Gene-Expression Signature Predicts Postoperative Recurrence in Stage I Non-Small Cell Lung Cancer Patients

PubMed Central

Lu, Yan; Wang, Liang; Liu, Pengyuan; Yang, Ping; You, Ming

2012-01-01

About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset −142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = −0.83, P<1e-16) and this signature was validated in four independent datasets with AUC >85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients. PMID:22292069

External Validation of the HERNIAscore: An Observational Study.

PubMed

Cherla, Deepa V; Moses, Maya L; Mueck, Krislynn M; Hannon, Craig; Ko, Tien C; Kao, Lillian S; Liang, Mike K

2017-09-01

The HERNIAscore is a ventral incisional hernia (VIH) risk assessment tool that uses only preoperative variables and predictable intraoperative variables. The aim of this study was to validate and modify, if needed, the HERNIAscore in an external dataset. This was a retrospective observational study of all patients undergoing resection for gastrointestinal malignancy from 2011 through 2015 at a safety-net hospital. The primary end point was clinical postoperative VIH. Patients were stratified into low-risk, medium-risk, and high-risk groups based on HERNIAscore. A revised HERNIAscore was calculated with the addition of earlier abdominal operation as a categorical variable. Cox regression of incisional hernia with stratification by risk class was performed. Incidence rates of clinical VIH formation within each risk class were also calculated. Two hundred and forty-seven patents were enrolled. On Cox regression, in addition to the 3 variables of the HERNIAscore (BMI, COPD, and incision length), earlier abdominal operation was also predictive of VIH. The revised HERNIAscore demonstrated improved predictive accuracy for clinical VIH. Although the original HERNIAscore effectively stratified the risk of an incisional radiographic VIH developing, the revised HERNIAscore provided a statistically significant stratification for both clinical and radiographic VIHs in this patient cohort. We have externally validated and improved the HERNIAscore. The revised HERNIAscore uses BMI, incision length, COPD, and earlier abdominal operation to predict risk of postoperative incisional hernia. Future research should assess methods to prevent incisional hernias in moderate-to-high risk patients. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Simultaneous confidence bands for Cox regression from semiparametric random censorship.

PubMed

Mondal, Shoubhik; Subramanian, Sundarraman

2016-01-01

Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.

Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso.

PubMed

Kong, Shengchun; Nan, Bin

2014-01-01

We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses.

Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso

PubMed Central

Kong, Shengchun; Nan, Bin

2013-01-01

We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses. PMID:24516328

Prognostic value of circulating microRNAs in upper tract urinary carcinoma

PubMed Central

Ingelmo-Torres, Mercedes; Lozano, Juan José; Capitán, David; Alcaraz, Antonio; Mengual, Lourdes

2018-01-01

The identification of upper tract urinary carcinoma (UTUC) prognostic biomarkers is urgently needed to predict tumour progression. This study aimed to identify serum microRNAs (miRNAs) that may be useful as minimally invasive predictive biomarkers of tumour progression and survival in UTUC patients. To this end, 33 UTUC patients who underwent radical nephroureterectomy at the Hospital Clinic of Barcelona were prospectively included. Expression of 800 miRNAs was evaluated in serum samples from these patients using nCounter® miRNA Expression Assays. The study was divided into an initial discovery phase (n=12) and a validation phase (n=21). Cox regression analysis was used for survival analysis. The median follow-up (range) of the series was 42 months (9-100 months). In the discovery phase, 38 differentially expressed miRNAs were identified between progressing and non-progressing UTUC patients (p<0.05). Validation of these 38 miRNAs in an independent set of UTUC patients confirmed the differential expression in 18 of them (p<0.05). Cox Regression analysis showed miR-151b and pathological stage as significant prognostic factors for tumour progression (HR=0.33, p<0.001 and HR=2.62, p=0.006, respectively) and cancer specific survival (HR=0.25, p<0.001 and HR=3.98, p=0.003, respectively). Survival curves revealed that miR-151b is able to discriminate between two groups of UTUC patients with a highly significant different probability of tumour progression (p=0.006) and cancer specific survival (p=0.034). Although the data needs to be externally validated, miRNA analysis in serum appears to be a valuable prognostic tool in UTUC patients. Particularly, differential expression of miR-151b in serum may serve as a minimally invasive prognostic tool in UTUC. PMID:29682178

Prognostic value of circulating microRNAs in upper tract urinary carcinoma.

PubMed

Montalbo, Ruth; Izquierdo, Laura; Ingelmo-Torres, Mercedes; Lozano, Juan José; Capitán, David; Alcaraz, Antonio; Mengual, Lourdes

2018-03-30

The identification of upper tract urinary carcinoma (UTUC) prognostic biomarkers is urgently needed to predict tumour progression. This study aimed to identify serum microRNAs (miRNAs) that may be useful as minimally invasive predictive biomarkers of tumour progression and survival in UTUC patients. To this end, 33 UTUC patients who underwent radical nephroureterectomy at the Hospital Clinic of Barcelona were prospectively included. Expression of 800 miRNAs was evaluated in serum samples from these patients using nCounter® miRNA Expression Assays. The study was divided into an initial discovery phase (n=12) and a validation phase (n=21). Cox regression analysis was used for survival analysis. The median follow-up (range) of the series was 42 months (9-100 months). In the discovery phase, 38 differentially expressed miRNAs were identified between progressing and non-progressing UTUC patients (p<0.05). Validation of these 38 miRNAs in an independent set of UTUC patients confirmed the differential expression in 18 of them (p<0.05). Cox Regression analysis showed miR-151b and pathological stage as significant prognostic factors for tumour progression (HR=0.33, p<0.001 and HR=2.62, p=0.006, respectively) and cancer specific survival (HR=0.25, p<0.001 and HR=3.98, p=0.003, respectively). Survival curves revealed that miR-151b is able to discriminate between two groups of UTUC patients with a highly significant different probability of tumour progression (p=0.006) and cancer specific survival (p=0.034). Although the data needs to be externally validated, miRNA analysis in serum appears to be a valuable prognostic tool in UTUC patients. Particularly, differential expression of miR-151b in serum may serve as a minimally invasive prognostic tool in UTUC.

Practical application of cure mixture model for long-term censored survivor data from a withdrawal clinical trial of patients with major depressive disorder.

PubMed

Arano, Ichiro; Sugimoto, Tomoyuki; Hamasaki, Toshimitsu; Ohno, Yuko

2010-04-23

Survival analysis methods such as the Kaplan-Meier method, log-rank test, and Cox proportional hazards regression (Cox regression) are commonly used to analyze data from randomized withdrawal studies in patients with major depressive disorder. However, unfortunately, such common methods may be inappropriate when a long-term censored relapse-free time appears in data as the methods assume that if complete follow-up were possible for all individuals, each would eventually experience the event of interest. In this paper, to analyse data including such a long-term censored relapse-free time, we discuss a semi-parametric cure regression (Cox cure regression), which combines a logistic formulation for the probability of occurrence of an event with a Cox proportional hazards specification for the time of occurrence of the event. In specifying the treatment's effect on disease-free survival, we consider the fraction of long-term survivors and the risks associated with a relapse of the disease. In addition, we develop a tree-based method for the time to event data to identify groups of patients with differing prognoses (cure survival CART). Although analysis methods typically adapt the log-rank statistic for recursive partitioning procedures, the method applied here used a likelihood ratio (LR) test statistic from a fitting of cure survival regression assuming exponential and Weibull distributions for the latency time of relapse. The method is illustrated using data from a sertraline randomized withdrawal study in patients with major depressive disorder. We concluded that Cox cure regression reveals facts on who may be cured, and how the treatment and other factors effect on the cured incidence and on the relapse time of uncured patients, and that cure survival CART output provides easily understandable and interpretable information, useful both in identifying groups of patients with differing prognoses and in utilizing Cox cure regression models leading to meaningful interpretations.

Internal validation of the prognostic index for spine metastasis (PRISM) for stratifying survival in patients treated with spinal stereotactic radiosurgery.

PubMed

Jensen, Garrett; Tang, Chad; Hess, Kenneth R; Bishop, Andrew J; Pan, Hubert Y; Li, Jing; Yang, James N; Tannir, Nizar M; Amini, Behrang; Tatsui, Claudio; Rhines, Laurence; Brown, Paul D; Ghia, Amol J

2017-01-01

We sought to validate the Prognostic Index for Spinal Metastases (PRISM), a scoring system that stratifies patients into subgroups by overall survival.Methods and materials: The PRISM was previously created from multivariate Cox regression with patients enrolled in prospective single institution trials of stereotactic spine radiosurgery (SSRS) for spinal metastasis. We assess model calibration and discrimination within a validation cohort of patients treated off-trial with SSRS for metastatic disease at the same institution. The training and validation cohorts consisted of 205 and 249 patients respectively. Similar survival trends were shown in the 4 PRISM. Survival was significantly different between PRISM subgroups (P<0.0001). C-index for the validation cohort was 0.68 after stratification into subgroups. We internally validated the PRISM with patients treated off-protocol, demonstrating that it can distinguish subgroups by survival, which will be useful for individualizing treatment of spinal metastases and stratifying patients for clinical trials.

A comparison between the use of Cox regression and the use of partial least squares-Cox regression to predict the survival of kidney-transplant patients

NASA Astrophysics Data System (ADS)

Solimun

2017-05-01

The aim of this research is to model survival data from kidney-transplant patients using the partial least squares (PLS)-Cox regression, which can both meet and not meet the no-multicollinearity assumption. The secondary data were obtained from research entitled "Factors affecting the survival of kidney-transplant patients". The research subjects comprised 250 patients. The predictor variables consisted of: age (X1), sex (X2); two categories, prior hemodialysis duration (X3), diabetes (X4); two categories, prior transplantation number (X5), number of blood transfusions (X6), discrepancy score (X7), use of antilymphocyte globulin(ALG) (X8); two categories, while the response variable was patient survival time (in months). Partial least squares regression is a model that connects the predictor variables X and the response variable y and it initially aims to determine the relationship between them. Results of the above analyses suggest that the survival of kidney transplant recipients ranged from 0 to 55 months, with 62% of the patients surviving until they received treatment that lasted for 55 months. The PLS-Cox regression analysis results revealed that patients' age and the use of ALG significantly affected the survival time of patients. The factor of patients' age (X1) in the PLS-Cox regression model merely affected the failure probability by 1.201. This indicates that the probability of dying for elderly patients with a kidney transplant is 1.152 times higher than that for younger patients.

Development and validation of prognostic models in metastatic breast cancer: a GOCS study.

PubMed

Rabinovich, M; Vallejo, C; Bianco, A; Perez, J; Machiavelli, M; Leone, B; Romero, A; Rodriguez, R; Cuevas, M; Dansky, C

1992-01-01

The significance of several prognostic factors and the magnitude of their influence on response rate and survival were assessed by means of uni- and multivariate analyses in 362 patients with stage IV (UICC) breast carcinoma receiving combination chemotherapy as first systemic treatment over an 8-year period. Univariate analyses identified performance status and prior adjuvant radiotherapy as predictors of objective regression (OR), whereas the performance status, prior chemotherapy and radiotherapy (adjuvants), white blood cells count, SGOT and SGPT levels, and metastatic pattern were significantly correlated to survival. In multivariate analyses favorable characteristics associated to OR were prior adjuvant radiotherapy, no prior chemotherapy and postmenopausal status. Regarding survival, the performance status and visceral involvement were selected by the Cox model. The predictive accuracy of the logistic and the proportional hazards models was retrospectively tested in the training sample, and prospectively in a new population of 126 patients also receiving combined chemotherapy as first treatment for metastatic breast cancer. A certain overfitting to data in the training sample was observed with the regression model for response. However, the discriminative ability of the Cox model for survival was clearly confirmed.

Immortal time bias in observational studies of time-to-event outcomes.

PubMed

Jones, Mark; Fowler, Robert

2016-12-01

The purpose of the study is to show, through simulation and example, the magnitude and direction of immortal time bias when an inappropriate analysis is used. We compare 4 methods of analysis for observational studies of time-to-event outcomes: logistic regression, standard Cox model, landmark analysis, and time-dependent Cox model using an example data set of patients critically ill with influenza and a simulation study. For the example data set, logistic regression, standard Cox model, and landmark analysis all showed some evidence that treatment with oseltamivir provides protection from mortality in patients critically ill with influenza. However, when the time-dependent nature of treatment exposure is taken account of using a time-dependent Cox model, there is no longer evidence of a protective effect of treatment. The simulation study showed that, under various scenarios, the time-dependent Cox model consistently provides unbiased treatment effect estimates, whereas standard Cox model leads to bias in favor of treatment. Logistic regression and landmark analysis may also lead to bias. To minimize the risk of immortal time bias in observational studies of survival outcomes, we strongly suggest time-dependent exposures be included as time-dependent variables in hazard-based analyses. Copyright © 2016 Elsevier Inc. All rights reserved.

Adjusted variable plots for Cox's proportional hazards regression model.

PubMed

Hall, C B; Zeger, S L; Bandeen-Roche, K J

1996-01-01

Adjusted variable plots are useful in linear regression for outlier detection and for qualitative evaluation of the fit of a model. In this paper, we extend adjusted variable plots to Cox's proportional hazards model for possibly censored survival data. We propose three different plots: a risk level adjusted variable (RLAV) plot in which each observation in each risk set appears, a subject level adjusted variable (SLAV) plot in which each subject is represented by one point, and an event level adjusted variable (ELAV) plot in which the entire risk set at each failure event is represented by a single point. The latter two plots are derived from the RLAV by combining multiple points. In each point, the regression coefficient and standard error from a Cox proportional hazards regression is obtained by a simple linear regression through the origin fit to the coordinates of the pictured points. The plots are illustrated with a reanalysis of a dataset of 65 patients with multiple myeloma.

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

Quality Reporting of Multivariable Regression Models in Observational Studies: Review of a Representative Sample of Articles Published in Biomedical Journals.

PubMed

Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M

2016-05-01

Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature.

COX-2 and PPAR-γ confer cannabidiol-induced apoptosis of human lung cancer cells.

PubMed

Ramer, Robert; Heinemann, Katharina; Merkord, Jutta; Rohde, Helga; Salamon, Achim; Linnebacher, Michael; Hinz, Burkhard

2013-01-01

The antitumorigenic mechanism of cannabidiol is still controversial. This study investigates the role of COX-2 and PPAR-γ in cannabidiol's proapoptotic and tumor-regressive action. In lung cancer cell lines (A549, H460) and primary cells from a patient with lung cancer, cannabidiol elicited decreased viability associated with apoptosis. Apoptotic cell death by cannabidiol was suppressed by NS-398 (COX-2 inhibitor), GW9662 (PPAR-γ antagonist), and siRNA targeting COX-2 and PPAR-γ. Cannabidiol-induced apoptosis was paralleled by upregulation of COX-2 and PPAR-γ mRNA and protein expression with a maximum induction of COX-2 mRNA after 8 hours and continuous increases of PPAR-γ mRNA when compared with vehicle. In response to cannabidiol, tumor cell lines exhibited increased levels of COX-2-dependent prostaglandins (PG) among which PGD(2) and 15-deoxy-Δ(12,14)-PGJ(2) (15d-PGJ(2)) caused a translocation of PPAR-γ to the nucleus and induced a PPAR-γ-dependent apoptotic cell death. Moreover, in A549-xenografted nude mice, cannabidiol caused upregulation of COX-2 and PPAR-γ in tumor tissue and tumor regression that was reversible by GW9662. Together, our data show a novel proapoptotic mechanism of cannabidiol involving initial upregulation of COX-2 and PPAR-γ and a subsequent nuclear translocation of PPAR-γ by COX-2-dependent PGs.

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.

PubMed

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei

2016-02-01

Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.

Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

PubMed Central

Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei

2015-01-01

Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979

Development and validation of a prognostic nomogram for terminally ill cancer patients.

PubMed

Feliu, Jaime; Jiménez-Gordo, Ana María; Madero, Rosario; Rodríguez-Aizcorbe, José Ramón; Espinosa, Enrique; Castro, Javier; Acedo, Jesús Domingo; Martínez, Beatriz; Alonso-Babarro, Alberto; Molina, Raquel; Cámara, Juan Carlos; García-Paredes, María Luisa; González-Barón, Manuel

2011-11-02

Determining life expectancy in terminally ill cancer patients is a difficult task. We aimed to develop and validate a nomogram to predict the length of survival in patients with terminal disease. From February 1, 2003, to December 31, 2005, 406 consecutive terminally ill patients were entered into the study. We analyzed 38 features prognostic of life expectancy among terminally ill patients by multivariable Cox regression and identified the most accurate and parsimonious model by backward variable elimination according to the Akaike information criterion. Five clinical and laboratory variables were built into a nomogram to estimate the probability of patient survival at 15, 30, and 60 days. We validated and calibrated the nomogram with an external validation cohort of 474 patients who were treated from June 1, 2006, through December 31, 2007. The median overall survival was 29.1 days for the training set and 18.3 days for the validation set. Eastern Cooperative Oncology Group performance status, lactate dehydrogenase levels, lymphocyte levels, albumin levels, and time from initial diagnosis to diagnosis of terminal disease were retained in the multivariable Cox proportional hazards model as independent prognostic factors of survival and formed the basis of the nomogram. The nomogram had high predictive performance, with a bootstrapped corrected concordance index of 0.70, and it showed good calibration. External independent validation revealed 68% predictive accuracy. We developed a highly accurate tool that uses basic clinical and analytical information to predict the probability of survival at 15, 30, and 60 days in terminally ill cancer patients. This tool can help physicians making decisions on clinical care at the end of life.

Estimation of variance in Cox's regression model with shared gamma frailties.

PubMed

Andersen, P K; Klein, J P; Knudsen, K M; Tabanera y Palacios, R

1997-12-01

The Cox regression model with a shared frailty factor allows for unobserved heterogeneity or for statistical dependence between the observed survival times. Estimation in this model when the frailties are assumed to follow a gamma distribution is reviewed, and we address the problem of obtaining variance estimates for regression coefficients, frailty parameter, and cumulative baseline hazards using the observed nonparametric information matrix. A number of examples are given comparing this approach with fully parametric inference in models with piecewise constant baseline hazards.

Properties of added variable plots in Cox's regression model.

PubMed

Lindkvist, M

2000-03-01

The added variable plot is useful for examining the effect of a covariate in regression models. The plot provides information regarding the inclusion of a covariate, and is useful in identifying influential observations on the parameter estimates. Hall et al. (1996) proposed a plot for Cox's proportional hazards model derived by regarding the Cox model as a generalized linear model. This paper proves and discusses properties of this plot. These properties make the plot a valuable tool in model evaluation. Quantities considered include parameter estimates, residuals, leverage, case influence measures and correspondence to previously proposed residuals and diagnostics.

Application and validation of Cox regression models in a single-center series of double kidney transplantation.

PubMed

Santori, G; Fontana, I; Bertocchi, M; Gasloli, G; Magoni Rossi, A; Tagliamacco, A; Barocci, S; Nocera, A; Valente, U

2010-05-01

A useful approach to reduce the number of discarded marginal kidneys and to increase the nephron mass is double kidney transplantation (DKT). In this study, we retrospectively evaluated the potential predictors for patient and graft survival in a single-center series of 59 DKT procedures performed between April 21, 1999, and September 21, 2008. The kidney recipients of mean age 63.27 +/- 5.17 years included 16 women (27%) and 43 men (73%). The donors of mean age 69.54 +/- 7.48 years included 32 women (54%) and 27 men (46%). The mean posttransplant dialysis time was 2.37 +/- 3.61 days. The mean hospitalization was 20.12 +/- 13.65 days. Average serum creatinine (SCr) at discharge was 1.5 +/- 0.59 mg/dL. In view of the limited numbers of recipient deaths (n = 4) and graft losses (n = 8) that occurred in our series, the proportional hazards assumption for each Cox regression model with P < .05 was tested by using correlation coefficients between transformed survival times and scaled Schoenfeld residuals, and checked with smoothed plots of Schoenfeld residuals. For patient survival, the variables that reached statistical significance were donor SCr (P = .007), donor creatinine cleararance (P = .023), and recipient age (P = .047). Each significant model passed the Schoenfeld test. By entering these variables into a multivariate Cox model for patient survival, no further significance was observed. In the univariate Cox models performed for graft survival, statistical significance was noted for donor SCr (P = .027), SCr 3 months post-DKT (P = .043), and SCr 6 months post-DKT (P = .017). All significant univariate models for graft survival passed the Schoenfeld test. A final multivariate model retained SCr at 6 months (beta = 1.746, P = .042) and donor SCr (beta = .767, P = .090). In our analysis, SCr at 6 months seemed to emerge from both univariate and multivariate Cox models as a potential predictor of graft survival among DKT. Multicenter studies with larger recipient populations and more graft losses should be performed to confirm our findings. Copyright (c) 2010 Elsevier Inc. All rights reserved.

NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

PubMed

Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

2015-10-15

In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to systematically reveal multi-biomarker panel from genomic and clinical data. It can serve as a useful tool to identify prognostic biomarkers for survival analysis. NCC-AUC is available at http://doc.aporc.org/wiki/NCC-AUC. ywang@amss.ac.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Cox regression analysis with missing covariates via nonparametric multiple imputation.

PubMed

Hsu, Chiu-Hsieh; Yu, Mandi

2018-01-01

We consider the situation of estimating Cox regression in which some covariates are subject to missing, and there exists additional information (including observed event time, censoring indicator and fully observed covariates) which may be predictive of the missing covariates. We propose to use two working regression models: one for predicting the missing covariates and the other for predicting the missing probabilities. For each missing covariate observation, these two working models are used to define a nearest neighbor imputing set. This set is then used to non-parametrically impute covariate values for the missing observation. Upon the completion of imputation, Cox regression is performed on the multiply imputed datasets to estimate the regression coefficients. In a simulation study, we compare the nonparametric multiple imputation approach with the augmented inverse probability weighted (AIPW) method, which directly incorporates the two working models into estimation of Cox regression, and the predictive mean matching imputation (PMM) method. We show that all approaches can reduce bias due to non-ignorable missing mechanism. The proposed nonparametric imputation method is robust to mis-specification of either one of the two working models and robust to mis-specification of the link function of the two working models. In contrast, the PMM method is sensitive to misspecification of the covariates included in imputation. The AIPW method is sensitive to the selection probability. We apply the approaches to a breast cancer dataset from Surveillance, Epidemiology and End Results (SEER) Program.

Hierarchy of higher-level physical functions: a longitudinal investigation on a nationally representative population of community-dwelling middle-aged and elderly persons.

PubMed

Yeh, Chih-Jung; Wang, Ching-Yi; Tang, Pei-Fang; Lee, Meng-Chih; Lin, Hui-Sheng; Chen, Hui-Ya

2012-01-01

Understanding the hierarchy of higher-level physical functions to infer disability level (mild, moderate or severe) is essential for the precise targeting of preventive interventions and has been examined previously in a cross-sectional study. Based on longitudinal data, this study evaluated the hierarchy of higher-level physical functions. Data from a cohort of 2729 community-dwelling persons aged over 50 with no initial disability were drawn from the "Survey of Health and Living Status of the Elderly in Taiwan" from 1996 through 2007. The three-level hierarchy of eight chosen activities was examined by the median ages to disability onset with survival analyses and by Cox regressions, which examined the effects of sex and age on the development of this hierarchy. The progression of incident disability was as follows: mild level-running, carrying weight, and squatting; moderate level-climbing stairs, walking, and standing; and severe level-grasping and raising arms up. Women and older persons were at greater risk of developing more severe levels of disability. Another Cox regression with one index activity from each hierarchical level revealed similar results. The three-level hierarchy of higher-level physical functions has been validated longitudinally, suggesting rich research and clinical implications.

Smad3 mutant mice develop colon cancer with overexpression of COX-2

PubMed Central

Zhu, Yu-Ping; Liu, Zhuo; Fu, Zhi-Xuan; Li, De-Chuan

2017-01-01

Colon cancer is the second most common cause of cancer-associated mortality in human populations. The aim of the present study was to identify the role of cyclooxygenase-2 (COX-2) in Smad3 mutant mice, which are known to develop colon cancer. Homozygous Smad3 (−/−) mutant mice were generated from inbred and hybrid Smad3 mouse strains by intercrossing the appropriate heterozygotes. Immunohistochemistry with COX-2 antibody was performed throughout this experiment and the data was validated and cross-checked with reverse transcription-polymerase chain reaction (RT-PCR). Homozygous mutant Smad3 mice were generated and the overexpression pattern of COX-2 was identified by immunohistochemistry and validated with RT-PCR. The results of the present study demonstrated a link between the Smad3 mutant mice, colon cancer and COX-2. In addition, the overexpression pattern of COX-2 in Smad3 mutant mice that develop colon cancer was identified. PMID:28454287

Bootstrap investigation of the stability of a Cox regression model.

PubMed

Altman, D G; Andersen, P K

1989-07-01

We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.

