hepatopathies are a common cause of morbidity and mortality in dogs. The underlying aetiology of most cases of canine hepatitis is unknown. Consequently, treatments are typically palliative and it is difficult to provide accurate prognostic information to owners. In human hepatology there is accumulating data which indicates that the presence of systemic inflammatory response syndrome (SIRS) is a common and debilitating event in patients with liver diseases. For example, the presence of SIRS has been linked to the development of complications such as hepatic encephalopathy (HE) and is associated with a poor clinical outcome in humans with liver diseases. In contrast, the relationship between SIRS and clinical outcome in dogs with a primary hepatitis is unknown. Seventy dogs with histologically confirmed primary hepatitis were enrolled into the study. Additional clinical and clinicopathological information including respiratory rate, heart rate, temperature, white blood cell count, sodium, potassium, sex, presence of ascites, HE score, alanine aminotransferase (ALT), alkaline phosphatase (ALP), bilirubin and red blood cell concentration were available in all cases. The median survival of dogs with a SIRS score of 0 or 1 (SIRS low) was 231 days compared to a median survival of 7 days for dogs with a SIRS score of 2, 3 or 4 (SIRS high) (p<0.001). A Cox proportional hazard model, which included all other co-variables, revealed that a SIRS high score was an independent predictor of a poor clinical outcome. The effect of modulating inflammation on treatment outcomes in dogs with a primary hepatitis is deserving of further study. PMID:26808672

  2. Predictors of primary breast cancers responsiveness to preoperative Epirubicin/Cyclophosphamide-based chemotherapy: translation of microarray data into clinically useful predictive signatures

    PubMed Central

    Modlich, Olga; Prisack, Hans-Bernd; Munnes, Marc; Audretsch, Werner; Bojar, Hans

    2005-01-01

    PLS-DA models were implemented to discriminate all three response classes in one step. Conclusion In this study signatures were identified capable to predict clinical outcome in an independent set of primary breast cancer patients undergoing PST-EC. PMID:16091131

  3. Clinical Utility of a New Automated Hepatitis C Virus Core Antigen Assay for Prediction of Treatment Response in Patients with Chronic Hepatitis C.

    PubMed

    Kim, Mi Na; Kim, Hyon Suk; Kim, Ja Kyung; Kim, Beom Kyung; Kim, Seung Up; Park, Jun Yong; Kim, Do Young; Ahn, Sang Hoon; Han, Kwang Hyub

    2016-09-01

    Hepatitis C virus core antigen (HCV Ag) is a recently developed marker of hepatitis C virus (HCV) infection. We investigated the clinical utility of the new HCV Ag assay for prediction of treatment response in HCV infection. We analyzed serum from 92 patients with HCV infection who had been treated with pegylated interferon and ribavirin. HCV Ag levels were determined at baseline in all enrolled patients and at week 4 in 15 patients. Baseline HCV Ag levels showed good correlations with HCV RNA (r = 0.79, P < 0.001). Mean HCV Ag levels at baseline were significantly lower in patients with a sustained virologic response (SVR) than in those with a non SVR (relapse plus non responder) based on HCV RNA analysis (2.8 log₁₀fmol/L vs. 3.27 log₁₀fmol/L, P = 0.023). Monitoring of the viral kinetics by determination of HCV RNA and HCV Ag levels resulted in similarly shaped curves. Patients with undetectable HCV Ag levels at week 4 had a 92.3% probability of achieving SVR based on HCV RNA assay results. The HCV Ag assay may be used as a supplement for predicting treatment response in HCV infection, but not as an alternative to the HCV RNA assay. PMID:27510387

  4. Clinical Utility of a New Automated Hepatitis C Virus Core Antigen Assay for Prediction of Treatment Response in Patients with Chronic Hepatitis C

    PubMed Central

    2016-01-01

    Hepatitis C virus core antigen (HCV Ag) is a recently developed marker of hepatitis C virus (HCV) infection. We investigated the clinical utility of the new HCV Ag assay for prediction of treatment response in HCV infection. We analyzed serum from 92 patients with HCV infection who had been treated with pegylated interferon and ribavirin. HCV Ag levels were determined at baseline in all enrolled patients and at week 4 in 15 patients. Baseline HCV Ag levels showed good correlations with HCV RNA (r = 0.79, P < 0.001). Mean HCV Ag levels at baseline were significantly lower in patients with a sustained virologic response (SVR) than in those with a non SVR (relapse plus non responder) based on HCV RNA analysis (2.8 log10fmol/L vs. 3.27 log10fmol/L, P = 0.023). Monitoring of the viral kinetics by determination of HCV RNA and HCV Ag levels resulted in similarly shaped curves. Patients with undetectable HCV Ag levels at week 4 had a 92.3% probability of achieving SVR based on HCV RNA assay results. The HCV Ag assay may be used as a supplement for predicting treatment response in HCV infection, but not as an alternative to the HCV RNA assay. PMID:27510387

  5. Clinical Predictive Modeling Development and Deployment through FHIR Web Services

    PubMed Central

    Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

    2015-01-01

    Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction. PMID:26958207

  6. Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

    PubMed

    Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

    2015-01-01

    Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction. PMID:26958207

  7. Early changes in biochemical markers of bone turnover predict the long-term response to alendronate therapy in representative elderly women: a randomized clinical trial.

    PubMed

    Greenspan, S L; Parker, R A; Ferguson, L; Rosen, H N; Maitland-Ramsey, L; Karpf, D B

    1998-09-01

    Although the antiresorptive agent alendronate has been shown to increase bone mineral density (BMD) at the hip and spine and decrease the incidence of osteoporotic fractures in older women, few data are available regarding early prediction of long-term response to therapy, particularly with regard to increases in hip BMD. Examining short-term changes in biochemical markers incorporates physiologic response with therapeutic compliance and should provide useful prognostic information for patients. The objective of this study was to examine whether early changes in biochemical markers of bone turnover predict long-term changes in hip BMD in elderly women. The study was a double-blind, placebo-controlled, randomized clinical trial which took place in a community-based academic hospital. One hundred and twenty community-dwelling, ambulatory women 65 years of age and older participated in the study. Intervention consisted of alendronate versus placebo for 2.5 years. All patients received appropriate calcium and vitamin D supplementation. The principal outcome measures included BMD of the hip (total hip, femoral neck, trochanter, and intertrochanter), spine (posteroanterior [PA] and lateral), total body, and radius. Biochemical markers of bone resorption included urinary N-telopeptide cross-linked collagen type I and free deoxypyridinoline; markers of bone formation included serum osteocalcin and bone-specific alkaline phosphatase. Long-term alendronate therapy was associated with increased BMD at the total hip (4.0%), femoral neck (3.1%), trochanter (5.5%), intertrochanter (3.8%), PA spine (7.8%), lateral spine (10.6%), total body (2.2%), and one-third distal radius (1.3%) in elderly women (all p < 0.01). In the placebo group, bone density increased 1.9-2.1% at the spine (p < 0.05) and remained stable at all other sites. At 6 months, there were significant decreases in all markers of bone turnover (-10% to -53%, p < 0.01) in women on alendronate. The changes in urinary

  8. Clinical ethics revisited: responses

    PubMed Central

    Benatar, Solomon R; Bhutta, Zulfiqar A; Daar, Abdallah S; Hope, Tony; MacRae, Sue; Roberts, Laura W; Sharpe, Virginia A

    2001-01-01

    This series of responses was commissioned to accompany the article by Singer et al, which can be found at . If you would like to comment on the article by Singer et al or any of the responses, please email us on editorial@biomedcentral.com. PMID:11346457

  9. How to Establish Clinical Prediction Models

    PubMed Central

    Bang, Heejung

    2016-01-01

    A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice. PMID:26996421

  10. How to Establish Clinical Prediction Models.

    PubMed

    Lee, Yong Ho; Bang, Heejung; Kim, Dae Jung

    2016-03-01

    A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice. PMID:26996421

  11. Predicting and measuring fluid responsiveness with echocardiography

    PubMed Central

    Mandeville, Justin

    2016-01-01

    Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart–lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid resuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately. PMID:27249550

  12. Predicting and measuring fluid responsiveness with echocardiography.

    PubMed

    Miller, Ashley; Mandeville, Justin

    2016-06-01

    Echocardiography is ideally suited to guide fluid resuscitation in critically ill patients. It can be used to assess fluid responsiveness by looking at the left ventricle, aortic outflow, inferior vena cava and right ventricle. Static measurements and dynamic variables based on heart-lung interactions all combine to predict and measure fluid responsiveness and assess response to intravenous fluid resuscitation. Thorough knowledge of these variables, the physiology behind them and the pitfalls in their use allows the echocardiographer to confidently assess these patients and in combination with clinical judgement manage them appropriately. PMID:27249550

  13. Can site response be predicted?

    USGS Publications Warehouse

    Boore, D.M.

    2004-01-01

    Large modifications of seismic waves are produced by variations of material properties near the Earth's surface and by both surface and buried topography. These modifications, usually referred to as "site response", in general lead to larger motions on soil sites than on rock-like sites. Because the soil amplifications can be as large as a factor of ten, they are important in engineering applications that require the quantitative specification of ground motions. This has been recognised for years by both seismologists and engineers, and it is hard to open an earthquake journal these days without finding an article on site response. What is often missing in these studies, however, are discussions of the uncertainty of the predicted response. A number of purely observational studies demonstrate that ground motions have large site-to-site variability for a single earthquake and large earthquake-location- dependent variability for a single site. This variability makes site-specific, earthquake-specific predictions of site response quite uncertain, even if detailed geotechnical and geological information is available near the site. Predictions of site response for average classes of sites exposed to the motions from many earthquakes can be made with much greater certainty if sufficient empirical observations are available.

  14. Outcome Prediction in Clinical Treatment Processes.

    PubMed

    Huang, Zhengxing; Dong, Wei; Ji, Lei; Duan, Huilong

    2016-01-01

    Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or patient physical factors, to estimate clinical outcomes at early stages of CTPs (e.g., admission). They lack the ability to deal with temporal evolution of CTPs. In addition, most of the existing studies employ data mining or machine learning methods to generate a prediction model for a specific type of clinical outcome, however, a mathematical model that predicts multiple clinical outcomes simultaneously, has not yet been established. In this study, a hybrid approach is proposed to provide a continuous predictive monitoring service on multiple clinical outcomes. More specifically, a probabilistic topic model is applied to discover underlying treatment patterns of CTPs from electronic medical records. Then, the learned treatment patterns, as low-dimensional features of CTPs, are exploited for clinical outcome prediction across various stages of CTPs based on multi-label classification. The proposal is evaluated to predict three typical classes of clinical outcomes, i.e., length of stay, readmission time, and the type of discharge, using 3492 pieces of patients' medical records of the unstable angina CTP, extracted from a Chinese hospital. The stable model was characterized by 84.9% accuracy and 6.4% hamming-loss with 3 latent treatment patterns discovered from data, which outperforms the benchmark multi-label classification algorithms for clinical outcome prediction. Our study indicates the proposed approach can potentially improve the quality of clinical outcome prediction, and assist physicians to understand the patient conditions, treatment inventions, and clinical outcomes in an integrated view. PMID:26573645

  15. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    PubMed

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. PMID:27089522

  16. Predicting Clinical Outcomes Using Molecular Biomarkers

    PubMed Central

    Burke, Harry B.

    2016-01-01

    Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician’s screen during the physician–patient interaction, they will be an integral part of physician–patient-shared decision-making, and they will improve clinical care and patient outcomes. PMID:27279751

  17. The value of lateral spread response monitoring in predicting the clinical outcome after microvascular decompression in hemifacial spasm: a prospective study on 100 patients.

    PubMed

    El Damaty, Ahmed; Rosenstengel, Christian; Matthes, Marc; Baldauf, Joerg; Schroeder, Henry W S

    2016-07-01

    Microvascular decompression represents an effective treatment for hemifacial spasm. The use of lateral spread response (LSR) monitoring remains a useful intraoperative tool to ensure adequate decompression of the facial nerve. The aim of this study was to assess the value of LSRs intraoperative monitoring as a prognostic indicator for the outcome of microvascular decompression in hemifacial spasm. Our study included 100 patients prospectively. The patients were classified into four groups whether LSRs were totally, partially, not relieved, or not detected from the start. According to clinical outcome, the patients were classified into four groups depending on the clinical course after surgery and the residual symptoms if any. Then, correlations were made between LSR events and treatment outcome to detect its reliability as a prognostic indicator. LSRs were relieved totally in 56 % of the patients, partially relieved in 14 %, not relieved in 10 %, and were not detected in 20 % of the patients from the start. HFS was relieved directly after operation in 62 % with clinical improvement of 90-100 %. Thirty-one percent described 50-90 % improvement over the next 3 months after surgery. Almost all of these 31 % (28 out of 31 patients) reported further clinical improvement of 90-100 % within 1 year after surgery. Three percent suffered from a relapse after a HFS-free period, and 4 % reported minimal or no improvement describing 0-50 % of the preoperative state. The percentage of the satisfied patients with the clinical outcome who reported after 1 year a clinical improvement of 90-100 % was 90 %. Statistical analysis did not find a significant correlation between the relief of LSRs and clinical outcome. LSRs may only represent an intraoperative tool to guide for an adequate decompression but failed to represent a reliable prognostic indicator for treatment outcome. PMID:27053220

  18. Prediction of earthquake response spectra

    USGS Publications Warehouse

    Joyner, W.B.; Boore, David M.

    1982-01-01

    We have developed empirical equations for predicting earthquake response spectra in terms of magnitude, distance, and site conditions, using a two-stage regression method similar to the one we used previously for peak horizontal acceleration and velocity. We analyzed horizontal pseudo-velocity response at 5 percent damping for 64 records of 12 shallow earthquakes in Western North America, including the recent Coyote Lake and Imperial Valley, California, earthquakes. We developed predictive equations for 12 different periods between 0.1 and 4.0 s, both for the larger of two horizontal components and for the random horizontal component. The resulting spectra show amplification at soil sites compared to rock sites for periods greater than or equal to 0.3 s, with maximum amplification exceeding a factor of 2 at 2.0 s. For periods less than 0.3 s there is slight deamplification at the soil sites. These results are generally consistent with those of several earlier studies. A particularly significant aspect of the predicted spectra is the change of shape with magnitude (confirming earlier results by McGuire and by Irifunac and Anderson). This result indicates that the conventional practice of scaling a constant spectral shape by peak acceleration will not give accurate answers. The Newmark and Hall method of spectral scaling, using both peak acceleration and peak velocity, largely avoids this error. Comparison of our spectra with the Nuclear Regulatory Commission's Regulatory Guide 1.60 spectrum anchored at the same value at 0.1 s shows that the Regulatory Guide 1.60 spectrum is exceeded at soil sites for a magnitude of 7.5 at all distances for periods greater than about 0.5 s. Comparison of our spectra for soil sites with the corresponding ATC-3 curve of lateral design force coefficient for the highest seismic zone indicates that the ATC-3 curve is exceeded within about 7 km of a magnitude 6.5 earthquake and within about 15 km of a magnitude 7.5 event. The amount by

  19. Identifying and managing clinical responsibility.

    PubMed

    Armitage, Mary; Shaw, Kirstyn; Drew, Peter

    2008-04-01

    Clinical responsibility is an area that requires extensive consideration and development to align with other changes in healthcare in the NHS. Increasing levels of litigation and investigation into the practice of medical practitioners have highlighted the need for clearer guidance for doctors. Using hypothetical case studies, this project explored the understandings and experiences of physicians and potential solutions in areas where there was ambiguity in clinical responsibility. In addition, existing policy and practice within trusts throughout the UK was analysed. The output from the focus group discussion and policy analysis led to the recommendations and guidance for doctors outlined in this paper, with the aim of illustrating the central themes that both doctors and trusts need to address in the future. PMID:18478855

  20. Improved tumour response prediction with equivalent uniform dose in pre-clinical study using direct intratumoural infusion of liposome-encapsulated 186Re radionuclides

    NASA Astrophysics Data System (ADS)

    Hrycushko, Brian A.; Ware, Steve; Li, Shihong; Bao, Ande

    2011-09-01

    Crucial to all cancer therapy modalities is a strong correlation between treatment and effect. Predictability of therapy success/failure allows for the optimization of treatment protocol and aids in the decision of whether additional treatment is necessary to prevent tumour progression. This work evaluated the relationship between cancer treatment and effect for intratumoural infusions of liposome-encapsulated 186Re to head and neck squamous cell carcinoma xenografts of nude rats. Absorbed dose calculations using a dose-point kernel convolution technique showed significant intratumoural dose heterogeneity due to the short range of the beta-particle emissions. The use of three separate tumour infusion locations improved dose homogeneity compared to a single infusion location as a result of a more uniform radioactivity distribution. An improved dose-response correlation was obtained when using effective uniform dose (EUD) calculations based on a generic set of radiobiological parameters (R2 = 0.84) than when using average tumour absorbed dose (R2 = 0.22). Varying radiobiological parameter values over ranges commonly used for all types of tumours showed little effect on EUD calculations, which suggests that individualized parameter use is of little significance as long as the intratumoural dose heterogeneity is taken into consideration in the dose-response relationship. The improved predictability achieved when using EUD calculations for this cancer therapy modality may be useful for treatment planning and evaluation.

  1. What predicts performance during clinical psychology training?

    PubMed Central

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2014-01-01

    Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Results Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Conclusions Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. Practitioner points While referee and selection interview ratings did not predict performance during training, they may be useful in screening out unsuitable candidates at the application stage High school final academic performance

  2. Early sorafenib-related adverse events predict therapy response of TACE plus sorafenib: A multicenter clinical study of 606 HCC patients.

    PubMed

    Zhao, Yan; Li, Hailiang; Bai, Wei; Liu, Jueshi; Lv, Weifu; Sahu, Sonia; Guan, Sheng; Qin, Xiao; Wang, Wenhui; Ren, Weixin; Mu, Wei; Guo, Weidong; Gu, Shanzhi; Ma, Yilong; Yin, Zhanxin; Guo, Wengang; Wang, Wenjun; Wang, Yongji; Duran, Rafael; Fan, Daiming; Zhang, Zhuoli; Han, Guohong

    2016-08-15

    The purpose of our study was to test the hypothesis that sorafenib-related dermatologic adverse events (AEs) as an early biomarker can predict the long-term outcomes following the combination therapy of transarterial chemoembolization (TACE) plus sorafenib (TACE-S). The intermediate-stage hepatocellular carcinoma patients who received either TACE-S or TACE-alone treatment were consecutively included into analysis. In the TACE-S group, patients with ≥ grade 2 dermatologic AEs within the first month of sorafenib initiation were defined as responders; whereas those with < grade 2 were defined as nonresponders. In the TACE-S group, the median overall survival (OS) of the responders was significantly longer than that of nonresponders (28.9 months vs. 16.8 months, respectively; p = 0.004). Multivariate analysis demonstrated that nonresponders were significantly associated with an increased risk of death compared with responders (HR = 1.9; 95% confidence Interval-CI: 1.3-2.7; p = 0.001). The survival analysis showed that the median OS was 27.9 months (95% CI: 25.0-30.8) among responders treated with TACE-S vs.18.3 months (95% CI: 14.5-22.1) among those who received TACE-alone (p = 0.046). The median time to progression was 13.1 months (95% CI: 4.4-21.8) in the TACE-S group, a duration that was significantly longer than that in the TACE-alone group [5 months (95% CI: 6.4-13.3), p = 0.014]. This study demonstrated that sorafenib-related dermatologic AEs are clinical biomarkers to identify responders from all of the patients for TACE-S therapy. Sorafenib-related dermatologic AEs, clinical biomarkers, can predict the efficacy of TACE-S in future randomized controlled trials. PMID:27038145

  3. (18)F-FDG PET/CT in the early prediction of pathological response in aggressive subtypes of breast cancer: review of the literature and recommendations for use in clinical trials.

    PubMed

    Groheux, David; Mankoff, David; Espié, Marc; Hindié, Elif

    2016-05-01

    Early assessment of response to neoadjuvant chemotherapy (NAC) might be helpful in avoiding the toxicity of ineffective chemotherapy and allowing refinement of treatment. We conducted a review of the literature regarding the applicability of (18)F-FDG PET/CT to the prediction of an early pathological response in different subgroups of breast cancer. Clinical research in this field has intensified in the last few years. Early studies by various groups have shown the potential of (18)F-FDG PET/CT in the early assessment of response to NAC. However, interim PET/CT in breast cancer has not yet gained wide acceptance compared to its use in other settings such as lymphomas. This is in part due to a lack of consensus that early evaluation of response can be used to direct change in therapy in the neoadjuvant breast cancer setting, and only limited data showing that response-adaptive therapy leads to improved outcomes. However, one major element that has hampered the use of (18)F-FDG PET/CT in directing neoadjuvant therapy is its evaluation in populations with mixed subtypes of breast cancer. However, major improvements have occurred in recent years. Pilot studies have highlighted the need for considering breast cancer subtype and the type of treatment, and have offered criteria for the use of PET/CT for the early prediction of response in specific settings. (18)F-FDG PET/CT has considerable potential for the early prediction of pathological complete response to NAC in aggressive subtypes such as triple-negative or HER2-positive breast cancers. The results of a multicentre trial that used early metabolic response on (18)F-FDG PET/CT as a means to select poor responders to adapt neoadjuvant treatment have recently been published. Other trials are ongoing or being planned. PMID:26758726

  4. Systemic IFNγ predicts local implant macrophage response.

    PubMed

    Hoene, Andreas; Patrzyk, Maciej; Walschus, Uwe; Finke, Birgit; Lucke, Silke; Nebe, Barbara; Schröder, Karsten; Schlosser, Michael

    2015-03-01

    Implantation of biomaterials can cause complications often associated with inflammatory reactions. However, repeated evaluation of the implant site would be burdening for patients. Alternatively, blood examinations with analysis of inflammatory serum markers could potentially be useful to reflect the local cellular response for detection and/or prediction of inflammation-related complications. Therefore, following intramuscular implantation of surface-modified Ti implants in rats, this study aimed at examining possible associations between the post-implantation time course of pro-inflammatory (INFγ, IL-2) and anti-inflammatory (IL-4, IL-10) cytokine serum concentrations and the local peri-implant tissue response after 56 days (pro-inflammatory CD68-positive monocytes/macrophages, anti-inflammatory CD163-positive macrophages, MHC class II-positive cells, activated natural killer cells and mast cells). Multivariate correlation analysis revealed a significant interaction between serum IFNγ and peri-implant tissue CD68-positive monocytes/macrophages (p = 0.001) while no interactions were found for other cytokines and cell types. Additional Pearson correlation analysis of IFNγ serum concentrations on each experimental day vs. the CD68-positive monocytes/macrophages response on day 56 demonstrated a consistently positive correlation that was strongest during the first three weeks. Thus, high early pro-inflammatory IFNγ serum concentration was associated with high late number of pro-inflammatory CD68-positive monocyte/macrophages and low early serum IFNγ with low late CD68-positive monocyte/macrophage numbers. Further studies aimed at examination of patient samples could establish the relevance of this association to predict clinical complications. After implantation of titanium samples, high early IFNγ serum concentrations were associated with a pronounced late pro-inflammatory CD68-positive monocyte/ macrophage (red circle) response, while no correlation was found

  5. Clinical trial designs incorporating predictive biomarkers.

    PubMed

    Renfro, Lindsay A; Mallick, Himel; An, Ming-Wen; Sargent, Daniel J; Mandrekar, Sumithra J

    2016-02-01

    Development of oncologic therapies has traditionally been performed in a sequence of clinical trials intended to assess safety (phase I), preliminary efficacy (phase II), and improvement over the standard of care (phase III) in homogeneous (in terms of tumor type and disease stage) patient populations. As cancer has become increasingly understood on the molecular level, newer "targeted" drugs that inhibit specific cancer cell growth and survival mechanisms have increased the need for new clinical trial designs, wherein pertinent questions on the relationship between patient biomarkers and response to treatment can be answered. Herein, we review the clinical trial design literature from initial to more recently proposed designs for targeted agents or those treatments hypothesized to have enhanced effectiveness within patient subgroups (e.g., those with a certain biomarker value or who harbor a certain genetic tumor mutation). We also describe a number of real clinical trials where biomarker-based designs have been utilized, including a discussion of their respective advantages and challenges. As cancers become further categorized and/or reclassified according to individual patient and tumor features, we anticipate a continued need for novel trial designs to keep pace with the changing frontier of clinical cancer research. PMID:26827695

  6. Predicting responses from Rasch measures.

    PubMed

    Linacre, John M

    2010-01-01

    There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines. PMID:20351444

  7. Caregiver Responsiveness to the Family Bereavement Program: What predicts responsiveness? What does responsiveness predict?

    PubMed Central

    Schoenfelder, Erin N.; Sandler, Irwin N.; Millsap, Roger E.; Wolchik, Sharlene A.; Berkel, Cady; Ayers, Timothy S.

    2013-01-01

    The study developed a multi-dimensional measure to assess participant responsiveness to a preventive intervention, and applied this measure to study how participant baseline characteristics predict responsiveness and how responsiveness predicts program outcomes. The study was conducted with caregivers who participated in the parenting-focused component of the Family Bereavement Program (FBP), a prevention program for families that have experienced parental death. The sample consisted of 89 caregivers assigned to the intervention condition in the efficacy trial of the FBP. Positive parenting, caregiver depression, and child externalizing problems at baseline were found to predict caregivers’ use of program skills outside the group, and more child internalizing problems predicted more positive perceptions of the group environment. Higher levels of skill use during the program predicted increased positive parenting at the 11-month follow-up, whereas positive perceptions of the group environment predicted decreased caregiver depressive symptoms at follow-up. Caregiver skill use mediated the relation between baseline positive parenting and improvements in positive parenting at 11-month follow-up, and skill use and perceived group environment mediated changes in caregiver depression from baseline to 11-month follow-up. PMID:23404661

  8. Usefulness of plasma renin activity in predicting haemodynamic and clinical responses and survival during long term converting enzyme inhibition in severe chronic heart failure. Experience in 100 consecutive patients.

    PubMed Central

    Packer, M; Medina, N; Yushak, M; Lee, W H

    1985-01-01

    The relation between plasma renin activity before treatment and the haemodynamic and clinical responses to converting enzyme inhibition was determined in 100 consecutive patients with severe chronic heart failure who were treated with captopril or enalapril. Initial doses of captopril produced significant increases in cardiac index and decreases in left ventricular filling pressure, mean arterial pressure, mean right atrial pressure, heart rate, and systemic vascular resistance that varied linearly with the pretreatment value for plasma renin activity. In contrast, there was no relation between the pretreatment activity and the magnitude of haemodynamic improvement after 1-3 months of treatment with the converting enzyme inhibitors, and, consequently, a similar proportion of patients with a high (greater than 6 ng/ml/h; greater than 4.62 mmol/l/h), intermediate (2-6 ng/ml/h; 1.54-4.62 mmol/l/h), and low (less than 2 ng/ml/h; less than 1.54 mmol/l/h) pretreatment value improved clinically during long term treatment (64%, 60%, and 64% respectively). Long term survival after one, two, and three years was similar in the three groups. Estimating the degree of activation of the renin-angiotensin system by measuring pretreatment plasma renin activity fails to predict the long term haemodynamic or clinical responses to converting enzyme inhibitors in patients with severe chronic heart failure, and thus appears to be of limited value in selecting those patients likely to benefit from treatment with these drugs. PMID:2994697

  9. Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas.

    PubMed

    Siegal, Tali

    2016-01-01

    Sorting and grading of glial tumors by the WHO classification provide clinicians with guidance as to the predicted course of the disease and choice of treatment. Nonetheless, histologically identical tumors may have very different outcome and response to treatment. Molecular markers that carry both diagnostic and prognostic information add useful tools to traditional classification by redefining tumor subtypes within each WHO category. Therefore, molecular markers have become an integral part of tumor assessment in modern neuro-oncology and biomarker status now guides clinical decisions in some subtypes of gliomas. The routine assessment of IDH status improves histological diagnostic accuracy by differentiating diffuse glioma from reactive gliosis. It carries a favorable prognostic implication for all glial tumors and it is predictive for chemotherapeutic response in anaplastic oligodendrogliomas with codeletion of 1p/19q chromosomes. Glial tumors that contain chromosomal codeletion of 1p/19q are defined as tumors of oligodendroglial lineage and have favorable prognosis. MGMT promoter methylation is a favorable prognostic marker in astrocytic high-grade gliomas and it is predictive for chemotherapeutic response in anaplastic gliomas with wild-type IDH1/2 and in glioblastoma of the elderly. The clinical implication of other molecular markers of gliomas like mutations of EGFR and ATRX genes and BRAF fusion or point mutation is highlighted. The potential of molecular biomarker-based classification to guide future therapeutic approach is discussed and accentuated. PMID:26508407

  10. Brain connectomics predict response to treatment in social anxiety disorder.

    PubMed

    Whitfield-Gabrieli, S; Ghosh, S S; Nieto-Castanon, A; Saygin, Z; Doehrmann, O; Chai, X J; Reynolds, G O; Hofmann, S G; Pollack, M H; Gabrieli, J D E

    2016-05-01

    We asked whether brain connectomics can predict response to treatment for a neuropsychiatric disorder better than conventional clinical measures. Pre-treatment resting-state brain functional connectivity and diffusion-weighted structural connectivity were measured in 38 patients with social anxiety disorder (SAD) to predict subsequent treatment response to cognitive behavioral therapy (CBT). We used a priori bilateral anatomical amygdala seed-driven resting connectivity and probabilistic tractography of the right inferior longitudinal fasciculus together with a data-driven multivoxel pattern analysis of whole-brain resting-state connectivity before treatment to predict improvement in social anxiety after CBT. Each connectomic measure improved the prediction of individuals' treatment outcomes significantly better than a clinical measure of initial severity, and combining the multimodal connectomics yielded a fivefold improvement in predicting treatment response. Generalization of the findings was supported by leave-one-out cross-validation. After dividing patients into better or worse responders, logistic regression of connectomic predictors and initial severity combined with leave-one-out cross-validation yielded a categorical prediction of clinical improvement with 81% accuracy, 84% sensitivity and 78% specificity. Connectomics of the human brain, measured by widely available imaging methods, may provide brain-based biomarkers (neuromarkers) supporting precision medicine that better guide patients with neuropsychiatric diseases to optimal available treatments, and thus translate basic neuroimaging into medical practice. PMID:26260493

  11. Predicting fish population response to instream flows

    SciTech Connect

    Studley, T.K.; Baldridge, J.E.; Railsback, S.F.

    1996-10-01

    A cooperative research program initiated by Pacific Gas and Electric is described. The goals of the project are to determine if trout populations respond to changes in base streamflows in a predictible manner, and to evaluate and improve the methods used to predict rainbow and brown trout population responses under altered flow regimes. Predictive methods based on computer models of the Physical Habitat Simulation System are described, and predictions generated for four diversions and creeks are tabulated. Baseline data indicates that instream flow assessments can be improved by using guild criteria in streams with competing species and including additional limiting factors (low recruitment, high winter flow, and high stream temperatures) in the analyses.

  12. Biomarkers in systemic sclerosis: Their potential to predict clinical courses.

    PubMed

    Hasegawa, Minoru

    2016-01-01

    The concept of a biomarker was defined as "a characteristic marker that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention" by the National Institutes of Health Biomarkers Definitions Working group in 2001. Clinical features, disease progress, therapeutic response and prognosis are heterogeneous among patients with systemic sclerosis (SSc). Therefore, biomarkers that can predict these matters are required for the progress of clinical practice. At present, SSc-specific autoantibodies are the most useful biomarkers for diagnosis and predicting clinical features. Otherwise, biomarkers specific only for SSc have not been identified yet. The glycoprotein krebs von den Lungen-6, surfactant protein-D and CCL18 are promising serum biomarkers of SSc-related interstitial lung diseases. Serum/plasma levels of brain natriuretic peptide and serum N-terminal pro-brain natriuretic peptide have been used as biomarkers for SSc-related pulmonary arterial hypertension. Other potential serum/plasma biomarkers for fibrosis and vascular involvement of SSc are connective tissue growth factor, interleukin-6, CCL2, CXCL4, intercellular adhesion molecule (ICAM)-1, P-selectin, vascular endothelial growth factor, von Willebrand factor, endostatin, endoglin and endothelin-1. In our multicenter prospective studies of Japanese early SSc, serum ICAM-1 levels were predictive for subsequent respiratory dysfunction and serum levels of CXCL8 and P-selectin were predictive for subsequent physical disability. Further large, multicenter, prospective, longitudinal studies will be needed to identify and validate critical biomarkers of SSc. PMID:26782004

  13. [Prognostic predictive factors of the clinical response to immunotherapy with subcutaneous interleukin-2, in patients with metastatic renal carcinoma: analysis of 60 cases].

    PubMed

    Lissoni, P; Scardino, E; Favini, P; Barni, S; Tancini, G; Baccalin, A; Verweij, F; Strada, G; Musci, R; Rocco, F

    1995-04-01

    The intravenous immunotherapy with high-dose interleukin-2 (IL-2) would constitute one of the most effective treatments of metastatic renal cell carcinoma (RCC). More recently, IL-2 subcutaneous therapy has also appeared active, either alone or in association with interferon, with results comparable to those found with the intravenous route of injection, but with a lower toxicity. On this basis, we have designed a protocol of treatment with low-dose IL-2 alone given subcutaneously as a first or a second line therapy in metastatic RCC. The study included 60 consecutive patients (pts) (M/F: 39/21, median age 56 years, range 26/74). IL-2 was given at a dose of 3 millions IU twice/day for 5 days/week, for 6 weeks, corresponding to one cycle. In non progressed pts a second cycle was repeated after a 28-day rest period. Dominant metastasis sites were, as follows: soft tissues: 8; bone: 11; lung: 29; liver: 3; liver plus lung: 7; adrenal: 2. The minimum follow-up was 18 months and the median follow-up was 34 months (range 18-48). A complete response (CR) was achieved in 2/60 (3%) pts. A partial response (PR) was obtained in 15/60 (25%). Therefore, tumor objective rate (CR + PR) was 17/60 (28%). The median duration of response was 13 months (4-33).(ABSTRACT TRUNCATED AT 250 WORDS) PMID:7787857

  14. Ethical responsibilities of the clinical engineer.

    PubMed

    Saha, P; Saha, S

    1986-01-01

    Because of the growth of medical technology, Clinical Engineers have increased responsibilities in respect to this new technology and so to modern medicine itself. This results in a need to ensure that an ethical consciousness of responsibilities to patients, physicians, and institutions grows within Clinical Engineers as they move into evermore important roles within the health care system. Clinical Engineers must have clearly defined roles, as well as authority acknowledged and supported by other health care professionals. Most importantly, Clinical Engineers themselves must recognize the seriousness of their professional responsibilities as they contribute to the maintenance of equipment, use and design instrumentation, and fulfill roles in administration, management, and research. As members of the health care team, Clinical Engineers must be prepared to face ethical issues arising from defective or inadequate equipment, hazards and incidents, scarcity and resources, conflict of interest, confidentiality, clinical research, "truth-telling," and care of the terminally ill. PMID:10275911

  15. Host Genetics Predict Clinical Deterioration in HCV-Related Cirrhosis

    PubMed Central

    King, Lindsay Y.; Johnson, Kara B.; Zheng, Hui; Wei, Lan; Gudewicz, Thomas; Hoshida, Yujin; Corey, Kathleen E.; Ajayi, Tokunbo; Ufere, Nneka; Baumert, Thomas F.; Chan, Andrew T.; Tanabe, Kenneth K.; Fuchs, Bryan C.; Chung, Raymond T.

    2014-01-01

    Single nucleotide polymorphisms (SNPs) in the epidermal growth factor (EGF, rs4444903), patatin-like phospholipase domain-containing protein 3 (PNPLA3, rs738409) genes, and near the interleukin-28B (IL28B, rs12979860) gene are linked to treatment response, fibrosis, and hepatocellular carcinoma (HCC) in chronic hepatitis C. Whether these SNPs independently or in combination predict clinical deterioration in hepatitis C virus (HCV)-related cirrhosis is unknown. We genotyped SNPs in EGF, PNPLA3, and IL28B from liver tissue from 169 patients with biopsy-proven HCV cirrhosis. We estimated risk of clinical deterioration, defined as development of ascites, encephalopathy, variceal hemorrhage, HCC, or liver-related death using Cox proportional hazards modeling. During a median follow-up of 6.6 years, 66 of 169 patients experienced clinical deterioration. EGF non-AA, PNPLA3 non-CC, and IL28B non-CC genotypes were each associated with increased risk of clinical deterioration in age, sex, and race-adjusted analysis. Only EGF non-AA genotype was independently associated with increased risk of clinical deterioration (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.31–6.25) after additionally adjusting for bilirubin, albumin, and platelets. Compared to subjects who had 0–1 unfavorable genotypes, the HR for clinical deterioration was 1.79 (95%CI 0.96–3.35) for 2 unfavorable genotypes and 4.03 (95%CI 2.13–7.62) for unfavorable genotypes for all three loci (Ptrend<0.0001). In conclusion, among HCV cirrhotics, EGF non-AA genotype is independently associated with increased risk for clinical deterioration. Specific PNPLA3 and IL28B genotypes also appear to be associated with clinical deterioration. These SNPs have potential to identify patients with HCV-related cirrhosis who require more intensive monitoring for decompensation or future therapies preventing disease progression. PMID:25504078

  16. A New Clinical Conceptualization: Prediction Therapy.

    ERIC Educational Resources Information Center

    DiMattia, Dominic J.; Huber, Charles H.

    1983-01-01

    Describes prediction therapy, a cognitive behavioral approach which suggests that individuals seek situations that are optimally predictable. Outlines a five-step protocol of prediction which includes establishing a climate for change, analysis and assessment, identification of therapeutic goals, reorientation and reeducation, and provision of…

  17. miR-155 Drives Metabolic Reprogramming of ER+ Breast Cancer Cells Following Long-Term Estrogen Deprivation and Predicts Clinical Response to Aromatase Inhibitors.

    PubMed

    Bacci, Marina; Giannoni, Elisa; Fearns, Antony; Ribas, Ricardo; Gao, Qiong; Taddei, Maria Letizia; Pintus, Gianfranco; Dowsett, Mitch; Isacke, Clare M; Martin, Lesley-Ann; Chiarugi, Paola; Morandi, Andrea

    2016-03-15

    Aromatase inhibitors (AI) have become the first-line endocrine treatment of choice for postmenopausal estrogen receptor-positive (ER(+)) breast cancer patients, but resistance remains a major challenge. Metabolic reprogramming is a hallmark of cancer and may contribute to drug resistance. Here, we investigated the link between altered breast cancer metabolism and AI resistance using AI-resistant and sensitive breast cancer cells, patient tumor samples, and AI-sensitive human xenografts. We found that long-term estrogen deprivation (LTED), a model of AI resistance, was associated with increased glycolysis dependency. Targeting the glycolysis-priming enzyme hexokinase-2 (HK2) in combination with the AI, letrozole, synergistically reduced cell viability in AI-sensitive models. Conversely, MCF7-LTED cells, which displayed a high degree of metabolic plasticity, switched to oxidative phosphorylation when glycolysis was impaired. This effect was ER dependent as breast cancer cells with undetectable levels of ER failed to exhibit metabolic plasticity. MCF7-LTED cells were also more motile than their parental counterparts and assumed amoeboid-like invasive abilities upon glycolysis inhibition with 2-deoxyglucose (2-DG). Mechanistic investigations further revealed an important role for miR-155 in metabolic reprogramming. Suppression of miR-155 resulted in sensitization of MCF7-LTED cells to metformin treatment and impairment of 2-DG-induced motility. Notably, high baseline miR-155 expression correlated with poor response to AI therapy in a cohort of ER(+) breast cancers treated with neoadjuvant anastrozole. These findings suggest that miR-155 represents a biomarker potentially capable of identifying the subset of breast cancers most likely to adapt to and relapse on AI therapy. PMID:26795347

  18. Electronic clinical predictive thermometer using logarithm for temperature prediction

    NASA Technical Reports Server (NTRS)

    Cambridge, Vivien J. (Inventor); Koger, Thomas L. (Inventor); Nail, William L. (Inventor); Diaz, Patrick (Inventor)

    1998-01-01

    A thermometer that rapidly predicts body temperature based on the temperature signals received from a temperature sensing probe when it comes into contact with the body. The logarithms of the differences between the temperature signals in a selected time frame are determined. A line is fit through the logarithms and the slope of the line is used as a system time constant in predicting the final temperature of the body. The time constant in conjunction with predetermined additional constants are used to compute the predicted temperature. Data quality in the time frame is monitored and if unacceptable, a different time frame of temperature signals is selected for use in prediction. The processor switches to a monitor mode if data quality over a limited number of time frames is unacceptable. Determining the start time on which the measurement time frame for prediction is based is performed by summing the second derivatives of temperature signals over time frames. When the sum of second derivatives in a particular time frame exceeds a threshold, the start time is established.

  19. Molecular Markers Predictive of Chemotherapy Response in Colorectal Cancer

    PubMed Central

    Shiovitz, Stacey; Grady, William M.

    2015-01-01

    Recognition of the molecular heterogeneity of colorectal cancer (CRC) has led to the classification of CRC based on a variety of clinical and molecular characteristics. Although the clinical significance of the majority of these molecular alterations is still being ascertained, it is widely anticipated that these characteristics will improve the accuracy of our ability to determine the prognosis and therapeutic response of CRC patients. A few of these markers, such as microsatellite instability and the CpG island methylator phenotype (CIMP), show promise as predictive markers for cytotoxic chemotherapy. KRAS is a validated biomarker for EGFR-targeted therapy, while NRAS and PI3KCA are evolving markers for targeted therapies. Multiple new actionable drug targets are being identified on a regular basis, but most are not ready for clinical use at this time. This review focuses on key molecular features of CRCs and the application of these molecular alterations as predictive biomarkers for CRC. PMID:25663616

  20. Clinical and EEG response to anticonvulsants in neonatal seizures.

    PubMed Central

    Connell, J; Oozeer, R; de Vries, L; Dubowitz, L M; Dubowitz, V

    1989-01-01

    During a two year period prospective continuous electroencephalographic (EEG) monitoring of 275 infants identified seizure activity in 55 cases, 31 of whom were treated with anticonvulsant drugs on clinical grounds. EEG and clinical response was complete in only two and equivocal in another six. Clinical response with persistent EEG seizures occurred in 13 and neither clinical nor EEG response in 10. There was no significant improvement in the generally poor neurological outcome compared with that in 24 infants whose seizures were not treated because of limited or absent clinical manifestations. Background EEG abnormality (as an index of associated cerebral dysfunction) was a guide to potential lack of response to anticonvulsant drugs; it was also predictive of subsequent clinical outcome irrespective of treatment. This study shows that commonly used anticonvulsant drugs (phenobarbitone, paraldehyde, phenytoin, and diazepam) have little effect on seizure control or neurological outcome in neonatal seizures associated with haemorrhagic, hypoxic, or ischaemic cerebral lesions. In view of the variable clinical appearance of EEG seizure activity, continuous EEG monitoring should be an essential feature of further study of neonatal anticonvulsant treatment. PMID:2730114

  1. Prediction of Achievement in Clinical Pharmacy Courses

    ERIC Educational Resources Information Center

    Simon, Lee S.

    1978-01-01

    A study sought to identify student characteristics which account for academic achievement in clinical pharmacy courses. Preclinical grade point average was the best predictor. Subscales of the California Personality Inventory and the Myers-Briggs Type Indicator, work experience, sex, and age were the other predictor variables. (SW)

  2. Personalized Nutrition by Prediction of Glycemic Responses.

    PubMed

    Zeevi, David; Korem, Tal; Zmora, Niv; Israeli, David; Rothschild, Daphna; Weinberger, Adina; Ben-Yacov, Orly; Lador, Dar; Avnit-Sagi, Tali; Lotan-Pompan, Maya; Suez, Jotham; Mahdi, Jemal Ali; Matot, Elad; Malka, Gal; Kosower, Noa; Rein, Michal; Zilberman-Schapira, Gili; Dohnalová, Lenka; Pevsner-Fischer, Meirav; Bikovsky, Rony; Halpern, Zamir; Elinav, Eran; Segal, Eran

    2015-11-19

    Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences. VIDEO ABSTRACT. PMID:26590418

  3. Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches

    PubMed Central

    Kim, Jae-Won; Sharma, Vinod

    2015-01-01

    Background: There are no objective, biological markers that can robustly predict methylphenidate response in attention deficit hyperactivity disorder. This study aimed to examine whether applying machine learning approaches to pretreatment demographic, clinical questionnaire, environmental, neuropsychological, neuroimaging, and genetic information can predict therapeutic response following methylphenidate administration. Methods: The present study included 83 attention deficit hyperactivity disorder youth. At baseline, parents completed the ADHD Rating Scale-IV and Disruptive Behavior Disorder rating scale, and participants undertook the continuous performance test, Stroop color word test, and resting-state functional MRI scans. The dopamine transporter gene, dopamine D4 receptor gene, alpha-2A adrenergic receptor gene (ADRA2A) and norepinephrine transporter gene polymorphisms, and blood lead and urine cotinine levels were also measured. The participants were enrolled in an 8-week, open-label trial of methylphenidate. Four different machine learning algorithms were used for data analysis. Results: Support vector machine classification accuracy was 84.6% (area under receiver operating characteristic curve 0.84) for predicting methylphenidate response. The age, weight, ADRA2A MspI and DraI polymorphisms, lead level, Stroop color word test performance, and oppositional symptoms of Disruptive Behavior Disorder rating scale were identified as the most differentiating subset of features. Conclusions: Our results provide preliminary support to the translational development of support vector machine as an informative method that can assist in predicting treatment response in attention deficit hyperactivity disorder, though further work is required to provide enhanced levels of classification performance. PMID:25964505

  4. Predicting outcome in clinically isolated syndrome using machine learning

    PubMed Central

    Wottschel, V.; Alexander, D.C.; Kwok, P.P.; Chard, D.T.; Stromillo, M.L.; De Stefano, N.; Thompson, A.J.; Miller, D.H.; Ciccarelli, O.

    2014-01-01

    We aim to determine if machine learning techniques, such as support vector machines (SVMs), can predict the occurrence of a second clinical attack, which leads to the diagnosis of clinically-definite Multiple Sclerosis (CDMS) in patients with a clinically isolated syndrome (CIS), on the basis of single patient's lesion features and clinical/demographic characteristics. Seventy-four patients at onset of CIS were scanned and clinically reviewed after one and three years. CDMS was used as the gold standard against which SVM classification accuracy was tested. Radiological features related to lesional characteristics on conventional MRI were defined a priori and used in combination with clinical/demographic features in an SVM. Forward recursive feature elimination with 100 bootstraps and a leave-one-out cross-validation was used to find the most predictive feature combinations. 30 % and 44 % of patients developed CDMS within one and three years, respectively. The SVMs correctly predicted the presence (or the absence) of CDMS in 71.4 % of patients (sensitivity/specificity: 77 %/66 %) at 1 year, and in 68 % (60 %/76 %) at 3 years on average over all bootstraps. Combinations of features consistently gave a higher accuracy in predicting outcome than any single feature. Machine-learning-based classifications can be used to provide an “individualised” prediction of conversion to MS from subjects' baseline scans and clinical characteristics, with potential to be incorporated into routine clinical practice. PMID:25610791

  5. Predicting and Monitoring Cancer Treatment Response with DW-MRI

    PubMed Central

    Thoeny, Harriet C.; Ross, Brian D.

    2010-01-01

    An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, non-image based clinical outcome metrics include morphology, clinical and laboratory parameters however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of a many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pre-treatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response. PMID:20575076

  6. Mouse models of human AML accurately predict chemotherapy response

    PubMed Central

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.

    2009-01-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691

  7. Mouse models of human AML accurately predict chemotherapy response.

    PubMed

    Zuber, Johannes; Radtke, Ina; Pardee, Timothy S; Zhao, Zhen; Rappaport, Amy R; Luo, Weijun; McCurrach, Mila E; Yang, Miao-Miao; Dolan, M Eileen; Kogan, Scott C; Downing, James R; Lowe, Scott W

    2009-04-01

    The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691

  8. Prediction of clinical behaviour and treatment for cancers.

    PubMed

    Futschik, Matthias E; Sullivan, Mike; Reeve, Anthony; Kasabov, Nikola

    2003-01-01

    Prediction of clinical behaviour and treatment for cancers is based on the integration of clinical and pathological parameters. Recent reports have demonstrated that gene expression profiling provides a powerful new approach for determining disease outcome. If clinical and microarray data each contain independent information then it should be possible to combine these datasets to gain more accurate prognostic information. Here, we have used existing clinical information and microarray data to generate a combined prognostic model for outcome prediction for diffuse large B-cell lymphoma (DLBCL). A prediction accuracy of 87.5% was achieved. This constitutes a significant improvement compared to the previously most accurate prognostic model with an accuracy of 77.6%. The model introduced here may be generally applicable to the combination of various types of molecular and clinical data for improving medical decision support systems and individualising patient care. PMID:15130817

  9. Roles and Responsibilities of Clinical Nurse Researchers.

    ERIC Educational Resources Information Center

    Kirchhoff, Karin T.; Mateo, Magdelena A.

    1996-01-01

    A follow-up survey of 142 nurse researchers employed in clinical settings (75% response) found that fewer than half have a budget, 52% have secretarial support, 82% have a research committee, and 71% report to the chief nurse executive. Although their positions were primarily research, the average time spent on research was 50%. (JOW)

  10. [Clinical Responses To Infants and Families.

    ERIC Educational Resources Information Center

    Fenichel, Emily, Ed.

    1995-01-01

    This journal issue focuses on family service clinical responses to infants and families. In "The Therapeutic Relationship as Human Connectedness," Jeree H. Pawl stresses the importance of caregivers creating in children the sense and experience of human connectedness that arises from the feeling of existing in the mind of someone else--that is,…

  11. Prediction of Psilocybin Response in Healthy Volunteers

    PubMed Central

    Studerus, Erich; Gamma, Alex; Kometer, Michael; Vollenweider, Franz X.

    2012-01-01

    Responses to hallucinogenic drugs, such as psilocybin, are believed to be critically dependent on the user's personality, current mood state, drug pre-experiences, expectancies, and social and environmental variables. However, little is known about the order of importance of these variables and their effect sizes in comparison to drug dose. Hence, this study investigated the effects of 24 predictor variables, including age, sex, education, personality traits, drug pre-experience, mental state before drug intake, experimental setting, and drug dose on the acute response to psilocybin. The analysis was based on the pooled data of 23 controlled experimental studies involving 409 psilocybin administrations to 261 healthy volunteers. Multiple linear mixed effects models were fitted for each of 15 response variables. Although drug dose was clearly the most important predictor for all measured response variables, several non-pharmacological variables significantly contributed to the effects of psilocybin. Specifically, having a high score in the personality trait of Absorption, being in an emotionally excitable and active state immediately before drug intake, and having experienced few psychological problems in past weeks were most strongly associated with pleasant and mystical-type experiences, whereas high Emotional Excitability, low age, and an experimental setting involving positron emission tomography most strongly predicted unpleasant and/or anxious reactions to psilocybin. The results confirm that non-pharmacological variables play an important role in the effects of psilocybin. PMID:22363492

  12. Predicting Flutter and Forced Response in Turbomachinery

    NASA Technical Reports Server (NTRS)

    VanZante, Dale E.; Adamczyk, John J.; Srivastava, Rakesh; Bakhle, Milind A.; Shabbir, Aamir; Chen, Jen-Ping; Janus, J. Mark; To, Wai-Ming; Barter, John

    2005-01-01

    TURBO-AE is a computer code that enables detailed, high-fidelity modeling of aeroelastic and unsteady aerodynamic characteristics for prediction of flutter, forced response, and blade-row interaction effects in turbomachinery. Flow regimes that can be modeled include subsonic, transonic, and supersonic, with attached and/or separated flow fields. The three-dimensional Reynolds-averaged Navier-Stokes equations are solved numerically to obtain extremely accurate descriptions of unsteady flow fields in multistage turbomachinery configurations. Blade vibration is simulated by use of a dynamic-grid-deformation technique to calculate the energy exchange for determining the aerodynamic damping of vibrations of blades. The aerodynamic damping can be used to assess the stability of a blade row. TURBO-AE also calculates the unsteady blade loading attributable to such external sources of excitation as incoming gusts and blade-row interactions. These blade loadings, along with aerodynamic damping, are used to calculate the forced responses of blades to predict their fatigue lives. Phase-lagged boundary conditions based on the direct-store method are used to calculate nonzero interblade phase-angle oscillations; this practice eliminates the need to model multiple blade passages, and, hence, enables large savings in computational resources.

  13. Biosocial processes predicting multisystemic therapy treatment response.

    PubMed

    Ryan, Stacy R; Brennan, Patricia A; Cunningham, Phillippe B; Foster, Sharon L; Brock, Rebecca L; Whitmore, Elizabeth

    2013-02-01

    This study examined biological (testosterone) and social (deviant peer affiliation) factors early in treatment as predictors of treatment outcome among adolescent boys receiving Multisystemic Therapy (MST) in community settings. Outcome variables included changes in youth aggression and delinquency as reported by the primary caregiver. Testosterone and deviant peer affiliation were assessed at treatment onset; and outcome variables (aggression and delinquency) were assessed at treatment onset, mid-treatment and end-of-treatment. Participants were 112 adolescent boys (M age=15.42, SD=1.31) and their caregivers. Growth curve analyses revealed that the combination of high testosterone and high deviant peer affiliation early in treatment were significantly associated with less of a decline in aggression and delinquency over the course of treatment. Results provide novel evidence for the role of testosterone in the prediction of future externalizing behaviors. Clinical and theoretical implications are discussed. PMID:23247043

  14. Clinical Trials for Predictive Medicine—New Challenges and Paradigms*

    PubMed Central

    Simon, Richard

    2014-01-01

    Background Developments in biotechnology and genomics have increased the focus of biostatisticians on prediction problems. This has led to many exciting developments for predictive modeling where the number of variables is larger than the number of cases. Heterogeneity of human diseases and new technology for characterizing them presents new opportunities and challenges for the design and analysis of clinical trials. Purpose In oncology, treatment of broad populations with regimens that do not benefit most patients is less economically sustainable with expensive molecularly targeted therapeutics. The established molecular heterogeneity of human diseases requires the development of new paradigms for the design and analysis of randomized clinical trials as a reliable basis for predictive medicine[1, 2]. Results We have reviewed prospective designs for the development of new therapeutics with candidate predictive biomarkers. We have also outlined a prediction based approach to the analysis of randomized clinical trials that both preserves the type I error and provides a reliable internally validated basis for predicting which patients are most likely or unlikely to benefit from the new regimen. Conclusions Developing new treatments with predictive biomarkers for identifying the patients who are most likely or least likely to benefit makes drug development more complex. But for many new oncology drugs it is the only science based approach and should increase the chance of success. It may also lead to more consistency in results among trials and has obvious benefits for reducing the number of patients who ultimately receive expensive drugs which expose them risks of adverse events but no benefit. This approach also has great potential value for controlling societal expenditures on health care. Development of treatments with predictive biomarkers requires major changes in the standard paradigms for the design and analysis of clinical trials. Some of the key assumptions

  15. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS.

    PubMed

    Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Altman, Russ B

    2016-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)<0.35 (e.g., pneumonia) to stable admissions for planned procedures (e.g., chemotherapy, surgery) with comparatively high RBO>0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10(-10)). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  16. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS

    PubMed Central

    CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B

    2015-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)<0.35 (e.g., pneumonia) to stable admissions for planned procedures (e.g., chemotherapy, surgery) with comparatively high RBO>0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10−10). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  17. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets.

    PubMed

    Swanton, Charles; Larkin, James M; Gerlinger, Marco; Eklund, Aron C; Howell, Michael; Stamp, Gordon; Downward, Julian; Gore, Martin; Futreal, P Andrew; Escudier, Bernard; Andre, Fabrice; Albiges, Laurence; Beuselinck, Benoit; Oudard, Stephane; Hoffmann, Jens; Gyorffy, Balázs; Torrance, Chris J; Boehme, Karen A; Volkmer, Hansjuergen; Toschi, Luisella; Nicke, Barbara; Beck, Marlene; Szallasi, Zoltan

    2010-01-01

    The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding

  18. Predicting Clinical Scores from Magnetic Resonance Scans in Alzheimer's Disease

    PubMed Central

    Stonnington, Cynthia M.; Chu, Carlton; Klöppel, Stefan; Jack, Clifford R; Ashburner, John; Frackowiak, Richard S.J.

    2010-01-01

    Machine learning and pattern recognition methods have been used to diagnose Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) from individual MRI scans. Another application of such methods is to predict clinical scores from individual scans. Using relevance vector regression (RVR), we predicted individuals' performances on established tests from their MRI T1 weighted image in two independent datasets. From Mayo Clinic, 73 probable AD patients and 91 cognitively normal (CN) controls completed the Mini-Mental State Examination (MMSE), Dementia Rating Scale (DRS), and Auditory Verbal Learning Test (AVLT) within 3 months of their scan. Baseline MRI's from the Alzheimer's disease Neuroimaging Initiative (ADNI) comprised the other dataset; 113 AD, 351 MCI, and 122 CN subjects completed the MMSE and Alzheimer's Disease Assessment Scale—Cognitive subtest (ADAS-cog) and 39 AD, 92 MCI, and 32 CN ADNI subjects completed MMSE, ADAS-cog, and AVLT. Predicted and actual clinical scores were highly correlated for the MMSE, DRS, and ADAS-cog tests (P<.0001). Training with one dataset and testing with another demonstrated stability between datasets. DRS, MMSE, and ADAS-Cog correlated better than AVLT with whole brain grey matter changes associated with AD. This result underscores their utility for screening and tracking disease. RVR offers a novel way to measure interactions between structural changes and neuropsychological tests beyond that of univariate methods. In clinical practice, we envision using RVR to aid in diagnosis and predict clinical outcome. PMID:20347044

  19. Elevated EBNA1 Immune Responses Predict Conversion to Multiple Sclerosis

    PubMed Central

    Lünemann, Jan D.; Tintoré, Mar; Messmer, Brady; Strowig, Till; Rovira, Álex; Perkal, Héctor; Caballero, Estrella; Münz, Christian; Montalban, Xavier; Comabella, Manuel

    2009-01-01

    Objective The aims of the study were to determine the immune responses to candidate viral triggers of multiple sclerosis (MS) in patients with clinically isolated syndromes (CIS), and to evaluate their potential value in predicting conversion to MS. Methods Immune responses to Epstein-Barr virus (EBV), human herpesvirus 6, cytomegalovirus (HCMV), and measles were determined in a cohort of 147 CIS patients with a mean follow-up of 7 years and compared with 50 demographically matched controls. Results Compared to controls, CIS patients showed increased humoral (p<0.0001) and cellular (p=0.007) immune responses to the EBV-encoded nuclear antigen-1 (EBNA1), but not to other EBV-derived proteins. IgG responses to other virus antigens and frequencies of T cells specific for HCMV and influenza virus gene products were unchanged in CIS patients. EBNA1 was the only viral antigen towards which immune responses correlated with number of T2 lesions (p=0.006) and number of Barkhof criteria (p=0.001) at baseline, and with number of T2 lesions (p=0.012 both at 1 and 5 years), presence of new T2 lesions (p=0.003 and p=0.028 at 1 and 5 years), and EDSS (p=0.015 and p=0.010 at 1 and 5 years) during follow-up. In a univariate Cox regression model, increased EBNA1-specific IgG responses predicted conversion to MS based on McDonald criteria [hazard ratio (95% confidence interval), 2.2 (1.2–4.3); p=0.003]. Interpretation Our results indicate that elevated immune responses towards EBNA1 are selectively increased in CIS patients and suggest that EBNA1-specific IgG titers could be used as a prognostic marker for disease conversion and disability progression. PMID:20225269

  20. On-time clinical phenotype prediction based on narrative reports

    PubMed Central

    Bejan, Cosmin A.; Vanderwende, Lucy; Evans, Heather L.; Wurfel, Mark M.; Yetisgen-Yildiz, Meliha

    2013-01-01

    In this paper we describe a natural language processing system which is able to predict whether or not a patient exhibits a specific phenotype using the information extracted from the narrative reports associated with the patient. Furthermore, the phenotypic annotations from our report dataset were performed at the report level which allows us to perform the prediction of the clinical phenotype at any point in time during the patient hospitalization period. Our experiments indicate that an important factor in achieving better results for this problem is to determine how much information to extract from the patient reports in the time interval between the patient admission time and the current prediction time. PMID:24551325

  1. Roles and responsibilities of clinical nurse researchers.

    PubMed

    Kirchhoff, K T; Mateo, M A

    1996-01-01

    A follow-up survey of 142 nurse researchers employed in clinical settings (NRECS) was conducted 10 years after the first one conducted by Knafl, Bevis, and Kirchhoff in which only 34 individuals qualified for inclusion. An 80-item questionnaire included items about the structure of the position, processes used, variables that may influence outcomes, and outside activities. When ineligible persons were excluded, the response rate was 75 per cent. Most commonly NRECS had positions in clinical settings only (55.7 per cent), offices (75.5 per cent), some staff (72.6 per cent), and secretarial support (52.8 per cent), and they usually reported to the chief nurse executives (71.7 per cent). Although the majority of NRECS reported responsibility for research activities, the average time spent on research is only 50 per cent. Most (82 per cent) have a nursing research committee, but NRECS also sit on other research-related committees in the department or hospital. Details about salary, responsibilities, and processes will be helpful to those preparing themselves or others for this role, for those who wish to start such a position for themselves or another, or for those in the role wanting to know how other NRECS perform. PMID:8632106

  2. Clinical and Immunological Responses in Ocular Demodecosis

    PubMed Central

    Kim, Jae Hoon; Chun, Yeoun Sook

    2011-01-01

    The purpose of this study was to investigate clinical and immunological responses to Demodex on the ocular surface. Thirteen eyes in 10 patients with Demodex blepharitis and chronic ocular surface disorders were included in this study and treated by lid scrubbing with tea tree oil for the eradication of Demodex. We evaluated ocular surface manifestations and Demodex counts, and analyzed IL-1β, IL-5, IL-7, IL-12, IL-13, IL-17, granulocyte colony-stimulating factor, and macrophage inflammatory protein-1β in tear samples before and after the treatment. All patients exhibited ocular surface manifestations including corneal nodular opacity, peripheral corneal vascularization, refractory corneal erosion and infiltration, or chronic conjunctival inflammatory signs before treatment. After treatment, Demodex was nearly eradicated, tear concentrations of IL-1β and IL-17 were significantly reduced and substantial clinical improvement was observed in all patients. In conclusion, we believe that Demodex plays an aggravating role in inflammatory ocular surface disorders. PMID:21935281

  3. Analysis of factors that predict clinical performance in medical school.

    PubMed

    White, Casey B; Dey, Eric L; Fantone, Joseph C

    2009-10-01

    Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT predict performance in medical school consistently across students, and whether either predicts clinical performance in clerkships. A path model was developed to examine relationships among indices of medical student performance during the first three years of medical school for five cohorts of medical students. A structural equation approach was used to calculate the coefficients hypothesized in the model for majority and minority students. Significant differences between majority and minority students were observed. MCAT scores, for example, did not predict performance of minority students in the first year of medical school but did predict performance of majority students. This information may be of use to medical school admissions and resident selection committees. PMID:18030590

  4. Response Predicting LTCC Firing Shrinkage: A Response Surface Analysis Study

    SciTech Connect

    Girardi, Michael; Barner, Gregg; Lopez, Cristie; Duncan, Brent; Zawicki, Larry

    2009-02-25

    The Low Temperature Cofired Ceramic (LTCC) technology is used in a variety of applications including military/space electronics, wireless communication, MEMS, medical and automotive electronics. The use of LTCC is growing due to the low cost of investment, short development time, good electrical and mechanical properties, high reliability, and flexibility in design integration (3 dimensional (3D) microstructures with cavities are possible)). The dimensional accuracy of the resulting x/y shrinkage of LTCC substrates is responsible for component assembly problems with the tolerance effect that increases in relation to the substrate size. Response Surface Analysis was used to predict product shrinkage based on specific process inputs (metal loading, layer count, lamination pressure, and tape thickness) with the ultimate goal to optimize manufacturing outputs (NC files, stencils, and screens) in achieving the final product design the first time. Three (3) regression models were developed for the DuPont 951 tape system with DuPont 5734 gold metallization based on green tape thickness.

