Science.gov

Sample records for predicting clinical response

  1. Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials

    PubMed Central

    Tétreault, Pascal; Mansour, Ali; Vachon-Presseau, Etienne; Schnitzer, Thomas J.; Apkarian, A. Vania

    2016-01-01

    Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo’s effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active

  2. Clinical predictive factors of sildenafil response: a penile hemodynamic study.

    PubMed

    Elhanbly, S M; Elkholy, A A-M; Alghobary, M; Abou Al-Ghar, M

    2015-03-01

    Phosphodiestrase-5 inhibitors are an important line of treatment for erectile dysfunction (ED). To detect the clinical and hemodynamic predictors of sildenafil response, we conducted this study on 124 Egyptian men with ED. All patients were evaluated by thorough history and clinical assessment with measurement of the abridged international index of erectile function-5 (IIEF-5) score. All patients were then subjected to intracavernosal injection (ICI) of trimix and pharmaco-penile duplex ultrasonography (PPDU). Patients were then classified into sildenafil responders and non-responders after six consecutive doses of 100 mg sildenafil. On doing the binary logistic stepwise regression analysis, only ED duration, IIEF-5 score, and response to ICI were the significant independent predictors of sildenafil response. These three parameters together correctly predicted the sildenafil response by 81.5% (p value <0.001). With the receiver operator characteristic curve analysis, the cut-off value of ED duration was 2.5 years and it was 14 for the IIEF-5 score. These findings indicate that ED duration, the IIEF-5 score and response to ICI are more significant predictors of sildenafil response than the more expensive and time-consuming PPDU testing. PMID:25644869

  3. Prediction of clinical response to antidepressants in patients with depression: neurophysiology in clinical practice.

    PubMed

    Pogarell, Oliver; Juckel, Georg; Norra, Christine; Leicht, Gregor; Karch, Susanne; Schaaff, Nadine; Folkerts, Malte; Ibrahim, Ahmad; Mulert, Christoph; Hegerl, Ulrich

    2007-04-01

    Brain monoaminergic neurotransmission is involved in the pathophysiology of various psychiatric disorders including depression. Reliable indicators of central monoaminergic activity might be helpful to specifically identify and differentiate dysfunctions in individual patients in order to selectively adjust medication and predict clinical response. In patients with depression, predictors of treatment response to serotonergic versus non-serotonergic (e.g., noradrenergic) antidepressants could be of considerable clinical relevance by avoiding unfavorable factors such as a prolonged duration of the disorder, risk of suicidality and therapy-resistance. Consequently, these tools might help to decrease direct and indirect costs of treatment. The loudness dependence of the N1/P2 component of auditory evoked potentials (LD) has been proposed as a noninvasive neurophysiological indicator of central serotonergic function. This review focuses on recent studies providing evidence for the validity of LD as an indirect serotonergic marker and highlights data on the clinical application in terms of prediction of treatment response in patients with depression.

  4. 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.

  5. 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.

  6. 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

  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

    Light, Gregory A; Swerdlow, Neal R

    2015-05-01

    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 nonpharmacologic interventions and accounts for substantial portions of variance in clinical, cognitive, and psychosocial functioning in schizophrenia (SZ). This measure has recently been validated for use in large-scale multisite clinical studies of SZ. Finally, 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. Clinical parameters model for predicting pathologic complete response following preoperative chemoradiation in patients with esophageal cancer

    PubMed Central

    Ajani, J. A.; Correa, A. M.; Hofstetter, W. L.; Rice, D. C.; Blum, M. A.; Suzuki, A.; Taketa, T.; Welsh, J.; Lin, S. H.; Lee, J. H.; Bhutani, M. S.; Ross, W. A.; Maru, D. M.; Macapinlac, H. A.; Erasmus, J.; Komaki, R.; Mehran, R. J.; Vaporciyan, A. A.; Swisher, S. G.

    2012-01-01

    Background Approximately 25% of patients with esophageal cancer (EC) who undergo preoperative chemoradiation, achieve a pathologic complete response (pathCR). We hypothesized that a model based on clinical parameters could predict pathCR with a high (≥60%) probability. Patients and methods We analyzed 322 patients with EC who underwent preoperative chemoradiation. All the patients had baseline and postchemoradiation positron emission tomography (PET) and pre- and postchemoradiation endoscopic biopsy. Logistic regression models were used for analysis, and cross-validation via the bootstrap method was carried out to test the model. Results The 70 (21.7%) patients who achieved a pathCR lived longer (median overall survival [OS], 79.76 months) than the 252 patients who did not achieve a pathCR (median OS, 39.73 months; OS, P = 0.004; disease-free survival, P = 0.003). In a logistic regression analysis, the following parameters contributed to the prediction model: postchemoradiation PET, postchemoradiation biopsy, sex, histologic tumor grade, and baseline EUST stage. The area under the receiver-operating characteristic curve was 0.72 (95% confidence interval [CI] 0.662–0.787); after the bootstrap validation with 200 repetitions, the bias-corrected AU-ROC was 0.70 (95% CI 0.643–0.728). Conclusion Our data suggest that the logistic regression model can predict pathCR with a high probability. This clinical model could complement others (biomarkers) to predict pathCR. PMID:22831985

  11. 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

  12. 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…

  13. Prediction of Response to Treatment in a Randomized Clinical Trial of Marital Therapy

    ERIC Educational Resources Information Center

    Atkins, David C.; Berns, Sara B.; George, William H.; Doss, Brian D.; Gattis, Krista; Christensen, Andrew

    2005-01-01

    This study investigated demographic, intrapersonal, and interpersonal predictors of treatment response in a randomized clinical trial of 134 distressed married couples, which examined traditional (N. S. Jacobson & G. Margolin, 1979) and integrative (N. S. Jacobson & A. Christensen, 1996) behavioral couple therapy. Results based on hierarchical…

  14. Machine Learning Approaches for Integrating Clinical and Imaging Features in LLD Classification and Response Prediction

    PubMed Central

    Patel, Meenal J.; Andreescu, Carmen; Price, Julie C.; Edelman, Kathryn L.; Reynolds, Charles F.; Aizenstein, Howard J.

    2015-01-01

    Objective Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Methods Late-life depression patients (medicated post-recruitment) [n=33] and elderly non-depressed individuals [n=35] were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pre-treatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. Results A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Conclusions Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures—rather than region-based differences—are associated with depression versus depression recovery since to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps towards personalized late-life depression treatment

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. Clinical relevance of total HCV core antigen testing for hepatitis C monitoring and for predicting patients' response to therapy.

    PubMed

    Maynard, M; Pradat, P; Berthillon, P; Picchio, G; Voirin, N; Martinot, M; Marcellin, P; Trepo, C

    2003-07-01

    To study the correlation between total Hepatitis C virus (HCV) Core antigen (Ag) and HCV-RNA, and to assess the proficiency of HCV Core Ag testing in monitoring and predicting virologic response during and after pegylated interferon (PEG-IFN) and ribavirin combination therapy. A total of 307 samples from treated and untreated patients were used to assess the correlation between the total HCV Core Ag test and quantitative HCV-RNA assays (Superquant, and Quantiplex branched DNA 2.0 assay). Twenty-four patients received combination therapy for 48 weeks. Blood samples were collected at day 0, and week 2, 4, 12, 24, 48 and 72 for virologic evaluation. A linear relation exists between total HCV Core Ag and HCV-RNA levels. At 3 months the positive predictive value (PPV) of response to therapy was 100% with either HCV Core Ag or HCV-RNA. For HCV Core Ag the negative predictive value (NPV) was 100% whereas for HCV-RNA the NPV was 80% (P > 0.05). At month 1, the PPV was 95% and 100% when determined by HCV Core Ag and HCV-RNA, respectively. The NPV value was 100% for HCV Core Ag and 33% for HCV-RNA (P = 0.005). HCV Core Ag quantification could be useful in clinical practice to predict a sustained virological response early during therapy (4 weeks), reaching an optimal performance at month 3. The determination of total HCV Core Ag levels in serum, constitutes an accurate and reliable alternative to HCV-RNA for monitoring and predicting treatment outcome in patients receiving PEG-IFN/Ribavirin combination therapy.

  1. 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…

  2. Clinical Evaluation of Rega 8: An Updated Genotypic Interpretation System That Significantly Predicts HIV-Therapy Response

    PubMed Central

    Vercauteren, Jurgen; Beheydt, Gertjan; Prosperi, Mattia; Libin, Pieter; Imbrechts, Stijn; Camacho, Ricardo; Clotet, Bonaventura; De Luca, Andrea; Grossman, Zehava; Kaiser, Rolf; Sönnerborg, Anders; Torti, Carlo; Van Wijngaerden, Eric; Schmit, Jean-Claude; Zazzi, Maurizio; Geretti, Anna-Maria; Vandamme, Anne-Mieke; Van Laethem, Kristel

    2013-01-01

    Introduction Clinically evaluating genotypic interpretation systems is essential to provide optimal guidance in designing potent individualized HIV-regimens. This study aimed at investigating the ability of the latest Rega algorithm to predict virological response on a short and longer period. Materials & Methods 9231 treatment changes episodes were extracted from an integrated patient database. The virological response after 8, 24 and 48 weeks was dichotomized to success and failure. Success was defined as a viral load below 50 copies/ml or alternatively, a 2 log decrease from the baseline viral load at 8 weeks. The predictive ability of Rega version 8 was analysed in comparison with that of previous evaluated version Rega 5 and two other algorithms (ANRS v2011.05 and Stanford HIVdb v6.0.11). A logistic model based on the genotypic susceptibility score was used to predict virological response, and additionally, confounding factors were added to the model. Performance of the models was compared using the area under the ROC curve (AUC) and a Wilcoxon signed-rank test. Results Per unit increase of the GSS reported by Rega 8, the odds on having a successful therapy response on week 8 increased significantly by 81% (OR = 1.81, CI = [1.76–1.86]), on week 24 by 73% (OR = 1.73, CI = [1.69–1.78]) and on week 48 by 85% (OR = 1.85, CI = [1.80–1.91]). No significant differences in AUC were found between the performance of Rega 8 and Rega 5, ANRS v2011.05 and Stanford HIVdb v6.0.11, however Rega 8 had the highest sensitivity: 76.9%, 76.5% and 77.2% on 8, 24 and 48 weeks respectively. Inclusion of additional factors increased the performance significantly. Conclusion Rega 8 is a significant predictor for virological response with a better sensitivity than previously, and with rules for recently approved drugs. Additional variables should be taken into account to ensure an effective regimen. PMID:23613852

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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…

  9. 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

  10. Utility of cardiac magnetic resonance imaging, echocardiography and electrocardiography for the prediction of clinical response and long-term survival following cardiac resynchronisation therapy.

    PubMed

    Ellims, Andris H; Pfluger, Heinz; Elsik, Maros; Butler, Michelle J; Hare, James L; Taylor, Andrew J

    2013-08-01

    Cardiac resynchronisation therapy (CRT) can reduce symptoms, hospitalisations, and mortality in patients with severe left ventricular (LV) systolic dysfunction and electro-mechanical dyssynchrony. Unfortunately, approximately 30 % of eligible patients fail to respond to CRT. This study prospectively compared electrocardiography (ECG), echocardiography, and cardiac magnetic resonance (CMR) imaging for the prediction of response to CRT. We performed ECG, echocardiography and CMR on 46 patients prior to planned CRT implantation. Patients were divided into predicted responder and non-responder groups using previously described criteria for each modality. Changes in indicators of CRT response were recorded 6 months post-implantation, and later for transplant-free survival. Less dyspnoea, lower levels of N-terminal pro-brain natriuretic peptide, more LV reverse remodelling, and longer transplant-free survival were observed in predicted responders compared to predicted non-responders using each of the three modalities (p < 0.05 for each comparison). Additionally, for patients with QRS duration <150 ms and/or non-left bundle branch block (non-LBBB) QRS morphology, CMR predicted both clinical response and improved longer term transplant-free survival (80 % transplant-free survival in predicted responders vs. 20 % in predicted non-responders, p = 0.04). ECG and cardiac imaging techniques predict improvements in markers of response following CRT with similar accuracy. However, for CRT candidates with shorter, non-LBBB QRS complexes, a subgroup known to derive less benefit from CRT, CMR may predict those who are more likely to gain both symptomatic and survival benefits.

  11. Event-related potentials. Do they reflect central serotonergic neurotransmission and do they predict clinical response to serotonin agonists?

    PubMed

    Hegerl, U; Gallinat, J; Juckel, G

    2001-01-01

    The increasing knowledge concerning anatomical structures and cellular processes underlying event-related potentials (ERP) as well as methodological advances in ERP data analysis (e.g. dipole source analysis) begin to bridge the gap between ERP and neurochemical aspects. Reliable indicators of the serotonin system are urgently needed because of its role in pathophysiology and as target of pharmacotherapeutic interventions in psychiatric disorders. Converging arguments from preclinical and clinical studies support the hypothesis that the loudness dependence of the auditory evoked N1/P2-response (LDAEP) is regulated by the level of central serotonergic neurotransmission. Dipole source analysis represents an important methodological advance in this context, because the two N1/P2-subcomponents, generated by the primary and secondary auditory cortex known to be differentially innervated by serotonergic fibers, can be separated. A pronounced LDAEP of primary auditory cortices is supposed to reflect low central serotonergic neurotransmission, and vice versa. LDAEP is a parameter with potential clinical value since subgroups of patients with a serotonergic dysfunction can be identified and can be treated more specifically. In depressed patients, a significant relationship between strong LDAEP, indicating low serotonergic function, and a favorable response to SSRI has been found. Additionally, there is evidence from several studies with patients with affective disorders implicating a strong LDAEP as a predictor of favorable response to a preventive lithium treatment. PMID:11172876

  12. 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.

  13. 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

  14. 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

  15. Clinical Model for Predicting Hepatocellular Carcinomas in Patients with Post-Sustained Virologic Responses of Chronic Hepatitis C: A Case Control Study

    PubMed Central

    Zeng, Qing-Lei; Li, Bing; Zhang, Xue-Xiu; Chen, Yan; Fu, Yan-Ling; Lv, Jun; Liu, Yan-Min; Yu, Zu-Jiang

    2016-01-01

    Background/Aims No clinical model exists to predict the occurrence of hepatocellular carcinoma in sustained virologic response-achieving (HCC after SVR) patients with chronic hepatitis C (CHC). Methods We performed a case-control study using a clinical database to research the risk factors for HCC after SVR. A predictive model based on risk factors was established, and the area under the receiver operating characteristic curve (AUC) was calculated. Results In the multivariate model, an initial diagnosis of compensated cirrhosis and post-SVR albumin reductions of 1 g/L were associated with 21.7-fold (95% CI, 4.2 to 112.3; p<0.001) and 1.3-fold (95% CI, 1.1 to 1.7; p=0.004) increases in the risk of HCC after SVR, respectively. A predictive model based on an initial diagnosis of compensated cirrhosis (yes, +1; no, 0) and post-SVR albumin ≤36.0 g/L (yes, +1; not, 0) predicted the occurrence of HCC after SVR with a cutoff value of >0, an AUC of 0.880, a sensitivity of 0.833, a specificity of 0.896, and a negative predictive value of 0.956. Conclusions An initial diagnosis of compensated cirrhosis combined with a post-SVR albumin value of ≤36.0 g/L predicts the occurrence of HCC after SVR in patients with CHC. PMID:27257023

  16. 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

  17. 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.

  18. Prediction of Methotrexate Clinical Response in Portuguese Rheumatoid Arthritis Patients: Implication of MTHFR rs1801133 and ATIC rs4673993 Polymorphisms

    PubMed Central

    Lima, Aurea; Monteiro, Joaquim; Bernardes, Miguel; Sousa, Hugo; Azevedo, Rita; Seabra, Vitor; Medeiros, Rui

    2014-01-01

    Objective. Methotrexate (MTX), the most used drug in rheumatoid arthritis (RA) treatment, showing variability in clinical response, is often associated with genetic polymorphisms. This study aimed to elucidate the role of methylenetetrahydrofolate reductase (MTHFR) C677T and aminoimidazole carboxamide adenosine ribonucleotide transformylase (ATIC) T675C polymorphisms and clinicopathological variables in clinical response to MTX in Portuguese RA patients. Methods. Study included 233 RA patients treated with MTX for at least six months. MTHFR C677T and ATIC T675C polymorphisms were genotyped and clinicopathological variables were collected. Statistical analyses were performed and binary logistic regression method adjusted to possible confounding variables. Results. Multivariate analyses demonstrated that MTHFR 677TT (OR = 4.63; P = 0.013) and ATIC 675T carriers (OR = 5.16; P = 0.013) were associated with over 4-fold increased risk for nonresponse. For clinicopathological variables, noncurrent smokers (OR = 7.98; P = 0.001), patients positive to anti-cyclic citrullinated peptide (OR = 3.53; P = 0.004) and antinuclear antibodies (OR = 2.28; P = 0.045), with higher health assessment questionnaire score (OR = 2.42; P = 0.007), and nonsteroidal anti-inflammatory drug users (OR = 2.77; P = 0.018) were also associated with nonresponse. Contrarily, subcutaneous administration route (OR = 0.11; P < 0.001) was associated with response. Conclusion. Our study suggests that MTHFR C677T and ATIC T675C genotyping combined with clinicopathological data may help to identify patients whom will not benefit from MTX treatment and, therefore, assist clinicians in personalizing RA treatment. PMID:24967362

  19. Prediction of student clinical performance.

    PubMed

    Hobfoll, S E; Benor, D E

    1981-07-01

    The predictive validity of 'traditional' tools utilized in the selection of medical students was evaluated in a 'non-traditional' selection paradigm, where a wide range of previous-academic ability was represented. The validity of the use of pre-academic grades and examination scores in the prediction of success in clinical performance was examined in a medical school which de-emphasizes these indicators and emphasizes personal characteristics assessed via interview ratings in student selection. Grades and examination scores were found to have no relation to clinical ratings which have an added interpersonal and community emphasis during the fourth-sixth years of medical school. A positive trend was found for interview ratings with clinical performance, but the skewed nature of interview scores was seen as limiting investigation of this variable. The meaning of these results vis-à-vis the continued use of academic and examination related selection criteria was discussed. PMID:7253988

  20. The role of Tc-99m sestamibi imaging in predicting clinical response to chemotherapy in lung cancer.

    PubMed

    Dirlik, Aysegul; Burak, Zeynep; Goksel, Tuncay; Erinc, Ruya; Karakus, Haydar; Ozcan, Zehra; Veral, Ali; Ozhan, Mustafa

    2002-04-01

    Multidrug resistance (MDR) is a major problem in lung cancer. Tc-99m methoxyisobutyl isonitrile (MIBI) has been demonstrated to be a non-invasive marker to diagnose MDRI related P-glycoprotein (Pgp) and multidrug resistance-associated protein (MRP) expression in various solid tumors. The aim of this study was to evaluate the relationship between the degree of Tc-99m MIBI uptake and its retention on delayed images and the response to chemotherapy in lung cancer. Twenty-three patients (1 woman and 22 men, age range 40-67 years) with lung cancer (9 small cell and 14 non-small cell) were examined with Tc-99m MIBI imaging before chemotherapy. After i.v. administration of 740 MBq Tc-99m MIBI, planar and SPECT imaging at 30 minutes and 2 hours was performed. Tumor to normal lung uptake ratio (T/N) and percent retention were measured. Response to chemotherapy was evaluated according to follow-up CT and grouped as complete responders (CR), partial responders (PR) and non-responders (NR). Clinical follow-up and CT evaluation revealed that 12 patients had partial remission, 4 patients had complete remission and 7 patients had no-remission after chemotherapy. Statistically, there was no significant correlation between early (30 min), delayed (2 hr) T/N ratios and percent retention of Tc-99m MIBI with chemotherapeutic response of the lung cancer among the three groups (p > 0.05). Results of the current study imply that Tc-99m MIBI uptake and the retention index may not correlate with chemotherapy response in lung cancer, so that the accuracy of this method needs to be verified in a larger series with additional investigation at the molecular level.

  1. 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

  2. [In unipolar depression does the response to the dexamethasone suppression test predict a symptomatic recurrence after clinical cure?].

    PubMed

    Charles, G; Schittecatte, M; Maes, J M; Rush, A J; Wilmotte, J

    1986-01-01

    We assessed the length and the quality of the remission of 13 unipolar endogenous depressed DST nonsuppressors before treatment in a 2-year prospective study. During this period, we recorded stressful life events. Persistent dexamethasone non-suppression after treatment and complete clinical recovery correlated highly with early clinical relapse. All six nonnormalizers but only one normalizer were rehospitalized within the following two years for a major depressive relapse. Persistent DST nonsuppression was unrelated to any impact of drug discontinuation, to the occurrence of stressful life events or to the length of illness-free intervals in the patient's prior course of illness. Persistent DST non-suppression appears to have a significant prognostic value.

  3. Biomarkers to Predict Antidepressant Response

    PubMed Central

    Cook, Ian A.; Hamilton, Steven P.; Narr, Katherine L.; Toga, Arthur; Hunter, Aimee M.; Faull, Kym; Whitelegge, Julian; Andrews, Anne M.; Loo, Joseph; Way, Baldwin; Nelson, Stanley F.; Horvath, Steven; Lebowitz, Barry D.

    2010-01-01

    During the past several years, we have achieved a deeper understanding of the etiology/pathophysiology of major depressive disorder (MDD). However, this improved understanding has not translated to improved treatment outcome. Treatment often results in symptomatic improvement, but not full recovery. Clinical approaches are largely trial-and-error, and when the first treatment does not result in recovery for the patient, there is little proven scientific basis for choosing the next. One approach to enhancing treatment outcomes in MDD has been the use of standardized sequential treatment algorithms and measurement-based care. Such treatment algorithms stand in contrast to the personalized medicine approach, in which biomarkers would guide decision making. Incorporation of biomarker measurements into treatment algorithms could speed recovery from MDD by shortening or eliminating lengthy and ineffective trials. Recent research results suggest several classes of physiologic biomarkers may be useful for predicting response. These include brain structural or functional findings, as well as genomic, proteomic, and metabolomic measures. Recent data indicate that such measures, at baseline or early in the course of treatment, may constitute useful predictors of treatment outcome. Once such biomarkers are validated, they could form the basis of new paradigms for antidepressant treatment selection. PMID:20963521

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Patients with collagen vascular disease and dyspnea. The value of gallium scanning and bronchoalveolar lavage in predicting response to steroid therapy and clinical outcome

    SciTech Connect

    Greene, N.B.; Solinger, A.M.; Baughman, R.P.

    1987-05-01

    Patients with collagen vascular disease with or without pulmonary symptoms were studied to determine the value of gallium scan and bronchoalveolar lavage (BAL) in predicting clinical outcome and response to steroid therapy. Thirty-six subjects, 20 with progressive dyspnea, were studied. Gallium uptake was seen in the lung in 17 of the 20 progressively dyspneic patient's and none of the 16 nonprogressive patients. The BAL fluid in the progressive patients had a higher percentage of neutrophils (13.4 percent +/- 2.88) and lymphocytes (16.1 percent +/- 2.75) than in the nonprogressive patients (neutrophils = 3.3 +/- 1.30 percent; lymphocytes = 5.6 +/- 1.57 percent. Of the 19 progressive patients who were treated with steroids or cyclophosphamide, six had only increased neutrophils in their BAL fluid and all died. The remaining 13 treated progressive patients had increased lymphocytes or a normal BAL (two patients): six had improvement in their vital capacity, six have had stable function, and one died. We found gallium scan and BAL useful in assessing progressive pulmonary fibrosis in collagen vascular disease.

  9. 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

  10. Clinical Usefulness of Urinary Fatty Acid Binding Proteins in Assessing the Severity and Predicting Treatment Response of Pneumonia in Critically Ill Patients

    PubMed Central

    Tsao, Tsung-Cheng; Tsai, Han-Chen; Chang, Shi-Chuan

    2016-01-01

    assessing the pneumonia severity and in predicting treatment response, respectively. Further studies with larger populations are needed to verify these issues. PMID:27175705

  11. The importance of molecular profiling in predicting response to epidermal growth factor receptor family inhibitors in non-small-cell lung cancer: focus on clinical trial results.

    PubMed

    Tsao, Anne S; Papadimitrakopoulou, Vassiliki

    2013-07-01

    In recent years, the epidermal growth factor receptor (EGFR) family has become a key focus of non-small-cell lung cancer biology and targeted therapies, such as the reversible EGFR tyrosine kinase inhibitors erlotinib and gefitinib. Initially, response to these agents was associated with certain demographic and clinical characteristics; subsequently, it was discovered that these subgroups were more likely to harbor specific mutations in the EGFR gene that enhanced tumor response. However, the presence of these mutations does not equate to therapeutic success. Other aspects of EGFR family signaling, including other types of EGFR mutations, EGFR protein expression, EGFR gene amplification, mediators of downstream signaling, and other receptors with similar downstream pathways may all play a role in response or resistance to treatment. The identification of these and other molecular determinants is driving the development of novel therapies designed to achieve improved clinical outcomes in patients.

  12. 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

  13. Healthcare provider perceptions of clinical prediction rules

    PubMed Central

    Richardson, Safiya; Khan, Sundas; McCullagh, Lauren; Kline, Myriam; Mann, Devin; McGinn, Thomas

    2015-01-01

    Objectives To examine internal medicine and emergency medicine healthcare provider perceptions of usefulness of specific clinical prediction rules. Setting The study took place in two academic medical centres. A web-based survey was distributed and completed by participants between 1 January and 31 May 2013. Participants Medical doctors, doctors of osteopathy or nurse practitioners employed in the internal medicine or emergency medicine departments at either institution. Primary and secondary outcome measures The primary outcome was to identify the clinical prediction rules perceived as most useful by healthcare providers specialising in internal medicine and emergency medicine. Secondary outcomes included comparing usefulness scores of specific clinical prediction rules based on provider specialty, and evaluating associations between usefulness scores and perceived characteristics of these clinical prediction rules. Results Of the 401 healthcare providers asked to participate, a total of 263 (66%), completed the survey. The CHADS2 score was chosen by most internal medicine providers (72%), and Pulmonary Embolism Rule-Out Criteria (PERC) score by most emergency medicine providers (45%), as one of the top three most useful from a list of 24 clinical prediction rules. Emergency medicine providers rated their top three significantly more positively, compared with internal medicine providers, as having a better fit into their workflow (p=0.004), helping more with decision-making (p=0.037), better fitting into their thought process when diagnosing patients (p=0.001) and overall, on a 10-point scale, more useful (p=0.009). For all providers, the perceived qualities of useful at point of care, helps with decision making, saves time diagnosing, fits into thought process, and should be the standard of clinical care correlated highly (≥0.65) with overall 10-point usefulness scores. Conclusions Healthcare providers describe clear preferences for certain clinical prediction

  14. 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

  15. Octreotide scintigraphy and Chromogranin A do not predict clinical response in patients with octreotide acetate-treated hormone-refractory prostate cancer.

    PubMed

    Kalkner, K M; Acosta, S; Thorsson, O; Frederiksen, H; Nilsson, A; Gustavsson, B; Elingsbo, M; Stridsberg, M; Abrahamsson, P-A

    2006-01-01

    In this pilot study, the predictive value of Octreotide scintigraphy (Octreoscan) and/or Chromogranin-A (CgA) was investigated in patients with hormone-refractory prostate cancer treated with Octreotide acetate. In total, 20 patients with progressive disease and bone metastases entered the trial. At baseline Octreoscan, CgA, PSA, alkaline phosphates (ALP) and two self-administered questionnaires (EORTC QLQ C-30 (v3) and brief pain index) were performed and a diary of the pharmaceutical was started. The treatment consisted of Octreotide (Sandostatin LAR) acetate 30 mg intramuscular injection every month. The blood samples and questionnaires were repeated every month until 3 months. Clinical responder was defined as a patient with increased global health score more than 10 units and stable or decreased pain score without an increase in analgesic. In all, 17 patients were treated per protocol, and four were assessed as clinical responders. Six patients developed a reduction in ALP (median -26%, range -5 to -78%). All patients increased in PSA. At baseline, three patients had a negative Octreoscan and the patients with positive lesions, demonstrated uptake of low intensity. At baseline the CgA was elevated above the normal range in 15 of the patients, and during treatment five patients decreased their CgA to the normal range. Neither baseline Octreoscan nor CgA could identify the clinical reponders. A minority of patients improves their health-related quality of life. The decrease and normalization of CgA levels in five patients during therapy indicates therapeutic activity but Octreoscan and CgA could not identify clinical responders.

  16. 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.

  17. 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

  18. 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.

  19. Predictions in the face of clinical reality: HistoCheck versus high-risk HLA allele mismatch combinations responsible for severe acute graft-versus-host disease.