Development and validation of a prognostic nomogram for colorectal cancer after radical resection based on individual patient data from three large-scale phase III trials

PubMed Central

Akiyoshi, Takashi; Maeda, Hiromichi; Kashiwabara, Kosuke; Kanda, Mitsuro; Mayanagi, Shuhei; Aoyama, Toru; Hamada, Chikuma; Sadahiro, Sotaro; Fukunaga, Yosuke; Ueno, Masashi; Sakamoto, Junichi; Saji, Shigetoyo; Yoshikawa, Takaki

2017-01-01

Background Few prediction models have so far been developed and assessed for the prognosis of patients who undergo curative resection for colorectal cancer (CRC). Materials and Methods We prepared a clinical dataset including 5,530 patients who participated in three major randomized controlled trials as a training dataset and 2,263 consecutive patients who were treated at a cancer-specialized hospital as a validation dataset. All subjects underwent radical resection for CRC which was histologically diagnosed to be adenocarcinoma. The main outcomes that were predicted were the overall survival (OS) and disease free survival (DFS). The identification of the variables in this nomogram was based on a Cox regression analysis and the model performance was evaluated by Harrell's c-index. The calibration plot and its slope were also studied. For the external validation assessment, risk group stratification was employed. Results The multivariate Cox model identified variables; sex, age, pathological T and N factor, tumor location, size, lymphnode dissection, postoperative complications and adjuvant chemotherapy. The c-index was 0.72 (95% confidence interval [CI] 0.66-0.77) for the OS and 0.74 (95% CI 0.69-0.78) for the DFS. The proposed stratification in the risk groups demonstrated a significant distinction between the Kaplan–Meier curves for OS and DFS in the external validation dataset. Conclusions We established a clinically reliable nomogram to predict the OS and DFS in patients with CRC using large scale and reliable independent patient data from phase III randomized controlled trials. The external validity was also confirmed on the practical dataset. PMID:29228760

Dynamic TIMI Risk Score for STEMI

PubMed Central

Amin, Sameer T.; Morrow, David A.; Braunwald, Eugene; Sloan, Sarah; Contant, Charles; Murphy, Sabina; Antman, Elliott M.

2013-01-01

Background Although there are multiple methods of risk stratification for ST‐elevation myocardial infarction (STEMI), this study presents a prospectively validated method for reclassification of patients based on in‐hospital events. A dynamic risk score provides an initial risk stratification and reassessment at discharge. Methods and Results The dynamic TIMI risk score for STEMI was derived in ExTRACT‐TIMI 25 and validated in TRITON‐TIMI 38. Baseline variables were from the original TIMI risk score for STEMI. New variables were major clinical events occurring during the index hospitalization. Each variable was tested individually in a univariate Cox proportional hazards regression. Variables with P<0.05 were incorporated into a full multivariable Cox model to assess the risk of death at 1 year. Each variable was assigned an integer value based on the odds ratio, and the final score was the sum of these values. The dynamic score included the development of in‐hospital MI, arrhythmia, major bleed, stroke, congestive heart failure, recurrent ischemia, and renal failure. The C‐statistic produced by the dynamic score in the derivation database was 0.76, with a net reclassification improvement (NRI) of 0.33 (P<0.0001) from the inclusion of dynamic events to the original TIMI risk score. In the validation database, the C‐statistic was 0.81, with a NRI of 0.35 (P=0.01). Conclusions This score is a prospectively derived, validated means of estimating 1‐year mortality of STEMI at hospital discharge and can serve as a clinically useful tool. By incorporating events during the index hospitalization, it can better define risk and help to guide treatment decisions. PMID:23525425

Dynamic TIMI risk score for STEMI.

PubMed

Amin, Sameer T; Morrow, David A; Braunwald, Eugene; Sloan, Sarah; Contant, Charles; Murphy, Sabina; Antman, Elliott M

2013-01-29

Although there are multiple methods of risk stratification for ST-elevation myocardial infarction (STEMI), this study presents a prospectively validated method for reclassification of patients based on in-hospital events. A dynamic risk score provides an initial risk stratification and reassessment at discharge. The dynamic TIMI risk score for STEMI was derived in ExTRACT-TIMI 25 and validated in TRITON-TIMI 38. Baseline variables were from the original TIMI risk score for STEMI. New variables were major clinical events occurring during the index hospitalization. Each variable was tested individually in a univariate Cox proportional hazards regression. Variables with P<0.05 were incorporated into a full multivariable Cox model to assess the risk of death at 1 year. Each variable was assigned an integer value based on the odds ratio, and the final score was the sum of these values. The dynamic score included the development of in-hospital MI, arrhythmia, major bleed, stroke, congestive heart failure, recurrent ischemia, and renal failure. The C-statistic produced by the dynamic score in the derivation database was 0.76, with a net reclassification improvement (NRI) of 0.33 (P<0.0001) from the inclusion of dynamic events to the original TIMI risk score. In the validation database, the C-statistic was 0.81, with a NRI of 0.35 (P=0.01). This score is a prospectively derived, validated means of estimating 1-year mortality of STEMI at hospital discharge and can serve as a clinically useful tool. By incorporating events during the index hospitalization, it can better define risk and help to guide treatment decisions.

A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

PubMed

Hong, Xia

2006-07-01

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

Survival analysis with error-prone time-varying covariates: a risk set calibration approach

PubMed Central

Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna

2010-01-01

Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928

A baseline-free procedure for transformation models under interval censorship.

PubMed

Gu, Ming Gao; Sun, Liuquan; Zuo, Guoxin

2005-12-01

An important property of Cox regression model is that the estimation of regression parameters using the partial likelihood procedure does not depend on its baseline survival function. We call such a procedure baseline-free. Using marginal likelihood, we show that an baseline-free procedure can be derived for a class of general transformation models under interval censoring framework. The baseline-free procedure results a simplified and stable computation algorithm for some complicated and important semiparametric models, such as frailty models and heteroscedastic hazard/rank regression models, where the estimation procedures so far available involve estimation of the infinite dimensional baseline function. A detailed computational algorithm using Markov Chain Monte Carlo stochastic approximation is presented. The proposed procedure is demonstrated through extensive simulation studies, showing the validity of asymptotic consistency and normality. We also illustrate the procedure with a real data set from a study of breast cancer. A heuristic argument showing that the score function is a mean zero martingale is provided.

Prognostic value of FDG PET/CT-based metabolic tumor volumes in metastatic triple negative breast cancer patients

PubMed Central

Marinelli, Brett; Espinet-Col, Carina; Ulaner, Gary A; McArthur, Heather L; Gonen, Mithat; Jochelson, Maxine; Weber, Wolfgang A

2016-01-01

FDG PET/CT-based measures of tumor burden show promise to predict survival in patients with metastatic breast cancer, but the patient populations studied so far are heterogeneous. The reports may have been confounded by the markedly different prognosis of the various subtypes of breast cancer. The purpose of this study is to evaluate the correlation between tumor burden on FDG PET/CT and overall survival (OS) in patients within a defined population: metastatic triple negative breast cancer (MTNBC). FDG PET/CT scans of 47 consecutive MTNBC patients (54±12 years-old) with no other known malignancies were analyzed. A total 393 lesions were identified, and maximum standardized uptake value (SUVmax), mean SUV, metabolic tumor volume (MTV), total lesion number (TLN) and total lesion glycolysis (TLG), were measured and correlated with patient survival by Mantel-Cox tests and Cox regression analysis. At a median follow-up time of 12.4 months, 41 patients died with a median OS of 12.1 months. Patients with MTV less than 51.5 ml lived nearly three times longer (22 vs 7.1 months) than those with a higher MTV (χ2=21.3, P<0.0001). In a multivariate Cox regression analysis only TLN and MTV were significantly correlated with survival. Those with an MTV burden in the 75th percentile versus the 25th percentile had a hazard ratio of 6.94 (p=0.001). In patients with MTNBC, MTV appears to be a strong prognostic factor. If validated in prospective studies, MTV may be a valuable tool for risk stratification of MTNBC patients in clinical trials and to guide patient management. PMID:27186439

BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER’S DISEASE*

PubMed Central

Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G

2015-01-01

The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer’s disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer’s Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM. PMID:26900412

Leigh syndrome associated with a novel mutation in the COX15 gene.

PubMed

Miryounesi, Mohammad; Fardaei, Majid; Tabei, Seyed Mohammadbagher; Ghafouri-Fard, Soudeh

2016-06-01

Leigh syndrome (LS) is a subacute necrotizing encephalomyelopathy with a diverse range of symptoms, such as psychomotor delay or regression, weakness, hypotonia, truncal ataxia, intention tremor as well as lactic acidosis in the blood, cerebrospinal fluid or urine. Both nuclear gene defects and mutations of the mitochondrial genome have been detected in these patients. Here we report a 7-year-old girl with hypotonia, tremor, developmental delay and psychomotor regression. However, serum lactate level as well as brain magnetic resonance imaging were normal. Mutational analysis has revealed a novel mutation in exon 4 of COX15 gene (c.415C>G) which results in p.Leu139Val. Previous studies have demonstrated that COX15 mutations are associated with typical LS as well as fatal infantile hypertrophic cardiomyopathy. Consequently, clinical manifestations of COX15 mutations may be significantly different in patients. Such information is of practical importance in genetic counseling.

Prognostic model for survival in patients with early stage cervical cancer.

PubMed

Biewenga, Petra; van der Velden, Jacobus; Mol, Ben Willem J; Stalpers, Lukas J A; Schilthuis, Marten S; van der Steeg, Jan Willem; Burger, Matthé P M; Buist, Marrije R

2011-02-15

In the management of early stage cervical cancer, knowledge about the prognosis is critical. Although many factors have an impact on survival, their relative importance remains controversial. This study aims to develop a prognostic model for survival in early stage cervical cancer patients and to reconsider grounds for adjuvant treatment. A multivariate Cox regression model was used to identify the prognostic weight of clinical and histological factors for disease-specific survival (DSS) in 710 consecutive patients who had surgery for early stage cervical cancer (FIGO [International Federation of Gynecology and Obstetrics] stage IA2-IIA). Prognostic scores were derived by converting the regression coefficients for each prognostic marker and used in a score chart. The discriminative capacity was expressed as the area under the curve (AUC) of the receiver operating characteristic. The 5-year DSS was 92%. Tumor diameter, histological type, lymph node metastasis, depth of stromal invasion, lymph vascular space invasion, and parametrial extension were independently associated with DSS and were included in a Cox regression model. This prognostic model, corrected for the 9% overfit shown by internal validation, showed a fair discriminative capacity (AUC, 0.73). The derived score chart predicting 5-year DSS showed a good discriminative capacity (AUC, 0.85). In patients with early stage cervical cancer, DSS can be predicted with a statistical model. Models, such as that presented here, should be used in clinical trials on the effects of adjuvant treatments in high-risk early cervical cancer patients, both to stratify and to include patients. Copyright © 2010 American Cancer Society.

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Multi-omics facilitated variable selection in Cox-regression model for cancer prognosis prediction.

PubMed

Liu, Cong; Wang, Xujun; Genchev, Georgi Z; Lu, Hui

2017-07-15

New developments in high-throughput genomic technologies have enabled the measurement of diverse types of omics biomarkers in a cost-efficient and clinically-feasible manner. Developing computational methods and tools for analysis and translation of such genomic data into clinically-relevant information is an ongoing and active area of investigation. For example, several studies have utilized an unsupervised learning framework to cluster patients by integrating omics data. Despite such recent advances, predicting cancer prognosis using integrated omics biomarkers remains a challenge. There is also a shortage of computational tools for predicting cancer prognosis by using supervised learning methods. The current standard approach is to fit a Cox regression model by concatenating the different types of omics data in a linear manner, while penalty could be added for feature selection. A more powerful approach, however, would be to incorporate data by considering relationships among omics datatypes. Here we developed two methods: a SKI-Cox method and a wLASSO-Cox method to incorporate the association among different types of omics data. Both methods fit the Cox proportional hazards model and predict a risk score based on mRNA expression profiles. SKI-Cox borrows the information generated by these additional types of omics data to guide variable selection, while wLASSO-Cox incorporates this information as a penalty factor during model fitting. We show that SKI-Cox and wLASSO-Cox models select more true variables than a LASSO-Cox model in simulation studies. We assess the performance of SKI-Cox and wLASSO-Cox using TCGA glioblastoma multiforme and lung adenocarcinoma data. In each case, mRNA expression, methylation, and copy number variation data are integrated to predict the overall survival time of cancer patients. Our methods achieve better performance in predicting patients' survival in glioblastoma and lung adenocarcinoma. Copyright © 2017. Published by Elsevier Inc.

Prognostic significance of hemoglobin level in patients with congestive heart failure and normal ejection fraction.

PubMed

Varadarajan, Padmini; Gandhi, Siddharth; Sharma, Sanjay; Umakanthan, Branavan; Pai, Ramdas G

2006-10-01

Previous studies have shown low hemoglobin (Hb) to have an adverse effect on survival in patients with congestive heart failure (CHF) and reduced left ventricular (LV) ejection fraction (EF); but its effect on survival in patients with CHF and normal EF is not known. This study sought to determine whether low Hb has an effect on survival in patients with both CHF and normal EF. Detailed chart reviews were performed by medical residents on 2,246 patients (48% with normal EF) with a discharge diagnosis of CHF in a large tertiary care hospital from 1990 to 1999. The CHF diagnosis was validated using the Framingham criteria. Mortality data were obtained from the National Death Index. Survival analysis was performed using Kaplan-Meier and Cox regression models. By Kaplan-Meier analysis, low Hb (< 12 gm/dl) compared with normal hemoglobin was associated with a lower 5-year survival in patients with CHF and both normal (38 vs. 50%, p = 0.0008) and reduced (35 vs. 48%, p = 0.0009) EF. Using the Cox regression model, low Hb was an independent predictor of mortality after adjusting for age, gender, renal dysfunction, diabetes mellitus, hypertension, and EF in both groups of patients. Low Hb has an independent adverse effect on survival in patients with CHF and both normal and reduced EF in both groups of patients.

A generalized multivariate regression model for modelling ocean wave heights

NASA Astrophysics Data System (ADS)

Wang, X. L.; Feng, Y.; Swail, V. R.

2012-04-01

In this study, a generalized multivariate linear regression model is developed to represent the relationship between 6-hourly ocean significant wave heights (Hs) and the corresponding 6-hourly mean sea level pressure (MSLP) fields. The model is calibrated using the ERA-Interim reanalysis of Hs and MSLP fields for 1981-2000, and is validated using the ERA-Interim reanalysis for 2001-2010 and ERA40 reanalysis of Hs and MSLP for 1958-2001. The performance of the fitted model is evaluated in terms of Pierce skill score, frequency bias index, and correlation skill score. Being not normally distributed, wave heights are subjected to a data adaptive Box-Cox transformation before being used in the model fitting. Also, since 6-hourly data are being modelled, lag-1 autocorrelation must be and is accounted for. The models with and without Box-Cox transformation, and with and without accounting for autocorrelation, are inter-compared in terms of their prediction skills. The fitted MSLP-Hs relationship is then used to reconstruct historical wave height climate from the 6-hourly MSLP fields taken from the Twentieth Century Reanalysis (20CR, Compo et al. 2011), and to project possible future wave height climates using CMIP5 model simulations of MSLP fields. The reconstructed and projected wave heights, both seasonal means and maxima, are subject to a trend analysis that allows for non-linear (polynomial) trends.

The Breslow estimator of the nonparametric baseline survivor function in Cox's regression model: some heuristics.

PubMed

Hanley, James A

2008-01-01

Most survival analysis textbooks explain how the hazard ratio parameters in Cox's life table regression model are estimated. Fewer explain how the components of the nonparametric baseline survivor function are derived. Those that do often relegate the explanation to an "advanced" section and merely present the components as algebraic or iterative solutions to estimating equations. None comment on the structure of these estimators. This note brings out a heuristic representation that may help to de-mystify the structure.

Use of Cox's Cure Model to Establish Clinical Determinants of Long-Term Disease-Free Survival in Neoadjuvant-Chemotherapy-Treated Breast Cancer Patients without Pathologic Complete Response.

PubMed

Asano, Junichi; Hirakawa, Akihiro; Hamada, Chikuma; Yonemori, Kan; Hirata, Taizo; Shimizu, Chikako; Tamura, Kenji; Fujiwara, Yasuhiro

2013-01-01

In prognostic studies for breast cancer patients treated with neoadjuvant chemotherapy (NAC), the ordinary Cox proportional-hazards (PH) model has been often used to identify prognostic factors for disease-free survival (DFS). This model assumes that all patients eventually experience relapse or death. However, a subset of NAC-treated breast cancer patients never experience these events during long-term follow-up (>10 years) and may be considered clinically "cured." Clinical factors associated with cure have not been studied adequately. Because the ordinary Cox PH model cannot be used to identify such clinical factors, we used the Cox PH cure model, a recently developed statistical method. This model includes both a logistic regression component for the cure rate and a Cox regression component for the hazard for uncured patients. The purpose of this study was to identify the clinical factors associated with cure and the variables associated with the time to recurrence or death in NAC-treated breast cancer patients without a pathologic complete response, by using the Cox PH cure model. We found that hormone receptor status, clinical response, human epidermal growth factor receptor 2 status, histological grade, and the number of lymph node metastases were associated with cure.

Semi-parametric regression model for survival data: graphical visualization with R

PubMed Central

2016-01-01

Cox proportional hazards model is a semi-parametric model that leaves its baseline hazard function unspecified. The rationale to use Cox proportional hazards model is that (I) the underlying form of hazard function is stringent and unrealistic, and (II) researchers are only interested in estimation of how the hazard changes with covariate (relative hazard). Cox regression model can be easily fit with coxph() function in survival package. Stratified Cox model may be used for covariate that violates the proportional hazards assumption. The relative importance of covariates in population can be examined with the rankhazard package in R. Hazard ratio curves for continuous covariates can be visualized using smoothHR package. This curve helps to better understand the effects that each continuous covariate has on the outcome. Population attributable fraction is a classic quantity in epidemiology to evaluate the impact of risk factor on the occurrence of event in the population. In survival analysis, the adjusted/unadjusted attributable fraction can be plotted against survival time to obtain attributable fraction function. PMID:28090517

A global goodness-of-fit statistic for Cox regression models.

PubMed

Parzen, M; Lipsitz, S R

1999-06-01

In this paper, a global goodness-of-fit test statistic for a Cox regression model, which has an approximate chi-squared distribution when the model has been correctly specified, is proposed. Our goodness-of-fit statistic is global and has power to detect if interactions or higher order powers of covariates in the model are needed. The proposed statistic is similar to the Hosmer and Lemeshow (1980, Communications in Statistics A10, 1043-1069) goodness-of-fit statistic for binary data as well as Schoenfeld's (1980, Biometrika 67, 145-153) statistic for the Cox model. The methods are illustrated using data from a Mayo Clinic trial in primary billiary cirrhosis of the liver (Fleming and Harrington, 1991, Counting Processes and Survival Analysis), in which the outcome is the time until liver transplantation or death. The are 17 possible covariates. Two Cox proportional hazards models are fit to the data, and the proposed goodness-of-fit statistic is applied to the fitted models.

Building and validation of a prognostic model for predicting extracorporeal circuit clotting in patients with continuous renal replacement therapy.

PubMed

Fu, Xia; Liang, Xinling; Song, Li; Huang, Huigen; Wang, Jing; Chen, Yuanhan; Zhang, Li; Quan, Zilin; Shi, Wei

2014-04-01

To develop a predictive model for circuit clotting in patients with continuous renal replacement therapy (CRRT). A total of 425 cases were selected. 302 cases were used to develop a predictive model of extracorporeal circuit life span during CRRT without citrate anticoagulation in 24 h, and 123 cases were used to validate the model. The prediction formula was developed using multivariate Cox proportional-hazards regression analysis, from which a risk score was assigned. The mean survival time of the circuit was 15.0 ± 1.3 h, and the rate of circuit clotting was 66.6 % during 24 h of CRRT. Five significant variables were assigned a predicting score according to the regression coefficient: insufficient blood flow, no anticoagulation, hematocrit ≥0.37, lactic acid of arterial blood gas analysis ≤3 mmol/L and APTT < 44.2 s. The Hosmer-Lemeshow test showed no significant difference between the predicted and actual circuit clotting (R (2) = 0.232; P = 0.301). A risk score that includes the five above-mentioned variables can be used to predict the likelihood of extracorporeal circuit clotting in patients undergoing CRRT.

Construction of a pathological risk model of occult lymph node metastases for prognostication by semi-automated image analysis of tumor budding in early-stage oral squamous cell carcinoma

PubMed Central

Pedersen, Nicklas Juel; Jensen, David Hebbelstrup; Lelkaitis, Giedrius; Kiss, Katalin; Charabi, Birgitte; Specht, Lena; von Buchwald, Christian

2017-01-01

It is challenging to identify at diagnosis those patients with early oral squamous cell carcinoma (OSCC), who have a poor prognosis and those that have a high risk of harboring occult lymph node metastases. The aim of this study was to develop a standardized and objective digital scoring method to evaluate the predictive value of tumor budding. We developed a semi-automated image-analysis algorithm, Digital Tumor Bud Count (DTBC), to evaluate tumor budding. The algorithm was tested in 222 consecutive patients with early-stage OSCC and major endpoints were overall (OS) and progression free survival (PFS). We subsequently constructed and cross-validated a binary logistic regression model and evaluated its clinical utility by decision curve analysis. A high DTBC was an independent predictor of both poor OS and PFS in a multivariate Cox regression model. The logistic regression model was able to identify patients with occult lymph node metastases with an area under the curve (AUC) of 0.83 (95% CI: 0.78–0.89, P <0.001) and a 10-fold cross-validated AUC of 0.79. Compared to other known histopathological risk factors, the DTBC had a higher diagnostic accuracy. The proposed, novel risk model could be used as a guide to identify patients who would benefit from an up-front neck dissection. PMID:28212555

Cox proportional hazards model of myopic regression for laser in situ keratomileusis flap creation with a femtosecond laser and with a mechanical microkeratome.

PubMed

Lin, Meng-Yin; Chang, David C K; Hsu, Wen-Ming; Wang, I-Jong

2012-06-01

To compare predictive factors for postoperative myopic regression between laser in situ keratomileusis (LASIK) with a femtosecond laser and LASIK with a mechanical microkeratome. Nobel Eye Clinic, Taipei, Taiwan. Retrospective comparative study. Refractive outcomes were recorded 1 day, 1 week, and 1, 3, 6, 9, and 12 months after LASIK. A Cox proportional hazards model was used to evaluate the impact of the 2 flap-creating methods and other covariates on postoperative myopic regression. The femtosecond group comprised 409 eyes and the mechanical microkeratome group, 377 eyes. For both methods, significant predictors for myopic regression after LASIK included preoperative manifest spherical equivalent (P=.0001) and central corneal thickness (P=.027). Laser in situ keratomileusis with a mechanical microkeratome had a higher probability of postoperative myopic regression than LASIK with a femtosecond laser (P=.0002). After adjusting for other covariates in the Cox proportional hazards model, the cumulative risk for myopic regression with a mechanical microkeratome was higher than with a femtosecond laser 12 months postoperatively (P=.0002). With the definition of myopic regression as a myopic shift of 0.50 diopter (D) or more and residual myopia of -0.50 D or less, the risk estimate based on the mean covariates in all eyes in the femtosecond group and mechanical microkeratome group at 12 months was 43.6% and 66.9%, respectively. Laser in situ keratomileusis with a mechanical microkeratome had a higher risk for myopic regression than LASIK with a femtosecond laser through 12 months postoperatively. Copyright © 2012. Published by Elsevier Inc.

ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL

PubMed Central

Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

2013-01-01

We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities. PMID:24086091

ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL.

PubMed

Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

2013-06-01

We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities.

Validation of a nomogram in the prediction of local recurrence risks after conserving surgery for Asian women with ductal carcinoma in situ of the breast.

PubMed

Wang, F; Li, H; Tan, P H; Chua, E T; Yeo, R M C; Lim, F L W T; Kim, S W; Tan, D Y H; Wong, F Y

2014-11-01

At our centre, ductal carcinoma in situ (DCIS) was commonly treated with breast-conservation therapy (BCT). Local recurrence after BCT is a major concern. The aims of our study were to review the outcomes of DCIS treatment in our patients and to evaluate a nomogram from Memorial Sloan Kettering Cancer Centre (MSKCC) for predicting ipsilateral breast tumour recurrence (IBTR) in our Asian population. Chart reviews of 716 patients with pure DCIS treated from 1992 to 2011 were carried out. Univariable Cox regression analyses were used to evaluate the effects of the 10 prognostic factors of the MSKCC nomogram on IBTR. We constructed a separate National Cancer Centre Singapore (NCCS) nomogram based on multivariable Cox regression via reduced model selection by applying the stopping rule of Akaike's information criterion to predict IBTR-free survival. The abilities of the NCCS nomogram and the MSKCC nomogram to predict IBTR of individual patients were evaluated with bootstrapping of 200 sets of resamples and the NCCS dataset, respectively. Harrell's c-index was calculated for each nomogram to evaluate the concordance between predicted and observed responses of individual subjects. Study patients were followed up for a median of 70 months. Over 95% of patients received adjuvant radiotherapy. The 5 and 10 year actuarial IBTR-free survival rates for the cohort were 95.5 and 92.6%, respectively. In the multivariate analysis, independent prognostic factors for IBTR included use of adjuvant endocrine therapy, presence of comedonecrosis and younger age at diagnosis. These factors formed the basis of the NCCS nomogram, which had a similar c-index (NCCS: 0.696; MSKCC: 0.673) compared with the MSKCC nomogram. The MSKCC nomogram was validated in an Asian population. A simpler NCCS nomogram using a different combination of fewer prognostic factors may be sufficient for the prediction of IBTR in Asians, but requires external validation to compare for relative performance. Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

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

Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less

Can D-Dimer Measurement Reduce the Frequency of Radiological Assessment in Patients Receiving Palliative Imatinib for Gastrointestinal Stromal Tumor (GIST)?

PubMed

Afshar, Mehran; Hamilton, Patrick; Seligmann, Jenny; Lord, Simon; Baxter, Paul; Marples, Maria; Stark, Dan; Hall, Peter S

2015-01-01

Imatinib therapy has improved outcomes in advanced GISTs. Current guidelines suggest monitoring with CT scanning every 12 weeks. There are no validated biomarkers to assist disease evaluation. We identified 50 patients treated with imatinib for GIST in a single tertiary center. We assessed the prognostic value of D-dimers by Cox regression, and the utility as a biomarker for radiological progression (rPD) using receiver-operator curve (ROC) analysis. In asymptomatic patients with D-dimer levels <1,000 and falling levels, the negative predictive value for rPD was 92%. D-dimers may reduce the burden of CT scanning in a proportion of patients in this setting.