  5. Clinical Prediction Rule of Drug Resistant Epilepsy in Children

    PubMed Central

    Boonluksiri, Pairoj; Visuthibhan, Anannit; Katanyuwong, Kamornwan

    2015-01-01

    Background and Purpose: Clinical prediction rules (CPR) are clinical decision-making tools containing variables such as history, physical examination, diagnostic tests by developing scoring model from potential risk factors. This study is to establish clinical prediction scoring of drug-resistant epilepsy (DRE) in children using clinical manifestationa and only basic electroencephalography (EEG). Methods: Retrospective cohort study was conducted. A total of 308 children with diagnosed epilepsy were recruited. Primary outcome was the incidence of DRE. Independent determinants were patient characteristics, clinical manifestations and electroencephalography. CPR was performed based on multiple logistic regression. Results: The incidence of DRE was 42%. Risk factors were age onset, prior neurological deficits, and abnormal EEG. CPR can be established and stratified the prediction using scores into 3 levels such as low risk (score<6), moderate risk (score 6–12) and high risk (score>12) with positive likelihood ratio of 0.5, 1.8 and 12.5 respectively. Conclusions: CPR with scoring risks were stratified into 3 levels. The strongest risk is prior global neurological deficits. PMID:26819940

  6. Clinical predictors of therapeutic response to antipsychotics in schizophrenia

    PubMed Central

    Carbon, Maren; Correll, Christoph U.

    2014-01-01

    The search for clinical outcome predictors for schizophrenia is as old as the field of psychiatry. However, despite a wealth of large, longitudinal studies into prognostic factors, only very few clinically useful outcome predictors have been identified. The goal of future treatment is to either affect modifiable risk factors, or use nonmodifiable factors to parse patients into therapeutically meaningful subgroups. Most clinical outcome predictors are nonspecific and/or nonmodifiable. Nonmodifiable predictors for poor odds of remission include male sex, younger age at disease onset, poor premorbid adjustment, and severe baseline psychopathology. Modifiable risk factors for poor therapeutic outcomes that clinicians can act upon include longer duration of untreated illness, nonadherence to antipsychotics, comorbidities (especially substance-use disorders), lack of early antipsychotic response, and lack of improvement with non-clozapine antipsychotics, predicting clozapine response. It is hoped that this limited capacity for prediction will improve as pathophysiological understanding increases and/or new treatments for specific aspects of schizophrenia become available. PMID:25733955

  7. Prediction and diagnosis of clinical outcomes affecting restoration margins.

    PubMed

    Dennison, J B; Sarrett, D C

    2012-04-01

    The longevity of dental restorations is largely dependent on the continuity at the interface between the restorative material and adjacent tooth structure (the restoration margin). Clinical decisions on restoration repair or replacement are usually based upon the weakest point along that margin interface. Physical properties of a restorative material, such as polymerisation shrinkage, water sorption, solubility, elastic modulus and shear strength, all have an effect on stress distribution and can significantly affect margin integrity. This review will focus on two aspects of margin deterioration in the oral environment: the in vitro testing of margin seal using emersion techniques to simulate the oral environment and to predict clinical margin failure and the relationship between clinically observable microleakage and secondary caries. The many variables associated with in vitro testing of marginal leakage and the interpretation of the data are presented in detail. The most recent studies of marginal leakage mirror earlier methodology and lack validity and reliability. The lack of standardised testing procedures makes it impossible to compare studies or to predict the clinical performance of adhesive materials. Continual repeated in vitro studies contribute little to the science in this area. Clinical evidence is cited to refute earlier conclusions that clinical microleakage (penetrating margin discoloration) leads to caries development and is an indication for restoration replacement. Margin defects, without visible evidence of soft dentin on the wall or base of the defect, should be monitored, repaired or resealed, in lieu of total restoration replacement. PMID:22066463

  8. Clinical Risk Prediction by Exploring High-Order Feature Correlations

    PubMed Central

    Wang, Fei; Zhang, Ping; Wang, Xiang; Hu, Jianying

    2014-01-01

    Clinical risk prediction is one important problem in medical informatics, and logistic regression is one of the most widely used approaches for clinical risk prediction. In many cases, the number of potential risk factors is fairly large and the actual set of factors that contribute to the risk is small. Therefore sparse logistic regression is proposed, which can not only predict the clinical risk but also identify the set of relevant risk factors. The inputs of logistic regression and sparse logistic regression are required to be in vector form. This limits the applicability of these models in the problems when the data cannot be naturally represented vectors (e.g., medical images are two-dimensional matrices). To handle the cases when the data are in the form of multi-dimensional arrays, we propose HOSLR: High-Order Sparse Logistic Regression, which can be viewed as a high order extension of sparse logistic regression. Instead of solving one classification vector as in conventional logistic regression, we solve for K classification vectors in HOSLR (K is the number of modes in the data). A block proximal descent approach is proposed to solve the problem and its convergence is guaranteed. Finally we validate the effectiveness of HOSLR on predicting the onset risk of patients with Alzheimer’s disease and heart failure. PMID:25954428

  9. Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

    PubMed Central

    Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

    2015-01-01

    Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

  10. Clinical Gestalt and the Prediction of Massive Transfusion after Trauma

    PubMed Central

    Pommerening, Matthew J.; Goodman, Michael D.; Holcomb, John B.; Wade, Charles E.; Fox, Erin E.; del Junco, Deborah J.; Brasel, Karen J.; Bulger, Eileen M.; Cohen, Mitch J.; Alarcon, Louis H.; Schreiber, Martin A.; Myers, John G.; Phelan, Herb A.; Muskat, Peter; Rahbar, Mohammad; Cotton, Bryan A.

    2016-01-01

    Introduction Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesized that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Methods Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centers in patients who survived ≥30 minutes after admission and received ≥1 unit of RBC within 6 hours of arrival. Subjects who received ≥ 10 units within 24 hours of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question “Is the patient likely to be massively transfused?” ten minutes after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Results Of the 1,245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all p < 0.05). Gestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Conclusion Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier. Level of Evidence II; Diagnostic study - Development of diagnostic criteria on basis of consecutive patients (with universally applied reference standard) PMID:25682314

  11. Target Predictability, Sustained Attention, and Response Inhibition

    ERIC Educational Resources Information Center

    Carter, Leonie; Russell, Paul N.; Helton, William S.

    2013-01-01

    We examined whether the sustained attention to response task is a better measure of response inhibition or sustained attention. Participants performed a number detection task for 37.3 min using either a Sustained Attention to Response Task (SART; high Go low No-Go) or a more traditionally formatted vigilance task (TFT; high No-Go low Go) response…

  12. Gambling severity predicts midbrain response to near-miss outcomes

    PubMed Central

    Chase, Henry W.; Clark, Luke

    2010-01-01

    Gambling is a common recreational activity that becomes dysfunctional in a subset of individuals, with DSM ‘pathological gambling’ regarded as the most severe form. During gambling, players experience a range of cognitive distortions that promote an over-estimation of the chances of winning. Near-miss outcomes are thought to fuel these distortions. We observed previously that near-misses recruited overlapping circuitry to monetary wins in a study in healthy volunteers (Clark et al. 2009). The present study sought to extend these observations in regular gamblers and relate brain responses to an index of gambling severity. Twenty regular gamblers, who varied in their involvement from recreational players to probable pathological gamblers, were scanned whilst performing a simplified slot-machine task that delivered occasional monetary wins, as well as near-miss and full-miss non-win outcomes. In the overall group, near-miss outcomes were associated with a significant response in the ventral striatum, which was also recruited by monetary wins. Gambling severity, measured with the South Oaks Gambling Screen, predicted a greater response in the dopaminergic midbrain to near-miss outcomes. This effect survived controlling for clinical co-morbidities that were present in the regular gamblers. Gambling severity did not predict win-related responses in the midbrain or elsewhere. These results demonstrate that near-miss events during gambling recruit reward-related brain circuitry in regular players. An association with gambling severity in the midbrain suggests that near-miss outcomes may enhance dopamine transmission in disordered gambling, which extends neurobiological similarities between pathological gambling and drug addiction. PMID:20445043

  13. How to predict clinical relapse in inflammatory bowel disease patients

    PubMed Central

    Liverani, Elisa; Scaioli, Eleonora; Digby, Richard John; Bellanova, Matteo; Belluzzi, Andrea

    2016-01-01

    Inflammatory bowel diseases have a natural course characterized by alternating periods of remission and relapse. Disease flares occur in a random way and are currently unpredictable for the most part. Predictors of benign or unfavourable clinical course are required to facilitate treatment decisions and to avoid overtreatment. The present article provides a literature review of the current evidence on the main clinical, genetic, endoscopic, histologic, serologic and fecal markers to predict aggressiveness of inflammatory bowel disease and discuss their prognostic role, both in Crohn’s disease and ulcerative colitis. No single marker seems to be reliable alone as a flare predictor, even in light of promising evidence regarding the role of fecal markers, in particular fecal calprotectin, which has reported good results recently. In order to improve our daily clinical practice, validated prognostic scores should be elaborated, integrating clinical and biological markers of prognosis. Finally, we propose an algorithm considering clinical history and biological markers to intercept patients with high risk of clinical relapse. PMID:26811644

  14. Variability in pathogenicity prediction programs: impact on clinical diagnostics

    PubMed Central

    Walters-Sen, Lauren C; Hashimoto, Sayaka; Thrush, Devon Lamb; Reshmi, Shalini; Gastier-Foster, Julie M; Astbury, Caroline; Pyatt, Robert E

    2015-01-01

    Current practice by clinical diagnostic laboratories is to utilize online prediction programs to help determine the significance of novel variants in a given gene sequence. However, these programs vary widely in their methods and ability to correctly predict the pathogenicity of a given sequence change. The performance of 17 publicly available pathogenicity prediction programs was assayed using a dataset consisting of 122 credibly pathogenic and benign variants in genes associated with the RASopathy family of disorders and limb-girdle muscular dystrophy. Performance metrics were compared between the programs to determine the most accurate program for loss-of-function and gain-of-function mechanisms. No one program correctly predicted the pathogenicity of all variants analyzed. A major hindrance to the analysis was the lack of output from a significant portion of the programs. The best performer was MutPred, which had a weighted accuracy of 82.6% in the full dataset. Surprisingly, combining the results of the top three programs did not increase the ability to predict pathogenicity over the top performer alone. As the increasing number of sequence changes in larger datasets will require interpretation, the current study demonstrates that extreme caution must be taken when reporting pathogenicity based on statistical online protein prediction programs in the absence of functional studies. PMID:25802880

  15. Excessive Cytolytic Responses Predict Tuberculosis Relapse After Apparently Successful Treatment

    PubMed Central

    Cliff, Jacqueline M.; Cho, Jang-Eun; Lee, Ji-Sook; Ronacher, Katharina; King, Elizabeth C.; van Helden, Paul; Walzl, Gerhard; Dockrell, Hazel M.

    2016-01-01

    Background. Currently, there are no tools to accurately predict tuberculosis relapse. This study aimed to determine whether patients who experience tuberculosis relapse have different immune responses to mycobacteria in vitro than patients who remain cured for 2 years. Methods. Patients with an initial episode of pulmonary tuberculosis were recruited in South Africa. Diluted blood, collected at diagnosis and after 2 and 4 weeks of treatment, was cultured with live Mycobacterium tuberculosis for 6 days, and cellular RNA was frozen. Gene expression in samples from 10 patients who subsequently experienced relapse, confirmed by strain genotyping, was compared to that in samples from patients who remained cured, using microarrays. Results. At diagnosis, expression of 668 genes was significantly different in samples from patients who experienced relapse, compared with expression in patients who remained successfully cured; these differences persisted for at least 4 weeks. Gene ontology and biological pathways analyses revealed significant upregulation of genes involved in cytotoxic cell-mediated killing. Results were confirmed by real-time quantitative reverse-transcription polymerase chain reaction analysis in a wider patient cohort. Conclusions. These data show that patients who will subsequently experience relapse exhibit altered immune responses, including excessively robust cytolytic responses to M. tuberculosis in vitro, at the time of diagnosis, compared with patients who will achieve durable cure. Together with microbiological and clinical indices, these differences could be exploited in drug development. PMID:26351358

  16. Statistical energy analysis response prediction methods for structural systems

    NASA Technical Reports Server (NTRS)

    Davis, R. F.

    1979-01-01

    The results of an effort to document methods for accomplishing response predictions for commonly encountered aerospace structural configurations is presented. Application of these methods to specified aerospace structure to provide sample analyses is included. An applications manual, with the structural analyses appended as example problems is given. Comparisons of the response predictions with measured data are provided for three of the example problems.

  17. 42 CFR 493.1457 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 5 2011-10-01 2011-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing High Complexity Testing § 493.1457 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the...

  18. 42 CFR 493.1419 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 5 2011-10-01 2011-10-01 false Standard; Clinical consultant responsibilities. 493... Testing Laboratories Performing Moderate Complexity Testing § 493.1419 Standard; Clinical consultant responsibilities. The clinical consultant provides consultation regarding the appropriateness of the...

  19. Ventricular repolarization markers for predicting malignant arrhythmias in clinical practice

    PubMed Central

    Castro-Torres, Yaniel; Carmona-Puerta, Raimundo; Katholi, Richard E

    2015-01-01

    Malignant cardiac arrhythmias which result in sudden cardiac death may be present in individuals apparently healthy or be associated with other medical conditions. The way to predict their appearance represents a challenge for the medical community due to the tragic outcomes in most cases. In the last two decades some ventricular repolarization (VR) markers have been found to be useful to predict malignant cardiac arrhythmias in several clinical conditions. The corrected QT, QT dispersion, Tpeak-Tend, Tpeak-Tend dispersion and Tp-e/QT have been studied and implemented in clinical practice for this purpose. These markers are obtained from 12 lead surface electrocardiogram. In this review we discuss how these markers have demonstrated to be effective to predict malignant arrhythmias in medical conditions such as long and short QT syndromes, Brugada syndrome, early repolarization syndrome, acute myocardial ischemia, heart failure, hypertension, diabetes mellitus, obesity and highly trained athletes. Also the main pathophysiological mechanisms that explain the arrhythmogenic predisposition in these diseases and the basis for the VR markers are discussed. However, the same results have not been found in all conditions. Further studies are needed to reach a global consensus in order to incorporate these VR parameters in risk stratification of these patients. PMID:26301231

  20. Prediction of nuclear hormone receptor response elements.

    PubMed

    Sandelin, Albin; Wasserman, Wyeth W

    2005-03-01

    The nuclear receptor (NR) class of transcription factors controls critical regulatory events in key developmental processes, homeostasis maintenance, and medically important diseases and conditions. Identification of the members of a regulon controlled by a NR could provide an accelerated understanding of development and disease. New bioinformatics methods for the analysis of regulatory sequences are required to address the complex properties associated with known regulatory elements targeted by the receptors because the standard methods for binding site prediction fail to reflect the diverse target site configurations. We have constructed a flexible Hidden Markov Model framework capable of predicting NHR binding sites. The model allows for variable spacing and orientation of half-sites. In a genome-scale analysis enabled by the model, we show that NRs in Fugu rubripes have a significant cross-regulatory potential. The model is implemented in a web interface, freely available for academic researchers, available at http://mordor.cgb.ki.se/NHR-scan. PMID:15563547

  1. Clinical Prediction Rules That Don't Hold Up-Where to Go From Here?

    PubMed

    Stanton, Tasha R

    2016-07-01

    Clinical prediction rules (CPRs) are created to help guide clinical decision making. To do this, they use the presence or absence of certain factors that have been shown to meaningfully predict a patient's prognosis, diagnosis, or response to treatment. While representing a seminal methodological step forward in individualized care, one of the main drawbacks of CPRs continues to be validation studies that do not support the initially derived CPR. This is particularly important because validation of CPRs in an independent patient population prior to clinical implementation is essential. Why is it quite common for existing CPRs to fall down at the validation stage? And what does this mean for research that aims to individualize treatment? J Orthop Sports Phys Ther 2016;46(7):502-505. doi:10.2519/jospt.2016.0606. PMID:27363570

  2. 18F-FDG PET/CT Prediction of an Aggressive Clinical Course for Dermatofibrosarcoma Protuberans.

    PubMed

    Basu, Sandip; Goliwale, Fahim

    2016-06-01

    The ability to assess tumor biology is a benefit of molecular imaging with (18)F-FDG PET/CT, which performs better than anatomic imaging in evaluating malignancies. We present an unusual case of fatal dermatofibrosarcoma protuberans, a usually indolent entity for which high-grade (18)F-FDG uptake was predictive of an aggressive clinical course unabated by tyrosine kinase inhibitor imatinib mesylate, to which the patient showed a poor response. PMID:26338485

  3. Predictable Outcomes with Porcelain Laminate Veneers: A Clinical Report.

    PubMed

    Pimentel, Welson; Teixeira, Marcelo Lucchesi; Costa, Priscila Paganini; Jorge, Mônica Zacharias; Tiossi, Rodrigo

    2016-06-01

    This clinical report describes how to achieve predictable outcomes for anterior teeth esthetic restorations with porcelain laminate veneers by associating the digital planning and design of the restoration with interim restorations. The previous digital smile design of the restoration eliminates the communication barrier with the patient and assists the clinician throughout patient treatment. Interim restorations (diagnostic mock-ups) further enhance communication with the patient and prevent unnecessary tooth reduction for conservative tooth preparation. Adequate communication between patient and clinician contributes to successful definitive restorations and patient satisfaction with the final esthetic outcome. PMID:26633080

  4. Clinical presentation and outcome prediction of clinical, serological, and histopathological classification schemes in ANCA-associated vasculitis with renal involvement.

    PubMed

    Córdova-Sánchez, Bertha M; Mejía-Vilet, Juan M; Morales-Buenrostro, Luis E; Loyola-Rodríguez, Georgina; Uribe-Uribe, Norma O; Correa-Rotter, Ricardo

    2016-07-01

    Several classification schemes have been developed for anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), with actual debate focusing on their clinical and prognostic performance. Sixty-two patients with renal biopsy-proven AAV from a single center in Mexico City diagnosed between 2004 and 2013 were analyzed and classified under clinical (granulomatosis with polyangiitis [GPA], microscopic polyangiitis [MPA], renal limited vasculitis [RLV]), serological (proteinase 3 anti-neutrophil cytoplasmic antibodies [PR3-ANCA], myeloperoxidase anti-neutrophil cytoplasmic antibodies [MPO-ANCA], ANCA negative), and histopathological (focal, crescenteric, mixed-type, sclerosing) categories. Clinical presentation parameters were compared at baseline between classification groups, and the predictive value of different classification categories for disease and renal remission, relapse, renal, and patient survival was analyzed. Serological classification predicted relapse rate (PR3-ANCA hazard ratio for relapse 2.93, 1.20-7.17, p = 0.019). There were no differences in disease or renal remission, renal, or patient survival between clinical and serological categories. Histopathological classification predicted response to therapy, with a poorer renal remission rate for sclerosing group and those with less than 25 % normal glomeruli; in addition, it adequately delimited 24-month glomerular filtration rate (eGFR) evolution, but it did not predict renal nor patient survival. On multivariate models, renal replacement therapy (RRT) requirement (HR 8.07, CI 1.75-37.4, p = 0.008) and proteinuria (HR 1.49, CI 1.03-2.14, p = 0.034) at presentation predicted renal survival, while age (HR 1.10, CI 1.01-1.21, p = 0.041) and infective events during the induction phase (HR 4.72, 1.01-22.1, p = 0.049) negatively influenced patient survival. At present, ANCA-based serological classification may predict AAV relapses, but neither clinical nor serological

  5. Personalized approach to growth hormone treatment: clinical use of growth prediction models.

    PubMed

    Wit, J M; Ranke, M B; Albertsson-Wikland, K; Carrascosa, A; Rosenfeld, R G; Van Buuren, S; Kristrom, B; Schoenau, E; Audi, L; Hokken-Koelega, A C S; Bang, P; Jung, H; Blum, W F; Silverman, L A; Cohen, P; Cianfarani, S; Deal, C; Clayton, P E; de Graaff, L; Dahlgren, J; Kleintjens, J; Roelants, M

    2013-01-01

    The goal of growth hormone (GH) treatment in a short child is to attain a fast catch-up growth toward the target height (TH) standard deviation score (SDS), followed by a maintenance phase, a proper pubertal height gain, and an adult height close to TH. The short-term response variable of GH treatment, first-year height velocity (HV) (cm/year or change in height SDS), can either be compared with GH response charts for diagnosis, age and gender, or with predicted HV based on prediction models. Three types of prediction models have been described: the Kabi International Growth Hormone Study models, the Gothenburg models and the Cologne model. With these models, 50-80% of the variance could be explained. When used prospectively, individualized dosing reduces the variation in growth response in comparison with a fixed dose per body weight. Insulin-like growth factor-I-based dose titration also led to a decrease in the variation. It is uncertain whether adding biochemical, genetic or proteomic markers may improve the accuracy of the prediction. Prediction models may lead to a more evidence-based approach to determine the GH dose regimen and may reduce the drug costs for GH treatment. There is a need for user-friendly software programs to make prediction models easily available in the clinic. PMID:23735882

  6. Predictive Response Value of Pre- and Postchemoradiotherapy Variables in Rectal Cancer: An Analysis of Histological Data

    PubMed Central

    Santos, Marisa D.; Silva, Cristina; Rocha, Anabela; Nogueira, Carlos; Matos, Eduarda; Lopes, Carlos

    2016-01-01

    Background. Neoadjuvant chemoradiotherapy (nCRT) followed by curative surgery in locally advanced rectal cancer (LARC) improves pelvic disease control. Survival improvement is achieved only if pathological response occurs. Mandard tumor regression grade (TRG) proved to be a valid system to measure nCRT response. Potential predictive factors for Mandard response are analyzed. Materials and Methods. 167 patients with LARC were treated with nCRT and curative surgery. Tumor biopsies and surgical specimens were reviewed and analyzed regarding mitotic count, necrosis, desmoplastic reaction, and inflammatory infiltration grade. Surgical specimens were classified according to Mandard TRG. The patients were divided as “good responders” (Mandard TRG1-2) and “bad responders” (Mandard TRG3-5). According to results from our previous data, good responders have better prognosis than bad responders. We examined predictive factors for Mandard response and performed statistical analysis. Results. In univariate analysis, distance from anal verge and ten other postoperative variables related with nCRT tumor response had predictive value for Mandard response. In multivariable analysis only mitotic count, necrosis, and differentiation grade in surgical specimen had predictive value. Conclusions. There is a lack of clinical and pathological preoperative variables able to predict Mandard response. Only postoperative pathological parameters related with nCRT response have predictive value. PMID:26885438

  7. A Novel, Noninvasive, Predictive Epilepsy Biomarker with Clinical Potential

    PubMed Central

    Choy, ManKin; Dubé, Celine M.; Patterson, Katelin; Barnes, Samuel R.; Maras, Pamela; Blood, Arlin B.; Hasso, Anton N.; Obenaus, Andre

    2014-01-01

    A significant proportion of temporal lobe epilepsy (TLE), a common, intractable brain disorder, arises in children with febrile status epilepticus (FSE). Preventative therapy development is hampered by our inability to identify early the FSE individuals who will develop TLE. In a naturalistic rat model of FSE, we used high-magnetic-field MRI and long-term video EEG to seek clinically relevant noninvasive markers of epileptogenesis and found that reduced amygdala T2 relaxation times in high-magnetic-field MRI hours after FSE predicted experimental TLE. Reduced T2 values likely represented paramagnetic susceptibility effects derived from increased unsaturated venous hemoglobin, suggesting augmented oxygen utilization after FSE termination. Indeed, T2 correlated with energy-demanding intracellular translocation of the injury-sensor high-mobility group box 1 (HMGB1), a trigger of inflammatory cascades implicated in epileptogenesis. Use of deoxyhemoglobin-sensitive MRI sequences enabled visualization of the predictive changes on lower-field, clinically relevant scanners. This novel MRI signature delineates the onset and suggests mechanisms of epileptogenesis that follow experimental FSE. PMID:24966369

  8. Dopamine neurons share common response function for reward prediction error

    PubMed Central

    Eshel, Neir; Tian, Ju; Bukwich, Michael; Uchida, Naoshige

    2016-01-01

    Dopamine neurons are thought to signal reward prediction error, or the difference between actual and predicted reward. How dopamine neurons jointly encode this information, however, remains unclear. One possibility is that different neurons specialize in different aspects of prediction error; another is that each neuron calculates prediction error in the same way. We recorded from optogenetically-identified dopamine neurons in the lateral ventral tegmental area (VTA) while mice performed classical conditioning tasks. Our tasks allowed us to determine the full prediction error functions of dopamine neurons and compare them to each other. We found striking homogeneity among individual dopamine neurons: their responses to both unexpected and expected rewards followed the same function, just scaled up or down. As a result, we could describe both individual and population responses using just two parameters. Such uniformity ensures robust information coding, allowing each dopamine neuron to contribute fully to the prediction error signal. PMID:26854803

  9. Clinical neuroprediction: Amygdala reactivity predicts depressive symptoms 2 years later.

    PubMed

    Mattson, Whitney I; Hyde, Luke W; Shaw, Daniel S; Forbes, Erika E; Monk, Christopher S

    2016-06-01

    Depression is linked to increased amygdala activation to neutral and negatively valenced facial expressions. Amygdala activation may be predictive of changes in depressive symptoms over time. However, most studies in this area have focused on small, predominantly female and homogenous clinical samples. Studies are needed to examine how amygdala reactivity relates to the course of depressive symptoms dimensionally, prospectively and in populations diverse in gender, race and socioeconomic status. A total of 156 men from predominately low-income backgrounds completed an fMRI task where they viewed emotional facial expressions. Left and right amygdala reactivity to neutral, but not angry or fearful, facial expressions relative to a non-face baseline at age 20 predicted greater depressive symptoms 2 years later, controlling for age 20 depressive symptoms. Heightened bilateral amygdala reactivity to neutral facial expressions predicted increases in depressive symptoms 2 years later in a large community sample. Neutral facial expressions are affectively ambiguous and a tendency to interpret these stimuli negatively may reflect to cognitive biases that lead to increases in depressive symptoms over time. Individual differences in amygdala reactivity to neutral facial expressions appear to identify those at most risk for a more problematic course of depressive symptoms across time. PMID:26865423

  10. PREDICTIVE BAYESIAN PATHOGEN DOSE-RESPONSE MODEL FORMS

    EPA Science Inventory

    The use of predictive Bayesian methods in dose-response assessment will be investigated. The predictive Bayesian approach offers an alternative to current approaches in that it does not require the selection of a specific confidence limit, yet provides an answer that is more cons...

  11. Psychological hardiness predicts neuroimmunological responses to stress.

    PubMed

    Sandvik, Asle M; Bartone, Paul T; Hystad, Sigurd William; Phillips, Terry M; Thayer, Julian F; Johnsen, Bjørn Helge

    2013-01-01

    Psychological hardiness characterizes people who remain healthy under psychosocial stress. The present exploratory study investigates possible links between hardiness and several immune and neuroendocrine markers: IL-6, IL-12, IL-4, IL-10, & neuropeptide-Y. A total of 21 Norwegian navy cadets were studied in the context of a highly stressful military field exercise. Blood samples were collected midway, and again late in the exercise when stress levels were highest. Psychological hardiness (including commitment, control, and challenge) was measured two days before the exercise. While all subjects scored high in hardiness, some were high only in commitment and control, but relatively low in challenge. These "unbalanced" hardiness subjects were also more stress reactive, showing suppressed proinflammatory cytokines (IL-12), increased anti-inflammatory cytokines (IL-4, IL-10), and lower neuropeptide-Y levels as compared to the hardiness-balanced group. This study thus shows that being high in hardiness with a balanced profile is linked to more moderate and healthy immune and neuroendocrine responses to stress. PMID:23458268

  12. Predictability of steel containment response near failure

    SciTech Connect

    Costello, J.F.; Ludwigsen, J.S.; Luk, V.K.; Hessheimer, M.F.

    2000-01-06

    The Nuclear Power Engineering Corporation of Japan and the US Nuclear Regulatory Commission Office of Nuclear Regulatory Research, are co-sponsoring and jointly funding a Cooperative Containment Research Program at Sandia National Laboratories, Albuquerque, New Mexico, USA. As a part of this program, a steel containment vessel model and contact structure assembly was tested to failure with over pressurization at Sandia on December 11--12, 1996. The steel containment vessel model was a mixed-scale model (1:10 in geometry and 1:4 in shell thickness) of a steel containment for an improved Mark-II Boiling Water Reactor plant in Japan. The contact structure, which is a thick, bell-shaped steel shell separated at a nominally uniform distance from the model, provides a simplified representation of features of the concrete reactor shield building in the actual plant. The objective of the internal pressurization test was to provide measurement data of the structural response of the model up to its failure in order to validate analytical modeling, to find its pressure capacity, and to observe the failure model and mechanisms.

  13. Clinical utility and validity of minoxidil response testing in androgenetic alopecia.

    PubMed

    Goren, Andy; Shapiro, Jerry; Roberts, Janet; McCoy, John; Desai, Nisha; Zarrab, Zoulikha; Pietrzak, Aldona; Lotti, Torello

    2015-01-01

    Clinical response to 5% topical minoxidil for the treatment of androgenetic alopecia (AGA) is typically observed after 3-6 months. Approximately 40% of patients will regrow hair. Given the prolonged treatment time required to elicit a response, a diagnostic test for ruling out nonresponders would have significant clinical utility. Two studies have previously reported that sulfotransferase enzyme activity in plucked hair follicles predicts a patient's response to topical minoxidil therapy. The aim of this study was to assess the clinical utility and validity of minoxidil response testing. In this communication, the present authors conducted an analysis of completed and ongoing studies of minoxidil response testing. The analysis confirmed the clinical utility of a sulfotransferase enzyme test in successfully ruling out 95.9% of nonresponders to topical minoxidil for the treatment of AGA. PMID:25112173

  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. A Model of Placebo Response in Antidepressant Clinical Trials

    PubMed Central

    Rutherford, Bret R; Roose, Steven P.

    2012-01-01

    Placebo response in clinical trials of antidepressant medications is substantial and increasing. High placebo response rates hamper efforts to detect signals of efficacy for new antidepressant medications, contributing to more failed trials and delaying the delivery of new treatments to market. Media reports seize upon increasing placebo response and modest advantages for active drugs as reasons to question the value of antidepressant medication, which may further stigmatize treatments for depression and dissuade patients from accessing mental health care. Conversely, enhancing the factors responsible for placebo response may represent a strategy for improving available treatments for Major Depressive Disorder. A conceptual framework describing the causes of placebo response is needed in order to develop strategies for minimizing placebo response in clinical trials, maximizing placebo response in clinical practice, and talking with depressed patients about the risks and benefits of antidepressant medications. This review examines contributors to placebo response in antidepressant clinical trials and proposes an explanatory model. Research aimed at reducing placebo response should focus on limiting patient expectancy and the intensity of therapeutic contact in antidepressant clinical trials, while the optimal strategy in clinical practice may be to combine active medication with a presentation and level of therapeutic contact that enhances treatment response. PMID:23318413

  16. Predicting the clinical effect of a short acting bronchodilator in individual patients using artificial neural networks.

    PubMed

    de Matas, Marcel; Shao, Qun; Biddiscombe, Martyn F; Meah, Sally; Chrystyn, Henry; Usmani, Omar S

    2010-12-23

    Artificial neural networks were used in this study to model the relationships between in vitro data, subject characteristics and in vivo outcomes from N=18 mild-moderate asthmatics receiving monodisperse salbutamol sulphate aerosols of 1.5, 3 and 6 μm mass median aerodynamic diameter in a cumulative dosing schedule of 10, 20, 40 and 100 μg. Input variables to the model were aerodynamic particle size (APS), body surface area (BSA), age, pre-treatment forced expiratory volume in one-second (FEV(1)), forced vital capacity, cumulative emitted drug dose and bronchodilator reversibility to a standard salbutamol sulphate 200 μg dose MDI (REV(%)). These factors were used by the model to predict the bronchodilator response at 10 (T10) and 20 (T20) min after receiving each of the 4 doses for each of the 3 different particle sizes. Predictability was assessed using data from selected patients in this study, which were set aside and not used in model generation. Models reliably predicted ΔFEV(1)(%) in individual subjects with non-linear determinants (R(2)) of ≥ 0.8. The average error between predicted and observed ΔFEV(1)(%) for individual subjects was <4% across the cumulative dosing regimen. Increases in APS and drug dose gave improved ΔFEV(1)(%). Models also showed trends towards improved responses in younger patients and those having greater REV(%), whilst BSA was also shown to influence clinical effect. These data show that APS can be used to discriminate predictably between aerosols giving different bronchodilator responses across a cumulative dosing schedule, whilst patient characteristics can be used to reliably estimate clinical response in individual subjects. PMID:20932900

  17. Drug-induced death signaling strategy rapidly predicts cancer response to chemotherapy

    PubMed Central

    Montero, Joan; Sarosiek, Kristopher A.; DeAngelo, Joseph D.; Maertens, Ophélia; Ryan, Jeremy; Ercan, Dalia; Piao, Huiying; Horowitz, Neil S.; Berkowitz, Ross S.; Matulonis, Ursula; Jänne, Pasi A.; Amrein, Philip C.; Cichowski, Karen; Drapkin, Ronny; Letai, Anthony

    2015-01-01

    SUMMARY There is a lack of effective predictive biomarkers to precisely assign optimal therapy to cancer patients. While most efforts are directed at inferring drug response phenotype based on genotype, there is very focused and useful phenotypic information to be gained from directly perturbing the patient’s living cancer cell with the drug(s) in question. To satisfy this unmet need we developed the Dynamic BH3 Profiling technique to measure early changes in net pro-apoptotic signaling at the mitochondrion (‘priming’) induced by chemotherapeutic agents in cancer cells, not requiring prolonged ex vivo culture. We find in cell line and clinical experiments that early drug-induced death signaling measured by Dynamic BH3 Profiling predicts chemotherapy response across many cancer types and many agents, including combinations of chemotherapies. We propose that Dynamic BH3 Profiling can be used as a broadly applicable predictive biomarker to predict cytotoxic response of cancers to chemotherapeutics in vivo. PMID:25723171

  18. Probabilistic prediction of barrier-island response to hurricanes

    USGS Publications Warehouse

    Plant, Nathaniel G.; Stockdon, Hilary F.

    2012-01-01

    Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

  19. Clinical and laboratory predictive markers for acute dengue infection

    PubMed Central

    2013-01-01

    Background Early diagnosis of dengue virus infection during the febrile stage is essential for adjusting appropriate management. This study is to identify the predictive markers of clinical and laboratory findings in the acute stage of dengue infection during a major outbreak of dengue virus type 1 that occurred in southern Taiwan during 2007. A retrospective, hospital-based study was conducted at a university hospital in southern Taiwan from January to December, 2007. Patient who was reported for clinically suspected dengue infection was enrolled. Laboratory-positive dengue cases are confirmed by enzyme-linked immunosorbent assay of specific dengue IgM, fourfold increase of dengue-specific IgG titers in convalescent serum, or by reverse transcription-polymerase chain reaction (RT-PCR) of dengue virus. Results The suspected dengue cases consist of 100 children (≤ 18 years) and 481 adults. Among the 581 patients, 67 (67%) children and 309 (64.2%) adults were laboratory-confirmed. Patients who had laboratory indeterminate were excluded. Most cases were uncomplicated and 3.8% of children and 2.9% of adults developed dengue hemorrhagic fever or dengue shock syndrome (DHF/DSS). The overall mortality rate in those with DHF/DSS was 7.1%, and the average duration of hospitalization was 20 days. The most common symptoms/signs at admission were myalgia (46.8%), petechiae (36.9%) and nausea/vomiting (33.5%). The most notable laboratory findings included leukopenia (2966 ± 1896/cmm), thrombocytopenia (102 ± 45 × 103/cmm), prolonged activated partial thromboplastin time (aPTT) (45 ± 10 s), and elevated serum levels of aminotransferase (AST, 166 ± 208 U/L; ALT, 82 ± 103 U/L) and low C - reactive protein (CRP) (6 ± 11 mg/L). Based on the clinical features for predicting laboratory-confirmed dengue infection, the sensitivities of typical rash, myalgia, and positive tourniquet test are 59.2%, 46.8%, and 34.2%, while the specificities for

  20. Improving Clinical Prediction of Bipolar Spectrum Disorders in Youth

    PubMed Central

    Frazier, Thomas W.; Youngstrom, Eric A.; Fristad, Mary A.; Demeter, Christine; Birmaher, Boris; Kowatch, Robert A.; Arnold, L. Eugene; Axelson, David; Gill, Mary K.; Horwitz, Sarah M.; Findling, Robert L.

    2014-01-01

    This report evaluates whether classification tree algorithms (CTA) may improve the identification of individuals at risk for bipolar spectrum disorders (BPSD). Analyses used the Longitudinal Assessment of Manic Symptoms (LAMS) cohort (629 youth, 148 with BPSD and 481 without BPSD). Parent ratings of mania symptoms, stressful life events, parenting stress, and parental history of mania were included as risk factors. Comparable overall accuracy was observed for CTA (75.4%) relative to logistic regression (77.6%). However, CTA showed increased sensitivity (0.28 vs. 0.18) at the expense of slightly decreased specificity and positive predictive power. The advantage of CTA algorithms for clinical decision making is demonstrated by the combinations of predictors most useful for altering the probability of BPSD. The 24% sample probability of BPSD was substantially decreased in youth with low screening and baseline parent ratings of mania, negative parental history of mania, and low levels of stressful life events (2%). High screening plus high baseline parent-rated mania nearly doubled the BPSD probability (46%). Future work will benefit from examining additional, powerful predictors, such as alternative data sources (e.g., clinician ratings, neurocognitive test data); these may increase the clinical utility of CTA models further. PMID:25143826

  1. Urate predicts rate of clinical decline in Parkinson disease

    PubMed Central

    Ascherio, Alberto; LeWitt, Peter A.; Xu, Kui; Eberly, Shirley; Watts, Arthur; Matson, Wayne R.; Marras, Connie; Kieburtz, Karl; Rudolph, Alice; Bogdanov, Mikhail B.; Schwid, Steven R.; Tennis, Marsha; Tanner, Caroline M.; Beal, M. Flint; Lang, Anthony E.; Oakes, David; Fahn, Stanley; Shoulson, Ira; Schwarzschild, Michael A.

    2009-01-01

    Context The risk of Parkinson disease (PD) and its rate of progression may decline with increasing blood urate, a major antioxidant. Objective To determine whether serum and cerebrospinal fluid (CSF) concentrations of urate predict clinical progression in patients with PD. Design, Setting, and Participants 800 subjects with early PD enrolled in the DATATOP trial. Pre-treatment urate was measured in serum for 774 subjects and in CSF for 713. Main Outcome Measures Treatment-, age- and sex-adjusted hazard ratios (HRs) for clinical disability requiring levodopa therapy, the pre-specified primary endpoint. Results The HR of progressing to endpoint decreased with increasing serum urate (HR for 1 standard deviation increase = 0.82; 95% CI = 0.73 to 0.93). In analyses stratified by α-tocopherol treatment (2,000 IU/day), a decrease in the HR for the primary endpoint was seen only among subjects not treated with α-tocopherol (HR = 0.75; 95% CI = 0.62 to 0.89, versus those treated HR = 0.90; 95% CI = 0.75 to 1.08). Results were similar for the rate of change in the United Parkinson Disease Rating Scale (UPDRS). CSF urate was also inversely related to both the primary endpoint (HR for highest versus lowest quintile = 0.65; 95% CI: 0.54 to 0.96) and to the rate of change in UPDRS. As with serum urate, these associations were present only among subjects not treated with α-tocopherol. Conclusion Higher serum and CSF urate at baseline were associated with slower rates of clinical decline. The findings strengthen the link between urate and PD and the rationale for considering CNS urate elevation as a potential strategy to slow PD progression. PMID:19822770

  2. Autoantibody Epitope Spreading in the Pre-Clinical Phase Predicts Progression to Rheumatoid Arthritis

    PubMed Central

    Deane, Kevin D.; Lahey, Lauren J.; Derber, Lezlie A.; Chandra, Piyanka E.; Edison, Jess D.; Gilliland, William R.; Tibshirani, Robert J.; Norris, Jill M.; Holers, V. Michael; Robinson, William H.

    2012-01-01

    Rheumatoid arthritis (RA) is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1–12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which

  3. Model-Based Prediction of the Patient-Specific Response to Adrenaline

    PubMed Central

    Chase, J. Geoffrey; Starfinger, Christina; Hann, Christopher E; Revie, James A; Stevenson, Dave; Shaw, Geoffrey M; Desaive, Thomas

    2010-01-01

    A model for the cardiovascular and circulatory systems has previously been validated in simulated cardiac and circulatory disease states. It has also been shown to accurately capture the main hemodynamic trends in porcine models of pulmonary embolism and PEEP (positive end-expiratory pressure) titrations at different volemic levels. In this research, the existing model and parameter identification process are used to study the effect of different adrenaline doses in healthy and critically ill patient populations, and to develop a means of predicting the hemodynamic response to adrenaline. The hemodynamic effects on arterial blood pressures and stroke volume (cardiac index) are simulated in the model and adrenaline-specific parameters are identified. The dose dependent changes in these parameters are then related to adrenaline dose using data from studies published in the literature. These relationships are then used to predict the future, patient-specific response to a change in dose or over time periods from 1-12 hours. The results are compared to data from 3 published adrenaline dosing studies comprising a total of 37 data sets. Absolute percentage errors for the identified model are within 10% when re-simulated and compared to clinical data for all cases. All identified parameter trends match clinically expected changes. Absolute percentage errors for the predicted hemodynamic responses (N=15) are also within 10% when re-simulated and compared to clinical data. Clinically accurate prediction of the effect of inotropic circulatory support drugs, such as adrenaline, offers significant potential for this type of model-based application. Overall, this work represents a further clinical, proof of concept, of the underlying fundamental mathematical model, methods and approach, as well as providing a template for using the model in clinical titration of adrenaline in a decision support role in critical care. They are thus a further justification in support of upcoming

  4. A novel neural-inspired learning algorithm with application to clinical risk prediction.

    PubMed

    Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

    2015-04-01

    Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials. PMID:25576352

  5. Factors predictive of a beneficial response to therapy of hepatitis C.

    PubMed

    Davis, G L; Lau, J Y

    1997-09-01

    Alpha interferon is the only drug that has been shown to be effective in the treatment of chronic hepatitis C, but only half of patients respond, either transiently or permanently. Pretreatment features that are associated with a greater likelihood of response to short courses of interferon include low hepatitis C virus (HCV) RNA levels, viral genotypes 2 or 3, and the absence of fibrosis or cirrhosis on liver biopsy. Each of these features is more predictive of sustained response (SR) than the end-of-treatment response (ETR). However, the accuracy of these features in predicting response in individual patients is poor. Furthermore, there are several limitations to using these factors in the clinical management of patients. Most importantly, they were identified in 6-month treatment trials. Longer treatment or combination of interferon with ribavirin reduces relapses and will therefore lessen the association of these factors with long-term response. In addition, changes in the definition of treatment end points and the technology used to measure HCV RNA might change the association between these predictive factors and response. The best predictor of a treatment response is the early normalization of the serum alanine aminotransferase (ALT) level during interferon treatment. HCV RNA loss during treatment may also be helpful in predicting response, but it is probably no better than serum ALT levels and is expensive. In summary, several clinical and virological features are associated with higher response rates to interferon treatment. Although pretreatment factors do not accurately predict treatment outcome in individuals, they may be helpful in counseling patients and making treatment decisions. PMID:9305676

  6. Predicting olfactory receptor neuron responses from odorant structure

    PubMed Central

    Schmuker, Michael; de Bruyne, Marien; Hähnel, Melanie; Schneider, Gisbert

    2007-01-01

    Background Olfactory receptors work at the interface between the chemical world of volatile molecules and the perception of scent in the brain. Their main purpose is to translate chemical space into information that can be processed by neural circuits. Assuming that these receptors have evolved to cope with this task, the analysis of their coding strategy promises to yield valuable insight in how to encode chemical information in an efficient way. Results We mimicked olfactory coding by modeling responses of primary olfactory neurons to small molecules using a large set of physicochemical molecular descriptors and artificial neural networks. We then tested these models by recording in vivo receptor neuron responses to a new set of odorants and successfully predicted the responses of five out of seven receptor neurons. Correlation coefficients ranged from 0.66 to 0.85, demonstrating the applicability of our approach for the analysis of olfactory receptor activation data. The molecular descriptors that are best-suited for response prediction vary for different receptor neurons, implying that each receptor neuron detects a different aspect of chemical space. Finally, we demonstrate that receptor responses themselves can be used as descriptors in a predictive model of neuron activation. Conclusion The chemical meaning of molecular descriptors helps understand structure-response relationships for olfactory receptors and their "receptive fields". Moreover, it is possible to predict receptor neuron activation from chemical structure using machine-learning techniques, although this is still complicated by a lack of training data. PMID:17880742

  7. Predicted ball grid array thermal response during reflow soldering

    SciTech Connect

    Voth, T.E.; Bergman, T.L.

    1995-12-31

    A numerical model is developed to predict the detailed thermomechanical response of a BGA assembly during reflow soldering. The governing coupled solid mechanics and heat diffusion equations are solved using a commercially available finite element package. Reported predictions illustrate the system`s sensitivity to both thermal and mechanical processing conditions, as well as component thermal properties. Specifically, assemblies with components of high thermal conductivity show the greatest sensitivity to mechanical loading conditions.

  8. A Systematic Review of Studies Comparing Diagnostic Clinical Prediction Rules with Clinical Judgment

    PubMed Central

    Sanders, Sharon; Doust, Jenny; Glasziou, Paul

    2015-01-01

    Background Diagnostic clinical prediction rules (CPRs) are developed to improve diagnosis or decrease diagnostic testing. Whether, and in what situations diagnostic CPRs improve upon clinical judgment is unclear. Methods and Findings We searched MEDLINE, Embase and CINAHL, with supplementary citation and reference checking for studies comparing CPRs and clinical judgment against a current objective reference standard. We report 1) the proportion of study participants classified as not having disease who hence may avoid further testing and or treatment and 2) the proportion, among those classified as not having disease, who do (missed diagnoses) by both approaches. 31 studies of 13 medical conditions were included, with 46 comparisons between CPRs and clinical judgment. In 2 comparisons (4%), CPRs reduced the proportion of missed diagnoses, but this was offset by classifying a larger proportion of study participants as having disease (more false positives). In 36 comparisons (78%) the proportion of diagnoses missed by CPRs and clinical judgment was similar, and in 9 of these, the CPRs classified a larger proportion of participants as not having disease (fewer false positives). In 8 comparisons (17%) the proportion of diagnoses missed by the CPRs was greater. This was offset by classifying a smaller proportion of participants as having the disease (fewer false positives) in 2 comparisons. There were no comparisons where the CPR missed a smaller proportion of diagnoses than clinical judgment and classified more participants as not having the disease. The design of the included studies allows evaluation of CPRs when their results are applied independently of clinical judgment. The performance of CPRs, when implemented by clinicians as a support to their judgment may be different. Conclusions In the limited studies to date, CPRs are rarely superior to clinical judgment and there is generally a trade-off between the proportion classified as not having disease and the

  9. Impairing loyalty: corporate responsibility for clinical misadventure.

    PubMed

    Kipnis, Kenneth

    2011-09-01

    A medical device manufacturer pays a surgeon to demonstrate a novel medical instrument in a live broadcast to an audience of specialists in another city. The surgical patient is unaware of the broadcast and unaware of the doctor's relationship with the manufacturer. It turns out that the patient required a different surgical approach to her condition-one that would not have allowed a demonstration of the instrument--and she later dies. The paper is an exploration of whether the manufacturer shares, along with the doctor, responsibility for the death of the patient. Three arguments for corporate responsibility are considered; two are criticized and the third is offered as sound. PMID:21877962

  10. Predicting MCI outcome with clinically available MRI and CSF biomarkers

    PubMed Central

    Heister, D.; Brewer, J.B.; Magda, S.; Blennow, K.

    2011-01-01

    Objective: To determine the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI). Methods: We stratified 192 MCI participants into positive and negative risk groups on the basis of 1) degree of learning impairment on the Rey Auditory Verbal Learning Test; 2) medial temporal atrophy, quantified from Food and Drug Administration–approved software for automated vMRI analysis; and 3) CSF biomarker levels. We also stratified participants based on combinations of risk factors. We computed Cox proportional hazards models, controlling for age, to assess 3-year risk of converting to AD as a function of risk group and used Kaplan-Meier analyses to determine median survival times. Results: When risk factors were examined separately, individuals testing positive showed significantly higher risk of converting to AD than individuals testing negative (hazard ratios [HR] 1.8–4.1). The joint presence of any 2 risk factors substantially increased risk, with the combination of greater learning impairment and increased atrophy associated with highest risk (HR 29.0): 85% of patients with both risk factors converted to AD within 3 years, vs 5% of those with neither. The presence of medial temporal atrophy was associated with shortest median dementia-free survival (15 months). Conclusions: Incorporating quantitative assessment of learning ability along with vMRI or CSF biomarkers in the clinical workup of MCI can provide critical information on risk of imminent conversion to AD. PMID:21998317

  11. An IL28B Genotype-Based Clinical Prediction Model for Treatment of Chronic Hepatitis C

    PubMed Central

    O'Brien, Thomas R.; Everhart, James E.; Morgan, Timothy R.; Lok, Anna S.; Chung, Raymond T.; Shao, Yongwu; Shiffman, Mitchell L.; Dotrang, Myhanh; Sninsky, John J.; Bonkovsky, Herbert L.; Pfeiffer, Ruth M.

    2011-01-01

    Background Genetic variation in IL28B and other factors are associated with sustained virological response (SVR) after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC). Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables. Methods HALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR) and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC). Results Among 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p<.0001); the model also included HCV RNA (log10 IU/ml), AST∶ALT ratio, Ishak fibrosis score and prior ribavirin treatment. For this model AUC was 78.5%, compared to 73.0% for a model restricted to the four clinical predictors and 60.0% for a model restricted to IL28B genotype (p<0.001). Subjects with a predicted probability of SVR <10% had an observed SVR rate of 3.8%; subjects with a predicted probability >10% (43.3% of subjects) had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study. Conclusion A clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC. PMID:21760886

  12. Prediction and control of neural responses to pulsatile electrical stimulation

    NASA Astrophysics Data System (ADS)

    Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

    2012-04-01

    This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

  13. Microsatellite Instability Predicts Clinical Outcome in Radiation-Treated Endometrioid Endometrial Cancer

    SciTech Connect

    Bilbao, Cristina; Lara, Pedro Carlos; Ramirez, Raquel; Henriquez-Hernandez, Luis Alberto; Rodriguez, German; Falcon, Orlando; Leon, Laureano; Perucho, Manuel

    2010-01-15

    Purpose: To elucidate whether microsatellite instability (MSI) predicts clinical outcome in radiation-treated endometrioid endometrial cancer (EEC). Methods and Materials: A consecutive series of 93 patients with EEC treated with extrafascial hysterectomy and postoperative radiotherapy was studied. The median clinical follow-up of patients was 138 months, with a maximum of 232 months. Five quasimonomorphic mononucleotide markers (BAT-25, BAT-26, NR21, NR24, and NR27) were used for MSI classification. Results: Twenty-five patients (22%) were classified as MSI. Both in the whole series and in early stages (I and II), univariate analysis showed a significant association between MSI and poorer 10-year local disease-free survival, disease-free survival, and cancer-specific survival. In multivariate analysis, MSI was excluded from the final regression model in the whole series, but in early stages MSI provided additional significant predictive information independent of traditional prognostic and predictive factors (age, stage, grade, and vascular invasion) for disease-free survival (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.01-10.49; p = 0.048) and cancer-specific survival (HR 4.20, 95% CI 1.23-14.35; p = 0.022) and was marginally significant for local disease-free survival (HR 3.54, 95% CI 0.93-13.46; p = 0.064). Conclusions: These results suggest that MSI may predict radiotherapy response in early-stage EEC.

  14. Clinical applications of the human brainstem responses to auditory stimuli

    NASA Technical Reports Server (NTRS)

    Galambos, R.; Hecox, K.

    1975-01-01

    A technique utilizing the frequency following response (FFR) (obtained by auditory stimulation, whereby the stimulus frequency and duration are mirror-imaged in the resulting brainwaves) as a clinical tool for hearing disorders in humans of all ages is presented. Various medical studies are discussed to support the clinical value of the technique. The discovery and origin of the FFR and another significant brainstem auditory response involved in studying the eighth nerve is also discussed.

  15. 42 CFR 493.1457 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 5 2010-10-01 2010-10-01 false Standard; Clinical consultant responsibilities. 493... HUMAN SERVICES (CONTINUED) STANDARDS AND CERTIFICATION LABORATORY REQUIREMENTS Personnel for Nonwaived Testing Laboratories Performing High Complexity Testing § 493.1457 Standard; Clinical...

  16. 42 CFR 493.1419 - Standard; Clinical consultant responsibilities.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... clinical consultation to the laboratory's clients; (b) Be available to assist the laboratory's clients in... 42 Public Health 5 2010-10-01 2010-10-01 false Standard; Clinical consultant responsibilities. 493... HUMAN SERVICES (CONTINUED) STANDARDS AND CERTIFICATION LABORATORY REQUIREMENTS Personnel for...

  17. Multifractal analysis of tumour microscopic images in the prediction of breast cancer chemotherapy response.

    PubMed

    Vasiljevic, Jelena; Pribic, Jelena; Kanjer, Ksenija; Jonakowski, Wojtek; Sopta, Jelena; Nikolic-Vukosavljevic, Dragica; Radulovic, Marko

    2015-10-01

    Due to the individual heterogeneity, highly accurate predictors of chemotherapy response in invasive breast cancer are needed for effective chemotherapeutic management. However, predictive molecular determinants for conventional chemotherapy are only emerging and still incorporate a high degree of predictive variability. Based on such pressing need for predictive performance improvement, we explored the value of pre-therapy tumour histology image analysis to predict chemotherapy response. Fractal analysis was applied to hematoxylin/eosin stained archival tissue of diagnostic biopsies derived from 106 patients diagnosed with invasive breast cancer. The tissue was obtained prior to neoadjuvant anthracycline-based chemotherapy and patients were subsequently divided into three groups according to their actual chemotherapy response: partial pathological response (pPR), pathological complete response (pCR) and progressive/stable disease (PD/SD). It was shown that multifractal analysis of breast tumour tissue prior to chemotherapy indeed has the capacity to distinguish between histological images of the different chemotherapy responder groups with accuracies of 91.4% for pPR, 82.9% for pCR and 82.1% for PD/SD. F(α)max was identified as the most important predictive parameter. It represents the maximum of multifractal spectrum f(α), where α is the Hölder's exponent. This is the first study investigating the predictive value of multifractal analysis as a simple and cost-effective tool to predict the chemotherapy response. Improvements in chemotherapy prediction provide clinical benefit by enabling more optimal chemotherapy decisions, thus directly affecting the quality of life and survival. PMID:26303582

  18. An Oracle: Antituberculosis Pharmacokinetics-Pharmacodynamics, Clinical Correlation, and Clinical Trial Simulations To Predict the Future▿

    PubMed Central

    Pasipanodya, Jotam; Gumbo, Tawanda

    2011-01-01

    Antimicrobial pharmacokinetic-pharmacodynamic (PK/PD) science and clinical trial simulations have not been adequately applied to the design of doses and dose schedules of antituberculosis regimens because many researchers are skeptical about their clinical applicability. We compared findings of preclinical PK/PD studies of current first-line antituberculosis drugs to findings from several clinical publications that included microbiologic outcome and pharmacokinetic data or had a dose-scheduling design. Without exception, the antimicrobial PK/PD parameters linked to optimal effect were similar in preclinical models and in tuberculosis patients. Thus, exposure-effect relationships derived in the preclinical models can be used in the design of optimal antituberculosis doses, by incorporating population pharmacokinetics of the drugs and MIC distributions in Monte Carlo simulations. When this has been performed, doses and dose schedules of rifampin, isoniazid, pyrazinamide, and moxifloxacin with the potential to shorten antituberculosis therapy have been identified. In addition, different susceptibility breakpoints than those in current use have been identified. These steps outline a more rational approach than that of current methods for designing regimens and predicting outcome so that both new and older antituberculosis agents can shorten therapy duration. PMID:20937778

  19. Variability in Multisensory Responses Predicts the Self-Space.

    PubMed

    Serino, Andrea

    2016-03-01

    Our brains distinguish between stimuli that are close enough to interact with our bodies and those that are further away by generating a multisensory representation of space near the self, termed peripersonal space. Recent findings show that variability in neuronal response to audio-tactile stimuli predicts the location of the peripersonal space boundary at the individual level. PMID:26833067

  20. Predicting the response of populations to environmental change

    SciTech Connect

    Ives, A.R.

    1995-04-01

    When subject to long-term directional environmental perturbations, changes in population densities depend on the positive and negative feedbacks operating through interactions within and among species in a community. This paper develops techniques to predict the long-term responses of population densities to environmental changes using data on short-term population fluctuations driven by short-term environmental variability. In addition to giving quantitative predictions, the techniques also reveal how different qualitative patterns of species interactions either buffer or accentuate population responses to environmental trends. All of the predictions are based on regression coefficients extracted from time series data, and they can therefore be applied with a minimum of mathematical and statistical gymnastics. 48 refs., 10 figs., 4 tabs.