    PubMed

    Askar, Medhat; Sobecks, Ronald; Morishima, Yasuo; Kawase, Takakazu; Nowacki, Amy; Makishima, Hideki; Maciejewski, Jaroslaw

    2011-09-01

    HLA polymorphism remains a major hurdle for hematopoietic stem cell transplantation (HSCT). In 2004, Elsner et al. proposed the HistoCheck Web-based tool to estimate the allogeneic potential between HLA-mismatched stem cell donor/recipient pairs expressed as a sequence similarity matching (SSM). SSM is based on the structure of HLA molecules and the functional similarity of amino acids. According to this algorithm, a high SSM score represents high dissimilarity between MHC molecules, resulting in a potentially more deleterious impact on stem cell transplant outcomes. We investigated the potential of SSM to predict high-risk HLA allele mismatch combinations responsible for severe acute graft-versus-host disease (aGVHD grades III and IV) published by Kawase et al., by comparing SSM in low- and high-risk combinations. SSM was calculated for allele mismatch combinations using the HistoCheck tool available on the Web (www.histocheck.org). We compared ranges and means of SSM among high-risk (15 combinations observed in 722 donor/recipient pairs) versus low-risk allele combinations (94 combinations in 3490 pairs). Simulation scenarios were created where the recipient's HLA allele was involved in multiple allele mismatch combinations with at least 1 high-risk and 1 low-risk mismatch combination. SSM values were then compared. The mean SSM for high- versus low-risk combinations were 2.39 and 2.90 at A, 1.06 and 2.53 at B, 16.60 and 14.99 at C, 4.02 and 3.81 at DRB1, and 7.47 and 6.94 at DPB1 loci, respectively. In simulation scenarios, no predictable SSM association with high- or low-risk combinations could be distinguished. No DQB1 combinations met the statistical criteria for our study. In conclusion, our analysis demonstrates that mean SSM scores were not significantly different, and SSM distributions were overlapping among high- and low-risk allele combinations within loci HLA-A, B, C, DRB1, and DPB1. This analysis does not support selecting donors for HSCT recipients

  20. Pairwise agonist scanning predicts cellular signaling responses to combinatorial stimuli.

    PubMed

    Chatterjee, Manash S; Purvis, Jeremy E; Brass, Lawrence F; Diamond, Scott L

    2010-07-01

    Prediction of cellular response to multiple stimuli is central to evaluating patient-specific clinical status and to basic understanding of cell biology. Cross-talk between signaling pathways cannot be predicted by studying them in isolation and the combinatorial complexity of multiple agonists acting together prohibits an exhaustive exploration of the complete experimental space. Here we describe pairwise agonist scanning (PAS), a strategy that trains a neural network model based on measurements of cellular responses to individual and all pairwise combinations of input signals. We apply PAS to predict calcium signaling responses of human platelets in EDTA-treated plasma to six different agonists (ADP, convulxin, U46619, SFLLRN, AYPGKF and PGE(2)) at three concentrations (0.1, 1 and 10 x EC(50)). The model predicted responses to sequentially added agonists, to ternary combinations of agonists and to 45 different combinations of four to six agonists (R = 0.88). Furthermore, we use PAS to distinguish between the phenotypic responses of platelets from ten donors. Training neural networks with pairs of stimuli across the dose-response regime represents an efficient approach for predicting complex signal integration in a patient-specific disease milieu. PMID:20562863

  1. Value of autoantibodies for prediction of treatment response in patients with autoimmune epilepsy: review of the literature and suggestions for clinical management.

    PubMed

    Bien, Christian G

    2013-05-01

    The detection of antineural autoantibodies in patients with epilepsy has led to the new concept of "autoimmune epilepsy." A particularly important implication is that knowledge of the antigenic target of the underlying antibody permits prognostic estimates. Patients with antibodies to the potassium channel complex (mostly to its leucine-rich glioma inactivated 1 [LGI1] component) have a high chance of becoming seizure free within days to months upon immunotherapy but less so with antiepileptic drug (AED) treatment alone. Seizures in the setting of antibodies to the N-methyl-d-aspartate receptor also have a high likelihood to remit, again especially with rapid institution of immunotherapy. In contrast to these antibodies to neuronal surface molecules, antibodies directed to intracellular antigens (onconeural antibodies, antibodies to glutamic acid decarboxylase) portend a low likelihood of seizure remission, regardless of the treatments chosen. These outcome differences are probably related to the underlying pathophysiology--with largely reversible functional effects of antibodies to surface antigens and irreversible destructive sequelae (probably caused by T cells) in patients with antibodies to intracellular antigens. With ongoing experience with these conditions, clinical and paraclinical clues to the diagnosis of autoimmune epilepsies are emerging. PMID:23646971

  2. Use of Feedback in Clinical Prediction

    ERIC Educational Resources Information Center

    Schroeder, Harold E.

    1972-01-01

    Results indicated that predictive accuracy is greater when feedback is applied to the basis for the prediction than when applied to gut" impressions. Judges forming hypotheses were also able to learn from experience. (Author)

  3. 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

  4. 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.

  5. 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

  6. Clinical Response to Valproate in Patients with Migraine

    PubMed Central

    Ichikawa, Mizuki; Katoh, Hirotaka; Kurihara, Tatsuya

    2016-01-01

    Background and Purpose Valproate is used as a prophylactic drug for migraine, but it is not be effective in all patients. We used medical records to investigate which clinical factors affected the response to valproate in patients with migraine as an original headache, and established a scoring system for predicting the clinical response to prophylactic therapy. Methods We investigated clinical factors from the medical records of 95 consistent responders (CRs) and 24 inconsistent responders (IRs) to valproate. Results Multivariate stepwise logistic regression analysis revealed that a history of hyperlipidemia and hay fever and the complication of depression or other psychiatric disorder were significant factors that independently contributed to a negative response, with odds ratios of 6.024 [no vs. yes; 95% confidence interval (CI)=1.616–22.222], 2.825 (no vs. yes; 95% CI=1.046–7.634), and 2.825 (no vs. yes; 95% CI=1.052–7.576), respectively. A predictive index (PI) of the clinical response to valproate in patients with migraine was calculated using the regression coefficients of these three factors as an integer, and the index was significantly higher for IRs than for CRs (1.46±1.10 vs. 0.69±0.74, mean±SD, p<0.001). Conclusions The obtained PI may represent an appropriate scoring system for predicting the responses in these patients.

  7. 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

  8. Coping styles predict responsiveness to cognitive behaviour therapy in psychosis.

    PubMed

    Premkumar, Preethi; Peters, Emmanuelle R; Fannon, Dominic; Anilkumar, Anantha P; Kuipers, Elizabeth; Kumari, Veena

    2011-05-30

    The study aimed to determine the clinical and neuropsychological predictors of responsiveness to cognitive behavioural therapy for psychosis (CBTp). Sixty patients with schizophrenia or schizoaffective disorder and 25 healthy individuals took part in the study. Thirty patients (25 protocol completers) received CBTp in addition to standard care (SC); 30 patients (18 protocol completers) received SC only. All patients were assessed on symptoms using the Positive and Negative Syndrome Scale (PANSS) and clinical and neuropsychological function before and after CBTp. Symptoms and self-esteem improved to a greater extent in the CBTp+SC than SC control group. Greater pre-therapy coping ability and the self-reflectiveness dimension of cognitive insight at baseline predicted improvement in symptoms in the CBTp+SC group, but not the SC control group, explaining up to 21% of the variance in symptom improvement. Pre-therapy neuropsychological function, duration of illness, clinical insight and gender did not predict CBTp responsiveness. Being able to have a range of coping strategies and reflect on one's experiences while refraining from overconfidence in one's interpretations before therapy is conducive to better CBTp responsiveness. PMID:21262541

  9. Clinical predictors of therapeutic response to antipsychotics in schizophrenia.

    PubMed

    Carbon, Maren; Correll, Christoph U

    2014-12-01

    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.

  10. 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

  11. [Personnel reduction in clinics and legal responsibility].

    PubMed

    Schelling, P

    2011-06-01

    Executive clinical physicians are increasingly being made jointly responsible for the economic success of clinics and it is to be expected that this joint responsibility will result in measures to reduce personnel. In this article it will be explained to which limits a reduction in medical personnel can be justified with respect to liability and from what level a reduction in staff can result in forensic risks. Furthermore, it will be discussed which liability or even penal responsibility in this connection affects the physicians, the hospital and especially the senior medical personnel.

  12. 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

  13. Prediction of psilocybin response in healthy volunteers.

    PubMed

    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.

  14. 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.

  15. Corticosteroid therapy in ulcerative colitis: Clinical response and predictors

    PubMed Central

    Li, Jin; Wang, Fan; Zhang, Hong-Jie; Sheng, Jian-Qiu; Yan, Wen-Feng; Ma, Min-Xing; Fan, Ru-Ying; Gu, Fang; Li, Chuan-Feng; Chen, Da-Fan; Zheng, Ping; Gu, Yu-Pei; Cao, Qian; Yang, Hong; Qian, Jia-Ming; Hu, Pin-Jin; Xia, Bing

    2015-01-01

    AIM: To evaluate clinical response to initial corticosteroid (CS) treatment in Chinese ulcerative colitis patients (UC) and identify predictors of clinical response. METHODS: Four hundred and twenty-three UC patients who were initially treated with oral or intravenous CS from 2007 to 2011 were retrospectively reviewed at eight inflammatory bowel disease centers in China, and 101 consecutive cases with one-year follow-up were analyzed further for clinical response and predictors. Short-term outcomes within one month were classified as primary response and primary non-response. Long-term outcomes within one year were classified as prolonged CS response, CS dependence and secondary non-response. CS refractoriness included primary and secondary non-response. Multivariate analyses were performed to identify predictors associated with clinical response. RESULTS: Within one month, 95.0% and 5.0% of the cases were classified into primary response and non-response, respectively. Within one year, 41.6% of cases were assessed as prolonged CS response, while 49.5% as CS dependence and 4.0% as secondary non-response. The rate of CS refractoriness was 8.9%, while the cumulative rate of surgery was 6.9% within one year. After multivariate analysis of all the variables, tenesmus was found to be a negative predictor of CS dependence (OR = 0.336; 95%CI: 0.147-0.768; P = 0.013) and weight loss as a predictor of CS refractoriness (OR = 5.662; 95%CI: 1.111-28.857; P = 0.040). After one-month treatment, sustained high Sutherland score (≥ 6) also predicted CS dependence (OR = 2.347; 95%CI: 0.935-5.890; P = 0.014). CONCLUSION: Tenesmus was a negative predictor of CS dependence, while weight loss and sustained high Sutherland score were strongly associated with poor CS response. PMID:25780299

  16. 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

  17. Clinical Evaluation of Predictive Data for Prospective Home Economics Teachers.

    ERIC Educational Resources Information Center

    Gilbert, Ardyce Lucile

    This investigation, part of a longitudinal study of homemaking teacher effectiveness, was designed to explore the usefulness of clinical judgments to predict teacher success. Clinical judgment is defined as involving the ability to make sound decisions after gathering and evaluating all the pertinent evidence, weighing possible alternatives in…

  18. The placebo response in clinical trials: more questions than answers

    PubMed Central

    Enck, Paul; Klosterhalfen, Sibylle; Weimer, Katja; Horing, Björn; Zipfel, Stephan

    2011-01-01

    Meta-analyses and re-analyses of trial data have not been able to answer some of the essential questions that would allow prediction of placebo responses in clinical trials. We will confront these questions with current empirical evidence. The most important question asks whether the placebo response rates in the drug arm and in the placebo arm are equal. This ‘additive model’ is a general assumption in almost all placebo-controlled drug trials but has rarely been tested. Secondly, we would like to address whether the placebo response is a function of the likelihood of receiving drug/placebo. Evidence suggests that the number of study arms in a trial may determine the size of the placebo and the drug response. Thirdly, we ask what the size of the placebo response is in ‘comparator’ studies with a direct comparison of a (novel) drug against another drug. Meta-analytic and experimental evidence suggests that comparator studies may produce higher placebo response rates when compared with placebo-controlled trials. Finally, we address the placebo response rate outside the laboratory and outside of trials in clinical routine. This question poses a serious challenge whether the drug response in trials can be taken as evidence of drug effects in clinical routine. PMID:21576146

  19. Responsive Assessment: Assessing Student Nurses' Clinical Competence.

    ERIC Educational Resources Information Center

    Neary, Mary

    2001-01-01

    A study involving 300 nursing students, 155 nurse practitioners, and 80 assessors tested a model of responsive assessment that includes identification of learning needs and potential, assignment to suitable placements, continuous assessment of clinical practice and patient care, and alignment of teaching and assessment with patient needs and…

  20. [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,…

  1. Human models of pain for the prediction of clinical analgesia.

    PubMed

    Lötsch, Jörn; Oertel, Bruno G; Ultsch, Alfred

    2014-10-01

    Human experimental pain models are widely used to study drug effects under controlled conditions. However, efforts to improve both animal and human experimental model selection, on the basis of increased understanding of the underlying pathophysiological pain mechanisms, have been disappointing, with poor translation of results to clinical analgesia. We have developed an alternative approach to the selection of suitable pain models that can correctly predict drug efficacy in particular clinical settings. This is based on the analysis of successful or unsuccessful empirical prediction of clinical analgesia using experimental pain models. We analyzed statistically the distribution of published mutual agreements or disagreements between drug efficacy in experimental and clinical pain settings. Significance limits were derived by random permutations of agreements. We found that a limited subset of pain models predicts a large number of clinically relevant pain settings, including efficacy against neuropathic pain for which novel analgesics are particularly needed. Thus, based on empirical evidence of agreement between drugs for their efficacy in experimental and clinical pain settings, it is possible to identify pain models that reliably predict clinical analgesic drug efficacy in cost-effective experimental settings.

  2. 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

  3. 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

  4. RECIST for Response (Clinical and Imaging) in Neoadjuvant Clinical Trials in Operable Breast Cancer.

    PubMed

    Semiglazov, Vladimir

    2015-05-01

    Although approximately 70% of breast cancer patients demonstrate a clinical response on neoadjuvant systemic therapy on physical examination or on anatomic radiographic imaging, only 3%-40% achieve a pathologic complete response (pCR). Magnetic resonance imaging (MRI) is superior to physical examination, ultrasound, and mammography in response evaluation during neoadjuvant systemic therapy. The accuracy of breast MRI to predict pCR has a moderate sensitivity, but high specificity. The accuracy of anatomic imaging to assess residual disease and predict pCR depended on anatomic radiographic imaging cancer subtypes. Response monitoring using breast is accurate in triple-negative or HER2-positive tumors. It was inaccurate in estrogen receptor-positive/HER2-negative subtype. Another approach currently under investigation is dynamic contrast-enhanced MRI and diffusion weighted-imaging, (18)F-fluorodeoxyglucose positron emission tomography, fluorodeoxyglucose positron emission tomography/computed tomography. PMID:26063880

  5. 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

  6. 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

  7. 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.

  8. Evaluating virulence of waterborne and clinical Aeromonas isolates using gene expression and mortality in neonatal mice followed by assessing cell culture’s ability to predict virulence based on transcriptional response

    SciTech Connect

    Hayes, S L; Rodgers, M R; Lye, D J; Stelma, G N; McKinstry, Craig A.; Malard, Joel M.; Vesper, Sephen J.

    2007-10-01

    Aims: To assess the virulence of Aeromonas spp. using two models, a neonatal mouse assay and a mouse intestinal cell culture. Methods and Results: After artificial infection with a variety of Aeromonas spp., mRNA extracts from the two models were processed and hydridized to murine microarrays to determine host gene response. Definition of virulence was determined based on host mRNA production in murine neonatal intestinal tissue and mortality of infected animals. Infections of mouse intestinal cell cultures were then performed to determine whether this simpler model system’s mRNA responses correlated to neonatal results and therefore be predictive of virulence of Aeromonas spp. Virulent aeromonads up-regulated transcripts in both models including multiple host defense gene products (chemokines, regulation of transcription and apoptosis and cell signalling). Avirulent species exhibited little or no host response in neonates. Mortality results correlated well with both bacterial dose and average fold change of up-regulated transcripts in the neonatal mice. Conclusions: Cell culture results were less discriminating but showed promise as potentially being able to be predictive of virulence. Jun oncogene up-regulation in murine cell culture is potentially predictive of Aeromonas virulence. Significance and Impact of the Study: Having the ability to determine virulence of waterborne pathogens quickly would potentially assist public health officials to rapidly assess exposure risks.

  9. 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

  10. 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

  11. Predictability Influences Stopping and Response Control

    ERIC Educational Resources Information Center

    Morein-Zamir, Sharon; Chua, Romeo; Franks, Ian; Nagelkerke, Paul; Kingstone, Alan

    2007-01-01

    Using a continuous tracking task, the authors examined whether stopping is resistant to expectancies as well as whether it is a representative measure of response control. Participants controlled the speed of a moving marker by continuously adjusting their response force. Participants stopped their ongoing tracking in response to auditory signals…

  12. 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…

  13. [Clinical probability of PE: should we use a clinical prediction rule?].

    PubMed

    Le Gal, G; Righini, M; Perrier, A

    2008-12-01

    The determination of the clinical pretest probability using clinical prediction models is an important step in the assessment of patients with suspected pulmonary embolism (PE). It helps establish which test or sequence of tests can effectively corroborate or safely rule out PE. For example, it has been demonstrated that it is safe to withhold anticoagulant therapy in patients with negative d-dimer results and low pretest probability at initial presentation. Clinical probability will also increase the diagnostic yield of ventilation perfusion lung scan. Compared with clinical gestalt, clinical prediction rules provide a standardized and more reproducible estimate of a patient's probability of having a PE. Clinical prediction models combine aspects of the history and physical examination to categorize a patient's probability of having a disease. The models classify patients as having a low, moderate, or high likelihood of having PE. Clinical prediction models have been validated and are well established for the diagnosis of PE in symptomatic patients. They allow all physicians, whatever their expertise, to reliably determine the clinical pretest probability of PE, and thus safely manage their patients using diagnostic and therapeutic algorithms. PMID:19084205

  14. Prediction of clinical risks by analysis of preclinical and clinical adverse events.

    PubMed

    Clark, Matthew

    2015-04-01

    This study examines the ability of nonclinical adverse event observations to predict human clinical adverse events observed in drug development programs. In addition it examines the relationship between nonclinical and clinical adverse event observations to drug withdrawal and proposes a model to predict drug withdrawal based on these observations. These analyses provide risk assessments useful for both planning patient safety programs, as well as a statistical framework for assessing the future success of drug programs based on nonclinical and clinical observations. Bayesian analyses were undertaken to investigate the connection between nonclinical adverse event observations and observations of that same event in clinical trial for a large set of approved drugs. We employed the same statistical methods used to evaluate the efficacy of diagnostic tests to evaluate the ability of nonclinical studies to predict adverse events in clinical studies, and adverse events in both to predict drug withdrawal. We find that some nonclinical observations suggest higher risk for observing the same adverse event in clinical studies, particularly arrhythmias, QT prolongation, and abnormal hepatic function. However the lack of these events in nonclinical studies is found to not be a good predictor of safety in humans. Some nonclinical and clinical observations appear to be associated with high risk of drug withdrawal from market, especially arrhythmia and hepatic necrosis. We use the method to estimate the overall risk of drug withdrawal from market using the product of the risks from each nonclinical and clinical observation to create a risk profile.

  15. Prediction of clinical risks by analysis of preclinical and clinical adverse events.

    PubMed

    Clark, Matthew

    2015-04-01

    This study examines the ability of nonclinical adverse event observations to predict human clinical adverse events observed in drug development programs. In addition it examines the relationship between nonclinical and clinical adverse event observations to drug withdrawal and proposes a model to predict drug withdrawal based on these observations. These analyses provide risk assessments useful for both planning patient safety programs, as well as a statistical framework for assessing the future success of drug programs based on nonclinical and clinical observations. Bayesian analyses were undertaken to investigate the connection between nonclinical adverse event observations and observations of that same event in clinical trial for a large set of approved drugs. We employed the same statistical methods used to evaluate the efficacy of diagnostic tests to evaluate the ability of nonclinical studies to predict adverse events in clinical studies, and adverse events in both to predict drug withdrawal. We find that some nonclinical observations suggest higher risk for observing the same adverse event in clinical studies, particularly arrhythmias, QT prolongation, and abnormal hepatic function. However the lack of these events in nonclinical studies is found to not be a good predictor of safety in humans. Some nonclinical and clinical observations appear to be associated with high risk of drug withdrawal from market, especially arrhythmia and hepatic necrosis. We use the method to estimate the overall risk of drug withdrawal from market using the product of the risks from each nonclinical and clinical observation to create a risk profile. PMID:25746390

  16. [Application of three compartment model and response surface model to clinical anesthesia using Microsoft Excel].

    PubMed

    Abe, Eiji; Abe, Mari

    2011-08-01

    With the spread of total intravenous anesthesia, clinical pharmacology has become more important. We report Microsoft Excel file applying three compartment model and response surface model to clinical anesthesia. On the Microsoft Excel sheet, propofol, remifentanil and fentanyl effect-site concentrations are predicted (three compartment model), and probabilities of no response to prodding, shaking, surrogates of painful stimuli and laryngoscopy are calculated using predicted effect-site drug concentration. Time-dependent changes in these calculated values are shown graphically. Recent development in anesthetic drug interaction studies are remarkable, and its application to clinical anesthesia with this Excel file is simple and helpful for clinical anesthesia.

  17. 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.

  18. 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

  19. 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

  20. Genomic and Histopathological Tissue Biomarkers That Predict Radiotherapy Response in Localised Prostate Cancer

    PubMed Central

    Wilkins, Anna; Dearnaley, David; Somaiah, Navita

    2015-01-01

    Localised prostate cancer, in particular, intermediate risk disease, has varied survival outcomes that cannot be predicted accurately using current clinical risk factors. External beam radiotherapy (EBRT) is one of the standard curative treatment options for localised disease and its efficacy is related to wide ranging aspects of tumour biology. Histopathological techniques including immunohistochemistry and a variety of genomic assays have been used to identify biomarkers of tumour proliferation, cell cycle checkpoints, hypoxia, DNA repair, apoptosis, and androgen synthesis, which predict response to radiotherapy. Global measures of genomic instability also show exciting capacity to predict survival outcomes following EBRT. There is also an urgent clinical need for biomarkers to predict the radiotherapy fraction sensitivity of different prostate tumours and preclinical studies point to possible candidates. Finally, the increased resolution of next generation sequencing (NGS) is likely to enable yet more precise molecular predictions of radiotherapy response and fraction sensitivity. PMID:26504789

  1. 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.

  2. The Autonomic System Functional State Predicts Responsiveness in Disorder of Consciousness.

    PubMed

    Riganello, Francesco; Cortese, Maria D; Dolce, Giuliano; Lucca, Lucia F; Sannita, Walter G

    2015-07-15

    Diagnosis and early prognosis of the vegetative state/unresponsive wakefulness syndrome (VS/UWS) and its differentiation from the minimally-conscious state still rest on the clinical observation of responsiveness. The incidence of established clinical indicators of responsiveness also has proven variable in the single subject and is correlated to measures of heart rate variability (HRV) describing the sympathetic/parasympathetic balance. We tested responsiveness when the HRV descriptors nuLF and peakLF were or were not in the ranges with highest incidence of response based on findings from previous studies (10.0-70.0 and 0.05-0.11 Hz, respectively). Testing was blind by The Coma Recovery Scale-revised in the two conditions and in two experimental sessions with a one-week interval. The incidence of responses was not randomly distributed in the "response" and "no-response" conditions (McNemar test; p < 0.0001). The observed incidence in the "response" condition (visual: 55.1%; auditory: 51.5%) was higher than predicted statistically (32.1%) or described in previous clinical studies; responses were only occasional in the "no-response" condition (visual, 15.9%; auditory, 13.4%). Models validated the predictability with high accuracy. The current clinical criteria for diagnosis and prognosis based on neurological signs should be reconsidered, including variability over time and the autonomic system functional state, which could also qualify per se as an independent indicator for diagnosis and prognosis.

  3. Pretreatment anterior cingulate activity predicts antidepressant treatment response in major depressive episodes.

    PubMed

    Rentzsch, Johannes; Adli, Mazda; Wiethoff, Katja; Gómez-Carrillo de Castro, Ana; Gallinat, Jürgen

    2014-04-01

    Major depressive disorder leads to substantial individual and socioeconomic costs. Despite the ongoing efforts to improve the treatment for this condition, a trial-and-error approach until an individually effective treatment is established still dominates clinical practice. Searching for clinically useful treatment response predictors is one of the most promising strategies to change this quandary therapeutic situation. This study evaluated the predictive value of a biological and a clinical predictor, as well as a combination of both. Pretreatment EEGs of 31 patients with a major depressive episode were analyzed with neuroelectric brain imaging technique to assess cerebral oscillations related to treatment response. Early improvement of symptoms served as a clinical predictor. Treatment response was assessed after 4 weeks of antidepressant treatment. Responders showed more slow-frequency power in the right anterior cingulate cortex compared to non-responders. Slow-frequency power in this region was found to predict response with good sensitivity (82 %) and specificity (100 %), while early improvement showed lower accuracy (73 % sensitivity and 65 % specificity). Combining both parameters did not further improve predictive accuracy. Pretreatment activity within the anterior cingulate cortex is related to antidepressive treatment response. Our results support the search for biological treatment response predictors using electric brain activity. This technique is advantageous due to its low individual and socioeconomic burden. The benefits of combining both, a clinically and a biologically based predictor, should be further evaluated using larger sample sizes.

  4. 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

  5. Both Financial and Cognitive Decline Predict Clinical Progression in MCI.

    PubMed

    Gerstenecker, Adam; Triebel, Kristen L; Martin, Roy; Snyder, Scott; Marson, Daniel C

    2016-01-01

    We investigated the roles of financial/functional and cognitive abilities in predicting clinical progression in patients with mild cognitive impairment (MCI). In a longitudinal sample of 51 patients with consensus conference diagnosed MCI likely due to Alzheimer disease (AD), two-year change scores were calculated for a performance measure of functional ability, cognitive variables, and 3 outcome measures used to track progression in neurological disorders. We examined patterns of financial and cognitive decline across the 2-year study period, and used these data and the 3 outcome variables to construct discrete predictor models of clinical progression in MCI. We found that both financial skills and cognitive abilities declined over the 2-year study period, were significantly associated with clinical progression, and contributed unique variance to all 3 predictor models. The resulting models accounted for 40% to 75% of variance in clinical progression across outcome variables. Taken together, our results indicate that changes in both cognitive abilities and higher order functional skills appear integral to understanding clinical progression in MCI likely due to AD. Specifically, declines in financial skills contribute unique variance to measures commonly used to track progression in neurological disorders associated with aging, and thus represent an important functional marker of clinical progression in prodromal AD.

  6. 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

  7. Mass Law Predicts Hyperbolic Hypoxic Ventilatory Response

    NASA Astrophysics Data System (ADS)

    Severinghaus, John W.

    The hyperbolic hypoxic ventilatory response vs PaO2, HVRp, is interpreted as relecting a mass hyperbolic relationship of cytochrome PcO2 to cytochrome potential Ec, offset 32 torr by the constant diffusion gradient between arterial blood and cytochrome in CB at its constant metabolic rate dot VO_2 . Ec is taken to be a linear function of redox reduction and CB ventilatory drive. As Ec rises in hypoxia, the absolute potentials of each step in the citric acid cycle rises equally while the potential drop across each step remains constant because flux rate remains constant. A hypothetic HVRs ( dot VE vs SaO2) response curve computed from these assumptions is strikingly non linear. A hypothetic HVRp calculated from an assumed linear HVRs cannot be fit to the observed hyperbolic increase of ventilation in response to isocapnic hypoxia at PO2 less than 40 torr. The incompatibility of these results suggest that in future studies HVRs will not be found to be linear, especially below 80% SaO2 and HVRp will fail to be accurately hyperbolic.