Prognostic Factors for Neurologic Outcome in Patients with Carotid Artery Stenting

PubMed Central

Hung, Chi-Sheng; Lin, Mao-Shin; Chen, Ying-Hsien; Huang, Ching-Chang; Li, Hung-Yuan; Kao, Hsien-Li

2016-01-01

Background Carotid artery stenting (CAS) is a valid treatment for patients with carotid artery stenosis. The long-term outcome and prognostic factors in Asian population after CAS are not clear. This study aimed to identify the prognostic factors among Asian patients who have undergone CAS. Methods We retrospectively analyzed 246 patients with CAS. Annual carotid duplex ultrasound was used to identify restenosis. Peri-procedural complications, restenosis, neurologic outcomes, and mortality were recorded. Cox regression analyses were used to identify prognostic factors. Results The mean follow-up time was 49.2 months. Procedural success was achieved in 237 patients (98.3%), and protection devices were used in 208 patients (84.5%). Within 30 days of CAS, 13 (4.3% per procedure) peri-procedural complications occurred. During the follow-up period, 24 (9.7%) patients developed restenosis, and 37 (15.0%) developed ischemic strokes. In a multiple logistic regression analysis, head and neck radiotherapy [hazard ratio (HR) = 9.9, 95% confidence interval (CI), 3.38-29.1, p < .001], stent diameter (HR = 0.72, 95% CI, 0.58-0.89, p = .003), and predilatation (HR = 3.08 95% CI, 1.21-7.81, p = .018) were independent predictors for restenosis. In Cox regression analysis, hypercholesterolemia (HR = 0.25, 95% CI, 0.07-0.94, p = .04), head and neck radiotherapy (HR = 6.2, 95% CI, 1.8-21.3, p = .004), and restenosis (HR = 3.6, 95% CI, 1.1-11.18, p = .04) were predictors for recurrent ipsilateral ischemic stroke. Conclusions CAS provides reliable long-term results in Asian patients with carotid stenosis. Restenosis is associated with an increased rate of recurrent stroke and should be monitored carefully following CAS. PMID:27122951

Protein-coding genes combined with long noncoding RNA as a novel transcriptome molecular staging model to predict the survival of patients with esophageal squamous cell carcinoma.

PubMed

Guo, Jin-Cheng; Wu, Yang; Chen, Yang; Pan, Feng; Wu, Zhi-Yong; Zhang, Jia-Sheng; Wu, Jian-Yi; Xu, Xiu-E; Zhao, Jian-Mei; Li, En-Min; Zhao, Yi; Xu, Li-Yan

2018-04-09

Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal carcinoma in China. This study was to develop a staging model to predict outcomes of patients with ESCC. Using Cox regression analysis, principal component analysis (PCA), partitioning clustering, Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, and classification and regression tree (CART) analysis, we mined the Gene Expression Omnibus database to determine the expression profiles of genes in 179 patients with ESCC from GSE63624 and GSE63622 dataset. Univariate cox regression analysis of the GSE63624 dataset revealed that 2404 protein-coding genes (PCGs) and 635 long non-coding RNAs (lncRNAs) were associated with the survival of patients with ESCC. PCA categorized these PCGs and lncRNAs into three principal components (PCs), which were used to cluster the patients into three groups. ROC analysis demonstrated that the predictive ability of PCG-lncRNA PCs when applied to new patients was better than that of the tumor-node-metastasis staging (area under ROC curve [AUC]: 0.69 vs. 0.65, P < 0.05). Accordingly, we constructed a molecular disaggregated model comprising one lncRNA and two PCGs, which we designated as the LSB staging model using CART analysis in the GSE63624 dataset. This LSB staging model classified the GSE63622 dataset of patients into three different groups, and its effectiveness was validated by analysis of another cohort of 105 patients. The LSB staging model has clinical significance for the prognosis prediction of patients with ESCC and may serve as a three-gene staging microarray.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

PubMed

Ching, Travers; Zhu, Xun; Garmire, Lana X

2018-04-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

Box-Cox transformation of left-censored data with application to the analysis of coronary artery calcification and pharmacokinetic data.

PubMed

Han, Cong; Kronmal, Richard

2004-12-15

Box-Cox transformation is investigated for regression models for left-censored data. Examples are provided using coronary calcification data from the Multi-Ethnic Study of Atherosclerosis and pharmacokinetic data of a nicotine nasal spray. Copyright 2004 John Wiley & Sons, Ltd.

Predictors of course in obsessive-compulsive disorder: logistic regression versus Cox regression for recurrent events.

PubMed

Kempe, P T; van Oppen, P; de Haan, E; Twisk, J W R; Sluis, A; Smit, J H; van Dyck, R; van Balkom, A J L M

2007-09-01

Two methods for predicting remissions in obsessive-compulsive disorder (OCD) treatment are evaluated. Y-BOCS measurements of 88 patients with a primary OCD (DSM-III-R) diagnosis were performed over a 16-week treatment period, and during three follow-ups. Remission at any measurement was defined as a Y-BOCS score lower than thirteen combined with a reduction of seven points when compared with baseline. Logistic regression models were compared with a Cox regression for recurrent events model. Logistic regression yielded different models at different evaluation times. The recurrent events model remained stable when fewer measurements were used. Higher baseline levels of neuroticism and more severe OCD symptoms were associated with a lower chance of remission, early age of onset and more depressive symptoms with a higher chance. Choice of outcome time affects logistic regression prediction models. Recurrent events analysis uses all information on remissions and relapses. Short- and long-term predictors for OCD remission show overlap.

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

PubMed

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

2009-12-01

Predicting the survival of heart-lung transplant patients has the potential to play a critical role in understanding and improving the matching procedure between the recipient and graft. Although voluminous data related to the transplantation procedures is being collected and stored, only a small subset of the predictive factors has been used in modeling heart-lung transplantation outcomes. The previous studies have mainly focused on applying statistical techniques to a small set of factors selected by the domain-experts in order to reveal the simple linear relationships between the factors and survival. The collection of methods known as 'data mining' offers significant advantages over conventional statistical techniques in dealing with the latter's limitations such as normality assumption of observations, independence of observations from each other, and linearity of the relationship between the observations and the output measure(s). There are statistical methods that overcome these limitations. Yet, they are computationally more expensive and do not provide fast and flexible solutions as do data mining techniques in large datasets. The main objective of this study is to improve the prediction of outcomes following combined heart-lung transplantation by proposing an integrated data-mining methodology. A large and feature-rich dataset (16,604 cases with 283 variables) is used to (1) develop machine learning based predictive models and (2) extract the most important predictive factors. Then, using three different variable selection methods, namely, (i) machine learning methods driven variables-using decision trees, neural networks, logistic regression, (ii) the literature review-based expert-defined variables, and (iii) common sense-based interaction variables, a consolidated set of factors is generated and used to develop Cox regression models for heart-lung graft survival. The predictive models' performance in terms of 10-fold cross-validation accuracy rates for two multi-imputed datasets ranged from 79% to 86% for neural networks, from 78% to 86% for logistic regression, and from 71% to 79% for decision trees. The results indicate that the proposed integrated data mining methodology using Cox hazard models better predicted the graft survival with different variables than the conventional approaches commonly used in the literature. This result is validated by the comparison of the corresponding Gains charts for our proposed methodology and the literature review based Cox results, and by the comparison of Akaike information criteria (AIC) values received from each. Data mining-based methodology proposed in this study reveals that there are undiscovered relationships (i.e. interactions of the existing variables) among the survival-related variables, which helps better predict the survival of the heart-lung transplants. It also brings a different set of variables into the scene to be evaluated by the domain-experts and be considered prior to the organ transplantation.

Charlson comorbidity index as a predictor of periodontal disease in elderly participants

PubMed Central

2018-01-01

Purpose This study investigated the validity of the Charlson comorbidity index (CCI) as a predictor of periodontal disease (PD) over a 12-year period. Methods Nationwide representative samples of 149,785 adults aged ≥60 years with PD (International Classification of Disease, 10th revision [ICD-10], K052–K056) were derived from the National Health Insurance Service-Elderly Cohort during 2002–2013. The degree of comorbidity was measured using the CCI (grade 0–6), including 17 diseases weighted on the basis of their association with mortality, and data were analyzed using multivariate Cox proportional-hazards regression in order to investigate the associations of comorbid diseases (CDs) with PD. Results The multivariate Cox regression analysis with adjustment for sociodemographic factors (sex, age, household income, insurance status, residence area, and health status) and CDs (acute myocardial infarction, congestive heart failure, peripheral vascular disease, cerebral vascular accident, dementia, pulmonary disease, connective tissue disorders, peptic ulcer, liver disease, diabetes, diabetes complications, paraplegia, renal disease, cancer, metastatic cancer, severe liver disease, and human immunodeficiency virus [HIV]) showed that the CCI in elderly comorbid participants was significantly and positively correlated with the presence of PD (grade 1: hazard ratio [HR], 1.11; P<0.001; grade ≥2: HR, 1.12, P<0.001). Conclusions We demonstrated that a higher CCI was a significant predictor of greater risk for PD in the South Korean elderly population. PMID:29770238

Fluorocoxib A enables targeted detection of cyclooxygenase-2 in laser-induced choroidal neovascularization

NASA Astrophysics Data System (ADS)

Uddin, Md. Jashim; Moore, Chauca E.; Crews, Brenda C.; Daniel, Cristina K.; Ghebreselasie, Kebreab; McIntyre, J. Oliver; Marnett, Lawrence J.; Jayagopal, Ashwath

2016-09-01

Ocular angiogenesis is a blinding complication of age-related macular degeneration and other retinal vascular diseases. Clinical imaging approaches to detect inflammation prior to the onset of neovascularization in these diseases may enable early detection and timely therapeutic intervention. We demonstrate the feasibility of a previously developed cyclooxygenase-2 (COX-2) targeted molecular imaging probe, fluorocoxib A, for imaging retinal inflammation in a mouse model of laser-induced choroidal neovascularization. This imaging probe exhibited focal accumulation within laser-induced neovascular lesions, with minimal detection in proximal healthy tissue. The selectivity of the probe for COX-2 was validated in vitro and by in vivo retinal imaging with nontargeted 5-carboxy-X-rhodamine dye, and by blockade of the COX-2 active site with nonfluorescent celecoxib prior to injection of fluorocoxib A. Fluorocoxib A can be utilized for imaging COX-2 expression in vivo for further validation as an imaging biomarker in retinal diseases.

Comparison of exact, efron and breslow parameter approach method on hazard ratio and stratified cox regression model

NASA Astrophysics Data System (ADS)

Fatekurohman, Mohamat; Nurmala, Nita; Anggraeni, Dian

2018-04-01

Lungs are the most important organ, in the case of respiratory system. Problems related to disorder of the lungs are various, i.e. pneumonia, emphysema, tuberculosis and lung cancer. Comparing all those problems, lung cancer is the most harmful. Considering about that, the aim of this research applies survival analysis and factors affecting the endurance of the lung cancer patient using comparison of exact, Efron and Breslow parameter approach method on hazard ratio and stratified cox regression model. The data applied are based on the medical records of lung cancer patients in Jember Paru-paru hospital on 2016, east java, Indonesia. The factors affecting the endurance of the lung cancer patients can be classified into several criteria, i.e. sex, age, hemoglobin, leukocytes, erythrocytes, sedimentation rate of blood, therapy status, general condition, body weight. The result shows that exact method of stratified cox regression model is better than other. On the other hand, the endurance of the patients is affected by their age and the general conditions.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

PubMed

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer.

PubMed

De Marchi, Tommaso; Liu, Ning Qing; Stingl, Cristoph; Timmermans, Mieke A; Smid, Marcel; Look, Maxime P; Tjoa, Mila; Braakman, Rene B H; Opdam, Mark; Linn, Sabine C; Sweep, Fred C G J; Span, Paul N; Kliffen, Mike; Luider, Theo M; Foekens, John A; Martens, John W M; Umar, Arzu

2016-01-01

Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were collected from multiple medical centers and divided into two sets: an in-house training and a multi-center test set. Epithelial tumor cells were enriched with LCM and analyzed by nano-LC Orbitrap mass spectrometry (MS), which yielded >3000 and >4000 quantified proteins in the training and test sets, respectively. Raw data are available via ProteomeXchange with identifiers PXD000484 and PXD000485. Statistical analysis showed differential abundance of 99 proteins, of which a subset of 4 proteins was selected through a multivariate step-down to develop a predictor for tamoxifen treatment outcome. The 4-protein signature significantly predicted poor outcome patients in the test set, independent of predictive histopathological characteristics (hazard ratio [HR] = 2.17; 95% confidence interval [CI] = 1.15 to 4.17; multivariate Cox regression p value = 0.017). Immunohistochemical (IHC) staining of PDCD4, one of the signature proteins, on an independent set of formalin-fixed paraffin-embedded tumor tissues provided and independent technical validation (HR = 0.72; 95% CI = 0.57 to 0.92; multivariate Cox regression p value = 0.009). We hereby report the first validated protein predictor for tamoxifen treatment outcome in recurrent ER-positive breast cancer. IHC further showed that PDCD4 is an independent marker. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Extended cox regression model: The choice of timefunction

NASA Astrophysics Data System (ADS)

Isik, Hatice; Tutkun, Nihal Ata; Karasoy, Durdu

2017-07-01

Cox regression model (CRM), which takes into account the effect of censored observations, is one the most applicative and usedmodels in survival analysis to evaluate the effects of covariates. Proportional hazard (PH), requires a constant hazard ratio over time, is the assumptionofCRM. Using extended CRM provides the test of including a time dependent covariate to assess the PH assumption or an alternative model in case of nonproportional hazards. In this study, the different types of real data sets are used to choose the time function and the differences between time functions are analyzed and discussed.

The UK-PBC risk scores: Derivation and validation of a scoring system for long-term prediction of end-stage liver disease in primary biliary cholangitis.

PubMed

Carbone, Marco; Sharp, Stephen J; Flack, Steve; Paximadas, Dimitrios; Spiess, Kelly; Adgey, Carolyn; Griffiths, Laura; Lim, Reyna; Trembling, Paul; Williamson, Kate; Wareham, Nick J; Aldersley, Mark; Bathgate, Andrew; Burroughs, Andrew K; Heneghan, Michael A; Neuberger, James M; Thorburn, Douglas; Hirschfield, Gideon M; Cordell, Heather J; Alexander, Graeme J; Jones, David E J; Sandford, Richard N; Mells, George F

2016-03-01

The biochemical response to ursodeoxycholic acid (UDCA)--so-called "treatment response"--strongly predicts long-term outcome in primary biliary cholangitis (PBC). Several long-term prognostic models based solely on the treatment response have been developed that are widely used to risk stratify PBC patients and guide their management. However, they do not take other prognostic variables into account, such as the stage of the liver disease. We sought to improve existing long-term prognostic models of PBC using data from the UK-PBC Research Cohort. We performed Cox's proportional hazards regression analysis of diverse explanatory variables in a derivation cohort of 1,916 UDCA-treated participants. We used nonautomatic backward selection to derive the best-fitting Cox model, from which we derived a multivariable fractional polynomial model. We combined linear predictors and baseline survivor functions in equations to score the risk of a liver transplant or liver-related death occurring within 5, 10, or 15 years. We validated these risk scores in an independent cohort of 1,249 UDCA-treated participants. The best-fitting model consisted of the baseline albumin and platelet count, as well as the bilirubin, transaminases, and alkaline phosphatase, after 12 months of UDCA. In the validation cohort, the 5-, 10-, and 15-year risk scores were highly accurate (areas under the curve: >0.90). The prognosis of PBC patients can be accurately evaluated using the UK-PBC risk scores. They may be used to identify high-risk patients for closer monitoring and second-line therapies, as well as low-risk patients who could potentially be followed up in primary care. © 2015 by the American Association for the Study of Liver Diseases.

Development of a prognostic nomogram for cirrhotic patients with upper gastrointestinal bleeding.

PubMed

Zhou, Yu-Jie; Zheng, Ji-Na; Zhou, Yi-Fan; Han, Yi-Jing; Zou, Tian-Tian; Liu, Wen-Yue; Braddock, Martin; Shi, Ke-Qing; Wang, Xiao-Dong; Zheng, Ming-Hua

2017-10-01

Upper gastrointestinal bleeding (UGIB) is a complication with a high mortality rate in critically ill patients presenting with cirrhosis. Today, there exist few accurate scoring models specifically designed for mortality risk assessment in critically ill cirrhotic patients with upper gastrointestinal bleeding (CICGIB). Our aim was to develop and evaluate a novel nomogram-based model specific for CICGIB. Overall, 540 consecutive CICGIB patients were enrolled. On the basis of Cox regression analyses, the nomogram was constructed to estimate the probability of 30-day, 90-day, 270-day, and 1-year survival. An upper gastrointestinal bleeding-chronic liver failure-sequential organ failure assessment (UGIB-CLIF-SOFA) score was derived from the nomogram. Performance assessment and internal validation of the model were performed using Harrell's concordance index (C-index), calibration plot, and bootstrap sample procedures. UGIB-CLIF-SOFA was also compared with other prognostic models, such as CLIF-SOFA and model for end-stage liver disease, using C-indices. Eight independent factors derived from Cox analysis (including bilirubin, creatinine, international normalized ratio, sodium, albumin, mean artery pressure, vasopressin used, and hematocrit decrease>10%) were assembled into the nomogram and the UGIB-CLIF-SOFA score. The calibration plots showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram using bootstrap (0.729; 95% confidence interval: 0.689-0.766) was higher than that of the other models for predicting survival of CICGIB. We have developed and internally validated a novel nomogram and an easy-to-use scoring system that accurately predicts the mortality probability of CICGIB on the basis of eight easy-to-obtain parameters. External validation is now warranted in future clinical studies.

Personality predicts time to remission and clinical status in hypochondriasis during a 6-year follow-up.

PubMed

Greeven, Anja; van Balkom, Anton J L M; Spinhoven, Philip

2014-05-01

We aimed to investigate whether personality characteristics predict time to remission and psychiatric status. The follow-up was at most 6 years and was performed within the scope of a randomized controlled trial that investigated the efficacy of cognitive behavioral therapy, paroxetine, and placebo in hypochondriasis. The Life Chart Interview was administered to investigate for each year if remission had occurred. Personality was assessed at pretest by the Abbreviated Dutch Temperament and Character Inventory. Cox's regression models for recurrent events were compared with logistic regression models. Sixteen (36.4%) of 44 patients achieved remission during the follow-up period. Cox's regression yielded approximately the same results as the logistic regression. Being less harm avoidant and more cooperative were associated with a shorter time to remission and a remitted state after the follow-up period. Personality variables seem to be relevant for describing patients with a more chronic course of hypochondriacal complaints.

ELASTIC NET FOR COX'S PROPORTIONAL HAZARDS MODEL WITH A SOLUTION PATH ALGORITHM.

PubMed

Wu, Yichao

2012-01-01

For least squares regression, Efron et al. (2004) proposed an efficient solution path algorithm, the least angle regression (LAR). They showed that a slight modification of the LAR leads to the whole LASSO solution path. Both the LAR and LASSO solution paths are piecewise linear. Recently Wu (2011) extended the LAR to generalized linear models and the quasi-likelihood method. In this work we extend the LAR further to handle Cox's proportional hazards model. The goal is to develop a solution path algorithm for the elastic net penalty (Zou and Hastie (2005)) in Cox's proportional hazards model. This goal is achieved in two steps. First we extend the LAR to optimizing the log partial likelihood plus a fixed small ridge term. Then we define a path modification, which leads to the solution path of the elastic net regularized log partial likelihood. Our solution path is exact and piecewise determined by ordinary differential equation systems.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

PubMed Central

Ching, Travers; Zhu, Xun

2018-01-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet. PMID:29634719

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

PubMed

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

2014-01-01

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

Effects of electroacupuncture on luteal regression and steroidogenesis in ovarian hyperstimulation syndrome model rat.

PubMed

Huang, Xuan; Chen, Li; Xia, You-Bing; Xie, Min; Sun, Qin; Yao, Bing

2018-03-15

Electroacupuncture (EA) is an effective and safe therapeutic method widely used for treating clinical diseases. Previously, we found that EA could decrease serum hormones and reduce ovarian size in ovarian hyperstimulation syndrome (OHSS) rat model. Nevertheless, the mechanisms that contribute to these improvements remain unclear. HE staining was used to count the number of corpora lutea (CL) and follicles. Immunohistochemical and ELISA were applied to examine luteal functional and structural regression. Immunoprecipitation was used for analyzing the interaction between NPY (neuropeptide Y) and COX-2; western blotting and qRT-PCR were used to evaluate the expressions of steroidogenic enzymes and PKA/CREB pathway. EA treatment significantly reduced the ovarian weight and the number of CL, also decreased ovarian and serum levels of PGE2 and COX-2 expression; increased ovarian PGF2α levels and PGF2α/PGE2 ratio; decreased PCNA expression and distribution; and increased cyclin regulatory inhibitor p27 expression to have further effect on the luteal formation, and promote luteal functional and structural regression. Moreover, expression of COX-2 in ovaries was possessed interactivity increased expression of NPY. Furthermore, EA treatment lowered the serum hormone levels, inhibited PKA/CREB pathway and decreased the expressions of steroidogenic enzymes. Hence, interaction with COX-2, NPY may affect the levels of PGF2α and PGE2 as well as impact the proliferation of granulosa cells in ovaries, thus further reducing the luteal formation, and promoting luteal structural and functional regression, as well as the ovarian steroidogenesis following EA treatment. EA treatment could be an option for preventing OHSS in ART. Copyright © 2018 Elsevier Inc. All rights reserved.

Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis.

PubMed

Dietrich, Stefan; Floegel, Anna; Troll, Martina; Kühn, Tilman; Rathmann, Wolfgang; Peters, Anette; Sookthai, Disorn; von Bergen, Martin; Kaaks, Rudolf; Adamski, Jerzy; Prehn, Cornelia; Boeing, Heiner; Schulze, Matthias B; Illig, Thomas; Pischon, Tobias; Knüppel, Sven; Wang-Sattler, Rui; Drogan, Dagmar

2016-10-01

The application of metabolomics in prospective cohort studies is statistically challenging. Given the importance of appropriate statistical methods for selection of disease-associated metabolites in highly correlated complex data, we combined random survival forest (RSF) with an automated backward elimination procedure that addresses such issues. Our RSF approach was illustrated with data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study, with concentrations of 127 serum metabolites as exposure variables and time to development of type 2 diabetes mellitus (T2D) as outcome variable. Out of this data set, Cox regression with a stepwise selection method was recently published. Replication of methodical comparison (RSF and Cox regression) was conducted in two independent cohorts. Finally, the R-code for implementing the metabolite selection procedure into the RSF-syntax is provided. The application of the RSF approach in EPIC-Potsdam resulted in the identification of 16 incident T2D-associated metabolites which slightly improved prediction of T2D when used in addition to traditional T2D risk factors and also when used together with classical biomarkers. The identified metabolites partly agreed with previous findings using Cox regression, though RSF selected a higher number of highly correlated metabolites. The RSF method appeared to be a promising approach for identification of disease-associated variables in complex data with time to event as outcome. The demonstrated RSF approach provides comparable findings as the generally used Cox regression, but also addresses the problem of multicollinearity and is suitable for high-dimensional data. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Evaluation of methodology for the analysis of 'time-to-event' data in pharmacogenomic genome-wide association studies.

PubMed

Syed, Hamzah; Jorgensen, Andrea L; Morris, Andrew P

2016-06-01

To evaluate the power to detect associations between SNPs and time-to-event outcomes across a range of pharmacogenomic study designs while comparing alternative regression approaches. Simulations were conducted to compare Cox proportional hazards modeling accounting for censoring and logistic regression modeling of a dichotomized outcome at the end of the study. The Cox proportional hazards model was demonstrated to be more powerful than the logistic regression analysis. The difference in power between the approaches was highly dependent on the rate of censoring. Initial evaluation of single-nucleotide polymorphism association signals using computationally efficient software with dichotomized outcomes provides an effective screening tool for some design scenarios, and thus has important implications for the development of analytical protocols in pharmacogenomic studies.

Tumor gene expression and prognosis in breast cancer patients with 10 or more positive lymph nodes.

PubMed

Cobleigh, Melody A; Tabesh, Bita; Bitterman, Pincas; Baker, Joffre; Cronin, Maureen; Liu, Mei-Lan; Borchik, Russell; Mosquera, Juan-Miguel; Walker, Michael G; Shak, Steven

2005-12-15

This study, along with two others, was done to develop the 21-gene Recurrence Score assay (Oncotype DX) that was validated in a subsequent independent study and is used to aid decision making about chemotherapy in estrogen receptor (ER)-positive, node-negative breast cancer patients. Patients with >or=10 nodes diagnosed from 1979 to 1999 were identified. RNA was extracted from paraffin blocks, and expression of 203 candidate genes was quantified using reverse transcription-PCR (RT-PCR). Seventy-eight patients were studied. As of August 2002, 77% of patients had distant recurrence or breast cancer death. Univariate Cox analysis of clinical and immunohistochemistry variables indicated that HER2/immunohistochemistry, number of involved nodes, progesterone receptor (PR)/immunohistochemistry (% cells), and ER/immunohistochemistry (% cells) were significantly associated with distant recurrence-free survival (DRFS). Univariate Cox analysis identified 22 genes associated with DRFS. Higher expression correlated with shorter DRFS for the HER2 adaptor GRB7 and the macrophage marker CD68. Higher expression correlated with longer DRFS for tumor protein p53-binding protein 2 (TP53BP2) and the ER axis genes PR and Bcl2. Multivariate methods, including stepwise variable selection and bootstrap resampling of the Cox proportional hazards regression model, identified several genes, including TP53BP2 and Bcl2, as significant predictors of DRFS. Tumor gene expression profiles of archival tissues, some more than 20 years old, provide significant information about risk of distant recurrence even among patients with 10 or more nodes.