  1. Does Level of Response to SI Joint Block Predict Response to SI Joint Fusion?

    PubMed Central

    Cher, Daniel; Whang, Peter G.; Frank, Clay; Sembrano, Jonathan

    2016-01-01

    Background The degree of pain relief required to diagnose sacroiliac joint (SIJ) dysfunction following a diagnostic SIJ block (SIJB) is not known. No gold standard exists. Response to definitive (i.e., accepted as effective) treatment might be a reference standard. Methods Subgroup analysis of 320 subjects enrolled in two prospective multicenter trials evaluating SIJ fusion (SIJF) in patients with SIJ dysfunction diagnosed by history, physical exam and standardized diagnostic SIJB. A 50% reduction in pain at 30 or 60 minutes following SIJB was considered confirmatory. The absolute and percentage improvements in Visual Analog Scale (VAS) SIJ pain and Oswestry Disability Index (ODI) scores at 6 and 12 months after SIJF were correlated with the average acute improvement in SIJ pain with SIJB. Results The average pain reduction during the first hour after SIJB was 79.3%. Six months after SIJF, the overall mean VAS SIJ pain reduction was 50.9 points (0-100 scale) and the mean ODI reduction was 24.6 points. Reductions at 12 months after SIJF were similar. Examined in multiple ways, improvements in SIJ pain and ODI at 6 and 12 months did not correlate with SIJB findings. Conclusions The degree of pain improvement during SIJB did not predict improvements in pain or ODI scores after SIJF. A 50% SIJB threshold resulted in excellent post-SIJF responses. Using overly stringent selection criteria (i.e. 75%) to qualify patients for SIJF has no basis in evidence and would withhold a beneficial procedure from a substantial number of patients with SIJ dysfunction. Level of Evidence Level 1. Clinical Relevance The degree of pain improvement during an SIJ block does not predict the degree of pain improvement after SIJ fusion. PMID:26913224

  2. Simplifying clinical use of the genetic risk prediction model BRCAPRO.

    PubMed

    Biswas, Swati; Atienza, Philamer; Chipman, Jonathan; Hughes, Kevin; Barrera, Angelica M Gutierrez; Amos, Christopher I; Arun, Banu; Parmigiani, Giovanni

    2013-06-01

    Health care providers need simple tools to identify patients at genetic risk of breast and ovarian cancers. Genetic risk prediction models such as BRCAPRO could fill this gap if incorporated into Electronic Medical Records or other Health Information Technology solutions. However, BRCAPRO requires potentially extensive information on the counselee and her family history. Thus, it may be useful to provide simplified version(s) of BRCAPRO for use in settings that do not require exhaustive genetic counseling. We explore four simplified versions of BRCAPRO, each using less complete information than the original model. BRCAPROLYTE uses information on affected relatives only up to second degree. It is in clinical use but has not been evaluated. BRCAPROLYTE-Plus extends BRCAPROLYTE by imputing the ages of unaffected relatives. BRCAPROLYTE-Simple reduces the data collection burden associated with BRCAPROLYTE and BRCAPROLYTE-Plus by not collecting the family structure. BRCAPRO-1Degree only uses first-degree affected relatives. We use data on 2,713 individuals from seven sites of the Cancer Genetics Network and MD Anderson Cancer Center to compare these simplified tools with the Family History Assessment Tool (FHAT) and BRCAPRO, with the latter serving as the benchmark. BRCAPROLYTE retains high discrimination; however, because it ignores information on unaffected relatives, it overestimates carrier probabilities. BRCAPROLYTE-Plus and BRCAPROLYTE-Simple provide better calibration than BRCAPROLYTE, so they have higher specificity for similar values of sensitivity. BRCAPROLYTE-Plus performs slightly better than BRCAPROLYTE-Simple. The Areas Under the ROC curve are 0.783 (BRCAPRO), 0.763 (BRCAPROLYTE), 0.772 (BRCAPROLYTE-Plus), 0.773 (BRCAPROLYTE-Simple), 0.728 (BRCAPRO-1Degree), and 0.745 (FHAT). The simpler versions, especially BRCAPROLYTE-Plus and BRCAPROLYTE-Simple, lead to only modest loss in overall discrimination compared to BRCAPRO in this dataset. Thus, we conclude that

  3. The Pupillary Orienting Response Predicts Adaptive Behavioral Adjustment after Errors

    PubMed Central

    Murphy, Peter R.; van Moort, Marianne L.; Nieuwenhuis, Sander

    2016-01-01

    Reaction time (RT) is commonly observed to slow down after an error. This post-error slowing (PES) has been thought to arise from the strategic adoption of a more cautious response mode following deployment of cognitive control. Recently, an alternative account has suggested that PES results from interference due to an error-evoked orienting response. We investigated whether error-related orienting may in fact be a pre-cursor to adaptive post-error behavioral adjustment when the orienting response resolves before subsequent trial onset. We measured pupil dilation, a prototypical measure of autonomic orienting, during performance of a choice RT task with long inter-stimulus intervals, and found that the trial-by-trial magnitude of the error-evoked pupil response positively predicted both PES magnitude and the likelihood that the following response would be correct. These combined findings suggest that the magnitude of the error-related orienting response predicts an adaptive change of response strategy following errors, and thereby promote a reconciliation of the orienting and adaptive control accounts of PES. PMID:27010472

  4. Predicting aquifer response time for application in catchment modeling.

    PubMed

    Walker, Glen R; Gilfedder, Mat; Dawes, Warrick R; Rassam, David W

    2015-01-01

    It is well established that changes in catchment land use can lead to significant impacts on water resources. Where land-use changes increase evapotranspiration there is a resultant decrease in groundwater recharge, which in turn decreases groundwater discharge to streams. The response time of changes in groundwater discharge to a change in recharge is a key aspect of predicting impacts of land-use change on catchment water yield. Predicting these impacts across the large catchments relevant to water resource planning can require the estimation of groundwater response times from hundreds of aquifers. At this scale, detailed site-specific measured data are often absent, and available spatial data are limited. While numerical models can be applied, there is little advantage if there are no detailed data to parameterize them. Simple analytical methods are useful in this situation, as they allow the variability in groundwater response to be incorporated into catchment hydrological models, with minimal modeling overhead. This paper describes an analytical model which has been developed to capture some of the features of real, sloping aquifer systems. The derived groundwater response timescale can be used to parameterize a groundwater discharge function, allowing groundwater response to be predicted in relation to different broad catchment characteristics at a level of complexity which matches the available data. The results from the analytical model are compared to published field data and numerical model results, and provide an approach with broad application to inform water resource planning in other large, data-scarce catchments. PMID:24842053

  5. Prediction of the mortality dose-response relationship in man

    SciTech Connect

    Morris, M.D.; Jones, T.D.

    1987-01-01

    Based upon an extensive data base including 100 separate animal studies, an estimate of the mortality dose-response relationship due to continuous photon radiation is predicted for 70 kg man. The model used in this prediction exercise includes fixed terms accounting for effects of body weight and dose rate, and random terms accounting for inter- and intra-species variation and experimental error. Point predictions and 95% prediction intervals are given for the LD/sub 05/, LD/sub 10/, LD/sub 25/, LD/sub 50/, LD/sub 75/, LD/sub 90/, and LD/sub 95/, for dose rates ranging from 1 to 50 R/min. 6 refs., 5 tabs.

  6. Etiology of Cellulitis and Clinical Prediction of Streptococcal Disease: A Prospective Study

    PubMed Central

    Bruun, Trond; Oppegaard, Oddvar; Kittang, Bård R.; Mylvaganam, Haima; Langeland, Nina; Skrede, Steinar

    2016-01-01

    Background. The importance of bacteria other than group A streptococci (GAS) in different clinical presentations of cellulitis is unclear, commonly leading to treatment with broad-spectrum antibiotics. The aim of this study was to describe the etiological and clinical spectrum of cellulitis and identify clinical features predicting streptococcal etiology. Methods. We prospectively enrolled 216 patients hospitalized with cellulitis. Clinical details were registered. Bacterial culture was performed from blood, cutaneous or subcutaneous tissue, and/or swabs from skin lesions. Paired serum samples were analyzed for anti-streptolysin O and anti-deoxyribonuclease B antibodies. Results. Serology or blood or tissue culture confirmed β-hemolytic streptococcal (BHS) etiology in 72% (146 of 203) of cases. An additional 13% (27 of 203) of cases had probable BHS infection, indicated by penicillin response or BHS cultured from skin swabs. β-hemolytic streptococcal etiology was predominant in all clinical subgroups, including patients without sharply demarcated erythema. β-hemolytic group C or G streptococci (GCS/GGS) were more commonly isolated than GAS (36 vs 22 cases). This predominance was found in the lower extremity infections. Group C or G streptococci in swabs were associated with seropositivity just as often as GAS. Staphylococcus aureus was cultured from swabs as a single pathogen in 24 cases, 14 (64%) of which had confirmed BHS etiology. Individual BHS-associated clinical characteristics increased the likelihood of confirmed BHS disease only slightly; positive likelihood ratios did not exceed 2.1. Conclusions. β-hemolytic streptococci were the dominating cause of cellulitis in all clinical subgroups and among cases with S aureus in cutaneous swabs. Group C or G streptococci were more frequently detected than GAS. No single clinical feature substantially increased the probability of confirmed BHS etiology. PMID:26734653

  7. Simplified Analysis Model for Predicting Pyroshock Responses on Composite Panel

    NASA Astrophysics Data System (ADS)

    Iwasa, Takashi; Shi, Qinzhong

    A simplified analysis model based on the frequency response analysis and the wave propagation analysis was established for predicting Shock Response Spectrum (SRS) on the composite panel subjected to pyroshock loadings. The complex composite panel was modeled as an isotropic single layer panel defined in NASA Lewis Method. Through the conductance of an impact excitation test on a composite panel with no equipment mounted on, it was presented that the simplified analysis model could estimate the SRS as well as the acceleration peak values in both near and far field in an accurate way. In addition, through the simulation for actual pyroshock tests on an actual satellite system, the simplified analysis model was proved to be applicable in predicting the actual pyroshock responses, while bringing forth several technical issues to estimate the pyroshock test specifications in early design stages.

  8. Clinical Prediction of Fall Risk and White Matter Abnormalities

    PubMed Central

    Koo, Bang-Bon; Bergethon, Peter; Qiu, Wei Qiao; Scott, Tammy; Hussain, Mohammed; Rosenberg, Irwin; Caplan, Louis R.; Bhadelia, Rafeeque A.

    2015-01-01

    Background The Tinetti scale is a simple clinical tool designed to predict risk of falling by focusing on gait and stance impairment in elderly persons. Gait impairment is also associated with white matter (WM) abnormalities. Objective To test the hypothesis that elderly subjects at risk for falling, as determined by the Tinetti scale, have specific patterns of WM abnormalities on diffusion tensor imaging. Design, Setting, and Patients Community-based cohort of 125 homebound elderly individuals. Main Outcome Measures Diffusion tensor imaging scans were analyzed using tract-based spatial statistics analysis to determine the location of WM abnormalities in subjects with Tinetti scale scores of 25 or higher (without risk of falls) and lower than 25 (with risk of falls). Multivariate linear least squares correlation analysis was performed to determine the association between Tinetti scale scores and local fractional anisotropy values on each skeletal voxel controlling for possible confounders. Results In subjects with risk of falls (Tinetti scale score <25), clusters of abnormal WM were seen in the medial frontal and parietal subcortical pathways, genu and splenium of corpus callosum, posterior cingulum, prefrontal and orbitofrontal pathways, and longitudinal pathways that connect frontal-parietal-temporal lobes. Among these abnormalities, those in medial frontal and parietal subcortical pathways correlated with Mini-Mental State Examination scores, while the other locations were unrelated to these scores. Conclusions Elderly individuals at risk for falls as determined by the Tinetti scale have WM abnormalities in specific locations on diffusion tensor imaging, some of which correlate with cognitive function scores. PMID:22332181

  9. Apoptosis and other immune biomarkers predict influenza vaccine responsiveness

    PubMed Central

    Furman, David; Jojic, Vladimir; Kidd, Brian; Shen-Orr, Shai; Price, Jordan; Jarrell, Justin; Tse, Tiffany; Huang, Huang; Lund, Peder; Maecker, Holden T; Utz, Paul J; Dekker, Cornelia L; Koller, Daphne; Davis, Mark M

    2013-01-01

    Despite the importance of the immune system in many diseases, there are currently no objective benchmarks of immunological health. In an effort to identifying such markers, we used influenza vaccination in 30 young (20–30 years) and 59 older subjects (60 to >89 years) as models for strong and weak immune responses, respectively, and assayed their serological responses to influenza strains as well as a wide variety of other parameters, including gene expression, antibodies to hemagglutinin peptides, serum cytokines, cell subset phenotypes and in vitro cytokine stimulation. Using machine learning, we identified nine variables that predict the antibody response with 84% accuracy. Two of these variables are involved in apoptosis, which positively associated with the response to vaccination and was confirmed to be a contributor to vaccine responsiveness in mice. The identification of these biomarkers provides new insights into what immune features may be most important for immune health. PMID:23591775

  10. Infants, mothers, and dyadic contributions to stability and prediction of social stress response at 6 months.

    PubMed

    Provenzi, Livio; Olson, Karen L; Montirosso, Rosario; Tronick, Ed

    2016-01-01

    The study of infants' interactive style and social stress response to repeated stress exposures is of great interest for developmental and clinical psychologists. Stable maternal and dyadic behavior is critical to sustain infants' development of an adaptive social stress response, but the association between infants' interactive style and social stress response has received scant attention in previous literature. In the present article, overtime stability of infant, maternal, and dyadic behaviors was measured across 2 social stress (i.e., Face-to-Face Still-Face, FFSF) exposures, separated by 15 days. Moreover, infant, maternal, and dyadic behaviors were simultaneously assessed as predictors of infants' social stress to both FFSF exposures. Eighty-one mother-infant dyads underwent the FFSF twice, at 6 months (Exposure 1: the first social stress) and at 6 months and 15 days (Exposure 2: repeated social stress). Infant and mother behavior and dyadic synchrony were microanalytically coded. Overall, individual behavioral stability emerged between FFSF exposures. Infants' response to the first stress was predicted by infant behavior during Exposure 1 Play. Infants' response to the repeated social stress was predicted by infants' response to the first exposure to the Still-Face and by infants' behavior and dyadic synchrony during Exposure 2 Play. Findings reveal stability for individual, but not for dyadic, behavior between 2 social stress exposures at 6 months. Infants' response to repeated social stress was predicted by infants' earlier stress response, infants' own behavior in play, and dyadic synchrony. No predictive effects of maternal behavior were found. Insights for research and clinical work are discussed. PMID:26569560

  11. A novel embryonic plasticity gene signature that predicts metastatic competence and clinical outcome

    PubMed Central

    Soundararajan, Rama; Paranjape, Anurag N.; Barsan, Valentin; Chang, Jeffrey T.; Mani, Sendurai A.

    2015-01-01

    Currently, very few prognosticators accurately predict metastasis in cancer patients. In order to complete the metastatic cascade and successfully colonize distant sites, carcinoma cells undergo dynamic epithelial-mesenchymal-transition (EMT) and its reversal, mesenchymal-epithelial-transition (MET). While EMT-centric signatures correlate with response to therapy, they are unable to predict metastatic outcome. One reason is due to the wide range of transient phenotypes required for a tumor cell to disseminate and recreate a similar histology at distant sites. Since such dynamic cellular processes are also seen during embryo development (epithelial-like epiblast cells undergo transient EMT to generate the mesoderm, which eventually redifferentiates into epithelial tissues by MET), we sought to utilize this unique and highly conserved property of cellular plasticity to predict metastasis. Here we present the identification of a novel prognostic gene expression signature derived from mouse embryonic day 6.5 that is representative of extensive cellular plasticity, and predicts metastatic competence in human breast tumor cells. This signature may thus complement conventional clinical parameters to offer accurate prediction for outcome among multiple classes of breast cancer patients. PMID:26123483

  12. Prediction of peak pressure from clinical and radiological measurements in patients with diabetes

    PubMed Central

    Guldemond, Nick A; Leffers, Pieter; Walenkamp, Geert HIM; Schaper, Nicolaas C; Sanders, Antal P; Nieman, Fred HM; van Rhijn, Lodewijk W

    2008-01-01

    Background Various structural and functional factors of foot function have been associated with high local plantar pressures. The therapist focuses on these features which are thought to be responsible for plantar ulceration in patients with diabetes. Risk assessment of the diabetic foot would be made easier if locally elevated plantar pressure could be indicated with a minimum set of clinical measures. Methods Ninety three patients were evaluated through vascular, orthopaedic, neurological and radiological assessment. A pressure platform was used to quantify the barefoot peak pressure for six forefoot regions: big toe (BT) and metatarsals one (MT-1) to five (MT-5). Stepwise regression modelling was performed to determine which set of the clinical and radiological measures explained most variability in local barefoot plantar peak pressure in each of the six forefoot regions. Comprehensive models were computed with independent variables from the clinical and radiological measurements. The difference between the actual plantar pressure and the predicted value was examined through Bland-Altman analysis. Results Forefoot pressures were significant higher in patients with neuropathy, compared to patients without neuropathy for the whole forefoot, the MT-1 region and the MT-5 region (respectively 138 kPa, 173 kPa and 88 kPa higher: mean difference). The clinical models explained up to 39 percent of the variance in local peak pressures. Callus formation and toe deformity were identified as relevant clinical predictors for all forefoot regions. Regression models with radiological variables explained about 26 percent of the variance in local peak pressures. For most regions the combination of clinical and radiological variables resulted in a higher explained variance. The Bland and Altman analysis showed a major discrepancy between the predicted and the actual peak pressure values. Conclusion At best, clinical and radiological measurements could only explain about 34

  13. Rorschach Prediction of Success in Clinical Training: A Second Look

    ERIC Educational Resources Information Center

    Carlson, Rae

    1969-01-01

    A Rorschach Index based on ego-psychological conceptualization of an optimal personality picture predicted for 155 trainees was compared with predictions from the Miller Analogies Test (MAT) and the Strong Vocational Interest Blank (SVIB). The Index predicted success and failure more effectively. (Author)

  14. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Cancer.gov

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  15. Modeling HIV Immune Response and Validation with Clinical Data

    PubMed Central

    Banks, H. T.; Davidian, M.; Hu, Shuhua; Kepler, Grace M.; Rosenberg, E.S.

    2009-01-01

    A system of ordinary differential equations is formulated to describe the pathogenesis of HIV infection, wherein certain features that have been shown to be important by recent experimental research are incorporated in the model. These include the role of CD4+ memory cells that serve as a major reservoir of latently infected cells, a critical role for T-helper cells in the generation of CD8 memory cells capable of efficient recall response, and stimulation by antigens other than HIV. A stability analysis illustrates the capability of this model in admitting multiple locally asymptotically stable (locally a.s.) off-treatment equilibria. We show that this more biologically-detailed model can exhibit the phenomenon of transient viremia experienced by some patients on therapy with viral load levels suppressed below the detection limit. We also show that the loss of CD4+ T-cell help in the generation of CD8+ memory cells leads to larger peak values for the viral load during transient viremia. Censored clinical data is used to obtain parameter estimates. We demonstrate that using a reduced set of 16 free parameters, obtained by fixing some parameters at their population averages, the model provides reasonable fits to the patient data and, moreover, that it exhibits good predictive capability. We further show that parameter values obtained for most clinical patients do not admit multiple locally a.s off-treatment equilibria. This suggests that treatment to move from a high viral load equilibrium state to an equilibrium state with a lower (or zero) viral load is not possible for these patients. PMID:19495424

  16. Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

    SciTech Connect

    Folkvord, Sigurd; Flatmark, Kjersti; Dueland, Svein

    2010-10-01

    Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatment as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.

  17. Baseline Brain Activity Predicts Response to Neuromodulatory Pain Treatment

    PubMed Central

    Jensen, Mark P.; Sherlin, Leslie H.; Fregni, Felipe; Gianas, Ann; Howe, Jon D.; Hakimian, Shahin

    2015-01-01

    Objectives The objective of this study was to examine the associations between baseline electroencephalogram (EEG)-assessed brain oscillations and subsequent response to four neuromodulatory treatments. Based on available research, we hypothesized that baseline theta oscillations would prospectively predict response to hypnotic analgesia. Analyses involving other oscillations and the other treatments (meditation, neurofeedback, and both active and sham transcranial direct current stimulation) were viewed as exploratory, given the lack of previous research examining brain oscillations as predictors of response to these other treatments. Design Randomized controlled study of single sessions of four neuromodulatory pain treatments and a control procedure. Methods Thirty individuals with spinal cord injury and chronic pain had their EEG recorded before each session of four active treatments (hypnosis, meditation, EEG biofeedback, transcranial direct current stimulation) and a control procedure (sham transcranial direct stimulation). Results As hypothesized, more presession theta power was associated with greater response to hypnotic analgesia. In exploratory analyses, we found that less baseline alpha power predicted pain reduction with meditation. Conclusions The findings support the idea that different patients respond to different pain treatments and that between-person treatment response differences are related to brain states as measured by EEG. The results have implications for the possibility of enhancing pain treatment response by either 1) better patient/treatment matching or 2) influencing brain activity before treatment is initiated in order to prepare patients to respond. Research is needed to replicate and confirm the findings in additional samples of individuals with chronic pain. PMID:25287554

  18. Predicting the shock compression response of heterogeneous powder mixtures

    NASA Astrophysics Data System (ADS)

    Fredenburg, D. A.; Thadhani, N. N.

    2013-06-01

    A model framework for predicting the dynamic shock-compression response of heterogeneous powder mixtures using readily obtained measurements from quasi-static tests is presented. Low-strain-rate compression data are first analyzed to determine the region of the bulk response over which particle rearrangement does not contribute to compaction. This region is then fit to determine the densification modulus of the mixture, σD, an newly defined parameter describing the resistance of the mixture to yielding. The measured densification modulus, reflective of the diverse yielding phenomena that occur at the meso-scale, is implemented into a rate-independent formulation of the P-α model, which is combined with an isobaric equation of state to predict the low and high stress dynamic compression response of heterogeneous powder mixtures. The framework is applied to two metal + metal-oxide (thermite) powder mixtures, and good agreement between the model and experiment is obtained for all mixtures at stresses near and above those required to reach full density. At lower stresses, rate-dependencies of the constituents, and specifically those of the matrix constituent, determine the ability of the model to predict the measured response in the incomplete compaction regime.

  19. Prediction of heart rate response to conclusion of the spontaneous breathing trial by fluctuation dissipation theory

    NASA Astrophysics Data System (ADS)

    Chen, Man; Niestemski, Liang Ren; Prevost, Robert; McRae, Michael; Cholleti, Sharath; Najarro, Gabriel; Buchman, Timothy G.; Deem, Michael W.

    2013-02-01

    The non-equilibrium fluctuation dissipation theorem is applied to predict how critically ill patients respond to treatment, based upon data currently collected by standard hospital monitoring devices. This framework is demonstrated on a common procedure in critical care: the spontaneous breathing trial. It is shown that the responses of groups of similar patients to the spontaneous breathing trial can be predicted by the non-equilibrium fluctuation dissipation approach. This mathematical framework, when fully formed and applied to other clinical interventions, may serve as part of the basis for personalized critical care.

  20. Operating Outpatient Clinics in 1990.

    ERIC Educational Resources Information Center

    Bohannan, Harry M.

    1984-01-01

    The future of dental school clinic operations is discussed including change within dental education, factors influencing change, and some predicted changes. Fundamental change can be predicted in educational philosophy, responsibility for clinical care, clinic facilities, clinic operation, and faculty. (MLW)

  1. Genetic studies of DRD4 and clinical response to neuroleptic medications

    SciTech Connect

    Kennedy, J.L.; Petronis, A.; Gao, J.

    1994-09-01

    Clozapine is an atypical antipsychotic drug that, like most other medications, is effective for some people and not for others. This variable response across individuals is likely significantly determined by genetic factors. An important candidate gene to investigate in clozapine response is the dopamine D4 receptor gene (DRD4). The D4 receptor has a higher affinity for clozapine than any of the other dopamine receptors. Furthermore, recent work by our consortium has shown a remarkable level of variability in the part of the gene coding for the third cytoplasmic loop. We have also identified polymorphisms in the upstream 5{prime} putative regulatory region and at two other sites. These polymorphisms were typed in a group of treatment-resistant schizophrenia subjects who were subsequently placed on clozapine (n = 60). In a logistic regression analysis, we compared genotype at the DRD4 polymorphism to response versus non-response to clozapine. Neither the exon-III nor any of the 5{prime} polymorphisms alone significantly predicted response; however, when the information from these polymorphisms was combined, more predictive power was obtained. In a correspondence analysis of the four DRD4 polymorphisms vs. response, we were able to predict 76% of the variance in response. Refinement of the analyses will include assessment of subfactors involved in clinical response phenotype and incorporation of the debrisoquine metabolizing locus (CYP2D6) into the prediction algorithm.

  2. Expression of Estrogen-Related Gene Markers in Breast Cancer Tissue Predicts Aromatase Inhibitor Responsiveness

    PubMed Central

    Moy, Irene; Lin, Zhihong; Rademaker, Alfred W.; Reierstad, Scott; Khan, Seema A.; Bulun, Serdar E.

    2013-01-01

    Aromatase inhibitors (AIs) are the most effective class of drugs in the endocrine treatment of breast cancer, with an approximate 50% treatment response rate. Our objective was to determine whether intratumoral expression levels of estrogen-related genes are predictive of AI responsiveness in postmenopausal women with breast cancer. Primary breast carcinomas were obtained from 112 women who received AI therapy after failing adjuvant tamoxifen therapy and developing recurrent breast cancer. Tumor ERα and PR protein expression were analyzed by immunohistochemistry (IHC). Messenger RNA (mRNA) levels of 5 estrogen-related genes–AKR1C3, aromatase, ERα, and 2 estradiol/ERα target genes, BRCA1 and PR–were measured by real-time PCR. Tumor protein and mRNA levels were compared with breast cancer progression rates to determine predictive accuracy. Responsiveness to AI therapy–defined as the combined complete response, partial response, and stable disease rates for at least 6 months–was 51%; rates were 56% in ERα-IHC-positive and 14% in ERα-IHC-negative tumors. Levels of ERα, PR, or BRCA1 mRNA were independently predictive for responsiveness to AI. In cross-validated analyses, a combined measurement of tumor ERα and PR mRNA levels yielded a more superior specificity (36%) and identical sensitivity (96%) to the current clinical practice (ERα/PR-IHC). In patients with ERα/PR-IHC-negative tumors, analysis of mRNA expression revealed either non-significant trends or statistically significant positive predictive values for AI responsiveness. In conclusion, expression levels of estrogen-related mRNAs are predictive for AI responsiveness in postmenopausal women with breast cancer, and mRNA expression analysis may improve patient selection. PMID:24223121

  3. Mothers' labeling responses to infants' gestures predict vocabulary outcomes.

    PubMed

    Olson, Janet; Masur, Elise Frank

    2015-11-01

    Twenty-nine infants aged 1;1 and their mothers were videotaped while interacting with toys for 18 minutes. Six experimental stimuli were presented to elicit infant communicative bids in two communicative intent contexts - proto-declarative and proto-imperative. Mothers' verbal responses to infants' gestural and non-gestural communicative bids were coded for object and action labels. Relations between maternal labeling responses and infants' vocabularies at 1;1 and 1;5 were examined. Mothers' labeling responses to infants' gestural communicative bids were concurrently and predictively related to infants' vocabularies, whereas responses to non-gestural communicative bids were not. Mothers' object labeling following gestures in the proto-declarative context mediated the association from infants' gesturing in the proto-declarative context to concurrent noun lexicons and was the strongest predictor of subsequent noun lexicons. Mothers' action labeling after infants' gestural bids in the proto-imperative context predicted infants' acquisition of action words at 1;5. Findings show that mothers' responsive labeling explain specific relations between infants' gestures and their vocabulary development. PMID:25643656

  4. Creating and evaluating genetic tests predictive of drug response

    PubMed Central

    Weiss, Scott T.; McLeod, Howard L.; Flockhart, David A.; Dolan, M. Eileen; Benowitz, Neal L.; Johnson, Julie A.; Ratain, Mark J.; Giacomini, Kathleen M.

    2009-01-01

    A key goal of pharmacogenetics — the use of genetic variation to elucidate inter-individual variation in drug treatment response — is to aid the development of predictive genetic tests that could maximize drug efficacy and minimize drug toxicity. The completion of the Human Genome Project and the associated HapMap Project, together with advances in technologies for investigating genetic variation, have greatly advanced the potential to develop such tests; however, many challenges remain. With the aim of helping to address some of these challenges, this article discusses the steps that are involved in the development of predictive tests for drug treatment response based on genetic variation, and factors that influence the development and performance of these tests. PMID:18587383

  5. Predictions of F-111 TACT aircraft buffet response

    NASA Technical Reports Server (NTRS)

    Cunningham, Atlee M., Jr.; Coe, Charles F.

    1990-01-01

    A summary is presented for the prediction method development and correlations of predicted response with flight test measurements. The prediction method was based on refinements to the method described by Cunningham. One improvement made use of direct time integration of the correlated fluctuating pressure data to obtain buffet excitation for the various modes of interest. Another improvement incorporated a hybrid technique for scaling measured wind tunnel damping data to full-scale for the modes of interest. A third improvement made use of the diagonalized form of the fully coupled equations of motion. Finally, a mechanism was described for explaining an apparent coupling between the aircraft wing torsion modes and shock induced trailing edge separation that led to very high wing motion on the aircraft that was not observed on the wind tunnel model.

  6. Predictive coding of music--brain responses to rhythmic incongruity.

    PubMed

    Vuust, Peter; Ostergaard, Leif; Pallesen, Karen Johanne; Bailey, Christopher; Roepstorff, Andreas

    2009-01-01

    During the last decades, models of music processing in the brain have mainly discussed the specificity of brain modules involved in processing different musical components. We argue that predictive coding offers an explanatory framework for functional integration in musical processing. Further, we provide empirical evidence for such a network in the analysis of event-related MEG-components to rhythmic incongruence in the context of strong metric anticipation. This is seen in a mismatch negativity (MMNm) and a subsequent P3am component, which have the properties of an error term and a subsequent evaluation in a predictive coding framework. There were both quantitative and qualitative differences in the evoked responses in expert jazz musicians compared with rhythmically unskilled non-musicians. We propose that these differences trace a functional adaptation and/or a genetic pre-disposition in experts which allows for a more precise rhythmic prediction. PMID:19054506

  7. Predicting Response to Hormonal Therapy and Survival in Men with Hormone Sensitive Metastatic Prostate Cancer

    PubMed Central

    Grivas, Petros D.; Robins, Diane M.; Hussain, Maha

    2014-01-01

    Androgen deprivation is the cornerstone of the management of metastatic prostate cancer. Despite several decades of clinical experience with this therapy there are no standard predictive biomarkers for response. Although several candidate genetic, hormonal, inflammatory, biochemical, metabolic biomarkers have been suggested as potential predictors of response and outcome, none has been prospectively validated nor has proven clinical utility to date. There is significant heterogeneity in the depth and duration of hormonal response and in the natural history of advanced disease; therefore to better optimize/individualize therapy and for future development, identification of biomarkers is critical. This review summarizes the current data on the role of several candidate biomarkers that have been evaluated in the advanced/metastatic disease setting. PMID:22705096

  8. Use of generalised additive models to categorise continuous variables in clinical prediction

    PubMed Central

    2013-01-01

    Background In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. Methods We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high- and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. Results The three-category proposal for the respiratory rate was ≤ 20;(20,24];> 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically

  9. Predictive Value of IL-8 for Sepsis and Severe Infections after Burn Injury - A Clinical Study

    PubMed Central

    Kraft, Robert; Herndon, David N; Finnerty, Celeste C; Cox, Robert A; Song, Juquan; Jeschke, Marc G

    2014-01-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring post-burn inflammation is of paramount importance but so far there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As IL-8 is a major mediator for inflammatory responses, the aim of our study was to determine whether IL-8 expression can be used to predict post-burn sepsis, infections, and mortality other outcomes post-burn. Plasma cytokines, acute phase proteins, constitutive proteins, and hormones were analyzed during the first 60 days post injury from 468 pediatric burn patients. Demographics and clinical outcome variables (length of stay, infection, sepsis, multiorgan failure (MOF), and mortality were recorded. A cut-off level for IL-8 was determined using receiver operating characteristic (ROC) analysis. Statistical significance is set at (p<0.05). ROC analysis identified a cut-off level of 234 pg/ml for IL-8 for survival. Patients were grouped according to their average IL-8 levels relative to this cut off and stratified into high (H) (n=133) and low (L) (n=335) groups. In the L group, regression analysis revealed a significant predictive value of IL-8 to percent of total body surface area (TBSA) burned and incidence of MOF (p<0.001). In the H group IL-8 levels were able to predict sepsis (p<0.002). In the H group, elevated IL-8 was associated with increased inflammatory and acute phase responses compared to the L group (p<0.05). High levels of IL-8 correlated with increased MOF, sepsis, and mortality. These data suggest that serum levels of IL-8 may be a valid biomarker for monitoring sepsis, infections, and mortality in burn patients. PMID:25514427

  10. Can quantitative sensory testing predict responses to analgesic treatment?

    PubMed

    Grosen, K; Fischer, I W D; Olesen, A E; Drewes, A M

    2013-10-01

    The role of quantitative sensory testing (QST) in prediction of analgesic effect in humans is scarcely investigated. This updated review assesses the effectiveness in predicting analgesic effects in healthy volunteers, surgical patients and patients with chronic pain. A systematic review of English written, peer-reviewed articles was conducted using PubMed and Embase (1980-2013). Additional studies were identified by chain searching. Search terms included 'quantitative sensory testing', 'sensory testing' and 'analgesics'. Studies on the relationship between QST and response to analgesic treatment in human adults were included. Appraisal of the methodological quality of the included studies was based on evaluative criteria for prognostic studies. Fourteen studies (including 720 individuals) met the inclusion criteria. Significant correlations were observed between responses to analgesics and several QST parameters including (1) heat pain threshold in experimental human pain, (2) electrical and heat pain thresholds, pressure pain tolerance and suprathreshold heat pain in surgical patients, and (3) electrical and heat pain threshold and conditioned pain modulation in patients with chronic pain. Heterogeneity among studies was observed especially with regard to application of QST and type and use of analgesics. Although promising, the current evidence is not sufficiently robust to recommend the use of any specific QST parameter in predicting analgesic response. Future studies should focus on a range of different experimental pain modalities rather than a single static pain stimulation paradigm. PMID:23658120

  11. Prediction of the Chemoreflex Gain by Common Clinical Variables in Heart Failure

    PubMed Central

    Mirizzi, Gianluca; Giannoni, Alberto; Ripoli, Andrea; Iudice, Giovanni; Bramanti, Francesca; Emdin, Michele; Passino, Claudio

    2016-01-01

    Background Peripheral and central chemoreflex sensitivity, assessed by the hypoxic or hypercapnic ventilatory response (HVR and HCVR, respectively), is enhanced in heart failure (HF) patients, is involved in the pathophysiology of the disease, and is under investigation as a potential therapeutic target. Chemoreflex sensitivity assessment is however demanding and, therefore, not easily applicable in the clinical setting. We aimed at evaluating whether common clinical variables, broadly obtained by routine clinical and instrumental evaluation, could predict increased HVR and HCVR. Methods and results 191 patients with systolic HF (left ventricular ejection fraction—LVEF—<50%) underwent chemoreflex assessment by rebreathing technique to assess HVR and HCVR. All patients underwent clinical and neurohormonal evaluation, comprising: echocardiogram, cardiopulmonary exercise test (CPET), daytime cardiorespiratory monitoring for breathing pattern evaluation. Regarding HVR, multivariate penalized logistic regression, Bayesian Model Averaging (BMA) logistic regression and random forest analysis identified, as predictors, the presence of periodic breathing and increased slope of the relation between ventilation and carbon dioxide production (VE/VCO2) during exercise. Again, the above-mentioned statistical tools identified as HCVR predictors plasma levels of N-terminal fragment of proBNP and VE/VCO2 slope. Conclusions In HF patients, the simple assessment of breathing pattern, alongside with ventilatory efficiency during exercise and natriuretic peptides levels identifies a subset of patients presenting with increased chemoreflex sensitivity to either hypoxia or hypercapnia. PMID:27099934

  12. Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

    NASA Astrophysics Data System (ADS)

    Marasco, Addolorata; de Paris, Alessandro; Migliore, Michele

    2016-04-01

    The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration.

  13. Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

    PubMed Central

    Marasco, Addolorata; De Paris, Alessandro; Migliore, Michele

    2016-01-01

    The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration. PMID:27053070

  14. Prognostic prediction through biclustering-based classification of clinical gene expression time series.

    PubMed

    Carreiro, André V; Anunciação, Orlando; Carriço, João A; Madeira, Sara C

    2011-01-01

    The constant drive towards a more personalized medicine led to an increasing interest in temporal gene expression analyzes. It is now broadly accepted that considering a temporal perpective represents a great advantage to better understand disease progression and treatment results at a molecular level. In this context, biclustering algorithms emerged as an important tool to discover local expression patterns in biomedical applications, and CCC-Biclustering arose as an efficient algorithm relying on the temporal nature of data to identify all maximal temporal patterns in gene expression time series. In this work, CCC-Biclustering was integrated in new biclustering-based classifiers for prognostic prediction. As case study we analyzed multiple gene expression time series in order to classify the response of Multiple Sclerosis patients to the standard treatment with Interferon-β, to which nearly half of the patients reveal a negative response. In this scenario, using an effective predictive model of a patient's response would avoid useless and possibly harmful therapies for the non-responder group. The results revealed interesting potentialities to be further explored in classification problems involving other (clinical) time series. PMID:21926438

  15. Predictive factors associated with hepatitis C antiviral therapy response.

    PubMed

    Cavalcante, Lourianne Nascimento; Lyra, André Castro

    2015-06-28

    Hepatitis C virus (HCV) infection may lead to significant liver injury, and viral, environmental, host, immunologic and genetic factors may contribute to the differences in the disease expression and treatment response. In the early 2000s, dual therapy using a combination of pegylated interferon plus ribavirin (PR) became the standard of care for HCV treatment. In this PR era, predictive factors of therapy response related to virus and host have been identified. In 2010/2011, therapeutic regimens for HCV genotype 1 patients were modified, and the addition of NS3/4a protease inhibitors (boceprevir or telaprevir) to dual therapy increased the effectiveness and chances of sustained virologic response (SVR). Nevertheless, the first-generation triple therapy is associated with many adverse events, some of which are serious and associated with death, particularly in cirrhotic patients. This led to the need to identify viral and host predictive factors that might influence the SVR rate to triple therapy and avoid unnecessary exposure to these drugs. Over the past four years, hepatitis C treatment has been rapidly changing with the development of new therapies and other developments. Currently, with the more recent generations of pangenotipic antiviral therapies, there have been higher sustained virologic rates, and prognostic factors may not have the same importance and strength as before. Nonetheless, some variables may still be consistent with the low rates of non-response with regimens that include sofosbuvir, daclatasvir and ledipasvir. In this manuscript, we review the predictive factors of therapy response across the different treatment regimens over the last decade including the new antiviral drugs. PMID:26140082

  16. Depression and anxiety predict sex-specific cortisol responses to interpersonal stress.

    PubMed

    Powers, Sally I; Laurent, Heidemarie K; Gunlicks-Stoessel, Meredith; Balaban, Susan; Bent, Eileen

    2016-07-01

    Clinical theories posit interpersonal stress as an important factor in the emergence and exacerbation of depression and anxiety, while neuroendocrine research confirms the association of these syndromes with dysregulation in a major stress response system, the hypothalamic-pituitary-adrenal (HPA) axis. However, the proposal that depression and anxiety symptoms and diagnoses are associated with problematic HPA responses to close relationship stress has not been directly tested. We examined 196 heterosexual dating couples' depression and anxiety symptoms and diagnoses, assessed with questionnaires and diagnostic interviews, in relation to cortisol responses to discussion of an unresolved relationship conflict. Participants provided seven salivary samples in anticipation of and directly following the discussion, and throughout an hour-long recovery period, which were assayed for cortisol. Multilevel models of the HPA response predicted by symptoms or diagnoses showed that women's depressive symptoms predicted attenuated cortisol levels, with a flatter response curve. In contrast, men's depression symptoms and women's anxiety symptoms and diagnoses predicted higher cortisol levels. These findings highlight the importance of examining sex differences in responses to interpersonal stressors for understanding HPA dysregulation in internalizing psychopathology. PMID:27107208

  17. Physicians' Professionally Responsible Power: A Core Concept of Clinical Ethics.

    PubMed

    McCullough, Laurence B

    2016-02-01

    The gathering of power unto themselves by physicians, a process supported by evidence-based practice, clinical guidelines, licensure, organizational culture, and other social factors, makes the ethics of power--the legitimation of physicians' power--a core concept of clinical ethics. In the absence of legitimation, the physician's power over patients becomes problematic, even predatory. As has occurred in previous issues of the Journal, the papers in the 2016 clinical ethics issue bear on the professionally responsible deployment of power by physicians. This introduction explores themes of physicians' power in papers from an international group of authors who address autonomy and trust, the virtues of perinatal hospice, conjoined twins in ethics and law, addiction and autonomy in clinical research on addicting substances, euthanasia of patients with dementia in Belgium, and a pragmatic approach to clinical futility. PMID:26671961

  18. Lipocalin-2 as an Infection-Related Biomarker to Predict Clinical Outcome in Ischemic Stroke

    PubMed Central

    Hochmeister, Sonja; Engel, Odilo; Adzemovic, Milena Z.; Pekar, Thomas; Kendlbacher, Paul; Zeitelhofer, Manuel; Haindl, Michaela; Meisel, Andreas; Fazekas, Franz; Seifert-Held, Thomas

    2016-01-01

    Objectives From previous data in animal models of cerebral ischemia, lipocalin-2 (LCN2), a protein related to neutrophil function and cellular iron homeostasis, is supposed to have a value as a biomarker in ischemic stroke patients. Therefore, we examined LCN2 expression in the ischemic brain in an animal model and measured plasma levels of LCN2 in ischemic stroke patients. Methods In the mouse model of transient middle cerebral artery occlusion (tMCAO), LCN2 expression in the brain was analyzed by immunohistochemistry and correlated to cellular nonheme iron deposition up to 42 days after tMCAO. In human stroke patients, plasma levels of LCN2 were determined one week after ischemic stroke. In addition to established predictive parameters such as age, National Institutes of Health Stroke Scale and thrombolytic therapy, LCN2 was included into linear logistic regression modeling to predict clinical outcome at 90 days after stroke. Results Immunohistochemistry revealed expression of LCN2 in the mouse brain already at one day following tMCAO, and the amount of LCN2 subsequently increased with a maximum at 2 weeks after tMCAO. Accumulation of cellular nonheme iron was detectable one week post tMCAO and continued to increase. In ischemic stroke patients, higher plasma levels of LCN2 were associated with a worse clinical outcome at 90 days and with the occurrence of post-stroke infections. Conclusions LCN2 is expressed in the ischemic brain after temporary experimental ischemia and paralleled by the accumulation of cellular nonheme iron. Plasma levels of LCN2 measured in patients one week after ischemic stroke contribute to the prediction of clinical outcome at 90 days and reflect the systemic response to post-stroke infections. PMID:27152948

  19. Can traits predict the competitive response of herbaceous Mediterranean species?

    NASA Astrophysics Data System (ADS)

    Navas, Marie-Laure; Moreau-Richard, Julie

    2005-03-01

    This study tested whether (i) functional traits, measured on individually grown plants, can be used to predict species response to competition; (ii) species competitive response depends on the standing biomass of neighbouring vegetation. Nine herbaceous Mediterranean species (targets) were grown as isolated plants or in mixture with one of three grasses (neighbours) differing in RGR, in pots during 4 months. Ten traits of targets, related to plant size, resource acquisition and conservation ability, and the above-ground biomass of neighbours were measured. Species with large basal area when individually grown were least suppressed by competition. No relationship was found between species competitive response and other traits measured on plants grown in isolation, including height and RGR. This result suggests that plant basal area could be used to predict the competitive ability of species in herbaceous communities. The competitive response of targets varied with the standing biomass of neighbours: it decreased with increasing neighbour biomass for low-productive mixtures, then reached a minimal value as neighbour biomass became larger, whatever the identity of neighbours. The implications of this relationship are discussed.

  20. Baseline Factors Predicting Placebo Response to Treatment in Children and Adolescents With Autism Spectrum Disorders

    PubMed Central

    King, Bryan H.; Dukes, Kimberly; Donnelly, Craig L.; Sikich, Linmarie; McCracken, James T.; Scahill, Lawrence; Hollander, Eric; Bregman, Joel D.; Anagnostou, Evdokia; Robinson, Fay; Sullivan, Lisa; Hirtz, Deborah

    2016-01-01

    IMPORTANCE The finding of factors that differentially predict the likelihood of response to placebo over that of an active drug could have a significant impact on study design in this population. OBJECTIVE To identify possible nonspecific, baseline predictors of response to intervention in a large randomized clinical trial of children and adolescents with autism spectrum disorders. DESIGN, SETTING, AND PARTICIPANTS Randomized clinical trial of citalopram hydrobromide for children and adolescents with autism spectrum disorders and prominent repetitive behavior. Baseline data at study entry were examined with respect to final outcome to determine if response predictors could be identified. A total of 149 children and adolescents 5 to 17 years of age (mean [SD] age, 9.4 [3.1] years) from 6 academic centers were randomly assigned to citalopram (n = 73) or placebo (n = 76). Participants had autistic disorder, Asperger syndrome, or pervasive developmental disorder, not otherwise specified; had illness severity ratings that were moderate or more than moderate on the Clinical Global Impression–Severity scale; and scored moderate or more than moderate on compulsive behaviors measured with the modified Children’s Yale-Brown Obsessive-Compulsive Scale. INTERVENTIONS Twelve weeks of treatment with citalopram (10 mg/5 mL) or placebo. The mean (SD) maximum dose of citalopram was 16.5 (6.5) mg by mouth daily (maximum dose, 20 mg/d). MAIN OUTCOMES AND MEASURES A positive response was defined as having a score of at least much improved on the Clinical Global Impression–Improvement scale at week 12. Baseline measures included demographic (sex, age, weight, and pubertal status), clinical, and family measures. Clinical variables included baseline illness severity ratings (the Aberrant Behavior Checklist, the Child and Adolescent Symptom Inventory, the Vineland Adaptive Behavior Scales, the Repetitive Behavior Scale–Revised, and the Children’s Yale-Brown Obsessive

  1. Nonlinear random response prediction using MSC/NASTRAN

    NASA Technical Reports Server (NTRS)

    Robinson, J. H.; Chiang, C. K.; Rizzi, S. A.

    1993-01-01

    An equivalent linearization technique was incorporated into MSC/NASTRAN to predict the nonlinear random response of structures by means of Direct Matrix Abstract Programming (DMAP) modifications and inclusion of the nonlinear differential stiffness module inside the iteration loop. An iterative process was used to determine the rms displacements. Numerical results obtained for validation on simple plates and beams are in good agreement with existing solutions in both the linear and linearized regions. The versatility of the implementation will enable the analyst to determine the nonlinear random responses for complex structures under combined loads. The thermo-acoustic response of a hexagonal thermal protection system panel is used to highlight some of the features of the program.

  2. Validation of a Deterministic Vibroacoustic Response Prediction Model

    NASA Technical Reports Server (NTRS)

    Caimi, Raoul E.; Margasahayam, Ravi

    1997-01-01

    This report documents the recently completed effort involving validation of a deterministic theory for the random vibration problem of predicting the response of launch pad structures in the low-frequency range (0 to 50 hertz). Use of the Statistical Energy Analysis (SEA) methods is not suitable in this range. Measurements of launch-induced acoustic loads and subsequent structural response were made on a cantilever beam structure placed in close proximity (200 feet) to the launch pad. Innovative ways of characterizing random, nonstationary, non-Gaussian acoustics are used for the development of a structure's excitation model. Extremely good correlation was obtained between analytically computed responses and those measured on the cantilever beam. Additional tests are recommended to bound the problem to account for variations in launch trajectory and inclination.

  3. A metabolomics approach for predicting the response to neoadjuvant chemotherapy in cervical cancer patients.

    PubMed

    Hou, Yan; Yin, Mingzhu; Sun, Fengyu; Zhang, Tao; Zhou, Xiaohua; Li, Huiyan; Zheng, Jian; Chen, Xiuwei; Li, Cong; Ning, Xiaoming; Lou, Ge; Li, Kang

    2014-08-01

    Cervical cancer is a clinical and pathological heterogeneity disease, which requires different types of treatments and leads to a variety of outcomes. In clinical practice, only some patients benefit from chemotherapy treatment. Identifying patients who will be responsive to chemotherapy could increase their survival time, which has important implications in personalized treatment and outcomes, while identifying non-responders may reduce the likelihood for these patients to receive ineffective treatment and thereby enable them to receive other potentially effective treatments. Plasma metabolite profiling was performed in this study to identify the potential biomarkers that could predict the response to neoadjuvant chemotherapy (NACT) for cervical cancer patients. The metabolic profiles of plasma from 38 cervical cancer patients with a complete, partial and non-response to NACT were studied using a combination of liquid chromatography coupled with mass spectrometry (LC/MS) and multivariate analysis methods. L-Valine and L-tryptophan were finally identified and verified as the potential biomarkers. A prediction model constructed with L-valine and L-tryptophan correctly identified approximately 80% of patients who were non-response to chemotherapy and 87% of patients who were had a pathologically complete response to chemotherapy. The model has an excellent discriminant performance with an AUC of 0.9407. These results show promise for larger studies that could produce more personalized treatment protocols for cervical cancer patients. PMID:24865370

  4. Prediction of HR/BP response to the spontaneous breathing trial by fluctuation dissipation theory

    NASA Astrophysics Data System (ADS)

    Chen, Man

    2014-03-01

    We applied the non-equilibrium fluctuation dissipation theorem to predict how critically-ill patients respond to treatment, based on both heart rate data and blood pressure data collected by standard hospital monitoring devices. The non-equilibrium fluctuation dissipation theorem relates the response of a system to a perturbation to the fluctuations in the stationary state of the system. It is shown that the response of patients to a standard procedure performed on patients, the spontaneous breathing trial (SBT), can be predicted by the non-equilibrium fluctuation dissipation approach. We classify patients into different groups according to the patients' characteristics. For each patient group, we extend the fluctuation dissipation theorem to predict interactions between blood pressure and beat-to-beat dynamics of heart rate in response to a perturbation (SBT), We also extract the form of the perturbation function directly from the physiological data, which may help to reduce the prediction error. We note this method is not limited to the analysis of the heart rate dynamics, but also can be applied to analyze the response of other physiological signals to other clinical interventions.

  5. Pressure Ulcers in Adults: Prediction and Prevention. Clinical Practice Guideline Number 3.

    ERIC Educational Resources Information Center

    Agency for Health Care Policy and Research (DHHS/PHS), Rockville, MD.

    This package includes a clinical practice guideline, quick reference guide for clinicians, and patient's guide to predicting and preventing pressure ulcers in adults. The clinical practice guideline includes the following: overview of the incidence and prevalence of pressure ulcers; clinical practice guideline (introduction, risk assessment tools…

  6. Prediction of individual response to antidepressants and antipsychotics: an integrated concept

    PubMed Central

    Preskorn, Sheldon H.

    2014-01-01

    In both clinical trials and daily practice, there can be substantial inter- and even intraindividual variability in response—whether beneficial or adverse—to antidepressants and antipsychotic medications. So far, no tools have become available to predict the outcome of these treatments in specific patients. This is because the causes of such variability are often not known, and when they are, there is no way of predicting the effects of their various potential combinations in an individual. Given this background, this paper presents a conceptual framework for understanding known factors and their combinations so that eventually clinicians can better predict what medication(s) to select and at what dose they can optimize the outcome for a given individual. This framework is flexible enough to be readily adaptable as new information becomes available. The causes of variation in patient response are grouped into four categories: (i) genetics; (ii) age; (iii) disease; and (iv) environment (internal). Four cases of increasing complexity are used to illustrate the applicability of this framework in a clinically relevant way In addition, this paper reviews tools that the clinician can use to assess for and quantify such inter- and intraindividual variability. With the information gained, treatment can be adjusted to compensate for such variability, in order to optimize outcome. Finally, the limitations of existing antidepressant and antipsychotic therapy and the way they reduce current ability to predict response is discussed. PMID:25733958

  7. Brachial artery peak velocity variation to predict fluid responsiveness in mechanically ventilated patients

    PubMed Central

    2009-01-01

    Introduction Although several parameters have been proposed to predict the hemodynamic response to fluid expansion in critically ill patients, most of them are invasive or require the use of special monitoring devices. The aim of this study is to determine whether noninvasive evaluation of respiratory variation of brachial artery peak velocity flow measured using Doppler ultrasound could predict fluid responsiveness in mechanically ventilated patients. Methods We conducted a prospective clinical research in a 17-bed multidisciplinary ICU and included 38 mechanically ventilated patients for whom fluid administration was planned due to the presence of acute circulatory failure. Volume expansion (VE) was performed with 500 mL of a synthetic colloid. Patients were classified as responders if stroke volume index (SVi) increased ≥ 15% after VE. The respiratory variation in Vpeakbrach (ΔVpeakbrach) was calculated as the difference between maximum and minimum values of Vpeakbrach over a single respiratory cycle, divided by the mean of the two values and expressed as a percentage. Radial arterial pressure variation (ΔPPrad) and stroke volume variation measured using the FloTrac/Vigileo system (ΔSVVigileo), were also calculated. Results VE increased SVi by ≥ 15% in 19 patients (responders). At baseline, ΔVpeakbrach, ΔPPrad and ΔSVVigileo were significantly higher in responder than nonresponder patients [14 vs 8%; 18 vs. 5%; 13 vs 8%; P < 0.0001, respectively). A ΔVpeakbrach value >10% predicted fluid responsiveness with a sensitivity of 74% and a specificity of 95%. A ΔPPrad value >10% and a ΔSVVigileo >11% predicted volume responsiveness with a sensitivity of 95% and 79%, and a specificity of 95% and 89%, respectively. Conclusions Respiratory variations in brachial artery peak velocity could be a feasible tool for the noninvasive assessment of fluid responsiveness in patients with mechanical ventilatory support and acute circulatory failure. Trial Registration

  8. Pain catastrophizing predicts poor response to topical analgesics in patients with neuropathic pain

    PubMed Central

    Mankovsky, Tsipora; Lynch, Mary E; Clark, AJ; Sawynok, J; Sullivan, Michael JL

    2012-01-01

    BACKGROUND: Previous research suggests that high levels of pain catastrophizing might predict poorer response to pharmacological interventions for neuropathic pain. OBJECTIVE: The present study sought to examine the clinical relevance of the relation between catastrophizing and analgesic response in individuals with neuropathic pain. Clinically meaningful reductions were defined in terms of the magnitude of reductions in pain through the course of treatment, and in terms of the number of patients whose end-of-treatment pain ratings were below 4/10. METHODS: Patients (n=82) with neuropathic pain conditions completed a measure of pain catastrophizing at the beginning of a three-week trial examining the efficacy of topical analgesics for neuropathic pain. RESULTS: Consistent with previous research, high scores on the measure of pain catastrophizing prospectively predicted poorer response to treatment. Fewer catastrophizers than noncatastrophizers showed moderate (≥2 points) or substantial reductions in pain ratings through the course of treatment. Fewer catastrophizers than noncatastrophizers achieved end-of-treatment pain ratings below 4/10. CONCLUSIONS: The results of the present study suggest that the development of brief interventions specifically targeting catastrophic thinking might be useful for enhancing the effects of pharmacological interventions for neuropathic pain. Furthermore, failure to account for the level of catastrophizing might contribute to null findings in clinical trials of analgesic medication. PMID:22518362

  9. Dissociation predicts treatment response in eye-movement desensitization and reprocessing for posttraumatic stress disorder.

    PubMed

    Bae, Hwallip; Kim, Daeho; Park, Yong Chon

    2016-01-01

    Using clinical data from a specialized trauma clinic, this study investigated pretreatment clinical factors predicting response to eye-movement desensitization and reprocessing (EMDR) among adult patients diagnosed with posttraumatic stress disorder (PTSD). Participants were evaluated using the Clinician-Administered PTSD Scale (CAPS), the Symptom Checklist-90-Revised, the Beck Depression Inventory, and the Dissociative Experiences Scale before treatment and were reassessed using the CAPS after treatment and at 6-month follow-up. A total of 69 patients underwent an average of 4 sessions of EMDR, and 60 (87%) completed the posttreatment evaluation, including 8 participants who terminated treatment prematurely. Intent-to-treat analysis revealed that 39 (65%) of the 60 patients were classified as responders and 21 (35%) as nonresponders when response was defined as more than a 30% decrease in total CAPS score. The nonresponders had higher levels of dissociation (depersonalization and derealization) and numbing symptoms, but other PTSD symptoms, such as avoidance, hyperarousal, and intrusion, were not significantly different. The number of psychiatric comorbidities was also associated with treatment nonresponse. The final logistic regression model yielded 2 significant variables: dissociation (p < .001) and more than 2 comorbidities compared to none (p < .05). These results indicate that complex symptom patterns in PTSD may predict treatment response and support the inclusion of the dissociative subtype of PTSD in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. PMID:26156867

  10. Using biomarkers to predict treatment response in major depressive disorder: evidence from past and present studies

    PubMed Central

    Thase, Michael E.