  8. Motor cortex activity predicts response alternation during sensorimotor decisions

    PubMed Central

    Pape, Anna-Antonia; Siegel, Markus

    2016-01-01

    Our actions are constantly guided by decisions based on sensory information. The motor cortex is traditionally viewed as the final output stage in this process, merely executing motor responses based on these decisions. However, it is not clear if, beyond this role, the motor cortex itself impacts response selection. Here, we report activity fluctuations over motor cortex measured using MEG, which are unrelated to choice content and predict responses to a visuomotor task seconds before decisions are made. These fluctuations are strongly influenced by the previous trial's response and predict a tendency to switch between response alternatives for consecutive decisions. This alternation behaviour depends on the size of neural signals still present from the previous response. Our results uncover a response-alternation bias in sensorimotor decision making. Furthermore, they suggest that motor cortex is more than an output stage and instead shapes response selection during sensorimotor decision making. PMID:27713396

  9. Clinical prediction rules for failed nonoperative reduction of intussusception

    PubMed Central

    Khorana, Jiraporn; Patumanond, Jayanton; Ukarapol, Nuthapong; Laohapensang, Mongkol; Visrutaratna, Pannee; Singhavejsakul, Jesda

    2016-01-01

    Purpose The nonoperative reduction of intussusception in children can be performed safely if there are no contraindications. Many risk factors associated with failed reduction were defined. The aim of this study was to develop a scoring system for predicting the failure of nonoperative reduction using various determinants. Patients and methods The data were collected from Chiang Mai University Hospital and Siriraj Hospital from January 2006 to December 2012. Inclusion criteria consisted of patients with intussusception aged 0–15 years with no contraindications for nonoperative reduction. The clinical prediction rules were developed using significant risk factors from the multivariable analysis. Results A total of 170 patients with intussusception were included in the study. In the final analysis model, 154 patients were used for identifying the significant risk factors of failure of reduction. Ten factors clustering by the age of 3 years were identified and used for developing the clinical prediction rules, and the factors were as follows: body weight <12 kg (relative risk [RR] =1.48, P=0.004), duration of symptoms >48 hours (RR =1.26, P<0.001), vomiting (RR =1.63, P<0.001), rectal bleeding (RR =1.50, P<0.001), abdominal distension (RR =1.60, P=0.003), temperature >37.8°C (RR =1.51, P<0.001), palpable mass (RR =1.26, P<0.001), location of mass (left over right side RR =1.48, P<0.001), ultrasound showed poor prognostic signs (RR =1.35, P<0.001), and the method of reduction (hydrostatic over pneumatic, RR =1.34, P=0.023). Prediction scores ranged from 0 to 16. A high-risk group (scores 12–16) predicted a greater chance of reduction failure (likelihood ratio of positive [LR+] =18.22, P<0.001). A low-risk group (score 0–11) predicted a lower chance of reduction failure (LR+ =0.79, P<0.001). The performance of the scoring model was 80.68% (area under the receiver operating characteristic curve). Conclusion This scoring guideline was used to predict the results of

  10. Clinical prediction rules for failed nonoperative reduction of intussusception

    PubMed Central

    Khorana, Jiraporn; Patumanond, Jayanton; Ukarapol, Nuthapong; Laohapensang, Mongkol; Visrutaratna, Pannee; Singhavejsakul, Jesda

    2016-01-01

    Purpose The nonoperative reduction of intussusception in children can be performed safely if there are no contraindications. Many risk factors associated with failed reduction were defined. The aim of this study was to develop a scoring system for predicting the failure of nonoperative reduction using various determinants. Patients and methods The data were collected from Chiang Mai University Hospital and Siriraj Hospital from January 2006 to December 2012. Inclusion criteria consisted of patients with intussusception aged 0–15 years with no contraindications for nonoperative reduction. The clinical prediction rules were developed using significant risk factors from the multivariable analysis. Results A total of 170 patients with intussusception were included in the study. In the final analysis model, 154 patients were used for identifying the significant risk factors of failure of reduction. Ten factors clustering by the age of 3 years were identified and used for developing the clinical prediction rules, and the factors were as follows: body weight <12 kg (relative risk [RR] =1.48, P=0.004), duration of symptoms >48 hours (RR =1.26, P<0.001), vomiting (RR =1.63, P<0.001), rectal bleeding (RR =1.50, P<0.001), abdominal distension (RR =1.60, P=0.003), temperature >37.8°C (RR =1.51, P<0.001), palpable mass (RR =1.26, P<0.001), location of mass (left over right side RR =1.48, P<0.001), ultrasound showed poor prognostic signs (RR =1.35, P<0.001), and the method of reduction (hydrostatic over pneumatic, RR =1.34, P=0.023). Prediction scores ranged from 0 to 16. A high-risk group (scores 12–16) predicted a greater chance of reduction failure (likelihood ratio of positive [LR+] =18.22, P<0.001). A low-risk group (score 0–11) predicted a lower chance of reduction failure (LR+ =0.79, P<0.001). The performance of the scoring model was 80.68% (area under the receiver operating characteristic curve). Conclusion This scoring guideline was used to predict the results of

  11. 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

  12. 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

  13. 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

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

    PubMed

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

    2016-03-01

    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 marked 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 were able to 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

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

    PubMed

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

    2016-03-01

    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 marked 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 were able to 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.

  16. Clinical Experiences Are Not Predictive of Outcomes on the NATABOC Examination

    PubMed Central

    Turocy, Paula Sammarone; Comfort, Ronald E.; Perrin, David H.; Gieck, Joe H.

    2000-01-01

    Objective: To determine the efficacy of the National Athletic Trainers' Association Board of Certification (NATABOC) clinical experience requirements and individual student characteristics to predict candidate outcomes on the NATABOC certification examination. Design and Setting: For all subjects, we gathered survey information and examination scores. The survey information included age, sex, route to certification, previous athletic training and allied health experience, and clinical education experiences. Subjects: A total of 269 subjects, 22.25% of all first-time candidates for the June and November 1993 NATABOC examinations, were included in this study. Measurements: Data were analyzed for standard descriptive statistics and parametric linear regression and correlational relationships. Results: Total clinical hours, high-risk sport experiences, and previous athletic training experience were not predictive of examination outcomes. Although our results indicated a relationship between previous allied health experience and both outcome on the written section of the examination and age and outcome on the oral/practical section, these characteristics also were not predictive of examination outcomes. Conclusions: Gaining clinical experience hours in excess of 400 hours beyond the 800-or 1500-hour requirement may yield no greater benefit for an entry-level professional than less time. The quality, rather than the quantity, of clinical experiences should be evaluated. More emphasis should be placed on the achievement of an entry level of clinical competency, rather than on total hour collection. Also, because high-risk sport experiences did not predict outcomes on the NATABOC examination, the emphasis of clinical education should be on students' receiving a more structured clinical experience, in which they are progressively required to assume greater responsibilities integrating both cognitive and psychomotor skills, while working under the supervision of a certified

  17. 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

  18. 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.

  19. Clinical and Predictive Significance of Hyponatremia after Aneurysmal Subarachnoid Hemorrhage

    PubMed Central

    Vrsajkov, Vladimir; Javanović, Gordana; Stanisavljević, Snežana; Uvelin, Arsen; Vrsajkov, Jelena Panti

    2012-01-01

    Objective: Hyponatremia after SAH was the object of several studies with conflicting results. The aim of this study was to determine a predictive correlation of hyponatremia with delayed cerebral ischemia (DCI) and poor clinical outcome. Material and Methods: We have used a retrospective hospital chart review of 82 patients with SAH treated from August 2008 to August 2010. Patients were divided into hyponatremia and normonatremia groups. Hyponatremia was defined as serum sodium level <135 mmol/l. Information compared and analyzed included demographics, preoperative neurological status, aneurysm characteristics, postoperative intensive care, duration of stay, DCI and clinical outcome at hospital discharge. P<0.05 was considered significant. Results: Thirty-two patients with SAH (39%) developed hyponatremia. In that group we had a significantly higher WFNS score at admission (p=0.03) and longer duration of stay in intensive care (p=0.001). DCI with transit or definitive deficit included 20 patients (62%) in the hyponatremia group, and 19 patients (38%) in the normonatremia group (p=0.03). Binary enter logistic regression revealed a significant correlation of hyponatremia with DCI (p=0.03) and poor clinical outcome (p=0.001). Conclusion: This result revealed a possible use of hyponatremia as an additional predictor of developing DCI and poor clinical outcome. PMID:25207008

  20. 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.

  1. Probabilistic prediction of barrier-island response to hurricanes

    NASA Astrophysics Data System (ADS)

    Plant, Nathaniel G.; Stockdon, Hilary F.

    2012-09-01

    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.

  2. 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

  3. 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

  4. Clinical Predictors of Response to Clozapine in Patients with Treatment Resistant Schizophrenia

    PubMed Central

    A.P., Rajkumar; C., Chitra; S., Bhuvaneshwari; B., Poonkuzhali; A., Kuruvilla; K.S., Jacob

    2011-01-01

    Objectives Despite clozapine’s superior clinical efficacy in Treatment Resistant Schizophrenia (TRS), its adverse effects, need for periodic leukocyte monitoring, cost and variable clinical outcomes make the therapeutic decision making process difficult and mandate a clinical need to predict its treatment response. Hence, we investigated various clinical variables associated with treatment responses and adverse events of clozapine in TRS. Experimental Design We assessed socio-demographic and clinical profiles, premorbid adjustment, traumatic life events, cognition, disability, psychopathology and serum clozapine levels of 101 patients with TRS on stable dose of clozapine using the following instruments: Brief Psychiatric Rating Scale, Abnormal Involuntary Movements Scale, Addenbrooke’s Cognitive Examination—Revised, WHO Disability Assessment Scale-II, Childhood and Recent Traumatic Events Scale, and Premorbid Assessment Scale. We defined clozapine response a priori, adopted a case-control design framework and employed appropriate multivariate analyses. Principal Observations Past history of catatonia (p = 0.005), smoking more than one pack/day (p = 0.008), hyper-somnolence (p = 0.03) and cognitive dysfunction (p = 0.007) were associated with non-response to clozapine. Outcome definitions of non-response to clozapine influenced its association with clinical predictors. Conclusions Clinical variables are useful to predict response to clozapine. Smoking can be a potentially modifiable risk factor. Future longitudinal studies, investigating clinical and pharmacogenetic variables together, are desired.

  5. Response to lithium in bipolar disorder: clinical and genetic findings.

    PubMed

    Rybakowski, Janusz K

    2014-06-18

    The use of lithium is a cornerstone for preventing recurrences in bipolar disorder (BD). The response of patients with bipolar disorder to lithium has different levels of magnitude. About one-third of lithium-treated patients are excellent lithium responders (ELR), showing total prevention of the episodes. A number of clinical characteristics were delineated in patients with favorable response to lithium as regards to clinical course, family history of mood disorders, and psychiatric comorbidity. We have also demonstrated that temperamental features of hypomania (a hyperthymic temperament) and a lack of cognitive disorganization predict the best results of lithium prophylaxis. A degree of prevention against manic and depressive episodes has been regarded as an endophenotype for pharmacogenetic studies. The majority of data have been gathered from so-called "candidate" gene studies. The candidates were selected on the basis of neurobiology of bipolar disorder and mechanisms of lithium action including, among others, neurotransmission, intracellular signaling, neuroprotection or circadian rhythms. We demonstrated that response to lithium has been connected with the genotype of BDNF gene and serum BDNF levels and have shown that ELR have normal cognitive functions and serum BDNF levels, even after long-term duration of the illness. A number of genome-wide association studies (GWAS) of BD have been also performed in recent years, some of which also focused on lithium response. The Consortium on Lithium Genetics (ConLiGen) has established the large sample for performing the genome-wide association study (GWAS) of lithium response in BD, and the first results have already been published.

  6. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

    PubMed

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

    2015-02-01

    Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

  7. Formalized prediction of clinically significant prostate cancer: is it possible?

    PubMed Central

    Nguyen, Carvell T; Kattan, Michael W

    2012-01-01

    Greater understanding of the biology and epidemiology of prostate cancer in the last several decades have led to significant advances in its management. Prostate cancer is now detected in greater numbers at lower stages of disease and is amenable to multiple forms of efficacious treatment. However, there is a lack of conclusive data demonstrating a definitive mortality benefit from this earlier diagnosis and treatment of prostate cancer. It is likely due to the treatment of a large proportion of indolent cancers that would have had little adverse impact on health or lifespan if left alone. Due to this overtreatment phenomenon, active surveillance with delayed intervention is gaining traction as a viable management approach in contemporary practice. The ability to distinguish clinically insignificant cancers from those with a high risk of progression and/or lethality is critical to the appropriate selection of patients for surveillance protocols versus immediate intervention. This chapter will review the ability of various prediction models, including risk groupings and nomograms, to predict indolent disease and determine their role in the contemporary management of clinically localized prostate cancer. PMID:22367181

  8. 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

  9. Idiopathic normal pressure hydrocephalus: diagnostic and predictive value of clinical testing, lumbar drainage, and CSF dynamics.

    PubMed

    Mahr, Cynthia V; Dengl, Markus; Nestler, Ulf; Reiss-Zimmermann, Martin; Eichner, Gerrit; Preuß, Matthias; Meixensberger, Jürgen

    2016-09-01

    OBJECTIVE The aim of the study was to analyze the diagnostic and predictive values of clinical tests, CSF dynamics, and intracranial pulsatility tests, compared with external lumbar drainage (ELD), for shunt response in patients with idiopathic normal pressure hydrocephalus (iNPH). METHODS Sixty-eight consecutive patients with suspected iNPH were prospectively evaluated. Preoperative assessment included clinical tests, overnight intracranial pressure (ICP) monitoring, lumbar infusion test (LIFT), and ELD for 24-72 hours. Simple and multiple linear regression analyses were conducted to identify predictive parameters concerning the outcome after shunt therapy. RESULTS Positive response to ELD correctly predicted improvement after CSF diversion in 87.9% of the patients. A Mini-Mental State Examination (MMSE) value below 21 was associated with nonresponse after shunt insertion (specificity 93%, sensitivity 67%). Resistance to outflow of CSF (ROut) > 12 mm Hg/ml/min was false negative in 21% of patients. Intracranial pulsatility parameters yielded different results in various parameters (correlation coefficient between pulse amplitude and ICP, slow wave amplitude, and mean ICP) but did not correlate to outcome. In multiple linear regression analysis, a calculation of presurgical MMSE versus the value after ELD, ROut, and ICP amplitude quotient during LIFT was significantly associated with outcome (p = 0.04). CONCLUSIONS Despite a multitude of invasive tests, presurgical clinical testing and response to ELD yielded the best prediction for improvement of symptoms following surgery. The complication rate of invasive testing was 5.4%. Multiple and simple linear regression analyses indicated that outcome can only be predicted by a combination of parameters, in accordance with a multifactorial pathogenesis of iNPH. PMID:26824377

  10. Pre-Treatment Amygdala Volume Predicts Electroconvulsive Therapy Response

    PubMed Central

    ten Doesschate, Freek; van Eijndhoven, Philip; Tendolkar, Indira; van Wingen, Guido A.; van Waarde, Jeroen A.

    2014-01-01

    Background: Electroconvulsive therapy (ECT) is an effective treatment for patients with severe depression. Knowledge on factors predicting therapeutic response may help to identify patients who will benefit most from the intervention. Based on the neuroplasticity hypothesis, volumes of the amygdala and hippocampus are possible candidates for predicting treatment outcome. Therefore, this prospective cohort study examines the predictive value of amygdala and hippocampal volumes for the effectiveness of ECT. Methods: Prior to ECT, 53 severely unipolar depressed patients [mean age 57 ± 14 years; 40% (n = 21) male] received structural magnetic resonance imaging (MRI) at 1.5 T. Normalized amygdala and hippocampal volumes were calculated based on automatic segmentation by FreeSurfer (FS). Regression analyses were used to test if the normalized volumes could predict the response to a course of ECT based on the Montgomery–Åsberg Depression Rating Scale (MADRS) scores. Results: A larger amygdala volume independently and significantly predicted a lower post-ECT MADRS score (β = −0.347, P = 0.013). The left amygdala volume had greater predictive value for treatment outcome relative to the right amygdala volume. Hippocampal volume had no independent predictive value. Conclusion: A larger pre-treatment amygdala volume predicted more effective ECT, independent of other known predictors. Almost all patients continued their medication during the study, which might have influenced the course of treatment in ways that were not taken into account. PMID:25505429

  11. Predicting the response of localised oesophageal cancer to neo-adjuvant chemoradiation

    PubMed Central

    Gillham, Charles M; Reynolds, John; Hollywood, Donal

    2007-01-01

    Background A complete pathological response to neo-adjuvant chemo-radiation for oesophageal cancer is associated with favourable survival. However, such a benefit is seen in the minority. If one could identify, at diagnosis, those patients who were unlikely to respond unnecessary toxicity could be avoided and alternative treatment can be considered. The aim of this review was to highlight predictive markers currently assessed and evaluate their clinical utility. Methods A systematic search of Pubmed and Google Scholar was performed using the following keywords; "neo-adjuvant", "oesophageal", "trimodality", "chemotherapy", "radiotherapy", "chemoradiation" and "predict". The original manuscripts were sourced for further articles of relevance. Results Conventional indices including tumour stage and grade seem unable to predict histological response. Immuno-histochemical markers have been extensively studied, but none has made its way into routine clinical practice. Global gene expression from fresh pre-treatment tissue using cDNA microarray has only recently been assessed, but shows considerable promise. Molecular imaging using FDG-PET seems to be able to predict response after neo-adjuvant chemoradiation has finished, but there is a paucity of data when such imaging is performed earlier. Conclusion Currently there are no clinically useful predictors of response based on standard pathological assessment and immunohistochemistry. Genomics, proteomics and molecular imaging may hold promise. PMID:17716369

  12. 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

  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.

  14. 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

  15. Predicting clinical image delivery time by monitoring PACS queue behavior.

    PubMed

    King, Nelson E; Documet, Jorge; Liu, Brent

    2006-01-01

    The expectation of rapid image retrieval from PACS users contributes to increased information technology (IT) infrastructure investments to increase performance as well as continuing demands upon PACS administrators to respond to "slow" system performance. The ability to provide predicted delivery times to a PACS user may curb user expectations for "fastest" response especially during peak hours. This, in turn, could result in a PACS infrastructure tailored to more realistic performance demands. A PACS with a stand-alone architecture under peak load typically holds study requests in a queue until the DICOM C-Move command can take place. We investigate the contents of a stand-alone architecture PACS RetrieveSend queue and identified parameters and behaviors that enable a more accurate prediction of delivery time. A prediction algorithm for studies delayed in a stand-alone PACS queue can be extendible to other potential bottlenecks such as long-term storage archives. Implications of a queue monitor in other PACS architectures are also discussed.

  16. 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.

  17. 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

  18. 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.

  19. Prediction and assessment of splicing alterations: implications for clinical testing.

    PubMed

    Spurdle, Amanda B; Couch, Fergus J; Hogervorst, Frans B L; Radice, Paolo; Sinilnikova, Olga M

    2008-11-01

    Sequence variants that may result in splicing alterations are a particular class of inherited variants for which consequences can be more readily assessed, using a combination of bioinformatic prediction methods and in vitro assays. There is also a general agreement that a variant would invariably be considered pathogenic on the basis of convincing evidence that it results in transcript(s) carrying a premature stop codon or an in-frame deletion disrupting known functional domain(s). This commentary discusses current practices used to assess the clinical significance of this class of variants, provides suggestions to improve assessment, and highlights the issues involved in routine assessment of potential splicing aberrations. We conclude that classification of sequence variants that may alter splicing is greatly enhanced by supporting in vitro analysis. Additional studies that assess large numbers of variants for induction of splicing aberrations and exon skipping are needed to define the contribution of splicing/exon skipping to cancer and disease. These studies will also provide the impetus for development of algorithms that better predict splicing patterns. To facilitate variant classification and development of more specific bioinformatic tools, we call for the deposition of all laboratory data from splicing analyses into national and international databases. PMID:18951448

  20. 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

  1. Personalized in vitro cancer models to predict therapeutic response: Challenges and a framework for improvement.

    PubMed

    Morgan, Molly M; Johnson, Brian P; Livingston, Megan K; Schuler, Linda A; Alarid, Elaine T; Sung, Kyung E; Beebe, David J

    2016-09-01

    Personalized cancer therapy focuses on characterizing the relevant phenotypes of the patient, as well as the patient's tumor, to predict the most effective cancer therapy. Historically, these methods have not proven predictive in regards to predicting therapeutic response. Emerging culture platforms are designed to better recapitulate the in vivo environment, thus, there is renewed interest in integrating patient samples into in vitro cancer models to assess therapeutic response. Successful examples of translating in vitro response to clinical relevance are limited due to issues with patient sample acquisition, variability and culture. We will review traditional and emerging in vitro models for personalized medicine, focusing on the technologies, microenvironmental components, and readouts utilized. We will then offer our perspective on how to apply a framework derived from toxicology and ecology towards designing improved personalized in vitro models of cancer. The framework serves as a tool for identifying optimal readouts and culture conditions, thus maximizing the information gained from each patient sample.

  2. Platelet response during the second cycle of decitabine treatment predicts response and survival for myelodysplastic syndrome patients.

    PubMed

    Jung, Hyun Ae; Maeng, Chi Hoon; Kim, Moonjin; Kim, Sungmin; Jung, Chul Won; Jang, Jun Ho

    2015-06-30

    Despite the efficacy of decitabine to myelodysplastic syndrome (MDS), there is a wide range of responses, and no definite predictive marker has been identified. This study aimed to describe the efficacy of decitabine and to identify potential predictors of response and survival in patients with MDS. We retrospectively analyzed clinical data of MDS patients at Samsung Medical Center between August 2008 and August 2011. The response assessment was conducted using the International Working Group (IWG) response criteria for MDS. We analyzed 101 MDS patients (total 613 cycles) who received decitabine for a median of four cycles. The overall response was 52.5% (n = 53/101). The median time to any response was two cycles with the median overall survival of 16.7 months. Patients who showed hematologic improvement had significantly longer survival than those who did not (9.8 vs. 22.9 months, p = 0.004). The difference in OS was evident in the Intermediate-2/High risk group (p = 0.002) but not in the Intermediate-1 risk group (p = 0.145). Multivariate analysis confirmed that platelet response (no platelet transfusions for at least 3 days) during the second cycle of treatment was an independent predictor for response, OS and Leukemia free survival. Based on the results of this study, for patients with hematological improvement, recovery of platelet count by the second cycle of therapy can be used as an early predictive marker of improved survival and an increased response rate.

  3. Predicting methylphenidate response in attention deficit hyperactivity disorder: a preliminary study.

    PubMed

    Johnston, Blair A; Coghill, David; Matthews, Keith; Steele, J Douglas

    2015-01-01

    Methylphenidate (MPH) is established as the main pharmacological treatment for patients with attention deficit hyperactivity disorder (ADHD). Whilst MPH is generally a highly effective treatment, not all patients respond, and some experience adverse reactions. Currently, there is no reliable method to predict how patients will respond, other than by exposure to a trial of medication. In this preliminary study, we sought to investigate whether an accurate predictor of clinical response to methylphenidate could be developed for individual patients, using sociodemographic, clinical and neuropsychological measures. Of the 43 boys with ADHD included in this proof-of-concept study, 30 were classed as responders and 13 as non-responders to MPH, with no significant differences in age nor verbal intelligence quotient (IQ) between the groups. Here we report the application of a multivariate analysis approach to the prediction of clinical response to MPH, which achieved an accuracy of 77% (p = 0.005). The most important variables to the classifier were performance on a 'go/no go' task and comorbid conduct disorder. This preliminary study suggested that further investigation is merited. Achieving a highly significant accuracy of 77% for the prediction of MPH response is an encouraging step towards finding a reliable and clinically useful method that could minimise the number of children needlessly being exposed to MPH.

  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.

  5. 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.

  6. 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.

  7. Histomorphological Factors Predicting the Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

    PubMed Central

    Jung, Yoon Yang; Hyun, Chang Lim; Jin, Min-Sun; Park, In Ae; Chung, Yul Ri; Shim, Bobae; Lee, Kyu Ho

    2016-01-01

    Purpose There is no standard targeted therapy for the treatment of triple-negative breast cancer (TNBC). Therefore, its management heavily depends on adjuvant chemotherapy. Using core needle biopsy, this study evaluated the histological factors of TNBC predicting the response to chemotherapy. Methods One hundred forty-three TNBC patients who received single-regimen neoadjuvant chemotherapy (NAC) with the combination of doxorubicin, cyclophosphamide, and docetaxel were enrolled. The core needle biopsy specimens acquired before NAC were used to analyze the clinicopathologic variables and overall performance of the predictive model for therapeutic response. Results Independent predictors of pathologic complete response after NAC were found to be higher number of tumor infiltrating lymphocytes (p=0.007), absence of clear cytoplasm (p=0.008), low necrosis (p=0.018), and high histologic grade (p=0.039). In the receiver operating characteristics curve analysis, the area under curve for the combination of these four variables was 0.777. Conclusion The present study demonstrated that a predictive model using the above four variables can predict therapeutic response to single-regimen NAC with the combination of doxorubicin, cyclophosphamide, and docetaxel in TNBC. Therefore, adding these morphologic variables to clinical and genomic signatures might enhance the ability to predict the therapeutic response to NAC in TNBC. PMID:27721875

  8. 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

  9. 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

  10. Apoptosis and other immune biomarkers predict influenza vaccine responsiveness.

    PubMed

    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

  11. 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.

  12. 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

  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. 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.

  15. 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.

  16. Dopamine Reward Prediction Error Responses Reflect Marginal Utility

    PubMed Central

    Stauffer, William R.; Lak, Armin; Schultz, Wolfram

    2014-01-01

    Summary Background Optimal choices require an accurate neuronal representation of economic value. In economics, utility functions are mathematical representations of subjective value that can be constructed from choices under risk. Utility usually exhibits a nonlinear relationship to physical reward value that corresponds to risk attitudes and reflects the increasing or decreasing marginal utility obtained with each additional unit of reward. Accordingly, neuronal reward responses coding utility should robustly reflect this nonlinearity. Results In two monkeys, we measured utility as a function of physical reward value from meaningful choices under risk (that adhered to first- and second-order stochastic dominance). The resulting nonlinear utility functions predicted the certainty equivalents for new gambles, indicating that the functions’ shapes were meaningful. The monkeys were risk seeking (convex utility function) for low reward and risk avoiding (concave utility function) with higher amounts. Critically, the dopamine prediction error responses at the time of reward itself reflected the nonlinear utility functions measured at the time of choices. In particular, the reward response magnitude depended on the first derivative of the utility function and thus reflected the marginal utility. Furthermore, dopamine responses recorded outside of the task reflected the marginal utility of unpredicted reward. Accordingly, these responses were sufficient to train reinforcement learning models to predict the behaviorally defined expected utility of gambles. Conclusions These data suggest a neuronal manifestation of marginal utility in dopamine neurons and indicate a common neuronal basis for fundamental explanatory constructs in animal learning theory (prediction error) and economic decision theory (marginal utility). PMID:25283778

  17. Use of reflectance spectrophotometry to predict the response of port wine stains to pulsed dye laser.

    PubMed

    Halachmi, Shlomit; Azaria, Ron; Inbar, Roy; Ad-El, Dean; Lapidoth, Moshe

    2014-01-01

    Reflectance spectroscopy can be used to quantitate subtle differences in color. We applied a portable reflectance spectrometer to determine its utility in the evaluation of pulsed dye laser treatment of port wine stains (PWS) and in prediction of clinical outcome, in a prospective study. Forty-eight patients with PWS underwent one to nine pulsed dye laser treatments. Patient age and skin color as well as PWS surface area, anatomic location, and color were recorded. Pretreatment spectrophotometric measurements were performed. The subjective clinical results of treatment and the quantitative spectrophotometry results were evaluated by two independent teams, and the findings were correlated. The impact of the clinical characteristics on the response to treatment was assessed as well. Patients with excellent to good clinical results of laser treatments had pretreatment spectrophotometric measurements which differed by more than 10%, whereas patients with fair to poor results had spectrophotometric measurements with a difference of of less than 10%. The correlation between the spectrophotometric results and the clinical outcome was 73% (p < 0.01). The impact of the other clinical variables on outcome agreed with the findings in the literature. Spectrophotometry has a higher correlation with clinical outcome and a better predictive value than other nonmeasurable, nonquantitative, dependent variables.

  18. Clinical errors as a lack of context responsiveness.

    PubMed

    Bugatti, Matteo; Boswell, James F

    2016-09-01

    Although standardized treatments have the potential to decrease clinical errors, within-session responsiveness is complicated and complementary frameworks may be needed to foster enhanced responsiveness in the context of evidence-based treatments. Recent efforts have targeted the enhancement of flexibility and responsiveness in the delivery of manualized treatments, including the development of transdiagnostic treatments (i.e., protocols that are designed to be used across different diagnoses) intended to tailor intervention principles to the needs of individual patients. Context-Responsive Psychotherapy Integration (Constantino, Boswell, Bernecker, & Castonguay, 2013) offers an framework that supports the utilization of evidence-based clinical strategies in response to the identification of specific process markers. Failure to identify or appropriately respond to such markers may result in negative therapeutic process as well as outcomes. This case study uses the context-response psychotherapy integration framework to understand critical moments of clinical decision-making through examining an individual treatment case that unilaterally terminated after seven sessions of transdiagnostic treatment. This illustrative empirical case analysis focuses on three potential clinical errors, as indicated by a lack of responsiveness to three candidate process markers: (a) low outcome expectations, (b) self-strivings, and (c) outcome monitoring. For each clinical error, alternative clinical strategies are discussed. (PsycINFO Database Record

  19. Clinical errors as a lack of context responsiveness.

    PubMed

    Bugatti, Matteo; Boswell, James F

    2016-09-01

    Although standardized treatments have the potential to decrease clinical errors, within-session responsiveness is complicated and complementary frameworks may be needed to foster enhanced responsiveness in the context of evidence-based treatments. Recent efforts have targeted the enhancement of flexibility and responsiveness in the delivery of manualized treatments, including the development of transdiagnostic treatments (i.e., protocols that are designed to be used across different diagnoses) intended to tailor intervention principles to the needs of individual patients. Context-Responsive Psychotherapy Integration (Constantino, Boswell, Bernecker, & Castonguay, 2013) offers an framework that supports the utilization of evidence-based clinical strategies in response to the identification of specific process markers. Failure to identify or appropriately respond to such markers may result in negative therapeutic process as well as outcomes. This case study uses the context-response psychotherapy integration framework to understand critical moments of clinical decision-making through examining an individual treatment case that unilaterally terminated after seven sessions of transdiagnostic treatment. This illustrative empirical case analysis focuses on three potential clinical errors, as indicated by a lack of responsiveness to three candidate process markers: (a) low outcome expectations, (b) self-strivings, and (c) outcome monitoring. For each clinical error, alternative clinical strategies are discussed. (PsycINFO Database Record PMID:27631853

  20. Predicting water table response to rainfall events, central Florida.

    PubMed

    van Gaalen, J F; Kruse, S; Lafrenz, W B; Burroughs, S M

    2013-01-01

    A rise in water table in response to a rainfall event is a complex function of permeability, specific yield, antecedent soil-water conditions, water table level, evapotranspiration, vegetation, lateral groundwater flow, and rainfall volume and intensity. Predictions of water table response, however, commonly assume a linear relationship between response and rainfall based on cumulative analysis of water level and rainfall logs. By identifying individual rainfall events and responses, we examine how the response/rainfall ratio varies as a function of antecedent water table level (stage) and rainfall event size. For wells in wetlands and uplands in central Florida, incorporating stage and event size improves forecasting of water table rise by more than 30%, based on 10 years of data. At the 11 sites studied, the water table is generally least responsive to rainfall at smallest and largest rainfall event sizes and at lower stages. At most sites the minimum amount of rainfall required to induce a rise in water table is fairly uniform when the water table is within 50 to 100 cm of land surface. Below this depth, the minimum typically gradually increases with depth. These observations can be qualitatively explained by unsaturated zone flow processes. Overall, response/rainfall ratios are higher in wetlands and lower in uplands, presumably reflecting lower specific yields and greater lateral influx in wetland sites. Pronounced depth variations in rainfall/response ratios appear to correlate with soil layer boundaries, where corroborating data are available.