Experiments to Determine Whether Recursive Partitioning (CART) or an Artificial Neural Network Overcomes Theoretical Limitations of Cox Proportional Hazards Regression

NASA Technical Reports Server (NTRS)

Kattan, Michael W.; Hess, Kenneth R.; Kattan, Michael W.

1998-01-01

New computationally intensive tools for medical survival analyses include recursive partitioning (also called CART) and artificial neural networks. A challenge that remains is to better understand the behavior of these techniques in effort to know when they will be effective tools. Theoretically they may overcome limitations of the traditional multivariable survival technique, the Cox proportional hazards regression model. Experiments were designed to test whether the new tools would, in practice, overcome these limitations. Two datasets in which theory suggests CART and the neural network should outperform the Cox model were selected. The first was a published leukemia dataset manipulated to have a strong interaction that CART should detect. The second was a published cirrhosis dataset with pronounced nonlinear effects that a neural network should fit. Repeated sampling of 50 training and testing subsets was applied to each technique. The concordance index C was calculated as a measure of predictive accuracy by each technique on the testing dataset. In the interaction dataset, CART outperformed Cox (P less than 0.05) with a C improvement of 0.1 (95% Cl, 0.08 to 0.12). In the nonlinear dataset, the neural network outperformed the Cox model (P less than 0.05), but by a very slight amount (0.015). As predicted by theory, CART and the neural network were able to overcome limitations of the Cox model. Experiments like these are important to increase our understanding of when one of these new techniques will outperform the standard Cox model. Further research is necessary to predict which technique will do best a priori and to assess the magnitude of superiority.

Approximate median regression for complex survey data with skewed response.

PubMed

Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M; Pan, Yi

2016-12-01

The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling, and weighting. In this article, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS)'based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. © 2016, The International Biometric Society.

Comparing spatial regression to random forests for large ...

EPA Pesticide Factsheets

Environmental data may be “large” due to number of records, number of covariates, or both. Random forests has a reputation for good predictive performance when using many covariates, whereas spatial regression, when using reduced rank methods, has a reputation for good predictive performance when using many records. In this study, we compare these two techniques using a data set containing the macroinvertebrate multimetric index (MMI) at 1859 stream sites with over 200 landscape covariates. Our primary goal is predicting MMI at over 1.1 million perennial stream reaches across the USA. For spatial regression modeling, we develop two new methods to accommodate large data: (1) a procedure that estimates optimal Box-Cox transformations to linearize covariate relationships; and (2) a computationally efficient covariate selection routine that takes into account spatial autocorrelation. We show that our new methods lead to cross-validated performance similar to random forests, but that there is an advantage for spatial regression when quantifying the uncertainty of the predictions. Simulations are used to clarify advantages for each method. This research investigates different approaches for modeling and mapping national stream condition. We use MMI data from the EPA's National Rivers and Streams Assessment and predictors from StreamCat (Hill et al., 2015). Previous studies have focused on modeling the MMI condition classes (i.e., good, fair, and po

Approximate Median Regression for Complex Survey Data with Skewed Response

PubMed Central

Fraser, Raphael André; Lipsitz, Stuart R.; Sinha, Debajyoti; Fitzmaurice, Garrett M.; Pan, Yi

2016-01-01

Summary The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling and weighting. In this paper, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS) based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. PMID:27062562

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

Survival analysis of postoperative nausea and vomiting in patients receiving patient-controlled epidural analgesia.

PubMed

Lee, Shang-Yi; Hung, Chih-Jen; Chen, Chih-Chieh; Wu, Chih-Cheng

2014-11-01

Postoperative nausea and vomiting as well as postoperative pain are two major concerns when patients undergo surgery and receive anesthetics. Various models and predictive methods have been developed to investigate the risk factors of postoperative nausea and vomiting, and different types of preventive managements have subsequently been developed. However, there continues to be a wide variation in the previously reported incidence rates of postoperative nausea and vomiting. This may have occurred because patients were assessed at different time points, coupled with the overall limitation of the statistical methods used. However, using survival analysis with Cox regression, and thus factoring in these time effects, may solve this statistical limitation and reveal risk factors related to the occurrence of postoperative nausea and vomiting in the following period. In this retrospective, observational, uni-institutional study, we analyzed the results of 229 patients who received patient-controlled epidural analgesia following surgery from June 2007 to December 2007. We investigated the risk factors for the occurrence of postoperative nausea and vomiting, and also assessed the effect of evaluating patients at different time points using the Cox proportional hazards model. Furthermore, the results of this inquiry were compared with those results using logistic regression. The overall incidence of postoperative nausea and vomiting in our study was 35.4%. Using logistic regression, we found that only sex, but not the total doses and the average dose of opioids, had significant effects on the occurrence of postoperative nausea and vomiting at some time points. Cox regression showed that, when patients consumed a higher average dose of opioids, this correlated with a higher incidence of postoperative nausea and vomiting with a hazard ratio of 1.286. Survival analysis using Cox regression showed that the average consumption of opioids played an important role in postoperative nausea and vomiting, a result not found by logistic regression. Therefore, the incidence of postoperative nausea and vomiting in patients cannot be reliably determined on the basis of a single visit at one point in time. Copyright © 2014. Published by Elsevier Taiwan.

Factors determining disease duration in Alzheimer's disease: a postmortem study of 103 cases using the Kaplan-Meier estimator and Cox regression.

PubMed

Armstrong, R A

2014-01-01

Factors associated with duration of dementia in a consecutive series of 103 Alzheimer's disease (AD) cases were studied using the Kaplan-Meier estimator and Cox regression analysis (proportional hazard model). Mean disease duration was 7.1 years (range: 6 weeks-30 years, standard deviation = 5.18); 25% of cases died within four years, 50% within 6.9 years, and 75% within 10 years. Familial AD cases (FAD) had a longer duration than sporadic cases (SAD), especially cases linked to presenilin (PSEN) genes. No significant differences in duration were associated with age, sex, or apolipoprotein E (Apo E) genotype. Duration was reduced in cases with arterial hypertension. Cox regression analysis suggested longer duration was associated with an earlier disease onset and increased senile plaque (SP) and neurofibrillary tangle (NFT) pathology in the orbital gyrus (OrG), CA1 sector of the hippocampus, and nucleus basalis of Meynert (NBM). The data suggest shorter disease duration in SAD and in cases with hypertensive comorbidity. In addition, degree of neuropathology did not influence survival, but spread of SP/NFT pathology into the frontal lobe, hippocampus, and basal forebrain was associated with longer disease duration.

Reliability, Factor Structure, and Associations With Measures of Problem Relationship and Behavior of the Personality Inventory for DSM-5 in a Sample of Italian Community-Dwelling Adolescents.

PubMed

Somma, Antonella; Borroni, Serena; Maffei, Cesare; Giarolli, Laura E; Markon, Kristian E; Krueger, Robert F; Fossati, Andrea

2017-10-01

In order to assess the reliability, factorial validity, and criterion validity of the Personality Inventory for DSM-5 (PID-5) among adolescents, 1,264 Italian high school students were administered the PID-5. Participants were also administered the Questionnaire on Relationships and Substance Use as a criterion measure. In the full sample, McDonald's ω values were adequate for the PID-5 scales (median ω = .85, SD = .06), except for Suspiciousness. However, all PID-5 scales showed average inter-item correlation values in the .20-.55 range. Exploratory structural equation modeling analyses provided moderate support for the a priori model of PID-5 trait scales. Ordinal logistic regression analyses showed that selected PID-5 trait scales predicted a significant, albeit moderate (Cox & Snell R 2 values ranged from .08 to .15, all ps < .001) amount of variance in Questionnaire on Relationships and Substance Use variables.

New medical diagnoses and length of stay of acutely unwell older patients: Implications for funding models.

PubMed

Basic, David; Khoo, Angela

2015-09-01

To examine the relationship between newly made medical diagnoses and length of stay (LOS) of acutely unwell older patients. Consecutive patients admitted under the care of four geriatricians were randomly allocated to a model development sample (n = 937) or a model validation sample (n = 855). Cox regression was used to model LOS. Variables considered for inclusion in the development model were established risk factors for LOS and univariate predictors from our dataset. Variables selected in the development sample were tested in the validation sample. A median of five new medical diagnoses were made during a median LOS of 10 days. New diagnoses predicted an increased LOS (hazard ratio 0.90, 95% confidence interval 0.88-0.92). Other significant predictors of increased LOS in both samples were malnutrition and frailty. Identification of new medical diagnoses may have implications for Diagnosis Related Groups-based funding models and may improve the care of older people. © 2015 AJA Inc.

A long-term predictive validity study: can the CDI Short Form be used to predict language and early literacy skills four years later?

PubMed

Can, Dilara Deniz; Ginsburg-Block, Marika; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

2013-09-01

This longitudinal study examined the predictive validity of the MacArthur Communicative Developmental Inventories-Short Form (CDI-SF), a parent report questionnaire about children's language development (Fenson, Pethick, Renda, Cox, Dale & Reznick, 2000). Data were first gathered from parents on the CDI-SF vocabulary scores for seventy-six children (mean age=1 ; 10). Four years later (mean age=6 ; 1), children were assessed on language outcomes (expressive vocabulary, syntax, semantics and pragmatics) and code-related skills, including phonemic awareness, word recognition and decoding skills. Hierarchical regression analyses revealed that early expressive vocabulary accounted for 17% of the variance in picture vocabulary, 11% of the variance in syntax, and 7% of the variance in semantics, while not accounting for any variance in pragmatics in kindergarten. CDI-SF scores did not predict code-related skills in kindergarten. The importance of early vocabulary skills for later language development and CDI-SF as a valuable research tool are discussed.

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

PubMed Central

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables. PMID:29713298

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

PubMed

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we assess a range of candidate distributions, including the Sichel, Delaporte, Box-Cox Green and Cole, and Box-Cox t distributions. We find that the Box-Cox t distribution, with appropriate modeling of its parameters, best fits the conditional distribution of phonemic inventory size. We finally discuss the specificities of phoneme counts, weak effects, and how GAMLSS should be considered for other linguistic variables.

Comparison of Cox's Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000-2012.

PubMed

Adelian, R; Jamali, J; Zare, N; Ayatollahi, S M T; Pooladfar, G R; Roustaei, N

2015-01-01

Identification of the prognostic factors for survival in patients with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. To compare Cox's regression model with parametric models for determining the independent factors for predicting adults' and pediatrics' survival after liver transplantation. This study was conducted on 183 pediatric patients and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all patients undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, Child class, initial diagnosis of the liver disease, PELD/MELD score, and pre-operative laboratory markers were selected for survival analysis. Among 529 patients, 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric patients. Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and Child class B (HR=2.12, p<0.05) in pediatric patients were the most important factors for prediction of survival after liver transplantation. Adult patients younger than the mean age and pediatric patients weighing above the mean and Child class A (compared to those with classes B or C) had better survival. Parametric regression model is a good alternative for the Cox's regression model.

Survival analysis of cervical cancer using stratified Cox regression

NASA Astrophysics Data System (ADS)

Purnami, S. W.; Inayati, K. D.; Sari, N. W. Wulan; Chosuvivatwong, V.; Sriplung, H.

2016-04-01

Cervical cancer is one of the mostly widely cancer cause of the women death in the world including Indonesia. Most cervical cancer patients come to the hospital already in an advanced stadium. As a result, the treatment of cervical cancer becomes more difficult and even can increase the death's risk. One of parameter that can be used to assess successfully of treatment is the probability of survival. This study raises the issue of cervical cancer survival patients at Dr. Soetomo Hospital using stratified Cox regression based on six factors such as age, stadium, treatment initiation, companion disease, complication, and anemia. Stratified Cox model is used because there is one independent variable that does not satisfy the proportional hazards assumption that is stadium. The results of the stratified Cox model show that the complication variable is significant factor which influent survival probability of cervical cancer patient. The obtained hazard ratio is 7.35. It means that cervical cancer patient who has complication is at risk of dying 7.35 times greater than patient who did not has complication. While the adjusted survival curves showed that stadium IV had the lowest probability of survival.

Decision tree analysis to stratify risk of de novo non-melanoma skin cancer following liver transplantation.

PubMed

Tanaka, Tomohiro; Voigt, Michael D

2018-03-01

Non-melanoma skin cancer (NMSC) is the most common de novo malignancy in liver transplant (LT) recipients; it behaves more aggressively and it increases mortality. We used decision tree analysis to develop a tool to stratify and quantify risk of NMSC in LT recipients. We performed Cox regression analysis to identify which predictive variables to enter into the decision tree analysis. Data were from the Organ Procurement Transplant Network (OPTN) STAR files of September 2016 (n = 102984). NMSC developed in 4556 of the 105984 recipients, a mean of 5.6 years after transplant. The 5/10/20-year rates of NMSC were 2.9/6.3/13.5%, respectively. Cox regression identified male gender, Caucasian race, age, body mass index (BMI) at LT, and sirolimus use as key predictive or protective factors for NMSC. These factors were entered into a decision tree analysis. The final tree stratified non-Caucasians as low risk (0.8%), and Caucasian males > 47 years, BMI < 40 who did not receive sirolimus, as high risk (7.3% cumulative incidence of NMSC). The predictions in the derivation set were almost identical to those in the validation set (r 2  = 0.971, p < 0.0001). Cumulative incidence of NMSC in low, moderate and high risk groups at 5/10/20 year was 0.5/1.2/3.3, 2.1/4.8/11.7 and 5.6/11.6/23.1% (p < 0.0001). The decision tree model accurately stratifies the risk of developing NMSC in the long-term after LT.

Dietary sodium to potassium ratio and the incidence of hypertension and cardiovascular disease: A population-based longitudinal study.

PubMed

Mirmiran, Parvin; Bahadoran, Zahra; Nazeri, Pantea; Azizi, Fereidoun

2018-01-30

There is an interaction between dietary sodium/potassium intake in the pathogenesis of hypertension (HTN) and cardiovascular disease (CVD). The aim of this study was to investigate the association of dietary sodium to potassium (Na/K) ratio and the risk of HTN and CVD in a general population of Iranian adults. In this prospective cohort study, adults men and women with complete baseline data were selected from among participants of the Tehran Lipid and Glucose Study and were followed up for 6.3 years for incidence of HTN and CVD outcomes. Dietary sodium and potassium were assessed using a valid and reliable 168-item food frequency questionnaire. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between dietary sodium, potassium and their ratio and risk of outcomes. During the study follow-up, 291 (15.1%) and 79 (5.0%) new cases of HTN and CVD were identified, respectively. No significant association was observed between usual intakes of sodium, potassium and dietary Na/K ratio with the incidence of HTN. There was no significant association between dietary intakes of sodium and potassium per se and the risk of CVD, whereas when dietary sodium to potassium ratio was considered as exposure in the fully-adjusted Cox regression model, and participants in the highest compared to lowest tertile had a significantly increased risk of CVD (HR = 2.19, 95% CI = 1.16-4.14). Our findings suggest that high dietary Na/K ratio could contribute to increased risk of CVD events.

Box-Cox transformation of firm size data in statistical analysis

NASA Astrophysics Data System (ADS)

Chen, Ting Ting; Takaishi, Tetsuya

2014-03-01

Firm size data usually do not show the normality that is often assumed in statistical analysis such as regression analysis. In this study we focus on two firm size data: the number of employees and sale. Those data deviate considerably from a normal distribution. To improve the normality of those data we transform them by the Box-Cox transformation with appropriate parameters. The Box-Cox transformation parameters are determined so that the transformed data best show the kurtosis of a normal distribution. It is found that the two firm size data transformed by the Box-Cox transformation show strong linearity. This indicates that the number of employees and sale have the similar property as a firm size indicator. The Box-Cox parameters obtained for the firm size data are found to be very close to zero. In this case the Box-Cox transformations are approximately a log-transformation. This suggests that the firm size data we used are approximately log-normal distributions.

An assay of optimal cytochrome c oxidase activity in fish gills.

PubMed

Hu, Yau-Chung; Chung, Meng-Han; Lee, Tsung-Han

2018-07-15

Cytochrome c oxidase (COX) catalyzes the terminal oxidation reaction in the electron transport chain (ETC) of aerobic respiratory systems. COX activity is an important indicator for the evaluation of energy production by aerobic respiration in various tissues. On the basis of the respiratory characteristics of muscle, we established an optimal method for the measurement of maximal COX activity. To validate the measurement of cytochrome c absorbance, different ionic buffer concentrations and tissue homogenate protein concentrations were used to investigate COX activity. The results showed that optimal COX activity is achieved when using 50-100 μg fish gill homogenate in conjunction with 75-100 mM potassium phosphate buffer. Furthermore, we compared branchial COX activities among three species of euryhaline teleost (Chanos chanos, Oreochromis mossambicus, and Oryzias dancena) to investigate differences in aerobic respiration of osmoregulatory organs. COX activities in the gills of these three euryhaline species were compared with COX subunit 4 (COX4) protein levels. COX4 protein abundance and COX activity patterns in the three species occurring in environments with various salinities increased when fish encountered salinity challenges. This COX activity assay therefore provides an effective and accurate means of assessing aerobic metabolism in fish. Copyright © 2018 Elsevier Inc. All rights reserved.

Development and validation of a risk model for long-term mortality after percutaneous coronary intervention: The IDEA-BIO Study.

PubMed

van Boven, Nick; van Domburg, Ron T; Kardys, Isabella; Umans, Victor A; Akkerhuis, K Martijn; Lenzen, Mattie J; Valgimigli, Marco; Daemen, Joost; Zijlstra, Felix; Boersma, Eric; van Geuns, Robert-Jan

2018-03-01

We aimed to develop a model to predict long-term mortality after percutaneous coronary intervention (PCI), to aid in selecting patients with sufficient life expectancy to benefit from bioabsorbable scaffolds. Clinical trials are currently designed to demonstrate superiority of bioabsorbable scaffolds over metal devices up to 5 years after implantation. From 2000 to 2011, 19.532 consecutive patients underwent PCI in a tertiary referral hospital. Patients were randomly (2:1) divided into a training (N = 13,090) and validation (N = 6,442) set. Cox regression was used to identify determinants of long-term mortality in the training set and used to develop a risk model. Model performance was studied in the training and validation dataset. Median age was 63 years (IQR 54-72) and 72% were men. Median follow-up was 3.6 years (interquartile range [IQR] 2.4-6.8). The ratio elective vs. non-elective PCIs was 42/58. During 88,620 patient-years of follow-up, 3,156 deaths occurred, implying an incidence rate of 35.6 per 1,000. Estimated 5-year mortality was 12.9%.Regression analysis revealed age, body mass index, diabetes mellitus, renal insufficiency, prior myocardial infarction, PCI indication, lesion location, number of diseased vessels and cardiogenic shock at presentation as determinants of mortality. The long-term risk model showed good discrimination in the training and validation sets (c-indices 0.76 and 0.74), whereas calibration was appropriate. A simple risk model, containing 9 baseline clinical and angiographic variables effectively predicts long-term mortality after PCI and may possibly be used to select suitable patients for bioabsorbable scaffolds. © 2017 Wiley Periodicals, Inc.

Censored quantile regression with recursive partitioning-based weights

PubMed Central

Wey, Andrew; Wang, Lan; Rudser, Kyle

2014-01-01

Censored quantile regression provides a useful alternative to the Cox proportional hazards model for analyzing survival data. It directly models the conditional quantile of the survival time and hence is easy to interpret. Moreover, it relaxes the proportionality constraint on the hazard function associated with the popular Cox model and is natural for modeling heterogeneity of the data. Recently, Wang and Wang (2009. Locally weighted censored quantile regression. Journal of the American Statistical Association 103, 1117–1128) proposed a locally weighted censored quantile regression approach that allows for covariate-dependent censoring and is less restrictive than other censored quantile regression methods. However, their kernel smoothing-based weighting scheme requires all covariates to be continuous and encounters practical difficulty with even a moderate number of covariates. We propose a new weighting approach that uses recursive partitioning, e.g. survival trees, that offers greater flexibility in handling covariate-dependent censoring in moderately high dimensions and can incorporate both continuous and discrete covariates. We prove that this new weighting scheme leads to consistent estimation of the quantile regression coefficients and demonstrate its effectiveness via Monte Carlo simulations. We also illustrate the new method using a widely recognized data set from a clinical trial on primary biliary cirrhosis. PMID:23975800

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis

PubMed Central

Gong, Xiajing; Hu, Meng

2018-01-01

Abstract Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time‐to‐event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high‐dimensional data featured by a large number of predictor variables. Our results showed that ML‐based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high‐dimensional data. The prediction performances of ML‐based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML‐based methods provide a powerful tool for time‐to‐event analysis, with a built‐in capacity for high‐dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. PMID:29536640

Immunohistochemical and morphometric evaluation of COX-1 and COX-2 in the remodeled lung in idiopathic pulmonary fibrosis and systemic sclerosis* ,**

PubMed Central

Parra, Edwin Roger; Lin, Flavia; Martins, Vanessa; Rangel, Maristela Peres; Capelozzi, Vera Luiza

2013-01-01

OBJECTIVE: To study the expression of COX-1 and COX-2 in the remodeled lung in systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients, correlating that expression with patient survival. METHODS: We examined open lung biopsy specimens from 24 SSc patients and 30 IPF patients, using normal lung tissue as a control. The histological patterns included fibrotic nonspecific interstitial pneumonia (NSIP) in SSc patients and usual interstitial pneumonia (UIP) in IPF patients. We used immunohistochemistry and histomorphometry to evaluate the expression of COX-1 and COX-2 in alveolar septa, vessels, and bronchioles. We then correlated that expression with pulmonary function test results and evaluated its impact on patient survival. RESULTS: The expression of COX-1 and COX-2 in alveolar septa was significantly higher in IPF-UIP and SSc-NSIP lung tissue than in the control tissue. No difference was found between IPF-UIP and SSc-NSIP tissue regarding COX-1 and COX-2 expression. Multivariate analysis based on the Cox regression model showed that the factors associated with a low risk of death were younger age, high DLCO/alveolar volume, IPF, and high COX-1 expression in alveolar septa, whereas those associated with a high risk of death were advanced age, low DLCO/alveolar volume, SSc (with NSIP), and low COX-1 expression in alveolar septa. CONCLUSIONS: Our findings suggest that strategies aimed at preventing low COX-1 synthesis will have a greater impact on SSc, whereas those aimed at preventing high COX-2 synthesis will have a greater impact on IPF. However, prospective randomized clinical trials are needed in order to confirm that. PMID:24473763

Quantile Regression with Censored Data

ERIC Educational Resources Information Center

Lin, Guixian

2009-01-01

The Cox proportional hazards model and the accelerated failure time model are frequently used in survival data analysis. They are powerful, yet have limitation due to their model assumptions. Quantile regression offers a semiparametric approach to model data with possible heterogeneity. It is particularly powerful for censored responses, where the…

Intake of different types of dairy and its prospective association with risk of type 2 diabetes: The Rotterdam Study.

PubMed

Brouwer-Brolsma, E M; van Woudenbergh, G J; Oude Elferink, S J W H; Singh-Povel, C M; Hofman, A; Dehghan, A; Franco, O H; Feskens, E J M

2016-11-01

The prevalence of type 2 diabetes (T2DM) is increasing. Several studies have suggested a beneficial effect of several major dairy nutrients on insulin production and sensitivity. Conversely, harmful effects have been suggested as well. This study aimed to investigate the impact of the full-range of dairy products and its association with incidence T2DM in Dutch adults aged ≥55 years participating in the Rotterdam Study. Dairy intake was assessed with a validated FFQ, including total, skimmed, semi-skimmed, full-fat, fermented, and non-fermented dairy, and subclasses of these product groups. Verified prevalent and incident diabetes were documented. Cox proportional hazards regression and spline regression were used to analyse data, adjusting for age, sex, alcohol, smoking, education, physical activity, body mass index, intake of total energy, energy-adjusted meat, and energy-adjusted fish intake. Median total dairy intake was 398 g/day (IQR 259-559 g/day). Through 9.5 ± 4.1 years of follow-up, 393 cases of incident T2DM were reported. Cox and spline regression did not point towards associations of total dairy consumption, dairy consumption based on fat content, non-fermented or fermented dairy consumption, or individual dairy product consumption with incident T2DM. The HR for total dairy intake and T2DM was 0.93 (95% CI: 0.70-1.23) in the upper quartile (P-for trend 0.76). This prospective cohort study did not point towards an association between dairy consumption and T2DM. Copyright © 2016 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study.

PubMed

Ngwa, Julius S; Cabral, Howard J; Cheng, Debbie M; Pencina, Michael J; Gagnon, David R; LaValley, Michael P; Cupples, L Adrienne

2016-11-03

Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.

Evaluation of Cox's model and logistic regression for matched case-control data with time-dependent covariates: a simulation study.