    2014-01-01

    Major depressive disorder (MDD) is a heterogeneous condition with a variable response to a wide range of treatments. Despite intensive efforts, no biomarker has been identified to date that can reliably predict response or non-response to any form of treatment, nor has one been identified that can be used to identify those at high risk of developing treatment-resistant depression (ie, non-response to a sequence of treatments delivered for adequate duration and intensity). This manuscript reviews some past areas of research that have proved informative, such as studies using indexes of hypercortisolism or sleep disturbance, and more recent research findings using measures of inflammation and different indicators of regional cortical activation to predict treatment response. It is concluded that, although no method has yet been demonstrated to be sufficiently accurate to be applied in clinical practice, progress has been made. It thus seems likely that—at some point in the not-too-distant future—it will be possible to prospectively identify, at least for some MDD patients, the likelihood of response or non-response to cognitive therapy or various antidepressant medications. PMID:25733957

  11. Prognostic and Predictive Biomarkers in Colorectal Cancer. From the Preclinical Setting to Clinical Practice.

    PubMed

    Maurel, Joan; Postigo, Antonio

    2015-01-01

    Colorectal cancer (CRC) is the second largest cause of cancer mortality in Western countries, mostly due to metastasis. Understanding the natural history and prognostic factors in patients with metastatic CRC (mCRC) is essential for the optimal design of clinical trials. The main prognostic factors currently used in clinical practice are related to tumor behavior (e.g., white blood counts, levels of lactate dehydrogenase, levels of alkaline phosphatase) disease extension (e.g., presence of extrahepatic spread, number of organs affected) and general functional status (e.g., performance status as defined by the Eastern Cooperative Oncology Group). However, these parameters are not always sufficient to establish appropriate therapeutic strategies. First-line therapy in mCRC combines conventional chemotherapy (CHT) (e.g., FOLFOX, FOLFIRI, CAPOX) with a number of agents targeted to specific signaling pathways (TA) (e.g., panitumumab and cetuximab for cases KRAS/NRAS WT, and bevacizumab). Although the response rate to this combination regime exceeds 50%, progression of the disease is almost universal and only less than 10% of patients are free of disease at 2 years. Current clinical trials with second and third line therapy include new TA, such as tyrosin-kinase receptors inhibitors (MET, HER2, IGF-1R), inhibitors of BRAF, MEK, PI3K, AKT, mTORC, NOTCH and JAK1/JAK2, immunotherapy modulators and check point inhibitors (anti-PD-L1 and anti- PD1). Despite the identification of multiple prognostic and predictive biomarkers and signatures, it is still unclear how expression of many of these biomarkers is modulated by CHT and/or TA, thus potentially affecting response to treatment. In this review we analyzed how certain biomarkers in tumor cells and microenvironment influence the response to new TA and immune-therapies strategies in mCRC pre-treated patients. PMID:26452385

  12. MGMT expression predicts response to temozolomide in pancreatic neuroendocrine tumors.

    PubMed

    Cros, J; Hentic, O; Rebours, V; Zappa, M; Gille, N; Theou-Anton, N; Vernerey, D; Maire, F; Lévy, P; Bedossa, P; Paradis, V; Hammel, P; Ruszniewski, P; Couvelard, A

    2016-08-01

    Temozolomide (TEM) showed encouraging results in well-differentiated pancreatic neuroendocrine tumors (WDPNETs). Low O(6)-methylguanine-DNA methyltransferase (MGMT) expression and MGMT promoter methylation within tumors correlate with a better outcome under TEM-based chemotherapy in glioblastoma. We aimed to assess whether MGMT expression and MGMT promoter methylation could help predict the efficacy of TEM-based chemotherapy in patients with WDPNET. Consecutive patients with progressive WDPNET and/or liver involvement over 50% who received TEM between 2006 and 2012 were retrospectively studied. Tumor response was assessed according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 guidelines. Nuclear expression of MGMT was assessed by immunochemistry (H-score, 0-300) and MGMT promoter methylation by pyrosequencing. Forty-three patients (21 men, 58years (27-84)) with grade 1 WDPNET (n=6) or 2 (n=36) were analyzed. Objective response, stable disease, and progression rates were seen in 17 patients (39.5%), 18 patients (41.9%), and 8 patients (18.6%), respectively. Low MGMT expression (≤50) was associated with radiological objective response (P=0.04) and better progression-free survival (PFS) (HR=0.35 (0.15-0.81), P=0.01). Disease control rate at 18months of treatment remained satisfying with an MGMT score up to 100 (74%) but dropped with a higher expression. High MGMT promoter methylation was associated with a low MGMT expression and longer PFS (HR=0.37 (0.29-1.08), P=0.05). Low MGMT score (≤50) appears to predict an objective tumor response, whereas an intermediate MGMT score (50-100) seems to be associated with prolonged stable disease. PMID:27353036

  13. Does stroke location predict walk speed response to gait rehabilitation?

    PubMed Central

    Jones, P. Simon; Pomeroy, Valerie M.; Wang, Jasmine; Schlaug, Gottfried; Tulasi Marrapu, S.; Geva, Sharon; Rowe, Philip J.; Chandler, Elizabeth; Kerr, Andrew

    2015-01-01

    Abstract Objectives Recovery of independent ambulation after stroke is a major goal. However, which rehabilitation regimen best benefits each individual is unknown and decisions are currently made on a subjective basis. Predictors of response to specific therapies would guide the type of therapy most appropriate for each patient. Although lesion topography is a strong predictor of upper limb response, walking involves more distributed functions. Earlier studies that assessed the cortico‐spinal tract (CST) were negative, suggesting other structures may be important. Experimental Design: The relationship between lesion topography and response of walking speed to standard rehabilitation was assessed in 50 adult‐onset patients using both volumetric measurement of CST lesion load and voxel‐based lesion–symptom mapping (VLSM) to assess non‐CST structures. Two functional mobility scales, the functional ambulation category (FAC) and the modified rivermead mobility index (MRMI) were also administered. Performance measures were obtained both at entry into the study (3–42 days post‐stroke) and at the end of a 6‐week course of therapy. Baseline score, age, time since stroke onset and white matter hyperintensities score were included as nuisance covariates in regression models. Principal Observations: CST damage independently predicted response to therapy for FAC and MRMI, but not for walk speed. However, using VLSM the latter was predicted by damage to the putamen, insula, external capsule and neighbouring white matter. Conclusions Walk speed response to rehabilitation was affected by damage involving the putamen and neighbouring structures but not the CST, while the latter had modest but significant impact on everyday functions of general mobility and gait. Hum Brain Mapp 37:689–703, 2016. © 2015 Wiley Periodicals, Inc. PMID:26621010

  14. Predicting cardiovascular disease from handgrip strength: the potential clinical implications.

    PubMed

    Leong, Darryl P; Teo, Koon K

    2015-12-01

    The measurement of handgrip strength has proven prognostic value for all-cause and cardiovascular death, and for cardiovascular disease. It is also an important indicator of frailty and vulnerability. The measurement of handgrip strength may be most useful in the context of multi-morbidity, where it may be a simple tool to identify the individual at particularly high risk of adverse outcomes, who may benefit from closer clinical attention. Research into dietary, exercise, and pharmacologic strategies to increase muscle strength is ongoing. Important issues will be the feasibility and sustainability of increases in muscle strength, and whether these increases translate into clinical benefit. PMID:26513210

  15. Uncontrolled diabetes predicts poor response to novel antiandrogens.

    PubMed

    Karantanos, Theodoros; Karanika, Styliani; Gignac, Gretchen

    2016-09-01

    Metabolic abnormalities including hyperglycemia and hyperlipidemia have been associated with worse prognosis of prostate cancer (PCa), but there are limited data regarding their impact on the prognosis of castrate-resistant prostate cancer (CRPC) and the response of novel antiandrogens, namely abiraterone acetate (AA) and enzalutamide. Retrospective analysis of 61 patients with CRPC on AA or enzalutamide, treated at the Boston Medical Center, was performed. We evaluated hemoglobin A1c (HbA1c), HDL, LDL, Triglycerides and BMI within 2months before the initiation of treatment with AA or enzalutamide and progression-free survival (PFS) under this treatment. Regression analysis and analysis of variance were used to evaluate the data. HbA1c levels were found to predict adversely the PFS on the novel agents (df (1, 37), P=0.00, R(2)=0.40, coeff=-3.28). The Kaplan-Meier analysis showed that there is significant difference in survival between the HbA1c 4.7-5.9% compared with patients with HbA1c 7.8-11.6% (6.72±1.3months, log rank test P<0.0001) LDL (P=0.07), HDL (P=0.14), and triglycerides (P=0.33) were not found to predict PFS. BMI predicted PFS positively (df (1.59), P=0.02, R(2)=0.09, coeff=0.03), but not independently of HbA1c (P=0.07). No significant implications of social and family history, previous chemotherapy regimen, and Gleason score with PFS were found. Multiple markers of patients' health state were not associated with HbA1c values. Uncontrolled diabetes can predict for poor response of CRPC patients to AA and enzalutamide determining PFS under this treatment. Elevated BMI can positively affect PFS at this stage of disease. PMID:27515296

  16. Human arm posture prediction in response to isometric endpoint forces.

    PubMed

    Davoudabadi Farahani, Saeed; Andersen, Michael Skipper; de Zee, Mark; Rasmussen, John

    2015-11-26

    The ability to predict the musculoskeletal response to external loads has multiple applications for the design of machines with a human interface and for the prediction of outcomes of musculoskeletal interventions. In this study, we applied an inverse-inverse dynamics technique to investigate its ability to predict arm posture in response to isometric hand forces. For each subject, we made a three-dimensional musculoskeletal model using the AnyBody Modelling System (AMS). Then, we had each subject-specific model hold a weight anteriorly to the right shoulder joint at a distance of half of the arm length. We selected the glenohumeral abduction angle (GHAA) as the only free parameter. Subsequently, we used inverse-inverse dynamics to find the optimal GHAA that minimised a performance criterion with physiological constraints. In this study, we investigated the performance of two different objective functions: summation of squared muscle activity (SSMA) and summation of squared normalised joint torques (SSNJT). To validate the simulation results, arm posture responses to different isometric downward hand forces were measured for six healthy male subjects. Five trials were performed for each loading condition. The results showed that, with an increase in hand load, there was a reduced GHAA in all subjects. Another interesting finding was that self-selected postures for lighter tasks varied more than postures for heavier tasks for all subjects. To understand this, we investigated the curvature of the objective function as a function of the load and observed an increased curvature with increased load. This may explain the reduced intra-subject variations observed for increasing loads. PMID:26482735

  17. The Prediction of Academic and Clinical Performance in Medical School

    ERIC Educational Resources Information Center

    Gough, Harrison G.; Hall, Wallace B.

    1975-01-01

    A study of medical student performance showed the clinical performance factor more or less unpredictable from aptitude and premedical academic achievement indices while the academic performance factor was forecast with acceptable accuracy by equations based on the Medical College Admissions Test and premedical grade point average. (JT)

  18. FTO predicts weight regain in the Look AHEAD clinical trial

    Technology Transfer Automated Retrieval System (TEKTRAN)

    BACKGROUND: Genome-wide association studies have provided new insights into the genetic factors that contribute to the development of obesity. We hypothesized that these genetic markers would also predict magnitude of weight loss and weight regain after initial weight loss. METHODS: Established obe...

  19. Analysis of Factors that Predict Clinical Performance in Medical School

    ERIC Educational Resources Information Center

    White, Casey B.; Dey, Eric L.; Fantone, Joseph C.

    2009-01-01

    Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT…

  20. Admission Privileges and Clinical Responsibilities for Interventional Radiologists

    SciTech Connect

    Al-Kutoubi, Aghiad

    2015-04-15

    Although clinical involvement by interventional radiologists in the care of their patients was advocated at the inception of the specialty, the change into the clinical paradigm has been slow and patchy for reasons related to pattern of practice, financial remuneration or absence of training. The case for the value of clinical responsibilities has been made in a number of publications and the consequences of not doing so have been manifest in the erosion of the role of the interventional radiologists particularly in the fields of peripheral vascular and neuro intervention. With the recent recognition of interventional radiology (IR) as a primary specialty in the USA and the formation of IR division in the Union of European Medical Specialists and subsequent recognition of the subspecialty in many European countries, it is appropriate to relook at the issue and emphasize the need for measures to promote the clinical role of the interventional radiologist.

  1. Exposure–Response Modeling of Clinical End Points Using Latent Variable Indirect Response Models

    PubMed Central

    Hu, C

    2014-01-01

    Exposure–response modeling facilitates effective dosing regimen selection in clinical drug development, where the end points are often disease scores and not physiological variables. Appropriate models need to be consistent with pharmacology and identifiable from the time courses of available data. This article describes a general framework of applying mechanism-based models to various types of clinical end points. Placebo and drug model parameterization, interpretation, and assessment are discussed with a focus on the indirect response models. PMID:24897307

  2. Clinical spectrum of dopa-responsive dystonia and related disorders.

    PubMed

    Lee, Woong-Woo; Jeon, Beom Seok

    2014-07-01

    Dopa-responsive dystonia (DRD) has a classic presentation of childhood or adolescent-onset dystonia, mild parkinsonism, marked diurnal fluctuations, improvement with sleep or rest, and a dramatic and sustained response to low doses of L-dopa without motor fluctuations or dyskinesias. However, there have been many papers on patients with a wide range of features, which report them as DRD mainly because they had dystonic syndromes with L-dopa responsiveness. Many mutations in the dopaminergic system have been found as molecular genetic defects. Therefore, the clinical and genetic spectra of DRD are unclear, which lead to difficulties in diagnostic work-ups and planning treatments. We propose the concept of DRD and DRD-plus to clarify the confusion in this area and to help understand the pathophysiology and clinical features, which will help in guiding diagnostic investigations and planning treatments. We critically reviewed the literature on atypical cases and discussed the limitations of the gene study. PMID:24844652

  3. [Legal responsibility in the exercising of the neurology clinical practice].

    PubMed

    Siso Martín, J

    2004-12-01

    The importance of responsibility in the clinical practice is derived from the transcendency of what they affect (life and health) and the risk implicit to it. The clinical performance does not require curing. The obligations that are derived from them are means and not results. It is also not correct to associate error and responsibility. Responsibility of the professional may be claimed by civil, patrimony, corporative, disciplinary and penal routes based on the reasons and according to who is making the claim. These claims may be presented individually or jointly based on whether the modality of the professional practice is free or carried out by others, whether in public health or private health care. The professional has different alternatives to respond to the possible lawsuits that are presented, both penal and civil action or protection have the common problem of the difficulty of proof. PMID:15719285

  4. A germline predictive signature of response to platinum chemotherapy in esophageal cancer.

    PubMed

    Rumiato, Enrica; Boldrin, Elisa; Malacrida, Sandro; Battaglia, Giorgio; Bocus, Paolo; Castoro, Carlo; Cagol, Matteo; Chiarion-Sileni, Vanna; Ruol, Alberto; Amadori, Alberto; Saggioro, Daniela

    2016-05-01

    Platinum-based neoadjuvant therapy is the standard treatment for esophageal cancer (EC). At present, no reliable response markers exist, and patient therapeutic outcome is variable and very often unpredictable. The aim of this study was to understand the contribution of host constitutive DNA polymorphisms in discriminating between responder and nonresponder patients. DNA collected from 120 EC patients treated with platinum-based neoadjuvant chemotherapy was analyzed using drug metabolism enzymes and transporters (DMET) array platform that interrogates polymorphisms in 225 genes of drug metabolism and disposition. Four gene variants of DNA repair machinery, 2 in ERCC1 (rs11615; rs3212986), and 2 in XPD (rs1799793; rs13181) were also studied. Association analysis was performed with pTest software and corrected by permutation test. Predictive models of response were created using the receiver-operating characteristics curve approach and adjusted by the bootstrap procedure. Sixteen single nucleotide polymorphisms (SNPs) of the DMET array resulted significantly associated with either good or poor response; no association was found for the 4 variants mapping in DNA repair genes. The predictive power of 5 DMET SNPs mapping in ABCC2, ABCC3, CYP2A6, PPARG, and SLC7A8 genes was greater than that of clinical factors alone (area under the curve [AUC] = 0.74 vs 0.62). Interestingly, their combination with the clinical variables significantly increased the predictivity of the model (AUC = 0.78 vs 0.62, P = 0.0016). In conclusion, we identified a genetic signature of response to platinum-based neoadjuvant chemotherapy in EC patients. Our results also disclose the potential benefit of combining genetic and clinical variables for personalized EC management. PMID:26772957

  5. Predicting Non-Response to Juvenile Drug Court Interventions

    PubMed Central

    Halliday-Boykins, Colleen A.; Schaeffer, Cindy M.; Henggeler, Scott W.; Chapman, Jason E.; Cunningham, Phillippe B.; Randall, Jeff; Shapiro, Steven B.

    2010-01-01

    Using data from a recent randomized clinical trial involving juvenile drug court (JDC), youth marijuana use trajectories and the predictors of treatment non-response were examined. Participants were 118 juvenile offenders meeting diagnostic criteria for substance use disorders assigned to JDC and their families. Urine drug screen results were gathered from weekly court visits for 6 months, and youth reported their marijuana use over 12 months. Semiparametric mixture modeling jointly estimated and classified trajectories of both marijuana use indices. Youth were classified into responder versus non-responder trajectory groups based on both outcomes. Regression analyses examined pretreatment individual, family, and extrafamilial predictors of non-response. Results indicated that youth whose caregivers reported illegal drug use pretreatment were almost 10 times as likely to be classified into the non-responder trajectory group. No other variable significantly distinguished drug use trajectory groups. Findings have implications for the design of interventions to improve JDC outcomes. PMID:20826076

  6. Monitoring Regulatory Immune Responses in Tumor Immunotherapy Clinical Trials

    PubMed Central

    Olson, Brian M.; McNeel, Douglas G.

    2013-01-01

    While immune monitoring of tumor immunotherapy often focuses on the generation of productive Th1-type inflammatory immune responses, the importance of regulatory immune responses is often overlooked, despite the well-documented effects of regulatory immune responses in suppressing anti-tumor immunity. In a variety of malignancies, the frequency of regulatory cell populations has been shown to correlate with disease progression and a poor prognosis, further emphasizing the importance of characterizing the effects of immunotherapy on these populations. This review focuses on the role of suppressive immune populations (regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages) in inhibiting anti-tumor immunity, how these populations have been used in the immune monitoring of clinical trials, the prognostic value of these responses, and how the monitoring of these regulatory responses can be improved in the future. PMID:23653893

  7. Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition Study

    PubMed Central

    Schmaal, Lianne; Marquand, Andre F.; Rhebergen, Didi; van Tol, Marie-José; Ruhé, Henricus G.; van der Wee, Nic J.A.; Veltman, Dick J.; Penninx, Brenda W.J.H.

    2015-01-01

    Background A chronic course of major depressive disorder (MDD) is associated with profound alterations in brain volumes and emotional and cognitive processing. However, no neurobiological markers have been identified that prospectively predict MDD course trajectories. This study evaluated the prognostic value of different neuroimaging modalities, clinical characteristics, and their combination to classify MDD course trajectories. Methods One hundred eighteen MDD patients underwent structural and functional magnetic resonance imaging (MRI) (emotional facial expressions and executive functioning) and were clinically followed-up at 2 years. Three MDD trajectories (chronic n = 23, gradual improving n = 36, and fast remission n = 59) were identified based on Life Chart Interview measuring the presence of symptoms each month. Gaussian process classifiers were employed to evaluate prognostic value of neuroimaging data and clinical characteristics (including baseline severity, duration, and comorbidity). Results Chronic patients could be discriminated from patients with more favorable trajectories from neural responses to various emotional faces (up to 73% accuracy) but not from structural MRI and functional MRI related to executive functioning. Chronic patients could also be discriminated from remitted patients based on clinical characteristics (accuracy 69%) but not when age differences between the groups were taken into account. Combining different task contrasts or data sources increased prediction accuracies in some but not all cases. Conclusions Our findings provide evidence that the prediction of naturalistic course of depression over 2 years is improved by considering neuroimaging data especially derived from neural responses to emotional facial expressions. Neural responses to emotional salient faces more accurately predicted outcome than clinical data. PMID:25702259

  8. Rapid response predicts treatment outcomes in binge eating disorder: implications for stepped care.

    PubMed

    Masheb, Robin M; Grilo, Carlos M

    2007-08-01

    The authors examined rapid response in 75 overweight patients with binge eating disorder (BED) who participated in a randomized clinical trial of guided self-help treatments (cognitive-behavioral therapy [CBTgsh] and behavioral weight loss [BWLgsh]). Rapid response, defined as a 65% or greater reduction in binge eating by the 4th treatment week, occurred in 62% of CBTgsh and 47% of BWLgsh participants. Rapid response was unrelated to most patient characteristics except for eating psychopathology and depressive symptoms. Participants with rapid response were more likely to achieve binge remission and had greater improvements in overall eating pathology and depressive symptomatology than participants without rapid response. Rapid response had different prognostic significance for the 2 treatments. In terms of binge eating, participants receiving CBTgsh, but not BWLgsh, did equally well regardless of whether they experienced rapid response. In terms of increasing restraint and weight loss, participants with rapid response receiving BWLgsh had greater restraint and weight loss than participants receiving CBTgsh. Rapid response has utility for predicting outcomes, provides evidence for specificity of treatment effects, and has implications for stepped care treatment models of BED. PMID:17663617

  9. Exploring the clinical validity of predicted TRE in navigation

    NASA Astrophysics Data System (ADS)

    Bickel, M.; Güler, Ö.; Kral, F.; Schwarm, F.; Freysinger, W.

    2010-02-01

    In a detailed laboratory investigation we performed a series of experiments in order to assess the validity of the widely used TRE concept to predict the application accuracy. On base of 1mm CT scan a plastic skull, a cadaver head and a volunteer were registered to an in house navigation system. We stored the position data of an optical camera (NDI Polaris) for registration with pre-defined CT coordinates. For every specimen we choose 3, 5, 7 and 9 registration and 10 evaluation points, respectively, performing 10 registrations. The data were evaluated both with the Arun and the Horn approaches. The vectorial difference between actual and predefined position in the CT data set was stored and evaluated for FRE and TRE. Evaluation and visualization was implemented in Matlab. The data were analyzed, specifically for normal distribution, with MS Excel and SPSS Version 15.0. For the plastic skull and the anatomic specimen submillimetric application accuracy was found experimentally and confirmed by the calculated TRE. Since for the volunteer no Titanium screws were implanted anatomic landmarks had to be used for registration and evaluation; an application accuracy in the low millimeter regime was found in all approaches. However, the detailed statistical analysis of the data revealed that the model predictions and the actual measurements do not exhibit a strong statistical correlation (p < 0.05). These data suggest that the TRE predictions are too optimistic and should be used with caution intraoperatively.

  10. Global Genetic Variations Predict Brain Response to Faces

    PubMed Central

    Dickie, Erin W.; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N.; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

    2014-01-01

    Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R2 = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network. PMID:25122193

  11. Global genetic variations predict brain response to faces.

    PubMed

    Dickie, Erin W; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

    2014-08-01

    Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼ 500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40-50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R(2) = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R(2) = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network. PMID:25122193

  12. Prediction of high frequency gust response with airfoil thickness effects

    NASA Astrophysics Data System (ADS)

    Lysak, Peter D.; Capone, Dean E.; Jonson, Michael L.

    2013-05-01

    The unsteady lift forces that act on an airfoil in turbulent flow are an undesirable source of vibration and noise in many industrial applications. Methods to predict these forces have traditionally treated the airfoil as a flat plate. At higher frequencies, where the relevant turbulent length scales are comparable to the airfoil thickness, the flat plate approximation becomes invalid and results in overprediction of the unsteady force spectrum. This work provides an improved methodology for the prediction of the unsteady lift forces that accounts for the thickness of the airfoil. An analytical model was developed to calculate the response of the airfoil to high frequency gusts. The approach is based on a time-domain calculation with a sharp-edged gust and accounts for the distortion of the gust by the mean flow around the airfoil leading edge. The unsteady lift is calculated from a weighted integration of the gust vorticity, which makes the model relatively straightforward to implement and verify. For routine design calculations of turbulence-induced forces, a closed-form gust response thickness correction factor was developed for NACA 65 series airfoils.

  13. CT contrast predicts pancreatic cancer treatment response to verteporfin-based photodynamic therapy

    NASA Astrophysics Data System (ADS)

    Jermyn, Michael; Davis, Scott C.; Dehghani, Hamid; Huggett, Matthew T.; Hasan, Tayyaba; Pereira, Stephen P.; Bown, Stephen G.; Pogue, Brian W.

    2014-04-01

    The goal of this study was to determine dominant factors affecting treatment response in pancreatic cancer photodynamic therapy (PDT), based on clinically available information in the VERTPAC-01 trial. This trial investigated the safety and efficacy of verteporfin PDT in 15 patients with locally advanced pancreatic adenocarcinoma. CT scans before and after contrast enhancement from the 15 patients in the VERTPAC-01 trial were used to determine venous-phase blood contrast enhancement and this was correlated with necrotic volume determined from post-treatment CT scans, along with estimation of optical absorption in the pancreas for use in light modeling of the PDT treatment. Energy threshold contours yielded estimates for necrotic volume based on this light modeling. Both contrast-derived venous blood content and necrotic volume from light modeling yielded strong correlations with observed necrotic volume (R2 = 0.85 and 0.91, respectively). These correlations were much stronger than those obtained by correlating energy delivered versus necrotic volume in the VERTPAC-01 study and in retrospective analysis from a prior clinical study. This demonstrates that contrast CT can provide key surrogate dosimetry information to assess treatment response. It also implies that light attenuation is likely the dominant factor in the VERTPAC treatment response, as opposed to other factors such as drug distribution. This study is the first to show that contrast CT provides needed surrogate dosimetry information to predict treatment response in a manner which uses standard-of-care clinical images, rather than invasive dosimetry methods.

  14. Stress responsiveness predicts individual variation in mate selectivity.

    PubMed

    Vitousek, Maren N; Romero, L Michael

    2013-06-15

    Steroid hormones, including glucocorticoids, mediate a variety of behavioral and physiological processes. Circulating hormone concentrations vary substantially within populations, and although hormone titers predict reproductive success in several species, little is known about how individual variation in circulating hormone concentrations is linked with most reproductive behaviors in free-living organisms. Mate choice is an important and often costly component of reproduction that also varies substantially within populations. We examined whether energetically costly mate selection behavior in female Galápagos marine iguanas (Amblyrhynchus cristatus) was associated with individual variation in the concentrations of hormones previously shown to differ between reproductive and non-reproductive females during the breeding season (corticosterone and testosterone). Stress-induced corticosterone levels - which are suppressed in female marine iguanas during reproduction - were individually repeatable throughout the seven-week breeding period. Mate selectivity was strongly predicted by individual variation in stress-induced corticosterone: reproductive females that secreted less corticosterone in response to a standardized stressor assessed more displaying males. Neither baseline corticosterone nor testosterone predicted variation in mate selectivity. Scaled body mass was not significantly associated with mate selectivity, but females that began the breeding period in lower body condition showed a trend towards being less selective about potential mates. These results provide the first evidence that individual variation in the corticosterone stress response is associated with how selective females are in their choice of a mate, an important contributor to fitness in many species. Future research is needed to determine the functional basis of this association, and whether transient acute increases in circulating corticosterone directly mediate mate choice behaviors. PMID

  15. Developing an International Register of Clinical Prediction Rules for Use in Primary Care: A Descriptive Analysis

    PubMed Central

    Keogh, Claire; Wallace, Emma; O’Brien, Kirsty K.; Galvin, Rose; Smith, Susan M.; Lewis, Cliona; Cummins, Anthony; Cousins, Grainne; Dimitrov, Borislav D.; Fahey, Tom

    2014-01-01

    PURPOSE We describe the methodology used to create a register of clinical prediction rules relevant to primary care. We also summarize the rules included in the register according to various characteristics. METHODS To identify relevant articles, we searched the MEDLINE database (PubMed) for the years 1980 to 2009 and supplemented the results with searches of secondary sources (books on clinical prediction rules) and personal resources (eg, experts in the field). The rules described in relevant articles were classified according to their clinical domain, the stage of development, and the clinical setting in which they were studied. RESULTS Our search identified clinical prediction rules reported between 1965 and 2009. The largest share of rules (37.2%) were retrieved from PubMed. The number of published rules increased substantially over the study decades. We included 745 articles in the register; many contained more than 1 clinical prediction rule study (eg, both a derivation study and a validation study), resulting in 989 individual studies. In all, 434 unique rules had gone through derivation; however, only 54.8% had been validated and merely 2.8% had undergone analysis of their impact on either the process or outcome of clinical care. The rules most commonly pertained to cardiovascular disease, respiratory, and musculoskeletal conditions. They had most often been studied in the primary care or emergency department settings. CONCLUSIONS Many clinical prediction rules have been derived, but only about half have been validated and few have been assessed for clinical impact. This lack of thorough evaluation for many rules makes it difficult to retrieve and identify those that are ready for use at the point of patient care. We plan to develop an international web-based register of clinical prediction rules and computer-based clinical decision support systems. PMID:25024245

  16. The effect of the stromal component of breast tumours on prediction of clinical outcome using gene expression microarray analysis

    PubMed Central

    Cleator, Susan J; Powles, Trevor J; Dexter, Tim; Fulford, Laura; Mackay, Alan; Smith, Ian E; Valgeirsson, Haukur; Ashworth, Alan; Dowsett, Mitch

    2006-01-01

    Introduction The aim of this study was to examine the effect of the cellular composition of biopsies on the error rates of multigene predictors of response of breast tumours to neoadjuvant adriamycin and cyclophosphamide (AC) chemotherapy. Materials and methods Core biopsies were taken from primary breast tumours of 43 patients prior to AC, and subsequent clinical response was recorded. Post-chemotherapy (day 21) samples were available for 16 of these samples. Frozen sections of each core were used to estimate the proportion of invasive cancer and other tissue components at three levels. Transcriptional profiling was performed using a cDNA array containing 4,600 elements. Results Twenty-three (53%) patients demonstrated a 'good' and 20 (47%) a 'poor' clinical response. The percentage invasive tumour in core biopsies collected from these patients varied markedly. Despite this, agglomerative clustering of sample expression profiles showed that almost all biopsies from the same tumour aggregated as nearest neighbours. SAM (significance analysis of microarrays) regression analysis identified 144 genes which distinguished high- and low-percentage invasive tumour biopsies at a false discovery rate of not more than 5%. The misclassification error of prediction of clinical response using microarray data from pre-treatment biopsies (on leave-one-out cross-validation) was 28%. When prediction was performed on subsets of samples which were more homogeneous in their proportions of malignant and stromal cells, the misclassification error was considerably lower (8%–13%, p < 0.05 on permutation). Conclusion The non-tumour content of breast cancer samples has a significant effect on gene expression profiles. Consideration of this factor improves accuracy of response prediction by expression array profiling. Future gene expression array prediction studies should be planned taking this into account. PMID:16790077

  17. Ethics and epistemology of accurate prediction in clinical research.

    PubMed

    Hey, Spencer Phillips

    2015-07-01

    All major research ethics policies assert that the ethical review of clinical trial protocols should include a systematic assessment of risks and benefits. But despite this policy, protocols do not typically contain explicit probability statements about the likely risks or benefits involved in the proposed research. In this essay, I articulate a range of ethical and epistemic advantages that explicit forecasting would offer to the health research enterprise. I then consider how some particular confidence levels may come into conflict with the principles of ethical research. PMID:25249375

  18. Plasma Biomarkers Can Predict Treatment Response in Tuberculosis Patients

    PubMed Central

    Lee, Meng-Rui; Tsai, Chia-Jung; Wang, Wei-Jie; Chuang, Tzu-Yi; Yang, Chih-Mann; Chang, Lih-Yu; Lin, Ching-Kai; Wang, Jann-Yuan; Shu, Chin-Chong; Lee, Li-Na; Yu, Chong-Jen

    2015-01-01

    Abstract Despite numerous studies, there has been little progress in the use of biomarkers for predicting treatment response in patients with tuberculosis (TB). Patients with culture-confirmed pulmonary TB between 2010 and 2014 were prospectively recruited. Blood samples were taken upon diagnosis and 2 months after the start of standard anti-TB treatment. A pilot study utilizing measurement of TB-antigen-stimulated cytokines was conducted to select potential biomarkers for further testing. Outcome was defined as persistent culture positivity at 2 months into treatment. Of 167 enrolled patients, 26 had persistent culture positivity. RANTES, IL-22, MMP-8, IL-18, MIG, and Granzyme A were selected as potential biomarkers. For predicting persistent culture positivity, receiver-operating characteristics (ROC) analysis showed that initial RANTES (AUC: 0.725 [0.624–0.827]) and 2-month MMP-8 (AUC: 0.632 [0.512–0.713]) had good discriminative ability. Using a logistic regression model, low initial RANTES level (<440 pg/mL), initial smear positivity, and high 2-month MMP-8 level (>3000 pg/mL) were associated with persistent culture positivity. Low initial RANTES level and initial smear positivity had a positive predictive value of 60% (12/20) for persistent culture positivity, compared with 4% (3/75) among patients with high RANTES level and smear negativity upon diagnosis. In the 72 patients with either low RANTES/smear negativity or high RANTES/smear positivity upon diagnosis, the 2-month MMP-8 level had a positive and negative predictive value of 24 and 94%, respectively, for 2-month culture status. Aside from an initial sputum smear status, serum RANTES level at diagnosis and MMP-8 level at 2 months of treatment may be used to stratify risk for culture persistence. PMID:26426648

  19. Prediction of placebo responses: a systematic review of the literature

    PubMed Central

    Horing, Bjoern; Weimer, Katja; Muth, Eric R.; Enck, Paul

    2014-01-01

    Objective: Predicting who responds to placebo treatment—and under which circumstances—has been a question of interest and investigation for generations. However, the literature is disparate and inconclusive. This review aims to identify publications that provide high quality data on the topic of placebo response (PR) prediction. Methods: To identify studies concerned with PR prediction, independent searches were performed in an expert database (for all symptom modalities) and in PubMed (for pain only). Articles were selected when (a) they assessed putative predictors prior to placebo treatment and (b) an adequate control group was included when the associations of predictors and PRs were analyzed. Results: Twenty studies were identified, most with pain as dependent variable. Most predictors of PRs were psychological constructs related to actions, expected outcomes and the emotional valence attached to these events (goal-seeking, self-efficacy/-esteem, locus of control, optimism). Other predictors involved behavioral control (desire for control, eating restraint), personality variables (fun seeking, sensation seeking, neuroticism), or biological markers (sex, a single nucleotide polymorphism related to dopamine metabolism). Finally, suggestibility and beliefs in expectation biases, body consciousness, and baseline symptom severity were found to be predictive. Conclusions: While results are heterogeneous, some congruence of predictors can be identified. PRs mainly appear to be moderated by expectations of how the symptom might change after treatment, or expectations of how symptom repetition can be coped with. It is suggested to include the listed constructs in future research. Furthermore, a closer look at variables moderating symptom change in control groups seems warranted. PMID:25324797

  20. Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach

    PubMed Central

    Niculescu, A B; Levey, D F; Phalen, P L; Le-Niculescu, H; Dainton, H D; Jain, N; Belanger, E; James, A; George, S; Weber, H; Graham, D L; Schweitzer, R; Ladd, T B; Learman, R; Niculescu, E M; Vanipenta, N P; Khan, F N; Mullen, J; Shankar, G; Cook, S; Humbert, C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R

    2015-01-01

    biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would

  1. Predicting the Response of the Mars Ionosphere to Solar Flares

    NASA Astrophysics Data System (ADS)

    Fallows, K.; Withers, P.; Gonzalez, G.

    2015-12-01

    The increased soft X-ray irradiance during solar flares generates increased electron densities in the lower ionosphere of Mars. The relative changes in electron density during a flare are greater for larger flares and also at lower altitudes and larger flares, due to the wavelength dependence of both the flux increase during the flare and the absorption of flux by the neutral atmosphere. These relationships have been explored [Bougher et al. 2001, Fox et al. 2004, Mendillo et al. 2006, Mahajan et al. 2011, Lollo et al. 2012] but not quantified, which has impeded the validation of simulations of the ionospheric effects of solar flares. Such simulations are necessary for developing accurate descriptions of the physical processes governing ionospheric behavior under extreme conditions. We present a response function, a mathematical expression for the change in electron density during a solar flare as a function of the change in solar flux and an optical depth proxy. This response function is based on analysis of 20 Mars Global Surveyor (MGS) radio occultation electron density profiles measured during solar flares. Characterizing the response as a function of optical depth, rather than altitude, provides the best description of ionospheric variability during a flare; otherwise non-negligible solar zenith angle effects are present. We demonstrate that the response function can be used to predict ionospheric electron densities during a specified solar flare by reproducing profiles known to be disturbed by a solar flare. We also demonstrate that the response function can be used to infer the strength of solar flares not visible at Earth by finding the flux enhancement required to reproduce an apparently flare affected profile given an undisturbed profile on the same date.

  2. Behavioral variant of frontotemporal dementia: Fundamental clinical issues associated with prediction of pathological bases.

    PubMed

    Miki, Tomoko; Yokota, Osamu; Ishizu, Hideki; Kuroda, Shigetoshi; Oshima, Etsuko; Terada, Seishi; Yamada, Norihito

    2016-08-01

    Behavioral variant of frontotemporal dementia (bvFTD) is a clinical syndrome characterized mainly by behavioral symptoms due to frontal dysfunction. Major neurodegenerative bases of bvFTD include Pick's disease, frontotemporal lobar degeneration with trans-activation response DNA protein 43-positive inclusions, corticobasal degeneration, and progressive supranuclear palsy. Early disinhibition characterized by socially inappropriate behaviors, loss of manners, and impulsive, rash and careless actions is the most important clinical feature of bvFTD. On the other hand, it was reported that clinical presentations of some Alzheimer's disease cases and patients with psychiatric disorders (e.g., addictive disorders, gambling disorder and kleptomania) often resemble that of bvFTD. Although clinical differentiation of 'true' bvFTD cases with frontotemporal lobar degeneration (FTLD) pathology from mimicking cases without it is not always easy, evaluation of the following features, which were noted in autopsy-confirmed FTLD cases and/or clinical bvFTD cases with circumscribed lobar atrophy, may often provide clues for the diagnosis. (i) The initial symptoms frequently develop at 65 years or younger, and (ii) 'socially inappropriate behaviors' can be frequently interpreted as contextually inappropriate behaviors prompted by environmental visual and auditory stimuli. Taking a detailed history usually reveals various kinds of such behaviors in various situations in everyday life rather than the repetition of a single kind of behavior (e.g., repeated shoplifting). (iii) A correlation between the distribution of cerebral atrophy and neurological and behavioral symptoms is usually observed, and the proportion of FTLD cases with right side-predominant cerebral atrophy may be higher in a psychiatric setting than a neurological setting. Finally, (iv) whether the previous course and the combination of symptoms observed at the first medical visit can be explained by major evolution

  3. In Vitro Drug Sensitivity Tests to Predict Molecular Target Drug Responses in Surgically Resected Lung Cancer

    PubMed Central

    Miyazaki, Ryohei; Anayama, Takashi; Hirohashi, Kentaro; Okada, Hironobu; Kume, Motohiko; Orihashi, Kazumasa

    2016-01-01

    Background Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) and anaplastic lymphoma kinase (ALK) inhibitors have dramatically changed the strategy of medical treatment of lung cancer. Patients should be screened for the presence of the EGFR mutation or echinoderm microtubule-associated protein-like 4 (EML4)-ALK fusion gene prior to chemotherapy to predict their clinical response. The succinate dehydrogenase inhibition (SDI) test and collagen gel droplet embedded culture drug sensitivity test (CD-DST) are established in vitro drug sensitivity tests, which may predict the sensitivity of patients to cytotoxic anticancer drugs. We applied in vitro drug sensitivity tests for cyclopedic prediction of clinical responses to different molecular targeting drugs. Methods The growth inhibitory effects of erlotinib and crizotinib were confirmed for lung cancer cell lines using SDI and CD-DST. The sensitivity of 35 cases of surgically resected lung cancer to erlotinib was examined using SDI or CD-DST, and compared with EGFR mutation status. Results HCC827 (Exon19: E746-A750 del) and H3122 (EML4-ALK) cells were inhibited by lower concentrations of erlotinib and crizotinib, respectively than A549, H460, and H1975 (L858R+T790M) cells were. The viability of the surgically resected lung cancer was 60.0 ± 9.8 and 86.8 ± 13.9% in EGFR-mutants vs. wild types in the SDI (p = 0.0003). The cell viability was 33.5 ± 21.2 and 79.0 ± 18.6% in EGFR mutants vs. wild-type cases (p = 0.026) in CD-DST. Conclusions In vitro drug sensitivity evaluated by either SDI or CD-DST correlated with EGFR gene status. Therefore, SDI and CD-DST may be useful predictors of potential clinical responses to the molecular anticancer drugs, cyclopedically. PMID:27070423

  4. The Use of Clinical Parameters to Predict Obstructive Sleep Apnea Syndrome Severity in Children

    PubMed Central

    Mitchell, Ron B.; Garetz, Suzan; Moore, Reneé H.; Rosen, Carol L.; Marcus, Carole L.; Katz, Eliot S.; Arens, Raanan; Chervin, Ronald D.; Paruthi, Shalini; Amin, Raouf; Elden, Lisa; Ellenberg, Susan S.; Redline, Susan

    2016-01-01

    IMPORTANCE It is important to distinguish children with different levels of severity of obstructive sleep apnea syndrome (OSAS) preoperatively using clinical parameters. This can identify children who most need polysomnography (PSG) prior to adenotonsillectomy (AT). OBJECTIVE To assess whether a combination of factors, including demographics, physical examination findings, and caregiver reports from questionnaires, can predict different levels of OSAS severity in children. DESIGN, SETTING, AND PARTICIPANTS Baseline data from 453 children from the Childhood Adenotonsillectomy (CHAT) study were analyzed. Children 5.0 to 9.9 years of age with PSG-diagnosed OSAS, who were considered candidates for AT, were included. INTERVENTIONS Polysomnography for diagnosis of OSAS. MAIN OUTCOMES AND MEASURES Linear or logistic regression models were fitted to identify which demographic, clinical, and caregiver reports were significantly associated with the apnea hypopnea index (AHI) and oxygen desaturation index (ODI). RESULTS Race (African American), obesity (body mass index z score > 2), and the Pediatric Sleep Questionnaire (PSQ) total score were associated with higher levels of AHI and ODI (P = .05). A multivariable model that included the most significant variables explained less than 3% of the variance in OSAS severity as measured by PSG outcomes. Tonsillar size and Friedman palate position were not associated with increased AHI or ODI. Models that tested for potential effect modification by race or obesity showed no evidence of interactions with any clinical measure, AHI, or ODI (P > .20 for all comparisons). CONCLUSIONS AND RELEVANCE This study of more than 450 children with OSAS identifies a number of clinical parameters that are associated with OSAS severity. However, information on demographics, physical findings, and questionnaire responses does not robustly discriminate different levels of OSAS severity. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00560859 PMID

  5. A clinical measure of DNA methylation predicts outcome in de novo acute myeloid leukemia

    PubMed Central

    Luskin, Marlise R.; Gimotty, Phyllis A.; Smith, Catherine; Loren, Alison W.; Figueroa, Maria E.; Harrison, Jenna; Sun, Zhuoxin; Tallman, Martin S.; Paietta, Elisabeth M.; Litzow, Mark R.; Melnick, Ari M.; Levine, Ross L.; Fernandez, Hugo F.; Luger, Selina M.; Carroll, Martin

    2016-01-01

    BACKGROUND Variable response to chemotherapy in acute myeloid leukemia (AML) represents a major treatment challenge. Clinical and genetic features incompletely predict outcome. The value of clinical epigenetic assays for risk classification has not been extensively explored. We assess the prognostic implications of a clinical assay for multilocus DNA methylation on adult patients with de novo AML. METHODS We performed multilocus DNA methylation assessment using xMELP on samples and calculated a methylation statistic (M-score) for 166 patients from UPENN with de novo AML who received induction chemotherapy. The association of M-score with complete remission (CR) and overall survival (OS) was evaluated. The optimal M-score cut-point for identifying groups with differing survival was used to define a binary M-score classifier. This classifier was validated in an independent cohort of 383 patients from the Eastern Cooperative Oncology Group Trial 1900 (E1900; NCT00049517). RESULTS A higher mean M-score was associated with death and failure to achieve CR. Multivariable analysis confirmed that a higher M-score was associated with death (P = 0.011) and failure to achieve CR (P = 0.034). Median survival was 26.6 months versus 10.6 months for low and high M-score groups. The ability of the M-score to perform as a classifier was confirmed in patients ≤ 60 years with intermediate cytogenetics and patients who achieved CR, as well as in the E1900 validation cohort. CONCLUSION The M-score represents a valid binary prognostic classifier for patients with de novo AML. The xMELP assay and associated M-score can be used for prognosis and should be further investigated for clinical decision making in AML patients. PMID:27446991

  6. DNA Repair Biomarkers Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

    SciTech Connect

    Alexander, Brian M.; Niemierko, Andrzej; Weaver, David T.; Mak, Raymond H.; Fidias, Panagiotis; Wain, John; Choi, Noah C.

    2012-05-01

    Purpose: The addition of neoadjuvant chemoradiotherapy prior to surgical resection for esophageal cancer has improved clinical outcomes in some trials. Pathologic complete response (pCR) following neoadjuvant therapy is associated with better clinical outcome in these patients, but only 22% to 40% of patients achieve pCR. Because both chemotherapy and radiotherapy act by inducing DNA damage, we analyzed proteins selected from multiple DNA repair pathways, using quantitative immunohistochemistry coupled with a digital pathology platform, as possible biomarkers of treatment response and clinical outcome. Methods and Materials: We identified 79 patients diagnosed with esophageal cancer between October 1994 and September 2002, with biopsy tissue available, who underwent neoadjuvant chemoradiotherapy prior to surgery at the Massachusetts General Hospital and used their archived, formalin-fixed, paraffin-embedded biopsy samples to create tissue microarrays (TMA). TMA sections were stained using antibodies against proteins in various DNA repair pathways including XPF, FANCD2, PAR, MLH1, PARP1, and phosphorylated MAPKAP kinase 2 (pMK2). Stained TMA slides were evaluated using machine-based image analysis, and scoring incorporated both the intensity and the quantity of positive tumor nuclei. Biomarker scores and clinical data were assessed for correlations with clinical outcome. Results: Higher scores for MLH1 (p = 0.018) and lower scores for FANCD2 (p = 0.037) were associated with pathologic response to neoadjuvant chemoradiation on multivariable analysis. Staining of MLH1, PARP1, XPF, and PAR was associated with recurrence-free survival, and staining of PARP1 and FANCD2 was associated with overall survival on multivariable analysis. Conclusions: DNA repair proteins analyzed by immunohistochemistry may be useful as predictive markers for response to neoadjuvant chemoradiotherapy in patients with esophageal cancer. These results are hypothesis generating and need

  7. Planning and predictability of clinical outcomes in esthetic rehabilitation.

    PubMed

    Kurbad, A

    2015-01-01

    In esthetic rehabilitation, it is a challenge to meet the needs of patients with growing expectations. Creating predictable results is the key to success. This can be accomplished by performing a comprehensive esthetic diagnosis, elaborating treatment proposals that satisfy today's esthetic standards, and using modern computer-assisted methods. The diagnostic wax-up and mock-up are effective tools that allow patients to visualize treatment proposals without invasive procedures. Once the patient has approved the proposals, they provide the basis for the fabrication of the final restoration. The use of modern ceramic materials makes it possible to achieve a good esthetic outcome, even in restorations with extremely thin layer thicknesses. Esthetic cementation is the final step of restorative treatment. PMID:25911830

  8. Early predictors of a clinical response at 8 weeks in patients with first-episode psychosis treated with paliperidone ER.

    PubMed

    Chung, Young-Chul; Cui, Yin; Kim, Min-Gul; Kim, Yun-Jeong; Lee, Keon-Hak; Chae, Soo-Wan

    2016-08-01

    Identification of early clinical markers that predict later treatment outcomes in first-episode psychosis is highly valuable. The present study was conducted to determine the best time at which to predict the late treatment response in first-episode psychosis patients treated with paliperidone extended release (ER), the factors predicting early treatment responses (at Week 2 and Week 3) and the relationships between the paliperidone ER plasma concentrations at Week 2 and Week 3, and the treatment responses at Week 2, Week 3 and Week 8. Various criteria for assessing treatment response were employed. We determined the plasma paliperidone concentrations at Week 2 and Week 3, using validated high-performance liquid chromatography/tandem mass spectrometry (HPLC-MS/MS). The treatment response at Week 3 optimally predicted the later (Week 8) response, in terms of negative predictive value (NPV). Independent predictors for good treatment responses at Week 2 and Week 3 were: Female gender, a higher educational level, a higher Positive and Negative Syndrome Scale (PANSS) excited score, and/or a shorter duration of untreated psychosis (DUP). The plasma paliperidone concentration at Week 3, but not Week 2, was a significant predictor of the late treatment response at Week 8. These results may help appropriate clinical decision-making for early non-responders after having their first episode of psychosis. PMID:27334812

  9. Do in-vivo behaviors predict early response in family-based treatment for anorexia nervosa?

    PubMed Central

    Darcy, Alison M; Bryson, Susan W.; Agras, W. Stewart; Fitzpatrick, Kathleen Kara; Le Grange, Daniel; Lock, James

    2014-01-01

    The aim of the study is to explore whether identified parental and patient behaviors observed in the first few sessions of family-based treatment (FBT) predict early response (weight gain of 1.8 kg by session four) to treatment. Therapy film recordings from 21 adolescent participants recruited into the FBT arm of a multi-site randomized clinical trial were coded for the presence of behaviors (length of observed behavior divided by length of session recording) in the first, second and fourth sessions. Behaviors that differed between early responders and non-early responders on univariate analysis were entered into discriminant class analyses. Participants with fewer negative verbal behaviors in the first session and were away from table during the meal session less had the greatest rates of early response. Parents who made fewer critical statements and who did not repeatedly present food during the meal session had children who had the greatest rates of early response. In-vivo behaviors in early sessions of FBT may predict early response to FBT. Adaptations to address participant resistance and to decrease the numbers of critical comments made by parents while encouraging their children to eat might improve early response to FBT. PMID:24091274

  10. Do in-vivo behaviors predict early response in family-based treatment for anorexia nervosa?

    PubMed

    Darcy, Alison M; Bryson, Susan W; Agras, W Stewart; Fitzpatrick, Kathleen Kara; Le Grange, Daniel; Lock, James

    2013-11-01

    The aim of the study is to explore whether identified parental and patient behaviors observed in the first few sessions of family-based treatment (FBT) predict early response (weight gain of 1.8 kg by session four) to treatment. Therapy film recordings from 21 adolescent participants recruited into the FBT arm of a multi-site randomized clinical trial were coded for the presence of behaviors (length of observed behavior divided by length of session recording) in the first, second and fourth sessions. Behaviors that differed between early responders and non-early responders on univariate analysis were entered into discriminant class analyses. Participants with fewer negative verbal behaviors in the first session and were away from table during the meal session less had the greatest rates of early response. Parents who made fewer critical statements and who did not repeatedly present food during the meal session had children who had the greatest rates of early response. In-vivo behaviors in early sessions of FBT may predict early response to FBT. Adaptations to address participant resistance and to decrease the numbers of critical comments made by parents while encouraging their children to eat might improve early response to FBT. PMID:24091274

  11. Clinical and electrophysiological responses to dietary challenge in migraineurs.

    PubMed

    Lai, C W; Dean, P; Ziegler, D K; Hassanein, R S

    1989-03-01

    Thirty eight patients with a history of diet-induced migraine were studied with recording of clinical responses, electroencephalography in resting state, in response to photic stimulation, and to hyperventilation and visual evoked potentials. Tests were carried out on an initial baseline day and on a second day, after challenge with chocolate, red wine, cheese, and fasting. Lateralized headache occurred in sixteen subjects (42%), four with scintillating scotomata. Electroencephalograms were abnormal on Day 1 and/or Day 2 in twelve subjects (32%), most abnormalities being non-specific slow waves. In three cases there were paroxysmal features. Electroencephalographic response to hyperventilation was calibrated and was found to be exaggerated in eight subjects (21%) on either Day 1 or Day 2; such response was not related to the occurrence of a headache. Photic simulation showed high frequency driving response (so called "H" response) in all 16 individuals who developed headache but in only 14 out of 22 (64%) who did not (p less than 0.01). Pattern reversal visual evoked responses were normal and failed to show any difference in latency or amplitude between headache responders and non-responders. PMID:2708047

  12. Should I Pack My Umbrella? Clinical versus Statistical Prediction of Mental Health Decisions

    ERIC Educational Resources Information Center

    Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.

    2006-01-01

    In this rejoinder, the authors respond to the insightful commentary of Strohmer and Arm, Chwalisz, and Hilton, Harris, and Rice about the meta-analysis on statistical versus clinical prediction techniques for mental health judgments. The authors address issues including the availability of statistical prediction techniques for real-life psychology…

  13. Sixty-Six Years of Research on the Clinical Versus Actuarial Prediction of Violence

    ERIC Educational Resources Information Center

    Hilton, N. Zoe; Harris, Grant T.; Rice, Marnie E.

    2006-01-01

    In their meta-analysis of clinical versus statistical prediction models, Aegisdottir et al. (this issue) extended previous findings of statistical-method superiority across such variables as clinicians' experience and familiarity with data. In this reaction, the authors are particularly interested in violence prediction, which yields the greatest…

  14. Spontaneous fluctuations in neural responses to heartbeats predict visual detection.

    PubMed

    Park, Hyeong-Dong; Correia, Stéphanie; Ducorps, Antoine; Tallon-Baudry, Catherine

    2014-04-01

    Spontaneous fluctuations of ongoing neural activity substantially affect sensory and cognitive performance. Because bodily signals are constantly relayed up to the neocortex, neural responses to bodily signals are likely to shape ongoing activity. Here, using magnetoencephalography, we show that in humans, neural events locked to heartbeats before stimulus onset predict the detection of a faint visual grating in the posterior right inferior parietal lobule and the ventral anterior cingulate cortex, two regions that have multiple functional correlates and that belong to the same resting-state network. Neither fluctuations in measured bodily parameters nor overall cortical excitability could account for this finding. Neural events locked to heartbeats therefore shape visual conscious experience, potentially by contributing to the neural maps of the organism that might underlie subjectivity. Beyond conscious vision, our results show that neural events locked to a basic physiological input such as heartbeats underlie behaviorally relevant differential activation in multifunctional cortical areas. PMID:24609466

  15. The evolution of predictive adaptive responses in human life history

    PubMed Central

    Nettle, Daniel; Frankenhuis, Willem E.; Rickard, Ian J.

    2013-01-01

    Many studies in humans have shown that adverse experience in early life is associated with accelerated reproductive timing, and there is comparative evidence for similar effects in other animals. There are two different classes of adaptive explanation for associations between early-life adversity and accelerated reproduction, both based on the idea of predictive adaptive responses (PARs). According to external PAR hypotheses, early-life adversity provides a ‘weather forecast’ of the environmental conditions into which the individual will mature, and it is adaptive for the individual to develop an appropriate phenotype for this anticipated environment. In internal PAR hypotheses, early-life adversity has a lasting negative impact on the individual's somatic state, such that her health is likely to fail more rapidly as she gets older, and there is an advantage to adjusting her reproductive schedule accordingly. We use a model of fluctuating environments to derive evolveability conditions for acceleration of reproductive timing in response to early-life adversity in a long-lived organism. For acceleration to evolve via the external PAR process, early-life cues must have a high degree of validity and the level of annual autocorrelation in the individual's environment must be almost perfect. For acceleration to evolve via the internal PAR process requires that early-life experience must determine a significant fraction of the variance in survival prospects in adulthood. The two processes are not mutually exclusive, and mechanisms for calibrating reproductive timing on the basis of early experience could evolve through a combination of the predictive value of early-life adversity for the later environment and its negative impact on somatic state. PMID:23843395

  16. The multiform motor cortical output: Kinematic, predictive and response coding.

    PubMed

    Sartori, Luisa; Betti, Sonia; Chinellato, Eris; Castiello, Umberto

    2015-09-01

    Observing actions performed by others entails a subliminal activation of primary motor cortex reflecting the components encoded in the observed action. One of the most debated issues concerns the role of this output: Is it a mere replica of the incoming flow of information (kinematic coding), is it oriented to anticipate the forthcoming events (predictive coding) or is it aimed at responding in a suitable fashion to the actions of others (response coding)? The aim of the present study was to disentangle the relative contribution of these three levels and unify them into an integrated view of cortical motor coding. We combined transcranial magnetic stimulation (TMS) and electromyography recordings at different timings to probe the excitability of corticospinal projections to upper and lower limb muscles of participants observing a soccer player performing: (i) a penalty kick straight in their direction and then coming to a full stop, (ii) a penalty kick straight in their direction and then continuing to run, (iii) a penalty kick to the side and then continuing to run. The results show a modulation of the observer's corticospinal excitability in different effectors at different times reflecting a multiplicity of motor coding. The internal replica of the observed action, the predictive activation, and the adaptive integration of congruent and non-congruent responses to the actions of others can coexist in a not mutually exclusive way. Such a view offers reconciliation among different (and apparently divergent) frameworks in action observation literature, and will promote a more complete and integrated understanding of recent findings on motor simulation, motor resonance and automatic imitation. PMID:25727547

  17. Optical imaging predicts tumor response to anti-EGFR therapy

    PubMed Central

    Helman, Emily E; Newman, J Robert; Dean, Nichole R; Zhang, Wenyue; Zinn, Kurt R

    2010-01-01

    To evaluate cetuximab treatment in head and neck squamous cell carcinoma xenografts and cell lines, we investigated a preclinical model of head and neck squamous cell carcinoma. Head and neck squamous cell carcinoma cell lines SCC-1, FaDu, CAL27, UM-SCC-5 and UM-SCC-22A were used to generate subcutaneous flank xenografts in SCID mice. Mice were divided into control and cetuximab treatment groups, mice in the latter group received 250 µg cetuximab once weekly for four weeks. After completion of therapy, SCC-1 (p < 0.001), UM-SCC-5 (p < 0.001), UM-SCC-22A (p = 0.016) and FaDu (p = 0.007) tumors were significantly smaller than control, while CAL27 tumors were not different from controls (p = 0.90). Mice were systemically injected with 50 µg of the Cy5.5-cetuximab bioconjugate and imaged by stereomicroscopy to determine if tumor fluorescence predicted tumor response. Intact tumor fluorescence did not predict response. Tissue was harvested from untreated xenografts to evaluate ex vivo imaging. Cell lines were then evaluated in vitro for fluorescence imaging after Cy5.5-cetuximab bioconjugate labeling. The location of fluorescence observed in labeled cells was significantly different for cell lines that responded to treatment, relative to unresponsive cells. Tumors from cell lines that showed low internalized signal in vitro responded best to treatment with cetuximab. This preclinical model may aid in determining which cancer patients are best suited for cetuximab therapy. PMID:20505368

  18. Predicting loss of employment over three years in multiple sclerosis: clinically meaningful cognitive decline.

    PubMed

    Morrow, Sarah A; Drake, Allison; Zivadinov, Robert; Munschauer, Frederick; Weinstock-Guttman, Bianca; Benedict, Ralph H B

    2010-10-01

    Cognitive dysfunction is common in multiple sclerosis (MS), yet the magnitude of change on objective neuropsychological (NP) tests that is clinically meaningful is unclear. We endeavored to determine NP markers of the transition from employment to work disability in MS, as indicated by degree of decline on individual tests. Participants were 97 employed MS patients followed over 41.3 ± 17.6 months with a NP battery covering six domains of cognitive function. Deterioration at follow-up was designated as documented and paid disability benefits (conservative definition) or a reduction in hours/work responsibilities (liberal definition). Using the conservative definition, 28.9% reported deteriorated employment status and for the liberal definition, 45.4%. The Symbol Digit Modalities Test (SDMT) and California Verbal Learning Test, Total Learning (CVLT2-TL) measures distinguished employed and disabled patients at follow-up. Controlling for demographic and MS characteristics, the odds ratio of a deterioration based on a change of 2.0 on the CVLT2-TL was 3.7 (95% CI 1.2-11.4 and SDMT by 4.0 was 4.2 (95% CI 1.2-14.8), accounting for 86.7% of the area under the ROC curve. We conclude that decline on NP testing over time is predictive of deterioration in vocational status, establishing a magnitude of decline on NP tests that is clinically meaningful. PMID:20830649

  19. Neural responses to exclusion predict susceptibility to social influence

    PubMed Central

    Falk, Emily B.; Cascio, Christopher N.; O’Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J.; Bingham, C. Raymond; Shope, Jean T.; Ouimet, Marie Claude; Pradhan, Anuj K.; Simons-Morton, Bruce G.

    2014-01-01

    Purpose Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence, and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American teens, traffic-related crashes are leading causes of non-fatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents’ vulnerability to peer influence. Methods We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently-licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately one week after the neuroimaging session. Results Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside of the neuroimaging lab one week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. Conclusions These results speak to the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging lab. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. PMID:24759437

  20. Prediction of spectral acceleration response ordinates based on PGA attenuation

    USGS Publications Warehouse

    Graizer, V.; Kalkan, E.

    2009-01-01

    Developed herein is a new peak ground acceleration (PGA)-based predictive model for 5% damped pseudospectral acceleration (SA) ordinates of free-field horizontal component of ground motion from shallow-crustal earthquakes. The predictive model of ground motion spectral shape (i.e., normalized spectrum) is generated as a continuous function of few parameters. The proposed model eliminates the classical exhausted matrix of estimator coefficients, and provides significant ease in its implementation. It is structured on the Next Generation Attenuation (NGA) database with a number of additions from recent Californian events including 2003 San Simeon and 2004 Parkfield earthquakes. A unique feature of the model is its new functional form explicitly integrating PGA as a scaling factor. The spectral shape model is parameterized within an approximation function using moment magnitude, closest distance to the fault (fault distance) and VS30 (average shear-wave velocity in the upper 30 m) as independent variables. Mean values of its estimator coefficients were computed by fitting an approximation function to spectral shape of each record using robust nonlinear optimization. Proposed spectral shape model is independent of the PGA attenuation, allowing utilization of various PGA attenuation relations to estimate the response spectrum of earthquake recordings.

  1. Turbomachinery Forced Response Prediction System (FREPS): User's Manual

    NASA Technical Reports Server (NTRS)

    Morel, M. R.; Murthy, D. V.

    1994-01-01

    The turbomachinery forced response prediction system (FREPS), version 1.2, is capable of predicting the aeroelastic behavior of axial-flow turbomachinery blades. This document is meant to serve as a guide in the use of the FREPS code with specific emphasis on its use at NASA Lewis Research Center (LeRC). A detailed explanation of the aeroelastic analysis and its development is beyond the scope of this document, and may be found in the references. FREPS has been developed by the NASA LeRC Structural Dynamics Branch. The manual is divided into three major parts: an introduction, the preparation of input, and the procedure to execute FREPS. Part 1 includes a brief background on the necessity of FREPS, a description of the FREPS system, the steps needed to be taken before FREPS is executed, an example input file with instructions, presentation of the geometric conventions used, and the input/output files employed and produced by FREPS. Part 2 contains a detailed description of the command names needed to create the primary input file that is required to execute the FREPS code. Also, Part 2 has an example data file to aid the user in creating their own input files. Part 3 explains the procedures required to execute the FREPS code on the Cray Y-MP, a computer system available at the NASA LeRC.

  2. Clinical parameters predictive of malignancy of thyroid follicular neoplasms

    SciTech Connect

    Davis, N.L.; Gordon, M.; Germann, E.; Robins, R.E.; McGregor, G.I. )

    1991-05-01

    Needle aspiration biopsy is commonly employed in the evaluation of thyroid nodules. Unfortunately, the cytologic finding of a 'follicular neoplasm' does not distinguish between a thyroid adenoma and a follicular cancer. The purpose of this study was to identify clinical parameters that characterize patients with an increased risk of having a thyroid follicular cancer who preoperatively have a 'follicular neoplasm' identified by needle aspiration biopsy. A total of 395 patients initially treated at Vancouver General Hospital and the British Columbia Cancer Agency between the years of 1965 and 1985 were identified and their data were entered into a computer database. Patients with thyroid adenomas were compared to patients with follicular cancer using the chi-square test and Student's t-test. Statistically significant parameters that distinguished patients at risk of having a thyroid cancer (p less than 0.05) included age greater than 50 years, nodule size greater than 3 cm, and a history of neck irradiation. Sex, family history of goiter or neoplasm, alcohol and tobacco use, and use of exogenous estrogen were not significant parameters. Patients can be identified preoperatively to be at an increased risk of having a follicular cancer and accordingly appropriate surgical resection can be planned.

  3. CT Imaging Biomarkers Predict Clinical Outcomes After Pancreatic Cancer Surgery

    PubMed Central

    Zhu, Liang; Shi, Xiaohua; Xue, Huadan; Wu, Huanwen; Chen, Ge; Sun, Hao; He, Yonglan; Jin, Zhengyu; Liang, Zhiyong; Zhang, Zhuoli

    2016-01-01

    Abstract This study aimed to determine whether changes in contrast-enhanced computed tomography (CT) parameters could predict postsurgery overall and progression-free survival (PFS) in pancreatic cancer patients. Seventy-nine patients with a final pathological diagnosis of pancreatic adenocarcinoma were included in this study from June 2008 to August 2012. Dynamic contrast-enhanced (DCE) CT of tumors was obtained before curative-intent surgery. Absolute enhancement change (AEC) and relative enhancement change (REC) were evaluated on DCE-CT. PFS and overall survival (OS) were compared based on CT enhancement patterns. The markers of fibrogenic alpha-smooth muscle antigen (α-SMA) and periostin in tumor specimens were evaluated by immunohistochemical staining. The χ2 test was performed to determine whether CT enhancement patterns were associated with α-SMA-periostin expression levels (recorded as positive or negative). Lower REC (<0.9) was associated with shorter PFS (HR 0.51, 95% CI: 0.31–0.89) and OS (HR 0.44, 95% CI: 0.25–0.78). The α-SMA and periostin expression level were negatively correlated with REC (both P = 0). Among several CT enhancement parameters, REC was the best predictor of patient postsurgery survival. Low REC was associated with a short progression-free time and poor survival. The pathological studies suggested that REC might be a reflection of cancer fibrogenic potential. PMID:26844495

  4. Modeling Clinical Radiation Responses in the IMRT Era

    NASA Astrophysics Data System (ADS)

    Schwartz, J. L.; Murray, D.; Stewart, R. D.; Phillips, M. H.