  1. Perturbation Predictability Can Influence the Long-Latency Stretch Response

    PubMed Central

    Forgaard, Christopher J.; Franks, Ian M.; Maslovat, Dana; Chua, Romeo

    2016-01-01

    Perturbations applied to the upper limbs elicit short (M1: 25–50 ms) and long-latency (M2: 50–100 ms) responses in the stretched muscle. M1 is produced by a spinal reflex loop, and M2 receives contribution from multiple spinal and supra-spinal pathways. While M1 is relatively immutable to voluntary intention, the remarkable feature of M2 is that its size can change based on intention or goal of the participant (e.g., increasing when resisting the perturbation and decreasing when asked to let-go or relax following the perturbation). While many studies have examined modulation of M2 between passive and various active conditions, through the use of constant foreperiods (interval between warning signal and a perturbation), it has also been shown that the magnitude of the M2 response in a passive condition can change based on factors such as habituation and anticipation of perturbation delivery. To prevent anticipation of a perturbation, most studies have used variable foreperiods; however, the range of possible foreperiod duration differs between experiments. The present study examined the influence of different variable foreperiods on modulation of the M2 response. Fifteen participants performed active and passive responses to a perturbation that stretched wrist flexors. Each block of trials had either a short (2.5–3.5 seconds; high predictability) or long (2.5–10.5 seconds; low predictability) variable foreperiod. As expected, no differences were found between any conditions for M1, while M2 was larger in the active rather than passive conditions. Interestingly, within the two passive conditions, the long variable foreperiods resulted in greater activity at the end of the M2 response than the trials with short foreperiods. These results suggest that perturbation predictability, even when using a variable foreperiod, can influence circuitry contributing to the long-latency stretch response. PMID:27727293

  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. 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.

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

    PubMed

    Preskorn, Sheldon H

    2014-12-01

    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.

  5. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

    PubMed

    Benson, M

    2016-03-01

    Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide

  6. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

    PubMed

    Benson, M

    2016-03-01

    Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide

  7. 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.

  8. 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...

  9. 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...

  10. 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)

  11. 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.

  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. Thai clinical laboratory responsible to economic crisis.

    PubMed

    Sirisali, K; Vattanaviboon, P; Manochiopinij, S; Ananskulwat, W

    1999-01-01

    Nowadays, Thailand encounters a serious economic crisis. A clear consensus has been made that a cost-saving system must be the important tool. Both private and government organizations are engaged in this situation. We studied the cost-saving in the clinical laboratory. A questionnaire was distributed to 45 hospital laboratories located in Bangkok. Results showed that efforts to control the cost are the essential policy. There was a variety of factors contributing to the cost-saving process. The usage of public utility, non-recycle material and unnecessary utility were reconsidered. Besides, capital cost (wages and salary) personnel incentive are assessed. Forty three of the 45 respondents had attempted to reduce the cost via curtailing the unnecessary electricity. Eliminating the needless usage of telephone-call. water and unnecessary material was also an effective strategy. A reduction of 86.9%, 80 % and 80.0% of the mentioned factors respectively, was reported. An inventory system of the reagent, chemical and supplies was focused. Most of the laboratories have a policy on cost-saving by decreased the storage. Twenty eight of the 45 laboratories considered to purchase the cheaper with similar quality reagents instead. And some one would purchase a bulky pack when it is the best bargain. A specific system "contact reagent with a free rent instrument" has been used widely (33.3%). Finally, a new personnel management system has been chosen. Workload has rearranged and unnecessary extra-hour work was abandoned.

  14. New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs

    PubMed Central

    Beckman, Robert A.; Chen, Cong

    2013-01-01

    Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy, increase the value of cancer medicines, and decrease the size and cost of clinical trials while increasing their chance of success. But predictive biomarkers do not always work. When unsuccessful, they add cost, complexity, and time to drug development. This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it can actually predict. PMID:23489587

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Predicting the Response to Intravenous Immunoglobulins in an Animal Model of Chronic Neuritis

    PubMed Central

    Pfaff, Johannes; Mathys, Christian; Mausberg, Anne K.; Bendszus, Martin; Pham, Mirko; Hartung, Hans-Peter; Kieseier, Bernd C.

    2016-01-01

    Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is a disabling autoimmune disorder of the peripheral nervous system (PNS). Intravenous immunoglobulins (IVIg) are effective in CIDP, but the treatment response varies greatly between individual patients. Understanding this interindividual variability and predicting the response to IVIg constitute major clinical challenges in CIDP. We previously established intercellular adhesion molecule (ICAM)-1 deficient non-obese diabetic (NOD) mice as a novel animal model of CIDP. Here, we demonstrate that similar to human CIDP patients, ICAM-1 deficient NOD mice respond to IVIg treatment by clinical and histological measures. Nerve magnetic resonance imaging and histology demonstrated that IVIg ameliorates abnormalities preferentially in distal parts of the sciatic nerve branches. The IVIg treatment response also featured great heterogeneity allowing us to identify IVIg responders and non-responders. An increased production of interleukin (IL)-17 positively predicted IVIg treatment responses. In human sural nerve biopsy sections, high numbers of IL-17 producing cells were associated with younger age and shorter disease duration. Thus, our novel animal model can be utilized to identify prognostic markers of treatment responses in chronic inflammatory neuropathies and we identify IL-17 production as one potential such prognostic marker. PMID:27711247

  1. 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.

  2. What Predicts and What Mediates the Response of Urge Urinary Incontinence to Biofeedback?

    PubMed Central

    Resnick, Neil M.; Perera, Subashan; Schaefer, Werner; Tadic, Stasa; Organist, Linda; Riley, Mary Alyce; Griffiths, Derek

    2016-01-01

    Aims To better target a behavioral approach for urge urinary incontinence (UUI) and enhance its efficacy by (1) identifying predictors of response to biofeedback-assisted pelvic muscle training (BFB), and (2) determining factors that mediate response. Methods BFB (4 biweekly visits) was administered to 183 women > 60 years (mean=73.6). Before and after intervention, all underwent comprehensive evaluation and videourodynamic testing. Postulated predictors and mediators from 4 urodynamic domains, specified a priori, were correlated with reduction in UUI frequency. Results Median UUI frequency decreased from 3.2/day to 1/day (p=.0001). UUI improved by ≥50% in 55% of subjects and by 100% in 13% of subjects. Frequent UUI predicted poor response (p < 0.01). Of the urodynamic parameters, only high amplitude and briskness of detrusor overactivity (DO) predicted decreased response (p< 0.05 and p<0.01) and these could be measured only in the 43% of subjects with elicitable DO. Decreased DO elicitability was the only urodynamic variable that changed in concert with improvement and thus was a candidate mediator. Response was neither predicted nor mediated by proprioception/warning, cystometric capacity, detrusor contractility, sphincter strength, or baseline DO elicitability. Conclusions Severe DO predicts poor response to BFB. Good response is mediated by reduction in DO elicitability. Other than baseline UUI frequency, there are no other clinically or urodynamically important predictors or mediators of BFB response in this population. BFB may be best for patients with less severe DO. Future research to enhance its efficacy might better focus on the brain than on the lower urinary tract. PMID:23168606

  3. Early Response to Antipsychotic Drug Therapy as a Clinical Marker of Subsequent Response in the Treatment of Schizophrenia

    PubMed Central

    Kinon, Bruce J; Chen, Lei; Ascher-Svanum, Haya; Stauffer, Virginia L; Kollack-Walker, Sara; Zhou, Wei; Kapur, Shitij; Kane, John M

    2010-01-01

    Our objective was to prospectively assess whether early (ie, 2 weeks) response to an antipsychotic predicts later (12-week) response and whether ‘switching' early non-responders to another antipsychotic is a better strategy than ‘staying'. This randomized, double-blind, flexible-dosed, 12-week study enrolled 628 patients diagnosed with schizophrenia or schizoaffective disorder. All initiated treatment with risperidone. Early response was defined as ⩾20% improvement on the Positive and Negative Syndrome Scale (PANSS) total score following 2 weeks of treatment. Early responders (ERs) continued on risperidone, whereas early non-responders (ENRs) were randomized (1 : 1) to continue on risperidone 2–6 mg/day or switch to olanzapine 10–20 mg/day for 10 additional weeks. Compared with ENRs, risperidone ERs showed significantly greater reduction in PANSS total score (end point; p<001). Early response/non-response was highly predictive of subsequent clinical outcomes. Switching risperidone ENRs to olanzapine at week 2 resulted in a small but significantly greater reduction in PANSS total score (end point; p=0.020) and in depressive symptoms (end point; p=0.004); the reduction in PANSS was greater among those who were still moderately ill at 2 weeks. Switching risperidone ENRs to olanzapine also resulted in significantly greater increases in triglycerides, a significantly greater decrease in prolactin, and significantly less treatment-emergent dyskinesia. This is the first study to prospectively show that early response/non-response to an antipsychotic (risperidone) is a reliable clinical marker of subsequent clinical outcomes and that a ‘switching' strategy based on this information may lead to greater clinical improvement than staying on a drug for a longer period in some patients. PMID:19890258

  4. 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.

  5. Predictive Value of IL-8 for Sepsis and Severe Infections After Burn Injury: A Clinical Study.

    PubMed

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

    2015-03-01

    The inflammatory response induced by burn injury contributes to increased incidence of infections, sepsis, organ failure, and mortality. Thus, monitoring postburn inflammation is of paramount importance but, so far, there are no reliable biomarkers available to monitor and/or predict infectious complications after burn. As interleukin 8 (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 postburn sepsis, infections, and mortality. Plasma cytokines, acute-phase proteins, constitutive proteins, and hormones were analyzed during the first 60 days after injury from 468 pediatric burn patients. Demographics and clinical outcome variables (length of stay, infection, sepsis, multiorgan failure [MOF], and mortality) were recorded. A cutoff level for IL-8 was determined using receiver operating characteristic analysis. Statistical significance is set at P < 0.05. Receiver operating characteristic analysis identified a cutoff level of 234 pg/mL for IL-8 for survival. Patients were grouped according to their average IL-8 levels relative to this cutoff 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 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 with 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.

  6. A nomogram that predicts pathologic complete response to neoadjuvant chemoradiation also predicts survival outcomes after definitive chemoradiation for esophageal cancer

    PubMed Central

    Wang, Jingya; Allen, Pamela K.; Correa, Arlene M.; Maru, Dipen M.; Swisher, Stephen G.; Hofstetter, Wayne L.; Liao, Zhongxing; Ajani, Jaffer A.

    2015-01-01

    Background Pathologic complete response (pCR) to neoadjuvant chemoradiation for esophageal cancer is associated with improved outcomes. We evaluated whether a nomogram designed to predict who would have a pCR after trimodality therapy could also predict outcome after definitive chemoradiation. Methods Patients in this retrospective, single-institution analysis had received chemoradiation without surgery for esophageal cancer from 1998 through 2010; 333 such patients had complete information on all variables required for the pCR nomogram: sex; T status (by endoscopic sonography); tumor grade; tumor avidity on positron emission tomography (PET); and esophagogastroduodenoscopy (EGD)-directed biopsy results after chemoradiation. We used multivariate Cox regression to test potential associations between clinical outcomes [overall survival (OS), locoregional recurrence, and distant metastasis] and patient or treatment factors and the pCR nomogram score; the component variables of the nomogram were not reintroduced into the multivariate analysis. Results The median follow-up time for all patients (median age 66 years) was 18.2 months (30.7 months for those alive at the time of analysis). Patients with nomogram scores ≤125 (median for all patients) had significantly worse outcomes than patients with scores >125: median OS time 19.7 vs. 48.2 months; disease-free survival (DFS) time 6.1 vs. 31.1 months; locoregional failure-free survival time 17.7 months vs. not reached; and distant metastasis-free survival time 11.7 months vs. not reached (all P<0.001). Multivariate Cox regression analysis indicated that nomogram score independently predicted each survival outcome, along with other patient and disease factors. Conclusions The pCR nomogram score predicted survival outcomes in patients receiving definitive chemoradiation for esophageal cancer. Although this nomogram requires further validation, it may prove useful for stratifying patients for clinical trials designed to

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. Prediction of Response to Medication and Cognitive Therapy in the Treatment of Moderate to Severe Depression

    PubMed Central

    Fournier, Jay C.; DeRubeis, Robert J.; Shelton, Richard C.; Hollon, Steven D.; Amsterdam, Jay D.; Gallop, Robert

    2009-01-01

    A recent randomized controlled trial found nearly equivalent response rates for antidepressant medications and cognitive therapy in a sample of moderate-to-severely depressed outpatients. In this article, we seek to identify the variables that were associated with response across both treatments as well as variables that predicted superior response in one treatment over the other. The sample consisted of 180 depressed outpatients: 60 of whom were randomly assigned to cognitive therapy; 120 were assigned to antidepressant medications. Treatment was provided for 16 weeks. Chronic depression, older age, and lower intelligence each predicted relatively poor response across both treatments. Three prescriptive variables were identified: marriage, unemployment, and having experienced a greater number of recent life events predicted superior response to cognitive therapy compared to antidepressant medications. Thus, six markers of treatment outcome were identified, each of which might be expected to carry considerable clinical utility. The three prognostic variables identify subgroups that might benefit from alternative treatment strategies; the three prescriptive variables identify groups who appear to respond particularly well to cognitive therapy. PMID:19634969

  13. 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

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

    PubMed

    Thase, Michael E

    2014-12-01

    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.

  15. 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

  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.

  17. 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

  18. Prospective assessment of a gene signature potentially predictive of clinical benefit in metastatic melanoma patients following MAGE-A3 immunotherapeutic (PREDICT)

    PubMed Central

    Saiag, P.; Gutzmer, R.; Ascierto, P. A.; Maio, M.; Grob, J.-J.; Murawa, P.; Dreno, B.; Ross, M.; Weber, J.; Hauschild, A.; Rutkowski, P.; Testori, A.; Levchenko, E.; Enk, A.; Misery, L.; Vanden Abeele, C.; Vojtek, I.; Peeters, O.; Brichard, V. G.; Therasse, P.

    2016-01-01

    Background Genomic profiling of tumor tissue may aid in identifying predictive or prognostic gene signatures (GS) in some cancers. Retrospective gene expression profiling of melanoma and non-small-cell lung cancer led to the characterization of a GS associated with clinical benefit, including improved overall survival (OS), following immunization with the MAGE-A3 immunotherapeutic. The goal of the present study was to prospectively evaluate the predictive value of the previously characterized GS. Patients and methods An open-label prospective phase II trial (‘PREDICT’) in patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma. Results Of 123 subjects who received the MAGE-A3 immunotherapeutic, 71 (58.7%) displayed the predictive GS (GS+). The 1-year OS rate was 83.1%/83.3% in the GS+/GS− populations. The rate of progression-free survival at 12 months was 5.8%/4.1% in GS+/GS− patients. The median time-to-treatment failure was 2.7/2.4 months (GS+/GS−). There was one complete response (GS−) and two partial responses (GS+). The MAGE-A3 immunotherapeutic was similarly immunogenic in both populations and had a clinically acceptable safety profile. Conclusion Treatment of patients with MAGE-A3-positive unresectable stage IIIB-C/IV-M1a melanoma with the MAGE-A3 immunotherapeutic demonstrated an overall 1-year OS rate of 83.5%. GS− and GS+ patients had similar 1-year OS rates, indicating that in this study, GS was not predictive of outcome. Unexpectedly, the objective response rate was lower in this study than in other studies carried out in the same setting with the MAGE-A3 immunotherapeutic. Investigation of a GS to predict clinical benefit to adjuvant MAGE-A3 immunotherapeutic treatment is ongoing in another melanoma study. This study is registered at www.clinicatrials.gov NCT00942162. PMID:27502712

  19. 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.

  20. A biometric approach to predictable treatment of clinical crown discrepancies.

    PubMed

    Chu, Stephen J

    2007-08-01

    Dental professionals have long been guided by mathematical principles when interpreting aesthetic and tooth proportions for their patients. While many acknowledge that such principles are merely launch points for a smile design or reconstructive procedure, their existence appears to indicate practitioners' desire for predictable, objective, and reproducible means of achieving success in aesthetic dentistry. This article introduces innovative aesthetic measurement gauges as a means of objectively quantifying tooth size discrepancies and enabling the clinician to perform aesthetic restorative dentistry with success and predictability.

  1. 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

  2. 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.

  3. 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

  4. Lateralization for speech predicts therapeutic response to cognitive behavioral therapy for depression.

    PubMed

    Kishon, Ronit; Abraham, Karen; Alschuler, Daniel M; Keilp, John G; Stewart, Jonathan W; McGrath, Patrick J; Bruder, Gerard E

    2015-08-30

    A prior study (Bruder, G.E., Stewart, J.W., Mercier, M.A., Agosti, V., Leite, P., Donovan, S., Quitkin, F.M., 1997. Outcome of cognitive-behavioral therapy for depression: relation of hemispheric dominance for verbal processing. Journal of Abnormal Psychology 106, 138-144.) found left hemisphere advantage for verbal dichotic listening was predictive of clinical response to cognitive behavioral therapy (CBT) for depression. This study aimed to confirm this finding and to examine the value of neuropsychological tests, which have shown promise for predicting antidepressant response. Twenty depressed patients who subsequently completed 14 weeks of CBT and 74 healthy adults were tested on a Dichotic Fused Words Test (DFWT). Patients were also tested on the National Adult Reading Test to estimate IQ, and word fluency, choice RT, and Stroop neuropsychological tests. Left hemisphere advantage on the DFWT was more than twice as large in CBT responders as in non-responders, and was associated with improvement in depression following treatment. There was no difference between responders and non-responders on neuropsychological tests. The results support the hypothesis that the ability of individuals with strong left hemisphere dominance to recruit frontal and temporal cortical regions involved in verbal dichotic listening predicts CBT response. The large effect size, sensitivity and specificity of DFWT predictions suggest the potential value of this brief and inexpensive test as an indicator of whether a patient will benefit from CBT for depression.

  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. 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.

  7. Graph-guided joint prediction of class label and clinical scores for the Alzheimer's disease.

    PubMed

    Yu, Guan; Liu, Yufeng; Shen, Dinggang

    2016-09-01

    Accurate diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, is very important for early treatment. Over the last decade, various machine learning methods have been proposed to predict disease status and clinical scores from brain images. It is worth noting that many features extracted from brain images are correlated significantly. In this case, feature selection combined with the additional correlation information among features can effectively improve classification/regression performance. Typically, the correlation information among features can be modeled by the connectivity of an undirected graph, where each node represents one feature and each edge indicates that the two involved features are correlated significantly. In this paper, we propose a new graph-guided multi-task learning method incorporating this undirected graph information to predict multiple response variables (i.e., class label and clinical scores) jointly. Specifically, based on the sparse undirected feature graph, we utilize a new latent group Lasso penalty to encourage the correlated features to be selected together. Furthermore, this new penalty also encourages the intrinsic correlated tasks to share a common feature subset. To validate our method, we have performed many numerical studies using simulated datasets and the Alzheimer's Disease Neuroimaging Initiative dataset. Compared with the other methods, our proposed method has very promising performance.

  8. DYNAMIC PREDICTION OF TREATMENT RESPONSE IN LATE-LIFE DEPRESSION

    PubMed Central

    Joel, Ian; Begley, Amy E.; Mulsant, Benoit H.; Lenze, Eric J.; Mazumdar, Sati; Dew, Mary Amanda; Blumberger, Daniel; Butters, Meryl; Reynolds, Charles F.

    2013-01-01

    Objective 1) identify actionable predictors of remission to antidepressant pharmacotherapy in depressed older adults and 2) use signal detection theory to develop decision trees to guide clinical decision making Method We treated 277 participants with current major depression using open-label venlafaxine XR (up to 300 mg/day) for 12 weeks, in an NIMH-sponsored randomized, placebo-controlled augmentation trial of adjunctive aripiprazole. Multiple logistic regression and signal detection approaches identified predictors of remission in both completer and intent-to-treat samples. Results Higher baseline depressive symptom severity (OR, 0.86, 95% CI, 0.80-0.93; p <0.001), smaller symptom improvement during the first two weeks of treatment (OR, 0.96, 95% CI, 0.94-0.97; p <0.001), male sex (OR, 0.41 95% CI, 0.18-0.93, p=0.03), duration of current episode ≥ 2 years (OR, 0.26 95% CI, 0.12-0.57, p<0.001) and adequate past depression treatment (ATHF >=3) (OR, 0.34 95% CI, 0.16-0.74, p=0.006) predicted lower probability of remission in the completer sample. Subjects with Montgomery Asberg (MADRS) decreasing by >27% in the first two weeks and with baseline MADRS scores of <27 (percentile rank = 51) had the best chance of remission (89%). Subjects with small symptom decrease in the first 2 weeks with adequate prior treatment and younger than 75 yrs old had the lowest chance of remission (16%). Conclusion Our results suggest the clinical utility of measuring pre-treatment illness severity and change during the first two weeks of treatment in predicting remission of late-life major depression. PMID:23567441

  9. Early clinical prediction of neurological outcome following out of hospital cardiac arrest managed with therapeutic hypothermia

    PubMed Central

    Ruknuddeen, Mohammed Ishaq; Ramadoss, Rajaram; Rajajee, V.; Grzeskowiak, Luke E.; Rajagopalan, Ram E.

    2015-01-01

    Background: Therapeutic hypothermia (TH) may improve neurological outcome in comatose patients following out of hospital cardiac arrest (OHCA). The reliability of clinical prediction of neurological outcome following TH remains unclear. In particular, there is very limited data on survival and predictors of neurological outcome following TH for OHCA from resource-constrained settings in general and South Asia in specific. Objective: The objective was to identify factors predicting unfavorable neurological outcome at hospital discharge in comatose survivors of OHCA treated with hypothermia. Design: Retrospective chart review. Setting: Urban 200-bed hospital in Chennai, India. Methods: Predictors of unfavorable neurological outcome (cerebral performance category score [3–5]) at hospital discharge were evaluated among patients admitted between January 2006 and December 2012 following OHCA treated with TH. Hypothermia was induced with cold intravenous saline bolus, ice packs and cold-water spray with bedside fan. Predictors of unfavorable neurological outcome were examined through multivariate exact logistic regression analysis. Results: A total of 121 patients were included with 106/121 (87%) experiencing the unfavorable neurological outcome. Independent predictors of unfavorable neurological outcome included: Status myoclonus <24 h (odds ratio [OR] 21.79, 95% confidence interval [CI] 2.89-Infinite), absent brainstem reflexes (OR 50.09, 6.55-Infinite), and motor response worse than flexion on day 3 (OR 99.41, 12.21-Infinite). All 3 variables had 100% specificity and positive predictive value. Conclusion: Status myoclonus within 24 h, absence of brainstem reflexes and motor response worse than flexion on day 3 reliably predict unfavorable neurological outcome in comatose patients with OHCA treated with TH. PMID:26195855

  10. Early response evaluation and prediction in neoadjuvant-treated patients with esophageal cancer

    PubMed Central

    Theisen, Joerg; Krause, Bernd; Peschel, Christian; Schmid, Roland; Geinitz, Hans; Friess, Helmut

    2009-01-01

    Since the introduction of multimodal therapy regimens, the prognosis of esophageal cancer has improved. There is undoubtedly true for patients with surgically resected tumors in the case of a response to neoadjuvant chemotherapy or chemoradiation. Important conclusions can be drawn from this regarding the indication for perioperative therapies, the radicality of surgery, or the surgical indications. Thus, most of the current research in this field is aimed at the early identification of this subset of patients, at the beginning of, or even before, neoadjuvant treatment. Conventional staging tools have failed to predict responses to neoadjuvant therapy. However, molecular imaging methods, e.g. positron emission tomography (PET)-scans, have shown promising results in the early selection of responders and non-responders during the course of neoadjuvant therapy, allowing physicians to alter the treatment plan accordingly. Even more desirable is the identification of potential responders before the start of neoadjuvant therapy. Preliminary molecular data on biopsy specimens demonstrate the possibility of early response prediction in these patients. We present the current knowledge on response evaluation and prediction in esophageal cancer and draw conclusions for future clinical practice and studies in this review. PMID:21160793

  11. 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

  12. Human reproductive costs and the predicted response to dietary restriction.

    PubMed

    Arking, Robert

    2007-09-01

    The question has arisen in the literature as to whether dietary restriction (DR) will have a significant effect on human longevity. I initially use literature data to estimate the energy costs necessary to carry a human from conception to caloric self-sufficiency to be approximately 12.6 x 10(6)kcal, which amounts to approximately 25% of the the two parents' combined daily caloric intake for 20 years. Similar levels of financial costs are expended in developed societies. Thus, human reproductive costs are high enough to permit a DR response. I then review four different models relating diet and life span, three of which have been previously used to estimate the effects of DR on humans. A review of the pertinent literature suggests that these three models, while plausible, are not capable of making robust predictions that are consistent with human data not used in their development. Given this weakness, none of the predictions made by these theories should be relied on for policy development at this time. The fourth, or biocultural model, examined combines biologic and cultural factors. Human longevity is more complex than our model systems have led us to believe, and thus any solution will require the development of a new quantitative model. The outlines of a suggested quantitative biocultural model based on the prior model of Crews and the disposable soma model of Shanley and Kirkwood are presented and a prediction of the possible data outcomes is made. If the human cultural pro-longevity practices can be quantified in terms of their effect on energy allocation, then this model may serve in future as a realistic quantitative model capable of identifying pertinent pathways and making robust predictions.

  13. Instruments for predicting visual acuity. A clinical comparison.

    PubMed

    Spurny, R C; Zaldivar, R; Belcher, C D; Simmons, R J

    1986-02-01

    A series of 54 eyes in 50 patients had preoperative predictions of postoperative visual acuity, using both a white-light interferometer (Lotmar Visometer) and a Snellen chart projector (Guyton-Minkowski Potential Acuity Meter). The predicted vision by each instrument was compared with the actual postoperative vision. Forty eyes in 36 of these patients, 25 with concurrent eye disease, had cataract extraction with intraocular lens implantation. Fifteen eyes in 15 patients, 11 with concurrent eye disease, had neodymium-YAG laser posterior capsulotomy. The Visometer gave more accurate predictions than the Potential Acuity Meter in cataract patients with open angle glaucoma, even with glaucomatous visual field loss, and in patients with a visual acuity of less than 20/400 due to advanced cataract formation.

  14. 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.

  15. 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

  16. 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.

  17. 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…

  18. The therapeutic effect of clinical trials: understanding placebo response rates in clinical trials – A secondary analysis

    PubMed Central

    Walach, Harald; Sadaghiani, Catarina; Dehm, Cornelia; Bierman, Dick

    2005-01-01

    Background and purpose Placebo response rates in clinical trials vary considerably and are observed frequently. For new drugs it can be difficult to prove effectiveness superior to placebo. It is unclear what contributes to improvement in the placebo groups. We wanted to clarify, what elements of clinical trials determine placebo variability. Methods We analysed a representative sample of 141 published long-term trials (randomized, double-blind, placebo-controlled; duration > 12 weeks) to find out what study characteristics predict placebo response rates in various diseases. Correlational and regression analyses with study characteristics and placebo response rates were carried out. Results We found a high and significant correlation between placebo and treatment response rate across diseases (r = .78; p < .001). A multiple regression model explained 79% of the variance in placebo variability (F = 59.7; p < 0.0001). Significant predictors are, among others, the duration of the study (beta = .31), the quality of the study (beta = .18), the fact whether a study is a prevention trial (beta = .44), whether dropouts have been documented (beta = -.20), or whether additional treatments have been documented (beta = -.17). Healing rates with placebo are lower in the following diagnoses; neoplasms (beta = -.21), nervous diseases (beta = -.10), substance abuse (beta = -.14). Without prevention trials the amount of variance explained is 42%. Conclusion Medication response rates and placebo response rates in clinical trials are highly correlated. Trial characteristics can explain some portion of the variance in placebo healing rates in RCTs. Placebo response in trials is only partially due to methodological artefacts and only partially dependent on the diagnoses treated. PMID:16109176

  19. Assessing Discriminative Performance at External Validation of Clinical Prediction Models

    PubMed Central

    Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

    2016-01-01

    Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect

  20. 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

  1. Exploring the Inflammatory Metabolomic Profile to Predict Response to TNF-α Inhibitors in Rheumatoid Arthritis.

    PubMed

    Cuppen, Bart V J; Fu, Junzeng; van Wietmarschen, Herman A; Harms, Amy C; Koval, Slavik; Marijnissen, Anne C A; Peeters, Judith J W; Bijlsma, Johannes W J; Tekstra, Janneke; van Laar, Jacob M; Hankemeier, Thomas; Lafeber, Floris P J G; van der Greef, Jan

    2016-01-01

    In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124). The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI). The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28), erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP). Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6), sn1-LPC(15:0), ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01). The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23) and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05). Our study established an accurate prediction model

  2. Exploring the Inflammatory Metabolomic Profile to Predict Response to TNF-α Inhibitors in Rheumatoid Arthritis

    PubMed Central

    van Wietmarschen, Herman A.; Harms, Amy C.; Koval, Slavik; Marijnissen, Anne C. A.; Peeters, Judith J. W.; Bijlsma, Johannes W. J.; Tekstra, Janneke; van Laar, Jacob M.; Hankemeier, Thomas; Lafeber, Floris P. J. G.; van der Greef, Jan

    2016-01-01

    In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA) respond insufficiently to TNF-α inhibitors (TNFis). The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients’ response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124). The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI). The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28), erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP). Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6), sn1-LPC(15:0), ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01). The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23) and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05). Our study established an accurate prediction

  3. 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

  4. PET-Based Treatment Response Evaluation in Rectal Cancer: Prediction and Validation

    SciTech Connect

    Janssen, Marco H.M.; Oellers, Michel C.; Stiphout, Ruud G.P.M. van; Riedl, Robert G.; Bogaard, Jorgen van den; Buijsen, Jeroen; Lambin, Philippe; Lammering, Guido

    2012-02-01

    select patients to be considered for less invasive surgical interventions or even a 'wait and see' policy. Also, based on the predicted response, early modifications of the treatment protocol are possible, which might result in an improved clinical outcome.