PubMed

Leffondré, Karen; Abrahamowicz, Michal; Siemiatycki, Jack

2003-12-30

Case-control studies are typically analysed using the conventional logistic model, which does not directly account for changes in the covariate values over time. Yet, many exposures may vary over time. The most natural alternative to handle such exposures would be to use the Cox model with time-dependent covariates. However, its application to case-control data opens the question of how to manipulate the risk sets. Through a simulation study, we investigate how the accuracy of the estimates of Cox's model depends on the operational definition of risk sets and/or on some aspects of the time-varying exposure. We also assess the estimates obtained from conventional logistic regression. The lifetime experience of a hypothetical population is first generated, and a matched case-control study is then simulated from this population. We control the frequency, the age at initiation, and the total duration of exposure, as well as the strengths of their effects. All models considered include a fixed-in-time covariate and one or two time-dependent covariate(s): the indicator of current exposure and/or the exposure duration. Simulation results show that none of the models always performs well. The discrepancies between the odds ratios yielded by logistic regression and the 'true' hazard ratio depend on both the type of the covariate and the strength of its effect. In addition, it seems that logistic regression has difficulty separating the effects of inter-correlated time-dependent covariates. By contrast, each of the two versions of Cox's model systematically induces either a serious under-estimation or a moderate over-estimation bias. The magnitude of the latter bias is proportional to the true effect, suggesting that an improved manipulation of the risk sets may eliminate, or at least reduce, the bias. Copyright 2003 JohnWiley & Sons, Ltd.

P21, COX-2, and E-cadherin are potential prognostic factors for esophageal squamous cell carcinoma.

PubMed

Lin, Yao; Shen, Lu-Yan; Fu, Hao; Dong, Bin; Yang, He-Li; Yan, Wan-Pu; Kang, Xiao-Zheng; Dai, Liang; Zhou, Hai-Tao; Yang, Yong-Bo; Liang, Zhen; Chen, Ke-Neng

2017-02-01

Much research effort has been devoted to identifying prognostic factors for esophageal squamous cell carcinoma (ESCC) by immunohistochemistry; however, no conclusive findings have been reached thus far. We hypothesized that certain molecules identified in previous studies might serve as useful prognostic markers for ESCC. Therefore, the aim of the current study was to validate the most relevant markers showing potential for ESCC prognosis in our prospective esophageal cancer database. A literature search was performed using the PubMed database for papers published between 1980 and 2015 using the following key words: 'esophageal cancer,' 'prognosis,' and 'immunohistochemistry.' Literature selection criteria were established to identify the most widely studied markers, and we further validated the selected markers in a cohort from our single-surgeon team, including 153 esophageal cancer patients treated from 2000 to 2010. A total of 1799 articles were identified, 82 of which met the selection criteria. Twelve markers were found to be the most widely studied, and the validation results indicated that only P21, COX-2, and E-cadherin were independent prognostic factors for ESCC patients in this series. The systemic review and cohort validation suggest that P21, COX-2, and E-cadherin are potential prognostic factors for ESCC, paving the way for more targeted prospective validation in the future. © 2016 International Society for Diseases of the Esophagus.

Molecular risk assessment of BIG 1-98 participants by expression profiling using RNA from archival tissue

PubMed Central

2010-01-01

Background The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months. Methods RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score. Results Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses. Conclusions Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer. Trial Registration Current Controlled Trials: NCT00004205 PMID:20144231

COX-2 verexpression in pretreatment biopsies predicts response of rectal cancers to neoadjuvant radiochemotherapy

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

Smith, Fraser M.; Reynolds, John V.; Kay, Elaine W.

2006-02-01

Purpose: To determine the utility of COX-2 expression as a response predictor for patients with rectal cancer who are undergoing neoadjuvant radiochemotherapy (RCT). Methods and Materials: Pretreatment biopsies (PTB) from 49 patients who underwent RCT were included. COX-2 and proliferation in PTB were assessed by immunohistochemistry (IHC) and apoptosis was detected by TUNEL stain. Response to treatment was assessed by a 5-point tumor-regression grade (TRG) based on the ratio of residual tumor to fibrosis. Results: Good response (TRG 1 + 2), moderate response (TRG 3), and poor response (TRG 4 + 5) were seen in 21 patients (42%), 11 patientsmore » (22%), and 17 patients (34%), respectively. Patients with COX-2 overexpression in PTB were more likely to demonstrate moderate or poor response (TRG 3 + 4) to treatment than were those with normal COX-2 expression (p = 0.026, chi-square test). Similarly, poor response was more likely if patients had low levels of spontaneous apoptosis in PTBs (p = 0.0007, chi-square test). Conclusions: COX-2 overexpression and reduced apoptosis in PTB can predict poor response of rectal cancer to RCT. As COX-2 inhibitors are commercially available, their administration to patients who overexpress COX-2 warrants assessment in clinical trials in an attempt to increase overall response rates.« less

Reliable prediction of clinical outcome in patients with chronic HCV infection and compensated advanced hepatic fibrosis: a validated model using objective and readily available clinical parameters.

PubMed

van der Meer, Adriaan J; Hansen, Bettina E; Fattovich, Giovanna; Feld, Jordan J; Wedemeyer, Heiner; Dufour, Jean-François; Lammert, Frank; Duarte-Rojo, Andres; Manns, Michael P; Ieluzzi, Donatella; Zeuzem, Stefan; Hofmann, W Peter; de Knegt, Robert J; Veldt, Bart J; Janssen, Harry L A

2015-02-01

Reliable tools to predict long-term outcome among patients with well compensated advanced liver disease due to chronic HCV infection are lacking. Risk scores for mortality and for cirrhosis-related complications were constructed with Cox regression analysis in a derivation cohort and evaluated in a validation cohort, both including patients with chronic HCV infection and advanced fibrosis. In the derivation cohort, 100/405 patients died during a median 8.1 (IQR 5.7-11.1) years of follow-up. Multivariate Cox analyses showed age (HR=1.06, 95% CI 1.04 to 1.09, p<0.001), male sex (HR=1.91, 95% CI 1.10 to 3.29, p=0.021), platelet count (HR=0.91, 95% CI 0.87 to 0.95, p<0.001) and log10 aspartate aminotransferase/alanine aminotransferase ratio (HR=1.30, 95% CI 1.12 to 1.51, p=0.001) were independently associated with mortality (C statistic=0.78, 95% CI 0.72 to 0.83). In the validation cohort, 58/296 patients with cirrhosis died during a median of 6.6 (IQR 4.4-9.0) years. Among patients with estimated 5-year mortality risks <5%, 5-10% and >10%, the observed 5-year mortality rates in the derivation cohort and validation cohort were 0.9% (95% CI 0.0 to 2.7) and 2.6% (95% CI 0.0 to 6.1), 8.1% (95% CI 1.8 to 14.4) and 8.0% (95% CI 1.3 to 14.7), 21.8% (95% CI 13.2 to 30.4) and 20.9% (95% CI 13.6 to 28.1), respectively (C statistic in validation cohort = 0.76, 95% CI 0.69 to 0.83). The risk score for cirrhosis-related complications also incorporated HCV genotype (C statistic = 0.80, 95% CI 0.76 to 0.83 in the derivation cohort; and 0.74, 95% CI 0.68 to 0.79 in the validation cohort). Prognosis of patients with chronic HCV infection and compensated advanced liver disease can be accurately assessed with risk scores including readily available objective clinical parameters. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Cox Regression Models with Functional Covariates for Survival Data.

PubMed

Gellar, Jonathan E; Colantuoni, Elizabeth; Needham, Dale M; Crainiceanu, Ciprian M

2015-06-01

We extend the Cox proportional hazards model to cases when the exposure is a densely sampled functional process, measured at baseline. The fundamental idea is to combine penalized signal regression with methods developed for mixed effects proportional hazards models. The model is fit by maximizing the penalized partial likelihood, with smoothing parameters estimated by a likelihood-based criterion such as AIC or EPIC. The model may be extended to allow for multiple functional predictors, time varying coefficients, and missing or unequally-spaced data. Methods were inspired by and applied to a study of the association between time to death after hospital discharge and daily measures of disease severity collected in the intensive care unit, among survivors of acute respiratory distress syndrome.

Ku80 cooperates with CBP to promote COX-2 expression and tumor growth

PubMed Central

Qin, Yu; Xuan, Yang; Jia, Yunlu; Hu, Wenxian; Yu, Wendan; Dai, Meng; Li, Zhenglin; Yi, Canhui; Zhao, Shilei; Li, Mei; Du, Sha; Cheng, Wei; Xiao, Xiangsheng; Chen, Yiming; Wu, Taihua; Meng, Songshu; Yuan, Yuhui; Liu, Quentin; Huang, Wenlin; Guo, Wei; Wang, Shusen; Deng, Wuguo

2015-01-01

Cyclooxygenase-2 (COX-2) plays an important role in lung cancer development and progression. Using streptavidin-agarose pulldown and proteomics assay, we identified and validated Ku80, a dimer of Ku participating in the repair of broken DNA double strands, as a new binding protein of the COX-2 gene promoter. Overexpression of Ku80 up-regulated COX-2 promoter activation and COX-2 expression in lung cancer cells. Silencing of Ku80 by siRNA down-regulated COX-2 expression and inhibited tumor cell growth in vitro and in a xenograft mouse model. Ku80 knockdown suppressed phosphorylation of ERK, resulting in an inactivation of the MAPK pathway. Moreover, CBP, a transcription co-activator, interacted with and acetylated Ku80 to co-regulate the activation of COX-2 promoter. Overexpression of CBP increased Ku80 acetylation, thereby promoting COX-2 expression and cell growth. Suppression of CBP by a CBP-specific inhibitor or siRNA inhibited COX-2 expression as well as tumor cell growth. Tissue microarray immunohistochemical analysis of lung adenocarcinomas revealed a strong positive correlation between levels of Ku80 and COX-2 and clinicopathologic variables. Overexpression of Ku80 was associated with poor prognosis in patients with lung cancers. We conclude that Ku80 promotes COX-2 expression and tumor growth and is a potential therapeutic target in lung cancer. PMID:25797267

CREATION OF A MODEL TO PREDICT SURVIVAL IN PATIENTS WITH REFRACTORY COELIAC DISEASE USING A MULTINATIONAL REGISTRY

PubMed Central

Rubio-Tapia, Alberto; Malamut, Georgia; Verbeek, Wieke H.M.; van Wanrooij, Roy L.J.; Leffler, Daniel A.; Niveloni, Sonia I.; Arguelles-Grande, Carolina; Lahr, Brian D.; Zinsmeister, Alan R.; Murray, Joseph A.; Kelly, Ciaran P.; Bai, Julio C.; Green, Peter H.; Daum, Severin; Mulder, Chris J.J.; Cellier, Christophe

2016-01-01

Background Refractory coeliac disease is a severe complication of coeliac disease with heterogeneous outcome. Aim To create a prognostic model to estimate survival of patients with refractory coeliac disease. Methods We evaluated predictors of 5-year mortality using Cox proportional hazards regression on subjects from a multinational registry. Bootstrap re-sampling was used to internally validate the individual factors and overall model performance. The mean of the estimated regression coefficients from 400 bootstrap models was used to derive a risk score for 5-year mortality. Results The multinational cohort was composed of 232 patients diagnosed with refractory coeliac disease across 7 centers (range of 11–63 cases per center). The median age was 53 years and 150 (64%) were women. A total of 51 subjects died during 5-year follow-up (cumulative 5-year all-cause mortality = 30%). From a multiple variable Cox proportional hazards model, the following variables were significantly associated with 5-year mortality: age at refractory coeliac disease diagnosis (per 20 year increase, hazard ratio = 2.21; 95% confidence interval: 1.38, 3.55), abnormal intraepithelial lymphocytes (hazard ratio = 2.85; 95% confidence interval: 1.22, 6.62), and albumin (per 0.5 unit increase, hazard ratio = 0.72; 95% confidence interval: 0.61, 0.85). A simple weighted 3-factor risk score was created to estimate 5-year survival. Conclusions Using data from a multinational registry and previously-reported risk factors, we create a prognostic model to predict 5-year mortality among patients with refractory coeliac disease. This new model may help clinicians to guide treatment and follow-up. PMID:27485029

The Relationship Between the Dietary Inflammatory Index and Incident Frailty: A Longitudinal Cohort Study.

PubMed

Shivappa, Nitin; Stubbs, Brendon; Hébert, James R; Cesari, Matteo; Schofield, Patricia; Soysal, Pinar; Maggi, Stefania; Veronese, Nicola

2018-01-01

Inflammation is key risk factor for several conditions in the elderly. However, the relationship between inflammation and frailty is still unclear. We investigated whether higher dietary inflammatory index (DII) scores were associated with higher incidence of frailty in a cohort of North Americans. Longitudinal, with a follow-up of 8 years. Osteoarthritis Initiative. A total of 4421 participants with, or at high risk of, knee osteoarthritis. DII scores were calculated using the validated Block Brief 2000 Food-Frequency Questionnaire and categorized into sex-specific quartiles. Frailty was defined as 2 out of 3 of the criteria of the Study of Osteoporotic Fracture study (ie, weight loss, inability to rise from a chair 5 times, and poor energy). The strength of the association between baseline DII score and incident frailty was assessed through a Cox's regression analysis, adjusted for potential baseline confounders, and reported as hazard ratios. A total of 4421 community-dwelling participants (2564 female participants; mean age: 61.3 years) without frailty at baseline were identified from the Osteoarthritis Initiative. During 8 years of follow-up, 356 individuals developed frailty (8.2%). Using Cox's regression analysis, adjusting for 11 potential confounders, participants with the highest DII score (quartile 4) had a significantly higher risk of experiencing frailty (hazard ratio 1.37; 95% confidence interval 1.01-1.89; P = .04) compared with participants with the lowest DII score (quartile 1). The association between DII score and frailty was significant only in men. Higher DII scores, indicating a more proinflammatory diet, are associated with higher incidence of frailty, particularly in men. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

An integrated mRNA and microRNA expression signature for glioblastoma multiforme prognosis.

PubMed

Xiong, Jie; Bing, Zhitong; Su, Yanlin; Deng, Defeng; Peng, Xiaoning

2014-01-01

Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures.

An Integrated mRNA and microRNA Expression Signature for Glioblastoma Multiforme Prognosis

PubMed Central

Xiong, Jie; Bing, Zhitong; Su, Yanlin; Deng, Defeng; Peng, Xiaoning

2014-01-01

Although patients with Glioblastoma multiforme (GBM) have grave prognosis, significant variability in patient outcome is observed. The objective of this study is to identify a molecular signature for GBM prognosis. We subjected 355 mRNA and microRNA expression profiles to elastic net-regulated Cox regression for identification of an integrated RNA signature for GBM prognosis. A prognostic index (PI) was generated for patient stratification. Survival comparison was conducted by Kaplan-Meier method and a general multivariate Cox regression procedure was applied to evaluate the independence of the PI. The abilities and efficiencies of signatures to predict GBM patient outcome was assessed and compared by the area under the curve (AUC) of the receiver-operator characteristic (ROC). An integrated RNA prognostic signature consisted by 4 protective mRNAs, 12 risky mRNAs, and 1 risky microRNA was identified. Decreased survival was associated with being in the high-risk group (hazard ratio = 2.864, P<0.0001). The prognostic value of the integrated signature was validated in five independent GBM expression datasets (n = 201, hazard ratio = 2.453, P<0.0001). The PI outperformed the known clinical factors, mRNA-only, and miRNA-only prognostic signatures for GBM prognosis (area under the ROC curve for the integrated RNA, mRNA-only, and miRNA-only signatures were 0.828, 0.742, and 0.757 at 3 years of overall survival, respectively, P<0.0001 by permutation test). We describe the first, to our knowledge, robust transcriptome-based integrated RNA signature that improves the current GBM prognosis based on clinical variables, mRNA-only, and miRNA-only signatures. PMID:24871302

Malnutrition is associated with increased mortality in older adults regardless of the cause of death.

PubMed

Söderström, Lisa; Rosenblad, Andreas; Thors Adolfsson, Eva; Bergkvist, Leif

2017-02-01

Malnutrition predicts preterm death, but whether this is valid irrespective of the cause of death is unknown. The aim of the present study was to determine whether malnutrition is associated with cause-specific mortality in older adults. This cohort study was conducted in Sweden and included 1767 individuals aged ≥65 years admitted to hospital in 2008-2009. On the basis of the Mini Nutritional Assessment instrument, nutritional risk was assessed as well nourished (score 24-30), at risk of malnutrition (score 17-23·5) or malnourished (score <17). Cause of death was classified according to the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, into twenty different causes of death. Data were analysed using Cox proportional hazards regression models. At baseline, 55·1 % were at risk of malnutrition, and 9·4 % of the participants were malnourished. During a median follow-up of 5·1 years, 839 participants (47·5 %) died. The multiple Cox regression model identified significant associations (hazard ratio (HR)) between malnutrition and risk of malnutrition, respectively, and death due to neoplasms (HR 2·43 and 1·32); mental or behavioural disorders (HR 5·73 and 5·44); diseases of the nervous (HR 4·39 and 2·08), circulatory (HR 1·95 and 1·57) or respiratory system (HR 2·19 and 1·49); and symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified (HR 2·23 and 1·43). Malnutrition and risk of malnutrition are associated with increased mortality regardless of the cause of death, which emphasises the need for nutritional screening to identify older adults who may require nutritional support in order to avoid preterm death.

Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models.

PubMed

Ternès, Nils; Rotolo, Federico; Michiels, Stefan

2016-07-10

Correct selection of prognostic biomarkers among multiple candidates is becoming increasingly challenging as the dimensionality of biological data becomes higher. Therefore, minimizing the false discovery rate (FDR) is of primary importance, while a low false negative rate (FNR) is a complementary measure. The lasso is a popular selection method in Cox regression, but its results depend heavily on the penalty parameter λ. Usually, λ is chosen using maximum cross-validated log-likelihood (max-cvl). However, this method has often a very high FDR. We review methods for a more conservative choice of λ. We propose an empirical extension of the cvl by adding a penalization term, which trades off between the goodness-of-fit and the parsimony of the model, leading to the selection of fewer biomarkers and, as we show, to the reduction of the FDR without large increase in FNR. We conducted a simulation study considering null and moderately sparse alternative scenarios and compared our approach with the standard lasso and 10 other competitors: Akaike information criterion (AIC), corrected AIC, Bayesian information criterion (BIC), extended BIC, Hannan and Quinn information criterion (HQIC), risk information criterion (RIC), one-standard-error rule, adaptive lasso, stability selection, and percentile lasso. Our extension achieved the best compromise across all the scenarios between a reduction of the FDR and a limited raise of the FNR, followed by the AIC, the RIC, and the adaptive lasso, which performed well in some settings. We illustrate the methods using gene expression data of 523 breast cancer patients. In conclusion, we propose to apply our extension to the lasso whenever a stringent FDR with a limited FNR is targeted. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Spinal cord multi-parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis.

PubMed

Querin, G; El Mendili, M M; Lenglet, T; Delphine, S; Marchand-Pauvert, V; Benali, H; Pradat, P-F

2017-08-01

Assessing survival is a critical issue in patients with amyotrophic lateral sclerosis (ALS). Neuroimaging seems to be promising in the assessment of disease severity and several studies also suggest a strong relationship between spinal cord (SC) atrophy described by magnetic resonance imaging (MRI) and disease progression. The aim of the study was to determine the predictive added value of multimodal SC MRI on survival. Forty-nine ALS patients were recruited and clinical data were collected. Patients were scored on the Revised ALS Functional Rating Scale and manual muscle testing. They were followed longitudinally to assess survival. The cervical SC was imaged using the 3 T MRI system. Cord volume and cross-sectional area (CSA) at each vertebral level were computed. Diffusion tensor imaging metrics were measured. Imaging metrics and clinical variables were used as inputs for a multivariate Cox regression survival model. On building a multivariate Cox regression model with clinical and MRI parameters, fractional anisotropy, magnetization transfer ratio and CSA at C2-C3, C4-C5, C5-C6 and C6-C7 vertebral levels were significant. Moreover, the hazard ratio calculated for CSA at the C3-C4 and C5-C6 levels indicated an increased risk for patients with SC atrophy (respectively 0.66 and 0.68). In our cohort, MRI parameters seem to be more predictive than clinical variables, which had a hazard ratio very close to 1. It is suggested that multimodal SC MRI could be a useful tool in survival prediction especially if used at the beginning of the disease and when combined with clinical variables. To validate it as a biomarker, confirmation of the results in bigger independent cohorts of patients is warranted. © 2017 EAN.

Creation of a model to predict survival in patients with refractory coeliac disease using a multinational registry.

PubMed

Rubio-Tapia, A; Malamut, G; Verbeek, W H M; van Wanrooij, R L J; Leffler, D A; Niveloni, S I; Arguelles-Grande, C; Lahr, B D; Zinsmeister, A R; Murray, J A; Kelly, C P; Bai, J C; Green, P H; Daum, S; Mulder, C J J; Cellier, C

2016-10-01

Refractory coeliac disease is a severe complication of coeliac disease with heterogeneous outcome. To create a prognostic model to estimate survival of patients with refractory coeliac disease. We evaluated predictors of 5-year mortality using Cox proportional hazards regression on subjects from a multinational registry. Bootstrap resampling was used to internally validate the individual factors and overall model performance. The mean of the estimated regression coefficients from 400 bootstrap models was used to derive a risk score for 5-year mortality. The multinational cohort was composed of 232 patients diagnosed with refractory coeliac disease across seven centres (range of 11-63 cases per centre). The median age was 53 years and 150 (64%) were women. A total of 51 subjects died during a 5-year follow-up (cumulative 5-year all-cause mortality = 30%). From a multiple variable Cox proportional hazards model, the following variables were significantly associated with 5-year mortality: age at refractory coeliac disease diagnosis (per 20 year increase, hazard ratio = 2.21; 95% confidence interval, CI: 1.38-3.55), abnormal intraepithelial lymphocytes (hazard ratio = 2.85; 95% CI: 1.22-6.62), and albumin (per 0.5 unit increase, hazard ratio = 0.72; 95% CI: 0.61-0.85). A simple weighted three-factor risk score was created to estimate 5-year survival. Using data from a multinational registry and previously reported risk factors, we create a prognostic model to predict 5-year mortality among patients with refractory coeliac disease. This new model may help clinicians to guide treatment and follow-up. © 2016 John Wiley & Sons Ltd.

The Clinicopathological Factors Associated with Disease Progression in Luminal A Breast Cancer and Characteristics of Metastasis: A Retrospective Study from A Single Center in China.

PubMed

Ye, Jingming; Wang, Wenjun; Xin, Ling; Owen, Sioned; Xu, Ling; Duan, Xuening; Cheng, Yuanjia; Zhang, Hong; Zhang, Shuang; Li, Ting; Liu, Yinhua

2017-08-01

This study investigated the clinicopathological factors associated with outcomes in patients with Luminal A breast cancer. Retrospective analysis of the association of clinicopathological factors and breast cancer outcome in 421 patients with newly-diagnosed Luminal-A breast cancer that were enrolled from January 2008 to December 2014. Clinicopathological data were analyzed to validate the relationship with disease-free survival (DFS) and overall survival (OS). Kaplan-Meier curves and log-rank tests were used to analyze the value of clinicopathological factors (tumor size, node status and lymphovascular invasion), and subsequent Cox regression analysis revealed significant prognostic factors. With a median of 61 months follow-up, the 5-year DFS and 5-year OS rate were 98.3% and 99.3%. Cox multivariate regression analysis showed that clinical anatomic stage, tumor size, status of lymph nodes, lymphovascular invasion and systemic treatment are strong prognostic factors for clinical outcome in patients with Luminal-A breast cancer. Of all 413 patients with stage I-III breast cancer, 14 presented with metastasis (3.4%) during the follow up. Bone (6/14, 42.9%) was the most common site of metastasis followed by liver (5/14, 35.7%) and lung (4/14, 28.6%). The median survival time after metastasis was 20.4 months. Of all the sites of distant metastasis, liver metastasis was the only factor that affected survival time after metastasis (χ 2 =6.263, p=0.012). Patients with Luminal A breast cancer have excellent outcomes. Liver metastasis is an important factor compressing the survival time after distant metastasis presents. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Multiple factors explain injury risk in adolescent elite athletes: Applying a biopsychosocial perspective.

PubMed

von Rosen, P; Frohm, A; Kottorp, A; Fridén, C; Heijne, A

2017-12-01

Many risk factors for injury are presented in the literature, few of those are however consistent and the majority is associated with adult and not adolescent elite athletes. The aim was to identify risk factors for injury in adolescent elite athletes, by applying a biopsychosocial approach. A total of 496 adolescent elite athletes (age range 15-19), participating in 16 different sports, were monitored repeatedly over 52 weeks using a valid questionnaire about injuries, training exposure, sleep, stress, nutrition, and competence-based self-esteem. Univariate and multiple Cox regression analyses were used to calculate hazard ratios (HR) for risk factors for first reported injury. The main finding was that an increase in training load, training intensity, and at the same time decreasing the sleep volume resulted in a higher risk for injury compared to no change in these variables (HR 2.25, 95% CI, 1.46-3.45, P<.01), which was the strongest risk factor identified. In addition, an increase by one score of competence-based self-esteem increased the hazard for injury with 1.02 (HR 95% CI, 1.00-1.04, P=.01). Based on the multiple Cox regression analysis, an athlete having the identified risk factors (Risk Index, competence-based self-esteem), with an average competence-based self-esteem score, had more than a threefold increased risk for injury (HR 3.35), compared to an athlete with a low competence-based self-esteem and no change in sleep or training volume. Our findings confirm injury occurrence as a result of multiple risk factors interacting in complex ways. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Genetic Polymorphisms in RNA Binding Proteins Contribute to Breast Cancer Survival

PubMed Central

Upadhyay, Rohit; Sanduja, Sandhya; Kaza, Vimala; Dixon, Dan A.