    2014-03-01

    The purpose of this review is to highlight the critical issues of radiobiological models, particularly as they apply to clinical radiation therapy. Developing models of radiation responses has a long history that continues to the present time. Many different models have been proposed, but in the field of radiation oncology, the linear-quadratic (LQ) model has had the most impact on the design of treatment protocols. Questions have been raised as to the value of the LQ model given that the biological assumption underlying it has been challenged by molecular analyses of cell and tissue responses to radiation. There are also questions as to use of the LQ model for hypofractionation, especially for high dose treatments using a single fraction. While the LQ model might over-estimate the effects of large radiation dose fractions, there is insufficient information to fully justify the adoption of alternative models. However, there is increasing evidence in the literature that non-targeted and other indirect effects of radiation sometimes produce substantial deviations from LQ-like dose-response curves. As preclinical and clinical hypofractionation studies accumulate, new or refined dose-response models that incorporate high-dose/fraction non-targeted and indirect effects may be required, but for now the LQ model remains a simple, useful tool to guide the design of treatment protocols.

  5. Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture.

    PubMed

    Sadeghi-Naini, Ali; Sannachi, Lakshmanan; Pritchard, Kathleen; Trudeau, Maureen; Gandhi, Sonal; Wright, Frances C; Zubovits, Judit; Yaffe, Martin J; Kolios, Michael C; Czarnota, Gregory J

    2014-06-15

    Early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, in conjunction with changes in their mean values, are demonstrated here, for the first time, to be capable of predicting ultimate clinical/pathologic responses of breast cancer patients to chemotherapy. Mechanisms of cell death, induced by chemotherapy within tumor, introduce morphological alterations in cancerous cells, resulting in measurable changes in tissue echogenicity. We have demonstrated that the development of such changes is reflected in early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, followed by consequent changes in their mean values. The spectral/textural biomarkers derived on this basis have been demonstrated as non-invasive surrogates of breast cancer chemotherapy response. Particularly, spectral biomarkers sensitive to the size and concentration of acoustic scatterers could predict treatment response of patients with up to 80% of sensitivity and specificity (p=0.050), after one week within 3-4 months of chemotherapy. However, textural biomarkers characterizing heterogeneities in distribution of acoustic scatterers, could differentiate between treatment responding and non-responding patients with up to 100% sensitivity and 93% specificity (p=0.002). Such early prediction permits offering effective alternatives to standard treatment, or switching to a salvage therapy, for refractory patients. PMID:24939867

  6. Clinical Parameters vs Cytokine Profiles as Predictive Markers of IgE-Mediated Allergy in Young Children

    PubMed Central

    Lombard, Catherine; André, Floriane; Paul, Jérôme; Wanty, Catherine; Vosters, Olivier; Bernard, Pierre; Pilette, Charles; Dupont, Pierre; Sokal, Etienne M.; Smets, Françoise

    2015-01-01

    Background Allergy afflicts one third of children, negatively impacting their quality of life and generating a significant socio-economic burden. To this day, this disorder remains difficult to diagnose early in young patients, with no predictive test available. Objective This study was designed to correlate cytokine profiles with clinical phenotypes of allergy development. Methods Three hundred patients were recruited and followed from birth to 18 months of age. They were given a clinical exam at birth and at 2, 6, 12, and 18 months of age, with skin prick tests at 6, and 18 months, in order to have a record of their medical history and determine their allergic status. In addition, mononuclear cells from 131 patients were isolated from cord blood and from peripheral blood samples at 2, 6 and 18 months of age, to analyse their cytokine and chemokine production. Results Cord blood mononuclear cells (CBMCs) from future Immunoglobulin (Ig) E-mediated allergic children produced significantly less Interleukin (IL)-12p70 and IL-15 than cells from the rest of the cohort. Multivariate analyses revealed that the best predictive model of allergy was built on cytokine data, whereas the best predictive model of IgE-mediated allergy was built on clinical parameters. Conclusions and clinical relevance Although univariate analyses can yield interesting information regarding the immune responses of allergic children, finding predictive markers of the disorder will likely rely on monitoring multiple parameters. Nonetheless these analyses suggest a potential key role for IL-15 in the development of atopic disease. In addition, the study highlights the importance of clinical parameters in predicting the development of IgE-mediated allergy. PMID:26214693

  7. In vitro simulation of pathological bone conditions to predict clinical outcome of bone tissue engineered materials

    NASA Astrophysics Data System (ADS)

    Nguyen, Duong Thuy Thi

    treatment strategy should focus on simulating, in vitro, a physiological bone environment to predict clinical effectiveness of engineered bone and understand cellular responses due to the proposed agents and bioactive scaffolds. An in vitro test system can be the necessary catalyst to reduce implant failures and non-unions in fragility fractures.

  8. Perceived Partner Responsiveness Predicts Diurnal Cortisol Profiles 10 Years Later

    PubMed Central

    Slatcher, Richard B.; Selcuk, Emre; Ong, Anthony D.

    2015-01-01

    Several decades of research have demonstrated that marital relationships have a powerful influence on physical health. However, surprisingly little is known about how marriage affects health—both in terms of psychological processes and biological ones. We investigated the associations between perceived partner responsiveness—the extent to which people feel understood, cared for and appreciated by their romantic partner—and diurnal cortisol over a 10-year period in a large sample of married and cohabitating couples in the U.S. Partner responsiveness predicted higher wakeup cortisol values and steeper (“healthier”) cortisol slopes at the 10-year follow-up, and these associations remained strong after controlling for demographic factors, depressive symptoms, agreeableness, and other positive and negative relationship factors. Further, declines in negative affect over the 10-year period mediated the prospective association between responsiveness and cortisol slope. These findings suggest that diurnal cortisol may be a key biological pathway through which social relationships impact long-term health. PMID:26015413

  9. Bioengineered human myobundles mimic clinical responses of skeletal muscle to drugs.

    PubMed

    Madden, Lauran; Juhas, Mark; Kraus, William E; Truskey, George A; Bursac, Nenad

    2015-01-01

    Existing in vitro models of human skeletal muscle cannot recapitulate the organization and function of native muscle, limiting their use in physiological and pharmacological studies. Here, we demonstrate engineering of electrically and chemically responsive, contractile human muscle tissues ('myobundles') using primary myogenic cells. These biomimetic constructs exhibit aligned architecture, multinucleated and striated myofibers, and a Pax7(+) cell pool. They contract spontaneously and respond to electrical stimuli with twitch and tetanic contractions. Positive correlation between contractile force and GCaMP6-reported calcium responses enables non-invasive tracking of myobundle function and drug response. During culture, myobundles maintain functional acetylcholine receptors and structurally and functionally mature, evidenced by increased myofiber diameter and improved calcium handling and contractile strength. In response to diversely acting drugs, myobundles undergo dose-dependent hypertrophy or toxic myopathy similar to clinical outcomes. Human myobundles provide an enabling platform for predictive drug and toxicology screening and development of novel therapeutics for muscle-related disorders. PMID:25575180

  10. Clinical Prediction Making: Examining Influential Factors Related to Clinician Predictions of Recidivism among Juvenile Offenders

    ERIC Educational Resources Information Center

    Calley, Nancy G.; Richardson, Emily M.

    2011-01-01

    This study examined factors influencing clinician predictions of recidivism for juvenile offenders, including youth age at initial juvenile justice system involvement, youth age at discharge, program completion status, clinician perception of strength of the therapeutic relationship, and clinician perception of youth commitment to treatment.…

  11. Diffusion-Weighted Magnetic Resonance Application in Response Prediction before, during, and after Neoadjuvant Radiochemotherapy in Primary Rectal Cancer Carcinoma

    PubMed Central

    Musio, Daniela; De Felice, Francesca; Magnante, Anna Lisa; Rengo, Marco; Redler, Adriano; Laghi, Andrea; Raffetto, Nicola; Tombolini, Vincenzo

    2013-01-01

    Introduction. Our interest was to monitor treatment response using ADC value to predict response of rectal tumour to preoperative radiochemotherapy. Materials and Methods. Twenty-two patients were treated with long course of radiochemotherapy, followed by surgery. Patients were examined by diffusion-weighted imaging MRI at three-time points (prior, during, and after radiochemotherapy) and were classified as responders and nonresponders. Results. A statistical significant correlation was found between preradiochemotherapy ADC values and during treatment ADC values, in responders (F = 21.50, P value <0.05). An increase in ADC value during treatment was predictive of at least a partial response. Discussion. Response of tumour to neoadjuvant therapy cannot be easily evaluated, and such capability might be of great importance in clinical practice, because the number of irradiated and operated patients may be superior to the number of who will really benefit from this multimodal treatment. A reliable prediction of the final clinical TN stage would allow radiotherapist to adapt multidisciplinary approach to a less invasive management, sparing surgical procedure in responder patients or even allowing an early surgery in nonresponders, which would significantly reduce radiochemotherapy related toxicity. Conclusion. Early evaluation of response during neoadjuvant radiochemotherapy treatment shows great promise to predict tumour response. PMID:23936841

  12. Prominent Clinical Dimension, Duration of Illness and Treatment Response in Schizophrenia: A Naturalistic Study

    PubMed Central

    Caldiroli, Alice; Panza, Gabriele; Altamura, Alfredo Carlo

    2012-01-01

    Objective Preliminary data indicate that predominant positive symptoms are predictive of subsequent treatment response, while negative and cognitive symptoms are associated with poor outcome. Purpose of the present study was to investigate the relation between the predominant clinical dimension, duration of illness and acute antipsychotic response in a sample of schizophrenic inpatients. Methods Fifty-one schizophrenic inpatients, receiving an antipsychotic mono-therapy, were dimensionally assessed at the admission in the Acute Psychiatric Unit of the University of Milan. Treatment response was selected as parameter of outcome and defined as a reduction >50% of baseline total The Positive and Negative Syndrome Scale (PANSS) score. Demographic and clinical variables between responders and non-responders were compared using one-way analysis of variance for continuous variables and χ2 test for dichotomous ones. Binary logistic regression was performed to find if dimensional scores and duration of illness were associated with acute antipsychotic response. Results A longer duration of illness was found in non-responders respect to responders (15.61 years vs. 8.28 years)(F=4.98, p=0.03). Higher scores on PANSS positive sub-scale (OR=1.3, p=0.03), lower scores on cognitive PANSS scores (OR=0.75, p=0.05) and shorter duration of illness (OR=0.93, p=0.04) were found to be predictive of acute antipsychotic response. Conclusion These preliminary results show that a long duration of illness as well as a more severe cognitive impairment is predictive of treatment non-response, indicating a worse outcome for chronic patients with predominant cognitive symptoms. PMID:23251199

  13. Does Cognition Predict Treatment Response and Remission in Psychotherapy for Late-Life Depression?

    PubMed Central

    Beaudreau, Sherry A.; Rideaux, Tiffany; O'Hara, Ruth; Arean, Patricia

    2014-01-01

    Objectives To identify cognitive predictors of geriatric depression treatment outcome. Method Older participants completed baseline measures of memory and executive function, health, and baseline and posttreatment Hamilton Depression Scales (HAM-D) in a 12-week trial comparing psychotherapies (problem-solving vs. supportive; n = 46). We examined cognitive predictors to identify treatment responders, i.e., HAM-D scores reduced by ≥50%, and remitters, i.e., posttreatment HAM-D score ≤ 10. Results Empirically-derived decision trees identified poorer performance on switching (i.e. Trails B), with a cut-score of ≥82” predicting psychotherapy responders. No other cognitive or health variables predicted psychotherapy outcomes in the decision trees. Conclusions Psychotherapies that support or improve the executive skill of switching may augment treatment response for older patients exhibiting executive dysfunction in depression. If replicated, Trails B has potential as a brief cognitive tool for clinical decision-making in geriatric depression. PMID:25441055

  14. Dopa-responsive dystonia--clinical and genetic heterogeneity.

    PubMed

    Wijemanne, Subhashie; Jankovic, Joseph

    2015-07-01

    Dopa-responsive dystonia (DRD) encompasses a group of clinically and genetically heterogeneous disorders that typically manifest as limb-onset, diurnally fluctuating dystonia and exhibit a robust and sustained response to levodopa treatment. Autosomal dominant GTP cyclohydrolase 1 deficiency, also known as Segawa disease, is the most common and best-characterized condition that manifests as DRD, but a similar presentation can be seen with genetic abnormalities that lead to deficiencies in tyrosine hydroxylase, sepiapterin reductase or other enzymes that are involved in the biosynthesis of dopamine. In rare cases, DRD can result from conditions that do not affect the biosynthesis of dopamine; single case reports have shown that DRD can be a manifestation of hereditary spastic paraplegia type 11, spinocerebellar ataxia type 3 and ataxia telangiectasia. This heterogeneity of conditions that underlie DRD frequently leads to misdiagnosis, which delays the appropriate treatment with levodopa. Correct diagnosis at an early stage requires use of the appropriate diagnostic tests, which include a levodopa trial, genetic testing (including whole-exome sequencing), cerebrospinal fluid neurotransmitter analysis, the phenylalanine loading test, and enzyme activity measurements. The selection of tests for use depends on the clinical presentation and level of complexity. This Review presents the common and rarer causes of DRD and their clinical features, and considers the most appropriate approaches to ensure early diagnosis and treatment. PMID:26100751

  15. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech.

    PubMed

    Whitwell, Jennifer L; Weigand, Stephen D; Duffy, Joseph R; Strand, Edythe A; Machulda, Mary M; Senjem, Matthew L; Gunter, Jeffrey L; Lowe, Val J; Jack, Clifford R; Josephs, Keith A

    2016-01-01

    Beta-amyloid (Aβ) deposition can be observed in primary progressive aphasia (PPA) and progressive apraxia of speech (PAOS). While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified) and PAOS (n = 42) subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+) status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+) status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+) status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified PPA subjects

  16. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech

    PubMed Central

    Whitwell, Jennifer L.; Weigand, Stephen D.; Duffy, Joseph R.; Strand, Edythe A.; Machulda, Mary M.; Senjem, Matthew L.; Gunter, Jeffrey L.; Lowe, Val J.; Jack, Clifford R.; Josephs, Keith A.

    2016-01-01

    Beta-amyloid (Aβ) deposition can be observed in primary progressive aphasia (PPA) and progressive apraxia of speech (PAOS). While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified) and PAOS (n = 42) subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+) status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+) status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+) status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified PPA subjects

  17. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer.

    PubMed

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I; Hernández, Roberto; Pedregal, Manuel; Martín, María J; Cortés, Delia; García-Olmo, Damian; Fernández, María J; Rojo, Federico; García-Foncillas, Jesús

    2016-01-01

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients. PMID:27271609

  18. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer

    PubMed Central

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P.; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I.; Hernández, Roberto; Pedregal, Manuel; Martín, María J.; Cortés, Delia; García-Olmo, Damian; Fernández, María J.; Rojo, Federico; García-Foncillas, Jesús

    2016-01-01

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients. PMID:27271609

  19. Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach.

    PubMed

    Niculescu, A B; Levey, D F; Phalen, P L; Le-Niculescu, H; Dainton, H D; Jain, N; Belanger, E; James, A; George, S; Weber, H; Graham, D L; Schweitzer, R; Ladd, T B; Learman, R; Niculescu, E M; Vanipenta, N P; Khan, F N; Mullen, J; Shankar, G; Cook, S; Humbert, C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R

    2015-11-01

    biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would

  20. Predicting response to chemotherapy with early-stage lung cancer.

    PubMed

    Rosell, Rafael; Taron, Miquel; Massuti, Bartomeu; Mederos, Nuria; Magri, Ignacio; Santarpia, Mariacarmela; Sanchez, Jose Miguel

    2011-01-01

    A recent meta-analysis of 11,107 patients with non-small cell lung cancer who had undergone surgical resection showed that the 5-year survival benefit of adjuvant chemotherapy was 4%, and that of adjuvant chemoradiotherapy was 5%. Two trials have shown a trend toward improved survival with adjuvant paclitaxel plus carboplatin. However, the benefit of adjuvant treatment remains suboptimal. We must distinguish between patients who will not relapse-and who can thus be spared adjuvant treatment-and those who will-for whom adjuvant treatment must be personalized. Several gene expression signatures, generally containing nonoverlapping genes, provide similar predictive information on clinical outcome, and a model combining several signatures did not perform better than did each of the signatures separately. The invasiveness gene signature, containing 186 genes, includes genes involved in the nuclear factor κB pathway, the RAS-mitogen-activated protein kinase pathway, and epigenetic control of gene expression. A 15-gene signature has identified JBR.10 patients who are more sensitive to adjuvant chemotherapy. PMID:21263267

  1. Predicting Out-of-Office Blood Pressure in the Clinic (PROOF-BP)

    PubMed Central

    Stevens, Richard; Gill, Paramjit; Martin, Una; Godwin, Marshall; Hanley, Janet; Heneghan, Carl; Hobbs, F.D. Richard; Mant, Jonathan; McKinstry, Brian; Myers, Martin; Nunan, David; Ward, Alison; Williams, Bryan; McManus, Richard J.

    2016-01-01

    Patients often have lower (white coat effect) or higher (masked effect) ambulatory/home blood pressure readings compared with clinic measurements, resulting in misdiagnosis of hypertension. The present study assessed whether blood pressure and patient characteristics from a single clinic visit can accurately predict the difference between ambulatory/home and clinic blood pressure readings (the home–clinic difference). A linear regression model predicting the home–clinic blood pressure difference was derived in 2 data sets measuring automated clinic and ambulatory/home blood pressure (n=991) using candidate predictors identified from a literature review. The model was validated in 4 further data sets (n=1172) using area under the receiver operator characteristic curve analysis. A masked effect was associated with male sex, a positive clinic blood pressure change (difference between consecutive measurements during a single visit), and a diagnosis of hypertension. Increasing age, clinic blood pressure level, and pulse pressure were associated with a white coat effect. The model showed good calibration across data sets (Pearson correlation, 0.48–0.80) and performed well-predicting ambulatory hypertension (area under the receiver operator characteristic curve, 0.75; 95% confidence interval, 0.72–0.79 [systolic]; 0.87; 0.85–0.89 [diastolic]). Used as a triaging tool for ambulatory monitoring, the model improved classification of a patient’s blood pressure status compared with other guideline recommended approaches (93% [92% to 95%] classified correctly; United States, 73% [70% to 75%]; Canada, 74% [71% to 77%]; United Kingdom, 78% [76% to 81%]). This study demonstrates that patient characteristics from a single clinic visit can accurately predict a patient’s ambulatory blood pressure. Usage of this prediction tool for triaging of ambulatory monitoring could result in more accurate diagnosis of hypertension and hence more appropriate treatment. PMID:27001299

  2. Prognostic and Predictive Biomarkers of Endocrine Responsiveness for Estrogen Receptor Positive Breast Cancer.

    PubMed

    Ma, Cynthia X; Bose, Ron; Ellis, Matthew J

    2016-01-01

    The estrogen-dependent nature of breast cancer is the fundamental basis for endocrine therapy. The presence of estrogen receptor (ER), the therapeutic target of endocrine therapy, is a prerequisite for this therapeutic approach. However, estrogen-independent growth often exists de novo at diagnosis or develops during the course of endocrine therapy. Therefore ER alone is insufficient in predicting endocrine therapy efficacy. Several RNA-based multigene assays are now available in clinical practice to assess distant recurrence risk, with majority of these assays evaluated in patients treated with 5 years of adjuvant endocrine therapy. While MammaPrint and Oncotype Dx are most predictive of recurrence risk within the first 5 years of diagnosis, Prosigna, Breast Cancer Index (BCI), and EndoPredict Clin have also demonstrated utility in predicting late recurrence. In addition, PAM50, or Prosigna, provides further biological insights by classifying breast cancers into intrinsic molecular subtypes. Additional strategies are under investigation in prospective clinical trials to differentiate endocrine sensitive and resistant tumors and include on-treatment Ki-67 and Preoperative Endocrine Prognostic Index (PEPI) score in the setting of neoadjuvant endocrine therapy. These biomarkers have become important tools in clinical practice for the identification of low risk patients for whom chemotherapy could be avoided. However, there is much work ahead toward the development of a molecular classification that informs the biology and novel therapeutic targets in high-risk disease as chemotherapy has only modest benefit in this population. The recognition of somatic mutations and their relationship to endocrine therapy responsiveness opens important opportunities toward this goal. PMID:26987533

  3. Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes

    PubMed Central

    Huo, Zhiguang; Martin, Amantha; Nelson, Joel B.; Tseng, George C.; Luo, Jian-Hua

    2015-01-01

    Accurate prediction of prostate cancer clinical courses remains elusive. In this study, we performed whole genome copy number analysis on leukocytes of 273 prostate cancer patients using Affymetrix SNP6.0 chip. Copy number variations (CNV) were found across all chromosomes of the human genome. An average of 152 CNV fragments per genome was identified in the leukocytes from prostate cancer patients. The size distributions of CNV in the genome of leukocytes were highly correlative with prostate cancer aggressiveness. A prostate cancer outcome prediction model was developed based on large size ratio of CNV from the leukocyte genomes. This prediction model generated an average prediction rate of 75.2%, with sensitivity of 77.3% and specificity of 69.0% for prostate cancer recurrence. When combined with Nomogram and the status of fusion transcripts, the average prediction rate was improved to 82.5% with sensitivity of 84.8% and specificity of 78.2%. In addition, the leukocyte prediction model was 62.6% accurate in predicting short prostate specific antigen doubling time. When combined with Gleason’s grade, Nomogram and the status of fusion transcripts, the prediction model generated a correct prediction rate of 77.5% with 73.7% sensitivity and 80.1% specificity. To our knowledge, this is the first study showing that CNVs in leukocyte genomes are predictive of clinical outcomes of a human malignancy. PMID:26295840

  4. Blinded prospective evaluation of computer-based mechanistic schizophrenia disease model for predicting drug response.

    PubMed

    Geerts, Hugo; Spiros, Athan; Roberts, Patrick; Twyman, Roy; Alphs, Larry; Grace, Anthony A

    2012-01-01

    The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published 'Quantitative Systems Pharmacology' computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA) and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D(2) antagonist and ocaperidone, a very high affinity dopamine D(2) antagonist, using only pharmacology and human positron emission tomography (PET) imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS) total score and the higher extra-pyramidal symptom (EPS) liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development. PMID:23251349

  5. Blinded Prospective Evaluation of Computer-Based Mechanistic Schizophrenia Disease Model for Predicting Drug Response

    PubMed Central

    Geerts, Hugo; Spiros, Athan; Roberts, Patrick; Twyman, Roy; Alphs, Larry; Grace, Anthony A.

    2012-01-01

    The tremendous advances in understanding the neurobiological circuits involved in schizophrenia have not translated into more effective treatments. An alternative strategy is to use a recently published ‘Quantitative Systems Pharmacology’ computer-based mechanistic disease model of cortical/subcortical and striatal circuits based upon preclinical physiology, human pathology and pharmacology. The physiology of 27 relevant dopamine, serotonin, acetylcholine, norepinephrine, gamma-aminobutyric acid (GABA) and glutamate-mediated targets is calibrated using retrospective clinical data on 24 different antipsychotics. The model was challenged to predict quantitatively the clinical outcome in a blinded fashion of two experimental antipsychotic drugs; JNJ37822681, a highly selective low-affinity dopamine D2 antagonist and ocaperidone, a very high affinity dopamine D2 antagonist, using only pharmacology and human positron emission tomography (PET) imaging data. The model correctly predicted the lower performance of JNJ37822681 on the positive and negative syndrome scale (PANSS) total score and the higher extra-pyramidal symptom (EPS) liability compared to olanzapine and the relative performance of ocaperidone against olanzapine, but did not predict the absolute PANSS total score outcome and EPS liability for ocaperidone, possibly due to placebo responses and EPS assessment methods. Because of its virtual nature, this modeling approach can support central nervous system research and development by accounting for unique human drug properties, such as human metabolites, exposure, genotypes and off-target effects and can be a helpful tool for drug discovery and development. PMID:23251349

  6. Response to clozapine in a clinically identifiable subtype of schizophrenia

    PubMed Central

    Butcher, Nancy J.; Fung, Wai Lun Alan; Fitzpatrick, Laura; Guna, Alina; Andrade, Danielle M.; Lang, Anthony E.; Chow, Eva W. C.; Bassett, Anne S.

    2015-01-01

    Background Genetic testing in psychiatry promises to improve patient care through advances in personalised medicine. However, there are few clinically relevant examples. Aims To determine whether patients with a well-established genetic subtype of schizophrenia show a different response profile to the antipsychotic clozapine than those with idiopathic schizophrenia. Method We retrospectively studied the long-term safety and efficacy of clozapine in 40 adults with schizophrenia, half with a 22q11.2 deletion (22q11.2DS group) and half matched for age and clinical severity but molecularly confirmed to have no pathogenic copy number variant (idiopathic group). Results Both groups showed similar clinical improvement and significant reductions in hospitalisations, achieved at a lower median dose for those in the 22q11.2DS group. Most common side-effects were similarly prevalent between the two groups, however, half of the 22q11.2DS group experienced at least one rare serious adverse event compared with none of the idiopathic group. Many were successfully retried on clozapine. Conclusions Individuals with 22q11.2DS-schizophrenia respond as well to clozapine treatment as those with other forms of schizophrenia, but may represent a disproportionate number of those with serious adverse events, primarily seizures. Lower doses and prophylactic (for example anticonvulsant) management strategies can help ameliorate side-effect risks. This first systematic evaluation of antipsychotic response in a genetic subtype of schizophrenia provides a proof-of-principle for personalised medicine and supports the utility of clinical genetic testing in schizophrenia. PMID:25745132

  7. Corticosteroid responsiveness and clinical characteristics in childhood difficult asthma

    PubMed Central

    Bossley, C.J.; Saglani, S.; Kavanagh, C.; Payne, D.N.R.; Wilson, N.; Tsartsali, L.; Rosenthal, M.; Balfour-Lynn, I.M.; Nicholson, A.G.; Bush, A.

    2012-01-01

    This study describes the clinical characteristics and corticosteroid responsiveness of children with difficult asthma (DA). We hypothesised that complete corticosteroid responsiveness (defined as improved symptoms, normal spirometry, normal exhaled nitric oxide fraction (FeNO) and no bronchodilator responsiveness (BDR <12%)) is uncommon in paediatric DA. We report on 102 children, mean±SD age 11.6±2.8 yrs, with DA in a cross-sectional study. 89 children underwent spirometry, BDR and FeNO before and after 2 weeks of systemic corticosteroids (corticosteroid response study). Bronchoscopy was performed after the corticosteroid trial. Of the 102 patients in the cross-sectional study, 88 (86%) were atopic, 60 (59%) were male and 52 (51%) had additional or alternative diagnoses. Out of the 81 patients in the corticosteroid response study, nine (11%) were complete responders. Of the 75 patients with symptom data available, 37 (49%) responded symptomatically, which was less likely if there were smokers in the home (OR 0.31, 95% CI 0.02–0.82). Of the 75 patients with available spirometry data, 35 (46%) had normal spirometry, with associations being BAL eosinophilia (OR 5.43, 95% CI 1.13–26.07) and high baseline forced expiratory volume in 1 s (FEV1) (OR 1.08, 95% CI 1.02–1.12). Of these 75 patients, BDR data were available in 64, of whom 36 (56%) had <12% BDR. FeNO data was available in 70 patients, of whom 53 (75%) had normal FeNO. Airflow limitation data was available in 75 patients, of whom 17 (26%) had persistent airflow limitation, which was associated with low baseline FEV1 (OR 0.93, 95% CI 0.90–0.97). Only 11% of DA children exhibited complete corticosteroid responsiveness. The rarity of complete corticosteroid responsiveness suggests alternative therapies are needed for children with DA. PMID:19541710

  8. Interactive Voice/Web Response System in clinical research

    PubMed Central

    Ruikar, Vrishabhsagar

    2016-01-01

    Emerging technologies in computer and telecommunication industry has eased the access to computer through telephone. An Interactive Voice/Web Response System (IxRS) is one of the user friendly systems for end users, with complex and tailored programs at its backend. The backend programs are specially tailored for easy understanding of users. Clinical research industry has experienced revolution in methodologies of data capture with time. Different systems have evolved toward emerging modern technologies and tools in couple of decades from past, for example, Electronic Data Capture, IxRS, electronic patient reported outcomes, etc. PMID:26952178

  9. Interactive Voice/Web Response System in clinical research.

    PubMed

    Ruikar, Vrishabhsagar

    2016-01-01

    Emerging technologies in computer and telecommunication industry has eased the access to computer through telephone. An Interactive Voice/Web Response System (IxRS) is one of the user friendly systems for end users, with complex and tailored programs at its backend. The backend programs are specially tailored for easy understanding of users. Clinical research industry has experienced revolution in methodologies of data capture with time. Different systems have evolved toward emerging modern technologies and tools in couple of decades from past, for example, Electronic Data Capture, IxRS, electronic patient reported outcomes, etc. PMID:26952178

  10. Assessment of tumour hypoxia for prediction of response to therapy and cancer prognosis

    PubMed Central

    Jubb, Adrian M; Buffa, Francesca M; Harris, Adrian L

    2010-01-01

    Abstract Tumour cells exploit both genetic and adaptive means to survive and proliferate in hypoxic microenvironments, resulting in the outgrowth of more aggressive tumour cell clones. Direct measurements of tumour oxygenation, and surrogate markers of the hypoxic response in tumours (for instance, hypoxia inducible factor-1α, carbonic anhydrase 9 and glucose transporter-1) are well-established prognostic markers in solid cancers. However, individual markers do not fully capture the complex, dynamic and heterogeneous hypoxic response in cancer. To overcome this, expression profiling has been employed to identify hypoxia signatures in cohorts or models of human cancer. Several of these hypoxia signatures have demonstrated prognostic significance in independent cancer datasets. Nevertheless, individual hypoxia markers have been shown to predict the benefit from hypoxia-modifying or anti-angiogenic therapies. This review aims to discuss the clinical impact of translational work on hypoxia markers and to explore future directions for research in this area. PMID:19840191

  11. Risk Prediction for Prostate Cancer Recurrence Through Regularized Estimation with Simultaneous Adjustment for Nonlinear Clinical Effects*

    PubMed Central

    Long, Qi; Chung, Matthias; Moreno, Carlos S.; Johnson, Brent A.

    2011-01-01

    In biomedical studies, it is of substantial interest to develop risk prediction scores using high-dimensional data such as gene expression data for clinical endpoints that are subject to censoring. In the presence of well-established clinical risk factors, investigators often prefer a procedure that also adjusts for these clinical variables. While accelerated failure time (AFT) models are a useful tool for the analysis of censored outcome data, it assumes that covariate effects on the logarithm of time-to-event are linear, which is often unrealistic in practice. We propose to build risk prediction scores through regularized rank estimation in partly linear AFT models, where high-dimensional data such as gene expression data are modeled linearly and important clinical variables are modeled nonlinearly using penalized regression splines. We show through simulation studies that our model has better operating characteristics compared to several existing models. In particular, we show that there is a non-negligible effect on prediction as well as feature selection when nonlinear clinical effects are misspecified as linear. This work is motivated by a recent prostate cancer study, where investigators collected gene expression data along with established prognostic clinical variables and the primary endpoint is time to prostate cancer recurrence. We analyzed the prostate cancer data and evaluated prediction performance of several models based on the extended c statistic for censored data, showing that 1) the relationship between the clinical variable, prostate specific antigen, and the prostate cancer recurrence is likely nonlinear, i.e., the time to recurrence decreases as PSA increases and it starts to level off when PSA becomes greater than 11; 2) correct specification of this nonlinear effect improves performance in prediction and feature selection; and 3) addition of gene expression data does not seem to further improve the performance of the resultant risk

  12. Validation Study: Response-Predictive Gene Expression Profiling of Glioma Progenitor Cells In Vitro

    PubMed Central

    Moeckel, Sylvia; Vollmann-Zwerenz, Arabel; Proescholdt, Martin; Brawanski, Alexander; Riemenschneider, Markus J.; Bogdahn, Ulrich; Bosserhoff, Anja-Katrin; Spang, Rainer; Hau, Peter

    2016-01-01

    Background In a previous publication we introduced a novel approach to identify genes that hold predictive information about treatment outcome. A linear regression model was fitted by using the least angle regression algorithm (LARS) with the expression profiles of a construction set of 18 glioma progenitor cells enhanced for brain tumor initiating cells (BTIC) before and after in vitro treatment with the tyrosine kinase inhibitor Sunitinib. Profiles from treated progenitor cells allowed predicting therapy-induced impairment of proliferation in vitro. Prediction performance was validated in leave one out cross validation. Methods In this study, we used an additional validation set of 18 serum-free short-term treated in vitro cell cultures to test the predictive properties of the signature in an independent cohort. We assessed proliferation rates together with transcriptome-wide expression profiles after Sunitinib treatment of each individual cell culture, following the methods of the previous publication. Results We confirmed treatment-induced expression changes in our validation set, but our signature failed to predict proliferation inhibition. Neither re-calculation of the combined dataset with all 36 BTIC cultures nor separation of samples into TCGA subclasses did generate a proliferation prediction. Conclusion Although the gene signature published from our construction set exhibited good prediction accuracy in cross validation, we were not able to validate the signature in an independent validation data set. Reasons could be regression to the mean, the moderate numbers of samples, or too low differences in the response to proliferation inhibition in the validation set. At this stage and based on the presented results, we conclude that the signature does not warrant further developmental steps towards clinical application. PMID:26978262

  13. Assessment of Predictive Markers for Placental Inflammatory Response in Preterm Births

    PubMed Central

    Kim, Min-A; Lee, You Sun; Seo, Kyung

    2014-01-01

    Placental inflammatory response (PIR) is associated with adverse neonatal outcomes such as sepsis, cerebral palsy, low birth weight, preterm birth, and neonatal mortality. However, there is an urgent need for noninvasive and sensitive biomarkers for prediction of PIR. In this study, we evaluated the clinical usefulness of maternal serum inflammatory markers for prediction of PIR in women with impending preterm birth. We conducted a retrospective cohort study of 483 patients who delivered preterm neonates. Serum levels of leukocyte differential counts, C-reactive protein (CRP), and neutrophil to lymphocyte ratio (NLR) were compared between women with no placental inflammation and women with PIR. The mean neutrophil counts, CRP levels, and NLR in both the patients with histologic chorioamnionitis (HCA) alone and those with HCA with funisitis were significantly higher than those in women with no placental inflammation. Compared to leukocyte subset or CRP, NLR in women with funisitis was significantly higher than in women with HCA alone and showed higher predictive accuracy, along with 71.4% sensitivity, 77.9% specificity, 80.7% positive predictive value, and 67.8% negative predictive value for prediction of PIR. On Kaplan-Meier survival analysis, women with both an elevated level of CRP and a high NLR had a shorter admission-to-delivery interval compared to women with either an elevated level of CRP or a high NLR alone. NLR may be a predictive marker of PIR and could be used as a cost-effective parameter for identifying women at risk of PIR. PMID:25291377

  14. Modified Logistic Regression Models Using Gene Coexpression and Clinical Features to Predict Prostate Cancer Progression

    PubMed Central

    Zhao, Hongya; Logothetis, Christopher J.; Gorlov, Ivan P.; Zeng, Jia; Dai, Jianguo

    2013-01-01

    Predicting disease progression is one of the most challenging problems in prostate cancer research. Adding gene expression data to prediction models that are based on clinical features has been proposed to improve accuracy. In the current study, we applied a logistic regression (LR) model combining clinical features and gene co-expression data to improve the accuracy of the prediction of prostate cancer progression. The top-scoring pair (TSP) method was used to select genes for the model. The proposed models not only preserved the basic properties of the TSP algorithm but also incorporated the clinical features into the prognostic models. Based on the statistical inference with the iterative cross validation, we demonstrated that prediction LR models that included genes selected by the TSP method provided better predictions of prostate cancer progression than those using clinical variables only and/or those that included genes selected by the one-gene-at-a-time approach. Thus, we conclude that TSP selection is a useful tool for feature (and/or gene) selection to use in prognostic models and our model also provides an alternative for predicting prostate cancer progression. PMID:24367394

  15. Appraisals and Responses to Experimental Symptom Analogues in Clinical and Nonclinical Individuals With Psychotic Experiences

    PubMed Central

    Ward, Thomas A.; Gaynor, Keith J.; Hunter, Mike D.; Woodruff, Peter W. R.; Garety, Philippa A.; Peters, Emmanuelle R.

    2014-01-01

    Objective: Cognitive models of psychosis suggest that anomalous experiences alone do not always lead to clinical psychosis, with appraisals and responses to experiences being central to understanding the transition to “need for care”. Methods: The appraisals and response styles of Clinical (C; n = 28) and Nonclinical (NC; n = 34) individuals with psychotic experiences were compared following experimental analogues of thought interference (Cards Task) and auditory hallucinations (Virtual Acoustic Space Paradigm). Results: The groups were matched in terms of their psychotic experiences. As predicted, the C group scored higher than the NC group on maladaptive appraisals following both tasks, rated the experience as more personally significant, and was more likely to incorporate the experimental setup into their ongoing experiences. The C group also appraised the Cards Task as more salient, distressing, and threatening; this group scored higher on maladaptive—and lower on adaptive—response styles, than the NC group on both tasks. Conclusions: The findings are consistent with cognitive models of psychosis, with maladaptive appraisals and response styles characterizing the C group only. Clinical applications of both tasks are suggested to facilitate the identification and modification of maladaptive appraisals. PMID:23858493

  16. Rapid-Response Impulsivity: Definitions, Measurement Issues, and Clinical Implications

    PubMed Central

    Hamilton, Kristen R.; Littlefield, Andrew K.; Anastasio, Noelle C.; Cunningham, Kathryn A.; Fink, Latham H.; Wing, Victoria C.; Mathias, Charles W.; Lane, Scott D.; Schutz, Christian; Swann, Alan C.; Lejuez, C.W.; Clark, Luke; Moeller, F. Gerard; Potenza, Marc N.

    2015-01-01

    Impulsivity is a multi-faceted construct that is a core feature of multiple psychiatric conditions and personality disorders. However, progress in understanding and treating impulsivity in the context of these conditions is limited by a lack of precision and consistency in its definition and assessment. Rapid-response-impulsivity (RRI) represents a tendency toward immediate action that occurs with diminished forethought and is out of context with the present demands of the environment. Experts from the International Society for Research on Impulsivity (InSRI) met to discuss and evaluate RRI-measures in terms of reliability, sensitivity, and validity with the goal of helping researchers and clinicians make informed decisions about the use and interpretation of findings from RRI-measures. Their recommendations are described in this manuscript. Commonly-used clinical and preclinical RRI-tasks are described, and considerations are provided to guide task selection. Tasks measuring two conceptually and neurobiologically distinct types of RRI, “refraining from action initiation” (RAI) and “stopping an ongoing action” (SOA) are described. RAI and SOA-tasks capture distinct aspects of RRI that may relate to distinct clinical outcomes. The InSRI group recommends that: 1) selection of RRI-measures should be informed by careful consideration of the strengths, limitations, and practical considerations of the available measures; 2) researchers use both RAI and SOA tasks in RRI studies to allow for direct comparison of RRI types and examination of their associations with clinically relevant measures; and, 3) similar considerations should be made for human and non-human studies in an effort to harmonize and integrate pre-clinical and clinical research. PMID:25867840

  17. Measures of endothelial dysfunction predict response to cardiac resynchronisation therapy

    PubMed Central

    Warriner, David R; Lawford, Patricia; Sheridan, Paul J

    2016-01-01

    Objectives Cardiac resynchronisation therapy (CRT) improves morbidity and mortality in heart failure (HF). Impaired endothelial function, as measured by flow-mediated dilation (FMD) is associated with increased morbidity and mortality in HF and may help to differentiate responders from non-responders. Methods 19 patients were recruited, comprising 94% men, mean age 69±8 years, New York Heart Association functional classes II–IV, QRSd 161±21 ms and mean left ventricular ejection fraction 26±8%. Markers of response and FMD were measured at baseline, 6 and 12 months following CRT. Results 14 patients were responders to CRT. Responders had significant improvements in VO2 (12.6±1.7 to 14.7±1.5 mL/kg/min, p<0.05), quality of life score (44.4±22.9–24.1±21.3, p<0.01), left ventricular end diastolic volume (201.5±72.5 mL–121.3±72.0 mL, p<0.01) and 6-min walk distance (374.0±112.8 m at baseline to 418.1±105.3 m, p<0.05). Baseline FMD in responders was 2.9±1.9% and 7.4±3.73% in non-responders (p<0.05). Conclusions Response to CRT at 6 and 12 months is predicted by baseline FMD. This study confirms that FMD identifies responders to CRT, due to endothelium-dependent mechanisms alone. PMID:27335654

  18. Predictive capacity of risk assessment scales and clinical judgment for pressure ulcers: a meta-analysis.

    PubMed

    García-Fernández, Francisco Pedro; Pancorbo-Hidalgo, Pedro L; Agreda, J Javier Soldevilla

    2014-01-01

    A systematic review with meta-analysis was completed to determine the capacity of risk assessment scales and nurses' clinical judgment to predict pressure ulcer (PU) development. Electronic databases were searched for prospective studies on the validity and predictive capacity of PUs risk assessment scales published between 1962 and 2010 in English, Spanish, Portuguese, Korean, German, and Greek. We excluded gray literature sources, integrative review articles, and retrospective or cross-sectional studies. The methodological quality of the studies was assessed according to the guidelines of the Critical Appraisal Skills Program. Predictive capacity was measured as relative risk (RR) with 95% confidence intervals. When 2 or more valid original studies were found, a meta-analysis was conducted using a random-effect model and sensitivity analysis. We identified 57 studies, including 31 that included a validation study. We also retrieved 4 studies that tested clinical judgment as a risk prediction factor. Meta-analysis produced the following pooled predictive capacity indicators: Braden (RR = 4.26); Norton (RR = 3.69); Waterlow (RR = 2.66); Cubbin-Jackson (RR = 8.63); EMINA (RR = 6.17); Pressure Sore Predictor Scale (RR = 21.4); and clinical judgment (RR = 1.89). Pooled analysis of 11 studies found adequate risk prediction capacity in various clinical settings; the Braden, Norton, EMINA (mEntal state, Mobility, Incontinence, Nutrition, Activity), Waterlow, and Cubbin-Jackson scales showed the highest predictive capacity. The clinical judgment of nurses was found to achieve inadequate predictive capacity when used alone, and should be used in combination with a validated scale. PMID:24280770

  19. Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study

    PubMed Central

    2013-01-01

    Background Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical prediction models for BPD. Methods We searched the main electronic databases and abstracts from annual meetings. The STROBE instrument was used to assess the methodological quality. External validation of the retrieved models was performed using an individual patient dataset of 3229 patients at risk for BPD. Receiver operating characteristic curves were used to assess discrimination for each model by calculating the area under the curve (AUC). Calibration was assessed for the best discriminating models by visually comparing predicted and observed BPD probabilities. Results We identified 26 clinical prediction models for BPD. Although the STROBE instrument judged the quality from moderate to excellent, only four models utilised external validation and none presented calibration of the predictive value. For 19 prediction models with variables matched to our dataset, the AUCs ranged from 0.50 to 0.76 for the outcome BPD. Only two of the five best discriminating models showed good calibration. Conclusions External validation demonstrates that, except for two promising models, most existing clinical prediction models are poor to moderate predictors for BPD. To improve the predictive accuracy and identify preterm infants for future intervention studies aiming to reduce the risk of BPD, additional variables are required. Subsequently, that model should be externally validated using a proper impact analysis before its clinical implementation. PMID:24345305

  20. [Responsible dealing with sexuality. Recommendations in a clinical institution].

    PubMed

    Steinberg, R; Rittner, C; Dormann, S; Spengler-Katerndahl, D

    2012-03-01

    Sexuality is excluded in house regulations, guidelines, instructions and regulations in German hospitals. The English literature does not show much more, but more often the wish for clear guidelines is formulated. Under the guidance of the clinical Ethics Committee a paper with recommendations was prepared, which comprises regulations for responsible handling of sexuality in the Pfalzklinikum. This includes sexuality of acute patients in psychiatry, nursing home inhabitants, forensic patients and above all patients in the department of child and youth psychiatry. The right of self-realization on the one hand, the staff's responsibility for patients with limitations in the determination of one's intent on the other hand and the rules for staff members define the range of the paper. PMID:21607802

  1. Use of clinical movement screening tests to predict injury in sport

    PubMed Central

    Chimera, Nicole J; Warren, Meghan

    2016-01-01

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention, and prevention. This editorial will review the following clinical movement screening tests: Functional Movement Screen™, Star Excursion Balance Test, Y Balance Test, Drop Jump Screening Test, Landing Error Scoring System, and the Tuck Jump Analysis in regards to test administration, reliability, validity, factors that affect test performance, intervention programs, and usefulness for injury prediction. It is important to review the aforementioned factors for each of these clinical screening tests as this may help clinicians interpret the current body of literature. While each of these screening tests were developed by clinicians based on what appears to be clinical practice, this paper brings to light that this is a need for collaboration between clinicians and researchers to ensure validity of clinically meaningful tests so that they are used appropriately in future clinical practice. Further, this editorial may help to identify where the research is lacking and, thus, drive future research questions in regards to applicability and appropriateness of clinical movement screening tools. PMID:27114928

  2. Use of clinical movement screening tests to predict injury in sport.

    PubMed

    Chimera, Nicole J; Warren, Meghan

    2016-04-18

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention, and prevention. This editorial will review the following clinical movement screening tests: Functional Movement Screen™, Star Excursion Balance Test, Y Balance Test, Drop Jump Screening Test, Landing Error Scoring System, and the Tuck Jump Analysis in regards to test administration, reliability, validity, factors that affect test performance, intervention programs, and usefulness for injury prediction. It is important to review the aforementioned factors for each of these clinical screening tests as this may help clinicians interpret the current body of literature. While each of these screening tests were developed by clinicians based on what appears to be clinical practice, this paper brings to light that this is a need for collaboration between clinicians and researchers to ensure validity of clinically meaningful tests so that they are used appropriately in future clinical practice. Further, this editorial may help to identify where the research is lacking and, thus, drive future research questions in regards to applicability and appropriateness of clinical movement screening tools. PMID:27114928

  3. Clinical Informatics Board Certification: History, Current Status, and Predicted Impact on the Clinical Informatics Workforce

    PubMed Central

    Detmer, Don E.; Munger, Benson S.; Lehmann, Christoph U.

    2010-01-01

    Within health and health care, medical informatics and its subspecialties of biomedical, clinical, and public health informatics have emerged as a new discipline with increasing demands for its own work force. Knowledge and skills in medical informatics are widely acknowledged as crucial to future success in patient care, research relating to biomedicine, clinical care, and public health, as well as health policy design. The maturity of the domain and the demand on expertise necessitate standardized training and certification of professionals. The American Medical Informatics Association (AMIA) embarked on a major effort to create professional level education and certification for physicians of various professions and specialties in informatics. This article focuses on the AMIA effort in the professional structure of medical specialization, e.g., the American Board of Medical Specialties (ABMS) and the related Accreditation Council for Graduate Medical Education (ACGME). This report summarizes the current progress to create a recognized sub-certificate of competence in Clinical Informatics and discusses likely near term (three to five year) implications on training, certification, and work force with an emphasis on clinical applied informatics. PMID:23616825

  4. Computer-aided breast MR image feature analysis for prediction of tumor response to chemotherapy

    SciTech Connect

    Aghaei, Faranak; Tan, Maxine; Liu, Hong; Zheng, Bin; Hollingsworth, Alan B.; Qian, Wei

    2015-11-15

    Purpose: To identify a new clinical marker based on quantitative kinetic image features analysis and assess its feasibility to predict tumor response to neoadjuvant chemotherapy. Methods: The authors assembled a dataset involving breast MR images acquired from 68 cancer patients before undergoing neoadjuvant chemotherapy. Among them, 25 patients had complete response (CR) and 43 had partial and nonresponse (NR) to chemotherapy based on the response evaluation criteria in solid tumors. The authors developed a computer-aided detection scheme to segment breast areas and tumors depicted on the breast MR images and computed a total of 39 kinetic image features from both tumor and background parenchymal enhancement regions. The authors then applied and tested two approaches to classify between CR and NR cases. The first one analyzed each individual feature and applied a simple feature fusion method that combines classification results from multiple features. The second approach tested an attribute selected classifier that integrates an artificial neural network (ANN) with a wrapper subset evaluator, which was optimized using a leave-one-case-out validation method. Results: In the pool of 39 features, 10 yielded relatively higher classification performance with the areas under receiver operating characteristic curves (AUCs) ranging from 0.61 to 0.78 to classify between CR and NR cases. Using a feature fusion method, the maximum AUC = 0.85 ± 0.05. Using the ANN-based classifier, AUC value significantly increased to 0.96 ± 0.03 (p < 0.01). Conclusions: This study demonstrated that quantitative analysis of kinetic image features computed from breast MR images acquired prechemotherapy has potential to generate a useful clinical marker in predicting tumor response to chemotherapy.

  5. Development and Validation of a Gene Expression Score That Predicts Response to Fulvestrant in Breast Cancer Patients

    PubMed Central

    Knudsen, Steen; Jensen, Thomas; Hansen, Anker; Mazin, Wiktor; Lindemann, Justin; Kuter, Irene; Laing, Naomi; Anderson, Elizabeth

    2014-01-01

    Fulvestrant is a selective estrogen receptor antagonist. Based on the measured growth inhibition of 60 human cancer cell lines (NCI60) in the presence of fulvestrant, as well as the baseline gene expression of the 60 cell lines, a gene expression score that predicts response to fulvestrant was developed. The score is based on 414 genes, 103 of which show increased expression in sensitive cell lines, while 311 show increased expression in the non-responding cell lines. The sensitivity genes primarily sense signaling through estrogen receptor alpha, whereas the resistance genes modulate the PI3K signaling pathway. The latter genes suggest that resistance to fulvestrant can be overcome by drugs targeting the PI3K pathway. The level of this gene expression score and its correlation with fulvestrant response was measured in a panel of 20 breast cancer cell lines. The predicted sensitivity matched the measured sensitivity well (CC = −0.63, P = 0.003). The predictor was applied to tumor biopies obtained from a Phase II clinical trial. The sensitivity of each patient to treatment with fulvestrant was predicted based on the RNA profile of the biopsy taken before neoadjuvant treatment and without knowledge of the subsequent response. The prediction was then compared to clinical response to show that the responders had a significantly higher sensitivity prediction than the non-responders (P = 0.01). When clinical covariates, tumor grade and estrogen receptor H-score, were included in the prediction, the difference in predicted senstivity between responders and non-responders improved (P = 0.003). Using a pre-defined cutoff to separate patients into predicted sensitive and predicted resistant yielded a positive predictive value of 88% and a negative predictive value of 100% when compared to clinical data. We conclude that pre-screening patients with the new gene expression predictor has the potential to identify those postmenopausal women with locally

  6. BIM expression in treatment naïve cancers predicts responsiveness to kinase inhibitors

    PubMed Central

    Faber, Anthony; Corcoran, Ryan B.; Ebi, Hiromichi; Sequist, Lecia V.; Waltman, Belinda A.; Chung, Euiheon; Incio, Joao; Digumarthy, Subba R.; Pollack, Sarah F.; Song, Youngchul; Muzikansky, Alona; Lifshits, Eugene; Roberge, Sylvie; Coffman, Erik J.; Benes, Cyril; Gómez, Henry; Baselga, Jose; Arteaga, Carlos L.; Rivera, Miguel N.; Dias-Santagata, Dora; Jain, Rakesh K.; Engelman, Jeffrey A.

    2011-01-01

    Cancers with specific genetic mutations are susceptible to selective kinase inhibitors. However, there is wide spectrum of benefit among cancers harboring the same sensitizing genetic mutations. Herein, we measured apoptotic rates among cell lines sharing the same driver oncogene following treatment with the corresponding kinase inhibitor. There was a wide range of kinase inhibitor-induced apoptosis despite comparable inhibition of the target and associated downstream signaling pathways. Surprisingly, pre-treatment RNA levels of the BH3-only pro-apoptotic BIM strongly predicted the capacity of EGFR, HER2, and PI3K inhibitors to induce apoptosis in EGFR mutant, HER2 amplified, and PIK3CA mutant cancers, respectively, but BIM levels did not predict responsiveness to standard chemotherapies. Furthermore, BIM RNA levels in EGFR mutant lung cancer specimens predicted response and duration of clinical benefit from EGFR inhibitors. These findings suggest assessment of BIM levels in treatment naïve tumor biopsies may indicate the degree of benefit from single-agent kinase inhibitors in multiple oncogene-addiction paradigms. PMID:22145099

  7. Can Nutritional Assessment Tools Predict Response to Nutritional Therapy?

    PubMed

    Patel, Chirag; Omer, Endashaw; Diamond, Sarah J; McClave, Stephen A

    2016-04-01

    Traditional tools and scoring systems for nutritional assessment have focused solely on parameters of poor nutritional status in the past, in an effort to define the elusive concept of malnutrition. Such tools fail to account for the contribution of disease severity to overall nutritional risk. High nutritional risk, caused by either deterioration of nutritional status or greater disease severity (or a combination of both factors), puts the patient in a metabolic stress state characterized by adverse outcome and increased complications. Newer scoring systems for determining nutritional risk, such as the Nutric Score and the Nutritional Risk Score-2002 have created a paradigm shift connecting assessment and treatment with quality outcome measures of success. Clinicians now have the opportunity to identify high risk patients through their initial assessment, provide adequate or sufficient nutrition therapy, and expect improved patient outcomes as a result. These concepts are supported by observational and prospective interventional trials. Greater clinical experience and refinement in these scoring systems are needed in the future to optimize patient response to nutrition therapy. PMID:26936031

  8. Predicting the asymmetric response of a genetic switch to noise.

    PubMed

    Ochab-Marcinek, Anna

    2008-09-01

    We present a simple analytical tool which gives an approximate insight into the stationary behavior of nonlinear systems undergoing the influence of a weak and rapid noise from one dominating source, e.g. the kinetic equations describing a genetic switch with the concentration of one substrate fluctuating around a constant mean. The proposed method allows for predicting the asymmetric response of the genetic switch to noise, arising from the noise-induced shift of stationary states. The method has been tested on an example model of the lac operon regulatory network: a reduced Yildirim-Mackey model with fluctuating extracellular lactose concentration. We calculate analytically the shift of the system's stationary states in the presence of noise. The results of the analytical calculation are in excellent agreement with the results of numerical simulation of the noisy system. The simulation results suggest that the structure of the kinetics of the underlying biochemical reactions protects the bistability of the lactose utilization mechanism from environmental fluctuations. We show that, in the consequence of the noise-induced shift of stationary states, the presence of fluctuations stabilizes the behavior of the system in a selective way: Although the extrinsic noise facilitates, to some extent, switching off the lactose metabolism, the same noise prevents it from switching on. PMID:18554612

  9. Key clinical considerations for demonstrating the utility of preclinical models to predict clinical drug-induced torsades de pointes

    PubMed Central

    Sager, P T

    2008-01-01

    While the QT/QTc interval is currently the best available clinical surrogate for the development of drug-induced torsades de pointes, it is overall an imperfect biomarker. In addition to low specificity for predicting arrhythmias, other issues relevant to using QT as a biomarker include (1) an apparent dissociation, for some drugs (for example, amiodarone, sodium pentobarbital, ranolazine) between QT/QTc interval prolongation and TdP risk, (2) Lack of clarity regarding what determines the relationship between QTc prolongation and TdP risk for an individual drug, (3) QT measurement issues, including effects of heart rate and autonomic perturbations, (4) the significant circadian changes to the QT/QTc interval and (5) concerns that the development, regulatory and commercial implications of finding even a mild QT prolongation effect during clinical development has significant impact the pharmaceutical discovery pipeline. These issues would be significantly reduced, clinical development simplified and marketing approval for some drugs might be accelerated if there were a battery of preclinical tests that could reliably predict a drug's propensity to cause TdP in humans, even in the presence of QTc interval prolongation. This approach is challenging and for it to be acceptable to pharmaceutical developers, the scientific community and regulators, it would need to be scientifically well validated. A very high-negative predictive value demonstrated in a wide range of drugs with different ionic effects would be critical. This manuscript explores the issues surrounding the use of QT as a clinical biomarker and potential approaches for validating preclinical assays for this purpose against clinical data sets. PMID:18536754

  10. Key clinical considerations for demonstrating the utility of preclinical models to predict clinical drug-induced torsades de pointes.

    PubMed

    Sager, P T

    2008-08-01

    While the QT/QTc interval is currently the best available clinical surrogate for the development of drug-induced torsades de pointes, it is overall an imperfect biomarker. In addition to low specificity for predicting arrhythmias, other issues relevant to using QT as a biomarker include (1) an apparent dissociation, for some drugs (for example, amiodarone, sodium pentobarbital, ranolazine) between QT/QTc interval prolongation and TdP risk, (2) Lack of clarity regarding what determines the relationship between QTc prolongation and TdP risk for an individual drug, (3) QT measurement issues, including effects of heart rate and autonomic perturbations, (4) the significant circadian changes to the QT/QTc interval and (5) concerns that the development, regulatory and commercial implications of finding even a mild QT prolongation effect during clinical development has significant impact the pharmaceutical discovery pipeline. These issues would be significantly reduced, clinical development simplified and marketing approval for some drugs might be accelerated if there were a battery of preclinical tests that could reliably predict a drug's propensity to cause TdP in humans, even in the presence of QTc interval prolongation. This approach is challenging and for it to be acceptable to pharmaceutical developers, the scientific community and regulators, it would need to be scientifically well validated. A very high-negative predictive value demonstrated in a wide range of drugs with different ionic effects would be critical. This manuscript explores the issues surrounding the use of QT as a clinical biomarker and potential approaches for validating preclinical assays for this purpose against clinical data sets. PMID:18536754

  11. Acute Pelvic Inflammatory Disease and Clinical Response to Parenteral Doxycycline

    PubMed Central

    Chow, Anthony W.; Malkasian, Kay L.; Marshall, John R.; Guze, Lucien B.

    1975-01-01

    The bacteriology of acute pelvic inflammatory disease (PID) and clinical response to parenteral doxycycline were evaluated in 30 patients. Only 3 of 21 cul-de-sac cultures from PID patients were sterile, whereas all 8 normal control subjects yielded negative results (P< 0.005). Poor correlation was observed between cervical and cul-de-sac cultures. Neisseria gonorrhoeae, isolated from the cervix in 17 patients (57%), was recovered from the cul-de-sac only once. Streptococcus, Peptococcus, Peptostreptococcus, coliforms, and other organisms normally present in the vagina were the predominant isolates recovered from the cul-de-sac. Parenteral doxycycline resulted in rapid resolution of signs and symptoms (within 48 h) in 20 of 27 evaluable patients (74%). In five others, signs and symptoms of infection abated within 4 days. The remaining two patients failed to respond; in both cases, adnexal masses developed during doxycycline therapy. Gonococci were eradicated from the cervix in all but one patient who, nevertheless, had a rapid defervescence of symptoms. There was no clear-cut correlation between the clinical response and in vitro susceptibility of cul-de-sac isolates to doxycycline. These data confirm the usefulness of broad-spectrum antibiotics in acute PID. Culdocentesis is a reliable means of obtaining material for the bacteriological diagnosis of acute PID; however, the pathogenetic role and relative importance of gonococci and various other bacteria in acute PID need to be clarified further. PMID:1169908

  12. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.