  5. 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

  6. 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

  7. 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

  8. Prestimulation phase predicts the TMS-evoked response.

    PubMed

    Kundu, Bornali; Johnson, Jeffrey S; Postle, Bradley R

    2014-10-15

    Prestimulation oscillatory phase and power in particular frequency bands predict perception of at-threshold visual stimuli and of transcranial magnetic stimulation (TMS)-induced phosphenes. These effects may be due to changes in cortical excitability, such that certain ranges of power and/or phase values result in a state in which a particular brain area is more receptive to input, thereby biasing behavior. However, the effects of trial-by-trial fluctuations in phase and power of ongoing oscillations on the brain's electrical response to TMS itself have thus far not been addressed. The present study adopts a combined TMS and electroencepalography (EEG) approach to determine whether the TMS-evoked response is sensitive to momentary fluctuations in prestimulation phase and/or power in different frequency bands. Specifically, TMS was applied to superior parietal lobule while subjects performed a short-term memory task. Results showed that the prestimulation phase, particularly within the beta (15-25 Hz) band, predicted pulse-by-pulse variations in the global mean field amplitude. No such relationship was observed between prestimulation power and the global mean field amplitude. Furthermore, TMS-evoked power in the beta band fluctuated with prestimulation phase in the beta band in a manner that differed from spontaneous brain activity. These effects were observed in areas at and distal to the stimulation site. Together, these results confirm the idea that fluctuating phase of ongoing neuronal oscillations create "windows of excitability" in the brain, and they give insight into how TMS interacts with ongoing brain activity on a pulse-by-pulse basis.

  9. 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.

  10. 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

  11. 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.

  12. [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.

  13. Pretreatment Mitochondrial Priming Correlates with Clinical Response to Cytotoxic Chemotherapy

    PubMed Central

    Chonghaile, Triona Ni; Sarosiek, Kristopher A.; Vo, Thanh-Trang; Ryan, Jeremy A.; Tammareddi, Anupama; Moore, Victoria Del Gaizo; Deng, Jing; Anderson, Ken; Richardson, Paul; Tai, Yu-Tzu; Mitsiades, Constantine S.; Matulonis, Ursula A.; Drapkin, Ronny; Stone, Richard; DeAngelo, Daniel J.; McConkey, David J.; Sallan, Stephen E.; Silverman, Lewis; Hirsch, Michelle S.; Carrasco, Daniel Ruben; Letai, Anthony

    2011-01-01

    Cytotoxic chemotherapy targets elements common to all nucleated human cells, such as DNA and microtubules, yet it selectively kills tumor cells. Here we show that clinical response to these drugs correlates with, and may be partially governed by, the pre-treatment proximity of tumor cell mitochondria to the apoptotic threshold, a property called mitochondrial priming. We used BH3 profiling to measure priming in tumor cells from patients with multiple myeloma, acute myelogenous and lymphoblastic leukemia, and ovarian cancer. This assay measures mitochondrial response to peptides derived from pro-apoptotic BH3 domains of proteins critical for death signaling to mitochondria. Patients with highly primed cancers exhibited superior clinical response to chemotherapy. In contrast, chemoresistant cancers and normal tissues were poorly primed. Manipulation of mitochondrial priming might enhance the efficacy of cytotoxic agents. PMID:22033517

  14. [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

  15. Design Characteristics Influence Performance of Clinical Prediction Rules in Validation: A Meta-Epidemiological Study

    PubMed Central

    Ban, Jong-Wook; Emparanza, José Ignacio; Urreta, Iratxe; Burls, Amanda

    2016-01-01

    Background Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules’ performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. Methods Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. Results A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2–4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. Conclusion Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved. PMID:26730980

  16. 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

  17. FTO predicts weight regain in the Look AHEAD Clinical Trial

    PubMed Central

    McCaffery, Jeanne; Papandonatos, George D.; Huggins, Gordon S.; Peter, Inga; Kahn, Steven E.; Knowler, William C.; Hudnall, Gina Evans; Lipkin, Edward; Kitabchi, Abbas E.; Wagenknecht, Lynne E.; Wing, Rena R.

    2013-01-01

    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 obesity risk alleles available on the Illumina CARe iSelect (IBC) chip were characterized in 3,899 overweight or obese participants with type 2 diabetes from the Look AHEAD (Action for Health in Diabetes), a randomized trial to determine the effects of intensive lifestyle intervention (ILI) and Diabetes Support and Education (DSE) on cardiovascular morbidity and mortality. Primary analyses examined the interaction between 13 obesity-risk polymorphisms in 8 genes and randomized treatment arm in predicting weight change at year 1, and weight regain at year 4 among individuals who lost 3% or more of their baseline weight by year 1. Results No SNPs were significantly associated with magnitude of weight loss or interacted with treatment arm at year 1. However, FTO rs3751812 predicted weight regain within DSE (1.56 kg per risk allele, p = 0.005), but not ILI (p = 0.761), resulting in SNP×treatment arm interaction (p = 0.009). In a partial replication of prior research, the obesity risk (G) allele at BDNF rs6265 was associated with greater weight regain across treatment arms (0.773 kg per risk allele), although results were of borderline statistical significance (p=0.051). Conclusions Variations in the FTO and BDNF loci may contribute risk of weight regain after weight loss. PMID:23628854

  18. 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.

  19. 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

  20. Efficient, Adaptive Clinical Validation of Predictive Biomarkers in Cancer Therapeutic Development.

    PubMed

    Beckman, Robert A; Chen, Cong

    2015-01-01

    Predictive biomarkers, defined as biomarkers that can be used to identify patient populations who will optimally benefit from therapy, are an important part of the future of oncology. They have the potential to reduce the size and cost of clinical development programs for oncology therapy, while increasing their probability of success and the ultimate value of cancer medicines. But predictive biomarkers do not always work, and under these circumstances they add cost, complexity, and time to drug development. This chapter describes Phase 2 and 3 development methods which efficiently and adaptively evaluate the ability of the biomarker to predict clinical outcomes. In the end, the biomarker is emphasized to the extent that it is actually predictive. This allows clinical cancer drug developers to manage uncertainty in the validity of biomarkers, leading to maximal value for predictive biomarkers and their associated oncology therapies.

  1. Locus Heterogeneity for Waardenburg Syndrome is Predictive of Clinical Subtypes

    PubMed Central

    Farrer, Lindsay A.; Arnos, Kathleen S.; Asher, James H.; Baldwin, Clinton T.; Diehl, Scott R.; Friedman, Thomas B.; Greenberg, Jacquie; Grundfast, Kenneth M.; Hoth, Christopher; Lalwani, Anil K.; Landa, Barbara; Leverton, Kate; Milunsky, Aubrey; Morell, Robert; Nance, Walter E.; Newton, Valerie; Ramesar, Rajkumar; Rao, Valluri S.; Reynolds, Jennifer E.; Agustin, Theresa B. San; Wilcox, Edward R.; Winship, Ingrid; Read, Andrew P.

    1994-01-01

    Waardenburg syndrome (WS) is a dominantly inherited and clinically variable syndrome of deafness, pigmentary changes, and distinctive facial features. Clinically, WS type I (WS1) is differentiated from WS type II (WS2) by the high frequency of dystopia canthorum in the family. In some families, WS is caused by mutations in the PAX3 gene on chromosome 2q. We have typed microsatellite markers within and flanking PAX3 in 41 WS1 kindreds and 26 WS2 kindreds in order to estimate the proportion of families with probable mutations in PAX3 and to study the relationship between phenotypic and genotypic heterogeneity. Evaluation of heterogeneity in location scores obtained by multilocus analysis indicated that WS is linked to PAX3 in 60% of all WS families and in 100% of WS1 families. None of the WS2 families were linked. In those families in which equivocal lod scores (between −2 and +1) were found, PAX3 mutations have been identified in 5 of the 15 WS1 families but in none of the 4 WS2 families. Although preliminary studies do not suggest any association between the phenotype and the molecular pathology in 20 families with known PAX3 mutations and in four patients with chromosomal abnormalities in the vicinity of PAX3, the presence of dystopia in multiple family members is a reliable indicator for identifying families likely to have a defect in PAX3. ImagesFigure 1 PMID:7942851

  2. 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

  3. Functional diffusion map: a noninvasive MRI biomarker for early stratification of clinical brain tumor response.

    PubMed

    Moffat, Bradford A; Chenevert, Thomas L; Lawrence, Theodore S; Meyer, Charles R; Johnson, Timothy D; Dong, Qian; Tsien, Christina; Mukherji, Suresh; Quint, Douglas J; Gebarski, Stephen S; Robertson, Patricia L; Junck, Larry R; Rehemtulla, Alnawaz; Ross, Brian D

    2005-04-12

    Assessment of radiation and chemotherapy efficacy for brain cancer patients is traditionally accomplished by measuring changes in tumor size several months after therapy has been administered. The ability to use noninvasive imaging during the early stages of fractionated therapy to determine whether a particular treatment will be effective would provide an opportunity to optimize individual patient management and avoid unnecessary systemic toxicity, expense, and treatment delays. We investigated whether changes in the Brownian motion of water within tumor tissue as quantified by using diffusion MRI could be used as a biomarker for early prediction of treatment response in brain cancer patients. Twenty brain tumor patients were examined by standard and diffusion MRI before initiation of treatment. Additional images were acquired 3 weeks after initiation of chemo- and/or radiotherapy. Images were coregistered to pretreatment scans, and changes in tumor water diffusion values were calculated and displayed as a functional diffusion map (fDM) for correlation with clinical response. Of the 20 patients imaged during the course of therapy, 6 were classified as having a partial response, 6 as stable disease, and 8 as progressive disease. The fDMs were found to predict patient response at 3 weeks from the start of treatment, revealing that early changes in tumor diffusion values could be used as a prognostic indicator of subsequent volumetric tumor response. Overall, fDM analysis provided an early biomarker for predicting treatment response in brain tumor patients. PMID:15805192

  4. 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.

  5. How electrodiagnosis predicts clinical outcome of focal peripheral nerve lesions.

    PubMed

    Robinson, Lawrence R

    2015-09-01

    This article reviews the electrodiagnostic (EDX) prognostic factors for focal traumatic and nontraumatic peripheral nerve injuries. Referring physicians and patients often benefit from general and nerve-specific prognostic information from the EDX consultant. Knowing the probable outcome from a nerve injury allows the referring physician to choose the best treatment options for his/her patients. Nerve injuries are variable in their mechanism, location, and pathophysiology. The general effects of the injuries on nerve and muscle are well known, but more research is needed for nerve-specific information. Several factors currently known to influence prognosis include: nature of the nerve trauma, amount of axon loss, recruitment in muscles supplied by the nerve, the extent of demyelination, and the distance to reinnervate functional muscles. This article reviews these general concepts and also nerve-specific EDX measures that predict outcome after focal neuropathies.

  6. 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

  7. Predicting early clinical function after hip or knee arthroplasty

    PubMed Central

    Poitras, S.; Wood, K. S.; Savard, J.; Dervin, G. F.; Beaule, P. E.

    2015-01-01

    Objectives Patient function after arthroplasty should ideally quickly improve. It is not known which peri-operative function assessments predict length of stay (LOS) and short-term functional recovery. The objective of this study was to identify peri-operative functions assessments predictive of hospital LOS and short-term function after hospital discharge in hip or knee arthroplasty patients. Methods In total, 108 patients were assessed peri-operatively with the timed-up-and-go (TUG), Iowa level of assistance scale, post-operative quality of recovery scale, readiness for hospital discharge scale, and the Western Ontario and McMaster Osteoarthritis Index (WOMAC). The older Americans resources and services activities of daily living (ADL) questionnaire (OARS) was used to assess function two weeks after discharge. Results Following multiple regressions, the pre- and post-operative day two TUG was significantly associated with LOS and OARS score, while the pre-operative WOMAC function subscale was associated with the OARS score. Pre-operatively, a cut-off TUG time of 11.7 seconds for LOS and 10.3 seconds for short-term recovery yielded the highest sensitivity and specificity, while a cut-off WOMAC function score of 48.5/100 yielded the highest sensitivity and specificity. Post-operatively, a cut-off day two TUG time of 31.5 seconds for LOS and 30.9 seconds for short-term function yielded the highest sensitivity and specificity. Conclusions The pre- and post-operative day two TUG can indicate hospital LOS and short-term functional capacities, while the pre-operative WOMAC function subscale can indicate short-term functional capacities. Cite this article: Bone Joint Res 2015;4:145–151. PMID:26336897

  8. Rituximab-induced depletion of anti-PLA2R autoantibodies predicts response in membranous nephropathy.

    PubMed

    Beck, Laurence H; Fervenza, Fernando C; Beck, David M; Bonegio, Ramon G B; Malik, Fahim A; Erickson, Stephen B; Cosio, Fernando G; Cattran, Daniel C; Salant, David J

    2011-08-01

    Autoantibodies to the M-type phospholipase A(2) receptor (PLA(2)R) are sensitive and specific for idiopathic membranous nephropathy. The anti-B cell agent rituximab is a promising therapy for this disease, but biomarkers of early response to treatment currently do not exist. Here, we investigated whether levels of anti-PLA(2)R correlate with the immunological activity of membranous nephropathy, potentially exhibiting a more rapid response to treatment than clinical parameters such as proteinuria. We measured the amount of anti-PLA(2)R using Western blot immunoassay in serial serum samples from a total of 35 patients treated with rituximab for membranous nephropathy in two distinct cohorts. Pretreatment samples from 25 of 35 (71%) patients contained anti-PLA(2)R, and these autoantibodies declined or disappeared in 17 (68%) of these patients within 12 months after rituximab. Those who demonstrated this immunologic response fared better clinically: 59% and 88% attained complete or partial remission by 12 and 24 months, respectively, compared with 0% and 33% among those with persistent anti-PLA(2)R levels. Changes in antibody levels preceded changes in proteinuria. One subject who relapsed during follow-up had a concomitant return of anti-PLA(2)R. In summary, measuring anti-PLA(2)R levels by immunoassay may be a method to follow and predict response to treatment with rituximab in membranous nephropathy.

  9. Rituximab-Induced Depletion of Anti-PLA2R Autoantibodies Predicts Response in Membranous Nephropathy

    PubMed Central

    Fervenza, Fernando C.; Beck, David M.; Bonegio, Ramon G.B.; Malik, Fahim A.; Erickson, Stephen B.; Cosio, Fernando G.; Cattran, Daniel C.; Salant, David J.

    2011-01-01

    Autoantibodies to the M-type phospholipase A2 receptor (PLA2R) are sensitive and specific for idiopathic membranous nephropathy. The anti-B cell agent rituximab is a promising therapy for this disease, but biomarkers of early response to treatment currently do not exist. Here, we investigated whether levels of anti-PLA2R correlate with the immunological activity of membranous nephropathy, potentially exhibiting a more rapid response to treatment than clinical parameters such as proteinuria. We measured the amount of anti-PLA2R using Western blot immunoassay in serial serum samples from a total of 35 patients treated with rituximab for membranous nephropathy in two distinct cohorts. Pretreatment samples from 25 of 35 (71%) patients contained anti-PLA2R, and these autoantibodies declined or disappeared in 17 (68%) of these patients within 12 months after rituximab. Those who demonstrated this immunologic response fared better clinically: 59% and 88% attained complete or partial remission by 12 and 24 months, respectively, compared with 0% and 33% among those with persistent anti-PLA2R levels. Changes in antibody levels preceded changes in proteinuria. One subject who relapsed during follow-up had a concomitant return of anti-PLA2R. In summary, measuring anti-PLA2R levels by immunoassay may be a method to follow and predict response to treatment with rituximab in membranous nephropathy. PMID:21784898

  10. Using biological markers to inform a clinically meaningful treatment response.

    PubMed

    Yehuda, Rachel; Bierer, Linda M; Pratchett, Laura C; Pelcovitz, Michelle

    2010-10-01

    Combat veterans with posttraumatic stress disorder (PTSD) demonstrate less robust improvement following treatments than do civilians with PTSD. This paper discusses a theoretical model for evaluating treatment response based on the extent of change in biological markers of symptom severity or resilience between treatment initiation and termination. Such analysis permits a determination of biological change associated with the liberal criteria commonly used to determine treatment response in combat PTSD, and a comparison of this to the biological change associated with clinical response determined according to the conservative definition more appropriate to civilian PTSD. Interim data supporting the utility of this approach is presented based on preliminary analyses from our work in progress. We propose that future studies consider the unique consequences of combat trauma and develop treatments that incorporate the complex nature of the exposure and response characteristic of a veteran population. PMID:20955338

  11. 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

  12. 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

  13. 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

    2016-06-03

    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.

  14. 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.

  15. 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

  16. 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…

  17. 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

  18. 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

  19. Cancer vaccines: identification of biomarkers predictive of clinical efficacy.

    PubMed

    Harrop, Richard

    2013-04-01

    Personalized medicine is playing an increasingly important role in the treatment of patients living with cancer. This landmark shift has been driven in part by statistics emerging from the "one size fits all" approach to the treatment of cancer patients. Some reports suggest that only a minority of individuals actually benefit from treatment and adverse effects of medications remain a major cause of hospitalization, morbidities and deaths. Although the side-effect profile of most immunotherapy treatment modalities is usually fairly benign, there is no reason to believe that immunotherapy is any different from other oncology therapies in that some patients are likely to receive more benefit than others. Indeed, the fact that generation of the therapeutic modality requires translation through multiple complex biological processes for an immunotherapy product to be effective may mean that such approaches require an even better understanding of the patient being treated. Furthermore, the very low success rate of cancer immunotherapy approaches to deliver benefit to patients demands a more detailed understanding of who will benefit and why. The identification of biomarkers predictive of treatment benefit is one route to improve the success rate of cancer vaccines.

  20. Volumetric Response beyond Six Months of Cardiac Resynchronization Therapy and Clinical Outcome

    PubMed Central

    van ’t Sant, Jetske; Fiolet, Aernoud T. L.; ter Horst, Iris A. H.; Cramer, Maarten J.; Mastenbroek, Mirjam H.; van Everdingen, Wouter M.; Mast, Thomas P.; Doevendans, Pieter A.

    2015-01-01

    Aims Response to cardiac resynchronization therapy (CRT) is often assessed six months after implantation. Our objective was to assess the number of patients changing from responder to non-responder between six and 14 months, so-called late non-responders, and compare them to patients who were responder both at six and 14 months, so-called stable responders. Furthermore, we assessed predictive values of six and 14-month response concerning clinical outcome. Methods 105 patients eligible for CRT were enrolled. Clinical, laboratory, ECG, and echocardiographic parameters and patient-reported health status (Kansas City Cardiomyopathy Questionnaire [KCCQ]) were assessed before, and six and 14 months after implantation. Response was defined as ≥15% LVESV decrease as compared to baseline. Major adverse cardiac events (MACE) were registered until 24 months after implantation. Predictive values of six and 14-month response for MACE were examined. Results In total, 75 (71%) patients were six-month responders of which 12 (16%) patients became late non-responder. At baseline, late non-responders more often had ischemic cardiomyopathy and atrial fibrillation, higher BNP and less dyssynchrony compared to stable responders. At six months, late non-responders showed significantly less LVESV decrease, and higher creatinine levels. Mean KCCQ scores of late non-responders were lower than those of stable responders at every time point, with the difference being significant at 14 months. The 14 months response was a better predictor of MACE than six months response. Conclusions The assessment of treatment outcomes after six months of CRT could be premature and response rates beyond might better correlate to long-term clinical outcome. PMID:25933068

  1. 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

  2. Preterm birth in twin pregnancies: Clinical outcomes and predictive parameters

    PubMed Central

    Dolgun, Zehra Nihal; Inan, Cihan; Altintas, Ahmet Salih; Okten, Sabri Berkem; Sayin, Niyazi Cenk

    2016-01-01

    Objective: To document the neonatal outcomes of preterm birth in twin pregnancies and to investigate whether perinatal and obstetric parameters are associated with clinical outcomes. Methods: This retrospective trial was conducted on data gathered from 176 preterm twins delivered in the obstetrics and gynecology department of our tertiary care center. Data extracted from medical files of 88 pregnant women who gave preterm birth (at 260/7 to 366/7 gestational weeks) to twins were analyzed. Maternal/fetal descriptive and obstetric parameters, sonographic data, route of delivery, indication for cesarean section, birth weight, Apgar scores, head circumference, umbilical cord length and placental weight were noted. Results: The average age of the pregnant women was 28.8±6.4 years and ultrasonographic gestational age was 31.9±2.6 weeks. Apgar scores at 1st minute were affected significantly by fetal body weight (p=0.001), gestational age (p=0.001), height (p=0.004) and head circumference (p=0.011). None of these variables exhibited a noteworthy effect on Apgar scores at 5th minute. Conclusion: Efforts must be made to achieve advancement of gestational age until delivery in the follow-up preterm of twins. A well-established algorithm with special emphasis to risk factors is necessary to standardize and popularize the appropriate management strategy.

  3. Preterm birth in twin pregnancies: Clinical outcomes and predictive parameters

    PubMed Central

    Dolgun, Zehra Nihal; Inan, Cihan; Altintas, Ahmet Salih; Okten, Sabri Berkem; Sayin, Niyazi Cenk

    2016-01-01

    Objective: To document the neonatal outcomes of preterm birth in twin pregnancies and to investigate whether perinatal and obstetric parameters are associated with clinical outcomes. Methods: This retrospective trial was conducted on data gathered from 176 preterm twins delivered in the obstetrics and gynecology department of our tertiary care center. Data extracted from medical files of 88 pregnant women who gave preterm birth (at 260/7 to 366/7 gestational weeks) to twins were analyzed. Maternal/fetal descriptive and obstetric parameters, sonographic data, route of delivery, indication for cesarean section, birth weight, Apgar scores, head circumference, umbilical cord length and placental weight were noted. Results: The average age of the pregnant women was 28.8±6.4 years and ultrasonographic gestational age was 31.9±2.6 weeks. Apgar scores at 1st minute were affected significantly by fetal body weight (p=0.001), gestational age (p=0.001), height (p=0.004) and head circumference (p=0.011). None of these variables exhibited a noteworthy effect on Apgar scores at 5th minute. Conclusion: Efforts must be made to achieve advancement of gestational age until delivery in the follow-up preterm of twins. A well-established algorithm with special emphasis to risk factors is necessary to standardize and popularize the appropriate management strategy. PMID:27648040

  4. 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.…

  5. 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.

  6. 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

  7. Improving the prediction of response to therapy in autism.

    PubMed

    Bent, Stephen; Hendren, Robert L

    2010-07-01

    Autism is a heterogeneous disorder involving complex mechanisms and systems occurring at diverse times. Because an individual child with autism may have only a subset of all possible abnormalities at a specific time, it may be challenging to identify beneficial effects of an intervention in double-blind, randomized, controlled trials, which compare the mean responses to treatments. Beneficial effects in a small subset of children may be obscured by the lack of effect in the majority. We review the evidence for several potential model systems of biochemical abnormalities that may contribute to the etiology of autism, we describe potential biomarkers or treatment targets for each of these abnormalities, and we provide illustrative treatment trials using this methodology. Potential model systems include immune over and under reactivity, inflammation, oxidative stress, free fatty acid metabolism, mitochondrial dysfunction, and excitotoxicity. Including potential biomarkers and targeted treatments in clinical trials for autism provides a potential method for limiting the heterogeneity of enrolled subjects, which may improve the power of studies to identify beneficial effects of treatments while also improving the understanding of the disease.

  8. 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.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26520742

  10. Expression levels of apoptosis-related proteins predict clinical outcome in anaplastic large cell lymphoma.

    PubMed

    ten Berge, Rosita L; Meijer, Chris J L M; Dukers, Danny F; Kummer, J Alain; Bladergroen, Bellinda A; Vos, Wim; Hack, C Erik; Ossenkoppele, Gert J; Oudejans, Joost J

    2002-06-15

    In vitro studies suggest that resistance to chemotherapy-induced apoptosis might explain poor response to therapy in fatal cases. Actual execution of apoptosis depends on proper functioning of effector caspases, particularly caspase 3, and on the expression levels of apoptosis-regulating proteins, including Bcl-2 and the recently identified granzyme B- specific protease inhibitor 9 (PI9). Thus, high levels of caspase 3 activation should reflect proper functioning of the apoptosis pathways, resulting in chemotherapy-sensitive neoplastic cells and a favorable prognosis. We tested this hypothesis by quantifying numbers of tumor cells positive for active caspase 3, Bcl-2, and PI9, respectively, in pretreatment biopsies of systemic anaplastic large cell lymphoma (ALCL) patients and by comparing these numbers with clinical outcome. Activation of caspase 3 in more than 5% of the tumor cells was strongly correlated with a highly favorable outcome. High numbers of Bcl-2- and PI9-positive tumor cells were found to predict unfavorable prognosis. This prognostic effect was strongly related to anaplastic lymphoma kinase (ALK) status: ALK-positive ALCL had significantly higher levels of active caspase 3, while high expression of the antiapoptotic proteins Bcl-2 and PI9 was almost completely restricted to ALK-negative cases. In conclusion, high numbers of active caspase 3-positive tumor cells predict a highly favorable prognosis in systemic ALCL patients. Poor prognosis is strongly related to high numbers of Bcl-2- and PI9-positive neoplastic cells. These data support the notion that a favorable response to chemotherapy depends on an intact apoptosis cascade. Moreover, these data indicate that differences in prognosis between ALK-positive and ALK-negative ALCL might be explained by differences in expression of apoptosis-inhibiting proteins.

  11. 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

  12. 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

  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.

    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. 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

    2016-08-23

    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.

  15. OVARIAN RESERVE TESTS AND THEIR UTILITY IN PREDICTING RESPONSE TO CONTROLLED OVARIAN STIMULATION IN RHESUS MONKEYS

    PubMed Central

    Wu, Julie M.; Takahashi, Diana L; Ingram, Donald K.; Mattison, Julie A.; Roth, George; Ottinger, Mary Ann; Zelinski, Mary B.

    2010-01-01

    Controlled ovarian stimulation (COS) is an alternative to natural breeding in nonhuman primates; however, these protocols are costly with no guarantee of success. Toward the objective of predicting COS outcome in rhesus monkeys, the current study evaluated three clinically used ovarian reserve tests (ORTs): day 3 (d3) follicle-stimulating hormone (FSH) with d3 inhibin B (INHB), the clomiphene citrate challenge test (CCCT), and the exogenous FSH Ovarian Reserve Test (EFORT). A COS was also performed and response was classified as either successful (COS+) or unsuccessful (COS−) and retrospectively compared to ORT predictions. FSH and INHB were assessed for best hormonal index in conjunction with the aforementioned tests. INHB was consistently more accurate than FSH in all ORTs used. Overall, a modified version of the CCCT using INHB values yielded the best percentage of correct predictions. This is the first report of ORT evaluation in rhesus monkeys and may provide a useful diagnostic test prior to costly follicle stimulations, as well as predicting the onset of menopause. PMID:20336797

  16. 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

  17. 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

  18. Outsmarting cancer: the power of hybrid genomic/proteomic biomarkers to predict drug response.

    PubMed

    Rexer, Brent N; Arteaga, Carlos L

    2014-01-01

    A recent study by Niepel and colleagues describes a novel approach to predicting response to targeted anti-cancer therapies. The authors used biochemical profiling of signaling activity in basal and ligand-stimulated states for a panel of receptor and intracellular kinases to develop predictive models of drug sensitivity. In some cases, the response to ligand stimulation predicted drug response better than did target abundance or genomic alterations in the targeted pathway. Furthermore, combining biochemical profiles with genomic information was better at predicting drug response. This work suggests that incorporating biochemical signaling profiles with genomic alterations should provide powerful predictors of response to molecularly targeted therapies.

  19. 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

  20. Predicted Interval Plots (PIPS): A Graphical Tool for Data Monitoring of Clinical Trials

    PubMed Central

    Li, Lingling; Evans, Scott R.; Uno, Hajime; Wei, L.J.