2012-01-01

The RNA-binding proteins TTP and HuR control expression of numerous genes associated with breast cancer pathogenesis by regulating mRNA stability. However, the role of genetic variation in TTP (ZFP36) and HuR (ELAVL1) genes is unknown in breast cancer prognosis. A total of 251 breast cancer patients (170 Caucasians and 81 African-Americans) were enrolled and followed-up from 2001 to 2011 (or until death). Genotyping was performed for 10 SNPs in ZFP36 and 7 in ELAVL1 genes. On comparing both races with one another, significant differences were found for clinical and genetic variables. The influence of genetic polymorphisms on survival was analyzed by using Cox-regression, Kaplan-Meier analysis, and the log-rank test. Univariate (Kaplan-Meier/Cox-regression) and multivariate (Cox-regression) analysis showed that the TTP gene polymorphism ZFP36*2 A>G was significantly associated with poor prognosis of Caucasian patients (HR = 2.03; 95% CI = 1.09–3.76; P = 0.025; log-rank P = 0.022). None of the haplotypes, but presence of more than six risk genotypes in Caucasian patients, was significantly associated with poor prognosis (HR=2.42; 95% CI=1.17–4.99; P = 0.017; log-rank P = 0.007). The effect of ZFP36*2 A>G on gene expression was evaluated from patients' tissue samples. Both TTP mRNA and protein expression was significantly decreased in ZFP36*2 G allele carriers compared to A allele homozygotes. Conversely, upregulation of the TTP-target gene COX-2 was observed ZFP36*2 G allele carriers. Through its ability to attenuate TTP gene expression, the ZFP36*2 A>G gene polymorphism has appeared as a novel prognostic breast cancer marker in Caucasian patients. PMID:22907529

Evaluating cardiovascular mortality in type 2 diabetes patients: an analysis based on competing risks Markov chains and additive regression models.

PubMed

Rosato, Rosalba; Ciccone, G; Bo, S; Pagano, G F; Merletti, F; Gregori, D

2007-06-01

Type 2 diabetes represents a condition significantly associated with increased cardiovascular mortality. The aims of the study are: (i) to estimate the cumulative incidence function for cause-specific mortality using Cox and Aalen model; (ii) to describe how the prediction of cardiovascular or other causes mortality changes for patients with different pattern of covariates; (iii) to show if different statistical methods may give different results. Cox and Aalen additive regression model through the Markov chain approach, are used to estimate the cause-specific hazard for cardiovascular or other causes mortality in a cohort of 2865 type 2 diabetic patients without insulin treatment. The models are compared in the estimation of the risk of death for patients of different severity. For younger patients with a better covariates profile, the Cumulative Incidence Function estimated by Cox and Aalen model was almost the same; for patients with the worst covariates profile, models gave different results: at the end of follow-up cardiovascular mortality rate estimated by Cox and Aalen model was 0.26 [95% confidence interval (CI) = 0.21-0.31] and 0.14 (95% CI = 0.09-0.18). Standard Cox and Aalen model capture the risk process for patients equally well with average profiles of co-morbidities. The Aalen model, in addition, is shown to be better at identifying cause-specific risk of death for patients with more severe clinical profiles. This result is relevant in the development of analytic tools for research and resource management within diabetes care.

Comparative analysis of COX-2, vascular endothelial growth factor and microvessel density in human renal cell carcinomas.

PubMed

Hemmerlein, B; Galuschka, L; Putzer, N; Zischkau, S; Heuser, M

2004-12-01

Cyclooxygenase-2 (COX-2) and vascular endothelial growth factor (VEGF) are frequently up-regulated in malignant tumours and play a role in proliferation, apoptosis, angiogenesis and tumour invasion. In the present study, the expression of COX-2 and VEGF in renal cell carcinoma (RCC) was analysed and correlated with the microvessel density (MVD). COX-2 and VEGF were analysed by realtime reverse transcriptase-polymerase chain reaction and immunohistochemistry. The MVD was assessed by CD31 immunohistochemistry. The expression of COX-2 and VEGF was determined in the RCC cell lines A498 and Caki-1 under short-term hypoxia and in multicellular tumour cell aggregates. COX-2 was expressed in RCC by tumour epithelia, endothelia and macrophages in areas of cystic tumour regression and tumour necrosis. COX-2 protein in RCC was not altered in comparison with normal renal tissue. VEGF mRNA was up-regulated in RCC and positively correlated with MVD. RCC with high up-regulation of VEGF mRNA showed weak intracytoplasmic expression of VEGF in tumour cells. Intracytoplasmic VEGF protein expression was negatively correlated with MVD. In RCC with necrosis the MVD was reduced in comparison with RCC without necrosis. A498 RCC cells down-regulated COX-2 and up-regulated VEGF under conditions of hypoxia. In Caki-1 cells COX-2 expression remained stable, whereas VEGF was significantly up-regulated. In multicellular A498 cell aggregates COX-2 and VEGF were up-regulated centrally, whereas no gradient was found in Caki-1 cells. COX-2 and VEGF are potential therapeutic targets because COX-2 and VEGF are expressed in RCC and associated cell populations such as endothelia and monocytes/macrophages.

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

PubMed

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

PubMed

Ritz, Christian; Van der Vliet, Leana

2009-09-01

The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

Statistical primer: how to deal with missing data in scientific research?

PubMed

Papageorgiou, Grigorios; Grant, Stuart W; Takkenberg, Johanna J M; Mokhles, Mostafa M

2018-05-10

Missing data are a common challenge encountered in research which can compromise the results of statistical inference when not handled appropriately. This paper aims to introduce basic concepts of missing data to a non-statistical audience, list and compare some of the most popular approaches for handling missing data in practice and provide guidelines and recommendations for dealing with and reporting missing data in scientific research. Complete case analysis and single imputation are simple approaches for handling missing data and are popular in practice, however, in most cases they are not guaranteed to provide valid inferences. Multiple imputation is a robust and general alternative which is appropriate for data missing at random, surpassing the disadvantages of the simpler approaches, but should always be conducted with care. The aforementioned approaches are illustrated and compared in an example application using Cox regression.

Molecular structure, spectroscopic and docking analysis of 1,3-diphenylpyrazole-4-propionic acid: A good prostaglandin reductase inhibitor

NASA Astrophysics Data System (ADS)

Kavitha, T.; Velraj, G.

2018-03-01

The molecule 1,3-diphenylpyrazole-4-propionic acid (DPPA) was optimized to its minimum energy level using density functional theory (DFT) calculations. The vibrational frequencies of DPPA were calculated along with their potential energy distribution (PED) and the obtained values are validated with the help of experimental calculations. The reactivity nature of the molecule was investigated with the aid of various DFT methods such as global reactivity descriptors, local reactivity descriptors, molecular electrostatic potential (MEP), natural bond orbitals (NBOs), etc. The prediction of activity spectra for substances (PASS) result forecast that, DPPA can be more active as a prostaglandin (PG) reductase inhibitor. The PGs are biologically synthesized by the cyclooxygenase (COX) enzyme which exists in COX1 and COX2 forms. The PGs produced by COX2 enzyme induces inflammation and fungal infections and hence the inhibition of COX2 enzyme is indispensable in anti-inflammation and anti-fungal activities. The docking analysis of DPPA with COX enzymes (both COX1 and COX2) were carried out and eventually, it was found that DPPA can selectively inhibit COX2 enzyme and can serve as a PG reductase inhibitor thereby acting as a lead compound for the treatment of inflammation and fungal diseases.

Psychosocial work environment and mental health-related long-term sickness absence among nurses.

PubMed

Roelen, Corné A M; van Hoffen, Marieke F A; Waage, Siri; Schaufeli, Wilmar B; Twisk, Jos W R; Bjorvatn, Bjørn; Moen, Bente E; Pallesen, Ståle

2018-02-01

We investigated which job demands and job resources were predictive of mental health-related long-term sickness absence (LTSA) in nurses. The data of 2059 nurses were obtained from the Norwegian survey of Shift work, Sleep and Health. Job demands (psychological demands, role conflict, and harassment at the workplace) and job resources (social support at work, role clarity, and fair leadership) were measured at baseline and linked to mental health-related LTSA during 2-year follow-up. Cox regression models estimated hazard ratios (HR) and related 95% confidence intervals (CI). The c-statistic was used to investigate the discriminative ability of the Cox regression models. A total of 1533 (75%) nurses were included in the analyses; 103 (7%) of them had mental health-related LTSA during 2-year follow-up. Harassment (HR = 1.07; 95% CI 1.01-1.17) and social support (HR = 0.92; 95% CI 0.87-0.98) were associated with mental health-related LTSA. However, the Cox regression model did not discriminate between nurses with and without mental health-related LTSA (c = 0.59; 95% CI 0.53-0.65). Harassment was positively and social support at the workplace was negatively related to mental health-related LTSA, but both failed to discriminate between nurses with and without mental health-related LTSA during 2-year follow-up.

The effect of delayed graft function on graft and patient survival in kidney transplantation: an approach using competing events analysis.

PubMed

Fonseca, Isabel; Teixeira, Laetitia; Malheiro, Jorge; Martins, La Salete; Dias, Leonídio; Castro Henriques, António; Mendonça, Denisa

2015-06-01

In kidney transplantation, the impact of delayed graft function (DGF) on long-term graft and patient survival is controversial. We examined the impact of DGF on graft and recipient survival by accounting for the possibility that death with graft function may act as a competing risk for allograft failure. We used data from 1281 adult primary deceased-donor kidney recipients whose allografts functioned at least 1 year. The probability of graft loss occurrence is overestimated using the complement of Kaplan-Meier estimates (1-KM). Both the cause-specific Cox proportional hazard regression model (standard Cox) and the subdistribution hazard regression model proposed by Fine and Gray showed that DGF was associated with shorter time to graft failure (csHR = 2.0, P = 0.002; sHR = 1.57, P = 0.009), independent of acute rejection (AR) and after adjusting for traditional factors associated with graft failure. Regarding patient survival, DGF was a predictor of patient death using the cause-specific Cox model (csHR = 1.57, P = 0.029) but not using the subdistribution model. The probability of graft loss from competing end points should not be reported with the 1-KM. Application of a regression model for subdistribution hazard showed that, independent of AR, DGF has a detrimental effect on long-term graft survival, but not on patient survival. © 2015 Steunstichting ESOT.

Overexpression of epithelial cell adhesion molecule protein is associated with favorable prognosis in an unselected cohort of ovarian cancer patients.

PubMed

Battista, Marco Johannes; Cotarelo, Cristina; Jakobi, Sina; Steetskamp, Joscha; Makris, Georgios; Sicking, Isabel; Weyer, Veronika; Schmidt, Marcus

2014-07-01

The aim of this study was to evaluate the prognostic influence of epithelial cell adhesion molecule (EpCAM) in an unselected cohort of ovarian cancer (OC) patients. Expression of EpCAM was determined by immunohistochemistry in an unselected cohort of 117 patients with OC. Univariable and multivariable Cox regression analyses adjusted for age, tumor stage, histological grading, histological subtype, postoperative tumor burden and completeness of chemotherapy were performed in order to determine the prognostic influence of EpCAM. The Kaplan-Meier method is used to estimate survival rates. Univariable Cox regression analysis showed that overexpression of EpCAM is associated with favorable prognosis in terms of progression-free survival (PFS) (p = 0.011) and disease-specific survival (DSS) (p = 0.003). In multivariable Cox regression analysis, overexpression of EpCAM retains its significance independent of established prognostic factors for longer PFS [hazard ratios (HR) 0.408, 95 % confidence interval (CI) 0.197-0.846, p = 0.003] but not for PFS (HR 0.666, 95 % CI 0.366-1.212, p = 0.183). Kaplan-Meier plots demonstrate an influence on 5-year PFS rates (0 vs. 27.6 %, p = 0.048) and DSS rates (11.8 vs. 54.0 %, p = 0.018). These findings support the hypothesis that the expression of EpCAM is associated with favorable prognosis in OC.

Comparison of Weibull and Lognormal Cure Models with Cox in the Survival Analysis Of Breast Cancer Patients in Rafsanjan.

PubMed

Hoseini, Mina; Bahrampour, Abbas; Mirzaee, Moghaddameh

2017-02-16

Breast cancer is the most common cancer after lung cancer and the second cause of death. In this study we compared Weibull and Lognormal Cure Models with Cox regression on the survival of breast cancer. A cohort study. The current study retrospective cohort study was conducted on 140 patients referred to Ali Ibn Abitaleb Hospital, Rafsanjan southeastern Iran from 2001 to 2015 suffering from breast cancer. We determined and analyzed the effective survival causes by different models using STATA14. According to AIC, log-normal model was more consistent than Weibull. In the multivariable Lognormal model, the effective factors like smoking, second -hand smoking, drinking herbal tea and the last breast-feeding period were included. In addition, using Cox regression factors of significant were the disease grade, size of tumor and its metastasis (p-value<0.05). As Rafsanjan is surrounded by pistachio orchards and pesticides applied by farmers, people of this city are exposed to agricultural pesticides and its harmful consequences. The effect of the pesticide on breast cancer was studied and the results showed that the effect of pesticides on breast cancer was not in agreement with the models used in this study. Based on different methods for survival analysis, researchers can decide how they can reach a better conclusion. This comparison indicates the result of semi-parametric Cox method is closer to clinical experiences evidences.

Actinic cheilitis: epithelial expression of COX-2 and its association with mast cell tryptase and PAR-2.

PubMed

Rojas, I Gina; Martínez, Alejandra; Brethauer, Ursula; Grez, Patricia; Yefi, Roger; Luza, Sandra; Marchesani, Francisco J

2009-03-01

Cyclooxygenase-2 (COX-2) is overexpressed in various types of human malignancies, including oral cancers. Recent studies have shown that mast cell-derived protease tryptase can induce COX-2 expression by the cleavage of proteinase-activated receptor-2 (PAR-2). Actinic cheilitis (AC) is a premalignant form of lip cancer characterized by an increased density of tryptase-positive mast cells. To investigate the possible contribution of tryptase to COX-2 overexpression during early lip carcinogenesis, normal lip (n=24) and AC (n=45) biopsies were processed for COX-2, PAR-2 and tryptase detection, using RT-PCR and immunohistochemistry. Expression scores were obtained for each marker and tested for statistical significance using Mann-Whitney and Spearmann's correlation tests as well as multivariate logistic regression analysis. Increased epithelial co-expression of COX-2 and PAR-2, as well as, elevated subepithelial density of tryptase-positive mast cells were found in AC as compared to normal lip (P<0.001). COX-2 overexpression was found to be a significant predictor of AC (P<0.034, forward stepwise, Wald), and to be correlated with both tryptase-positive mast cells and PAR-2 expression (P<0.01). The results suggest that epithelial COX-2 overexpression is a key event in AC, which is associated with increased tryptase-positive mast cells and PAR-2. Therefore, tryptase may contribute to COX-2 up-regulation by epithelial PAR-2 activation during early lip carcinogenesis.

Validation of the Killip-Kimball Classification and Late Mortality after Acute Myocardial Infarction

PubMed Central

de Mello, Bruno Henrique Gallindo; Oliveira, Gustavo Bernardes F.; Ramos, Rui Fernando; Lopes, Bernardo Baptista C.; Barros, Cecília Bitarães S.; Carvalho, Erick de Oliveira; Teixeira, Fabio Bellini P.; Arruda, Guilherme D'Andréa S.; Revelo, Maria Sol Calero; Piegas, Leopoldo Soares

2014-01-01

Background The classification or index of heart failure severity in patients with acute myocardial infarction (AMI) was proposed by Killip and Kimball aiming at assessing the risk of in-hospital death and the potential benefit of specific management of care provided in Coronary Care Units (CCU) during the decade of 60. Objective To validate the risk stratification of Killip classification in the long-term mortality and compare the prognostic value in patients with non-ST-segment elevation MI (NSTEMI) relative to patients with ST-segment elevation MI (STEMI), in the era of reperfusion and modern antithrombotic therapies. Methods We evaluated 1906 patients with documented AMI and admitted to the CCU, from 1995 to 2011, with a mean follow-up of 05 years to assess total mortality. Kaplan-Meier (KM) curves were developed for comparison between survival distributions according to Killip class and NSTEMI versus STEMI. Cox proportional regression models were developed to determine the independent association between Killip class and mortality, with sensitivity analyses based on type of AMI. Results: The proportions of deaths and the KM survival distributions were significantly different across Killip class >1 (p <0.001) and with a similar pattern between patients with NSTEMI and STEMI. Cox models identified the Killip classification as a significant, sustained, consistent predictor and independent of relevant covariables (Wald χ2 16.5 [p = 0.001], NSTEMI) and (Wald χ2 11.9 [p = 0.008], STEMI). Conclusion The Killip and Kimball classification performs relevant prognostic role in mortality at mean follow-up of 05 years post-AMI, with a similar pattern between NSTEMI and STEMI patients. PMID:25014060

A microRNA-based prediction model for lymph node metastasis in hepatocellular carcinoma.

PubMed

Zhang, Li; Xiang, Zuo-Lin; Zeng, Zhao-Chong; Fan, Jia; Tang, Zhao-You; Zhao, Xiao-Mei

2016-01-19

We developed an efficient microRNA (miRNA) model that could predict the risk of lymph node metastasis (LNM) in hepatocellular carcinoma (HCC). We first evaluated a training cohort of 192 HCC patients after hepatectomy and found five LNM associated predictive factors: vascular invasion, Barcelona Clinic Liver Cancer stage, miR-145, miR-31, and miR-92a. The five statistically independent factors were used to develop a predictive model. The predictive value of the miRNA-based model was confirmed in a validation cohort of 209 consecutive HCC patients. The prediction model was scored for LNM risk from 0 to 8. The cutoff value 4 was used to distinguish high-risk and low-risk groups. The model sensitivity and specificity was 69.6 and 80.2%, respectively, during 5 years in the validation cohort. And the area under the curve (AUC) for the miRNA-based prognostic model was 0.860. The 5-year positive and negative predictive values of the model in the validation cohort were 30.3 and 95.5%, respectively. Cox regression analysis revealed that the LNM hazard ratio of the high-risk versus low-risk groups was 11.751 (95% CI, 5.110-27.021; P < 0.001) in the validation cohort. In conclusion, the miRNA-based model is reliable and accurate for the early prediction of LNM in patients with HCC.

Risk Prediction of New Adjacent Vertebral Fractures After PVP for Patients with Vertebral Compression Fractures: Development of a Prediction Model

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

Zhong, Bin-Yan; He, Shi-Cheng; Zhu, Hai-Dong

PurposeWe aim to determine the predictors of new adjacent vertebral fractures (AVCFs) after percutaneous vertebroplasty (PVP) in patients with osteoporotic vertebral compression fractures (OVCFs) and to construct a risk prediction score to estimate a 2-year new AVCF risk-by-risk factor condition.Materials and MethodsPatients with OVCFs who underwent their first PVP between December 2006 and December 2013 at Hospital A (training cohort) and Hospital B (validation cohort) were included in this study. In training cohort, we assessed the independent risk predictors and developed the probability of new adjacent OVCFs (PNAV) score system using the Cox proportional hazard regression analysis. The accuracy ofmore » this system was then validated in both training and validation cohorts by concordance (c) statistic.Results421 patients (training cohort: n = 256; validation cohort: n = 165) were included in this study. In training cohort, new AVCFs after the first PVP treatment occurred in 33 (12.9%) patients. The independent risk factors were intradiscal cement leakage and preexisting old vertebral compression fracture(s). The estimated 2-year absolute risk of new AVCFs ranged from less than 4% in patients with neither independent risk factors to more than 45% in individuals with both factors.ConclusionsThe PNAV score is an objective and easy approach to predict the risk of new AVCFs.« less

Risk factors and nomogram for pancreatic pseudocysts in chronic pancreatitis: A cohort of 1998 patients.

PubMed

Hao, Lu; Pan, Jun; Wang, Dan; Bi, Ya-Wei; Ji, Jun-Tao; Xin, Lei; Liao, Zhuan; Du, Ting-Ting; Lin, Jin-Huan; Zhang, Di; Zeng, Xiang-Peng; Ye, Bo; Zou, Wen-Bin; Chen, Hui; Xie, Ting; Li, Bai-Rong; Zheng, Zhao-Hong; Hu, Liang-Hao; Li, Zhao-Shen

2017-07-01

Pancreatic pseudocyst is a common complication of chronic pancreatitis. The identification of risk factors and development of a nomogram for pancreatic pseudocysts in chronic pancreatitis patients may contribute to the early diagnosis and intervention of pancreatic pseudocysts. Patients with chronic pancreatitis admitted to our center from January 2000 to December 2013 were enrolled. Cumulative rates of pancreatic pseudocysts after the onset of chronic pancreatitis and after the diagnosis of chronic pancreatitis were calculated. Patients were randomly assigned, in a 2:1 ratio, to the training and validation cohort. Based on the training cohort, risk factors were identified through Cox proportional hazards regression model, and nomogram was developed. Internal and external validations were performed based on the training and validation cohort, respectively. With a total of 1998 patients, pancreatic pseudocysts were detected in 228 (11.41%) patients. Age at the onset of chronic pancreatitis, smoking, and severe acute pancreatitis were identified risk factors for pancreatic pseudocysts development while steatorrhea and pancreatic stones were protective factors. Incorporating these five factors, the nomogram achieved good concordance indexes of 0.735 and 0.628 in the training and validation cohorts, respectively, with well-fitted calibration curves. The nomogram achieved an individualized prediction of pancreatic pseudocysts development in chronic pancreatitis. It may help the early diagnosis and management of pancreatic pseudocysts. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Validation of a contemporary prostate cancer grading system using prostate cancer death as outcome.

PubMed

Berney, Daniel M; Beltran, Luis; Fisher, Gabrielle; North, Bernard V; Greenberg, David; Møller, Henrik; Soosay, Geraldine; Scardino, Peter; Cuzick, Jack

2016-05-10

Gleason scoring (GS) has major deficiencies and a novel system of five grade groups (GS⩽6; 3+4; 4+3; 8; ⩾9) has been recently agreed and included in the WHO 2016 classification. Although verified in radical prostatectomies using PSA relapse for outcome, it has not been validated using prostate cancer death as an outcome in biopsy series. There is debate whether an 'overall' or 'worst' GS in biopsies series should be used. Nine hundred and eighty-eight prostate cancer biopsy cases were identified between 1990 and 2003, and treated conservatively. Diagnosis and grade was assigned to each core as well as an overall grade. Follow-up for prostate cancer death was until 31 December 2012. A log-rank test assessed univariable differences between the five grade groups based on overall and worst grade seen, and using univariable and multivariable Cox proportional hazards. Regression was used to quantify differences in outcome. Using both 'worst' and 'overall' GS yielded highly significant results on univariate and multivariate analysis with overall GS slightly but insignificantly outperforming worst GS. There was a strong correlation with the five grade groups and prostate cancer death. This is the largest conservatively treated prostate cancer cohort with long-term follow-up and contemporary assessment of grade. It validates the formation of five grade groups and suggests that the 'worst' grade is a valid prognostic measure.

The predictive validity of the Two-Tiered Violence Risk Estimates Scale (TTV) in a long-term follow-up of violent offenders.

PubMed

Churcher, Frances P; Mills, Jeremy F; Forth, Adelle E

2016-08-01

Over the past few decades many structured risk appraisal measures have been created to respond to this need. The Two-Tiered Violence Risk Estimates Scale (TTV) is a measure designed to integrate both an actuarial estimate of violence risk with critical risk management indicators. The current study examined interrater reliability and the predictive validity of the TTV in a sample of violent offenders (n = 120) over an average follow-up period of 17.75 years. The TTV was retrospectively scored and compared with the Violence Risk Appraisal Guide (VRAG), the Statistical Information of Recidivism Scale-Revised (SIR-R1), and the Psychopathy Checklist-Revised (PCL-R). Approximately 53% of the sample reoffended violently, with an overall recidivism rate of 74%. Although the VRAG was the strongest predictor of violent recidivism in the sample, the Actuarial Risk Estimates (ARE) scale of the TTV produced a small, significant effect. The Risk Management Indicators (RMI) produced nonsignificant area under the curve (AUC) values for all recidivism outcomes. Comparisons between measures using AUC values and Cox regression showed that there were no statistical differences in predictive validity. The results of this research will be used to inform the validation and reliability literature on the TTV, and will contribute to the overall risk assessment literature. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

QSAR analyses of conformationally restricted 1,5-diaryl pyrazoles as selective COX-2 inhibitors: application of connection table representation of ligands.

PubMed

Prasanna, S; Manivannan, E; Chaturvedi, S C

2005-04-15

As a part of our continuing efforts in discerning the structural and physicochemical requirements for selective COX-2 over COX-1 inhibition among the fused pyrazole ring systems, herein we report the QSAR analyses of the title compounds. The conformational flexibility of the title compounds was examined using a simple connection table representation. The conformational investigation was aided by calculating a connection table parameter called fraction of rotable bonds, b_rotR encompassing the number of rotable bonds and b_count, the number of bonds including implicit hydrogens of each ligand. The hydrophobic and steric correlation of the title compounds towards selective COX-2 inhibition was reported previously in one of our recent publications. In this communication, we attempt to calculate Wang-Ford charges of the non-hydrogen common atoms of AM1 optimized geometries of the title compounds. Owing to the partial conformational flexibility of title compounds, conformationally restricted and unrestricted descriptors were calculated from MOE. Correlation analysis of these 2D, 3D and Wang-Ford charges was accomplished by linear regression analysis. 2D molecular descriptor b_single, 3D molecular descriptors glob, std_dim3 showed significant contribution towards COX-2 inhibitory activity. Balaban J, a connectivity topological index showed a negative and positive contribution towards COX-1 and selective COX-2 over COX-1 inhibition, respectively. Wang-Ford charges calculated on C(7) showed a significant contribution towards COX-1 inhibitory activity whereas charges calculated on C(8) were crucial in governing the selectivity of COX-2 over COX-1 inhibition among these congeners.