    PubMed

    Sieberts, Solveig K; Zhu, Fan; García-García, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornés, Oriol; Guney, Emre; Li, Hongdong; Marín, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S K; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-Ud-Din, Muhammad; Azencott, Chloe-Agathe; Bellón, Víctor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R; Marttinen, Pekka; Mezlini, Aziz M; Molparia, Bhuvan; Pirinen, Matti; Saarela, Janna; Samwald, Matthias; Stoven, Véronique; Tang, Hao; Tang, Jing; Torkamani, Ali; Vert, Jean-Phillipe; Wang, Bo; Wang, Tao; Wennerberg, Krister; Wineinger, Nathan E; Xiao, Guanghua; Xie, Yang; Yeung, Rae; Zhan, Xiaowei; Zhao, Cheng; Greenberg, Jeff; Kremer, Joel; Michaud, Kaleb; Barton, Anne; Coenen, Marieke; Mariette, Xavier; Miceli, Corinne; Shadick, Nancy; Weinblatt, Michael; de Vries, Niek; Tak, Paul P; Gerlag, Danielle; Huizinga, Tom W J; Kurreeman, Fina; Allaart, Cornelia F; Louis Bridges, S; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M; Bridges, S Louis; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M

    2016-01-01

    Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2)=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data. PMID:27549343

  13. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

    PubMed Central

    Sieberts, Solveig K.; Zhu, Fan; García-García, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornés, Oriol; Guney, Emre; Li, Hongdong; Marín, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O.; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S. K.; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-ud-din, Muhammad; Azencott, Chloe-Agathe; Bellón, Víctor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R.; Marttinen, Pekka; Mezlini, Aziz M.; Molparia, Bhuvan; Pirinen, Matti; Saarela, Janna; Samwald, Matthias; Stoven, Véronique; Tang, Hao; Tang, Jing; Torkamani, Ali; Vert, Jean-Phillipe; Wang, Bo; Wang, Tao; Wennerberg, Krister; Wineinger, Nathan E.; Xiao, Guanghua; Xie, Yang; Yeung, Rae; Zhan, Xiaowei; Zhao, Cheng; Calaza, Manuel; Elmarakeby, Haitham; Heath, Lenwood S.; Long, Quan; Moore, Jonathan D.; Opiyo, Stephen Obol; Savage, Richard S.; Zhu, Jun; Greenberg, Jeff; Kremer, Joel; Michaud, Kaleb; Barton, Anne; Coenen, Marieke; Mariette, Xavier; Miceli, Corinne; Shadick, Nancy; Weinblatt, Michael; de Vries, Niek; Tak, Paul P.; Gerlag, Danielle; Huizinga, Tom W. J.; Kurreeman, Fina; Allaart, Cornelia F.; Louis Bridges Jr., S.; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K.; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M.; Bridges, S. Louis; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K.; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M.

    2016-01-01

    Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data. PMID:27549343

  14. Clinical iron deficiency disturbs normal human responses to hypoxia

    PubMed Central

    Frise, Matthew C.; Cheng, Hung-Yuan; Nickol, Annabel H.; Curtis, M. Kate; Pollard, Karen A.; Roberts, David J.; Ratcliffe, Peter J.; Dorrington, Keith L.; Robbins, Peter A.

    2016-01-01

    BACKGROUND. Iron bioavailability has been identified as a factor that influences cellular hypoxia sensing, putatively via an action on the hypoxia-inducible factor (HIF) pathway. We therefore hypothesized that clinical iron deficiency would disturb integrated human responses to hypoxia. METHODS. We performed a prospective, controlled, observational study of the effects of iron status on hypoxic pulmonary hypertension. Individuals with absolute iron deficiency (ID) and an iron-replete (IR) control group were exposed to two 6-hour periods of isocapnic hypoxia. The second hypoxic exposure was preceded by i.v. infusion of iron. Pulmonary artery systolic pressure (PASP) was serially assessed with Doppler echocardiography. RESULTS. Thirteen ID individuals completed the study and were age- and sex-matched with controls. PASP did not differ by group or study day before each hypoxic exposure. During the first 6-hour hypoxic exposure, the rise in PASP was 6.2 mmHg greater in the ID group (absolute rises 16.1 and 10.7 mmHg, respectively; 95% CI for difference, 2.7–9.7 mmHg, P = 0.001). Intravenous iron attenuated the PASP rise in both groups; however, the effect was greater in ID participants than in controls (absolute reductions 11.1 and 6.8 mmHg, respectively; 95% CI for difference in change, –8.3 to –0.3 mmHg, P = 0.035). Serum erythropoietin responses to hypoxia also differed between groups. CONCLUSION. Clinical iron deficiency disturbs normal responses to hypoxia, as evidenced by exaggerated hypoxic pulmonary hypertension that is reversed by subsequent iron administration. Disturbed hypoxia sensing and signaling provides a mechanism through which iron deficiency may be detrimental to human health. TRIAL REGISTRATION. ClinicalTrials.gov (NCT01847352). FUNDING. M.C. Frise is the recipient of a British Heart Foundation Clinical Research Training Fellowship (FS/14/48/30828). K.L. Dorrington is supported by the Dunhill Medical Trust (R178/1110). D.J. Roberts was

  15. Predicting 6-week treatment response to escitalopram pharmacotherapy in late-life major depressive disorder

    PubMed Central

    Saghafi, Ramin; Brown, Charlotte; Butters, Meryl A.; Cyranowski, Jill; Dew, Mary Amanda; Frank, Ellen; Gildengers, Ariel; Karp, Jordan F.; Lenze, Eric J.; Lotrich, Francis; Martire, Lynn; Mazumdar, Sati; Miller, Mark D.; Mulsant, Benoit H.; Weber, Elizabeth; Whyte, Ellen; Morse, Jennifer; Stack, Jacqueline; Houck, Patricia R.; Bensasi, Salem; Reynolds, Charles F.

    2013-01-01

    SUMMARY Objective Approximately half of older patients treated for major depressive disorder (MDD) do not achieve symptomatic remission and functional recovery with first-line pharmacotherapy. This study aims to characterize sociodemographic, clinical, and neuropsychologic correlates of full, partial, and non-response to escitalopram monotherapy of unipolar MDD in later life. Methods One hundred and seventy-five patients aged 60 and older were assessed at baseline on demographic variables, depression severity, hopelessness, anxiety, cognitive functioning, co-existing medical illness burden, social support, and quality of life (disability). Subjects received 10 mg/d of open-label escitalopram and were divided into full (n =55; 31%), partial (n =75; 42.9%), and non-responder (n =45; 25.7%) groups based on Hamilton depression scores at week 6. Univariate followed by multivariate analyses tested for differences between the three groups. Results Non-responders to treatment were found to be more severely depressed and anxious at baseline than both full and partial responders, more disabled, and with lower self-esteem than full responders. In general partial responders resembled full responders more than they resembled non-responders. In multivariate models, more severe anxiety symptoms (both psychological and somatic) and lower self-esteem predicted worse response status at 6 weeks. Conclusion Among treatment-seeking elderly persons with MDD, higher anxiety symptoms and lower self-esteem predict poorer response after six weeks of escitalopram treatment. PMID:17486678

  16. Nurse-Administered, Gut-Directed Hypnotherapy in IBS: Efficacy and Factors Predicting a Positive Response.

    PubMed

    Lövdahl, Jenny; Ringström, Gisela; Agerforz, Pia; Törnblom, Hans; Simrén, Magnus

    2015-07-01

    Hypnotherapy is an effective treatment in irritable bowel syndrome (IBS). It is often delivered by a psychotherapist and is costly and time consuming. Nurse-administered hypnotherapy could increase availability and reduce costs. In this study the authors evaluate the effectiveness of nurse-administered, gut-directed hypnotherapy and identify factors predicting treatment outcome. Eighty-five patients were included in the study. Participants received hypnotherapy by a nurse once/week for 12 weeks. Patients reported marked improvement in gastrointestinal (GI) and extra-colonic symptoms after treatment, as well as a reduction in GI-specific anxiety, general anxiety, and depression. Fifty-eight percent were responders after the 12 weeks treatment period, and of these 82% had a favorable clinical response already at week 6. Women were more likely than men to respond favorably to the treatment. Nurse-administered hypnotherapy is an effective treatment for IBS. Being female and reporting a favorable response to treatment by week 6 predicted a positive treatment response at the end of the 12 weeks treatment period. PMID:26046719

  17. Prediction of delayed treatment response in pulmonary tuberculosis: use of time to positivity values of Bactec cultures.

    PubMed

    Carroll, N M; Uys, P; Hesseling, A; Lawrence, K; Pheiffer, C; Salker, F; Duncan, K; Beyers, N; van Helden, P D

    2008-11-01

    New drugs that can shorten tuberculosis (TB) treatment and target drug resistant strains are urgently needed. A test which could predict patients at risk of a delayed response to treatment would facilitate clinical trials of new anti-tuberculosis drugs. A widely-used test for the assessment of response to treatment is sputum smear examination. Patients who are smear positive after 2 and 3 months of treatment are said to have delayed and significantly delayed treatment responses respectively. Time to positivity (TTP) values of Bactec cultures, from the first 2 weeks of treatment were used to predict delayed and significantly delayed treatment responses in patients with first time pulmonary tuberculosis. Changes in TTP values early in treatment were transformed to a response ratio (r). Values of r that were less than a threshold value (r(c)) indicated patients who were at risk of having delayed or significantly delayed response to treatment. Accuracy of prediction was sensitive to the timing of sputum sampling and adherence to therapy in the first 2 weeks. Based on TTP data from the first 2 weeks of treatment, significantly delayed treatment response could be predicted with a sensitivity of 75% and a specificity of 62% while the positive (PPV) and negative predictive values (NPV) were 14% and 97% respectively. While the high NPV indicates that a large proportion of patients with a satisfactory response to treatment can be reliably identified, the low PPV value underlines the need to use TTP in conjunction with other markers of disease activity to predict unfavourable treatment response in tuberculosis treatment. PMID:18456556

  18. Comparison of MCNPX and Geant4 proton energy deposition predictions for clinical use

    PubMed Central

    Titt, U.; Bednarz, B.; Paganetti, H.

    2012-01-01

    Several different Monte Carlo codes are currently being used at proton therapy centers to improve upon dose predictions over standard methods using analytical or semi-empirical dose algorithms. There is a need to better ascertain the differences between proton dose predictions from different available Monte Carlo codes. In this investigation Geant4 and MCNPX, the two most-utilized Monte Carlo codes for proton therapy applications, were used to predict energy deposition distributions in a variety of geometries, comprising simple water phantoms, water phantoms with complex inserts and in a voxelized geometry based on clinical CT data. The gamma analysis was used to evaluate the differences of the predictions between the codes. The results show that in the all cases the agreement was better than clinical acceptance criteria. PMID:22996039

  19. Bridging the Gap: Moving Predictive and Prognostic Assays from Research to Clinical Use

    PubMed Central

    Williams, P. Michael; Lively, Tracy G.; Jessup, J. Milburn; Conley, Barbara A.

    2012-01-01

    The development of clinically useful molecular diagnostics requires validation of clinical assay performance and achievement of clinical qualification in clinical trials. As discussed elsewhere in this Focus Section on Molecular Diagnostics, validation of assay performance must be rigorous especially when the assay will be used to guide treatment decisions. Here we review some of the problems or hurdles associated with assay development, especially for academic investigators. These include lack of expertise and resources for analytical validation, lack of experience in project design for a specific clinical use, lack of specimens from appropriate patient groups, and lack of access to Clinical Laboratory Improvement Act (CLIA) certified laboratories. In addition, financial support for assay validation has lagged behind financial support for marker discovery or drug development, even though the molecular diagnostic may be considered necessary for the successful use of the companion therapeutic. The National Cancer Institute supports a large number of clinical trials and a significant effort in drug development. In order to address some of these barriers for predictive and prognostic assays that will be used in clinical trials to select patients for a particular treatment, stratify patients into molecularly defined subgroups, or choose between treatments for molecularly defined tumors, the National Cancer Institute (NCI) has begun a pilot program designed to lessen barriers to the development of validated prognostic and predictive assays. PMID:22422405

  20. A Probabilistic Reasoning Method for Predicting the Progression of Clinical Findings from Electronic Medical Records

    PubMed Central

    Goodwin, Travis; Harabagiu, Sanda M.

    2015-01-01

    In this paper, we present a probabilistic reasoning method capable of generating predictions of the progression of clinical findings (CFs) reported in the narrative portion of electronic medical records. This method benefits from a probabilistic knowledge representation made possible by a graphical model. The knowledge encoded in the graphical model considers not only the CFs extracted from the clinical narratives, but also their chronological ordering (CO) made possible by a temporal inference technique described in this paper. Our experiments indicate that the predictions about the progression of CFs achieve high performance given the COs induced from patient records. PMID:26306238

  1. Translational potential of a mouse in vitro bioassay in predicting gastrointestinal adverse drug reactions in Phase I clinical trials

    PubMed Central

    Keating, C; Ewart, L; Grundy, L; Valentin, JP; Grundy, D

    2014-01-01

    Background Motility-related gastrointestinal (GI) adverse drug reactions (GADRs) such as diarrhea and constipation are a common and deleterious feature associated with drug development. Novel biomarkers of GI function are therefore required to aid decision making on the GI liability of compounds in development. Methods Fifteen compounds associated with or without clinical GADRs were used to assess the ability of an in vitro colonic motility bioassay to predict motility-related GADRs. Compounds were examined in a blinded fashion for their effects on mouse colonic peristaltic motor complexes in vitro. For each compound concentration-response relationships were determined and the results compared to clinical data. Compounds were also assessed using GI transit measurements obtained using an in vivo rat charcoal meal model. Key Results Within a clinically relevant dosing range, the in vitro assay identified five true and three false positives, four true and three false negatives, which gave a predictive capacity of 60%. The in vivo assay detected four true and four false positives, four false and three true negatives, giving rise to a predictive capacity for this model of 47%. Conclusions & Inferences Overall these results imply that both assays are poor predictors of GADRs. Further analysis would benefit from a larger compound set, but the data show a clear need for improved models for use in safety pharmacology assessment of GI motility. PMID:24813024

  2. An Endotoxin Tolerance Signature Predicts Sepsis and Organ Dysfunction at Initial Clinical Presentation

    PubMed Central

    Pena, Olga M.; Hancock, David G.; Lyle, Ngan H.; Linder, Adam; Russell, James A.; Xia, Jianguo; Fjell, Christopher D.; Boyd, John H.; Hancock, Robert E.W.

    2014-01-01

    Background Sepsis involves aberrant immune responses to infection, but the exact nature of this immune dysfunction remains poorly defined. Bacterial endotoxins like lipopolysaccharide (LPS) are potent inducers of inflammation, which has been associated with the pathophysiology of sepsis, but repeated exposure can also induce a suppressive effect known as endotoxin tolerance or cellular reprogramming. It has been proposed that endotoxin tolerance might be associated with the immunosuppressive state that was primarily observed during late-stage sepsis. However, this relationship remains poorly characterised. Here we clarify the underlying mechanisms and timing of immune dysfunction in sepsis. Methods We defined a gene expression signature characteristic of endotoxin tolerance. Gene-set test approaches were used to correlate this signature with early sepsis, both newly and retrospectively analysing microarrays from 593 patients in 11 cohorts. Then we recruited a unique cohort of possible sepsis patients at first clinical presentation in an independent blinded controlled observational study to determine whether this signature was associated with the development of confirmed sepsis and organ dysfunction. Findings All sepsis patients presented an expression profile strongly associated with the endotoxin tolerance signature (p < 0.01; AUC 96.1%). Importantly, this signature further differentiated between suspected sepsis patients who did, or did not, go on to develop confirmed sepsis, and predicted the development of organ dysfunction. Interpretation Our data support an updated model of sepsis pathogenesis in which endotoxin tolerance-mediated immune dysfunction (cellular reprogramming) is present throughout the clinical course of disease and related to disease severity. Thus endotoxin tolerance might offer new insights guiding the development of new therapies and diagnostics for early sepsis. PMID:25685830

  3. Dendritic Cell Responses to Surface Properties of Clinical Titanium Surfaces

    PubMed Central

    Kou, Peng Meng; Schwartz, Zvi; Boyan, Barbara D.

    2010-01-01

    Dendritic cells (DCs) play pivotal roles in responding to foreign entities during an innate immune response and initiating effective adaptive immunity as well as maintaining immune tolerance. The sensitivity of DCs to foreign stimuli also makes them useful cells to assess the inflammatory response to biomaterials. Elucidating the material property-DC phenotype relationships using a well-defined biomaterial system is expected to provide criteria for immuno-modulatory biomaterial design. Clinical titanium (Ti) substrates, including pretreatment (PT), sand-blasted and acid-etched (SLA), and modified SLA (modSLA), with different roughness and surface energy were used to treat DCs and resulted in differential DC responses. PT and SLA induced a mature DC (mDC) phenotype, while modSLA promoted a non-inflammatory environment by supporting an immature DC (iDC) phenotype based on surface marker expression, cytokine production profiles and cell morphology. Principal component analysis (PCA) confirmed these experimental results, and it also indicated that the non-stimulating property of modSLA covaried with certain surface properties, such as high surface hydrophilicity, % oxygen and % Ti of the substrates. In addition to the previous research that demonstrated the superior osteogenic property of modSLA compared to PT and SLA, the result reported herein indicates that modSLA may further benefit implant osteo-integration by reducing local inflammation and its associated osteoclastogenesis. PMID:20977948

  4. Upper esophageal sphincter abnormalities are strongly predictive of treatment response in patients with achalasia

    PubMed Central

    Mathews, Simon C; Ciarleglio, Maria; Chavez, Yamile Haito; Clarke, John O; Stein, Ellen; Chander Roland, Bani

    2014-01-01

    AIM: To investigate the relationship between upper esophageal sphincter abnormalities achalasia treatment METHODS: We performed a retrospective study of 41 consecutive patients referred for high resolution esophageal manometry with a final manometric diagnosis of achalasia. Patients were sub-divided by presence or absence of Upper esophageal sphincter (UES) abnormality, and clinical and manometric profiles were compared. Correlation between UES abnormality and sub-type (i.e., hypertensive, hypotensive or impaired relaxation) and a number of variables, including qualitative treatment response, achalasia sub-type, co-morbid medical illness, psychiatric illness, surgical history, dominant presenting symptom, treatment type, age and gender were also evaluated. RESULTS: Among all 41 patients, 24 (58.54%) had a UES abnormality present. There were no significant differences between the groups in terms of age, gender or any other clinical or demographic profiles. Among those with UES abnormalities, the majority were either hypertensive (41.67%) or had impaired relaxation (37.5%) as compared to hypotensive (20.83%), although this did not reach statistical significance (P = 0.42). There was no specific association between treatment response and treatment type received; however, there was a significant association between UES abnormalities and treatment response. In patients with achalasia and concomitant UES abnormalities, 87.5% had poor treatment response, while only 12.5% had favorable response. In contrast, in patients with achalasia and no UES abnormalities, the majority (78.57%) had good treatment response, as compared to 21.43% with poor treatment response (P = 0.0001). After controlling for achalasia sub-type, those with UES abnormality had 26 times greater odds of poor treatment response than those with no UES abnormality (P = 0.009). Similarly, after controlling for treatment type, those with UES abnormality had 13.9 times greater odds of poor treatment response

  5. Predicting breast tumor response to neoadjuvant chemotherapy with Diffuse Optical Spectroscopic Tomography prior to treatment

    PubMed Central

    Jiang, Shudong; Pogue, Brian W.; Kaufman, Peter A.; Gui, Jiang; Jermyn, Michael; Frazee, Tracy E.; Poplack, Steven P.; DiFlorio-Alexander, Roberta; Wells, Wendy A.; Paulsen, Keith D.

    2014-01-01

    Purpose Determine if pre-treatment biomarkers obtained from Diffuse Optical Spectroscopic Tomographic (DOST) imaging predict breast tumor response to Neoadjuvant Chemotherapy (NAC), which would have value to potentially eliminate delays in prescribing definitive local regional therapy that may occur from a standard complete 6–8 months course of NAC. Experimental design Nineteen patients undergoing NAC were imaged with DOST before, during and after treatment. The DOST images of total hemoglobin concentration (HbT), tissue oxygen saturation (StO2), and water (H2O) fraction at different time points have been used for testing the abilities of differentiating patients having pathologic complete response (pCR) vs. pathologic incomplete response (pIR). Results Significant differences (P-value<0.001, AUC=1.0) were found between pCR patients vs. pIR in outcome, based on the percentage change in tumor HbT within the first cycle of treatment. In addition, pre-treatment tumor HbT (Pre-TxHbT) relative to the contralateral breast was statistically significant (p-value=0.01, AUC=0.92) in differentiating pCR from pIR. Conclusions This is the first clinical evidence that DOST HbT may differentiate the two groups with predictive significance based on data acquired before NAC even begins. The study also demonstrates the potential of accelerating the validation of optimal NAC regimens through future randomized clinical trials by reducing the number of patients required and the length of time they need to be followed by using a validated imaging surrogate as an outcome measure. PMID:25294916

  6. Post-Exercise Heart Rate Recovery Independently Predicts Clinical Outcome in Patients with Acute Decompensated Heart Failure

    PubMed Central

    Youn, Jong-Chan; Lee, Hye Sun; Choi, Suk-Won; Han, Seong-Woo; Ryu, Kyu-Hyung; Shin, Eui-Cheol; Kang, Seok-Min

    2016-01-01

    Background Post-exercise heart rate recovery (HRR) is an index of parasympathetic function associated with clinical outcome in patients with chronic heart failure. However, its relationship with the pro-inflammatory response and prognostic value in consecutive patients with acute decompensated heart failure (ADHF) has not been investigated. Methods We measured HRR and pro-inflammatory markers in 107 prospectively and consecutively enrolled, recovered ADHF patients (71 male, 59 ± 15 years, mean ejection fraction 28.9 ± 14.2%) during the pre-discharge period. The primary endpoint included cardiovascular (CV) events defined as CV mortality, cardiac transplantation, or rehospitalization due to HF aggravation. Results The CV events occurred in 30 (28.0%) patients (5 cardiovascular deaths and 7 cardiac transplantations) during the follow-up period (median 214 days, 11–812 days). When the patients with ADHF were grouped by HRR according to the Contal and O’Quigley’s method, low HRR was shown to be associated with significantly higher levels of serum monokine-induced by gamma interferon (MIG) and poor clinical outcome. Multivariate Cox regression analysis revealed that low HRR was an independent predictor of CV events in both enter method and stepwise method. The addition of HRR to a model significantly increased predictability for CV events across the entire follow-up period. Conclusion Impaired post-exercise HRR is associated with a pro-inflammatory response and independently predicts clinical outcome in patients with ADHF. These findings may explain the relationship between autonomic dysfunction and clinical outcome in terms of the inflammatory response in these patients. PMID:27135610

  7. S100B Serum Levels Predict Treatment Response in Patients with Melancholic Depression

    PubMed Central

    Bergink, Veerle; Grosse, Laura; Alferink, Judith; Drexhage, Hemmo A.; Rothermundt, Matthias; Arolt, Volker; Birkenhäger, Tom K.

    2016-01-01

    Background: There is an ongoing search for biomarkers in psychiatry, for example, as diagnostic tools or predictors of treatment response. The neurotrophic factor S100 calcium binding protein B (S100B) has been discussed as a possible predictor of antidepressant response in patients with major depression, but also as a possible biomarker of an acute depressive state. The aim of the present study was to study the association of serum S100B levels with antidepressant treatment response and depression severity in melancholically depressed inpatients. Methods: After a wash-out period of 1 week, 40 inpatients with melancholic depression were treated with either venlafaxine or imipramine. S100B levels and Hamilton Depression Rating Scale (HAM-D) scores were assessed at baseline, after 7 weeks of treatment, and after 6 months. Results: Patients with high S100B levels at baseline showed a markedly better treatment response defined as relative reduction in HAM-D scores than those with low baseline S100B levels after 7 weeks (P=.002) and 6 months (P=.003). In linear regression models, S100B was a significant predictor for treatment response at both time points. It is of interest to note that nonresponders were detected with a predictive value of 85% and a false negative rate of 7.5%. S100B levels were not associated with depression severity and did not change with clinical improvement. Conclusions: Low S100B levels predict nonresponse to venlafaxine and imipramine with high precision. Future studies have to show which treatments are effective in patients with low levels of S100B so that this biomarker will help to reduce patients’ burden of nonresponding to frequently used antidepressants. PMID:26364276

  8. Exhaled NO predicts cyclophosphamide response in scleroderma-related lung disease.

    PubMed

    Tiev, Kiet Phong; Rivière, Sébastien; Hua-Huy, Thong; Cabane, Jean; Dinh-Xuan, Anh Tuan

    2014-08-31

    Cyclophosphamide (CYC) is not always effective in patients with scleroderma-related interstitial lung disease (SSc-ILD), hence the need for biomarkers able to predict beneficial responses to CYC therapy. We therefore assessed whether baseline alveolar concentration of nitric oxide (CANO) could predict the favourable response to CYC therapy in patients with SSc-ILD. Nineteen non-smoker patients with SSc-ILD, were enrolled and treated with 6 courses of CYC (0.75 g/m2/monthly) for lung function decline the year before inclusion, and followed-up for 2 years period. We assessed the proportion of favourable response to CYC, defined as improvement of forced vital capacity (FVC) or total pulmonary capacity (TLC) more than 10% between the inclusion and each following visit, according to the validated cut-off of CANO at 8.5 ppb identifying progressive SSc-ILD subset. At inclusion, 7 patients out of 19 had CANO >8.5 ppb. Clinical parameters were comparable between patients with high (>8.5 ppb) and low level of CANO (≤8.5 ppb). After CYC therapy, and during the follow-up, 9 out of 19 patients had favourable response to CYC therapy, 10 did not meet responder's criteria, from whom 4 patients died from respiratory failure. Six out of 7 patients with CANO >8.5 ppb at inclusion had favourable response to CYC therapy, while only 3 out of 12 patients with CANO ≤8.5 ppb responded favourably to CYC therapy (p=0.001). High level of CANO >8.5 ppb reflecting alveolar inflammation identify SSc patients with a greater chance to benefit from CYC treatment with a significant lung function improvement. PMID:24831352

  9. Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model

    PubMed Central

    Hu, Scott B.; Wong, Deborah J. L.; Correa, Aditi; Li, Ning; Deng, Jane C.

    2016-01-01

    Introduction Clinical deterioration (ICU transfer and cardiac arrest) occurs during approximately 5–10% of hospital admissions. Existing prediction models have a high false positive rate, leading to multiple false alarms and alarm fatigue. We used routine vital signs and laboratory values obtained from the electronic medical record (EMR) along with a machine learning algorithm called a neural network to develop a prediction model that would increase the predictive accuracy and decrease false alarm rates. Design Retrospective cohort study. Setting The hematologic malignancy unit in an academic medical center in the United States. Patient Population Adult patients admitted to the hematologic malignancy unit from 2009 to 2010. Intervention None. Measurements and Main Results Vital signs and laboratory values were obtained from the electronic medical record system and then used as predictors (features). A neural network was used to build a model to predict clinical deterioration events (ICU transfer and cardiac arrest). The performance of the neural network model was compared to the VitalPac Early Warning Score (ViEWS). Five hundred sixty five consecutive total admissions were available with 43 admissions resulting in clinical deterioration. Using simulation, the neural network outperformed the ViEWS model with a positive predictive value of 82% compared to 24%, respectively. Conclusion We developed and tested a neural network-based prediction model for clinical deterioration in patients hospitalized in the hematologic malignancy unit. Our neural network model outperformed an existing model, substantially increasing the positive predictive value, allowing the clinician to be confident in the alarm raised. This system can be readily implemented in a real-time fashion in existing EMR systems. PMID:27532679

  10. Anti-citrullinated peptide antibodies and their value for predicting responses to biologic agents: a review.

    PubMed

    Martin-Mola, Emilio; Balsa, Alejandro; García-Vicuna, Rosario; Gómez-Reino, Juan; González-Gay, Miguel Angel; Sanmartí, Raimon; Loza, Estíbaliz

    2016-08-01

    Anti-citrullinated peptide antibodies (ACPAs) play an important pathogenic role both at the onset and during the disease course. These antibodies precede the clinical appearance of rheumatoid arthritis (RA) and are associated with a less favorable prognosis, both clinically and radiologically. The objective of this work was to conduct a comprehensive review of studies published through September 2015 of ACPAs' role as a predictor of the therapeutic response to the biological agents in RA patients. The review also includes summary of the biology and detection of ACPAs as well as ACPAs in relation to joint disease and CV disease and the possible role of seroconversion. The reviews of studies examining TNF inhibitors and tocilizumab yielded negative results. In the case of rituximab, the data indicated a greater probability of clinical benefit in ACPA(+) patients versus ACPA(-) patients, as has been previously described for rheumatoid factor. Nonetheless, the effect is discreet and heterogeneous. Another drug that may have greater effectiveness in ACPA(+) patients is abatacept. Some studies have suggested that the drug is more efficient in ACPA(+) patients and that those patients show greater drug retention. In a subanalysis of the AMPLE trial, patients with very high ACPA titers who were treated with abatacept had a statistically significant response compared to patients with lower titers. In summary, the available studies suggest that the presence of or high titers of ACPA may predict a better response to rituximab and/or abatacept. Evidence regarding TNFi and tocilizumab is lacking. However, there is a lack of studies with appropriate designs to demonstrate that some drugs are superior to others for ACPA(+) patients. PMID:27271502

  11. Maternal Responsiveness Predicts Child Language at Ages 3 and 4 in a Community-Based Sample of Slow-to-Talk Toddlers

    ERIC Educational Resources Information Center

    Hudson, Sophie; Levickis, Penny; Down, Kate; Nicholls, Ruth; Wake, Melissa

    2015-01-01

    Background: Maternal responsiveness has been shown to predict child language outcomes in clinical samples of children with language delay and non-representative samples of typically developing children. An effective and timely measure of maternal responsiveness for use at the population level has not yet been established. Aims: To determine…

  12. Clinical and Actuarial Prediction of Physical Violence in a Forensic Intellectual Disability Hospital: A Longitudinal Study

    ERIC Educational Resources Information Center

    McMillan, Dean; Hastings, Richard P.; Coldwell, Jon

    2004-01-01

    Background: There is a high rate of physical violence in populations with intellectual disabilities, and this has been linked to problems for the victim, the assailant, members of staff and services. Despite the clinical significance of this behaviour, few studies have assessed methods of predicting its occurrence. The present study examined…

  13. Predicting Performance during Clinical Years from the New Medical College Admission Test.

    ERIC Educational Resources Information Center

    Caroline, Jan D.; And Others

    1983-01-01

    The results of a predictive validity study of the new Medical College Admission Test (MCAT) using criteria from the clinical years of undergraduate medical education are discussed. The criteria included course grades and faculty ratings of clerks in internal medicine, surgery, obstetrics and gynecology, pediatrics, and psychiatry. (Author/MLW)

  14. Predictive Validity of DSM-IV Oppositional Defiant and Conduct Disorders in Clinically Referred Preschoolers

    ERIC Educational Resources Information Center

    Keenan, Kate; Boeldt, Debra; Chen, Diane; Coyne, Claire; Donald, Radiah; Duax, Jeanne; Hart, Katherine; Perrott, Jennifer; Strickland, Jennifer; Danis, Barbara; Hill, Carri; Davis, Shante; Kampani, Smita; Humphries, Marisha

    2011-01-01

    Background: Diagnostic validity of oppositional defiant and conduct disorders (ODD and CD) for preschoolers has been questioned based on concerns regarding the ability to differentiate normative, transient disruptive behavior from clinical symptoms. Data on concurrent validity have accumulated, but predictive validity is limited. Predictive…

  15. Clinical prediction of fall risk and white matter abnormalities: a diffusion tensor imaging study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Tinetti scale is a simple clinical tool designed to predict risk of falling by focusing on gait and stance impairment in elderly persons. Gait impairment is also associated with white matter (WM) abnormalities. Objective: To test the hypothesis that elderly subjects at risk for falling, as deter...

  16. The Brief Accessibility, Responsiveness, and Engagement Scale: A Tool for Measuring Attachment Behaviors in Clinical Couples.

    PubMed

    Sandberg, Jonathan G; Novak, Joshua R; Davis, Stephanie Y; Busby, Dean M

    2016-01-01

    Measuring attachment behaviors is relevant to creating secure couple relationships. This article seeks to test and examine the reliability and validity of the Brief Accessibility, Responsiveness, and Engagement (BARE) Scale-a practical measure of couple attachment-in a clinical sample. Couples took the BARE and other assessments measuring relationship functioning (self and partner reports of relationship satisfaction, relationship stability, positive and negative communication, and attachment styles). Results suggest that the BARE appears to be a reliable and valid tool for assessing couple attachment and can accurately predict and classify whether the couples belong in the clinical or nonclinical group, as well as their level of relationship satisfaction. Results also indicate attachment behaviors are related to relationship outcomes. PMID:26748730

  17. Can Minnesota Multiphasic Personality Inventory-2 predict response to selective serotonin reuptake inhibitors in depressed outpatients?

    PubMed

    Kertzman, Semion; Vainder, Michael; Reznik, Ilya; Gotzlav, Yossef; Weizman, Abraham; Kotler, Moshe; Iancu, Iulian

    2012-05-01

    There is growing evidence that individual differences among patients with major depressive disorder (MDD) on psychological and demographic measures may predict the therapeutic response to selective serotonin reuptake inhibitors (SSRIs). In this retrospective chart review, 108 outpatients with current major depressive episodes were treated with citalopram, paroxetine, or fluvoxamine. The Hamilton Depression Rating Scale and the Minnesota Multiphasic Personality Inventory-2 were administered before and after 8 weeks of SSRIs treatment. Clinical response was defined as a 50% or greater decrease in the 17-item Hamilton Depression Rating Scale total score (final visit minus baseline). This naturalistic short-term follow-up outcome study demonstrates that among depressive outpatients who responded to an 8-week trial, 57.4% achieved a good response to SSRIs. Statistical analysis showed that SSRI treatment may be 3.03 times more advantageous for MDD outpatients who are younger than 39 years. The patients with an elevated score of above 66T on the Social Introversion Minnesota Multiphasic Personality Inventory-2 scale are approximately 0.37 times as likely to be SSRI responders as are patients with a Social Introversion score less than 66T. Thus, it seems that in MDD outpatient age is the strongest predictor of response to SSRIs. PMID:22415223

  18. Plasma microRNAs to predict the response of radiotherapy in esophageal squamous cell carcinoma patients

    PubMed Central

    Yu, Qi; Li, Bingxin; Li, Ping; Shi, Zeliang; Vaughn, Amanda; Zhu, Liucun; Fu, Shen

    2015-01-01

    Although microRNAs (miRNAs) play an important role in esophageal squamous cell carcinoma (ESCC), their roles in radiotherapy response remain unexplored. Our study aims to investigate whether plasma miRNAs can be used as predictors of radiotherapy outcome in ESCC patients. We selected nine miRNAs, which were reported to be associated with carcinogenesis or radiobiology of ESCC, as the targets of our study. Plasma miRNA expression was investigated with 24 subjects (pre-, at the first week and post-radiotherapy). Tumor radiographic response and 3-year overall survival were used to evaluate the response. The results showed that the level of miR-16 in the patients with good outcome was significantly higher than that in the patients with poor outcome (P < 0.05, AUC: 0.762) at the post-radiotherapy. We also found that the variation tendency of miRNA expression were related to its radiotherapy response. Moreover, miR-16 levels increased by more than 2-fold following treatment, which were shown to be associated with longer OS (log-rank P = 0.009). In conclusion, miR-16 has considerable clinical value in predicting radiotherapy outcomes for ESCC patients. PMID:26692950

  19. Practical Guidance for Implementing Predictive Biomarkers into Early Phase Clinical Studies

    PubMed Central

    Marton, Matthew J.; Weiner, Russell

    2013-01-01

    The recent U.S. Food and Drug Administration (FDA) coapprovals of several therapeutic compounds and their companion diagnostic devices (FDA News Release, 2011, 2013) to identify patients who would benefit from treatment have led to considerable interest in incorporating predictive biomarkers in clinical studies. Yet, the translation of predictive biomarkers poses unique technical, logistic, and regulatory challenges that need to be addressed by a multidisciplinary team including discovery scientists, clinicians, biomarker experts, regulatory personnel, and assay developers. These issues can be placed into four broad categories: sample collection, assay validation, sample analysis, and regulatory requirements. In this paper, we provide a primer for drug development teams who are eager to implement a predictive patient segmentation marker into an early clinical trial in a way that facilitates subsequent development of a companion diagnostic. Using examples of nucleic acid-based assays, we briefly review common issues encountered when translating a biomarker to the clinic but focus primarily on key practical issues that should be considered by clinical teams when planning to use a biomarker to balance arms of a study or to determine eligibility for a clinical study. PMID:24236296

  20. Prediction of Driving Safety in Individuals with Homonymous Hemianopia and Quadrantanopia from Clinical Neuroimaging

    PubMed Central

    Vaphiades, Michael S.; Kline, Lanning B.; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M.

    2014-01-01

    Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from −0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions. PMID:24683493

  1. Genetic prediction of common diseases. Still no help for the clinical diabetologist!

    PubMed Central

    Prudente, Sabrina; Dallapiccola, Bruno; Pellegrini, Fabio; Doria, Alessandro; Trischitta, Vincenzo

    2013-01-01

    Genome-wide association studies (GWAS) have identified several loci associated with many common, multifactorial diseases which have been recently used to market genetic testing directly to the consumers. We here addressed the clinical utility of such GWAS-derived genetic information in predicting type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) in diabetic patients. In addition, the development of new statistical approaches, novel technologies of genome sequencing and ethical, legal and social aspects related to genetic testing have been also addressed. Available data clearly show that, similarly to what reported for most common diseases, genetic testing offered today by commercial companies cannot be used as predicting tools for T2DM and CAD, both in the general and in the diabetic population. Further studies taking into account the complex interaction between genes as well as between genetic and non genetic factors, including age, obesity and glycemic control which seem to modify genetic effects on the risk of T2DM and CAD, might mitigate such negative conclusions. Also, addressing the role of relatively rare variants by next-generation sequencing may help identify novel and strong genetic markers with an important role in genetic prediction. Finally, statistical tools concentrated on reclassifying patients might be a useful application of genetic information for predicting many common diseases. By now, prediction of such diseases, including those of interest for the clinical diabetologist, have to be pursued by using traditional clinical markers which perform well and are not costly. PMID:22819342

  2. Prediction of driving safety in individuals with homonymous hemianopia and quadrantanopia from clinical neuroimaging.

    PubMed

    Vaphiades, Michael S; Kline, Lanning B; McGwin, Gerald; Owsley, Cynthia; Shah, Ritu; Wood, Joanne M

    2014-01-01

    Background. This study aimed to determine whether it is possible to predict driving safety of individuals with homonymous hemianopia or quadrantanopia based upon a clinical review of neuroimages that are routinely available in clinical practice. Methods. Two experienced neuroophthalmologists viewed a summary report of the CT/MRI scans of 16 participants with homonymous hemianopic or quadrantanopic field defects which indicated the site and extent of the lesion and they made predictions regarding whether participants would be safe/unsafe to drive. Driving safety was independently defined at the time of the study using state-recorded motor vehicle crashes (all crashes and at-fault) for the previous 5 years and ratings of driving safety determined through a standardized on-road driving assessment by a certified driving rehabilitation specialist. Results. The ability to predict driving safety was highly variable regardless of the driving safety measure, ranging from 31% to 63% (kappa levels ranged from -0.29 to 0.04). The level of agreement between the neuroophthalmologists was only fair (kappa = 0.28). Conclusions. Clinical evaluation of summary reports of currently available neuroimages by neuroophthalmologists is not predictive of driving safety. Future research should be directed at identifying and/or developing alternative tests or strategies to better enable clinicians to make these predictions. PMID:24683493

  3. Clinical implementation of dose-volume histogram predictions for organs-at-risk in IMRT planning

    NASA Astrophysics Data System (ADS)

    Moore, K. L.; Appenzoller, L. M.; Tan, J.; Michalski, J. M.; Thorstad, W. L.; Mutic, S.

    2014-03-01

    True quality control (QC) of the planning process requires quantitative assessments of treatment plan quality itself, and QC in IMRT has been stymied by intra-patient anatomical variability and inherently complex three-dimensional dose distributions. In this work we describe the development of an automated system to reduce clinical IMRT planning variability and improve plan quality using mathematical models that predict achievable OAR DVHs based on individual patient anatomy. These models rely on the correlation of expected dose to the minimum distance from a voxel to the PTV surface, whereby a three-parameter probability distribution function (PDF) was used to model iso-distance OAR subvolume dose distributions. DVH models were obtained by fitting the evolution of the PDF with distance. Initial validation on clinical cohorts of 40 prostate and 24 head-and-neck plans demonstrated highly accurate model-based predictions for achievable DVHs in rectum, bladder, and parotid glands. By quantifying the integrated difference between candidate DVHs and predicted DVHs, the models correctly identified plans with under-spared OARs, validated by replanning all cases and correlating any realized improvements against the predicted gains. Clinical implementation of these predictive models was demonstrated in the PINNACLE treatment planning system by use of existing margin expansion utilities and the scripting functionality inherent to the system. To maintain independence from specific planning software, a system was developed in MATLAB to directly process DICOM-RT data. Both model training and patient-specific analyses were demonstrated with significant computational accelerations from parallelization.

  4. Intra-articular corticosteroids are effective in osteoarthritis but there are no clinical predictors of response.

    PubMed Central

    Jones, A; Doherty, M

    1996-01-01

    OBJECTIVES: To show whether intra-articular steroid injections are effective in osteoarthritis; to determine factors that predict response; and to determine whether injection has a beneficial effect on muscle strength. METHODS: Double blind, placebo controlled, crossover study in 59 patients with symptomatic osteoarthritis of the knee. Outcome measure-Primary outcome measure: change in visual analogue score for pain at three weeks. Predictors of response analysed using logistic regression with a 15% decrease in pain score at three weeks defining response. RESULTS: Intra-articular methyl prednisolone acetate produced a significant reduction in visual analogue pain score at three weeks compared to both baseline (median change -2.0 mm, interquartile range -16.25 to 4.0) and placebo (median 0.0 mm, interquartile range -9.0 to 6.25). No clinical predictors of response could be identified. Muscle strength was not significantly improved in the short term by intra-articular injection. CONCLUSIONS: Intra-articular corticosteroids are effective for short term relief of pain in osteoarthritis but predicting responders is not possible. There may be a place for their more widespread use. PMID:8976640

  5. Older Persons' Reasoning about Responsibility for Health: Variations and Predictions

    ERIC Educational Resources Information Center

    Kjellstrom, Sofia; Ross, Sara Nora

    2011-01-01

    With many Western societies structured for adults to live longer and take responsibility for their health, it is valuable to investigate how older persons reason about this demand. Using mixed methods, this pilot studied how older persons reason about responsibility for health and their responsibility as a patient. Interviews with a small Swedish…

  6. The clinical and predictive value of the initial dream of treatment.

    PubMed

    Glucksman, Myron L; Kramer, Milton

    2011-01-01

    The authors collected the initial dreams of treatment from 63 patients and independently evaluated the manifest dream report (MDR). Variables included: Affect and Valence of Affect; Associations; Psychodynamic Theme; Psychodynamic Theme as Predictor of Core Psychodynamic Issues; Transference; Gender; Psychodynamic Theme Categories; Clinical Progress in relation to Psychodynamic Theme Categories and Transference. The initial MDR invariably contains Affect that is frequently Negative. The Psychodynamic Themes of MDRs are dependable predictors of Core Psychodynamic Issues that emerge during treatment. Transference is evident in a significant number of MDRs and is often Negative. Gender of the majority of MDRs is predictable. The most frequent Psychodynamic Themes of initial MDRs fall into Relational and Injury Categories. Relational and Injury Themes, as well as Positive and Negative Transference, are associated with clinical progress. This study confirms that the initial MDR of treatment provides a significant amount of clinical and predictive information. PMID:21699352

  7. Clinical Prediction of Alzheimer Disease Dementia Across the Spectrum of Mild Cognitive Impairment

    PubMed Central

    Dickerson, Bradford C.; Sperling, Reisa A.; Hyman, Bradley T.; Albert, Marilyn S.; Blacker, Deborah

    2008-01-01

    Objective: To determine whether clinical assessment methods that grade the severity of impairments within the spectrum of mild cognitive impairment (MCI) can predict clinical course, particularly among very mildly impaired individuals who do not meet formal MCI criteria as implemented in clinical trials. Design: Cohort. Setting: Community volunteers. Participants: From a longitudinal study of normal (Clinical Dementia Rating [CDR]=0; n=77) and mildly impaired (CDR=0.5; n=167) participants with 5 or more annual clinical assessments, baseline level of cognitive impairment in daily life was graded using CDR sum of boxes (CDR-SB) and level of cognitive performance impairment was graded using neuropsychological test scores. Main Outcome Measures: Five-year outcome measures included (1) probable Alzheimer disease (AD) diagnosis and (2) clinical “decline” (CDR-SB increase ≥1.0). Logistic regression models were used to assess the ability of baseline measures to predict outcomes in the full sample and separately in the subjects who did not meet formal MCI criteria as implemented in a multicenter clinical trial (n = 125; “very mild cognitive impairment” [vMCI]). Results: The presence of both higher CDR-SB and lower verbal memory and executive function at baseline predicted greater likelihood of probable AD and decline. Five-year rates of probable AD and decline in vMCI (20%, AD; 49%, decline) were intermediate between normal participants (0%, AD; 28%, decline) and participants with MCI (41%, AD; 62%, decline). Within vMCI, likelihood of probable AD was predicted by higher CDR-SB and lower executive function. Conclusions: Even in very mildly impaired individuals who do not meet strict MCI criteria as implemented in clinical trials, the degree of cognitive impairment in daily life and performance on neuropsychological testing predict likelihood of an AD diagnosis within 5 years. The clinical determination of relative severity of impairment along the spectrum of MCI

  8. A synonymous EGFR polymorphism predicting responsiveness to anti-EGFR therapy in metastatic colorectal cancer patients.

    PubMed

    Bonin, Serena; Donada, Marisa; Bussolati, Gianni; Nardon, Ermanno; Annaratone, Laura; Pichler, Martin; Chiaravalli, Anna Maria; Capella, Carlo; Hoefler, Gerald; Stanta, Giorgio

    2016-06-01

    Genetic factors are known to affect the efficiency of therapy with monoclonal antibodies (mAbs) targeting the epidermal growth factor receptor (EGFR) in patients with metastatic colorectal cancer (mCRC). At present, the only accepted molecular marker predictive of the response to anti-EGFR mAbs is the somatic mutation of KRAS and NRAS as a marker of resistance to anti-EGFR. However, only a fraction of KRAS wild-type patients benefit from that treatment. In this study, we show that the EGFR gene polymorphism rs1050171 defines, independently of RAS mutational status, a sub-population of 11 % of patients with a better clinical outcome after anti-EGFR treatment. Median PFS for patients with the GG genotype was 10.17 months compared to 5.37 of those with AG + AA genotypes. Taken together, our findings could be used to better define CRC populations responding to anti-EGFR therapy. Further studies in larger independent cohorts are necessary to validate the present observation that a synonymous polymorphism in EGFR gene impacts on clinical responsiveness. PMID:26666825

  9. Bronchodilator response following methacholine-induced bronchoconstriction predicts acute asthma exacerbations.

    PubMed

    Park, Heung-Woo; Song, Woo-Jung; Chang, Yoon-Suk; Cho, Sang-Heon; Datta, Soma; Weiss, Scott T; Tantisira, Kelan G

    2016-07-01

    Methacholine bronchial provocation test provides the concentration of methacholine causing a 20% decrease in forced expiratory volume in 1 s (FEV1) from baseline (PC20). The dose-response slope (DRS), and other continuous indices of responsiveness (CIR; the percentage decline from the post-diluent baseline FEV1 after the last dose of methacholine), and per cent recovery index (PRI; the percentage increase from the maximally reduced FEV1 after bronchodilator inhalation) are alternative measures. The clinical relevance of these indices in predicting acute asthma exacerbations has not been fully evaluated.In two prospective cohorts of childhood and elderly asthmatics, baseline PC20, DRS, CIR and PRI were measured and evaluated as predictors of acute asthma exacerbations.We found that PRI was significantly related to the presence of asthma exacerbations during the first year of follow-up in both cohorts of childhood (p=0.025) and elderly asthmatics (p=0.003). In addition, PRI showed a significant association with the total number of steroid bursts during 4.3 years of follow-up in the cohort of childhood asthmatics (p=0.04).We demonstrated that PRI, an index of reversibility following methacholine-induced bronchoconstriction, was a good clinical predictor of acute exacerbations of asthma in both childhood and elderly asthmatics. PMID:27076579

  10. Neuroimaging biomarkers to predict treatment response in schizophrenia: the end of 30 years of solitude?

    PubMed Central

    Dazzan, Paola

    2014-01-01

    Studies that have used structural magnetic resonance imaging (MRI) suggest that individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, and in the white matter tracts that connect them. Furthermore, these studies suggest that brain alterations may be particularly prominent, already at illness onset, in those individuals more likely to have poorer outcomes (eg, higher number of hospital admissions, and poorer symptom remission, level of functioning, and response to the first treatment with antipsychotic drugs). The fact that, even when present, these brain alterations are subtle and distributed in nature, has limited, until now, the utility of MRI in the clinical management of these disorders. More recently, MRI approaches, such as machine learning, have suggested that these neuroanatomical biomarkers can be used for direct clinical benefits. For example, using support vector machine, MRI data obtained at illness onset have been used to predict, with significant accuracy, whether a specific individual is likely to experience a remission of symptoms later on in the course of the illness. Taken together, this evidence suggests that validated, strong neuroanatomical markers could be used not only to inform tailored intervention strategies in a single individual, but also to allow patient stratification in clinical trials for new treatments. PMID:25733954

  11. Neuroimaging biomarkers to predict treatment response in schizophrenia: the end of 30 years of solitude?

    PubMed

    Dazzan, Paola

    2014-12-01

    Studies that have used structural magnetic resonance imaging (MRI) suggest that individuals with psychoses have brain alterations, particularly in frontal and temporal cortices, and in the white matter tracts that connect them. Furthermore, these studies suggest that brain alterations may be particularly prominent, already at illness onset, in those individuals more likely to have poorer outcomes (eg, higher number of hospital admissions, and poorer symptom remission, level of functioning, and response to the first treatment with antipsychotic drugs). The fact that, even when present, these brain alterations are subtle and distributed in nature, has limited, until now, the utility of MRI in the clinical management of these disorders. More recently, MRI approaches, such as machine learning, have suggested that these neuroanatomical biomarkers can be used for direct clinical benefits. For example, using support vector machine, MRI data obtained at illness onset have been used to predict, with significant accuracy, whether a specific individual is likely to experience a remission of symptoms later on in the course of the illness. Taken together, this evidence suggests that validated, strong neuroanatomical markers could be used not only to inform tailored intervention strategies in a single individual, but also to allow patient stratification in clinical trials for new treatments. PMID:25733954

  12. A Nomogram for Predicting the Pathological Response of Axillary Lymph Node Metastasis in Breast Cancer Patients.

    PubMed

    Jin, Xi; Jiang, Yi-Zhou; Chen, Sheng; Shao, Zhi-Ming; Di, Gen-Hong

    2016-01-01

    The value of sentinel lymph node biopsy (SLNB) in post-neoadjuvant chemotherapy (NCT) patients is still controversial. We aimed to identify predictors and construct a nomogram for predicting the pathologically complete response (pCR) of axillary lymph nodes (ALNs) after NCT in node positive breast cancer patients. In total, 426 patients with pathologically proven ALN metastasis before NCT were enrolled, randomized 1:1 and divided into a training set and a validation set. We developed a nomogram based on independent predictors for ALN pCR identified by multivariate logistic regression as well as clinical significant predictors. The multivariate logistic regression analysis showed that hormone receptor (HR) status, human epidermal growth factor 2 (HER2) status and Ki67 index were independent predictors. The nomogram was thereby constructed by those independent predictors as well as tumor size and NCT regimens. The areas under the receiver operating characteristic curve of the training set and the validation set were 0.804 and 0.749, respectively. We constructed a nomogram for predicting ALN pCR in patients who received NCT. Our nomogram can improve risk stratification, accurately predict post-NCT ALN status and avoid unnecessary ALN dissection. PMID:27576704

  13. A Nomogram for Predicting the Pathological Response of Axillary Lymph Node Metastasis in Breast Cancer Patients

    PubMed Central

    Jin, Xi; Jiang, Yi-Zhou; Chen, Sheng; Shao, Zhi-Ming; Di, Gen-Hong

    2016-01-01

    The value of sentinel lymph node biopsy (SLNB) in post-neoadjuvant chemotherapy (NCT) patients is still controversial. We aimed to identify predictors and construct a nomogram for predicting the pathologically complete response (pCR) of axillary lymph nodes (ALNs) after NCT in node positive breast cancer patients. In total, 426 patients with pathologically proven ALN metastasis before NCT were enrolled, randomized 1:1 and divided into a training set and a validation set. We developed a nomogram based on independent predictors for ALN pCR identified by multivariate logistic regression as well as clinical significant predictors. The multivariate logistic regression analysis showed that hormone receptor (HR) status, human epidermal growth factor 2 (HER2) status and Ki67 index were independent predictors. The nomogram was thereby constructed by those independent predictors as well as tumor size and NCT regimens. The areas under the receiver operating characteristic curve of the training set and the validation set were 0.804 and 0.749, respectively. We constructed a nomogram for predicting ALN pCR in patients who received NCT. Our nomogram can improve risk stratification, accurately predict post-NCT ALN status and avoid unnecessary ALN dissection. PMID:27576704

  14. Clinical Prediction Models for Sleep Apnea: The Importance of Medical History over Symptoms

    PubMed Central

    Ustun, Berk; Westover, M. Brandon; Rudin, Cynthia; Bianchi, Matt T.

    2016-01-01

    Study Objective: Obstructive sleep apnea (OSA) is a treatable contributor to morbidity and mortality. However, most patients with OSA remain undiagnosed. We used a new machine learning method known as SLIM (Supersparse Linear Integer Models) to test the hypothesis that a diagnostic screening tool based on routinely available medical information would be superior to one based solely on patient-reported sleep-related symptoms. Methods: We analyzed polysomnography (PSG) and self-reported clinical information from 1,922 patients tested in our clinical sleep laboratory. We used SLIM and 7 state-of-the-art classification methods to produce predictive models for OSA screening using features from: (i) self-reported symptoms; (ii) self-reported medical information that could, in principle, be extracted from electronic health records (demographics, comorbidities), or (iii) both. Results: For diagnosing OSA, we found that model performance using only medical history features was superior to model performance using symptoms alone, and similar to model performance using all features. Performance was similar to that reported for other widely used tools: sensitivity 64.2% and specificity 77%. SLIM accuracy was similar to state-of-the-art classification models applied to this dataset, but with the benefit of full transparency, allowing for hands-on prediction using yes/no answers to a small number of clinical queries. Conclusion: To predict OSA, variables such as age, sex, BMI, and medical history are superior to the symptom variables we examined for predicting OSA. SLIM produces an actionable clinical tool that can be applied to data that is routinely available in modern electronic health records, which may facilitate automated, rather than manual, OSA screening. Commentary: A commentary on this article appears in this issue on page 159. Citation: Ustun B, Westover MB, Rudin C, Bianchi MT. Clinical prediction models for sleep apnea: the importance of medical history over symptoms

  15. Sex Offender Populations and Clinical Efficacy: A Response to Rosky.

    PubMed

    Jensen, Todd M; Shafer, Kevin; Roby, C Y; Roby, Jini L

    2016-06-01

    We provide a brief response to a commentary submitted by Rosky in which he questions the rationale and methodological merits of our original study about full-disclosure polygraph outcome differences between juvenile and adult sex offenders. At the heart of Rosky's substantive concerns is the premise that only research tying polygraphy outcomes to actual recidivism is useful or worthwhile. He also questions the overall utility and validity of polygraphy. We acknowledge and challenge these two points. Furthermore, many of the methodological concerns expressed by Rosky represent either a misunderstanding of our research question, study design, and sample, or a disregard for the explicit declarations we made with respect to our study limitations. Overall, it appears Rosky has accused us of not answering well a question we were not trying to ask. Our response addresses the key substantive and methodological concerns extended by Rosky and clarifies the actual aims and scope of our original study. We also argue that a calm, rational, and scientific discussion is the best approach to understanding how to improve clinical methods used in sex offender treatment. PMID:25670743

  16. Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease

    PubMed Central

    Pavlides, Michael; Banerjee, Rajarshi; Sellwood, Joanne; Kelly, Catherine J.; Robson, Matthew D.; Booth, Jonathan C.; Collier, Jane; Neubauer, Stefan; Barnes, Eleanor

    2016-01-01

    Background & Aims Multiparametric magnetic resonance (MR) imaging has been demonstrated to quantify hepatic fibrosis, iron, and steatosis. The aim of this study was to determine if MR can be used to predict negative clinical outcomes in liver disease patients. Methods Patients with chronic liver disease (n = 112) were recruited for MR imaging and data on the development of liver related clinical events were collected by medical records review. The median follow-up was 27 months. MR data were analysed blinded for the Liver Inflammation and Fibrosis score (LIF; <1, 1–1.99, 2–2.99, and ⩾3 representing normal, mild, moderate, and severe liver disease, respectively), T2∗ for liver iron content and proportion of liver fat. Baseline liver biopsy was performed in 102 patients. Results Liver disease aetiologies included non-alcoholic fatty liver disease (35%) and chronic viral hepatitis (30%). Histologically, fibrosis was mild in 54 (48%), moderate in 17 (15%), and severe in 31 (28%) patients. Overall mortality was 5%. Ten patients (11%) developed at least one liver related clinical event. The negative predictive value of LIF <2 was 100%. Two patients with LIF 2–2.99 and eight with LIF ⩾3 had a clinical event. Patients with LIF ⩾3 had a higher cumulative risk for developing clinical events, compared to those with LIF <1 (p = 0.02) and LIF 1–1.99 (p = 0.03). Cox regression analysis including all 3 variables (fat, iron, LIF) resulted in an enhanced LIF predictive value. Conclusions Non-invasive standardised multiparametric MR technology may be used to predict clinical outcomes in patients with chronic liver disease. PMID:26471505

  17. Evaluation of the tip-bending response in clinically used endoscopes

    PubMed Central

    Rozeboom, Esther D.; Reilink, Rob; Schwartz, Matthijs P.; Fockens, Paul; Broeders, Ivo A. M. J.

    2016-01-01

    Background and study aims: Endoscopic interventions require accurate and precise control of the endoscope tip. The endoscope tip response depends on a cable pulling system, which is known to deliver a significantly nonlinear response that eventually reduces control. It is unknown whether the current technique of endoscope tip control is adequate for a future of high precision procedures, steerable accessories, and add-on robotics. The aim of this study was to determine the status of the tip response of endoscopes used in clinical practice. Materials and methods: We evaluated 20 flexible colonoscopes and five gastroscopes, used in the endoscopy departments of a Dutch university hospital and two Dutch teaching hospitals, in a bench top setup. First, maximal tip bending was determined manually. Next, the endoscope navigation wheels were rotated individually in a motor setup. Tip angulation was recorded with a USB camera. Cable slackness was derived from the resulting hysteresis plot. Results: Only two of the 20 colonoscopes (10 %) and none of the five gastroscopes reached the maximal tip angulation specified by the manufacturer. Four colonoscopes (20 %) and none of the gastroscopes demonstrated the recommended cable tension. Eight colonoscopes (40 %) had undergone a maintenance check 1 month before the measurements were made. The tip responses of these eight colonoscopies did not differ significantly from the tip responses of the other colonoscopes. Conclusion: This study suggests that the majority of clinically used endoscopes are not optimally tuned to reach maximal bending angles and demonstrate adequate tip responses. We suggest a brief check before procedures to predict difficulties with bending angles and tip responses. PMID:27092330

  18. Comparison of Decision-Assist and Clinical Judgment of Experts for Prediction of Lifesaving Interventions.

    PubMed

    Mackenzie, Colin F; Gao, Cheng; Hu, Peter F; Anazodo, Amechi; Chen, Hegang; Dinardo, Theresa; Imle, P Cristina; Hartsky, Lauren; Stephens, Christopher; Menaker, Jay; Fouche, Yvette; Murdock, Karen; Galvagno, Samuel; Alcorta, Richard; Shackelford, Stacy

    2015-03-01

    Early recognition of hemorrhage during the initial resuscitation of injured patients is associated with improved survival in both civilian and military casualties. We tested a transfusion and lifesaving intervention (LSI) prediction algorithm in comparison with clinical judgment of expert trauma care providers. We collected 15 min of pulse oximeter photopletysmograph waveforms and extracted features to predict LSIs. We compared this with clinical judgment of LSIs by individual categories of prehospital providers, nurses, and physicians and a combined judgment of all three providers using the Area Under Receiver Operating Curve (AUROC). We obtained clinical judgment of need for LSI from 405 expert clinicians in135 trauma patients. The pulse oximeter algorithm predicted transfusion within 6 h (AUROC, 0.92; P < 0.003) more accurately than either physicians or prehospital providers and as accurately as nurses (AUROC, 0.76; P = 0.07). For prediction of surgical procedures, the algorithm was as accurate as the three categories of clinicians. For prediction of fluid bolus, the diagnostic algorithm (AUROC, 0.9) was significantly more accurate than prehospital providers (AUROC, 0.62; P = 0.02) and nurses (AUROC, 0.57; P = 0.04) and as accurate as physicians (AUROC, 0.71; P = 0.06). Prediction of intubation by the algorithm (AUROC, 0.92) was as accurate as each of the three categories of clinicians. The algorithm was more accurate (P < 0.03) for blood and fluid prediction than the combined clinical judgment of all three providers but no different from the clinicians in the prediction of surgery (P = 0.7) or intubation (P = 0.8). Automated analysis of 15 min of pulse oximeter waveforms predicts the need for LSIs during initial trauma resuscitation as accurately as judgment of expert trauma clinicians. For prediction of emergency transfusion and fluid bolus, pulse oximetry features were more accurate than these experts. Such automated decision support could assist

  19. Early Prediction of Long-Term Response to Cabergoline in Patients with Macroprolactinomas

    PubMed Central

    Lee, Youngki; Ku, Cheol Ryong; Kim, Eui-Hyun; Lee, Eun Jig; Kim, Sun Ho

    2014-01-01

    Background Cabergoline is typically effective for treating prolactinomas; however, some patients display cabergoline resistance, and the early characteristics of these patients remain unclear. We analyzed early indicators predicting long-term response to cabergoline. Methods We retrospectively reviewed the cases of 44 patients with macroprolactinomas who received cabergoline as first-line treatment; the patients were followed for a median of 16 months. The influence of various clinical parameters on outcomes was evaluated. Results Forty patients (90.9%) were treated medically and displayed tumor volume reduction (TVR) of 74.7%, a prolactin normalization (NP) rate of 81.8%, and a complete response (CR; TVR >50% with NP, without surgery) rate of 70.5%. Most patients (93.1%) with TVR ≥25% and NP at 3 months eventually achieved CR, whereas only 50% of patients with TVR ≥25% without NP and no patients with TVR <25% achieved CR. TVR at 3 months was strongly correlated with final TVR (R=0.785). Patients with large macroadenomas exhibited a low NP rate at 3 months, but eventually achieved TVR and NP rates similar to those of patients with smaller tumors. Surgery independently reduced the final dose of cabergoline (β=-1.181 mg/week), and two of four patients who underwent surgery were able to discontinue cabergoline. Conclusion Determining cabergoline response using TVR and NP 3 months after treatment is useful for predicting later outcomes. However, further cabergoline administration should be considered for patients with TVR >25% at 3 months without NP, particularly those with huge prolactinomas, because a delayed response may be achieved. As surgery can reduce the cabergoline dose necessary for successful disease control, it should be considered for cabergoline-resistant patients. PMID:25309786

  20. Early prediction of the response of breast tumors to neoadjuvant chemotherapy using quantitative MRI and machine learning.