    2011-01-01

    Group sequential designs are often used in clinical trials to evaluate efficacy and/or futility. Many methods have been developed for different types of endpoints and scenarios. However, few of these methods convey information regarding effect sizes (e.g., treatment differences) and none uses prediction to convey information regarding potential effect size estimates and associated precision, with trial continuation. To address these limitations, Evans et al. (2007) proposed to use prediction and predicted intervals as a flexible and practical tool for quantitative monitoring of clinical trials. In this article, we reaffirm the importance and usefulness of this innovative approach and introduce a graphical summary, predicted interval plots (PIPS), to display the information obtained in the prediction process in a straightforward yet comprehensive manner. We outline the construction of PIPS and apply this method in two examples. The results and the interpretations of the PIPS are discussed. PMID:21423789

  1. ALDH-1 Expression Levels Predict Response or Resistance to Preoperative Chemoradiation in Resectable Esophageal Cancer Patients

    PubMed Central

    Ajani, J. A.; Wang, X.; Song, S.; Suzuki, A.; Taketa, T.; Sudo, K.; Wadhwa, R.; Hofstetter, W. L.; Komaki, R.; Maru, D. M.; Lee, J. H.; Bhutani, M. S.; Weston, B.; Baladandayuthapani, V.; Yao, Y.; Honjo, S.; Scott, A. W.; Skinner, H. D.; Johnson, R. L.; Berry, D.

    2013-01-01

    Purpose: Operable thoracic esophageal/gastroesophageal junction carcinoma (EC) is often treated with chemoradiation and surgery but tumor responses are unpredictable and heterogeneous. We hypothesized that aldehyde dehydrogenase-1 (ALDH-1) could be associated with response. Methods: The labeling indices (LIs) of ALDH-1 by immunohistochemistry in untreated tumor specimens were established in EC patients who had chemoradiation and surgery. Univariate logistic regression and 3-fold cross validation were carried out for the training (67% of patients) and validation (33%) sets. Non-clinical experiments in EC cells were performed to generate complimentary data. Results: Of 167 EC patients analyzed, 40 (24%) had a pathologic complete response (pathCR) and 27 (16%) had an extremely resistant (exCRTR) cancer. The median ALDH-1 LI was 0.2 (range, 0.01 to 0.85). There was a significant association between pathCR and low ALDH-1 LI (p=<0.001; odds-ratio [OR]=0.432). The 3-fold cross validation led to a concordance index (C-index) of 0.798 for the fitted model. There was a significant association between exCRTR and high ALDH-1 LI (p=<0.001; OR=3.782). The 3-fold cross validation led to the C-index of 0.960 for the fitted model. In several cell lines, higher ALDH-1 LIs correlated with resistant/aggressive phenotype. Cells with induced chemotherapy resistance upregulated ALDH-1 and resistance conferring genes (SOX9 and YAP1). Sorted ALDH-1+ cells were more resistant and had an aggressive phenotype in tumor spheres than ALDH-1− cells. Conclusions: Our clinical and non-clinical data demonstrate that ALDH-1 LIs are predictive of response to therapy and further research could lead to individualized therapeutic strategies and novel therapeutic targets for EC patients. PMID:24210755

  2. Variants in KCNJ11 and BAD do not predict response to ketogenic dietary therapies for epilepsy

    PubMed Central

    Schoeler, Natasha E.; Leu, Costin; White, Jon; Plagnol, Vincent; Ellard, Sian; Matarin, Mar; Yellen, Gary; Thiele, Elizabeth A.; Mackay, Mark; McMahon, Jacinta M.; Scheffer, Ingrid E.; Sander, Josemir W.; Cross, J. Helen; Sisodiya, Sanjay M.

    2015-01-01

    In the absence of specific metabolic disorders, predictors of response to ketogenic dietary therapies (KDT) are unknown. We aimed to determine whether variants in established candidate genes KCNJ11 and BAD influence response to KDT. We sequenced KCNJ11 and BAD in individuals without previously-known glucose transporter type 1 deficiency syndrome or other metabolic disorders, who received KDT for epilepsy. Hospital records were used to obtain demographic and clinical data. Two response phenotypes were used: ≥50% seizure reduction and seizure-freedom at 3-month follow-up. Case/control association tests were conducted with KCNJ11 and BAD variants with minor allele frequency (MAF) > 0.01, using PLINK. Response to KDT in individuals with variants with MAF < 0.01 was evaluated. 303 Individuals had KCNJ11 and 246 individuals had BAD sequencing data and diet response data. Six SNPs in KCNJ11 and two in BAD had MAF > 0.01. Eight variants in KCNJ11 and seven in BAD (of which three were previously-unreported) had MAF < 0.01. No significant results were obtained from association analyses, with either KDT response phenotype. P-values were similar when accounting for ethnicity using a stratified Cochran–Mantel–Haenszel test. There did not seem to be a consistent effect of rare variants on response to KDT, although the cohort size was too small to assess significance. Common variants in KCNJ11 and BAD do not predict response to KDT for epilepsy. We can exclude, with 80% power, association from variants with a MAF of >0.05 and effect size >3. A larger sample size is needed to detect associations from rare variants or those with smaller effect sizes. PMID:26590798

  3. Variants in KCNJ11 and BAD do not predict response to ketogenic dietary therapies for epilepsy.

    PubMed

    Schoeler, Natasha E; Leu, Costin; White, Jon; Plagnol, Vincent; Ellard, Sian; Matarin, Mar; Yellen, Gary; Thiele, Elizabeth A; Mackay, Mark; McMahon, Jacinta M; Scheffer, Ingrid E; Sander, Josemir W; Cross, J Helen; Sisodiya, Sanjay M

    2015-12-01

    In the absence of specific metabolic disorders, predictors of response to ketogenic dietary therapies (KDT) are unknown. We aimed to determine whether variants in established candidate genes KCNJ11 and BAD influence response to KDT. We sequenced KCNJ11 and BAD in individuals without previously-known glucose transporter type 1 deficiency syndrome or other metabolic disorders, who received KDT for epilepsy. Hospital records were used to obtain demographic and clinical data. Two response phenotypes were used: ≥ 50% seizure reduction and seizure-freedom at 3-month follow-up. Case/control association tests were conducted with KCNJ11 and BAD variants with minor allele frequency (MAF)>0.01, using PLINK. Response to KDT in individuals with variants with MAF<0.01 was evaluated. 303 Individuals had KCNJ11 and 246 individuals had BAD sequencing data and diet response data. Six SNPs in KCNJ11 and two in BAD had MAF>0.01. Eight variants in KCNJ11 and seven in BAD (of which three were previously-unreported) had MAF<0.01. No significant results were obtained from association analyses, with either KDT response phenotype. P-values were similar when accounting for ethnicity using a stratified Cochran-Mantel-Haenszel test. There did not seem to be a consistent effect of rare variants on response to KDT, although the cohort size was too small to assess significance. Common variants in KCNJ11 and BAD do not predict response to KDT for epilepsy. We can exclude, with 80% power, association from variants with a MAF of >0.05 and effect size >3. A larger sample size is needed to detect associations from rare variants or those with smaller effect sizes.

  4. Rapid-response impulsivity: definitions, measurement issues, and clinical implications.

    PubMed

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

    2015-04-01

    Impulsivity is a multifaceted construct that is a core feature of multiple psychiatric conditions and personality disorders. However, progress in understanding and treating impulsivity 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 article. 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 (a) selection of RRI measures should be informed by careful consideration of the strengths, limitations, and practical considerations of the available measures; (b) 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 (c) similar considerations be made for human and nonhuman studies in an effort to harmonize and integrate preclinical and clinical research.

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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

  10. The Use of Factorial Forecasting to Predict Public Response

    ERIC Educational Resources Information Center

    Weiss, David J.

    2012-01-01

    Policies that call for members of the public to change their behavior fail if people don't change; predictions of whether the requisite changes will take place are needed prior to implementation. I propose to solve the prediction problem with Factorial Forecasting, a version of functional measurement methodology that employs group designs. Aspects…

  11. 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

  12. 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

  13. Sympathetic skin response: basic mechanisms and clinical applications.

    PubMed

    Vetrugno, Robert; Liguori, Rocco; Cortelli, Pietro; Montagna, Pasquale

    2003-08-01

    Sympathetic skin response (SSR), defined as the momentary change of the electrical potential of the skin, may be spontaneous or reflexively evoked by a variety of internal or by externally applied arousal stimuli. Although the suprasegmental structures influencing the SSR in humans are not well known, SSR has been proposed as a non-invasive approach to investigate the function of the sympathetic system. SSR is easy to apply but current procedures are not sufficiently reliable for diagnostic purposes, and show imperfect correlations both with clinical features and other measurements of autonomic, in particular, sudomotor dysfunction. PMID:12955550

  14. Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

    PubMed

    Storchi, Riccardo; Zippo, Antonio G; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M

    2012-01-01

    Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neuronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

  15. 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

  16. 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

  17. 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…

  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. Clinical algorithm for improved prediction of ambulation and patient stratification after incomplete spinal cord injury.

    PubMed

    Zörner, Björn; Blanckenhorn, Wolf U; Dietz, Volker; Curt, Armin

    2010-01-01

    The extent of ambulatory recovery after motor incomplete spinal cord injury (miSCI) differs considerably amongst affected persons. This makes individual outcome prediction difficult and leads to increased within-group variation in clinical trials. The aims of this study on subjects with miSCI were: (1) to rank the strongest single predictors and predictor combinations of later walking capacity; (2) to develop a reliable algorithm for clinical prediction; and (3) to identify subgroups with only limited recovery of walking function. Correlation and logistic regression analyses were performed on a dataset of 90 subjects with tetra- or paraparesis, recruited in a prospective European multicenter study. Eleven measures obtained in the subacute injury period, including clinical examination, tibial somatosensory evoked potentials (tSSEP), and demographic factors, were related to ambulatory outcome (WISCI II, 6minWT) 6 months after injury. The lower extremity motor score (LEMS) alone and in combination was identified as most predictive for later walking capacity in miSCI. Ambulatory outcome of subjects with tetraparesis was correctly predicted for 92% (WISCI II) or 100% (6minWT) of the cases when LEMS was combined with either tSSEP or the ASIA Impairment Scale, respectively. For individuals with paraparesis, prediction was less distinct, mainly due to low prediction rates for individuals with poor walking outcome. A clinical algorithm was generated that allowed for the identification of a subgroup composed of individuals with tetraparesis and poor ambulatory recovery. These data provide evidence that a combination of predictors enables a reliable prediction of walking function and early patient stratification for clinical trials in miSCI.

  20. Label Propagation Prediction of Drug-Drug Interactions Based on Clinical Side Effects.

    PubMed

    Zhang, Ping; Wang, Fei; Hu, Jianying; Sorrentino, Robert

    2015-01-01

    Drug-drug interaction (DDI) is an important topic for public health, and thus attracts attention from both academia and industry. Here we hypothesize that clinical side effects (SEs) provide a human phenotypic profile and can be translated into the development of computational models for predicting adverse DDIs. We propose an integrative label propagation framework to predict DDIs by integrating SEs extracted from package inserts of prescription drugs, SEs extracted from FDA Adverse Event Reporting System, and chemical structures from PubChem. Experimental results based on hold-out validation demonstrated the effectiveness of the proposed algorithm. In addition, the new algorithm also ranked drug information sources based on their contributions to the prediction, thus not only confirming that SEs are important features for DDI prediction but also paving the way for building more reliable DDI prediction models by prioritizing multiple data sources. By applying the proposed algorithm to 1,626 small-molecule drugs which have one or more SE profiles, we obtained 145,068 predicted DDIs. The predicted DDIs will help clinicians to avoid hazardous drug interactions in their prescriptions and will aid pharmaceutical companies to design large-scale clinical trial by assessing potentially hazardous drug combinations. All data sets and predicted DDIs are available at http://astro.temple.edu/~tua87106/ddi.html. PMID:26196247

  1. Label Propagation Prediction of Drug-Drug Interactions Based on Clinical Side Effects.

    PubMed

    Zhang, Ping; Wang, Fei; Hu, Jianying; Sorrentino, Robert

    2015-01-01

    Drug-drug interaction (DDI) is an important topic for public health, and thus attracts attention from both academia and industry. Here we hypothesize that clinical side effects (SEs) provide a human phenotypic profile and can be translated into the development of computational models for predicting adverse DDIs. We propose an integrative label propagation framework to predict DDIs by integrating SEs extracted from package inserts of prescription drugs, SEs extracted from FDA Adverse Event Reporting System, and chemical structures from PubChem. Experimental results based on hold-out validation demonstrated the effectiveness of the proposed algorithm. In addition, the new algorithm also ranked drug information sources based on their contributions to the prediction, thus not only confirming that SEs are important features for DDI prediction but also paving the way for building more reliable DDI prediction models by prioritizing multiple data sources. By applying the proposed algorithm to 1,626 small-molecule drugs which have one or more SE profiles, we obtained 145,068 predicted DDIs. The predicted DDIs will help clinicians to avoid hazardous drug interactions in their prescriptions and will aid pharmaceutical companies to design large-scale clinical trial by assessing potentially hazardous drug combinations. All data sets and predicted DDIs are available at http://astro.temple.edu/~tua87106/ddi.html.

  2. 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

  3. 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…

  4. Evaluating predictive modeling’s potential to improve teleretinal screening participation in urban safety net clinics

    PubMed Central

    Ogunyemi, Omolola; Teklehaimanot, Senait; Patty, Lauren; Moran, Erin; George, Sheba

    2013-01-01

    Introduction Screening guidelines for diabetic patients recommend yearly eye examinations to detect diabetic retinopathy and other forms of diabetic eye disease. However, annual screening rates for retinopathy in US urban safety net settings remain low. Methods Using data gathered from a study of teleretinal screening in six urban safety net clinics, we assessed whether predictive modeling could be of value in identifying patients at risk of developing retinopathy. We developed and examined the accuracy of two predictive modeling approaches for diabetic retinopathy in a sample of 513 diabetic individuals, using routinely available clinical variables from retrospective medical record reviews. Bayesian networks and radial basis function (neural) networks were learned using ten-fold cross-validation. Results The predictive models were modestly predictive with the best model having an AUC of 0.71. Discussion Using routinely available clinical variables to predict patients at risk of developing retinopathy and to target them for annual eye screenings may be of some usefulness to safety net clinics. PMID:23920536

  5. Predictive biomarkers in colorectal cancer: usage, validation, and design in clinical trials.

    PubMed

    Shi, Qian; Mandrekar, Sumithra J; Sargent, Daniel J

    2012-03-01

    As cancer treatment development has shifted its attention to targeted therapies, it is becoming increasingly important to provide tools for selecting the right treatment for an individual patient to achieve optimal clinical benefit. Biomarkers, identified and studied in the process of understanding the nature of the disease at the molecular pathogenesis level, have been increasingly recognized as a critical aspect in more accurate diagnosis, prognosis assessment, and therapeutic targeting. Predictive biomarkers, which can aid treatment decisions, require extensive data for validation. In this article, we discuss the definition, clinical usages, and more extensively the clinical trial designs for the validation of predictive biomarkers. Predictive biomarker validation methods can be broadly grouped into retrospective and prospective designs. Retrospective validation utilizes data from previously conducted prospective randomized controlled trials. Prospective designs include enrichment designs, treatment-by-marker interaction designs, marker-based strategy designs, and adaptive designs. We discuss each design with examples and provide comparisons of the advantages and disadvantages among the different designs. We conclude that the combination of scientific, clinical, statistical, ethical, and practical considerations provides guidance for the choice of the clinical trial design for validation of each proposed predictive biomarker.

  6. Parents' responses to predictive genetic testing in their children: report of a single case study.

    PubMed

    Michie, S; McDonald, V; Bobrow, M; McKeown, C; Marteau, T

    1996-04-01

    There is a widely held view among health professionals that predictive genetic testing of children for late onset diseases is not desirable clinical practice. Yet, little is known about the views of parents, or their responses, to predictive genetic testing in their children. Since such testing is being carried out in some genetic centres, the opportunity was taken to conduct a single case study of the parents of 2 and 4 year old sisters who were tested for the gene for familial adenomatous polyposis. Interviews before testing, after, and 15 months later showed a stable attitude, that parental responsibility included making decisions about such testing, and that the role of health professionals should be one of information giving rather than decision making. These parents had no regrets about having their children tested and reported no changes in their behaviour towards either the child who tested positively or the child who tested negatively. Using standardised scales, mood was found to be within the normal range both before and after testing in the mother and father. This case study is a first step towards systematic empirical studies determining the consequences of acquiescing to parents' requests for genetic testing in their children.

  7. Identifying predictive features in drug response using machine learning: opportunities and challenges.

    PubMed

    Vidyasagar, Mathukumalli

    2015-01-01

    This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

  8. 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

  9. 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

  10. Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data

    PubMed Central

    Guo, Wentian; Li, Hui; Zhu, Yitan; Lan, Li; Yang, Shengjie; Drukker, Karen; Morris, Elizabeth; Burnside, Elizabeth; Whitman, Gary; Giger, Maryellen L.; Ji, Yuan; TCGA Breast Phenotype Research Group

    2015-01-01

    Abstract. Genomic and radiomic imaging profiles of invasive breast carcinomas from The Cancer Genome Atlas and The Cancer Imaging Archive were integrated and a comprehensive analysis was conducted to predict clinical outcomes using the radiogenomic features. Variable selection via LASSO and logistic regression were used to select the most-predictive radiogenomic features for the clinical phenotypes, including pathological stage, lymph node metastasis, and status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Cross-validation with receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve (AUC) was employed as the prediction metric. Higher AUCs were obtained in the prediction of pathological stage, ER, and PR status than for lymph node metastasis and HER2 status. Overall, the prediction performances by genomics alone, radiomics alone, and combined radiogenomics features showed statistically significant correlations with clinical outcomes; however, improvement on the prediction performance by combining genomics and radiomics data was not found to be statistically significant, most likely due to the small sample size of 91 cancer cases with 38 radiomic features and 144 genomic features. PMID:26835491

  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. 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

  13. 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.

  14. Role of genetics in prediction of disease course and response to therapy

    PubMed Central

    Vermeire, Severine; Van Assche, Gert; Rutgeerts, Paul

    2010-01-01

    The clinical course of Crohn’s disease and ulcerative colitis is highly variable between patients, and this has therapeutic implications. A number of clinical features have been identified, which predict a mild or more severe outcome. However, several of these are subjective and/or not persistent over time. With the progress in genetics research in inflammatory bowel disease (IBD), genetic markers are increasingly being proposed to improve stratification of patients. Genetics have the major advantage of being stable over time and not prone to subjective interpretation. Nevertheless, none of the genetic variants associated with particular outcomes have shown sufficient sensitivity or specificity to have been implemented in daily management. Along the same line of thinking, pharmacogenetics or the study of association between variability in drug response and genetic variation has also received more attention as part of the endeavor for personalized medicine. The ultimate goal in this area of medicine is to adapt medication to a patient’s specific genetic background and therefore improve on efficacy and safety rates. Although pharmacogenetic studies have been performed for all classes of drugs applied in IBD, few have generated consistent findings or have been replicated. The only genetic test approved for clinical practice is thiopurine S-methyltransferase testing prior to starting treatment with thiopurine analogues. The other reported associations have suffered from lack of confirmation or still need replication efforts. Nevertheless, the importance and necessity of pharmacogenetic studies will increase further as more therapeutic classes are being developed. PMID:20518082

  15. 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

  16. A predictive framework to understand forest responses to global change.

    PubMed

    McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S

    2009-04-01

    Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.

  17. Development and evaluation of a new method for predicting aircraft buffet response

    NASA Technical Reports Server (NTRS)

    Cunningham, A. M., Jr.; Waner, P. G., Jr.; Watts, J. D.; Benepe, D. B.; Riddle, D. W.

    1975-01-01

    The buffet prediction method uses rigid wind tunnel model fluctuating pressure data to form a buffet forcing function. The response is then calculated with a mathematical dynamic model of the airplane developed for gust response analysis. By including the extremes of phasing and contribution of symmetric and antisymmetric airplane responses, the upper and lower bounds are established for buffet response. F-111A flight test data show good agreement with predicted bounds for a variety of flight conditions.

  18. Clinical and inflammatory response to bloodstream infections in octogenarians

    PubMed Central

    2014-01-01

    Background Given the increasing incidence of bacteraemia causing significant morbidity and mortality in older patients, this study aimed to compare the clinical features, laboratory findings and mortality of patients over the age of 80 to younger adults. Methods This study was a retrospective, observational study. Participants were taken to be all patients aged 18 and above with confirmed culture positive sepsis, admitted to a large metropolitan hospital in the year 2010. Measurements taken included patient demographics (accommodation, age, sex, comorbidities), laboratory investigations (white cell count, neutrophil count, C-reactive protein, microbiology results), clinical features (vital signs, presence of localising symptoms, complications, place of acquisition). Results A total of 1367 patient episodes were screened and 155 met study inclusion criteria. There was no statistically significant difference between likelihood of fever or systolic blood pressure between younger and older populations (p-values of 0.81 and 0.64 respectively). Neutrophil count was higher in the older cohort (p = 0.05). Higher Charlson (J Chronic Dis40(5):373–383, 1987) comorbidity index, greater age and lower systolic blood pressure were found to be statistically significant predictors of mortality (p-values of 0.01, 0.02 and 0.03 respectively). Conclusion The findings of this study indicate older patients are more likely to present without localising features. However, importantly, there is no significant difference in the likelihood of fever or inflammatory markers. This study also demonstrates the importance of the Charlson Index of Comorbidities (J Chronic Dis40(5):373–383, 1987) as a predictive factor for mortality, with age and hypotension being less important but statistically significant predictive factors of mortality. PMID:24754903

  19. Prediction of clinical manifestations of transurethral resection syndrome by preoperative ultrasonographic estimation of prostate weight

    PubMed Central

    2014-01-01

    Background This study aimed to investigate the relationship between preoperative estimated prostate weight on ultrasonography and clinical manifestations of transurethral resection (TUR) syndrome. Methods The records of patients who underwent TUR of the prostate under regional anesthesia over a 6-year period were retrospectively reviewed. TUR syndrome is usually defined as a serum sodium level of < 125 mmol/l combined with clinical cardiovascular or neurological manifestations. This study focused on the clinical manifestations only, and recorded specific central nervous system and cardiovascular abnormalities according to the checklist proposed by Hahn. Patients with and without clinical manifestations of TUR syndrome were compared to determine the factors associated with TUR syndrome. Receiver operating characteristic curve analysis was used to determine the optimal cutoff value of estimated prostate weight for the prediction of clinical manifestations of TUR syndrome. Results This study included 167 patients, of which 42 developed clinical manifestations of TUR syndrome. There were significant differences in preoperative estimated prostate weight, operation time, resected prostate weight, intravenous fluid infusion volume, blood transfusion volume, and drainage of the suprapubic irrigation fluid between patients with and without clinical manifestations of TUR syndrome. The preoperative estimated prostate weight was correlated with the resected prostate weight (Spearman’s correlation coefficient, 0.749). Receiver operator characteristic curve analysis showed that the optimal cutoff value of estimated prostate weight for the prediction of clinical manifestations of TUR syndrome was 75 g (sensitivity, 0.70; specificity, 0.69; area under the curve, 0.73). Conclusions Preoperative estimation of prostate weight by ultrasonography can predict the development of clinical manifestations of TUR syndrome. Particular care should be taken when the estimated prostate

  20. Short‐Term Efficacy Reliably Predicts Long‐Term Clinical Benefit in Rheumatoid Arthritis Clinical Trials as Demonstrated by Model‐Based Meta‐Analysis

    PubMed Central

    Zhu, Rui; Xiao, Jim; Davis, John C.; Mandema, Jaap W.; Jin, Jin Y.; Tang, Meina T.

    2015-01-01

    Abstract The objective of this study was to assess the relationship between short‐term and long‐term treatment effects measured by the American College of Rheumatology (ACR) 50 responses and to assess the feasibility of predicting 6‐month efficacy from short‐term data. A rheumatoid arthritis (RA) database was constructed from 68 reported trials. We focused on the relationship between 3‐ and 6‐month ACR50 treatment effects and developed a generalized nonlinear model to quantify the relationship and test the impact of covariates. The ΔACR50 at 6 months strongly correlated with that at 3 months, moderately correlated with that at 2 months, and only weakly correlated with results obtained at <2 months. A scaling factor that reflected the ratio of 6‐ to 3‐month treatment effects was estimated to be 0.997, suggesting that the treatment effects at 3 months are approaching a “plateau.” Drug classes, baseline Disease Activity Score in 28 Joints, and the magnitude of control arm response did not show significant impacts on the scaling factor. This work quantitatively supports the empirical clinical development paradigm of using 3‐month efficacy data to predict long‐term efficacy and to inform the probability of clinical success based on early efficacy readout. PMID:26517752

  1. Rapid-response impulsivity: definitions, measurement issues, and clinical implications.

    PubMed

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

    2015-04-01

    Impulsivity is a multifaceted construct that is a core feature of multiple psychiatric conditions and personality disorders. However, progress in understanding and treating impulsivity 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 article. 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 (a) selection of RRI measures should be informed by careful consideration of the strengths, limitations, and practical considerations of the available measures; (b) 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 (c) similar considerations be made for human and nonhuman studies in an effort to harmonize and integrate preclinical and clinical research. PMID:25867840

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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...

  7. 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…

  8. 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)

  9. Synergistic combination of clinical and imaging features predicts abnormal imaging patterns of pulmonary infections

    PubMed Central

    Bagci, Ulas; Jaster-Miller, Kirsten; Olivier, Kenneth N.; Yao, Jianhua; Mollura, Daniel J.

    2013-01-01

    We designed and tested a novel hybrid statistical model that accepts radiologic image features and clinical variables, and integrates this information in order to automatically predict abnormalities in chest computed-tomography (CT) scans and identify potentially important infectious disease biomarkers. In 200 patients, 160 with various pulmonary infections and 40 healthy controls, we extracted 34 clinical variables from laboratory tests and 25 textural features from CT images. From the CT scans, pleural effusion (PE), linear opacity (or thickening) (LT), tree-in-bud (TIB), pulmonary nodules, ground glass opacity (GGO), and consolidation abnormality patterns were analyzed and predicted through clinical, textural (imaging), or combined attributes. The presence and severity of each abnormality pattern was validated by visual analysis of the CT scans. The proposed biomarker identification system included two important steps: (i) a coarse identification of an abnormal imaging pattern by adaptively selected features (AmRMR), and (ii) a fine selection of the most important features from the previous step, and assigning them as biomarkers, depending on the prediction accuracy. Selected biomarkers were used to classify normal and abnormal patterns by using a boosted decision tree (BDT) classifier. For all abnormal imaging patterns, an average prediction accuracy of 76.15% was obtained. Experimental results demonstrated that our proposed biomarker identification approach is promising and may advance the data processing in clinical pulmonary infection research and diagnostic techniques. PMID:23930819

  10. False Positives among Adolescent Sex Offenders: Concurrent and Predictive Validity of the Millon Adolescent Clinical Inventory

    ERIC Educational Resources Information Center

    Kennedy, Wallace A.; Licht, Mark H.; Caminez, Mary

    2004-01-01

    The ability of the "Millon Adolescent Clinical Inventory"("MACI"; Millon, 1993) to identify serious adolescent, male sexual-offenders and to predict their recidivism following treatment was examined. "MACI" scores were evaluated for 381 adolescent, male sexual-offenders adjudicated delinquent for felony crimes and given maximum sentences, and, on…

  11. 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…

  12. Predictive value of clinical and laboratory findings in the diagnosis of the enteric fever.

    PubMed

    Kuvandik, Ceren; Karaoglan, Ilkay; Namiduru, Mustafa; Baydar, Ibrahim

    2009-01-01

    Although the definitive diagnosis of enteric fever requires the isolation of Salmonella enterica serotype typhi or paratyphi, the diagnosis is usually made according to clinical and laboratory findings. There is usually a diagnostic dilemma. The aim of this study was to determine the minimum required parameters that could be valuable in the diagnosis of enteric fever. A retrospective study was performed to compare the clinical and laboratory findings in 60 patients who proved to have enteric fever by cultures and 58 patients with non-enteric fever. Features independently predictive of enteric fever were assessed by multivariate logistic regression. Sensitivity, specificity and positive predictive and negative predictive values were estimated. Significant clinical features of enteric fever were hepatomegaly, splenomegaly, relative bradycardia, rose spots, leucopenia, trombocytopenia, eosinopenia and elevated AST level. Five of these features were found to be predictive for the diagnosis of enteric fever; splenomegaly, relative bradycardia, rose spots and trombocytopenia and elevated AST level. In conclusion, clinical and laboratory findings can help the clinician to diagnose enteric fever in the absence of microbiological confirmation. PMID:19382666

  13. 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

  14. 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

  15. Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest.

    PubMed

    Huang, Lei; Jin, Yan; Gao, Yaozong; Thung, Kim-Han; Shen, Dinggang

    2016-10-01

    Alzheimer's disease (AD) is an irreversible neurodegenerative disease and affects a large population in the world. Cognitive scores at multiple time points can be reliably used to evaluate the progression of the disease clinically. In recent studies, machine learning techniques have shown promising results on the prediction of AD clinical scores. However, there are multiple limitations in the current models such as linearity assumption and missing data exclusion. Here, we present a nonlinear supervised sparse regression-based random forest (RF) framework to predict a variety of longitudinal AD clinical scores. Furthermore, we propose a soft-split technique to assign probabilistic paths to a test sample in RF for more accurate predictions. In order to benefit from the longitudinal scores in the study, unlike the previous studies that often removed the subjects with missing scores, we first estimate those missing scores with our proposed soft-split sparse regression-based RF and then utilize those estimated longitudinal scores at all the previous time points to predict the scores at the next time point. The experiment results demonstrate that our proposed method is superior to the traditional RF and outperforms other state-of-art regression models. Our method can also be extended to be a general regression framework to predict other disease scores. PMID:27500865

  16. 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

  17. Childhood trauma predicts antidepressant response in adults with major depression: data from the randomized international study to predict optimized treatment for depression

    PubMed Central

    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

  18. 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

  19. 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...