Simulation program for estimating statistical power of Cox's proportional hazards model assuming no specific distribution for the survival time.

PubMed

Akazawa, K; Nakamura, T; Moriguchi, S; Shimada, M; Nose, Y

1991-07-01

Small sample properties of the maximum partial likelihood estimates for Cox's proportional hazards model depend on the sample size, the true values of regression coefficients, covariate structure, censoring pattern and possibly baseline hazard functions. Therefore, it would be difficult to construct a formula or table to calculate the exact power of a statistical test for the treatment effect in any specific clinical trial. The simulation program, written in SAS/IML, described in this paper uses Monte-Carlo methods to provide estimates of the exact power for Cox's proportional hazards model. For illustrative purposes, the program was applied to real data obtained from a clinical trial performed in Japan. Since the program does not assume any specific function for the baseline hazard, it is, in principle, applicable to any censored survival data as long as they follow Cox's proportional hazards model.

The importance of extent of choroid plexus cauterization in addition to endoscopic third ventriculostomy for infantile hydrocephalus: a retrospective North American observational study using propensity score-adjusted analysis.

PubMed

Fallah, Aria; Weil, Alexander G; Juraschka, Kyle; Ibrahim, George M; Wang, Anthony C; Crevier, Louis; Tseng, Chi-Hong; Kulkarni, Abhaya V; Ragheb, John; Bhatia, Sanjiv

2017-12-01

OBJECTIVE Combined endoscopic third ventriculostomy (ETC) and choroid plexus cauterization (CPC)-ETV/CPC- is being investigated to increase the rate of shunt independence in infants with hydrocephalus. The degree of CPC necessary to achieve improved rates of shunt independence is currently unknown. METHODS Using data from a single-center, retrospective, observational cohort study involving patients who underwent ETV/CPC for treatment of infantile hydrocephalus, comparative statistical analyses were performed to detect a difference in need for subsequent CSF diversion procedure in patients undergoing partial CPC (describes unilateral CPC or bilateral CPC that only extended from the foramen of Monro [FM] to the atrium on one side) or subtotal CPC (describes CPC extending from the FM to the posterior temporal horn bilaterally) using a rigid neuroendoscope. Propensity scores for extent of CPC were calculated using age and etiology. Propensity scores were used to perform 1) case-matching comparisons and 2) Cox multivariable regression, adjusting for propensity score in the unmatched cohort. Cox multivariable regression adjusting for age and etiology, but not propensity score was also performed as a third statistical technique. RESULTS Eighty-four patients who underwent ETV/CPC had sufficient data to be included in the analysis. Subtotal CPC was performed in 58 patients (69%) and partial CPC in 26 (31%). The ETV/CPC success rates at 6 and 12 months, respectively, were 49% and 41% for patients undergoing subtotal CPC and 35% and 31% for those undergoing partial CPC. Cox multivariate regression in a 48-patient cohort case-matched by propensity score demonstrated no added effect of increased extent of CPC on ETV/CPC survival (HR 0.868, 95% CI 0.422-1.789, p = 0.702). Cox multivariate regression including all patients, with adjustment for propensity score, demonstrated no effect of extent of CPC on ETV/CPC survival (HR 0.845, 95% CI 0.462-1.548, p = 0.586). Cox multivariate regression including all patients, with adjustment for age and etiology, but not propensity score, demonstrated no effect of extent of CPC on ETV/CPC survival (HR 0.908, 95% CI 0.495-1.664, p = 0.755). CONCLUSIONS Using multiple comparative statistical analyses, no difference in need for subsequent CSF diversion procedure was detected between patients in this cohort who underwent partial versus subtotal CPC. Further investigation regarding whether there is truly no difference between partial versus subtotal extent of CPC in larger patient populations and whether further gain in CPC success can be achieved with complete CPC is warranted.

A Review of the Study Designs and Statistical Methods Used in the Determination of Predictors of All-Cause Mortality in HIV-Infected Cohorts: 2002–2011

PubMed Central

Otwombe, Kennedy N.; Petzold, Max; Martinson, Neil; Chirwa, Tobias

2014-01-01

Background Research in the predictors of all-cause mortality in HIV-infected people has widely been reported in literature. Making an informed decision requires understanding the methods used. Objectives We present a review on study designs, statistical methods and their appropriateness in original articles reporting on predictors of all-cause mortality in HIV-infected people between January 2002 and December 2011. Statistical methods were compared between 2002–2006 and 2007–2011. Time-to-event analysis techniques were considered appropriate. Data Sources Pubmed/Medline. Study Eligibility Criteria Original English-language articles were abstracted. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports and any other ineligible articles were excluded. Results A total of 189 studies were identified (n = 91 in 2002–2006 and n = 98 in 2007–2011) out of which 130 (69%) were prospective and 56 (30%) were retrospective. One hundred and eighty-two (96%) studies described their sample using descriptive statistics while 32 (17%) made comparisons using t-tests. Kaplan-Meier methods for time-to-event analysis were commonly used in the earlier period (n = 69, 76% vs. n = 53, 54%, p = 0.002). Predictors of mortality in the two periods were commonly determined using Cox regression analysis (n = 67, 75% vs. n = 63, 64%, p = 0.12). Only 7 (4%) used advanced survival analysis methods of Cox regression analysis with frailty in which 6 (3%) were used in the later period. Thirty-two (17%) used logistic regression while 8 (4%) used other methods. There were significantly more articles from the first period using appropriate methods compared to the second (n = 80, 88% vs. n = 69, 70%, p-value = 0.003). Conclusion Descriptive statistics and survival analysis techniques remain the most common methods of analysis in publications on predictors of all-cause mortality in HIV-infected cohorts while prospective research designs are favoured. Sophisticated techniques of time-dependent Cox regression and Cox regression with frailty are scarce. This motivates for more training in the use of advanced time-to-event methods. PMID:24498313

Validation of the FRAIL scale in Mexican elderly: results from the Mexican Health and Aging Study.

PubMed

Díaz de León González, Enrique; Gutiérrez Hermosillo, Hugo; Martinez Beltran, Jesus Avilio; Chavez, Juan Humberto Medina; Palacios Corona, Rebeca; Salinas Garza, Deborah Patricia; Rodriguez Quintanilla, Karina Alejandra

2016-10-01

The aging population in Latin America is characterized by not optimal conditions for good health, experiencing high burden of comorbidity, which contribute to increase the frequency of frailty; thus, identification should be a priority, to classify patients at high risk to develop its negative consequences. The objective of this analysis was to validate the FRAIL instrument to measure frailty in Mexican elderly population, from the database of the Mexican Health and Aging Study (MHAS). Prospective, population study in Mexico, that included subjects of 60 years and older who were evaluated for the variables of frailty during the year 2001 (first wave of the study). Frailty was measured with the five-item FRAIL scale (fatigue, resistance, ambulation, illnesses, and weight loss). The robust, pre-frail or intermediate, and the frail group were considered when they had zero, one, and at least two components, respectively. Mortality, hospitalizations, falls, and functional dependency were evaluated during 2003 (second wave of the study). Relative risk was calculated for each complications, as well as hazard ratio (for mortality) through Cox regression model and odds ratio with logistic regression (for the rest of the outcomes), adjusted for covariates. The state of frailty was independently associated with mortality, hospitalizations, functional dependency, and falls. The pre-frailty state was only independently associated with hospitalizations, functional dependency, and falls. Frailty measured through the FRAIL scale, is associated with an increase in the rate of mortality, hospitalizations, dependency in activities of daily life, and falls.

Bayesian dynamic regression models for interval censored survival data with application to children dental health.

PubMed

Wang, Xiaojing; Chen, Ming-Hui; Yan, Jun

2013-07-01

Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on event times, which could be hidden from a Cox proportional hazards model. Methodology development for varying coefficient Cox models, however, has been largely limited to right censored data; only limited work on interval censored data has been done. In most existing methods for varying coefficient models, analysts need to specify which covariate coefficients are time-varying and which are not at the time of fitting. We propose a dynamic Cox regression model for interval censored data in a Bayesian framework, where the coefficient curves are piecewise constant but the number of pieces and the jump points are covariate specific and estimated from the data. The model automatically determines the extent to which the temporal dynamics is needed for each covariate, resulting in smoother and more stable curve estimates. The posterior computation is carried out via an efficient reversible jump Markov chain Monte Carlo algorithm. Inference of each coefficient is based on an average of models with different number of pieces and jump points. A simulation study with three covariates, each with a coefficient of different degree in temporal dynamics, confirmed that the dynamic model is preferred to the existing time-varying model in terms of model comparison criteria through conditional predictive ordinate. When applied to a dental health data of children with age between 7 and 12 years, the dynamic model reveals that the relative risk of emergence of permanent tooth 24 between children with and without an infected primary predecessor is the highest at around age 7.5, and that it gradually reduces to one after age 11. These findings were not seen from the existing studies with Cox proportional hazards models.

[Risk factors on the recurrence of ischemic stroke and the establishment of a Cox's regression model].

PubMed

An, Ya-chen; Chen, Yun-xia; Wang, Yu-xun; Zhao, Xiao-jing; Wang, Yan; Zhang, Jiang; Li, Chun-ling; Peng, Yan-bo; Gao, Su-ling; Chang, Li-sha; Zhang, Li; Xue, Xin-hong; Chen, Rui-ying; Wang, Da-li

2011-08-01

To investigate the risk factors and establish the Cox's regression model on the recurrence of ischemic stroke. We retrospectively reviewed consecutive patients with ischemic stroke admitted to the Neurology Department of the Hebei United University Affiliated Hospital between January 1, 2008 and December 31, 2009. Cases had been followed since the onset of ischemic stroke. The follow-up program was finished in June 30, 2010. Kaplan-Meier methods were used to describe the recurrence rate. Monovariant and multivariate Cox's proportional hazard regression model were used to analyze the risk factors associated to the episodes of recurrence. And then, a recurrence model was set up. During the period of follow-up program, 79 cases were relapsed, with the recurrence rates as 12.75% in one year and 18.87% in two years. Monovariant and multivariate Cox's proportional hazard regression model showed that the independent risk factors that were associated with the recurrence appeared to be age (X₁) (RR = 1.025, 95%CI: 1.003 - 1.048), history of hypertension (X₂) (RR = 1.976, 95%CI: 1.014 - 3.851), history of family strokes (X₃) (RR = 2.647, 95%CI: 1.175 - 5.961), total cholesterol amount (X₄) (RR = 1.485, 95%CI: 1.214 - 1.817), ESRS total scores (X₅) (RR = 1.327, 95%CI: 1.057 - 1.666) and progression of the disease (X₆) (RR = 1.889, 95%CI: 1.123 - 3.178). Personal prognosis index (PI) of the recurrence model was as follows: PI = 0.025X₁ + 0.681X₂ + 0.973X₃ + 0.395X₄ + 0.283X₅ + 0.636X₆. The smaller the personal prognosis index was, the lower the recurrence risk appeared, while the bigger the personal prognosis index was, the higher the recurrence risk appeared. Age, history of hypertension, total cholesterol amount, total scores of ESRS, together with the disease progression were the independent risk factors associated with the recurrence episodes of ischemic stroke. Both recurrence model and the personal prognosis index equation were successful constructed.

Methodological comparison of marginal structural model, time-varying Cox regression, and propensity score methods: the example of antidepressant use and the risk of hip fracture.

PubMed

Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H

2016-03-01

Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and the risk of hip fracture. A cohort of patients with a first prescription for antidepressants (SSRI or tricyclic antidepressants) was extracted from the Dutch Mondriaan and Spanish Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria (BIFAP) general practice databases for the period 2001-2009. The net (total) effect of SSRI versus no SSRI on the risk of hip fracture was estimated using time-varying Cox regression, stratification and covariate adjustment using the PS, and MSM. In MSM, censoring was accounted for by inverse probability of censoring weights. The crude hazard ratio (HR) of SSRI use versus no SSRI use on hip fracture was 1.75 (95%CI: 1.12, 2.72) in Mondriaan and 2.09 (1.89, 2.32) in BIFAP. After confounding adjustment using time-varying Cox regression, stratification, and covariate adjustment using the PS, HRs increased in Mondriaan [2.59 (1.63, 4.12), 2.64 (1.63, 4.25), and 2.82 (1.63, 4.25), respectively] and decreased in BIFAP [1.56 (1.40, 1.73), 1.54 (1.39, 1.71), and 1.61 (1.45, 1.78), respectively]. MSMs with stabilized weights yielded HR 2.15 (1.30, 3.55) in Mondriaan and 1.63 (1.28, 2.07) in BIFAP when accounting for censoring and 2.13 (1.32, 3.45) in Mondriaan and 1.66 (1.30, 2.12) in BIFAP without accounting for censoring. In this empirical study, differences between the different methods to control for time-dependent confounding were small. The observed differences in treatment effect estimates between the databases are likely attributable to different confounding information in the datasets, illustrating that adequate information on (time-varying) confounding is crucial to prevent bias. Copyright © 2016 John Wiley & Sons, Ltd.

[HIV/AIDS related mortality in southern Shanxi province and its risk factors].

PubMed

Ning, Shaoping; Xue, Zidong; Wei, Jun; Mu, Shengcai; Xu, Yajuan; Jia, Shaoxian; Qiu, Chao; Xu, Jianqing

2015-03-01

To explore factors influencing mortality rate of HIV/AIDS and to improve the effectiveness of antiretroviral therapy (ART). By means of retrospective cohort study and the AIDS control information system, HIV/AIDS case reports and antiviral treatment information of 4 cities in southern Shanxi province up to end of December 2012 were selected, to calculate the mortality rate and treatment coverage based on further data collected, along with analysis using the Cox proportional hazards survival regression. 4 040 cases confirmed of HIV/AIDS were included in this study. The average age was (36.0 ± 12.9) years, with 65.3% being male, 56.5% being married, 73.5% having junior high school education or lower, 58.4% being peasants, 54.3% with sexually transmitted infection (40.1% were heterosexual, 14.2% were homosexual), and 38.9% were infected via blood transmission (20.2% were former plasma donors, 16.2% blood transfusion or products recipients, 2.4% were injection drug users). Overall mortality decreased from 40.2 per 100 person/year in 2004 to 6.3 per 100 person/year in 2012, with treatment coverage concomitantly increasing from almost 14.8% to 63.4%. Cox proportional hazards survival regression was used on 4 040 qualified cases, demonstrating the top mortality risk factor was without antiretroviral therapy (RR = 14.9, 95% CI: 12.7-17.4). Cox proportional hazards survival regression was made on 1 938 cases of antiviral treatment, demonstrating that the mortality risk of underweight or obese before treatment was higher than those of normal and overweight cases (RR = 2.7, 95% CI: 1.6-4.5), and the mortality of those having a CD4(+) T-lymphocyte count ≤ 50 cells per µl before treatment was more than 50 cases (RR = 2.6, 95% CI: 1.5-4.5); Cox proportional hazards survival regression was made on 2 102 cases of untreated cases, demonstrating the mortality risk of those initially diagnosed as AIDS was higher than those initially diagnosed as HIV (RR = 3.4, 95% CI: 2.9-4.0). The ART could successfully make lower HIV/AIDS mortality rate, indicating effective ART can further decrease mortality.

Optimizing the time-frame for the definition of bleeding-related death after acute variceal bleeding in cirrhosis.

PubMed

Merkel, C; Gatta, A; Bellumat, A; Bolognesi, M; Borsato, L; Caregaro, L; Cavallarin, G; Cielo, R; Cristina, P; Cucci, E; Donada, C; Donadon, V; Enzo, E; Martin, R; Mazzaro, C; Sacerdoti, D; Torboli, P

1996-01-01

To identify the best time-frame for defining bleeding-related death after variceal bleeding in patients with cirrhosis. Prospective long-term evaluation of a cohort of 155 patients admitted with variceal bleeding. Eight medical departments in seven hospitals in north-eastern Italy. Non-linear regression analysis of a hazard curve for death, and Cox's multiple regression analyses using different zero-time points. Cumulative hazard plots gave two slopes, the first corresponding to the risk of death from acute bleeding, the second a baseline risk of death. The first 30 days were outside the confidence limits of the regression curve for the baseline risk of death. Using Cox's regression analysis, the significant predictors of overall mortality risk were balanced between factors related to severity of bleeding and those related to severity of liver disease. If only deaths occurring after 30 days were considered, only predictors related to the severity of liver disease were found to be of importance. Thirty days after bleeding is considered to be a reasonable time-frame for the definition of bleeding-related death in patients with cirrhosis and variceal bleeding.

Using instrumental variables to estimate a Cox's proportional hazards regression subject to additive confounding

PubMed Central

Tosteson, Tor D.; Morden, Nancy E.; Stukel, Therese A.; O'Malley, A. James

2014-01-01

The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival. PMID:25506259

Using instrumental variables to estimate a Cox's proportional hazards regression subject to additive confounding.

PubMed

MacKenzie, Todd A; Tosteson, Tor D; Morden, Nancy E; Stukel, Therese A; O'Malley, A James

2014-06-01

The estimation of treatment effects is one of the primary goals of statistics in medicine. Estimation based on observational studies is subject to confounding. Statistical methods for controlling bias due to confounding include regression adjustment, propensity scores and inverse probability weighted estimators. These methods require that all confounders are recorded in the data. The method of instrumental variables (IVs) can eliminate bias in observational studies even in the absence of information on confounders. We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival.

Outlier identification in urban soils and its implications for identification of potential contaminated land

NASA Astrophysics Data System (ADS)

Zhang, Chaosheng

2010-05-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with.

Marital status and survival in patients with renal cell carcinoma.

PubMed

Li, Yan; Zhu, Ming-Xi; Qi, Si-Hua

2018-04-01

Previous studies have shown that marital status is an independent prognostic factor for survival in several types of cancer. In this study, we investigated the effects of marital status on survival outcomes among renal cell carcinoma (RCC) patients.We identified patients diagnosed with RCC between 1973 and 2013 from the Surveillance, Epidemiology and End Results (SEER) database. Kaplan-Meier analysis and Cox regression were used to identify the effects of marital status on overall survival (OS) and cancer-specific survival (CSS).We enrolled 97,662 eligible RCC patients, including 64,884 married patients, and 32,778 unmarried (9831 divorced/separated, 9692 widowed, and 13,255 single) patients at diagnosis. The 5-year OS and CSS rates of the married, separated/divorced, widowed, and single patients were 73.7%, 69.5%, 58.3%, and 73.2% (OS), and 82.2%, 80.7%, 75.7%, and 83.3% (CSS), respectively. Multivariate Cox regression showed that, compared with married patients, widowed individuals showed poorer OS (hazard ratio, 1.419; 95% confidence interval, 1.370-1.469) and CSS (hazard ratio, 1.210; 95% confidence interval, 1.144-1.279). Stratified analyses and multivariate Cox regression showed that, in the insured and uninsured groups, married patients had better survival outcomes while widowed patients suffered worse OS outcomes; however, this trend was not significant for CSS.In RCC patients, married patients had better survival outcomes while widowed patients tended to suffer worse survival outcomes in terms of both OS and CSS.

Marital status and survival in patients with renal cell carcinoma

PubMed Central

Li, Yan; Zhu, Ming-xi; Qi, Si-hua

2018-01-01

Abstract Previous studies have shown that marital status is an independent prognostic factor for survival in several types of cancer. In this study, we investigated the effects of marital status on survival outcomes among renal cell carcinoma (RCC) patients. We identified patients diagnosed with RCC between 1973 and 2013 from the Surveillance, Epidemiology and End Results (SEER) database. Kaplan–Meier analysis and Cox regression were used to identify the effects of marital status on overall survival (OS) and cancer-specific survival (CSS). We enrolled 97,662 eligible RCC patients, including 64,884 married patients, and 32,778 unmarried (9831 divorced/separated, 9692 widowed, and 13,255 single) patients at diagnosis. The 5-year OS and CSS rates of the married, separated/divorced, widowed, and single patients were 73.7%, 69.5%, 58.3%, and 73.2% (OS), and 82.2%, 80.7%, 75.7%, and 83.3% (CSS), respectively. Multivariate Cox regression showed that, compared with married patients, widowed individuals showed poorer OS (hazard ratio, 1.419; 95% confidence interval, 1.370–1.469) and CSS (hazard ratio, 1.210; 95% confidence interval, 1.144–1.279). Stratified analyses and multivariate Cox regression showed that, in the insured and uninsured groups, married patients had better survival outcomes while widowed patients suffered worse OS outcomes; however, this trend was not significant for CSS. In RCC patients, married patients had better survival outcomes while widowed patients tended to suffer worse survival outcomes in terms of both OS and CSS. PMID:29668592

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Coastal Storm Surge Analysis: Modeling System Validation. Report 4: Intermediate Submission No. 2.0

DTIC Science & Technology

2013-07-01

Oceanweather Vince Cardone Andrew Cox Wind Field Reconstructions Renaissance Computing Institute (RENCI) Brian Blanton Lisa Stillwell Kevin...Greenwood, V. J. Cardone , and V. R. Swail. 1995. An interactive objective kinematic analysis system. In Proceedings of the 4th International Workshop...A. Cox, V. Cardone , J. Hanson, and B. Blanton. Coastal storm surge analysis: Storm forcing, Submittal 1.3 to FEMA. In preparation. Vicksburg, MS

Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network

PubMed Central

Chiu, Herng-Chia; Ho, Te-Wei; Lee, King-Teh; Chen, Hong-Yaw; Ho, Wen-Hsien

2013-01-01

The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC) patients undergoing resection between artificial neural network (ANN) and logistic regression (LR) models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. We constructed a prognostic model for 434 patients with 21 potential input variables by Cox regression model. Model performance was measured by numbers of significant predictors and predictive accuracy. The results indicated that ANN had double to triple numbers of significant predictors at 1-, 3-, and 5-year survival models as compared with LR models. Scores of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of 1-, 3-, and 5-year survival estimation models using ANN were superior to those of LR in all the training sets and most of the validation sets. The study demonstrated that ANN not only had a great number of predictors of mortality variables but also provided accurate prediction, as compared with conventional methods. It is suggested that physicians consider using data mining methods as supplemental tools for clinical decision-making and prognostic evaluation. PMID:23737707

Prediction of overall survival for metastatic pancreatic cancer: Development and validation of a prognostic nomogram with data from open clinical trial and real-world study.

PubMed

Hang, Junjie; Wu, Lixia; Zhu, Lina; Sun, Zhiqiang; Wang, Ge; Pan, Jingjing; Zheng, Suhua; Xu, Kequn; Du, Jiadi; Jiang, Hua

2018-06-01

It is necessary to develop prognostic tools of metastatic pancreatic cancer (MPC) for optimizing therapeutic strategies. Thus, we tried to develop and validate a prognostic nomogram of MPC. Data from 3 clinical trials (NCT00844649, NCT01124786, and NCT00574275) and 133 Chinese MPC patients were used for analysis. The former 2 trials were taken as the training cohort while NCT00574275 was used as the validation cohort. In addition, 133 MPC patients treated in China were taken as the testing cohort. Cox regression model was used to investigate prognostic factors in the training cohort. With these factors, we established a nomogram and verified it by Harrell's concordance index (C-index) and calibration plots. Furthermore, the nomogram was externally validated in the validation cohort and testing cohort. In the training cohort (n = 445), performance status, liver metastasis, Carbohydrate antigen 19-9 (CA19-9) log-value, absolute neutrophil count (ANC), and albumin were independent prognostic factors for overall survival (OS). A nomogram was established with these factors to predict OS and survival probabilities. The nomogram showed an acceptable discrimination ability (C-index: .683) and good calibration, and was further externally validated in the validation cohort (n = 273, C-index: .699) and testing cohort (n = 133, C-index: .653).The nomogram total points (NTP) had the potential to stratify patients into 3-risk groups with median OS of 11.7, 7.0 and 3.7 months (P < .001), respectively. In conclusion, the prognostic nomogram with NTP can predict OS for patients with MPC with considerable accuracy. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition

PubMed Central

Chagas-Paula, Daniela A.; Zhang, Tong; Da Costa, Fernando B.; Edrada-Ebel, RuAngelie

2015-01-01

The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential for the treatment of several inflammatory diseases, but there is not much investigation reported in the literature for natural products. In this study, 57 leaf extracts (EtOH-H2O 7:3, v/v) from different genera and species of the Asteraceae family were tested against COX-1 and 5-LOX while HPLC-ESI-HRMS analysis of the extracts indicated high diversity in their chemical compositions. Using O2PLS-DA (R2 > 0.92; VIP > 1 and positive Y-correlation values), dual inhibition potential of low-abundance metabolites was determined. The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions. The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action. In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes. PMID:26184333

Non-Steroidal Anti-Inflammatory Drugs and Cardiovascular Outcomes in Women: Results from the Women’s Health Initiative

PubMed Central

Bavry, Anthony A.; Thomas, Fridtjof; Allison, Matthew; Johnson, Karen C.; Howard, Barbara V.; Hlatky, Mark; Manson, JoAnn E.; Limacher, Marian C.