    PubMed

    Mani, Subramani; Chen, Yukun; Arlinghaus, Lori R; Li, Xia; Chakravarthy, A Bapsi; Bhave, Sandeep R; Welch, E Brian; Levy, Mia A; Yankeelov, Thomas E

    2011-01-01

    The ability to predict early in the course of treatment the response of breast tumors to neoadjuvant chemotherapy can stratify patients based on response for patient-specific treatment strategies. Currently response to neoadjuvant chemotherapy is evaluated based on physical exam or breast imaging (mammogram, ultrasound or conventional breast MRI). There is a poor correlation among these measurements and with the actual tumor size when measured by the pathologist during definitive surgery. We tested the feasibility of using quantitative MRI as a tool for early prediction of tumor response. Between 2007 and 2010 twenty consecutive patients diagnosed with Stage II/III breast cancer and receiving neoadjuvant chemotherapy were enrolled on a prospective imaging study. Our study showed that quantitative MRI parameters along with routine clinical measures can predict responders from non-responders to neoadjuvant chemotherapy. The best predictive model had an accuracy of 0.9, a positive predictive value of 0.91 and an AUC of 0.96. PMID:22195145

  1. Polymorphisms in the drug transporter gene ABCB1 predict antidepressant treatment response in depression.

    PubMed

    Uhr, Manfred; Tontsch, Alina; Namendorf, Christian; Ripke, Stephan; Lucae, Susanne; Ising, Marcus; Dose, Tatjana; Ebinger, Martin; Rosenhagen, Marcus; Kohli, Martin; Kloiber, Stefan; Salyakina, Daria; Bettecken, Thomas; Specht, Michael; Pütz, Benno; Binder, Elisabeth B; Müller-Myhsok, Bertram; Holsboer, Florian

    2008-01-24

    The clinical efficacy of a systemically administered drug acting on the central nervous system depends on its ability to pass the blood-brain barrier, which is regulated by transporter molecules such as ABCB1 (MDR1). Here we report that polymorphisms in the ABCB1 gene predict the response to antidepressant treatment in those depressed patients receiving drugs that have been identified as substrates of ABCB1 using abcb1ab double-knockout mice. Our results indicate that the combined consideration of both the medication's capacity to act as an ABCB1-transporter substrate and the patient's ABCB1 genotype are strong predictors for achieving a remission. This finding can be viewed as a further step into personalized antidepressant treatment. PMID:18215618

  2. HIV-specific Th2 and Th17 responses predict HIV vaccine protection efficacy

    PubMed Central

    Sauce, Delphine; Gorochov, Guy; Larsen, Martin

    2016-01-01

    Understanding the factors that delineate the efficacy of T-cell responses towards pathogens is crucial for our ability to develop potent therapies and vaccines against infectious diseases, such as HIV. Here we show that a recently developed analytical tool, the polyfunctionality index (PI), not only enables prediction of protection after vaccination against HIV, but also allows identification of the immunological pathways involved. Our data suggest that induction of a synergistic network of CD4+ T-cell subsets is implicated in HIV-protection. Accordingly, we provide evidence that vaccine-induced protection is associated with CD40L expressing Th2 cells and IL-2 secreting Th17 cells. In conclusion, we describe a novel approach that is widely applicable and readily interpretable in a biological and clinical context. This approach could greatly impact our fundamental understanding of T-cell immunity as well as the search for effective vaccines. PMID:27324186

  3. Clinical and Radiographic Factors Predicting Hearing Preservation Rates in Large Vestibular Schwannomas.

    PubMed

    Mendelsohn, Daniel; Westerberg, Brian D; Dong, Charles; Akagami, Ryojo

    2016-06-01

    Objectives Postoperative hearing preservation rates for patients with large vestibular schwannomas range from 0 to 43%. The clinical and radiographic factors predicting hearing preservation in smaller vestibular schwannomas are well described; however, their importance in larger tumors is unclear. We investigated factors predicting hearing preservation in large vestibular schwannomas. Design Retrospective review. Setting Quaternary care academic center. Participants A total of 85 patients with unilateral vestibular schwannomas > 3 cm underwent retrosigmoid resections. Main Outcomes Measures Preoperative and postoperative serviceable hearing rates. Methods Clinical and radiographic data including preoperative and postoperative audiograms, preoperative symptoms, magnetic resonance imaging features, and postoperative facial weakness were analyzed. Results Hearing was preserved in 41% of patients (17 of 42) with preoperative serviceable hearing. Hypertension and diabetes increased the likelihood of preoperative hearing loss. Preoperative tinnitus predicted a lower likelihood of hearing preservation. No radiographic factors predicted hearing preservation; however, larger tumor size, smaller fourth ventricular width, and the presence of a cerebrospinal fluid cleft surrounding the tumor predicted postoperative facial weakness. Conclusion Systemic comorbidities may influence hearing loss preoperatively in patients with large vestibular schwannomas. The absence of tinnitus may reflect hearing reserve and propensity for hearing preservation. Preoperative radiographic features did not predict hearing preservation despite some associations with postoperative facial weakness. PMID:27175312

  4. Improving Personalized Clinical Risk Prediction Based on Causality-Based Association Rules

    PubMed Central

    Cheng, Chih-wen; Wang, May D.

    2016-01-01

    Developing clinical risk prediction models is one of the main tasks of healthcare data mining. Advanced data collection techniques in current Big Data era have created an emerging and urgent need for scalable, computer-based data mining methods. These methods can turn data into useful, personalized decision support knowledge in a flexible, cost-effective, and productive way. In our previous study, we developed a tool, called icuARM- II, that can generate personalized clinical risk prediction evidence using a temporal rule mining framework. However, the generation of final risk prediction possibility with icuARM-II still relied on human interpretation, which was subjective and, most of time, biased. In this study, we propose a new mechanism to improve icuARM-II’s rule selection by including the concept of causal analysis. The generated risk prediction is quantitatively assessed using calibration statistics. To evaluate the performance of the new rule selection mechanism, we conducted a case study to predict short-term intensive care unit mortality based on personalized lab testing abnormalities. Our results demonstrated a better-calibrated ICU risk prediction using the new causality-base rule selection solution by comparing with conventional confidence-only rule selection methods. PMID:27532063

  5. Steroid-responsive and nephrotic syndrome and allergy: clinical studies.

    PubMed Central

    Meadow, S R; Sarsfield, J K

    1981-01-01

    Eighty-four children with steroid-responsive nephrotic syndrome who had been shown to have, or were believed to have, minimal change histology were investigated to study the relationship between steroid-responsive nephrotic syndrome and allergy. They were found to have a greater incidence of the standard atopic disorders--asthma, eczema, recurrent urticaria, and hay fever. Their 1st-degree relatives had an increased incidence of these atopic disorders too. A nasal discharge was a frequent precursor or an accompaniment of nephrotic syndrome, but an overt atrophic disorder at the same time was rare. Such disorders, related to relapse, occurred in only 5 children; in none was it a consistent or recurrent happening at the time of each relapse. No example of pollen hypersensitivity nephrotic syndrome was found, and no particular allergen could be identified with certainty as responsible for a child's nephrotic syndrome. No association was found between the time of relapse and the season of the year, or the season in which the child was born. Children with nephrotic syndrome had a greater incidence of positive skin tests to common antigens, the comparative frequency of positive reactions to different antigens being similar to that found in children with asthma, although the total frequency was about half that of children with asthma. Despite the increased incidence of clinical features of atopy, measures to reduce the frequency of relapse of nephrotic syndrome by allergen avoidance, the use of sodium cromoglycate, and the use of a new oral antiallergic drug were unsuccessful. PMID:6791592

  6. Steroid-responsive and nephrotic syndrome and allergy: clinical studies.

    PubMed

    Meadow, S R; Sarsfield, J K

    1981-07-01

    Eighty-four children with steroid-responsive nephrotic syndrome who had been shown to have, or were believed to have, minimal change histology were investigated to study the relationship between steroid-responsive nephrotic syndrome and allergy. They were found to have a greater incidence of the standard atopic disorders--asthma, eczema, recurrent urticaria, and hay fever. Their 1st-degree relatives had an increased incidence of these atopic disorders too. A nasal discharge was a frequent precursor or an accompaniment of nephrotic syndrome, but an overt atrophic disorder at the same time was rare. Such disorders, related to relapse, occurred in only 5 children; in none was it a consistent or recurrent happening at the time of each relapse. No example of pollen hypersensitivity nephrotic syndrome was found, and no particular allergen could be identified with certainty as responsible for a child's nephrotic syndrome. No association was found between the time of relapse and the season of the year, or the season in which the child was born. Children with nephrotic syndrome had a greater incidence of positive skin tests to common antigens, the comparative frequency of positive reactions to different antigens being similar to that found in children with asthma, although the total frequency was about half that of children with asthma. Despite the increased incidence of clinical features of atopy, measures to reduce the frequency of relapse of nephrotic syndrome by allergen avoidance, the use of sodium cromoglycate, and the use of a new oral antiallergic drug were unsuccessful. PMID:6791592

  7. Predicting viscoelastic response and delayed failures in general laminated composites

    NASA Technical Reports Server (NTRS)

    Dillard, D. A.; Morris, D. H.; Brinson, H. F.

    1982-01-01

    Although graphite fibers behave in an essentially elastic manner, the polymeric matrix of graphite/epoxy composites is a viscoelastic material which exhibits creep and delayed failures. The creep process is quite slow at room temperature, but may be accelerated by higher temperatures, moisture absorption, and other factors. Techniques are being studied to predict long-term behavior of general laminates based on short-term observations of the unidirectional material at elevated temperatures. A preliminary numerical procedure based on lamination theory is developed for predicting creep and delayed failures in laminated composites. A modification of the Findley nonlinear power law is used to model the constitutive behavior of a lamina. An adaptation of the Tsai-Hill failure criterion is used to predict the time-dependent strength of a lamina. Predicted creep and delayed failure results are compared with typical experimental data.

  8. Application of Static Models to Predict Midazolam Clinical Interactions in the Presence of Single or Multiple Hepatitis C Virus Drugs.

    PubMed

    Cheng, Yaofeng; Ma, Li; Chang, Shu-Ying; Humphreys, W Griffith; Li, Wenying

    2016-08-01

    Asunaprevir (ASV), daclatasvir (DCV), and beclabuvir (BCV) are three drugs developed for the treatment of chronic hepatitis C virus infection. Here, we evaluated the CYP3A4 induction potential of each drug, as well as BCV-M1 (the major metabolite of BCV), in human hepatocytes by measuring CYP3A4 mRNA alteration. The induction responses were quantified as induction fold (mRNA fold change) and induction increase (mRNA fold increase), and then fitted with four nonlinear regression algorithms. Reversible inhibition and time-dependent inhibition (TDI) on CYP3A4 activity were determined to predict net drug-drug interactions (DDIs). All four compounds were CYP3A4 inducers and inhibitors, with ASV demonstrating TDI. The curve-fitting results demonstrated that fold increase is a better assessment to determine kinetic parameters for compounds inducing weak responses. By summing the contribution of each inducer, the basic static model was able to correctly predict the potential for a clinically meaningful induction signal for single or multiple perpetrators, but with over prediction of the magnitude. With the same approach, the mechanistic static model improved the prediction accuracy of DCV and BCV when including both induction and inhibition effects, but incorrectly predicted the net DDI effects for ASV alone or triple combinations. The predictions of ASV or the triple combination could be improved by only including the induction and reversible inhibition but not the ASV CYP3A4 TDI component. Those results demonstrated that static models can be applied as a tool to help project the DDI risk of multiple perpetrators using in vitro data. PMID:27226352

  9. An Integrated Analysis of Heterogeneous Drug Responses in Acute Myeloid Leukemia That Enables the Discovery of Predictive Biomarkers.

    PubMed

    Chen, Weihsu C; Yuan, Julie S; Xing, Yan; Mitchell, Amanda; Mbong, Nathan; Popescu, Andreea C; McLeod, Jessica; Gerhard, Gitte; Kennedy, James A; Bogdanoski, Goce; Lauriault, Stevan; Perdu, Sofie; Merkulova, Yulia; Minden, Mark D; Hogge, Donna E; Guidos, Cynthia; Dick, John E; Wang, Jean C Y

    2016-03-01

    Many promising new cancer drugs proceed through preclinical testing and early-phase trials only to fail in late-stage clinical testing. Thus, improved models that better predict survival outcomes and enable the development of biomarkers are needed to identify patients most likely to respond to and benefit from therapy. Here, we describe a comprehensive approach in which we incorporated biobanking, xenografting, and multiplexed phospho-flow (PF) cytometric profiling to study drug response and identify predictive biomarkers in acute myeloid leukemia (AML) patients. To test the efficacy of our approach, we evaluated the investigational JAK2 inhibitor fedratinib (FED) in 64 patient samples. FED robustly reduced leukemia in mouse xenograft models in 59% of cases and was also effective in limiting the protumorigenic activity of leukemia stem cells as shown by serial transplantation assays. In parallel, PF profiling identified FED-mediated reduction in phospho-STAT5 (pSTAT5) levels as a predictive biomarker of in vivo drug response with high specificity (92%) and strong positive predictive value (93%). Unexpectedly, another JAK inhibitor, ruxolitinib (RUX), was ineffective in 8 of 10 FED-responsive samples. Notably, this outcome could be predicted by the status of pSTAT5 signaling, which was unaffected by RUX treatment. Consistent with this observed discrepancy, PF analysis revealed that FED exerted its effects through multiple JAK2-independent mechanisms. Collectively, this work establishes an integrated approach for testing novel anticancer agents that captures the inherent variability of response caused by disease heterogeneity and in parallel, facilitates the identification of predictive biomarkers that can help stratify patients into appropriate clinical trials. PMID:26833125

  10. Pharmacogenomic test that predicts response to inhaled corticosteroids in adults with asthma likely to be cost-saving

    PubMed Central

    Wu, Ann Chen; Gay, Charlene; Rett, Melisa D; Stout, Natasha; Weiss, Scott T; Fuhlbrigge, Anne L

    2015-01-01

    Aim To identify the clinical and economic circumstances under which a pharmacogenomic test that predicts response to inhaled corticosteroids might be a cost-effective option for individuals with asthma. Materials & methods We synthesized published data on clinical and economic outcomes to project 10-year costs, quality-adjusted life-years and cost–effectiveness of pharmacogenomic testing for inhaled corticosteroid response. We assumed the pharmacogenomic test cost was $500 with a sensitivity and specificity of 84 and 98%, respectively. These were varied in sensitivity analyses. Results Both strategies, pharmacogenomic testing for inhaled corticosteroid response and no testing conferred 7.1 quality-adjusted life-years. Compared with no testing, pharmacogenomic testing costs less. Conclusion Pharmacogenomic testing for asthma is cost-saving and noninferior in improving health. PMID:25880024

  11. Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression.

    PubMed

    Küffner, Robert; Zach, Neta; Norel, Raquel; Hawe, Johann; Schoenfeld, David; Wang, Liuxia; Li, Guang; Fang, Lilly; Mackey, Lester; Hardiman, Orla; Cudkowicz, Merit; Sherman, Alexander; Ertaylan, Gokhan; Grosse-Wentrup, Moritz; Hothorn, Torsten; van Ligtenberg, Jules; Macke, Jakob H; Meyer, Timm; Schölkopf, Bernhard; Tran, Linh; Vaughan, Rubio; Stolovitzky, Gustavo; Leitner, Melanie L

    2015-01-01

    Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with substantial heterogeneity in its clinical presentation. This makes diagnosis and effective treatment difficult, so better tools for estimating disease progression are needed. Here, we report results from the DREAM-Phil Bowen ALS Prediction Prize4Life challenge. In this crowdsourcing competition, competitors developed algorithms for the prediction of disease progression of 1,822 ALS patients from standardized, anonymized phase 2/3 clinical trials. The two best algorithms outperformed a method designed by the challenge organizers as well as predictions by ALS clinicians. We estimate that using both winning algorithms in future trial designs could reduce the required number of patients by at least 20%. The DREAM-Phil Bowen ALS Prediction Prize4Life challenge also identified several potential nonstandard predictors of disease progression including uric acid, creatinine and surprisingly, blood pressure, shedding light on ALS pathobiology. This analysis reveals the potential of a crowdsourcing competition that uses clinical trial data for accelerating ALS research and development. PMID:25362243

  12. Artificial neural network modeling using clinical and knowledge independent variables predicts salt intake reduction behavior

    PubMed Central

    Isma’eel, Hussain A.; Sakr, George E.; Almedawar, Mohamad M.; Fathallah, Jihan; Garabedian, Torkom; Eddine, Savo Bou Zein

    2015-01-01

    Background High dietary salt intake is directly linked to hypertension and cardiovascular diseases (CVDs). Predicting behaviors regarding salt intake habits is vital to guide interventions and increase their effectiveness. We aim to compare the accuracy of an artificial neural network (ANN) based tool that predicts behavior from key knowledge questions along with clinical data in a high cardiovascular risk cohort relative to the least square models (LSM) method. Methods We collected knowledge, attitude and behavior data on 115 patients. A behavior score was calculated to classify patients’ behavior towards reducing salt intake. Accuracy comparison between ANN and regression analysis was calculated using the bootstrap technique with 200 iterations. Results Starting from a 69-item questionnaire, a reduced model was developed and included eight knowledge items found to result in the highest accuracy of 62% CI (58-67%). The best prediction accuracy in the full and reduced models was attained by ANN at 66% and 62%, respectively, compared to full and reduced LSM at 40% and 34%, respectively. The average relative increase in accuracy over all in the full and reduced models is 82% and 102%, respectively. Conclusions Using ANN modeling, we can predict salt reduction behaviors with 66% accuracy. The statistical model has been implemented in an online calculator and can be used in clinics to estimate the patient’s behavior. This will help implementation in future research to further prove clinical utility of this tool to guide therapeutic salt reduction interventions in high cardiovascular risk individuals. PMID:26090333

  13. Predicting counseling psychologists attitudes and clinical judgments with respect to older adults.

    PubMed

    Tomko, Jody K; Munley, Patrick H

    2013-01-01

    The purpose of this study was to examine age, gender, training and experience in aging issues, fear of death, and multicultural competence in predicting counseling psychologists' global attitudes toward older adults and specific clinical judgments concerning a case vignette of an older client. A national sample of 364 practicing counseling psychologists participated in the study. Participants completed a demographic measure, Polizzi's refined version of the Aging Semantic Differential (Polizzi, 2003 ), a survey of professional bias based on a clinical vignette of a 70-year-old woman (James & Haley, 1995), the Collett-Lester Fear of Death Scale 3.0 (Lester, & Abdel-Khalek, 2003), the Multicultural Counseling Knowledge and Awareness Scale (MCKAS; Ponterotto, Gretchen, Utsey, Rieger, & Austin, 2002), and a Training and Experience Questionnaire. Hierarchical multiple regression analyses were used to investigate the extent to which the selected variables predicted more favorable attitudes toward older adults and less professional bias toward an older client beyond prediction by age and gender. Results revealed that older age and higher total scores on the MCKAS predicted less professional bias in clinical judgments. Gender was a significant predictor of global attitudes toward older adults. Findings suggest that multicultural knowledge, awareness, and skills are important in working with older adults. PMID:22913506

  14. X-linked acrogigantism syndrome: clinical profile and therapeutic responses.

    PubMed

    Beckers, Albert; Lodish, Maya Beth; Trivellin, Giampaolo; Rostomyan, Liliya; Lee, Misu; Faucz, Fabio R; Yuan, Bo; Choong, Catherine S; Caberg, Jean-Hubert; Verrua, Elisa; Naves, Luciana Ansaneli; Cheetham, Tim D; Young, Jacques; Lysy, Philippe A; Petrossians, Patrick; Cotterill, Andrew; Shah, Nalini Samir; Metzger, Daniel; Castermans, Emilie; Ambrosio, Maria Rosaria; Villa, Chiara; Strebkova, Natalia; Mazerkina, Nadia; Gaillard, Stéphan; Barra, Gustavo Barcelos; Casulari, Luis Augusto; Neggers, Sebastian J; Salvatori, Roberto; Jaffrain-Rea, Marie-Lise; Zacharin, Margaret; Santamaria, Beatriz Lecumberri; Zacharieva, Sabina; Lim, Ee Mun; Mantovani, Giovanna; Zatelli, Maria Chaira; Collins, Michael T; Bonneville, Jean-François; Quezado, Martha; Chittiboina, Prashant; Oldfield, Edward H; Bours, Vincent; Liu, Pengfei; W de Herder, Wouter; Pellegata, Natalia; Lupski, James R; Daly, Adrian F; Stratakis, Constantine A

    2015-06-01

    X-linked acrogigantism (X-LAG) is a new syndrome of pituitary gigantism, caused by microduplications on chromosome Xq26.3, encompassing the gene GPR101, which is highly upregulated in pituitary tumors. We conducted this study to explore the clinical, radiological, and hormonal phenotype and responses to therapy in patients with X-LAG syndrome. The study included 18 patients (13 sporadic) with X-LAG and microduplication of chromosome Xq26.3. All sporadic cases had unique duplications and the inheritance pattern in two families was dominant, with all Xq26.3 duplication carriers being affected. Patients began to grow rapidly as early as 2-3 months of age (median 12 months). At diagnosis (median delay 27 months), patients had a median height and weight standard deviation scores (SDS) of >+3.9 SDS. Apart from the increased overall body size, the children had acromegalic symptoms including acral enlargement and facial coarsening. More than a third of cases had increased appetite. Patients had marked hypersecretion of GH/IGF1 and usually prolactin, due to a pituitary macroadenoma or hyperplasia. Primary neurosurgical control was achieved with extensive anterior pituitary resection, but postoperative hypopituitarism was frequent. Control with somatostatin analogs was not readily achieved despite moderate to high levels of expression of somatostatin receptor subtype-2 in tumor tissue. Postoperative use of adjuvant pegvisomant resulted in control of IGF1 in all five cases where it was employed. X-LAG is a new infant-onset gigantism syndrome that has a severe clinical phenotype leading to challenging disease management. PMID:25712922

  15. Clinical Evaluation of Tuberculosis Viability Microscopy for Assessing Treatment Response

    PubMed Central

    Datta, Sumona; Sherman, Jonathan M.; Bravard, Marjory A.; Valencia, Teresa; Gilman, Robert H.; Evans, Carlton A.

    2015-01-01

    Background. It is difficult to determine whether early tuberculosis treatment is effective in reducing the infectiousness of patients' sputum, because culture takes weeks and conventional acid-fast sputum microscopy and molecular tests cannot differentiate live from dead tuberculosis. Methods. To assess treatment response, sputum samples (n = 124) from unselected patients (n = 35) with sputum microscopy–positive tuberculosis were tested pretreatment and after 3, 6, and 9 days of empiric first-line therapy. Tuberculosis quantitative viability microscopy with fluorescein diacetate, quantitative culture, and acid-fast auramine microscopy were all performed in triplicate. Results. Tuberculosis quantitative viability microscopy predicted quantitative culture results such that 76% of results agreed within ±1 logarithm (rS = 0.85; P < .0001). In 31 patients with non-multidrug-resistant (MDR) tuberculosis, viability and quantitative culture results approximately halved (both 0.27 log reduction, P < .001) daily. For patients with non-MDR tuberculosis and available data, by treatment day 9 there was a >10-fold reduction in viability in 100% (24/24) of cases and quantitative culture in 95% (19/20) of cases. Four other patients subsequently found to have MDR tuberculosis had no significant changes in viability (P = .4) or quantitative culture (P = .6) results during early treatment. The change in viability and quantitative culture results during early treatment differed significantly between patients with non-MDR tuberculosis and those with MDR tuberculosis (both P < .001). Acid-fast microscopy results changed little during early treatment, and this change was similar for non-MDR tuberculosis vs MDR tuberculosis (P = .6). Conclusions. Tuberculosis quantitative viability microscopy is a simple test that within 1 hour predicted quantitative culture results that became available weeks later, rapidly indicating whether patients were responding to tuberculosis therapy

  16. Islet Oxygen Consumption Rate (OCR) Dose Predicts Insulin Independence in Clinical Islet Autotransplantation

    PubMed Central

    Papas, Klearchos K.; Bellin, Melena D.; Sutherland, David E. R.; Suszynski, Thomas M.; Kitzmann, Jennifer P.; Avgoustiniatos, Efstathios S.; Gruessner, Angelika C.; Mueller, Kathryn R.; Beilman, Gregory J.; Balamurugan, Appakalai N.; Loganathan, Gopalakrishnan; Colton, Clark K.; Koulmanda, Maria; Weir, Gordon C.; Wilhelm, Josh J.; Qian, Dajun; Niland, Joyce C.; Hering, Bernhard J.

    2015-01-01

    Background Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR) in predicting clinical islet autotransplant (IAT) insulin independence (II). IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding factors such as immune rejection and immunosuppressant toxicity. Methods Membrane integrity staining (FDA/PI), OCR normalized to DNA (OCR/DNA), islet equivalent (IE) and OCR (viable IE) normalized to recipient body weight (IE dose and OCR dose), and OCR/DNA normalized to islet size index (ISI) were used to characterize autoislet preparations (n = 35). Correlation between pre-IAT islet product characteristics and II was determined using receiver operating characteristic analysis. Results Preparations that resulted in II had significantly higher OCR dose and IE dose (p<0.001). These islet characterization methods were highly correlated with II at 6–12 months post-IAT (area-under-the-curve (AUC) = 0.94 for IE dose and 0.96 for OCR dose). FDA/PI (AUC = 0.49) and OCR/DNA (AUC = 0.58) did not correlate with II. OCR/DNA/ISI may have some utility in predicting outcome (AUC = 0.72). Conclusions Commonly used assays to determine whether a clinical islet preparation is of high quality prior to transplantation are greatly lacking in sensitivity and specificity. While IE dose is highly predictive, it does not take into account islet cell quality. OCR dose, which takes into consideration both islet cell quality and quantity, may enable a more accurate and prospective evaluation of clinical islet preparations. PMID:26258815

  17. Predicting binaural responses from monaural responses in the gerbil medial superior olive.

    PubMed

    Plauška, Andrius; Borst, J Gerard; van der Heijden, Marcel

    2016-06-01

    Accurate sound source localization of low-frequency sounds in the horizontal plane depends critically on the comparison of arrival times at both ears. A specialized brainstem circuit containing the principal neurons of the medial superior olive (MSO) is dedicated to this comparison. MSO neurons are innervated by segregated inputs from both ears. The coincident arrival of excitatory inputs from both ears is thought to trigger action potentials, with differences in internal delays creating a unique sensitivity to interaural time differences (ITDs) for each cell. How the inputs from both ears are integrated by the MSO neurons is still debated. Using juxtacellular recordings, we tested to what extent MSO neurons from anesthetized Mongolian gerbils function as simple cross-correlators of their bilateral inputs. From the measured subthreshold responses to monaural wideband stimuli we predicted the rate-ITD functions obtained from the same MSO neuron, which have a damped oscillatory shape. The rate of the oscillations and the position of the peaks and troughs were accurately predicted. The amplitude ratio between dominant and secondary peaks of the rate-ITD function, captured in the width of its envelope, was not always exactly reproduced. This minor imperfection pointed to the methodological limitation of using a linear representation of the monaural inputs, which disregards any temporal sharpening occurring in the cochlear nucleus. The successful prediction of the major aspects of rate-ITD curves supports a simple scheme in which the ITD sensitivity of MSO neurons is realized by the coincidence detection of excitatory monaural inputs. PMID:27009164

  18. Childhood trauma predicts antidepressant response in adults with major depression: data from the randomized international study to predict optimized treatment for depression.

    PubMed

    Williams, L M; Debattista, C; Duchemin, A-M; Schatzberg, A F; Nemeroff, C B

    2016-01-01

    Few reliable predictors indicate which depressed individuals respond to antidepressants. Several studies suggest that a history of early-life trauma predicts poorer response to antidepressant therapy but results are variable and limited in adults. The major goal of the present study was to evaluate the role of early-life trauma in predicting acute response outcomes to antidepressants in a large sample of well-characterized patients with major depressive disorder (MDD). The international Study to Predict Optimized Treatment for Depression (iSPOT-D) is a randomized clinical trial with enrollment from December 2008 to January 2012 at eight academic and nine private clinical settings in five countries. Patients (n=1008) meeting DSM-IV criteria for MDD and 336 matched healthy controls comprised the study sample. Six participants withdrew due to serious adverse events. Randomization was to 8 weeks of treatment with escitalopram, sertraline or venlafaxine with dosage adjusted by the participant's treating clinician per routine clinical practice. Exposure to 18 types of traumatic events before the age of 18 was assessed using the Early-Life Stress Questionnaire. Impact of early-life stressors-overall trauma 'load' and specific type of abuse-on treatment outcomes measures: response: (⩾50% improvement on the 17-item Hamilton Rating Scale for Depression, HRSD17 or on the 16-item Quick Inventory of Depressive Symptomatology-Self-Rated, QIDS_SR16) and remission (score ⩽7 on the HRSD17 and ⩽5 on the QIDS_SR16). Trauma prevalence in MDD was compared with controls. Depressed participants were significantly more likely to report early-life stress than controls; 62.5% of MDD participants reported more than two traumatic events compared with 28.4% of controls. The higher rate of early-life trauma was most apparent for experiences of interpersonal violation (emotional, sexual and physical abuses). Abuse and notably abuse occurring at ⩽7 years of age predicted poorer outcomes

  19. Infrared spectra of primary melanomas can predict response to chemotherapy: The example of dacarbazine.

    PubMed

    Wald, N; Le Corre, Y; Martin, L; Mathieu, V; Goormaghtigh, E

    2016-02-01

    Metastatic melanomas are highly aggressive and median survival is 6-9months for stage IV patients in the absence of treatment with anti-tumor activity. Dacarbazine is an alkylating agent that has been widely used in the treatment of metastatic melanomas and that could be still used in combination with targeted or immune therapies. Indeed, therapeutic benefits of these treatments in monotherapy are poor and one option to improve them is to combine drugs and/or to better anticipate the individual response to a defined treatment. To our best knowledge and to date, there is no test available to predict the response of a patient to dacarbazine. We show here that examination of melanoma histological sections by infrared micro-spectroscopy reveals the sensitivity of the cancer to dacarbazine. Unsupervised analysis of the FTIR spectra evidences spontaneous and significant clustering of infrared spectra into two groups that match the clinical responsiveness of the patients to dacarbazine used as a first-line treatment. A supervised model resulted in 83% of the patient status (responder/non-responder) being correctly identified. The spectra revealed a key modification in the nature and quantity of lipids in the cells of both groups. PMID:26577766

  20. Response to methotrexate predicts long-term patient-related outcomes in rheumatoid arthritis.

    PubMed

    Krause, Dietmar; Gabriel, Bernadette; Herborn, Gertraud; Braun, Juergen; Rau, Rolf

    2016-05-01

    This study was conducted to investigate the predictive value of the initial response to methotrexate (MTX) on long-term patient-related outcomes (PROs) in rheumatoid arthritis (RA). All RA patients starting MTX treatment between 1980 and 1987 in our department were enrolled in a prospective observational study. After an average of 18 years, patient-related outcomes were assessed in three dimensions according to the International Classification of Functioning, Disability and Health (ICF). Statistical analyses employed multivariable models with baseline values for age, gender, disease duration, rheumatoid factor positivity, disease activity, response to MTX after 1 year and continuous use of MTX as covariates. The 271 patients enrolled had a mean disease duration of 8.5 years, a mean number of swollen joints of 18 (out of 32), and a mean erythrocyte sedimentation rate of 55 mm/h. After 18 years, PRO was available in 89 patients (33 %). A clinical improvement of at least 20 % 1 year after the initiation of MTX was associated with a favourable outcome in all three dimensions of the ICF, independent of continuation of MTX (p < 0.05). The initial response to MTX is an independent predictor of PRO in RA as assessed after an average of 18 years. PMID:26920753

  1. Impaired Neural Response to Negative Prediction Errors in Cocaine Addiction

    PubMed Central

    Parvaz, Muhammad A.; Konova, Anna B.; Proudfit, Greg H.; Dunning, Jonathan P.; Malaker, Pias; Moeller, Scott J.; Maloney, Tom; Alia-Klein, Nelly

    2015-01-01

    Learning can be guided by unexpected success or failure, signaled via dopaminergic positive reward prediction error (+RPE) and negative reward-prediction error (−RPE) signals, respectively. Despite conflicting empirical evidence, RPE signaling is thought to be impaired in drug addiction. To resolve this outstanding question, we studied as a measure of RPE the feedback negativity (FN) that is sensitive to both reward and the violation of expectation. We examined FN in 25 healthy controls; 25 individuals with cocaine-use disorder (CUD) who tested positive for cocaine on the study day (CUD+), indicating cocaine use within the past 72 h; and in 25 individuals with CUD who tested negative for cocaine (CUD−). EEG was acquired while the participants performed a gambling task predicting whether they would win or lose money on each trial given three known win probabilities (25, 50, or 75%). FN was scored for the period in each trial when the actual outcome (win or loss) was revealed. A significant interaction between prediction, outcome, and group revealed that controls showed increased FN to unpredicted compared with predicted wins (i.e., intact +RPE) and decreased FN to unpredicted compared with predicted losses (i.e., intact −RPE). However, neither CUD subgroup showed FN modulation to loss (i.e., impaired −RPE), and unlike CUD+ individuals, CUD− individuals also did not show FN modulation to win (i.e., impaired +RPE). Thus, using FN, the current study directly documents −RPE deficits in CUD individuals. The mechanisms underlying −RPE signaling impairments in addiction may contribute to the disadvantageous nature of excessive drug use, which can persist despite repeated unfavorable life experiences (e.g., frequent incarcerations). PMID:25653348

  2. Impaired neural response to negative prediction errors in cocaine addiction.

    PubMed

    Parvaz, Muhammad A; Konova, Anna B; Proudfit, Greg H; Dunning, Jonathan P; Malaker, Pias; Moeller, Scott J; Maloney, Tom; Alia-Klein, Nelly; Goldstein, Rita Z

    2015-02-01

    Learning can be guided by unexpected success or failure, signaled via dopaminergic positive reward prediction error (+RPE) and negative reward-prediction error (-RPE) signals, respectively. Despite conflicting empirical evidence, RPE signaling is thought to be impaired in drug addiction. To resolve this outstanding question, we studied as a measure of RPE the feedback negativity (FN) that is sensitive to both reward and the violation of expectation. We examined FN in 25 healthy controls; 25 individuals with cocaine-use disorder (CUD) who tested positive for cocaine on the study day (CUD+), indicating cocaine use within the past 72 h; and in 25 individuals with CUD who tested negative for cocaine (CUD-). EEG was acquired while the participants performed a gambling task predicting whether they would win or lose money on each trial given three known win probabilities (25, 50, or 75%). FN was scored for the period in each trial when the actual outcome (win or loss) was revealed. A significant interaction between prediction, outcome, and group revealed that controls showed increased FN to unpredicted compared with predicted wins (i.e., intact +RPE) and decreased FN to unpredicted compared with predicted losses (i.e., intact -RPE). However, neither CUD subgroup showed FN modulation to loss (i.e., impaired -RPE), and unlike CUD+ individuals, CUD- individuals also did not show FN modulation to win (i.e., impaired +RPE). Thus, using FN, the current study directly documents -RPE deficits in CUD individuals. The mechanisms underlying -RPE signaling impairments in addiction may contribute to the disadvantageous nature of excessive drug use, which can persist despite repeated unfavorable life experiences (e.g., frequent incarcerations). PMID:25653348

  3. Even modest prediction accuracy of genomic models can have large clinical utility

    PubMed Central

    Dhurandhar, Emily J.; Vazquez, Ana I.; Argyropoulos, George A.; Allison, David B.

    2014-01-01

    Whole Genome Prediction (WGP) jointly fits thousands of SNPs into a regression model to yield estimates for the contribution of markers to the overall variance of a particular trait, and for their associations with that trait. To date, WGP has offered only modest prediction accuracy, but in some cases even modest prediction accuracy may be useful. We provide an illustration of this using a theoretical simulation that used WGP to predict weight loss after bariatric surgery with moderate accuracy (R2 = 0.07) to assess the clinical utility of WGP despite these limitations. Prevention of Type 2 Diabetes (T2DM) post-surgery was considered the major outcome. Treating only patients above predefined threshold of predicted weight loss in our simulation, in the realistic context of finite resources for the surgery, significantly reduced lifetime risk of T2DM in the treatable population by selecting those most likely to succeed. Thus, our example illustrates how WGP may be clinically useful in some situations, and even with moderate accuracy, may provide a clear path for turning personalized medicine from theory to reality. PMID:25506355

  4. [Prediction of histological liver damage in asymptomatic alcoholic patients by means of clinical and laboratory data].

    PubMed

    Iturriaga, H; Hirsch, S; Bunout, D; Díaz, M; Kelly, M; Silva, G; de la Maza, M P; Petermann, M; Ugarte, G

    1993-04-01

    Looking for a noninvasive method to predict liver histologic alterations in alcoholic patients without clinical signs of liver failure, we studied 187 chronic alcoholics recently abstinent, divided in 2 series. In the model series (n = 94) several clinical variables and results of common laboratory tests were confronted to the findings of liver biopsies. These were classified in 3 groups: 1. Normal liver; 2. Moderate alterations; 3. Marked alterations, including alcoholic hepatitis and cirrhosis. Multivariate methods used were logistic regression analysis and a classification and regression tree (CART). Both methods entered gamma-glutamyltransferase (GGT), aspartate-aminotransferase (AST), weight and age as significant and independent variables. Univariate analysis with GGT and AST at different cutoffs were also performed. To predict the presence of any kind of damage (Groups 2 and 3), CART and AST > 30 IU showed the higher sensitivity, specificity and correct prediction, both in the model and validation series. For prediction of marked liver damage, a score based on logistic regression and GGT > 110 IU had the higher efficiencies. It is concluded that GGT and AST are good markers of alcoholic liver damage and that, using sample cutoffs, histologic diagnosis can be correctly predicted in 80% of recently abstinent asymptomatic alcoholics. PMID:7903815

  5. Using complete genome comparisons to identify sequences whose presence accurately predicts clinically important phenotypes.

    PubMed

    Hall, Barry G; Cardenas, Heliodoro; Barlow, Miriam

    2013-01-01

    In clinical settings it is often important to know not just the identity of a microorganism, but also the danger posed by that particular strain. For instance, Escherichia coli can range from being a harmless commensal to being a very dangerous enterohemorrhagic (EHEC) strain. Determining pathogenic phenotypes can be both time consuming and expensive. Here we propose a simple, rapid, and inexpensive method of predicting pathogenic phenotypes on the basis of the presence or absence of short homologous DNA segments in an isolate. Our method compares completely sequenced genomes without the necessity of genome alignments in order to identify the presence or absence of the segments to produce an automatic alignment of the binary string that describes each genome. Analysis of the segment alignment allows identification of those segments whose presence strongly predicts a phenotype. Clinical application of the method requires nothing more that PCR amplification of each of the set of predictive segments. Here we apply the method to identifying EHEC strains of E. coli and to distinguishing E. coli from Shigella. We show in silico that with as few as 8 predictive sequences, if even three of those predictive sequences are amplified the probability of being EHEC or Shigella is >0.99. The method is thus very robust to the occasional amplification failure for spurious reasons. Experimentally, we apply the method to screening a set of 98 isolates to distinguishing E. coli from Shigella, and EHEC from non-EHEC E. coli strains and show that all isolates are correctly identified. PMID:23935901

  6. Predicting reoffense in pedophilic child molesters by clinical diagnoses and risk assessment.

    PubMed

    Eher, Reinhard; Olver, Mark E; Heurix, Isabelle; Schilling, Frank; Rettenberger, Martin

    2015-12-01

    A Diagnostic and Statistical Manual of Mental Disorders (DSM)-based diagnosis of pedophilia has so far failed to predict sexual reoffense in convicted child molesters, probably because of its broad and unspecific conceptualization. In this study, therefore, we investigated the prognostic value of the subtype exclusive pedophilia and a series of customary risk assessment instruments (SSPI, Static-99, Stable-2007, VRS:SO) and the PCL-R in a sample of prison released pedophilic sexual offenders. First, we examined the convergent validity of risk assessment instruments (N = 261). Then, we calculated the predictive accuracy of the measures and diagnosis for sexual recidivism by ROC analyses and subsequent Cox regression (N = 189). Also, predictive values with more clinical immediacy were calculated (sensitivity, specificity, PPV and NPV). The VRS:SO, the SSPI, and the Static-99 significantly predicted sexual recidivism, as did a diagnosis of exclusive pedophilia. Also, the VRS:SO predicted sexual reoffense significantly better than the Stable-2007, the Static-99/Stable-2007 combined score, and the PCL-R. When used combined, only the VRS:SO and a diagnosis of exclusive pedophilia added incremental validity to each other. Our findings support that the clinical diagnosis of an exclusive pedophilia based on DSM criteria and VRS:SO defined risk factors can reliably discriminate higher from lower risk offenders, even within the select subgroup of pedophilic child molesters. PMID:26146817

  7. Physiologically-based pharmacokinetic modeling to predict the clinical pharmacokinetics of monoclonal antibodies.

    PubMed

    Glassman, Patrick M; Balthasar, Joseph P

    2016-08-01

    Accurate prediction of the clinical pharmacokinetics of new therapeutic entities facilitates decision making during drug discovery, and increases the probability of success for early clinical trials. Standard strategies employed for predicting the pharmacokinetics of small-molecule drugs (e.g., allometric scaling) are often not useful for predicting the disposition monoclonal antibodies (mAbs), as mAbs frequently demonstrate species-specific non-linear pharmacokinetics that is related to mAb-target binding (i.e., target-mediated drug disposition, TMDD). The saturable kinetics of TMDD are known to be influenced by a variety of factors, including the sites of target expression (which determines the accessibility of target to mAb), the extent of target expression, the rate of target turnover, and the fate of mAb-target complexes. In most cases, quantitative information on the determinants of TMDD is not available during early phases of drug discovery, and this has complicated attempts to employ mechanistic mathematical models to predict the clinical pharmacokinetics of mAbs. In this report, we introduce a simple strategy, employing physiologically-based modeling, to predict mAb disposition in humans. The approach employs estimates of inter-antibody variability in rate processes of extravasation in tissues and fluid-phase endocytosis, estimates for target concentrations in tissues derived through use of categorical immunohistochemical scores, and in vitro measures of the turnover of target and target-mAb complexes. Monte Carlo simulations were performed for four mAbs (cetuximab, figitumumab, dalotuzumab, trastuzumab) directed against three targets (epidermal growth factor receptor, insulin-like growth factor receptor 1, human epidermal growth factor receptor 2). The proposed modeling strategy was able to predict well the pharmacokinetics of cetuximab, dalotuzumab, and trastuzumab at a range of doses, but trended towards underprediction of figitumumab concentrations

  8. Genetic markers predicting sulphonylurea treatment outcomes in type 2 diabetes patients: current evidence and challenges for clinical implementation.

    PubMed

    Loganadan, N K; Huri, H Z; Vethakkan, S R; Hussein, Z

    2016-06-01

    The clinical response to sulphonylurea, an oral antidiabetic agent often used in combination with metformin to control blood glucose in type 2 diabetes (T2DM) patients, has been widely associated with a number of gene polymorphisms, particularly those involved in insulin release. We have reviewed the genetic markers of CYP2C9, ABCC8, KCNJ11, TCF7L2 (transcription factor 7-like 2), IRS-1 (insulin receptor substrate-1), CDKAL1, CDKN2A/2B, KCNQ1 and NOS1AP (nitric oxide synthase 1 adaptor protein) genes that predict treatment outcomes of sulphonylurea therapy. A convincing pattern for poor sulphonylurea response was observed in Caucasian T2DM patients with rs7903146 and rs1801278 polymorphisms of the TCF7L2 and IRS-1 genes, respectively. However, limitations in evaluating the available studies including dissimilarities in study design, definitions of clinical end points, sample sizes and types and doses of sulphonylureas used as well as ethnic variability make the clinical applications challenging. Future studies need to address these limitations to develop personalized sulphonylurea medicine for T2DM management. PMID:26810132

  9. Predicting Treatment Response for Oppositional Defiant and Conduct Disorder Using Pre-treatment Adrenal and Gonadal Hormones

    PubMed Central

    Shenk, Chad E.; Dorn, Lorah D.; Kolko, David J.; Susman, Elizabeth J.; Noll, Jennie G.; Bukstein, Oscar G.

    2016-01-01

    Variations in adrenal and gonadal hormone profiles have been linked to increased rates of oppositional defiant disorder (ODD) and conduct disorder (CD). These relationships suggest that certain hormone profiles may be related to how well children respond to psychological treatments for ODD and CD. The current study assessed whether pre-treatment profiles of adrenal and gonadal hormones predicted response to psychological treatment of ODD and CD. One hundred five children, 6 – 11 years old, participating in a randomized, clinical trial provided samples for cortisol, testosterone, dehydroepiandrosterone, and androstenedione. Diagnostic interviews of ODD and CD were administered up to three years post-treatment to track treatment response. Group-based trajectory modeling identified two trajectories of treatment response: 1) a High-response trajectory where children demonstrated lower rates of an ODD or CD diagnosis throughout follow-up, and 2) a Low-response trajectory where children demonstrated higher rates of an ODD or CD diagnosis throughout follow-up. Hierarchical logistic regression predicting treatment response demonstrated that children with higher pre-treatment concentrations of testosterone were four times more likely to be in the Low-response trajectory. No other significant relationship existed between pre-treatment hormone profiles and treatment response. These results suggest that higher concentrations of testosterone are related to how well children diagnosed with ODD or CD respond to psychological treatment over the course of three years.

  10. Predicting fertilizer nitrogen response in corn following alfalfa

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Correct prediction and application of alfalfa nitrogen (N) credits to first-year corn can reduce fertilizer N costs for growers, reduce over-application of N, and reduce the potential for water contamination. For decades, researchers have found that first-year corn following alfalfa often requires n...

  11. A rat retinal damage model predicts for potential clinical visual disturbances induced by Hsp90 inhibitors

    SciTech Connect

    Zhou, Dan; Liu, Yuan; Ye, Josephine; Ying, Weiwen; Ogawa, Luisa Shin; Inoue, Takayo; Tatsuta, Noriaki; Wada, Yumiko; Koya, Keizo; Huang, Qin; Bates, Richard C.; Sonderfan, Andrew J.

    2013-12-01

    In human trials certain heat shock protein 90 (Hsp90) inhibitors, including 17-DMAG and NVP-AUY922, have caused visual disorders indicative of retinal dysfunction; others such as 17-AAG and ganetespib have not. To understand these safety profile differences we evaluated histopathological changes and exposure profiles of four Hsp90 inhibitors, with or without clinical reports of adverse ocular effects, using a rat retinal model. Retinal morphology, Hsp70 expression (a surrogate marker of Hsp90 inhibition), apoptotic induction and pharmacokinetic drug exposure analysis were examined in rats treated with the ansamycins 17-DMAG and 17-AAG, or with the second-generation compounds NVP-AUY922 and ganetespib. Both 17-DMAG and NVP-AUY922 induced strong yet restricted retinal Hsp70 up-regulation and promoted marked photoreceptor cell death 24 h after the final dose. In contrast, neither 17-AAG nor ganetespib elicited photoreceptor injury. When the relationship between drug distribution and photoreceptor degeneration was examined, 17-DMAG and NVP-AUY922 showed substantial retinal accumulation, with high retina/plasma (R/P) ratios and slow elimination rates, such that 51% of 17-DMAG and 65% of NVP-AUY922 present at 30 min post-injection were retained in the retina 6 h post-dose. For 17-AAG and ganetespib, retinal elimination was rapid (90% and 70% of drugs eliminated from the retina at 6 h, respectively) which correlated with lower R/P ratios. These findings indicate that prolonged inhibition of Hsp90 activity in the eye results in photoreceptor cell death. Moreover, the results suggest that the retina/plasma exposure ratio and retinal elimination rate profiles of Hsp90 inhibitors, irrespective of their chemical class, may predict for ocular toxicity potential. - Highlights: • In human trials some Hsp90 inhibitors cause visual disorders, others do not. • Prolonged inhibition of Hsp90 in the rat eye results in photoreceptor cell death. • Retina/plasma ratio and retinal

  12. The value of integrating pre-clinical data to predict nausea and vomiting risk in humans as illustrated by AZD3514, a novel androgen receptor modulator.

    PubMed

    Grant, Claire; Ewart, Lorna; Muthas, Daniel; Deavall, Damian; Smith, Simon A; Clack, Glen; Newham, Pete

    2016-04-01

    Nausea and vomiting are components of a complex mechanism that signals food avoidance and protection of the body against the absorption of ingested toxins. This response can also be triggered by pharmaceuticals. Predicting clinical nausea and vomiting liability for pharmaceutical agents based on pre-clinical data can be problematic as no single animal model is a universal predictor. Moreover, efforts to improve models are hampered by the lack of translational animal and human data in the public domain. AZD3514 is a novel, orally-administered compound that inhibits androgen receptor signaling and down-regulates androgen receptor expression. Here we have explored the utility of integrating data from several pre-clinical models to predict nausea and vomiting in the clinic. Single and repeat doses of AZD3514 resulted in emesis, salivation and gastrointestinal disturbances in the dog, and inhibited gastric emptying in rats after a single dose. AZD3514, at clinically relevant exposures, induced dose-responsive "pica" behaviour in rats after single and multiple daily doses, and induced retching and vomiting behaviour in ferrets after a single dose. We compare these data with the clinical manifestation of nausea and vomiting encountered in patients with castration-resistant prostate cancer receiving AZD3514. Our data reveal a striking relationship between the pre-clinical observations described and the experience of nausea and vomiting in the clinic. In conclusion, the emetic nature of AZD3514 was predicted across a range of pre-clinical models, and the approach presented provides a valuable framework for predicition of clinical nausea and vomiting. PMID:26876616

  13. The ability of early changes in motivation to predict later antidepressant treatment response

    PubMed Central

    Gorwood, Philip; Vaiva, Guillaume; Corruble, Emmanuelle; Llorca, Pierre-Michel; Baylé, Franck J; Courtet, Philippe

    2015-01-01

    Introduction Baseline values and early changes of emotional reactivity, cognitive speed, psychomotor function, motivation, and sensory perception have not been studied to any extent in unipolar depression, although they could help to characterize different dimensions of illness that are harder to capture by clinicians, give new insights on how patients improve, and offer new early clinical markers for later treatment response. Methods About 1,565 adult outpatients with major depressive disorder receiving agomelatine completed the clinician-rated 16-item quick inventory of depressive symptoms, Clinical Global Impression, and Multidimensional Assessment of Thymic States (MAThyS) rating scales at inclusion, Week 2 and Week 6. The MAThyS includes a 20-item self-rated visual analog scale (from inhibition [0] to activation [10], with [5] representing the usual state) leading to five a priori dimensions (emotional reactivity, cognitive speed, psychomotor function, motivation, and sensory perception). Results All MAThyS dimension scores increased from inclusion to Week 2 and from inclusion to Week 6 (P<0.001). Improvement was around 2 points (out of 10) for motivation, 1.5 points for psychomotor function, and 0.5 points for other dimensions. Motivation showed a trend to being more severely impaired at inclusion in future nonresponders (t=1.25, df=1,563, P=0.10). Its improvement at Week 2 was the most discriminating MAThyS dimension between future responders and nonresponders, and represents the best predictor of future response, with the highest area under the receptor operating characteristic curve (area under curve =0.616, 95% confidence interval [0.588–0.643], P<0.001). Finally, improvements in motivation correlated the most strongly with clinician-rated 16-item quick inventory of depressive symptoms improvement (r=−0.491, df=1,563, P<0.001). Conclusion Motivation had the most capacity for early improvement, the best predictive value for response, and the largest

  14. Bronchodilator response in adults with bronchiectasis: correlation with clinical parameters and prognostic implications

    PubMed Central

    Guan, Wei-Jie; Gao, Yong-Hua; Xu, Gang; Li, Hui-Min; Yuan, Jing-Jing; Zheng, Jin-Ping

    2016-01-01

    Background Bronchial dilation testing is an important tool to assess airway reversibility in adults with bronchiectasis. This study aims to investigate the association of bronchodilator response (BDR) and clinical parameters in bronchiectasis, and the utility of BDR to indicate lung function decline and risks of bronchiectasis exacerbations (BEs). Methods We recruited 129 patients with clinically stable bronchiectasis. Baseline measurements included assessment of sputum inflammation and matrix metalloproteinase-8 and -9, sputum bacterial culture, spirometry, bronchial dilation test (for baseline FEV1 less than 80% predicted only) and chest high-resolution computed tomography (HRCT). Bronchiectasis patients were followed-up for 1 year to determine the incidence of BEs and lung function trajectories. Significant BDR was defined as FEV1 improvement from pre-dose value by at least 200 mL and 12%. Clinical trial registry No.: NCT01761214; URL: www.clinicaltrials.gov. Results BDR was negatively correlated with baseline FEV1 percentage predicted, but not blood or sputum eosinophil count. Significant BDR was not associated with greater proportion of never-smokers, poorer past history, greater HRCT scores, poorer diffusing capacity or increased sputum matrix metalloproteinases (all P>0.05). There was a trend towards higher bronchiectasis severity index (BSI) and greater proportion of patients with Pseudomonas aeruginosa isolation or infection. Significant BDR at baseline was linked to poorer spirometry, but not more rapid lung function decline, throughout follow-up. Patients with significant BDR demonstrated non-significantly lower risks of experiencing the first BEs than those without (P=0.09 for log-rank test). Conclusions Significant BDR is associated with poorer lung function compared with non-significant BDR. Whether BDR predicts future risks of BEs needs to be tested in a larger cohort. PMID:26904207

  15. Accreditation Stimuli and Evaluation Responses in a Clinical Training Program.

    ERIC Educational Resources Information Center

    Wood, David; And Others

    Assessment and evaluation skills are significant goals of clinical training, yet many clinical and counseling students lack personal experiences with applied program evaluation. Clinical psychology graduate students responded to successive impending accreditation visits by conducting in-house evaluations. Students in 1977 (N=38) and 1980 (N=35)…

  16. Fusion of clinical and stochastic finite element data for hip fracture risk prediction.

    PubMed

    Jiang, Peng; Missoum, Samy; Chen, Zhao

    2015-11-26

    Hip fracture affects more than 250,000 people in the US and 1.6 million worldwide per year. With an aging population, the development of reliable fracture risk models is therefore of prime importance. Due to the complexity of the hip fracture phenomenon, the use of clinical data only, as it is done traditionally, might not be sufficient to ensure an accurate and robust hip fracture prediction model. In order to increase the predictive ability of the risk model, the authors propose to supplement the clinical data with computational data from finite element models. The fusion of the two types of data is performed using deterministic and stochastic computational data. In the latter case, uncertainties in loading and material properties of the femur are accounted for and propagated through the finite element model. The predictive capability of a support vector machine (SVM) risk model constructed by combining clinical and finite element data was assessed using a Women׳s Health Initiative (WHI) dataset. The dataset includes common factors such as age and BMD as well as geometric factors obtained from DXA imaging. The fusion of computational and clinical data systematically leads to an increase in predictive ability of the SVM risk model as measured by the AUC metric. It is concluded that the largest gains in AUC are obtained by the stochastic approach. This gain decreases as the dimensionality of the problem increases: a 5.3% AUC improvement was achieved for a 9 dimensional problem involving geometric factors and weight while a 1.3% increase was obtained for a 20 dimensional case including geometric and conventional factors. PMID:26482733

  17. The Prediction of Response to Galantamine Treatment in Patients with Mild to Moderate Alzheimer’s Disease

    PubMed Central

    Ohnishi, Takashi; Sakiyama, Yojiro; Okuri, Yuichi; Kimura, Yuji; Sugiyama, Nami; Saito, Takayuki; Takahashi, Masayoshi; Kobayashi, Takumi

    2014-01-01

    The prediction of efficacy in long-term treatment of acetylcholinesterase inhibitors (AChEIs) is a major clinical issue, although no consistently strong predictive factors have emerged thus far. The present analyses aimed to identify factors for predicting long-term outcome of galantamine treatment. Analyses were conducted with data from a 24 weeks randomized, double-blind, placebo controlled trial to evaluate the efficacy and the safety of galantamine in the treatment of 303 patients with mild to moderate AD. Patients were divided into responders (4 or more point improvement of ADAS-cog scores at 24 weeks of treatment) and non-responders. We explored whether patients’ background (e.g. sex, age, and duration of disease) and scores of cognitive scales at early stage, are relevant to the long-term response to AChEIs. Predictive values were estimated by the logistic regression model. The responder rate was 31.7 %. We found that changes in scores of ADAS-J cog subscales between week 4 and baseline, especially word recognition, can be a good variable to predict subsequent response to galantamine, with approximately 75% of predictive performance. Characteristics of patients, including demographic characteristics, severity of disease and neuropsychological features before treatment were poorly predictive. The present study indicate that initial response to galantamine administration in patients with mild to moderate AD seems to be a reliable predictor of response of consequent galantamine treatment. Patients who show improvement of episodic memory function during the first 4 weeks of galantamine administration may be likely to particularly benefit from galantamine treatment. PMID:24156269

  18. Science, technology, and innovation: nursing responsibilities in clinical research.

    PubMed

    Grady, Christine; Edgerly, Maureen

    2009-12-01

    Clinical research is a systematic investigation of human biology, health, or illness involving human beings. It builds on laboratory and animal studies and often involves clinical trials, which are specifically designed to test the safety and efficacy of interventions in humans. Nurses are critical to the conduct of ethical clinical research and face clinical, ethical, and regulatory challenges in research in many diverse roles. Understanding and addressing the ethical challenges that complicate clinical research is integral to upholding the moral commitment that nurses make to patients, including protecting their rights and ensuring their safety as patients and as research participants. PMID:19850183

  19. Endovascular Treatment of Malignant Superior Vena Cava Syndrome: Results and Predictive Factors of Clinical Efficacy

    SciTech Connect

    Fagedet, Dorothee; Thony, Frederic; Timsit, Jean-Francois; Rodiere, Mathieu; Monnin-Bares, Valerie; Ferretti, Gilbert R.; Vesin, Aurelien; Moro-Sibilot, Denis

    2013-02-15

    To demonstrate the effectiveness of endovascular treatment (EVT) with self-expandable bare stents for malignant superior vena cava syndrome (SVCS) and to analyze predictive factors of EVT efficacy. Retrospective review of the 164 patients with malignant SVCS treated with EVT in our hospital from August 1992 to December 2007 and followed until February 2009. Endovascular treatment includes angioplasty before and after stent placement. We used self-expandable bare stents. We studied results of this treatment and looked for predictive factors of clinical efficacy, recurrence, and complications by statistical analysis. Endovascular treatment was clinically successful in 95% of cases, with an acceptable rate of early mortality (2.4%). Thrombosis of the superior vena cava was the only independent factor for EVT failure. The use of stents over 16 mm in diameter was a predictive factor for complications (P = 0.008). Twenty-one complications (12.8%) occurred during the follow-up period. Relapse occurred in 36 patients (21.9%), with effective restenting in 75% of cases. Recurrence of SVCS was significantly increased in cases of occlusion (P = 0.01), initial associated thrombosis (P = 0.006), or use of steel stents (P = 0.004). Long-term anticoagulant therapy did not influence the risk of recurrence or complications. In malignancy, EVT with self-expandable bare stents is an effective SVCS therapy. These results prompt us to propose treatment with stents earlier in the clinical course of patients with SVCS and to avoid dilatation greater than 16 mm.