  20. 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

  1. 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

  2. Detecting qualitative interactions in clinical trials with binary responses.

    PubMed

    Kitsche, Andreas

    2014-01-01

    This study considers the detection of treatment-by-subset interactions in a stratified, randomised clinical trial with a binary-response variable. The focus lies on the detection of qualitative interactions. In addition, the presented method is useful more generally, as it can assess the inconsistency of the treatment effects among strata by using an a priori-defined inconsistency margin. The methodology presented is based on the construction of ratios of treatment effects. In addition to multiplicity-adjusted p-values, simultaneous confidence intervals are recommended to use in detecting the source and the amount of a potential qualitative interaction. The proposed method is demonstrated on a multi-regional trial using the open-source statistical software R. PMID:25049176

  3. Interleukin-28b CC genotype predicts early treatment response and CT/TT genotypes predicts non-response in patients infected with HCV genotype 3.

    PubMed

    Gupta, Abhishak Chander; Trehanpati, Nirupma; Sukriti, Sukriti; Hissar, Syed; Midha, Vandana; Sood, Ajit; Sarin, Shiv K

    2014-04-01

    Response to antiviral therapy for hepatitis C virus (HCV) depends upon the genotype and host immune response. IL28b gene mutations have been shown to modulate host antiviral immune response against genotype 1. However, the predictive value of IL28b polymorphism in genotype 3 HCV patients is largely unknown. The association of IL28b polymorphism with virological response was studied in 356 patients with genotype 3 chronic HCV undergoing treatment with peg-interferon and ribavirin and was compared with matched controls. IL28b genotyping followed by DNA sequencing was performed to identify the CC, CT, or TT genotypes. Two log reduction of HCV RNA at Day 7 (Quick Viral Response, QVR) and HCV RNA negativity at Day 28 (Rapid Viral Response, RVR) were analyzed with CC and non-CC genotypes in addition to other predictors of response. The associations of alleles with the response patterns were predicted. Sustained viral response was seen in 250 (70.2%) patients and the IL28b genotype CC/CT/TT distribution was 61.1%; 30.5%; and 8.4%, respectively. The non-CC genotypes were significantly higher in non-responders when compared to responders (67.6% vs. 38.9%, P < 0.001). Interestingly, the rapid viral response in responders was observed in 72.7% with the CC genotype and in 27.2% with the non-CC genotype (P < 0.001). Multivariate analysis showed CC genotype as an independent factor predicting the sustained viral response in patients infected with HCV genotype 3. In conclusion, the IL28b CT/TT genotype strongly correlates with treatment non-response in patients infected with HCV genotype 3 and CC genotype of IL28b is associated with higher quick viral response.

  4. 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

  5. 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

  6. 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

  7. Circadian gene expression predicts patient response to neoadjuvant chemoradiation therapy for rectal cancer.

    PubMed

    Lu, Haijie; Chu, Qiqi; Xie, Guojiang; Han, Hao; Chen, Zheng; Xu, Benhua; Yue, Zhicao

    2015-01-01

    Preoperative neoadjuvant chemoradiation therapy may be useful in patients with operable rectal cancer, but treatment responses are variable. We examined whether expression levels of circadian clock genes could be used as biomarkers to predict treatment response. We retrospectively analyzed clinical data from 250 patients with rectal cancer, treated with neoadjuvant chemoradiation therapy in a single institute between 2011 and 2013. Gene expression analysis (RT-PCR) was performed in tissue samples from 20 patients showing pathological complete regression (pCR) and 20 showing non-pCR. The genes analyzed included six core clock genes (Clock, Per1, Per2, Cry1, Cry2 and Bmal1) and three downstream target genes (Wee1, Chk2 and c-Myc). Patient responses were analyzed through contrast-enhanced pelvic MRI and endorectal ultrasound, and verified by histological assessment. pCR was defined histologically as an absence of tumor cells. Among the 250 included patients, 70.8% showed regression of tumor size, and 18% showed pCR. Clock, Cry2 and Per2 expressions were significantly higher in the pCR group than in the non-pCR group (P<0.05), whereas Per1, Cry1 and Bmal1 expressions did not differ significantly between groups. Among the downstream genes involved in cell cycle regulation, c-Myc showed significantly higher expression in the pCR group (P<0.05), whereas Wee1 and Chk2 expression did not differ significantly between groups. Circadian genes are potential biomarkers for predicting whether a patient with rectal cancer would benefit from neoadjuvant chemoradiation therapy. PMID:26617816

  8. 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

  9. 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

  10. 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

  11. Does response on the PHQ-9 Depression Questionnaire predict subsequent suicide attempt or suicide death?

    PubMed

    Simon, Gregory E; Rutter, Carolyn M; Peterson, Do; Oliver, Malia; Whiteside, Ursula; Operskalski, Belinda; Ludman, Evette J

    2013-12-01

    OBJECTIVE As use of standard depression questionnaires in clinical practice increases, clinicians will frequently encounter patients reporting thoughts of death or suicide. This study examined whether responses to the Patient Health Questionnaire for depression (PHQ-9) predict subsequent suicide attempt or suicide death. METHODS Electronic records from a large integrated health system were used to link PHQ-9 responses from outpatient visits to subsequent suicide attempts and suicide deaths. A total of 84,418 outpatients age ≥13 completed 207,265 questionnaires between 2007 and 2011. Electronic medical records, insurance claims, and death certificate data documented 709 subsequent suicide attempts and 46 suicide deaths in this sample. RESULTS Cumulative risk of suicide attempt over one year increased from .4% among outpatients reporting thoughts of death or self-harm "not at all" to 4% among those reporting thoughts of death or self-harm "nearly every day." After adjustment for age, sex, treatment history, and overall depression severity, responses to item 9 of the PHQ-9 remained a strong predictor of suicide attempt. Cumulative risk of suicide death over one year increased from .03% among those reporting thoughts of death or self-harm ideation "not at all" to .3% among those reporting such thoughts "nearly every day." Response to item 9 remained a moderate predictor of subsequent suicide death after the same factor adjustments. CONCLUSIONS Response to item 9 of the PHQ-9 for depression identified outpatients at increased risk of suicide attempt or death. This excess risk emerged over several days and continued to grow for several months, indicating that suicidal ideation was an enduring vulnerability rather than a short-term crisis.

  12. Predicting dangerousness and the public health response to AIDS.

    PubMed

    Macklin, R

    1986-12-01

    It is argued on ethical grounds that public health measures to control the spread of acquired immunodeficiency syndrome (AIDS) must rely on voluntary efforts, rather than on mandatory quarantine or isolation of infected individuals. Although state interference to prevent harm to third parties is accepted when criminal behavior is involved, application of the harm principle is controversial in other contexts. Using the analogy of involuntary commitment of the mentally ill, where prediction of dangerousness is based on past behavior, the author points out that testing for HIV antibodies can give a yes-or-no answer to whether a person is infected. However, because there is little basis for predicting whether the person will act to infect others, only people who are known wantonly to jeopardize others should be isolated. Macklin also examines the special situations of prisoners and prostitutes, as well as the social impact of mass invasions of privacy and denial of civil rights.

  13. 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

  14. 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

  15. 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

  16. Assessing the predictive value of the rodent neurofunctional assessment for commonly reported adverse events in phase I clinical trials.

    PubMed

    Mead, Andy N; Amouzadeh, Hamid R; Chapman, Kathryn; Ewart, Lorna; Giarola, Alessandra; Jackson, Samuel J; Jarvis, Philip; Jordaan, Pierre; Redfern, Will; Traebert, Martin; Valentin, Jean-Pierre; Vargas, Hugo M

    2016-10-01

    Central Nervous System (CNS)-related safety concerns are major contributors to delays and failure during the development of new candidate drugs (CDs). CNS-related safety data on 141 small molecule CDs from five pharmaceutical companies were analyzed to identify the concordance between rodent multi-parameter neurofunctional assessments (Functional Observational Battery: FOB, or Irwin test: IT) and the five most common adverse events (AEs) in Phase I clinical trials, namely headache, nausea, dizziness, fatigue/somnolence and pain. In the context of this analysis, the FOB/IT did not predict the occurrence of these particular AEs in man. For AEs such as headache, nausea, dizziness and pain the results are perhaps unsurprising, as the FOB/IT were not originally designed to predict these AEs. More unexpected was that the FOB/IT are not adequate for predicting 'somnolence/fatigue' nonclinically. In drug development, these five most prevalent AEs are rarely responsible for delaying or stopping further progression of CDs. More serious AEs that might stop CD development occurred at too low an incidence rate in our clinical dataset to enable translational analysis.

  17. Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model

    PubMed Central

    Yamamoto, Kimiyo N.; Ishii, Masatsugu; Inoue, Yoshihiro; Hirokawa, Fumitoshi; MacArthur, Ben D.; Nakamura, Akira; Haeno, Hiroshi; Uchiyama, Kazuhisa

    2016-01-01

    Although the capacity of the liver to recover its size after resection has enabled extensive liver resection, post-hepatectomy liver failure remains one of the most lethal complications of liver resection. Therefore, it is clinically important to discover reliable predictive factors after resection. In this study, we established a novel mathematical framework which described post-hepatectomy liver regeneration in each patient by incorporating quantitative clinical data. Using the model fitting to the liver volumes in series of computed tomography of 123 patients, we estimated liver regeneration rates. From the estimation, we found patients were divided into two groups: i) patients restored the liver to its original size (Group 1, n = 99); and ii) patients experienced a significant reduction in size (Group 2, n = 24). From discriminant analysis in 103 patients with full clinical variables, the prognosis of patients in terms of liver recovery was successfully predicted in 85–90% of patients. We further validated the accuracy of our model prediction using a validation cohort (prediction = 84–87%, n = 39). Our interdisciplinary approach provides qualitative and quantitative insights into the dynamics of liver regeneration. A key strength is to provide better prediction in patients who had been judged as acceptable for resection by current pragmatic criteria. PMID:27694914

  18. 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.

  19. 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

  20. 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

  1. 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

  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

    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

    2015-08-28

    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.

  4. 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

  5. Does early improvement predict endpoint response in patients with generalized anxiety disorder (GAD) treated with pregabalin or venlafaxine XR?

    PubMed

    Baldwin, David S; Schweizer, Edward; Xu, Yikang; Lyndon, Gavin

    2012-02-01

    Many patients with generalized anxiety disorder (GAD) only respond to pharmacological treatment after a delay of some weeks, and approximately 35% of patients do not respond. Therefore, early identification of potential responders may have important implications for clinical decision-making. In order to identify early improvement criteria that optimally predict eventual response during short-term treatment of GAD with pregabalin or venlafaxine XR, data were pooled from four double-blind, placebo-controlled GAD treatment studies. A range of measures were analyzed using logistic regression models and receiver operator characteristic (ROC) curve analysis, to predict endpoint response. Results showed that early improvement (≥ 20% reduction from baseline score) on the Hamilton Anxiety Scale (HAM-A) was associated with a high probability of achieving an endpoint response at Weeks 1 and 2 among patients treated with pregabalin (~67%), and at Week 2 with venlafaxine XR (60%). A Clinical Global Impression - Improvement (CGI-I) score ≤ 3 at Week 2 was a reliable predictor of achieving endpoint response for pregabalin and venlafaxine XR (odds ratio [OR], 5.33 and 2.47, respectively) with high sensitivity (pregabalin, 0.91; venlafaxine XR, 0.86) and relatively low specificity (pregabalin, 0.33; venlafaxine XR, 0.29), indicating a high true positive rate, but relatively low true negative rate. These findings indicate that improvement by Week 2 on the single item CGI may be a simple and reliable way to predict treatment response with pregabalin or venlafaxine XR in patients with GAD, but a less reliable way to predict non-responders.

  6. 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

  7. 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…

  8. 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…

  9. COMT val158met predicts reward responsiveness in humans.

    PubMed

    Lancaster, T M; Linden, D E; Heerey, E A

    2012-11-01

    A functional variant of the catechol-O-methyltransferase (COMT) gene [val158met (rs4680)] is frequently implicated in decision-making and higher cognitive functions. It may achieve its effects by modulating dopamine-related decision-making and reward-guided behaviour. Here we demonstrate that individuals with the met/met polymorphism have greater responsiveness to reward than carriers of the val allele and that this correlates with risk-seeking behaviour. We assessed performance on a reward responsiveness task and the Balloon analogue risk task, which measure how participants (N = 70, western European, university and postgraduate students) respond to reward and take risks in the presence of available reward. Individuals with the met/met genotype (n = 19) showed significantly higher reward responsiveness, F2,64 = 4.02, P = 0.02, and reward-seeking behaviour, F(2,68) = 4.52, P = 0.01, than did either val/met (n = 25) or val/val (n = 26) carriers. These results highlight a scenario in which genotype-dependent reward responsiveness shapes reward-seeking, therefore suggesting a novel framework by which COMT may modulate behaviour. PMID:22900954

  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. Predictive monitoring of mobile patients by combining clinical observations with data from wearable sensors.

    PubMed

    Clifton, Lei; Clifton, David A; Pimentel, Marco A F; Watkinson, Peter J; Tarassenko, Lionel

    2014-05-01

    The majority of patients in the hospital are ambulatory and would benefit significantly from predictive and personalized monitoring systems. Such patients are well suited to having their physiological condition monitored using low-power, minimally intrusive wearable sensors. Despite data-collection systems now being manufactured commercially, allowing physiological data to be acquired from mobile patients, little work has been undertaken on the use of the resultant data in a principled manner for robust patient care, including predictive monitoring. Most current devices generate so many false-positive alerts that devices cannot be used for routine clinical practice. This paper explores principled machine learning approaches to interpreting large quantities of continuously acquired, multivariate physiological data, using wearable patient monitors, where the goal is to provide early warning of serious physiological determination, such that a degree of predictive care may be provided. We adopt a one-class support vector machine formulation, proposing a formulation for determining the free parameters of the model using partial area under the ROC curve, a method arising from the unique requirements of performing online analysis with data from patient-worn sensors. There are few clinical evaluations of machine learning techniques in the literature, so we present results from a study at the Oxford University Hospitals NHS Trust devised to investigate the large-scale clinical use of patient-worn sensors for predictive monitoring in a ward with a high incidence of patient mortality. We show that our system can combine routine manual observations made by clinical staff with the continuous data acquired from wearable sensors. Practical considerations and recommendations based on our experiences of this clinical study are discussed, in the context of a framework for personalized monitoring.

  12. The burden of the systemic inflammatory response predicts vasospasm and outcome after subarachnoid hemorrhage

    PubMed Central

    Dhar, Rajat; Diringer, Michael N.

    2008-01-01

    Introduction: Subarachnoid hemorrhage (SAH) can trigger immune activation sufficient to induce the systemic inflammatory response syndrome (SIRS). This may promote both extra-cerebral organ dysfunction and delayed cerebral ischemia, contributing to worse outcome. We ascertained the frequency and predictors of SIRS after spontaneous SAH, and determined whether degree of early systemic inflammation predicted the occurrence of vasospasm and clinical outcome. Methods: Retrospective analysis of prospectively collected data on 276 consecutive patients admitted to a neurosciences intensive care unit with acute, non-traumatic SAH between 2002 and 2005. A daily SIRS score was derived by summing the number of variables meeting standard criteria (HR >90, RR >20, Temperature >38°C or <36°C, WBC count <4,000 or >12,000). SIRS was considered present if two or more criteria were met, while SIRS burden over the first four days was calculated by averaging daily scores. Regression modeling was used to determine the relationship between SIRS burden (after controlling for confounders including infection, surgery, and corticosteroid use), symptomatic vasospasm, and outcome, determined by hospital disposition. Results: SIRS was present in over half the patients on admission and developed in 85% within the first four days. Factors associated with SIRS included poor clinical grade, thick cisternal blood, larger aneurysm size, higher admission blood pressure, and surgery for aneurysm clipping. Higher SIRS burden was independently associated with death or discharge to nursing home (OR 2.20/point, 95% CI 1.27-3.81). All of those developing clinical vasospasm had evidence of SIRS, with greater SIRS burden predicting increased risk for delayed ischemic neurological deficits (OR 1.77/point, 95% CI 1.12-2.80). Conclusions: Systemic inflammatory activation is common after SAH even in the absence of infection; it is more frequent in those with more severe hemorrhage and in those who undergo

  13. Effects of scale in predicting global structural response

    NASA Technical Reports Server (NTRS)

    Deo, R. B.; Kan, H. P.

    1991-01-01

    Analytical techniques for scale-up effects were reviewed. The advantages and limitations of applying the principles of similitude to composite structures is summarized and illustrated by simple examples. An analytical procedure was formulated to design scale models of an axially compressed composite cylinder. A building-block approach was outlined where each structural detail is analyzed independently and the probable failure sequence of a selected component is predicted, taking into account load redistribution subsequent to first element failure. Details of this building-block approach are under development.

  14. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs.

    PubMed

    De Buck, Stefan S; Sinha, Vikash K; Fenu, Luca A; Nijsen, Marjoleen J; Mackie, Claire E; Gilissen, Ron A H J

    2007-10-01

    The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics. PMID:17620347

  15. Even modest prediction accuracy of genomic models can have large clinical utility.

    PubMed

    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 (R (2) = 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.

  16. 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

  17. [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

  18. Predicting nonlinear properties of metamaterials from the linear response.

    PubMed

    O'Brien, Kevin; Suchowski, Haim; Rho, Junsuk; Salandrino, Alessandro; Kante, Boubacar; Yin, Xiaobo; Zhang, Xiang

    2015-04-01

    The discovery of optical second harmonic generation in 1961 started modern nonlinear optics. Soon after, R. C. Miller found empirically that the nonlinear susceptibility could be predicted from the linear susceptibilities. This important relation, known as Miller's Rule, allows a rapid determination of nonlinear susceptibilities from linear properties. In recent years, metamaterials, artificial materials that exhibit intriguing linear optical properties not found in natural materials, have shown novel nonlinear properties such as phase-mismatch-free nonlinear generation, new quasi-phase matching capabilities and large nonlinear susceptibilities. However, the understanding of nonlinear metamaterials is still in its infancy, with no general conclusion on the relationship between linear and nonlinear properties. The key question is then whether one can determine the nonlinear behaviour of these artificial materials from their exotic linear behaviour. Here, we show that the nonlinear oscillator model does not apply in general to nonlinear metamaterials. We show, instead, that it is possible to predict the relative nonlinear susceptibility of large classes of metamaterials using a more comprehensive nonlinear scattering theory, which allows efficient design of metamaterials with strong nonlinearity for important applications such as coherent Raman sensing, entangled photon generation and frequency conversion.

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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

  4. External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

    PubMed

    Hickey, Graeme L; Blackstone, Eugene H

    2016-08-01

    Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting.

  5. A Clinic-Based Lifestyle Intervention for Pediatric Obesity: Efficacy and Behavioral and Biochemical Predictors of Response

    PubMed Central

    Madsen, Kristine A.; Garber, Andrea K.; Mietus-Snyder, Michele L.; Orrell-Valente, Joan K.; Tran, Cam-Tu; Wlasiuk, Lidya; Matos, Renee I.; Neuhaus, John; Lustig, Robert H.

    2010-01-01

    Aim To examine efficacy and predictors of response to a lifestyle intervention for obese youth. Methods Retrospective chart review of 214 children and adolescents aged 8-19 years. Linear regression identified baseline predictors of response (Δ BMI z-score) at first and ultimate follow-up visits. Results Mean Δ BMI z-score from baseline was -0.04 (p <0.001) at first follow-up and -0.09 (p <0.001) at ultimate follow-up (median time 10 mo) among 156 children and adolescents. Higher baseline BMI z-score predicted poor response at first and ultimate follow-up, explaining 10% of variance in response. Fasting insulin explained 6% of response variance at first follow-up. Δ BMI z-score at the first visit along with baseline BMI z-score explained up to 50% of variance in response at ultimate visit. Conclusion Clinic-based interventions improve weight status. Baseline variables predict only a small proportion of response; response at the first visit is a more meaningful tool to guide clinical decisions. PMID:19960890

  6. 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

  7. VO2 prediction and cardiorespiratory responses during underwater treadmill exercise.

    PubMed

    Greene, Nicholas P; Greene, Elizabeth S; Carbuhn, Aaron F; Green, John S; Crouse, Stephen F

    2011-06-01

    We compared cardiorespiratory responses to exercise on an underwater treadmill (UTM) and land treadmill (LTM) and derived an equation to estimate oxygen consumption (VO2) during UTM exercise. Fifty-five men and women completed one LTM and five UTM exercise sessions on separate days. The UTM sessions consisted of chest-deep immersion, with 0, 25, 50, 75, and 100% water-jet resistance. All session treadmill velocities increased every 3 min from 53.6 to 187.8 m x min(-1). Cardiorespiratory responses were similar between LTM and UTM when jet resistance for UTM was 50%. Using multiple regression analysis, weight-relative VO2 could be estimated as: VO2 (mLO2 c kg(-1) x min(-1)) = 0.19248 x height (cm) + 0.17422 x jet resistance (% max) + 0.14092 x velocity (m x min(-1)) -0.12794 x weight (kg)-27.82849, R2 = .82. Our data indicate that similar LTM and UTM cardiorespiratory responses are achievable, and we provide a reasonable estimate of UTM VO2.

  8. 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

  9. Can subject-specific single-fibre electrically evoked auditory brainstem response data be predicted from a model?

    PubMed

    Malherbe, Tiaan K; Hanekom, Tania; Hanekom, Johan J

    2013-07-01

    This article investigates whether prediction of subject-specific physiological data is viable through an individualised computational model of a cochlear implant. Subject-specific predictions could be particularly useful to assess and quantify the peripheral factors that cause inter-subject variations in perception. The results of such model predictions could potentially be translated to clinical application through optimisation of mapping parameters for individual users, since parameters that affect perception would be reflected in the model structure and parameters. A method to create a subject-specific computational model of a guinea pig with a cochlear implant is presented. The objectives of the study are to develop a method to construct subject-specific models considering translation of the method to in vivo human models and to assess the effectiveness of subject-specific models to predict peripheral neural excitation on subject level. Neural excitation patterns predicted by the model are compared with single-fibre electrically evoked auditory brainstem responses obtained from the inferior colliculus in the same animal. Results indicate that the model can predict threshold frequency location, spatial spread of bipolar and tripolar stimulation and electrode thresholds relative to one another where electrodes are located in different cochlear structures. Absolute thresholds and spatial spread using monopolar stimulation are not predicted accurately. Improvements to the model should address this.

  10. International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol

    PubMed Central

    2011-01-01

    Background Clinically useful treatment moderators of Major Depressive Disorder (MDD) have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators. Methods/Design The International Study to Predict Optimized Treatment - in Depression (iSPOT-D) is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65) from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls). Study-eligible patients are antidepressant medication (ADM) naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary) and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary). Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm. Discussion First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide. Trial registration International Study to Predict Optimised Treatment - in Depression (iSPOT-D) ClinicalTrials.gov Identifier: NCT00693849 URL: http

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. Clinical response to chemotherapy in oesophageal adenocarcinoma patients is linked to defects in mitochondria.

    PubMed

    Aichler, Michaela; Elsner, Mareike; Ludyga, Natalie; Feuchtinger, Annette; Zangen, Verena; Maier, Stefan K; Balluff, Benjamin; Schöne, Cédrik; Hierber, Ludwig; Braselmann, Herbert; Meding, Stephan; Rauser, Sandra; Zischka, Hans; Aubele, Michaela; Schmitt, Manfred; Feith, Marcus; Hauck, Stefanie M; Ueffing, Marius; Langer, Rupert; Kuster, Bernhard; Zitzelsberger, Horst; Höfler, Heinz; Walch, Axel K

    2013-08-01

    Chemotherapeutic drugs kill cancer cells, but it is unclear why this happens in responding patients but not in non-responders. Proteomic profiles of patients with oesophageal adenocarcinoma may be helpful in predicting response and selecting more effective treatment strategies. In this study, pretherapeutic oesophageal adenocarcinoma biopsies were analysed for proteomic changes associated with response to chemotherapy by MALDI imaging mass spectrometry. Resulting candidate proteins were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and investigated for functional relevance in vitro. Clinical impact was validated in pretherapeutic biopsies from an independent patient cohort. Studies on the incidence of these defects in other solid tumours were included. We discovered that clinical response to cisplatin correlated with pre-existing defects in the mitochondrial respiratory chain complexes of cancer cells, caused by loss of specific cytochrome c oxidase (COX) subunits. Knockdown of a COX protein altered chemosensitivity in vitro, increasing the propensity of cancer cells to undergo cell death following cisplatin treatment. In an independent validation, patients with reduced COX protein expression prior to treatment exhibited favourable clinical outcomes to chemotherapy, whereas tumours with unchanged COX expression were chemoresistant. In conclusion, previously undiscovered pre-existing defects in mitochondrial respiratory complexes cause cancer cells to become chemosensitive: mitochondrial defects lower the cells' threshold for undergoing cell death in response to cisplatin. By contrast, cancer cells with intact mitochondrial respiratory complexes are chemoresistant and have a high threshold for cisplatin-induced cell death. This connection between mitochondrial respiration and chemosensitivity is relevant to anticancer therapeutics that target the mitochondrial electron transport chain.

  3. 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

  4. Anger responses to psychosocial stress predict heart rate and cortisol stress responses in men but not women.

    PubMed

    Lupis, Sarah B; Lerman, Michelle; Wolf, Jutta M

    2014-11-01

    While previous research has suggested that anger and fear responses to stress are linked to distinct sympathetic nervous system (SNS) stress responses, little is known about how these emotions predict hypothalamus-pituitary-adrenal (HPA) axis reactivity. Further, earlier research primarily relied on retrospective self-report of emotion. The current study aimed at addressing both issues in male and female individuals by assessing the role of anger and fear in predicting heart rate and cortisol stress responses using both self-report and facial coding analysis to assess emotion responses. We exposed 32 healthy students (18 female; 19.6±1.7 yr) to an acute psychosocial stress paradigm (TSST) and measured heart rate and salivary cortisol levels throughout the protocol. Anger and fear before and after stress exposure was assessed by self-report, and video recordings of the TSST were assessed by a certified facial coder to determine emotion expression (FACS). Self-reported emotions and emotion expressions did not correlate (all p>.23). Increases in self-reported fear predicted blunted cortisol responses in men (β=0.41, p=.04). Also for men, longer durations of anger expression predicted exaggerated cortisol responses (β=0.67 p=.004), and more anger incidences predicted exaggerated cortisol and heart rate responses (β=0.51, p=.033; β=0.46, p=.066, resp.). Anger and fear did not predict SNS or HPA activity for females (all p>.23). The current differential self-report and facial coding findings support the use of multiple modes of emotion assessment. Particularly, FACS but not self-report revealed a robust anger-stress association that could have important downstream health effects for men. For women, future research may clarify the role of other emotions, such as self-conscious expressions of shame, for physiological stress responses. A better understanding of the emotion-stress link may contribute to behavioral interventions targeting health-promoting ways of

  5. Exposure and Response Prevention Process Predicts Treatment Outcome in Youth with OCD

    PubMed Central

    Kircanski, Katharina; Peris, Tara S.

    2014-01-01

    Recent research on the treatment of adults with anxiety disorders suggests that aspects of the in-session exposure therapy process are relevant to clinical outcomes. However, few comprehensive studies have been conducted with children and adolescents. In the present study, 35 youth diagnosed with primary obsessive-compulsive disorder (OCD; M age=12.9 years, 49% male, 63% Caucasian) completed 12 sessions of exposure and response prevention (ERP) in one of two treatment conditions as part of a pilot randomized controlled testing of a family focused intervention for OCD. Key exposure process variables, including youth self-reported distress during ERP and the quantity and quality of ERP completed, were computed. These variables were examined as predictors of treatment outcomes assessed at mid-treatment, post-treatment, and three-month follow-up, partialing treatment condition. In general, greater variability of distress during ERP and completing a greater proportion of combined exposures (i.e., exposures targeting more than one OC symptom at once) were predictive of better outcomes. Conversely, greater distress at the end of treatment was generally predictive of poorer outcomes. Finally, several variables, including within- and between-session decreases in distress during ERP, were not consistently predictive of outcomes. Findings signal potentially important facets of exposure for youth with OCD and have implications for treatment. A number of results also parallel recent findings in the adult literature, suggesting that there may be some continuity in exposure processes from child to adult development. Future work should examine additional measures of exposure process, such as psychophysiological arousal during exposure, in youth. PMID:25052626

  6. Diagnostic agreement predicts treatment process and outcomes in youth mental health clinics.

    PubMed

    Jensen-Doss, Amanda; Weisz, John R

    2008-10-01

    Several studies have documented low rates of agreement between clinician- and researcher-generated diagnoses. However, little is known about whether this lack of agreement has implications for the processes and outcomes of subsequent treatment. To study this possibility, the authors used diagnostic agreement to predict therapy engagement and outcomes for 197 youths treated in 5 community mental health clinics. Diagnostic agreement predicted better therapy engagement, with the agree group having fewer therapy no-shows and cancellations and a decreased likelihood of therapy dropout. Additionally, support for a link between agreement and treatment outcomes was found, as the agree group obtained larger reductions in parent-reported internalizing problems during treatment. These findings suggest that diagnostic accuracy may be an important precursor to successful treatment and highlight the importance of future research to find ways to incorporate standardized diagnostic procedures into clinical care settings. PMID:18837589

  7. Real-time prediction of clinical trial enrollment and event counts: A review.

    PubMed

    Heitjan, Daniel F; Ge, Zhiyun; Ying, Gui-Shuang

    2015-11-01

    Clinical trial planning involves the specification of a projected duration of enrollment and follow-up needed to achieve the targeted study power. If pre-trial estimates of enrollment and event rates are inaccurate, projections can be faulty, leading potentially to inadequate power or other mis-allocation of resources. Recent years have witnessed the development of methods that use the accumulating data from the trial itself to create improved predictions in real time. We review these methods, taking as a case study REMATCH, a trial that compared a left-ventricular assist device to optimal medical management in the treatment of end-stage heart failure. REMATCH provided the motivation and test bed for the first real-time clinical trial prediction model. Our review summarizes developments to date and points to unresolved issues and open research opportunities. PMID:26188165

  8. Clinical and molecular prognostic and predictive biomarkers in clear cell renal cell cancer.

    PubMed

    Czarnecka, Anna M; Kukwa, Wojciech; Kornakiewicz, Anna; Lian, Fei; Szczylik, Cezary

    2014-12-01

    The natural history of clear cell renal cell cancer is highly unpredictable with various progressors and with populations where small renal masses may be accompanied by metastatic disease. Currently, there is a critical need to determine patient risk and optimize treatment regimes. For these patients, molecular markers may offer significant information in terms of prognostic and predictive values, as well as determination of valid therapeutic targets. Until now, only a few of the many identified clear cell renal cell cancer biomarkers have been clinically validated in large cohorts. And only several biomarkers are integrated in predictive or prognostic models. Therefore, a large cohesive effort is required to advance the field of clear cell renal cell cancer prognostic biomarkers through systematic discovery, verification, validation and clinical implementation.