  20. Dose-response curve slope helps predict therapeutic potency and breadth of HIV broadly neutralizing antibodies.

    PubMed

    Webb, Nicholas E; Montefiori, David C; Lee, Benhur

    2015-01-01

    A new generation of HIV broadly neutralizing antibodies (bnAbs) with remarkable potency, breadth and epitope diversity has rejuvenated interest in immunotherapeutic strategies. Potencies defined by in vitro IC50 and IC80 values (50 and 80% inhibitory concentrations) figure prominently into the selection of clinical candidates; however, much higher therapeutic levels will be required to reduce multiple logs of virus and impede escape. Here we predict bnAb potency at therapeutic levels by analysing dose-response curve slopes, and show that slope is independent of IC50/IC80 and specifically relates to bnAb epitope class. With few exceptions, CD4-binding site and V3-glycan bnAbs exhibit slopes >1, indicative of higher expected therapeutic effectiveness, whereas V2-glycan, gp41 membrane-proximal external region (MPER) and gp120-gp41 bnAbs exhibit less favourable slopes <1. Our results indicate that slope is one major predictor of both potency and breadth for bnAbs at clinically relevant concentrations, and may better coordinate the relationship between bnAb epitope structure and therapeutic expectations. PMID:26416571

  1. Dendritic cell vaccination for glioblastoma multiforme: review with focus on predictive factors for treatment response

    PubMed Central

    Dejaegher, Joost; Van Gool, Stefaan; De Vleeschouwer, Steven

    2014-01-01

    Glioblastoma multiforme (GBM) is the most common and most aggressive type of primary brain cancer. Since median overall survival with multimodal standard therapy is only 15 months, there is a clear need for additional effective and long-lasting treatments. Dendritic cell (DC) vaccination is an experimental immunotherapy being tested in several Phase I and Phase II clinical trials. In these trials, safety and feasibility have been proven, and promising clinical results have been reported. On the other hand, it is becoming clear that not every GBM patient will benefit from this highly personalized treatment. Defining the subgroup of patients likely to respond to DC vaccination will position this option correctly amongst other new GBM treatment modalities, and pave the way to incorporation in standard therapy. This review provides an overview of GBM treatment options and focuses on the currently known prognostic and predictive factors for response to DC vaccination. In this way, it will provide the clinician with the theoretical background to refer patients who might benefit from this treatment.

  2. A computational model that predicts reverse growth in response to mechanical unloading

    PubMed Central

    Genet, M.; Acevedo-Bolton, G.; Ordovas, K.; Guccione, J. M.; Kuhl, E.

    2014-01-01

    Ventricular growth is widely considered to be an important feature in the adverse progression of heart diseases, whereas reverse ventricular growth (or reverse remodeling) is often considered to be a favorable response to clinical intervention. In recent years, a number of theoretical models have been proposed to model the process of ventricular growth while little has been done to model its reverse. Based on the framework of volumetric strain-driven finite growth with a homeostatic equilibrium range for the elastic myofiber stretch, we propose here a reversible growth model capable of describing both ventricular growth and its reversal. We used this model to construct a semi-analytical solution based on an idealized cylindrical tube model, as well as numerical solutions based on a truncated ellipsoidal model and a human left ventricular model that was reconstructed from magnetic resonance images. We show that our model is able to predict key features in the end-diastolic pressure–volume relationship that were observed experimentally and clinically during ventricular growth and reverse growth. We also show that the residual stress fields generated as a result of differential growth in the cylindrical tube model are similar to those in other nonidentical models utilizing the same geometry. PMID:24888270

  3. Molecular profiling of prostate cancer derived exosomes may reveal a predictive signature for response to docetaxel

    PubMed Central

    Kharaziha, Pedram; Chioureas, Dimitris; Rutishauser, Dorothea; Baltatzis, George; Lennartsson, Lena; Fonseca, Pedro; Azimi, Alireza; Hultenby, Kjell; Zubarev, Roman; Ullén, Anders; Yachnin, Jeffrey; Nilsson, Sten; Panaretakis, Theocharis

    2015-01-01

    Docetaxel is a cornerstone treatment for metastatic, castration resistant prostate cancer (CRPC) which remains a leading cause of cancer-related deaths, worldwide. The clinical usage of docetaxel has resulted in modest gains in survival, primarily due to the development of resistance. There are currently no clinical biomarkers available that predict whether a CRPC patient will respond or acquire resistance to this therapy. Comparative proteomics analysis of exosomes secreted from DU145 prostate cancer cells that are sensitive (DU145 Tax-Sen) or have acquired resistance (DU145 Tax-Res) to docetaxel, demonstrated significant differences in the amount of exosomes secreted and in their molecular composition. A panel of proteins was identified by proteomics to be differentially enriched in DU145 Tax-Res compared to DU145 Tax-Sen exosomes and was validated by western blotting. Importantly, we identified MDR-1, MDR-3, Endophilin-A2 and PABP4 that were enriched only in DU145 Tax-Res exosomes. We validated the presence of these proteins in the serum of a small cohort of patients. DU145 cells that have uptaken DU145 Tax-Res exosomes show properties of increased matrix degradation. In summary, exosomes derived from DU145 Tax-Res cells may be a valuable source of biomarkers for response to therapy. PMID:25844599

  4. Dose–response curve slope helps predict therapeutic potency and breadth of HIV broadly neutralizing antibodies

    PubMed Central

    Webb, Nicholas E.; Montefiori, David C.; Lee, Benhur

    2015-01-01

    A new generation of HIV broadly neutralizing antibodies (bnAbs) with remarkable potency, breadth and epitope diversity has rejuvenated interest in immunotherapeutic strategies. Potencies defined by in vitro IC50 and IC80 values (50 and 80% inhibitory concentrations) figure prominently into the selection of clinical candidates; however, much higher therapeutic levels will be required to reduce multiple logs of virus and impede escape. Here we predict bnAb potency at therapeutic levels by analysing dose–response curve slopes, and show that slope is independent of IC50/IC80 and specifically relates to bnAb epitope class. With few exceptions, CD4-binding site and V3-glycan bnAbs exhibit slopes >1, indicative of higher expected therapeutic effectiveness, whereas V2-glycan, gp41 membrane-proximal external region (MPER) and gp120–gp41 bnAbs exhibit less favourable slopes <1. Our results indicate that slope is one major predictor of both potency and breadth for bnAbs at clinically relevant concentrations, and may better coordinate the relationship between bnAb epitope structure and therapeutic expectations. PMID:26416571

  5. Using unknown knowns to predict coastal response to future climate

    NASA Astrophysics Data System (ADS)

    Plant, N. G.; Lentz, E. E.; Gutierrez, B.; Thieler, E. R.; Passeri, D. L.

    2015-12-01

    The coastal zone, including its bathymetry, topography, ecosystem, and communities, depends on and responds to a wide array of natural and engineered processes associated with climate variability. Climate affects the frequency of coastal storms, which are only resolved probabilistically for future conditions, as well as setting the pace for persistent processes (e.g., waves driving daily alongshore transport; beach nourishment). It is not clear whether persistent processes or extreme events contribute most to the integrated evolution of the coast. Yet, observations of coastal change record the integration of persistent and extreme processes. When these observations span a large spatial domain and/or temporal range they may reflect a wide range of forcing and boundary conditions that include different levels of sea-level rise, storminess, sediment input, engineering activities, and elevation distributions. We have been using a statistical approach to characterize the interrelationships between oceanographic, ecological, and geomorphic processes—including the role played by human activities via coastal protection, beach nourishment, and other forms of coastal management. The statistical approach, Bayesian networks, incorporates existing information to establish underlying prior expectations for the distributions and inter-correlations of variables most relevant to coastal geomorphic evolution. This underlying information can then be used to make predictions. We demonstrate several examples of the utility of this approach using data as constraints and then propagating the constraints and uncertainty to make predictions of unobserved variables that include changes in shorelines, dunes, and overwash deposits. We draw on data from the Gulf and Atlantic Coasts of the United States, resolving time scales of years to a century. The examples include both short-term storm impacts and long-term evolution associated with sea-level rise. We show that the Bayesian network can

  6. Clinical Neurochemistry of Subarachnoid Hemorrhage: Toward Predicting Individual Outcomes via Biomarkers of Brain Energy Metabolism.

    PubMed

    Tholance, Yannick; Barcelos, Gleicy; Dailler, Frederic; Perret-Liaudet, Armand; Renaud, Bernard

    2015-12-16

    The functional outcome of patients with subarachnoid hemorrhage is difficult to predict at the individual level. The monitoring of brain energy metabolism has proven to be useful in improving the pathophysiological understanding of subarachnoid hemorrhage. Nonetheless, brain energy monitoring has not yet clearly been included in official guidelines for the management of subarachnoid hemorrhage patients, likely because previous studies compared only biological data between two groups of patients (unfavorable vs favorable outcomes) and did not determine decision thresholds that could be useful in clinical practice. Therefore, this Viewpoint discusses recent findings suggesting that monitoring biomarkers of brain energy metabolism at the level of individuals can be used to predict the outcomes of subarachnoid hemorrhage patients. Indeed, by taking into account specific neurochemical patterns obtained by local or global monitoring of brain energy metabolism, it may become possible to predict routinely, and with sufficient sensitivity and specificity, the individual outcomes of subarachnoid hemorrhage patients. Moreover, combining both local and global monitoring improves the overall performance of individual outcome prediction. Such a combined neurochemical monitoring approach may become, after prospective clinical validation, an important component in the management of subarachnoid hemorrhage patients to adapt individualized therapeutic interventions. PMID:26595414

  7. Development of an algorithm to predict comfort of wheelchair fit based on clinical measures

    PubMed Central

    Kon, Keisuke; Hayakawa, Yasuyuki; Shimizu, Shingo; Nosaka, Toshiya; Tsuruga, Takeshi; Matsubara, Hiroyuki; Nomura, Tomohiro; Murahara, Shin; Haruna, Hirokazu; Ino, Takumi; Inagaki, Jun; Kobayashi, Toshiki

    2015-01-01

    [Purpose] The purpose of this study was to develop an algorithm to predict the comfort of a subject seated in a wheelchair, based on common clinical measurements and without depending on verbal communication. [Subjects] Twenty healthy males (mean age: 21.5 ± 2 years; height: 171 ± 4.3 cm; weight: 56 ± 12.3 kg) participated in this study. [Methods] Each experimental session lasted for 60 min. The clinical measurements were obtained under 4 conditions (good posture, with and without a cushion; bad posture, with and without a cushion). Multiple regression analysis was performed to determine the relationship between a visual analogue scale and exercise physiology parameters (respiratory and metabolism), autonomic nervous parameters (heart rate, blood pressure, and salivary amylase level), and 3D-coordinate posture parameters (good or bad posture). [Results] For the equation (algorithm) to predict the visual analogue scale score, the adjusted multiple correlation coefficient was 0.72, the residual standard deviation was 1.2, and the prediction error was 12%. [Conclusion] The algorithm developed in this study could predict the comfort of healthy male seated in a wheelchair with 72% accuracy. PMID:26504299

  8. Development of an algorithm to predict comfort of wheelchair fit based on clinical measures.

    PubMed

    Kon, Keisuke; Hayakawa, Yasuyuki; Shimizu, Shingo; Nosaka, Toshiya; Tsuruga, Takeshi; Matsubara, Hiroyuki; Nomura, Tomohiro; Murahara, Shin; Haruna, Hirokazu; Ino, Takumi; Inagaki, Jun; Kobayashi, Toshiki

    2015-09-01

    [Purpose] The purpose of this study was to develop an algorithm to predict the comfort of a subject seated in a wheelchair, based on common clinical measurements and without depending on verbal communication. [Subjects] Twenty healthy males (mean age: 21.5 ± 2 years; height: 171 ± 4.3 cm; weight: 56 ± 12.3 kg) participated in this study. [Methods] Each experimental session lasted for 60 min. The clinical measurements were obtained under 4 conditions (good posture, with and without a cushion; bad posture, with and without a cushion). Multiple regression analysis was performed to determine the relationship between a visual analogue scale and exercise physiology parameters (respiratory and metabolism), autonomic nervous parameters (heart rate, blood pressure, and salivary amylase level), and 3D-coordinate posture parameters (good or bad posture). [Results] For the equation (algorithm) to predict the visual analogue scale score, the adjusted multiple correlation coefficient was 0.72, the residual standard deviation was 1.2, and the prediction error was 12%. [Conclusion] The algorithm developed in this study could predict the comfort of healthy male seated in a wheelchair with 72% accuracy. PMID:26504299

  9. Data Science Solution to Event Prediction in Outsourced Clinical Trial Models.

    PubMed

    Dalevi, Daniel; Lovick, Susan; Mann, Helen; Metcalfe, Paul D; Spencer, Stuart; Hollis, Sally; Ruau, David

    2015-01-01

    Late phase clinical trials are regularly outsourced to a Contract Research Organisation (CRO) while the risk and accountability remain within the sponsor company. Many statistical tasks are delivered by the CRO and later revalidated by the sponsor. Here, we report a technological approach to standardised event prediction. We have built a dynamic web application around an R-package with the aim of delivering reliable event predictions, simplifying communication and increasing trust between the CRO and the in-house statisticians via transparency. Short learning curve, interactivity, reproducibility and data diagnostics are key here. The current implementation is motivated by time-to-event prediction in oncology. We demonstrate a clear benefit of standardisation for both parties. The tool can be used for exploration, communication, sensitivity analysis and generating standard reports. At this point we wish to present this tool and share some of the insights we have gained during the development. PMID:26262364

  10. Up-regulation of emotional responses to reward-predicting stimuli: an ERP study.

    PubMed

    Langeslag, Sandra J E; van Strien, Jan W

    2013-09-01

    Altered reward processing is a hallmark symptom of many psychiatric disorders. It has recently been shown that people are capable of down-regulating reward processing. Here, we examined whether people are capable of up-regulating emotional responses to reward-predicting stimuli. Participants passively viewed colored squares that predicted a reward or no reward, and up- or down-regulated their emotional responses to these reward-predicting stimuli by focusing on the reward meaning or the color of the squares respectively. The amplitude of the late positive potential (LPP) was taken as an objective index of regulation success. The LPP in response to reward-predicting squares was enhanced by up-regulation, suggesting that up-regulation of emotional responses to reward-predicting stimuli using a cognitive strategy is feasible. These results are highly relevant for the treatment of disorders characterized by diminished motivation, and for reward-based decision making in daily life. PMID:23770414

  11. Augmenting Predictive Modeling Tools with Clinical Insights for Care Coordination Program Design and Implementation

    PubMed Central

    Johnson, Tracy L.; Brewer, Daniel; Estacio, Raymond; Vlasimsky, Tara; Durfee, Michael J.; Thompson, Kathy R.; Everhart, Rachel M.; Rinehart, Deborath J.; Batal, Holly

    2015-01-01

    Context: The Center for Medicare and Medicaid Innovation (CMMI) awarded Denver Health’s (DH) integrated, safety net health care system $19.8 million to implement a “population health” approach into the delivery of primary care. This major practice transformation builds on the Patient Centered Medical Home (PCMH) and Wagner’s Chronic Care Model (CCM) to achieve the “Triple Aim”: improved health for populations, care to individuals, and lower per capita costs. Case description: This paper presents a case study of how DH integrated published predictive models and front-line clinical judgment to implement a clinically actionable, risk stratification of patients. This population segmentation approach was used to deploy enhanced care team staff resources and to tailor care-management services to patient need, especially for patients at high risk of avoidable hospitalization. Developing, implementing, and gaining clinical acceptance of the Health Information Technology (HIT) solution for patient risk stratification was a major grant objective. Findings: In addition to describing the Information Technology (IT) solution itself, we focus on the leadership and organizational processes that facilitated its multidisciplinary development and ongoing iterative refinement, including the following: team composition, target population definition, algorithm rule development, performance assessment, and clinical-workflow optimization. We provide examples of how dynamic business intelligence tools facilitated clinical accessibility for program design decisions by enabling real-time data views from a population perspective down to patient-specific variables. Conclusions: We conclude that population segmentation approaches that integrate clinical perspectives with predictive modeling results can better identify high opportunity patients amenable to medical home-based, enhanced care team interventions. PMID:26290884

  12. Mothers' Labeling Responses to Infants' Gestures Predict Vocabulary Outcomes

    ERIC Educational Resources Information Center

    Olson, Janet; Masur, Elise Frank

    2015-01-01

    Twenty-nine infants aged 1;1 and their mothers were videotaped while interacting with toys for 18 minutes. Six experimental stimuli were presented to elicit infant communicative bids in two communicative intent contexts--proto-declarative and proto-imperative. Mothers' verbal responses to infants' gestural and non-gestural communicative bids were…

  13. Relationship-Based Infant Care: Responsive, on Demand, and Predictable

    ERIC Educational Resources Information Center

    Petersen, Sandra; Wittmer, Donna

    2008-01-01

    Young babies are easily overwhelmed by the pain of hunger or gas. However, when an infant's day is filled with caregiving experiences characterized by quick responses to his cries and accurate interpretations of the meaning of his communication, the baby learns that he can count on being fed and comforted. He begins to develop trust in his teacher…

  14. Predicting Postfeedback Performance from Students' Confidence in Their Responses.

    ERIC Educational Resources Information Center

    Bender, Timothy A.

    The model of feedback processing proposed by R. W. Kulhavy and W. A. Stock (1989) was studied in a traditional classroom setting in which methods of assessing students' response confidence as predictors of postfeedback performance were also examined. The relationship between confidence ratings at the time of the test and confidence assessed prior…

  15. Prediction of Non-invasive Mechanical Ventilation Response. Moving from Art to Science?

    PubMed

    Glover, G; Fletcher, S; Esquinas, A

    2016-03-21

    Predicting the outcome from NIV is important and the study by Martin-Gonzalez and colleagues applies data mining techniques to improve our understanding of the field. Nevertheless, the predictor variables must be robust and reliably available before NIV is applied. A predictive model must be generalisable in other clinical settings. Until models such as this are extremely robust in their predictive ability and have been shown to positively influence patient centered outcomes, they may be able to assist decision making but cannot replace clinical judgement by an experienced bedside clinician. PMID:26928232

  16. Use of Clinical Data to Predict Appendicitis in Patients with Equivocal US Findings.

    PubMed

    Athans, Brett S; Depinet, Holly E; Towbin, Alexander J; Zhang, Yue; Zhang, Bin; Trout, Andrew T

    2016-08-01

    Purpose To determine the incremental value of clinical data in patients with ultrasonographic (US) examinations that were interpreted as being equivocal for acute appendicitis. Materials and Methods Institutional review board approval, with a waiver of informed consent, was obtained for this analysis of clinical and imaging data in patients younger than 18 years old who were evaluated for acute appendicitis. Findings from US examinations were reported in a structured fashion, including two possible equivocal impressions. Clinical data were captured as Pediatric Appendicitis (PAS) or Alvarado scores and considered as categoric (high, intermediate, or low likelihood) and continuous variables to simulate stratification of equivocal US examinations to predict appendicitis. Receiver operating characteristic curves were used to define score cutoffs, and logistic regression was used to assess individual clinical variables as predictors of appendicitis. Results The study population was made up of 776 patients (mean age, 11.7 years ± 3.7), with 429 (55.2%) girls. A total of 203 (26%) patients had appendicitis. US had a negative predictive value of 96.2% and a positive predictive value of 93.3% for depicting appendicitis, with 89 of 782 (11.4%) equivocal examinations. Categoric PAS and Alvarado scores were equivocal for 59.5% (53 of 89) and 50.6% (45 of 89) of equivocal US examinations, respectively. Categoric low- and high-likelihood PAS and Alvarado scores correctly predicted the presence of appendicitis in 61.1% (22 of 36) and 77.3% (34 of 44) of equivocal US examinations, respectively. As continuous variables, a PAS or Alvarado score of 5 or lower could be used to exclude appendicitis, with a 80.8% (21 of 26) and 90% (18 of 20) negative predictive value, respectively. Conclusion The study confirms the excellent performance of US for depicting pediatric appendicitis. In the subset of equivocal US examinations, a low clinical score (≤5) may be used to identify patients

  17. Lineage-specific biomarkers predict response to FGFR inhibition.

    PubMed

    Loch, David C; Pollock, Pamela M

    2012-12-01

    In this issue of Cancer Discovery, Guagnano and colleagues use a large and diverse annotated collection of cancer cell lines, the Cancer Cell Line Encyclopedia, to correlate whole-genome expression and genomic alteration datasets with cell line sensitivity data to the novel pan-fibroblast growth factor receptor (FGFR) inhibitor NVP-BGJ398. Their findings underscore not only the preclinical use of such cell line panels in identifying predictive biomarkers, but also the emergence of the FGFRs as valid therapeutic targets, across an increasingly broad range of malignancies. PMID:23230185

  18. Bioengineered human myobundles mimic clinical responses of skeletal muscle to drugs

    PubMed Central

    Madden, Lauran; Juhas, Mark; Kraus, William E; Truskey, George A; Bursac, Nenad

    2015-01-01

    Existing in vitro models of human skeletal muscle cannot recapitulate the organization and function of native muscle, limiting their use in physiological and pharmacological studies. Here, we demonstrate engineering of electrically and chemically responsive, contractile human muscle tissues (‘myobundles’) using primary myogenic cells. These biomimetic constructs exhibit aligned architecture, multinucleated and striated myofibers, and a Pax7+ cell pool. They contract spontaneously and respond to electrical stimuli with twitch and tetanic contractions. Positive correlation between contractile force and GCaMP6-reported calcium responses enables non-invasive tracking of myobundle function and drug response. During culture, myobundles maintain functional acetylcholine receptors and structurally and functionally mature, evidenced by increased myofiber diameter and improved calcium handling and contractile strength. In response to diversely acting drugs, myobundles undergo dose-dependent hypertrophy or toxic myopathy similar to clinical outcomes. Human myobundles provide an enabling platform for predictive drug and toxicology screening and development of novel therapeutics for muscle-related disorders. DOI: http://dx.doi.org/10.7554/eLife.04885.001 PMID:25575180

  19. Clinical presentation and pharmacotherapy response in social anxiety disorder: The effect of etiological beliefs.

    PubMed

    Cohen, Jonah N; Potter, Carrie M; Drabick, Deborah A G; Blanco, Carlos; Schneier, Franklin R; Liebowitz, Michael R; Heimberg, Richard G

    2015-07-30

    Therapies for social anxiety disorder (SAD) leave many patients symptomatic at the end of treatment and little is known about predictors of treatment response. This study investigated the predictive relationship of patients' etiological attributions to initial clinical features and response to pharmacotherapy. One hundred thirty-seven individuals seeking treatment for SAD received 12 weeks of open treatment with paroxetine. Participants completed the Attributions for the Etiology of Social Anxiety Scale at baseline in addition to measures of social anxiety and depression at baseline and over the course of treatment. A latent class analysis suggested four profiles of etiological beliefs about one's SAD that may be characterized as: Familial Factors, Need to be Liked, Bad Social Experiences, and Diffuse Beliefs. Patients in the more psychosocially-driven classes, Need to be Liked and Bad Social Experiences, had the most severe social anxiety and depression at baseline. Patients in the Familial Factors class, who attributed their SAD to genetic, biological, and early life experiences, had the most rapid response to paroxetine.These results highlight the effect of biological and genetically-oriented etiological beliefs on pharmacological intervention, have implications for person-specific treatment selection, and identify potential points of intervention to augment treatment response. PMID:25920804

  20. Early Improvement in One Week Predicts the Treatment Response to Escitalopram in Patients with Social Anxiety Disorder: A Preliminary Study

    PubMed Central

    Oh, Kang-Seob; Shin, Eunsook; Ha, Juwon; Shin, Dongwon; Shin, Youngchul; Lim, Se-Won

    2016-01-01

    Objective Social anxiety disorder (SAD) shows relatively delayed responses to pharmacotherapy when compared to other anxiety disorders. Therefore, more effective early therapeutic decisions can be made if the therapeutic response is predictable as early as possible. We studied whether the therapeutic response at 12 weeks is predictable based on the early improvement with escitalopram at 1 week. Methods The subjects were 28 outpatients diagnosed with SAD. The subjects took 10–20 mg/day of escitalopram. The results of the Liebowitz social anxiety scale (LSAS), Hamilton anxiety rating scale, and Montgomery-Asberg depression rating scale were evaluated at 0, 1, 4, 8, and 12 weeks of treatment. Early improvement was defined as a ≥10% reduction in the LSAS total at 1 week of treatment, and endpoint response was defined as a ≥35% reduction in the LSAS total score. The correlation between clinical characteristics and therapeutic responses was analyzed by simple linear regression. The correlation between early improvement responses and endpoint responses was analyzed by multivariate logistic regression analysis and receiver operating characteristic curves. Results When we adjusted the influence of a ≥35% reduction in the LSAS total endpoint score on a ≥10% reduction of the LSAS total score at 1 week of treatment for the patients’ age, the early improvement group at 1 week of treatment was expected to show stronger endpoint responses compared to the group with no early improvement. Conclusion The results suggest that a ≥10% reduction in the LSAS total score in a week can predict endpoint treatment response. PMID:27121427

  1. Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications

    PubMed Central

    Howrylak, Judie A.; Fuhlbrigge, Anne L.; Strunk, Robert C.; Zeiger, Robert S.; Weiss, Scott T.; Raby, Benjamin A.

    2014-01-01

    Background Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been explored. Objective Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. Methods We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. Results We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone (P < .0001) or additional controller medications (P = .001), as well as longitudinal differences in pulmonary function (P < .0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide (P = .02) and nedocromil (P = .01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide (P = .12) and nedocromil (P = .56) compared with placebo. Conclusion Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design. PMID:24892144

  2. Multi-scale simulations predict responses to non-invasive nerve root stimulation

    NASA Astrophysics Data System (ADS)

    Laakso, Ilkka; Matsumoto, Hideyuki; Hirata, Akimasa; Terao, Yasuo; Hanajima, Ritsuko; Ugawa, Yoshikazu

    2014-10-01

    Objective. Established biophysical neurone models have achieved limited success in reproducing electrophysiological responses to non-invasive stimulation of the human nervous system. This is related to our insufficient knowledge of the induced electric currents inside the human body. Despite the numerous research and clinical applications of non-invasive stimulation, it is still unclear which internal sites are actually affected by it. Approach. We performed multi-scale computer simulations that, by making use of advances in computing power and numerical algorithms, combine a microscopic model of electrical excitation of neurones with a macroscopic electromagnetic model of the realistic whole-body anatomy. Main results. The simulations yield responses consistent with those experimentally recorded following magnetic and electrical motor root stimulation in human subjects, and reproduce the observed amplitudes and latencies for a wide variety of stimulation parameters. Significance. Our findings demonstrate that modern computational techniques can produce detailed predictions about which and where neurones are activated, leading to improved understanding of the physics and basic mechanisms of non-invasive stimulation and enabling potential new applications that make use of improved targeting of stimulation.

  3. The impact of degree of hearing loss on auditory brainstem response predictions of behavioral thresholds

    PubMed Central

    McCreery, Ryan W.; Kaminski, Jan; Beauchaine, Kathryn; Lenzen, Natalie; Simms, Kendell; Gorga, Michael P.

    2014-01-01

    Objectives: Diagnosis of hearing loss and prescription of amplification for infants and young children require accurate estimates of ear- and frequency-specific behavioral thresholds based on auditory brainstem response measurements. Although the overall relationship between ABR and behavioral thresholds has been demonstrated, the agreement is imperfect, and the accuracy of predictions of behavioral threshold based on ABR may depend on degree of hearing loss. Behavioral thresholds are lower than ABR thresholds, at least in part due to differences in calibration interacting with the effects of temporal integration, which are manifest in behavioral measurements but not ABR measurements and depend on behavioral threshold. Listeners with sensory hearing loss exhibit reduced or absent temporal integration, which could impact the relationship between ABR and behavioral thresholds as degree of hearing loss increases. The current study evaluated the relationship between ABR and behavioral thresholds in infants and children over a range of hearing thresholds, and tested an approach for adjusting the correction factor based on degree of hearing loss as estimated by ABR measurements. Design: A retrospective review of clinical records was completed for 309 ears of 177 children with hearing thresholds ranging from normal to profound hearing loss and for whom both ABR and behavioral thresholds were available. Children were required to have the same middle-ear status at both evaluations. The relationship between ABR and behavioral thresholds was examined. Factors that potentially could affect the relationship between ABR and behavioral thresholds were analyzed, including degree of hearing loss observed on the ABR, behavioral test method (visual reinforcement, conditioned play or conventional audiometry), the length of time between ABR and behavioral assessments, and clinician-reported reliability of the behavioral assessment. Predictive accuracy of a correction factor based on

  4. Sensory input attenuation allows predictive sexual response in yeast.

    PubMed

    Banderas, Alvaro; Koltai, Mihaly; Anders, Alexander; Sourjik, Victor

    2016-01-01

    Animals are known to adjust their sexual behaviour depending on mate competition. Here we report similar regulation for mating behaviour in a sexual unicellular eukaryote, the budding yeast Saccharomyces cerevisiae. We demonstrate that pheromone-based communication between the two mating types, coupled to input attenuation by recipient cells, enables yeast to robustly monitor relative mate abundance (sex ratio) within a mixed population and to adjust their commitment to sexual reproduction in proportion to their estimated chances of successful mating. The mechanism of sex-ratio sensing relies on the diffusible peptidase Bar1, which is known to degrade the pheromone signal produced by mating partners. We further show that such a response to sexual competition within a population can optimize the fitness trade-off between the costs and benefits of mating response induction. Our study thus provides an adaptive explanation for the known molecular mechanism of pheromone degradation in yeast. PMID:27557894

  5. Sensory input attenuation allows predictive sexual response in yeast

    PubMed Central

    Banderas, Alvaro; Koltai, Mihaly; Anders, Alexander; Sourjik, Victor

    2016-01-01

    Animals are known to adjust their sexual behaviour depending on mate competition. Here we report similar regulation for mating behaviour in a sexual unicellular eukaryote, the budding yeast Saccharomyces cerevisiae. We demonstrate that pheromone-based communication between the two mating types, coupled to input attenuation by recipient cells, enables yeast to robustly monitor relative mate abundance (sex ratio) within a mixed population and to adjust their commitment to sexual reproduction in proportion to their estimated chances of successful mating. The mechanism of sex-ratio sensing relies on the diffusible peptidase Bar1, which is known to degrade the pheromone signal produced by mating partners. We further show that such a response to sexual competition within a population can optimize the fitness trade-off between the costs and benefits of mating response induction. Our study thus provides an adaptive explanation for the known molecular mechanism of pheromone degradation in yeast. PMID:27557894

  6. Conceptualizing, Understanding, and Predicting Responsible Decisions and Quality Input

    NASA Astrophysics Data System (ADS)

    Wall, N.; PytlikZillig, L. M.

    2012-12-01

    In areas such as climate change, where uncertainty is high, it is arguably less difficult to tell when efforts have resulted in changes in knowledge, than when those efforts have resulted in responsible decisions. What is a responsible decision? More broadly, when it comes to citizen input, what is "high quality" input? And most importantly, how are responsible decisions and quality input enhanced? The aim of this paper is to contribute to the understanding of the different dimensions of "responsible" or "quality" public input and citizen decisions by comparing and contrasting the different predictors of those different dimensions. We first present different possibilities for defining, operationalizing and assessing responsible or high quality decisions. For example, responsible decisions or quality input might be defined as using specific content (e.g., using climate change information in decisions appropriately), as using specific processes (e.g., investing time and effort in learning about and discussing the issues prior to making decisions), or on the basis of some judgment of the decision or input itself (e.g., judgments of the rationale provided for the decisions, or number of issues considered when giving input). Second, we present results from our work engaging people with science policy topics, and the different ways that we have tried to define these two constructs. In the area of climate change specifically, we describe the development of a short survey that assesses exposure to climate information, knowledge of and attitudes toward climate change, and use of climate information in one's decisions. Specifically, the short survey was developed based on a review of common surveys of climate change related knowledge, attitudes, and behaviors, and extensive piloting and cognitive interviews. Next, we analyze more than 200 responses to that survey (data collection is currently ongoing and will be complete after the AGU deadline), and report the predictors of

  7. Attachment avoidance predicts inflammatory responses to marital conflict.

    PubMed

    Gouin, Jean-Philippe; Glaser, Ronald; Loving, Timothy J; Malarkey, William B; Stowell, Jeffrey; Houts, Carrie; Kiecolt-Glaser, Janice K

    2009-10-01

    Marital stress has been associated with immune dysregulation, including increased production of interleukin-6 (IL-6). Attachment style, one's expectations about the availability and responsiveness of others in intimate relationships, appears to influence physiological stress reactivity and thus could influence inflammatory responses to marital conflict. Thirty-five couples were invited for two 24-h admissions to a hospital research unit. The first visit included a structured social support interaction, while the second visit comprised the discussion of a marital disagreement. A mixed effect within-subject repeated measure model indicated that attachment avoidance significantly influenced IL-6 production during the conflict visit but not during the social support visit. Individuals with higher attachment avoidance had on average an 11% increase in total IL-6 production during the conflict visit as compared to the social support visit, while individuals with lower attachment avoidance had, on average, a 6% decrease in IL-6 production during the conflict visit as compared to the social support visit. Furthermore, greater attachment avoidance was associated with a higher frequency of negative behaviors and a lower frequency of positive behaviors during the marital interaction, providing a mechanism by which attachment avoidance may influence inflammatory responses to marital conflict. In sum, these results suggest that attachment avoidance modulates marital behavior and stress-induced immune dysregulation. PMID:18952163

  8. Clinical benefits of a multivariable prediction model for bladder cancer: a decision analytic approach

    PubMed Central

    Vickers, Andrew J; Cronin, Angel M; Kattan, Michael W; Gonen, Mithat; Scardino, Peter T; Milowsky, Matthew I.; Dalbagni, Guido; Bochner, Bernard H.

    2009-01-01

    Background Multivariable prediction models have been shown to predict cancer outcomes more accurately than cancer stage. The effects on clinical management are unclear. We aimed to determine whether a published multivariable prediction model for bladder cancer (“bladder nomogram”) improves medical decision making, using referral for adjuvant chemotherapy as a model. Methods We analyzed data from an international cohort study of 4462 patients undergoing cystectomy without chemotherapy 1969 – 2004. The number of patients eligible for chemotherapy was determined using pathologic stage criteria (lymph node positive or stage pT3 or pT4), and for three cut-offs on the bladder nomogram (10%, 25% and 70% risk of recurrence with surgery alone). The number of recurrences was calculated by applying a relative risk reduction to eligible patients' baseline risk. Clinical net benefit was then calculated by combining recurrences and treatments, weighting the latter by a factor related to drug tolerability. Results A nomogram cut-off outperformed pathologic stage for chemotherapy for every scenario of drug effectiveness and tolerability. For a drug with a relative risk of 0.80, where clinicians would treat no more than 20 patients to prevent one recurrence, use of the nomogram was equivalent to a strategy that resulted in 60 fewer chemotherapy treatments per 1000 patients without any increase in recurrence rates. Conclusions Referring cystectomy patients to adjuvant chemotherapy on the basis of a multivariable model is likely to lead to better patient outcomes than the use of pathological stage. Further research is warranted to evaluate the clinical effects of multivariable prediction models. PMID:19823979

  9. Negative-Margin Criterion for Impact-Response Prediction

    NASA Astrophysics Data System (ADS)

    Anderson, Denton

    2006-01-01

    Some space missions require a nuclear-power source to generate electrical power to meet mission objectives. At present, the nuclear-power source is an assembly of modular heat sources called the general purpose heat source (GPHS) modules. Each module comprises graphite shells designed to protect iridium-alloy clads which serve as the primary containment shells for the radioactive, heat-producing material. In the course of launching the space vehicle to perform its mission the nuclear heat source may be exposed to severe accident environments. One particular environment is a primary impact event where individual GPHS modules impact hard surfaces at speeds in the range of 50 meters per second or more. Tests have shown that some clads may be breached in particularly severe impacts and release a small fraction of their contents. This paper presents an empirical model for predicting essential ingredients for assessing the risk associated with primary impact events. The ingredients include: clad failure probability, release fraction of clad contents, characterization of the released material in terms of particle-size distribution and a means to estimate uncertainty in the prediction process. The empirical model focuses on the deformation of the clads and their capability to withstand deformation without breaching, measured by ductility. The basic criterion used to estimate all ingredients is called ``negative margin''. The procedure for estimating risk factors entails calculation of clad distortion by, e.g. hydrocode simulation, and high-strain-rate ductility of the iridium alloy. Negative margin is a linear combination of distortion and ductility. Regression equations derived from test data are used to calculate the clad failure probability and the fractional activity release as functions of negative margin. The mass-based particle-size distribution is calculated as a function of release fraction. Cumulative uncertainty in this computing process is evaluated using

  10. Serum miRNAs as predictive and preventive biomarker for pre-clinical hepatocellular carcinoma.

    PubMed

    Li, Liang; Chen, Jianguo; Chen, Xin; Tang, Jing; Guo, Huan; Wang, Xiaofeng; Qian, Ji; Luo, Guijuan; He, Fangping; Lu, Xiaomei; Ding, Yibo; Yang, Yingchen; Huang, Wentao; Hou, Guojun; Lin, Ximeng; Ouyang, Qin; Li, Hengyu; Wang, Ruoyu; Jiang, Feng; Pu, Rui; Lu, Jianhua; Jin, Mudan; Tan, Yexiong; Gonzalez, Frank J; Cao, Guangwen; Wu, Mengchao; Wen, Hao; Wu, Tangchun; Jin, Li; Chen, Lei; Wang, Hongyang

    2016-04-10

    The extremely poor prognosis of patients with symptomatic hepatocellular carcinoma (HCC) diagnosed clinically at advanced stages suggests an urgent need for biomarkers that can be used for prospective surveillance and pre-clinical screening for early presence of pre-malignant lesions and tumors. In a retrospective longitudinal phase 3 biomarker study in seven medical centers of China, time-series and 6 months interval-serum samples were collected from chronic hepatitis B virus infected (CHB) patient cohorts at the pre-malignant or pre-clinical stages (average 6 months prior to clinical diagnosis) and CHB patients that did not develop cancer, and circulating miRNAs measured. A set of serum miRNAs including miR-193a-3p, miR-369-5p, miR-672, miR-429 and let-7i* were identified in pre-clinical HCC patients and have the potential to screen for CHB patients at high risk to develop HCC 6-12 months after miRNAs measurement. These circulating miRNAs combined with the conventional screening tools using α-fetoprotein and ultrasound, may have great promise for the prediction and prevention of HCC in high-risk populations. PMID:26850373

  11. Breast Cancer Spatial Heterogeneity in Near-Infrared Spectra and the Prediction of Neoadjuvant Chemotherapy Response

    NASA Astrophysics Data System (ADS)

    Santoro, Ylenia

    Breast cancer accounts for more than 20% of all female cancers. Many of these patients receive neoadjuvant chemotherapy (NAC) to reduce the size of the tumor before surgery and to anticipate the efficacy of treatments for after the procedure. Breast cancer is a heterogeneous disease that comes in several clinical and histological forms. The prediction of the efficacy of chemotherapy would potentially select good candidates who would respond while excluding poor candidates who would not benefit from treatment. In this work we investigate the possibility of noninvasively predicting chemotherapy response prior to treatment based on optical biomarkers obtained from tumor spatial heterogeneities of spectral features measured using Diffuse Optical Spectroscopy. We describe an algorithm to calculate an index that characterizes spatial differences in broadband near-infrared absorption spectra of tumor-containing breast tissue. Patient-specific tumor spatial heterogeneities are visualized through a Heterogeneity Spectrum (HS). HS is a biomarker that can be attributed to different molecular distributions within the tumor. To classify lesion heterogeneities, we built a Heterogeneity Index (HI) from the HS by weighing specific absorption bands. It has been shown that NAC response is potentially related to tumor heterogeneity. Therefore, we correlate the HI obtained prior to treatment with the final response to NAC. In this thesis we also present a novel digital parallel frequency domain system for tissue imaging. The systems employs a supercontinuum laser with high brightness, and a photomultiplier with a large detection area, both allowing a deep penetration with extremely low power on the sample. The digital parallel acquisition is performed through the use of the Flimbox and it decreases the time required for standard serial systems that need to scan through all modulation frequencies. The all-digital acquisition removes analog noise, avoids the analog mixer and it does not

  12. Reward Region Responsivity Predicts Future Weight Gain and Moderating Effects of the TaqIA Allele

    PubMed Central

    Burger, Kyle S.; Yokum, Sonja

    2015-01-01

    Because no large prospective study has investigated neural vulnerability factors that predict future weight gain, we tested whether neural response to receipt and anticipated receipt of palatable food and monetary reward predicted body fat gain over a 3-year follow-up in healthy-weight adolescent humans and whether the TaqIA polymorphism moderates these relations. A total of 153 adolescents completed fMRI paradigms assessing response to these events; body fat was assessed annually over follow-up. Elevated orbitofrontal cortex response to cues signaling impending milkshake receipt predicted future body fat gain (r = 0.32), which is a novel finding that provides support for the incentive sensitization theory of obesity. Neural response to receipt and anticipated receipt of monetary reward did not predict body fat gain, which has not been tested previously. Replicating an earlier finding (Stice et al., 2008a), elevated caudate response to milkshake receipt predicted body fat gain for adolescents with a genetic propensity for greater dopamine signaling by virtue of possessing the TaqIA A2/A2 allele, but lower caudate response predicted body fat gain for adolescents with a genetic propensity for less dopamine signaling by virtue of possessing a TaqIA A1 allele, though this interaction was only marginal [p-value <0.05 corrected using voxel-level familywise error rate (pFWE) = 0.06]. Parental obesity, which correlated with TaqIA allele status (odds ratio = 2.7), similarly moderated the relation of caudate response to milkshake receipt to future body fat gain, which is another novel finding. The former interaction implies that too much or too little dopamine signaling and reward region responsivity increases risk for overeating, suggesting qualitatively distinct reward surfeit and reward deficit pathways to obesity. SIGNIFICANCE STATEMENT Because no large prospective study has investigated neural vulnerability factors that predict future weight gain we tested whether

  13. Integrative Analysis of Epigenetic Modulation in Melanoma Cell Response to Decitabine: Clinical Implications

    PubMed Central

    Halaban, Ruth; Krauthammer, Michael; Pelizzola, Mattia; Cheng, Elaine; Kovacs, Daniela; Sznol, Mario; Ariyan, Stephan; Narayan, Deepak; Bacchiocchi, Antonella; Molinaro, Annette; Kluger, Yuval; Deng, Min; Tran, Nam; Zhang, Wengeng; Picardo, Mauro; Enghild, Jan J.

    2009-01-01

    Decitabine, an epigenetic modifier that reactivates genes otherwise suppressed by DNA promoter methylation, is effective for some, but not all cancer patients, especially those with solid tumors. It is commonly recognized that to overcome resistance and improve outcome, treatment should be guided by tumor biology, which includes genotype, epigenotype, and gene expression profile. We therefore took an integrative approach to better understand melanoma cell response to clinically relevant dose of decitabine and identify complementary targets for combined therapy. We employed eight different melanoma cell strains, determined their growth, apoptotic and DNA damage responses to increasing doses of decitabine, and chose a low, clinically relevant drug dose to perform whole-genome differential gene expression, bioinformatic analysis, and protein validation studies. The data ruled out the DNA damage response, demonstrated the involvement of p21Cip1 in a p53-independent manner, identified the TGFβ pathway genes CLU and TGFBI as markers of sensitivity to decitabine and revealed an effect on histone modification as part of decitabine-induced gene expression. Mutation analysis and knockdown by siRNA implicated activated β-catenin/MITF, but not BRAF, NRAS or PTEN mutations as a source for resistance. The importance of protein stability predicted from the results was validated by the synergistic effect of Bortezomib, a proteasome inhibitor, in enhancing the growth arrest of decitabine in otherwise resistant melanoma cells. Our integrative analysis show that improved therapy can be achieved by comprehensive analysis of cancer cells, identified biomarkers for patient's selection and monitoring response, as well as targets for improved combination therapy. PMID:19234609

  14. A Coupled Probabilistic Wake Vortex and Aircraft Response Prediction Model

    NASA Technical Reports Server (NTRS)

    Gloudemans, Thijs; Van Lochem, Sander; Ras, Eelco; Malissa, Joel; Ahmad, Nashat N.; Lewis, Timothy A.

    2016-01-01

    Wake vortex spacing standards along with weather and runway occupancy time, restrict terminal area throughput and impose major constraints on the overall capacity and efficiency of the National Airspace System (NAS). For more than two decades, the National Aeronautics and Space Administration (NASA) has been conducting research on characterizing wake vortex behavior in order to develop fast-time wake transport and decay prediction models. It is expected that the models can be used in the systems level design of advanced air traffic management (ATM) concepts that safely increase the capacity of the NAS. It is also envisioned that at a later stage of maturity, these models could potentially be used operationally, in groundbased spacing and scheduling systems as well as on the flight deck.

  15. Predictions of cardiovascular responses during STS reentry using mathematical models

    NASA Technical Reports Server (NTRS)

    Leonard, J. I.; Srinivasan, R.

    1985-01-01

    The physiological adaptation to weightless exposure includes cardiovascular deconditioning arising in part from a loss of total circulating blood volume and resulting in a reduction of orthostatic tolerance. The crew of the Shuttle orbiter are less tolerant to acceleration forces in the head-to-foot direction during the reentry phase of the flight at a time they must function at a high level of performance. The factors that contribute to orthostatic intolerance during and following reentry and to predict the likelihood of impaired crew performance are evaluated. A computer simulation approach employing a mathematical model of the cardiovascular system is employed. It is shown that depending on the severity of blood volume loss, the reentry acceleration stress may be detrimental to physiologic function and may place the physiologic status of the crew near the borderline of some type of impairment. They are in agreement with conclusions from early ground-based experiments and from observations of early Shuttle flights.

  16. Response of dorsomedial prefrontal cortex predicts altruistic behavior

    PubMed Central

    Waytz, Adam; Zaki, Jamil; Mitchell, Jason P.

    2012-01-01

    Human beings have an unusual proclivity for altruistic behavior, and recent commentators have suggested that these prosocial tendencies arise from our unique capacity to understand the minds of others (i.e., to mentalize). The current studies test this hypothesis by examining the relation between altruistic behavior and the reflexive engagement of a neural system reliably associated with mentalizing. Results indicated that activity in the dorsomedial prefrontal cortex (dorsal MPFC)—a region consistently involved in understanding others’ mental states—predicts both monetary donations to others and time spent helping others. These findings address long-standing questions about the proximate source of human altruism by suggesting that prosocial behavior results, in part, from our broader tendency for social-cognitive thought. PMID:22649243

  17. Prediction of Early Response to Chemotherapy in Lung Cancer by Using Diffusion-Weighted MR Imaging

    PubMed Central

    Yu, Jing; Li, Weidong; Zhang, Zhang; Yu, Tielian; Li, Dong

    2014-01-01

    Purpose. To determine whether change of apparent diffusion coefficient (ADC) value could predict early response to chemotherapy in lung cancer. Materials and Methods. Twenty-five patients with advanced non-small cell lung cancer underwent chest MR imaging including DWI before and at the end of the first cycle of chemotherapy. The tumor's mean ADC value and diameters on MR images were calculated and compared. The grouping reference was based on serial CT scans according to Response Evaluation Criteria in Solid Tumors. Logistic regression was applied to assess treatment response prediction ability of ADC value and diameters. Results. The change of ADC value in partial response group was higher than that in stable disease group (P = 0.004). ROC curve showed that ADC value could predict treatment response with 100% sensitivity, 64.71% specificity, 57.14% positive predictive value, 100% negative predictive value, and 82.7% accuracy. The area under the curve for combination of ADC value and longest diameter change was higher than any parameter alone (P ≤ 0.01). Conclusions. The change of ADC value may be a sensitive indicator to predict early response to chemotherapy in lung cancer. Prediction ability could be improved by combining the change of ADC value and longest diameter. PMID:24688359

  18. Translating Clinical Findings into Knowledge in Drug Safety Evaluation - Drug Induced Liver Injury Prediction System (DILIps)

    PubMed Central

    Liu, Zhichao; Shi, Qiang; Ding, Don; Kelly, Reagan; Fang, Hong; Tong, Weida

    2011-01-01

    Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60–70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the “Rule of Three” was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity. PMID:22194678

  19. Western Mountain Initiative: predicting ecosystem responses to climate change

    USGS Publications Warehouse

    Baron, Jill S.; Peterson, David L.; Wilson, J.T.

    2008-01-01

    Mountain ecosystems of the western United States provide irreplaceable goods and services such as water, timber, biodiversity, and recreational opportunities, but their responses to climatic changes are complex and not well understood. The Western Mountain Initiative (WMI), a collaboration between USGS and U.S. Forest Service scientists, catalyzes assessment and synthesis of the effects of disturbance and climate change across western mountain areas, focusing on national parks and surrounding national forests. The WMI takes an ecosystem approach to science, integrating research across science disciplines at scales ranging from field studies to global trends.

  20. Development and validation of a clinical prediction rule for chest wall syndrome in primary care

    PubMed Central

    2012-01-01

    Background Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. Methods Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. Results From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner’s concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. Conclusions This CWS score offers a useful

  1. Glutamine synthetase predicts adjuvant TACE response in hepatocellular carcinoma

    PubMed Central

    Zhang, Bo; Liu, Kai; Zhang, Jian; Dong, Liwei; Jin, Zhichao; Zhang, Xinji; Xue, Feng; He, Jia

    2015-01-01

    Background: Adjuvant transcatheter arterial chemoembolization (TACE) is associated with better outcome and reduced tumor recurrence in hepatocellular carcinoma (HCC) patients. This study aimed to investigate the relationship between glutamine synthetase (GS) expression and survival of HCC patients after postoperative adjuvant TACE. Methods: We retrospectively analyzed 554 HCC patients in two independent cohorts who underwent curative resection. Immunohistochemistry assay was used to investigate the expression of GS protein and evaluate the association with survival and the response to adjuvant TACE. Results: In training cohort, patients with low GS expression who received postoperative adjuvant TACE showed a better overall survival (OS) (P<0.001) and less early phase recurrence (P=0.016). Adjuvant TACE was an independent prognostic factor for 5-year OS (HR=0.408, 95% CI 0.261-0.639, P<0.001) and early phase recurrence (HR=0.592, 95% CI 0.376-0.931, P=0.023). The same result was confirmed in validation cohort. Patients with high GS expression in both cohorts did not have a significant response to adjuvant TACE in OS and early phase recurrence. Conclusions: GS status in tumor might be a useful tool in the selection of HCC patients who would be likely to benefit from postoperative adjuvant TACE. PMID:26884995

  2. Improving models to predict phenological responses to global change

    SciTech Connect

    Richardson, Andrew D.

    2015-11-25

    The term phenology describes both the seasonal rhythms of plants and animals, and the study of these rhythms. Plant phenological processes, including, for example, when leaves emerge in the spring and change color in the autumn, are highly responsive to variation in weather (e.g. a warm vs. cold spring) as well as longer-term changes in climate (e.g. warming trends and changes in the timing and amount of rainfall). We conducted a study to investigate the phenological response of northern peatland communities to global change. Field work was conducted at the SPRUCE experiment in northern Minnesota, where we installed 10 digital cameras. Imagery from the cameras is being used to track shifts in plant phenology driven by elevated carbon dioxide and elevated temperature in the different SPRUCE experimental treatments. Camera imagery and derived products (“greenness”) is being posted in near-real time on a publicly available web page (http://phenocam.sr.unh.edu/webcam/gallery/). The images will provide a permanent visual record of the progression of the experiment over the next 10 years. Integrated with other measurements collected as part of the SPRUCE program, this study is providing insight into the degree to which phenology may mediate future shifts in carbon uptake and storage by peatland ecosystems. In the future, these data will be used to develop improved models of vegetation phenology, which will be tested against ground observations collected by a local collaborator.

  3. Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

    PubMed Central

    Cao, Jinlin; Yuan, Ping; Wang, Luming; Wang, Yiqing; Ma, Honghai; Yuan, Xiaoshuai; Lv, Wang; Hu, Jian

    2016-01-01

    The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resampling and a Chinese cohort (n = 145). A total of 4,109 patients from the SEER database were included for analysis. The multivariate analyses showed that the factors of age, race, histology, tumor site, tumor size, grade and depth of invasion, and the numbers of metastases and retrieved nodes were independent prognostic factors. All of these factors were selected into the nomogram. The nomogram showed a clear prognostic superiority over the seventh AJCC-TNM classification (C-index: SEER cohort, 0.716 vs 0.693, respectively; P < 0.01; Chinese cohort, 0.699 vs 0.680, respectively; P < 0.01). Calibration of the nomogram predicted the probabilities of 3- and 5-year survival, which corresponded closely with the actual survival rates. This novel prognostic model may improve clinicians’ abilities to predict individualized survival and to make treatment recommendations. PMID:27215834

  4. Predictive clinical and laboratory parameters for serum zinc and copper in rheumatoid arthritis.

    PubMed Central

    Mussalo-Rauhamaa, H; Konttinen, Y T; Lehto, J; Honkanen, V

    1988-01-01

    Zinc and copper have important effects on T cell mediated immunity and on neutrophil function, but it is not known how the causes or effects, of low serum zinc and high serum copper relate to the clinical picture of rheumatoid arthritis (RA). In this study serum zinc and copper determined by flame atomic absorption spectrometry and 30 other clinical, immunological, and laboratory parameters in 60 patients with RA were analysed by stepwise multiple linear regression analysis. Joint score index, rheumatoid factor titre, seropositivity, haemoglobin, and C reactive protein (CRP) were among the nine independent variables which together predicted 73% of the serum zinc variation. This suggests that there is an association between the immune-inflammatory rheumatoid process and the serum zinc concentration. CRP alone had only a 3% independent predicting value for serum zinc, however. This suggests that metallothionein mediated sequestration in the liver, induced by interleukin 1, is not an important explanatory factor in a cross sectional study of chronic inflammation. Furthermore, serum zinc did not have any predictive value at all for serum copper concentration. This does not support the hypothesis suggesting that serum zinc deficiency leads to high serum copper by inducing gastrointestinal metallothionein and high caeruloplasmin. PMID:3196083

  5. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    PubMed Central

    Alberti, Andrea; Paciaroni, Maurizio; Caso, Valeria; Venti, Michele; Palmerini, Francesco; Agnelli, Giancarlo

    2008-01-01

    Background Early seizure (ES) may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke. Patients and methods A total of 638 consecutive patients with first-ever stroke (543 ischemic, 95 hemorrhagic), admitted to our Stroke Unit, were included in this prospective study. ES were defined as seizures occurring within 7 days from acute stroke. Patients with history of epilepsy were excluded. Results Thirty-one patients (4.8%) had ES. Seizures were significantly more common in patients with cortical involvement, severe and large stroke, and in patient with cortical hemorrhagic transformation of ischemic stroke. ES was not associated with an increase in adverse outcome (mortality and disability). After multivariate analysis, hemorrhagic transformation resulted as an independent predictive factor for ES (OR = 6.5; 95% CI: 1.95–22.61; p = 0.003). Conclusion ES occur in about 5% of patients with acute stroke. In these patients hemorrhagic transformation is a predictive factor for ES. ES does not seem to be associated with an adverse outcome at hospital discharge after acute stroke. PMID:18827922

  6. Dynamic contrast-enhanced magnetic resonance imaging for prediction of response to neoadjuvant chemotherapy in breast cancer

    NASA Astrophysics Data System (ADS)

    Fu, Juzhong; Fan, Ming; Zheng, Bin; Shao, Guoliang; Zhang, Juan; Li, Lihua

    2016-03-01

    Breast cancer is the second leading cause of women death in the United States. Currently, Neoadjuvant Chemotherapy (NAC) has become standard treatment paradigms for breast cancer patients. Therefore, it is important to find a reliable non-invasive assessment and prediction method which can evaluate and predict the response of NAC on breast cancer. The Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) approach can reflect dynamic distribution of contrast agent in tumor vessels, providing important basis for clinical diagnosis. In this study, the efficacy of DCE-MRI on evaluation and prediction of response to NAC in breast cancer was investigated. To this end, fifty-seven cases of malignant breast cancers with MRI examination both before and after two cycle of NAC were analyzed. After pre-processing approach for segmenting breast lesions and background regions, 126-dimensional imaging features were extracted from DCE-MRI. Statistical analyses were then performed to evaluate the associations between the extracted DCE-MRI features and the response to NAC. Specifically, pairwise t test was used to calculate differences of imaging features between MRI examinations before-and-after NAC. Moreover, the associations of these image features with response to NAC were assessed using logistic regression. Significant association are found between response to NAC and the features of lesion morphology and background parenchymal enhancement, especially the feature of background enhancement in normal side of breast (P=0.011). Our study indicate that DCE-MRI features can provide candidate imaging markers to predict response of NAC in breast cancer.

  7. Camera response prediction for various capture settings using the spectral sensitivity and crosstalk model.

    PubMed

    Qiu, Jueqin; Xu, Haisong

    2016-09-01

    In this paper, a camera response formation model is proposed to accurately predict the responses of images captured under various exposure settings. Differing from earlier works that estimated the camera relative spectral sensitivity, our model constructs the physical spectral sensitivity curves and device-dependent parameters that convert the absolute spectral radiances of target surfaces to the camera readout responses. With this model, the camera responses to miscellaneous combinations of surfaces and illuminants could be accurately predicted. Thus, creating an "imaging simulator" by using the colorimetric and photometric research based on the cameras would be of great convenience. PMID:27607275

  8. Post-radioembolization yttrium-90 PET/CT - part 2: dose-response and tumor predictive dosimetry for resin microspheres

    PubMed Central

    2013-01-01

    Background Coincidence imaging of low-abundance yttrium-90 (90Y) internal pair production by positron emission tomography with integrated computed tomography (PET/CT) achieves high-resolution imaging of post-radioembolization microsphere biodistribution. Part 2 analyzes tumor and non-target tissue dose-response by 90Y PET quantification and evaluates the accuracy of tumor 99mTc macroaggregated albumin (MAA) single-photon emission computed tomography with integrated CT (SPECT/CT) predictive dosimetry. Methods Retrospective dose quantification of 90Y resin microspheres was performed on the same 23-patient data set in part 1. Phantom studies were performed to assure quantitative accuracy of our time-of-flight lutetium-yttrium-oxyorthosilicate system. Dose-responses were analyzed using 90Y dose-volume histograms (DVHs) by PET voxel dosimetry or mean absorbed doses by Medical Internal Radiation Dose macrodosimetry, correlated to follow-up imaging or clinical findings. Intended tumor mean doses by predictive dosimetry were compared to doses by 90Y PET. Results Phantom studies demonstrated near-perfect detector linearity and high tumor quantitative accuracy. For hepatocellular carcinomas, complete responses were generally achieved at D70 > 100 Gy (D70, minimum dose to 70% tumor volume), whereas incomplete responses were generally at D70 < 100 Gy; smaller tumors (<80 cm3) achieved D70 > 100 Gy more easily than larger tumors. There was complete response in a cholangiocarcinoma at D70 90 Gy and partial response in an adrenal gastrointestinal stromal tumor metastasis at D70 53 Gy. In two patients, a mean dose of 18 Gy to the stomach was asymptomatic, 49 Gy caused gastritis, 65 Gy caused ulceration, and 53 Gy caused duodenitis. In one patient, a bilateral kidney mean dose of 9 Gy (V20 8%) did not cause clinically relevant nephrotoxicity. Under near-ideal dosimetric conditions, there was excellent correlation between intended tumor mean doses by predictive dosimetry and those

  9. Predicting antiviral compliance: physicians' responsibilities vs. patients' rights.

    PubMed

    Senak, M

    1997-06-01

    Predicting which patients will comply with anti-HIV drug regimens is a very serious issue, since lack of compliance may cause development of drug-resistant strains of HIV that can be passed on to others. Ethical issues include addressing the well-being of the patient versus public health. Physicians are put in the position of trying to judge whether patients will comply with treatment; there are many factors involved in making this judgment. Some of these involve socioeconomic factors, e.g., a patient might sell his drugs, while other factors are failure to keep appointments or taking drugs incorrectly. Physicians should carefully examine the question of a possible noncompliance before prescribing common antiviral therapies; however, there is concern that physicians' personal biases may enter into this decision. Appropriate care and helping patients comply necessitates a partnership between the physician and patient, and decision making should be a shared process. Physicians should try to understand and address the reasons for noncompliance, so that their patients can be treated. If at all possible, the regimen should be simplified to help the patient comply with a less-difficult regimen. PMID:11364430

  10. Clinical prediction rules in Staphylococcus aureus bacteremia demonstrate the usefulness of reporting likelihood ratios in infectious diseases.

    PubMed

    Bai, A D; Showler, A; Burry, L; Steinberg, M; Tomlinson, G A; Bell, C M; Morris, A M

    2016-09-01

    Infectious diseases specialists often use diagnostic tests to assess the probability of a disease based on knowledge of the diagnostic properties. It has become standard for published studies on diagnostic tests to report sensitivity, specificity and predictive values. Likelihood ratios are often omitted. We compared published clinical prediction rules in Staphylococcus aureus bacteremia to illustrate the importance of likelihood ratios. We performed a narrative review comparing published clinical prediction rules used for excluding endocarditis in S. aureus bacteremia. Of nine published clinical prediction rules, only three studies reported likelihood ratios. Many studies concluded that the clinical