  9. Robust Microarray Meta-Analysis Identifies Differentially Expressed Genes for Clinical Prediction

    PubMed Central

    Phan, John H.; Young, Andrew N.; Wang, May D.

    2012-01-01

    Combining multiple microarray datasets increases sample size and leads to improved reproducibility in identification of informative genes and subsequent clinical prediction. Although microarrays have increased the rate of genomic data collection, sample size is still a major issue when identifying informative genetic biomarkers. Because of this, feature selection methods often suffer from false discoveries, resulting in poorly performing predictive models. We develop a simple meta-analysis-based feature selection method that captures the knowledge in each individual dataset and combines the results using a simple rank average. In a comprehensive study that measures robustness in terms of clinical application (i.e., breast, renal, and pancreatic cancer), microarray platform heterogeneity, and classifier (i.e., logistic regression, diagonal LDA, and linear SVM), we compare the rank average meta-analysis method to five other meta-analysis methods. Results indicate that rank average meta-analysis consistently performs well compared to five other meta-analysis methods. PMID:23365541

  10. 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

  11. 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.

  12. Response variability in rapid automatized naming predicts reading comprehension.

    PubMed

    Li, James J; Cutting, Laurie E; Ryan, Matthew; Zilioli, Monica; Denckla, Martha B; Mahone, E Mark

    2009-10-01

    A total of 37 children ages 8 to 14 years, screened for word-reading difficulties (23 with attention-deficit/hyperactivity disorder, ADHD; 14 controls) completed oral reading and rapid automatized naming (RAN) tests. RAN trials were segmented into pause and articulation time and intraindividual variability. There were no group differences on reading or RAN variables. Color- and letter-naming pause times and number-naming articulation time were significant predictors of reading fluency. In contrast, number and letter pause variability were predictors of comprehension. Results support analysis of subcomponents of RAN and add to literature emphasizing intraindividual variability as a marker for response preparation, which has relevance to reading comprehension.

  13. 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

  14. A genomic and clinical prognostic index for hepatitis C-related early-stage cirrhosis that predicts clinical deterioration

    PubMed Central

    King, Lindsay Y.; Canasto-Chibuque, Claudia; Johnson, Kara B.; Yip, Shun; Chen, Xintong; Kojima, Kensuke; Deshmukh, Manjeet; Venkatesh, Anu; Tan, Poh Seng; Sun, Xiaochen; Villanueva, Augusto; Sangiovanni, Angelo; Nair, Venugopalan; Mahajan, Milind; Kobayashi, Masahiro; Kumada, Hiromitsu; Iavarone, Massimo; Colombo, Massimo; Fiel, Maria Isabel; Friedman, Scott L.; Llovet, Josep M.; Chung, Raymond T.; Hoshida, Yujin

    2014-01-01

    Objective The number of patients with hepatitis C virus (HCV)-related cirrhosis is increasing, leading to a rising risk of complications and death. Prognostic stratification in patients with early-stage cirrhosis is still challenging. We aimed to develop and validate a clinically useful prognostic index based on genomic and clinical variables to identify patients at high risk of disease progression. Design We developed a prognostic index, comprised of a 186-gene signature validated in our previous genome-wide profiling study, bilirubin (>1mg/dL), and platelet count (<100,000/mm3), in an Italian HCV cirrhosis cohort (training cohort, n=216, median follow-up 10 years). The gene signature test was implemented utilizing a digital transcript counting (nCounter) assay specifically developed for clinical use, and the prognostic index was evaluated using archived specimens from an independent cohort of HCV-related cirrhosis in the U.S. (validation cohort, n=145, median follow-up 8 years). Results In the training cohort, the prognostic index was associated with hepatic decompensation (HR=2.71, p=0.003), overall death (HR=6.00, p<0.001), hepatocellular carcinoma (HR=3.31, p=0.001), and progression of Child-Turcotte-Pugh class (HR=6.70, p<0.001). The patients in the validation cohort were stratified into high (16%), intermediate (42%), or low (42%) risk group by the prognostic index. The high-risk group had a significantly increased risk of hepatic decompensation (HR=7.36, p<0.001), overall death (HR=3.57, p=0.002), liver-related death (HR=6.49, p<0.001), and all liver-related adverse events (HR=4.98, p<0.001). Conclusion A genomic and clinical prognostic index readily available for clinical use was successfully validated, warranting further clinical evaluation for prognostic prediction, and clinical trial stratification and enrichment for preventive interventions. PMID:25143343

  15. 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

  16. 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.

  17. 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.

  18. Predicting evolutionary responses to climate change in the sea.

    PubMed

    Munday, Philip L; Warner, Robert R; Monro, Keyne; Pandolfi, John M; Marshall, Dustin J

    2013-12-01

    An increasing number of short-term experimental studies show significant effects of projected ocean warming and ocean acidification on the performance on marine organisms. Yet, it remains unclear if we can reliably predict the impact of climate change on marine populations and ecosystems, because we lack sufficient understanding of the capacity for marine organisms to adapt to rapid climate change. In this review, we emphasise why an evolutionary perspective is crucial to understanding climate change impacts in the sea and examine the approaches that may be useful for addressing this challenge. We first consider what the geological record and present-day analogues of future climate conditions can tell us about the potential for adaptation to climate change. We also examine evidence that phenotypic plasticity may assist marine species to persist in a rapidly changing climate. We then outline the various experimental approaches that can be used to estimate evolutionary potential, focusing on molecular tools, quantitative genetics, and experimental evolution, and we describe the benefits of combining different approaches to gain a deeper understanding of evolutionary potential. Our goal is to provide a platform for future research addressing the evolutionary potential for marine organisms to cope with climate change.

  19. Predicting evolutionary responses to climate change in the sea.

    PubMed

    Munday, Philip L; Warner, Robert R; Monro, Keyne; Pandolfi, John M; Marshall, Dustin J

    2013-12-01

    An increasing number of short-term experimental studies show significant effects of projected ocean warming and ocean acidification on the performance on marine organisms. Yet, it remains unclear if we can reliably predict the impact of climate change on marine populations and ecosystems, because we lack sufficient understanding of the capacity for marine organisms to adapt to rapid climate change. In this review, we emphasise why an evolutionary perspective is crucial to understanding climate change impacts in the sea and examine the approaches that may be useful for addressing this challenge. We first consider what the geological record and present-day analogues of future climate conditions can tell us about the potential for adaptation to climate change. We also examine evidence that phenotypic plasticity may assist marine species to persist in a rapidly changing climate. We then outline the various experimental approaches that can be used to estimate evolutionary potential, focusing on molecular tools, quantitative genetics, and experimental evolution, and we describe the benefits of combining different approaches to gain a deeper understanding of evolutionary potential. Our goal is to provide a platform for future research addressing the evolutionary potential for marine organisms to cope with climate change. PMID:24119205

  20. Genomic risk prediction of complex human disease and its clinical application.

    PubMed

    Abraham, Gad; Inouye, Michael

    2015-08-01

    Recent advances in genome-wide association studies have stimulated interest in the genomic prediction of disease risk, potentially enabling individual-level risk estimates for early intervention and improved diagnostic procedures. Here, we review recent findings and approaches to genomic prediction model construction and performance, then contrast the potential benefits of such models in two complex human diseases, aiding diagnosis in celiac disease and prospective risk prediction for cardiovascular disease. Early indications are that optimal application of genomic risk scores will differ substantially for each disease depending on underlying genetic architecture as well as current clinical and public health practice. As costs decline, genomic profiles become common, and popular understanding of risk and its communication improves, genomic risk will become increasingly useful for the individual and the clinician.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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

  6. Predicting the Response of Electricity Load to Climate Change

    SciTech Connect

    Sullivan, Patrick; Colman, Jesse; Kalendra, Eric

    2015-07-28

    Our purpose is to develop a methodology to quantify the impact of climate change on electric loads in the United States. We perform simple linear regression, assisted by geospatial smoothing, on paired temperature and load time-series to estimate the heating- and coolinginduced sensitivity to temperature across 300 transmission zones and 16 seasonal and diurnal time periods. The estimated load sensitivities can be coupled with climate scenarios to quantify the potential impact of climate change on load, with a primary application being long-term electricity scenarios. The method allows regional and seasonal differences in climate and load response to be reflected in the electricity scenarios. While the immediate product of this analysis was designed to mesh with the spatial and temporal resolution of a specific electricity model to enable climate change scenarios and analysis with that model, we also propose that the process could be applied for other models and purposes.

  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. 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.

  9. Predictive factors of a successful testicular biopsy and subsequent clinical pregnancy.

    PubMed

    Botelho, F; Figueiredo, L; Leite, R; Carvalho, A; Tomada, N; Vendeira, P

    2012-08-01

    Forecast of success with testicular sperm extraction and intracytoplasmic sperm injection (ICSI) remains unknown, as predictive factors have rarely been studied. We evaluated the association among possible predictive factors and a successful biopsy and clinical pregnancy. A consecutive sample of men submitted to a testicular open biopsy in S. João Hospital was used. Patient's age, medical history, testicular volume, spermogram, genetic testing, endocrinologic results, biopsy results and clinical pregnancy information were collected. From the 113 men included, it was possible to retrieve spermatozoa in 79.6% of the cases, which resulted in 58 fertilisations and 22 clinical pregnancies. Retrieving viable spermatozoa on biopsy was associated with the identification of spermatozoa in the spermogram (100.0% versus 74.4%; P = 0.010), diseases causing obstructive infertility (100.0% versus 79.2%; P = 0.036) and no genetic causes detected (82.4% versus 54.5%; P = 0.030). Successful clinical pregnancy was only associated with lower female partner age (31.7 versus 36.0 year; P = 0.001) but not the quality of the spermatozoa or the time until the reproduction cycle. Identification of spermatozoa in the spermogram, diseases causing obstructive infertility and lack of genetic causes for infertility were associated with higher probability of viable spermatozoa retrieval but the female partner age remained the principal determinant of a successful pregnancy.

  10. Predicting Emotional Responses to Horror Films from Cue-Specific Affect.

    ERIC Educational Resources Information Center

    Neuendorf, Kimberly A.; Sparks, Glenn G.

    1988-01-01

    Assesses individuals' fear and enjoyment reactions to horror films, applying theories of cognition and affect that predict emotional responses to a stimulus on the basis of prior affect toward specific cues included in that stimulus. (MM)

  11. MATHEMATICAL MODEL OF STERIODOGENESIS TO PREDICT DYNAMIC RESPONSE TO ENDOCRINE DISRUPTORS

    EPA Science Inventory

    WE ARE DEVELOPING A MECHANISTIC MATHEMATICAL MODEL OF THE INTRATESTICULAR AND INTRAOVARIAN METABOLIC NETWORK THAT MEDIATES STEROID SYNTHESIS, AND THE KINETICS FOR ENZYME INHIBITION BY EDCs TO PREDICT THE TIME AND DOSE-RESPONSE.

  12. Mysid Population Responses to Resource Limitation Differ from those Predicted by Cohort Studies

    EPA Science Inventory

    Effects of anthropogenic stressors on animal populations are often evaluated by assembling vital rate responses from isolated cohort studies into a single demographic model. However, models constructed from cohort studies are difficult to translate into ecological predictions be...

  13. A noise level prediction method based on electro-mechanical frequency response function for capacitors.

    PubMed

    Zhu, Lingyu; Ji, Shengchang; Shen, Qi; Liu, Yuan; Li, Jinyu; Liu, Hao

    2013-01-01

    The capacitors in high-voltage direct-current (HVDC) converter stations radiate a lot of audible noise which can reach higher than 100 dB. The existing noise level prediction methods are not satisfying enough. In this paper, a new noise level prediction method is proposed based on a frequency response function considering both electrical and mechanical characteristics of capacitors. The electro-mechanical frequency response function (EMFRF) is defined as the frequency domain quotient of the vibration response and the squared capacitor voltage, and it is obtained from impulse current experiment. Under given excitations, the vibration response of the capacitor tank is the product of EMFRF and the square of the given capacitor voltage in frequency domain, and the radiated audible noise is calculated by structure acoustic coupling formulas. The noise level under the same excitations is also measured in laboratory, and the results are compared with the prediction. The comparison proves that the noise prediction method is effective.

  14. [OsteoLaus: prediction of osteoporotic fractures by clinical risk factors and DXA, IVA and TBS].

    PubMed

    Lamy, O; Metzger, M; Krieg, M-A; Aubry-Rozier, B; Stoll, D; Hans, D

    2011-11-01

    OsteoLaus is a cohort of 1400 women 50 to 80 years living in Lausanne, Switzerland. Clinical risk factors for osteoporosis, bone ultrasound of the heel, lumbar spine and hip bone mineral density (BMD), assessment of vertebral fracture by DXA, and microarchitecture evaluation by TBS (Trabecular Bone Score) will be recorded. TBS is a new parameter obtained after a re-analysis of a DXA exam. TBS is correlated with parameters of microarchitecture. His reproducibility is good. TBS give an added diagnostic value to BMD, and predict osteoporotic fracture (partially) independently to BMD. The position of TBS in clinical routine in complement to BMD and clinical risk factors will be evaluated in the OsteoLaus cohort.

  15. 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.

  16. Effect and clinical prediction of worsening renal function in acute decompensated heart failure.

    PubMed

    Breidthardt, Tobias; Socrates, Thenral; Noveanu, Markus; Klima, Theresia; Heinisch, Corinna; Reichlin, Tobias; Potocki, Mihael; Nowak, Albina; Tschung, Christopher; Arenja, Nisha; Bingisser, Roland; Mueller, Christian

    2011-03-01

    We aimed to establish the prevalence and effect of worsening renal function (WRF) on survival among patients with acute decompensated heart failure. Furthermore, we sought to establish a risk score for the prediction of WRF and externally validate the previously established Forman risk score. A total of 657 consecutive patients with acute decompensated heart failure presenting to the emergency department and undergoing serial creatinine measurements were enrolled. The potential of the clinical parameters at admission to predict WRF was assessed as the primary end point. The secondary end point was all-cause mortality at 360 days. Of the 657 patients, 136 (21%) developed WRF, and 220 patients had died during the first year. WRF was more common in the nonsurvivors (30% vs 41%, p = 0.03). Multivariate regression analysis found WRF to independently predict mortality (hazard ratio 1.92, p <0.01). In a single parameter model, previously diagnosed chronic kidney disease was the only independent predictor of WRF and achieved an area under the receiver operating characteristic curve of 0.60. After the inclusion of the blood gas analysis parameters into the model history of chronic kidney disease (hazard ratio 2.13, p = 0.03), outpatient diuretics (hazard ratio 5.75, p <0.01), and bicarbonate (hazard ratio 0.91, p <0.01) were all predictive of WRF. A risk score was developed using these predictors. On receiver operating characteristic curve analysis, the Forman and Basel prediction rules achieved an area under the curve of 0.65 and 0.71, respectively. In conclusion, WRF was common in patients with acute decompensated heart failure and was linked to significantly worse outcomes. However, the clinical parameters failed to adequately predict its occurrence, making a tailored therapy approach impossible.

  17. 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

  18. Predicting subtle behavioral responses of invertebrates to soil contaminants

    SciTech Connect

    Donkin, S.G.

    1995-12-31

    At concentration levels well below those which cause death and injury to soil invertebrates, a toxic chemical plume may yet effectively damage a soil ecosystem by triggering avoidance behavior among sensitive invertebrates as they move along the concentration gradient. The result may be a soil ecosystem lacking the benefits of effective nutrient cycling and mineralization which a thriving invertebrate population provides. While determining actual detection limits of invertebrates for chemical gradients in soils is experimentally difficult, theoretical calculations have suggested that such limits may be extremely low, and hence many organisms may sense and avoid concentrations of chemicals far below levels commonly considered acceptable. The minimum gradient (G) that can be detected by a receptor depends on the receptor radius (R), the chemical concentration (C), the diffusion constant of the chemical (D), the velocity of the organism (v), and the time over which the receptor integrates the chemical signal (t). In addition, the characteristics of that gradient are determined by interactions between the chemical and the soil particles (sorption/desorption), and advection through the pore spaces. The example of lead (Pb), a neurotoxic metal with demonstrated behavioral effects on the free-living nematode Caenorhabditis elegans, is used to model a chemical migrating through a soil. Based on experimentally determined Pb concentrations which elicited avoidance behavior in nematodes, and sorption characteristics of defined Pb-soil systems, the minimum detectable gradient (G) produced by a solubilized Pb plume in several soils was modeled. The results predict maximum allowable Pb levels in a soil if a healthy invertebrate community is desired, and suggest areas for further research into the subtle behavioral effects of environmental toxicants ore sensitive invertebrates.

  19. Dopamine reward prediction-error signalling: a two-component response.

    PubMed

    Schultz, Wolfram

    2016-03-01

    Environmental stimuli and objects, including rewards, are often processed sequentially in the brain. Recent work suggests that the phasic dopamine reward prediction-error response follows a similar sequential pattern. An initial brief, unselective and highly sensitive increase in activity unspecifically detects a wide range of environmental stimuli, then quickly evolves into the main response component, which reflects subjective reward value and utility. This temporal evolution allows the dopamine reward prediction-error signal to optimally combine speed and accuracy. PMID:26865020

  20. Serotonin modulates the effects of Pavlovian aversive predictions on response vigor.

    PubMed

    Crockett, Molly J; Clark, Luke; Apergis-Schoute, Annemieke M; Morein-Zamir, Sharon; Robbins, Trevor W

    2012-09-01

    Updated theoretical accounts of the role of serotonin (5-HT) in motivation propose that 5-HT operates at the intersection of aversion and inhibition, promoting withdrawal in the face of aversive predictions. However, the specific cognitive mechanisms through which 5-HT modulates withdrawal behavior remain poorly understood. Behavioral inhibition in response to punishments reflects at least two concurrent processes: instrumental aversive predictions linking stimuli, responses, and punishments, and Pavlovian aversive predictions linking stimuli and punishments irrespective of response. In the current study, we examined to what extent 5-HT modulates the impact of instrumental vs Pavlovian aversive predictions on behavioral inhibition. We used acute tryptophan depletion to lower central 5-HT levels in healthy volunteers, and observed behavior in a novel task designed to measure the influence of Pavlovian and instrumental aversive predictions on choice (response bias) and response vigor (response latencies). After placebo treatment, participants were biased against responding on the button that led to punishment, and they were slower to respond in a punished context, relative to a non-punished context. Specifically, participants slowed their responses in the presence of stimuli predictive of punishments. Tryptophan depletion removed the bias against responding on the punished button, and abolished slowing in the presence of punished stimuli, irrespective of response. We suggest that this set of results can be explained by a role for 5-HT in Pavlovian aversive predictions. These findings suggest additional specificity for the influence of 5-HT on aversively motivated behavioral inhibition and extend recent models of the role of 5-HT in aversive predictions. PMID:22643930

  1. Auditory Brainstem Response to Complex Sounds Predicts Self-Reported Speech-in-Noise Performance

    ERIC Educational Resources Information Center

    Anderson, Samira; Parbery-Clark, Alexandra; White-Schwoch, Travis; Kraus, Nina

    2013-01-01

    Purpose: To compare the ability of the auditory brainstem response to complex sounds (cABR) to predict subjective ratings of speech understanding in noise on the Speech, Spatial, and Qualities of Hearing Scale (SSQ; Gatehouse & Noble, 2004) relative to the predictive ability of the Quick Speech-in-Noise test (QuickSIN; Killion, Niquette,…

  2. The Utility of Situational Theory of Publics for Assessing Public Response to a Disaster Prediction.

    ERIC Educational Resources Information Center

    Major, Anne Marie

    1998-01-01

    Examines the utility of public-relations theory, specifically situational theory of publics, for assessing response to the New Madrid earthquake prediction. Finds that high personalized risk was associated with high constraint recognition regardless of belief in the prediction. Suggests development of more effective messages for communicating with…

  3. Predicting out-of-office blood pressure level using repeated measurements in the clinic: an observational cohort study

    PubMed Central

    Sheppard, James P.; Holder, Roger; Nichols, Linda; Bray, Emma; Hobbs, F.D. Richard; Mant, Jonathan; Little, Paul; Williams, Bryan; Greenfield, Sheila; McManus, Richard J.

    2014-01-01

    Objectives: Identification of people with lower (white-coat effect) or higher (masked effect) blood pressure at home compared to the clinic usually requires ambulatory or home monitoring. This study assessed whether changes in SBP with repeated measurement at a single clinic predict subsequent differences between clinic and home measurements. Methods: This study used an observational cohort design and included 220 individuals aged 35–84 years, receiving treatment for hypertension, but whose SBP was not controlled. The characteristics of change in SBP over six clinic readings were defined as the SBP drop, the slope and the quadratic coefficient using polynomial regression modelling. The predictive abilities of these characteristics for lower or higher home SBP readings were investigated with logistic regression and repeated operating characteristic analysis. Results: The single clinic SBP drop was predictive of the white-coat effect with a sensitivity of 90%, specificity of 50%, positive predictive value of 56% and negative predictive value of 88%. Predictive values for the masked effect and those of the slope and quadratic coefficient were slightly lower, but when the slope and quadratic variables were combined, the sensitivity, specificity, positive and negative predictive values for the masked effect were improved to 91, 48, 24 and 97%, respectively. Conclusion: Characteristics obtainable from multiple SBP measurements in a single clinic in patients with treated hypertension appear to reasonably predict those unlikely to have a large white-coat or masked effect, potentially allowing better targeting of out-of-office monitoring in routine clinical practice. PMID:25144295

  4. 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

  5. Patients with schizophrenia have a reduced neural response to both unpredictable and predictable primary reinforcers.

    PubMed

    Waltz, James A; Schweitzer, Julie B; Gold, James M; Kurup, Pradeep K; Ross, Thomas J; Salmeron, Betty Jo; Rose, Emma Jane; McClure, Samuel M; Stein, Elliot A

    2009-05-01

    One prevalent theory of learning states that dopamine neurons signal mismatches between expected and actual outcomes, called temporal difference errors (TDEs). Evidence indicates that dopamine system dysfunction is involved in negative symptoms of schizophrenia (SZ), including avolition and anhedonia. As such, we predicted that brain responses to TDEs in dopamine midbrain nuclei and target areas would be abnormal in SZ. A total of 18 clinically stable patients with chronic SZ and 18 controls participated in an fMRI study, which used a passive conditioning task. In the task, the delivery of a small amount of juice followed a light stimulus by exactly 6 s on approximately 75% of 78 total trials, and was further delayed by 4-7 s on the remaining trials. The delayed juice delivery was designed to elicit the two types of TDE signals, associated with the recognition that a reward was omitted at the expected time, and delivered at an unexpected time. Main effects of TDE valence and group differences in the positive-negative TDE contrast (unexpected juice deliveries-juice omissions) were assessed through whole-brain and regions of interest (ROI) analyses. Main effects of TDE valence were observed for the entire sample in the midbrain, left putamen, left cerebellum, and primary gustatory cortex, bilaterally. Whole-brain analyses revealed group differences in the positive-negative TDE contrast in the right putamen and left precentral gyrus, whereas ROI analyses revealed additional group differences in the midbrain, insula, and parietal operculum, on the right, the putamen and cerebellum, on the left, and the frontal operculum, bilaterally. Further, these group differences were generally driven by attenuated responses in patients to positive TDEs (unexpected juice deliveries), whereas responses to negative TDEs (unexpected juice omissions) were largely intact. Patients also showed reductions in responses to juice deliveries on standard trials, and more blunted reinforcer

  6. CXCL10 mRNA expression predicts response to neoadjuvant chemoradiotherapy in rectal cancer patients.

    PubMed

    Li, Cong; Wang, Zhimin; Liu, Fangqi; Zhu, Ji; Yang, Li; Cai, Guoxiang; Zhang, Zhen; Huang, Wei; Cai, Sanjun; Xu, Ye

    2014-10-01

    Chemoradiotherapy has been commonly used as neoadjuvant therapy for rectal cancer to allow for less aggressive surgical approaches and to improve quality of life. In cancer, it has been reported that CXCL10 has an anti-tumor function. However, the association between CXCL10 and chemoradiosensitivity has not been fully investigated. We performed this study to investigate the relationship between CXCL10 expression and chemoradiosensitivity in rectal cancer patients. Ninety-five patients with rectal cancer who received neoadjuvant chemoradiotherapy (NCRT) were included. Clinical parameters were compared with the outcome of NCRT and CXCL10 messenger RNA (mRNA) expression between the pathological complete response (pCR) group and non-pathological complete response (npCR) group. CXCL10 mRNA and protein expressions between groups were analyzed using the Student's t test and chi-square test. The mean mRNA level of CXCL10 in the pCR group was significantly higher than that in the npCR group (p = 0.010). In the pCR group, 73.7 % of the patients had high CXCL10 mRNA expression, and 61.4 % of the patients in the npCR group had low CXCL10 mRNA expression. Subjects with high CXCL10 mRNA expression demonstrated a higher sensitivity to NCRT (p = 0.011). The receiver operating characteristic curve showed that the diagnostic performance of CXCL10 mRNA expression had an area under the curve of 0.720 (95 % confidence interval, 0.573-0.867). There were no differences between the pCR and npCR groups in CXCL10 protein expression (p > 0.05). High CXCL10 mRNA expression is associated with a better tumor response to NCRT in rectal cancer patients and may predict the outcome of NCRT in this malignancy.

  7. Habitat specialization predicts genetic response to fragmentation in tropical birds.

    PubMed

    Khimoun, Aurélie; Eraud, Cyril; Ollivier, Anthony; Arnoux, Emilie; Rocheteau, Vincent; Bely, Marine; Lefol, Emilie; Delpuech, Martin; Carpentier, Marie-Laure; Leblond, Gilles; Levesque, Anthony; Charbonnel, Anaïs; Faivre, Bruno; Garnier, Stéphane

    2016-08-01

    Habitat fragmentation is one of the most severe threats to biodiversity as it may lead to changes in population genetic structure, with ultimate modifications of species evolutionary potential and local extinctions. Nonetheless, fragmentation does not equally affect all species and identifying which ecological traits are related to species sensitivity to habitat fragmentation could help prioritization of conservation efforts. Despite the theoretical link between species ecology and extinction proneness, comparative studies explicitly testing the hypothesis that particular ecological traits underlies species-specific population structure are rare. Here, we used a comparative approach on eight bird species, co-occurring across the same fragmented landscape. For each species, we quantified relative levels of forest specialization and genetic differentiation among populations. To test the link between forest specialization and susceptibility to forest fragmentation, we assessed species responses to fragmentation by comparing levels of genetic differentiation between continuous and fragmented forest landscapes. Our results revealed a significant and substantial population structure at a very small spatial scale for mobile organisms such as birds. More importantly, we found that specialist species are more affected by forest fragmentation than generalist ones. Finally, our results suggest that even a simple habitat specialization index can be a satisfying predictor of genetic and demographic consequences of habitat fragmentation, providing a reliable practical and quantitative tool for conservation biology. PMID:27314987

  8. The functional response predicts the effect of resource distribution on the optimal movement rate of consumers.

    PubMed

    Calcagno, Vincent; Grognard, Frédéric; Hamelin, Frédéric M; Wajnberg, Éric; Mailleret, Ludovic

    2014-12-01

    Understanding how often individuals should move when foraging over patchy habitats is a central question in ecology. By combining optimality and functional response theories, we show analytically how the optimal movement rate varies with the average resource level (enrichment) and resource distribution (patch heterogeneity). We find that the type of functional response predicts the effect of enrichment in homogeneous habitats: enrichment should decrease movement for decelerating functional responses, but increase movement for accelerating responses. An intermediate resource level thus maximises movement for type-III responses. Counterintuitively, greater movement costs favour an increase in movement. In heterogeneous habitats predictions further depend on how enrichment alters the variance of resource distribution. Greater patch variance always increases the optimal rate of movement, except for type-IV functional responses</