2014-01-01

Background Conclusive data regarding cardiovascular (CV) toxicity of non-steroidal anti-inflammatory drugs (NSAIDs) are sparse. We hypothesized that regular NSAID use is associated with increased risk for CV events in post-menopausal women, and that this association is stronger with greater cyclooxygenase (cox)-2 compared with cox-1 inhibition. Methods and Results Post-menopausal women enrolled in the Women’s Health Initiative (WHI) were classified as regular users or non-users of non-aspirin NSAIDs. Cox regression examined NSAID use as a time-varying covariate and its association with the primary outcome of total CV disease defined as CV death, nonfatal myocardial infarction, or nonfatal stroke. Secondary analyses considered the association of selective cox-2 inhibitors (e.g., celecoxib), non-selective agents with cox-2>cox-1 inhibition (e.g., naproxen), and non-selective agents with cox-1>cox-2 inhibition (e.g., ibuprofen) with the primary outcome. Overall, 160,801 participants were available for analysis (mean follow-up 11.2 years). Regular NSAID use at some point in time was reported by 53,142 participants. Regular NSAID use was associated with an increased hazard for CV events versus no NSAID use (HR=1.10[95% CI 1.06–1.15], Pitalic>0.001). Selective cox-2 inhibitors were associated with a modest increased hazard for CV events (HR=1.13[1.04–1.23], P=0.004; celecoxib only HR=1.13[1.01–1.27], P=0.031). Among aspirin users, concomitant selective cox-2 inhibitor use was no longer associated with increased hazard for CV events. There was an increased risk for agents with cox-2>cox-1 inhibition (HR=1.17[1.10–1.24], Pbold>0.001; naproxen only HR=1.22[1.12–1.34], P<0.001). This harmful association remained among concomitant aspirin users. We did not observe a risk elevation for agents with cox-1>cox-2 inhibition (HR=1.01[0.95–1.07], P=0.884; ibuprofen only HR=1.00[0.93–1.07], P=0.996). Conclusions Regular use of selective cox-2 inhibitors and non-selective NSAIDs with cox-2>cox-1 inhibition showed a modestly increased hazard for CV events. Non-selective agents with cox-1>cox-2 inhibition were not associated with increased CV risk. Clinical Trial Registration www.clinicaltrials.gov NCT00000611 PMID:25006185

Effects of the estrous cycle, pregnancy and interferon tau on expression of cyclooxygenase two (COX-2) in ovine endometrium

PubMed Central

Kim, Seokwoon; Choi, Youngsok; Spencer, Thomas E; Bazer, Fuller W

2003-01-01

In sheep, the uterus produces luteolytic pulses of prostaglandin F2α (PGF) on Days 15 to 16 of estrous cycle to regress the corpus luteum (CL). These PGF pulses are produced by the endometrial lumenal epithelium (LE) and superficial ductal glandular epithelium (sGE) in response to binding of pituitary and/or luteal oxytocin to oxytocin receptors (OTR) and liberation of arachidonic acid, the precursor of PGF. Cyclooxygenase-one (COX-1) and COX-2 are rate-limiting enzymes in PGF synthesis, and COX-2 is the major form expressed in ovine endometrium. During pregnancy recognition, interferon tau (IFNτ), produced by the conceptus trophectoderm, acts in a paracrine manner to suppress development of the endometrial epithelial luteolytic mechanism by inhibiting transcription of estrogen receptor α (ERα) (directly) and OTR (indirectly) genes. Conflicting studies indicate that IFNτ increases, decreases or has no effect on COX-2 expression in bovine and ovine endometrial cells. In Study One, COX-2 mRNA and protein were detected solely in endometrial LE and sGE of both cyclic and pregnant ewes. During the estrous cycle, COX-2 expression increased from Days 10 to 12 and then decreased to Day 16. During early pregnancy, COX-2 expression increased from Days 10 to 12 and remained higher than in cyclic ewes. In Study Two, intrauterine infusion of recombinant ovine IFNτ in cyclic ewes from Days 11 to 16 post-estrus did not affect COX-2 expression in the endometrial epithelium. These results clearly indicate that IFNτ has no effect on expression of the COX-2 gene in the ovine endometrium. Therefore, antiluteolytic effects of IFNτ are to inhibit ERα and OTR gene transcription, thereby preventing endometrial production of luteolytic pulses of PGF. Indeed, expression of COX-2 in the endometrial epithelia as well as conceptus is likely to have a beneficial regulatory role in implantation and development of the conceptus. PMID:12956885

Predicting recidivism in sex offenders with the Psychological Inventory of Criminal Thinking Styles (PICTS).

PubMed

Walters, Glenn D; Deming, Adam; Casbon, Todd

2015-04-01

The purpose of this study was to determine whether the Psychological Inventory of Criminal Thinking Styles (PICTS) was capable of predicting recidivism in 322 male sex offenders released from prison-based sex offender programs in a Midwestern state. The Static-99R and PICTS General Criminal Thinking (GCT), Reactive (R), and Entitlement (En) scores all correlated significantly with general recidivism, the Static-99R correlated significantly with violent recidivism, and the Static-99R score and PICTS GCT, Proactive (P), and En scores correlated significantly with failure to register as a sex offender (FTR) recidivism. Area under the curve effect size estimates varied from small to large, and Cox regression analyses revealed that the PICTS En score achieved incremental validity relative to the Static-99R in predicting general recidivism and the PICTS GCT, P, and En scores achieved incremental validity relative to the Static-99R in predicting FTR recidivism. It is speculated that the PICTS in general and the En scale in particular may have utility in risk management and treatment planning for sex offenders by virtue of their focus on antisocial thinking. © The Author(s) 2014.

Validation of Risk Assessment Models of Venous Thromboembolism in Hospitalized Medical Patients.

PubMed

Greene, M Todd; Spyropoulos, Alex C; Chopra, Vineet; Grant, Paul J; Kaatz, Scott; Bernstein, Steven J; Flanders, Scott A

2016-09-01

Patients hospitalized for acute medical illness are at increased risk for venous thromboembolism. Although risk assessment is recommended and several at-admission risk assessment models have been developed, these have not been adequately derived or externally validated. Therefore, an optimal approach to evaluate venous thromboembolism risk in medical patients is not known. We conducted an external validation study of existing venous thromboembolism risk assessment models using data collected on 63,548 hospitalized medical patients as part of the Michigan Hospital Medicine Safety (HMS) Consortium. For each patient, cumulative venous thromboembolism risk scores and risk categories were calculated. Cox regression models were used to quantify the association between venous thromboembolism events and assigned risk categories. Model discrimination was assessed using Harrell's C-index. Venous thromboembolism incidence in hospitalized medical patients is low (1%). Although existing risk assessment models demonstrate good calibration (hazard ratios for "at-risk" range 2.97-3.59), model discrimination is generally poor for all risk assessment models (C-index range 0.58-0.64). The performance of several existing risk assessment models for predicting venous thromboembolism among acutely ill, hospitalized medical patients at admission is limited. Given the low venous thromboembolism incidence in this nonsurgical patient population, careful consideration of how best to utilize existing venous thromboembolism risk assessment models is necessary, and further development and validation of novel venous thromboembolism risk assessment models for this patient population may be warranted. Published by Elsevier Inc.

Validation of a contemporary prostate cancer grading system using prostate cancer death as outcome

PubMed Central

Berney, Daniel M; Beltran, Luis; Fisher, Gabrielle; North, Bernard V; Greenberg, David; Møller, Henrik; Soosay, Geraldine; Scardino, Peter; Cuzick, Jack

2016-01-01

Background: Gleason scoring (GS) has major deficiencies and a novel system of five grade groups (GS⩽6; 3+4; 4+3; 8; ⩾9) has been recently agreed and included in the WHO 2016 classification. Although verified in radical prostatectomies using PSA relapse for outcome, it has not been validated using prostate cancer death as an outcome in biopsy series. There is debate whether an ‘overall' or ‘worst' GS in biopsies series should be used. Methods: Nine hundred and eighty-eight prostate cancer biopsy cases were identified between 1990 and 2003, and treated conservatively. Diagnosis and grade was assigned to each core as well as an overall grade. Follow-up for prostate cancer death was until 31 December 2012. A log-rank test assessed univariable differences between the five grade groups based on overall and worst grade seen, and using univariable and multivariable Cox proportional hazards. Regression was used to quantify differences in outcome. Results: Using both ‘worst' and ‘overall' GS yielded highly significant results on univariate and multivariate analysis with overall GS slightly but insignificantly outperforming worst GS. There was a strong correlation with the five grade groups and prostate cancer death. Conclusions: This is the largest conservatively treated prostate cancer cohort with long-term follow-up and contemporary assessment of grade. It validates the formation of five grade groups and suggests that the ‘worst' grade is a valid prognostic measure. PMID:27100731

Word Memory Test Predicts Recovery in Claimants With Work-Related Head Injury.

PubMed

Colangelo, Annette; Abada, Abigail; Haws, Calvin; Park, Joanne; Niemeläinen, Riikka; Gross, Douglas P

2016-05-01

To investigate the predictive validity of the Word Memory Test (WMT), a verbal memory neuropsychological test developed as a performance validity measure to assess memory, effort, and performance consistency. Cohort study with 1-year follow-up. Workers' compensation rehabilitation facility. Participants included workers' compensation claimants with work-related head injury (N=188; mean age, 44y; 161 men [85.6%]). Not applicable. Outcome measures for determining predictive validity included days to suspension of wage replacement benefits during the 1-year follow-up and work status at discharge in claimants undergoing rehabilitation. Analysis included multivariable Cox and logistic regression. Better WMT performance was significantly but weakly correlated with younger age (r=-.30), documented brain abnormality (r=.28), and loss of consciousness at the time of injury (r=.25). Claimants with documented brain abnormalities on diagnostic imaging scans performed better (∼9%) on the WMT than those without brain abnormalities. The WMT predicted days receiving benefits (adjusted hazard ratio, 1.13; 95% confidence interval, 1.04-1.24) and work status outcome at program discharge (adjusted odds ratio, 1.62; 95% confidence interval, 1.13-2.34). Our results provide evidence for the predictive validity of the WMT in workers' compensation claimants. Younger claimants and those with more severe brain injuries performed better on the WMT. It may be that financial incentives or other factors related to the compensation claim affected the performance. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Sodium Intake and Osteoporosis. Findings From the Women's Health Initiative.

PubMed

Carbone, Laura; Johnson, Karen C; Huang, Ying; Pettinger, Mary; Thomas, Fridjtof; Cauley, Jane; Crandall, Carolyn; Tinker, Lesley; LeBoff, Meryl Susan; Wactawski-Wende, Jean; Bethel, Monique; Li, Wenjun; Prentice, Ross

2016-04-01

In this large, prospective, observational cohort study of postmenopausal women in the WHI, Cox proportional hazard regression models showed that sodium intake at or near recommended levels is not likely to impact bone metabolism.

An evaluation of treatment strategies for head and neck cancer in an African American population.

PubMed

Ignacio, D N; Griffin, J J; Daniel, M G; Serlemitsos-Day, M T; Lombardo, F A; Alleyne, T A

2013-07-01

This study evaluated treatment strategies for head and neck cancers in a predominantly African American population. Data were collected utilizing medical records and the tumour registry at the Howard University Hospital. Kaplan-Meier method was used for survival analysis and Cox proportional hazards regression analysis predicted the hazard of death. Analysis revealed that the main treatment strategy was radiation combined with platinum for all stages except stage I. Cetuximab was employed in only 1% of cases. Kaplan-Meier analysis revealed stage II patients had poorer outcome than stage IV while Cox proportional hazard regression analysis (p = 0.4662) showed that stage I had a significantly lower hazard of death than stage IV (HR = 0.314; p = 0.0272). Contributory factors included tobacco and alcohol but body mass index (BMI) was inversely related to hazard of death. There was no difference in survival using any treatment modality for African Americans.

Statistical Methodology for the Analysis of Repeated Duration Data in Behavioral Studies.

PubMed

Letué, Frédérique; Martinez, Marie-José; Samson, Adeline; Vilain, Anne; Vilain, Coriandre

2018-03-15

Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. We propose a methodology based on Cox mixed models and written under the R language. This semiparametric model is indeed flexible enough to fit duration data. To compare log-linear and Cox mixed models in terms of goodness-of-fit on real data sets, we also provide a procedure based on simulations and quantile-quantile plots. We present two examples from a data set of speech and gesture interactions, which illustrate the limitations of linear and log-linear mixed models, as compared to Cox models. The linear models are not validated on our data, whereas Cox models are. Moreover, in the second example, the Cox model exhibits a significant effect that the linear model does not. We provide methods to select the best-fitting models for repeated duration data and to compare statistical methodologies. In this study, we show that Cox models are best suited to the analysis of our data set.

Cyclooxygenase 2 gene polymorphisms and chronic periodontitis in a North Indian population: a pilot study

PubMed Central

Daing, Anika; Singh, Sarvendra Vikram; Saimbi, Charanjeet Singh; Khan, Mohammad Akhlaq

2012-01-01

Purpose Cyclooxygenase (COX) enzyme catalyzes the production of prostaglandins, which are important mediators of tissue destruction in periodontitis. Single nucleotide polymorphisms of COX2 enzyme have been associated with increasing susceptibility to inflammatory diseases. The present study evaluates the association of two single nucleotide polymorphisms in COX2 gene (-1195G>A and 8473C>T) with chronic periodontitis in North Indians. Methods Both SNPs and their haplotypes were used to explore the associations between COX2 polymorphisms and chronic periodontitis in 56 patients and 60 controls. Genotyping was done by polymerase chain reaction followed by restriction fragment length polymorphism. Chi-square test and logistic regression analysis were performed for association analysis. Results By the individual genotype analysis, mutant genotypes (GA and AA) of COX2 -1195 showed more than a two fold risk (odds ratio [OR]>2) and COX2 8473 (TC and CC) showed a reduced risk for the disease, but the findings were not statistically significant. Haplotype analysis showed that the frequency of the haplotype AT was higher in the case group and a significant association was found for haplotype AT (OR, 1.79; 95% confidence interval, 1.03 to 3.11; P=0.0370) indicating an association between the AT haplotype of COX2 gene SNPs and chronic periodontitis. Conclusions Individual genotypes of both the SNPs were not associated while haplotype AT was found to be associated with chronic periodontitis in North Indians. PMID:23185695

Quantile regression via vector generalized additive models.

PubMed

Yee, Thomas W

2004-07-30

One of the most popular methods for quantile regression is the LMS method of Cole and Green. The method naturally falls within a penalized likelihood framework, and consequently allows for considerable flexible because all three parameters may be modelled by cubic smoothing splines. The model is also very understandable: for a given value of the covariate, the LMS method applies a Box-Cox transformation to the response in order to transform it to standard normality; to obtain the quantiles, an inverse Box-Cox transformation is applied to the quantiles of the standard normal distribution. The purposes of this article are three-fold. Firstly, LMS quantile regression is presented within the framework of the class of vector generalized additive models. This confers a number of advantages such as a unifying theory and estimation process. Secondly, a new LMS method based on the Yeo-Johnson transformation is proposed, which has the advantage that the response is not restricted to be positive. Lastly, this paper describes a software implementation of three LMS quantile regression methods in the S language. This includes the LMS-Yeo-Johnson method, which is estimated efficiently by a new numerical integration scheme. The LMS-Yeo-Johnson method is illustrated by way of a large cross-sectional data set from a New Zealand working population. Copyright 2004 John Wiley & Sons, Ltd.

A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score

PubMed Central

Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars

2018-01-01

Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359

The TP53 gene polymorphisms and survival of sporadic breast cancer patients.

PubMed

Bišof, V; Salihović, M Peričić; Narančić, N Smolej; Skarić-Jurić, T; Jakić-Razumović, J; Janićijević, B; Rudan, P

2012-06-01

The TP53 gene polymorphisms, Arg72Pro and PIN3 (+16 bp), can have prognostic and predictive value in different cancers including breast cancer. The aim of the present study is to investigate a potential association between different genotypes of these polymorphisms and clinicopathological variables with survival of breast cancer patients in Croatian population. Ninety-four women with sporadic breast cancer were retrospectively analyzed. Median follow-up period was 67.9 months. The effects of basic clinical and histopathological characteristics of tumor on survival were tested by Cox's proportional hazards regression analysis. The TNM stage was associated with overall survival by Kaplan-Meier analysis, univariate, and multivariate Cox's proportional hazards regression analysis, while grade was associated with survival by Kaplan-Meier analysis and univariate Cox's proportional hazards regression analysis. Different genotypes of the Arg72Pro and PIN3 (+16 bp) polymorphisms had no significant impact on survival in breast cancer patients. However, in subgroup of patients treated with chemotherapy without anthracycline, the A2A2 genotype of the PIN3 (+16 bp) polymorphism was associated with poorer overall survival than other genotypes by Kaplan-Meier analysis (P = 0.048). The TP53 polymorphisms, Arg72Pro and PIN3 (+16 bp), had no impact on survival in unselected sporadic breast cancer patients in Croatian population. However, the results support the role of the A2A2 genotype of the PIN3 (+16 bp) polymorphism as a marker for identification of patients that may benefit from anthracycline-containing chemotherapy.

Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

PubMed

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

Does buccal cancer have worse prognosis than other oral cavity cancers?

PubMed

Camilon, P Ryan; Stokes, William A; Fuller, Colin W; Nguyen, Shaun A; Lentsch, Eric J

2014-06-01

To determine whether buccal squamous cell carcinoma has worse overall survival (OS) and disease-specific survival (DSS) than cancers in the rest of the oral cavity. Retrospective analysis of a large population database. We began with a Kaplan-Meier analysis of OS and DSS for buccal versus nonbuccal tumors with unmatched data, followed by an analysis of cases matched for race, age at diagnosis, stage at diagnosis, and treatment modality. This was supported by a univariate Cox regression comparing buccal cancer to nonbuccal cancer, followed by a multivariate Cox regression that included all significant variables studied. With unmatched data, buccal cancer had significantly lesser OS and DSS values than cancers in the rest of the oral cavity (P < .001). After case matching, the differences between OS and DSS for buccal cancer versus nonbuccal oral cancer were no longer significant. Univariate Cox regression models with respect to OS and DSS showed a significant difference between buccal cancer and nonbuccal cancer. However, with multivariate analysis, buccal hazard ratios for OS and DSS were not significant. With the largest series of buccal carcinoma to date, our study concludes that the OS and DSS of buccal cancer are similar to those of cancers in other oral cavity sites once age at diagnosis, tumor stage, treatment, and race are taken into consideration. The previously perceived poor prognosis of buccal carcinoma may be due to variations in tumor presentation, such as later stage and older patient age. 2b. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Assessing the prediction accuracy of cure in the Cox proportional hazards cure model: an application to breast cancer data.

PubMed

Asano, Junichi; Hirakawa, Akihiro; Hamada, Chikuma

2014-01-01

A cure rate model is a survival model incorporating the cure rate with the assumption that the population contains both uncured and cured individuals. It is a powerful statistical tool for prognostic studies, especially in cancer. The cure rate is important for making treatment decisions in clinical practice. The proportional hazards (PH) cure model can predict the cure rate for each patient. This contains a logistic regression component for the cure rate and a Cox regression component to estimate the hazard for uncured patients. A measure for quantifying the predictive accuracy of the cure rate estimated by the Cox PH cure model is required, as there has been a lack of previous research in this area. We used the Cox PH cure model for the breast cancer data; however, the area under the receiver operating characteristic curve (AUC) could not be estimated because many patients were censored. In this study, we used imputation-based AUCs to assess the predictive accuracy of the cure rate from the PH cure model. We examined the precision of these AUCs using simulation studies. The results demonstrated that the imputation-based AUCs were estimable and their biases were negligibly small in many cases, although ordinary AUC could not be estimated. Additionally, we introduced the bias-correction method of imputation-based AUCs and found that the bias-corrected estimate successfully compensated the overestimation in the simulation studies. We also illustrated the estimation of the imputation-based AUCs using breast cancer data. Copyright © 2014 John Wiley & Sons, Ltd.

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

PubMed

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

2016-12-16

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

Validation of the FRAIL scale in Mexican elderly: results from the Mexican Health and Aging Study

PubMed Central

Díaz de León González, Enrique; Gutiérrez Hermosillo, Hugo; Martinez Beltran, Jesus Avilio; Medina Chavez, Juan Humberto; Palacios Corona, Rebeca; Salinas Garza, Deborah Patricia; Rodriguez Quintanilla, Karina Alejandra

2016-01-01

Background The aging population in Latin America is characterized by not optimal conditions for good health, experiencing high burden of comorbidity, which contribute to increase the frequency of frailty; thus, identification should be a priority, to classify patients at high risk to develop its negative consequences. Aim The objective of this analysis was to validate the FRAIL instrument to measure frailty in Mexican elderly population, from the database of the Mexican Health and Aging Study (MHAS). Materials and methods Prospective, population study in Mexico, that included subjects of 60 years and older who were evaluated for the variables of frailty during the year 2001 (first wave of the study). Frailty was measured with the five-item FRAIL scale (fatigue, resistance, ambulation, illnesses, and weight loss). The robust, pre-frail or intermediate, and the frail group were considered when they had zero, one, and at least two components, respectively. Mortality, hospitalizations, falls, and functional dependency were evaluated during 2003 (second wave of the study). Relative risk was calculated for each complications, as well as hazard ratio (for mortality) through Cox regression model and odds ratio with logistic regression (for the rest of the outcomes), adjusted for covariates. Results The state of frailty was independently associated with mortality, hospitalizations, functional dependency, and falls. The pre-frailty state was only independently associated with hospitalizations, functional dependency, and falls. Conclusions Frailty measured through the FRAIL scale, is associated with an increase in the rate of mortality, hospitalizations, dependency in activities of daily life, and falls. PMID:26646253

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Cyclooxygenase-2 inhibitors for non-small-cell lung cancer: A phase II trial and literature review.

PubMed

Yokouchi, Hiroshi; Kanazawa, Kenya; Ishida, Takashi; Oizumi, Satoshi; Shinagawa, Naofumi; Sukoh, Noriaki; Harada, Masao; Ogura, Shigeaki; Munakata, Mitsuru; Dosaka-Akita, Hirotoshi; Isobe, Hiroshi; Nishimura, Masaharu

2014-09-01

Several preclinical and clinical studies have demonstrated that cyclooxygenase-2 (COX-2) inhibitors are efficient for the treatment of non-small-cell lung cancer (NSCLC). However, two recent phase III clinical trials using COX-2 inhibitors in combination with platinum-based chemotherapy failed to demonstrate a survival benefit. Thus, validation and discussion regarding the usefulness of COX-2 inhibitors for patients with NSCLC are required. We conducted a prospective trial using COX-2 inhibitors for the treatment of 50 NSCLC patients accrued between April, 2005 and July, 2006. Patients with untreated advanced NSCLC received oral meloxicam (150 mg daily), carboplatin (area under the curve = 5 mg/ml × min on day 1) and docetaxel (60 mg/m 2 on day 1) every 3 weeks. The primary endpoint was response rate. The response and disease control rates were 36.0 and 76.0%, respectively. The time-to-progression (TTP) and overall survival (OS) were 5.7 months [95% confidence interval (CI): 4.6-6.7] and 13.7 months (95% CI: 11.4-15.9), respectively. The 1-year survival ratio was 56.0%. Grade 3 neuropathy was observed in only 1 patient. We performed tumor immunohistochemistry for COX-2 and p27 and investigated the correlation between their expression and clinical outcome. COX-2 expression in the tumor tended to correlate with a higher response rate (50.0% in the high- and 18.2% in the low-COX-2 group; P=0.092). Based on our results and previous reports, various trial designs, such as the prospective use of COX-2 inhibitors only for patients with COX-2-positive NSCLC, including the exploratory analysis of biomarkers associated with the COX-2 pathway, may be worth further consideration.

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

PubMed

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

2015-08-01

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

Functional polymorphisms of cyclooxygenase-2 (COX-2) gene and risk for esophageal squmaous cell carcinoma.

PubMed

Upadhyay, Rohit; Jain, Meenu; Kumar, Shaleen; Ghoshal, Uday Chand; Mittal, Balraj

2009-04-26

Cyclooxygenase-2 (COX-2) influences carcinogenesis through regulation of angiogenesis, apoptosis and cytokine expression. We aimed to evaluate association of COX-2 polymorphisms with predisposition to esophageal squamous cell carcinoma (ESCC), its phenotype variability and modulation of environmental risk in northern Indian population. We genotyped 174 patients with ESCC and 216 controls for COX-2 gene polymorphisms (-765G>C; -1195G>A; -1290A>G; 3'UTR 8473T>C) using PCR-RFLP. Data were statistically analyzed using chi-square test and logistic regression model. COX-2 -765C allele carriers were at increased risk for ESCC (OR=1.66; 95% CI=1.08-2.54; P=0.004). However, -1195G>A; -1290A>G; 3'UTR 8473T>C polymorphisms of COX-2 gene were not significantly associated with ESCC. We observed significantly enhanced risk for ESCC due to interaction between COX-2 -1195GAx-765GC+CC genotypes (OR=4.60; 95% CI=1.63-13.01; P=0.004). High risk to ESCC was also observed with respect to COX-2 haplotypes, A(-1290)G(-1195)C(-765)T(8473) and A(-1290)A(-1195)C(-765)T(8473) [OR=3.35; 95% CI=0.83-13.44; P=0.089; OR=4.28; 95% CI=0.43-42.40; P=0.246] however, it was not statistically significant. Stratification of subjects based on gender showed that females were at higher risk for ESCC due to COX-2 -765C carrier genotypes (OR=2.97; 95% CI=1.23-7.18; P=0.016). In association of genotypes with clinical characteristics, -765C carrier genotype conferred risk of ESCC in middle third of esophagus (OR=1.78; 95% CI=1.08-2.93; P=0.023). In case-only analysis, interaction of environmental risk factors and COX-2 genotypes did not further modulate the risk for ESCC. In summary, COX-2 -765G>C polymorphism confers ESCC susceptibility particularly in females and patients with middle third anatomical location of the tumor. Interaction of COX-2 -1195GA and -765C carrier genotypes also modulates ESCC risk.

Yonsei nomogram: A predictive model of new-onset chronic kidney disease after on-clamp partial nephrectomy in patients with T1 renal tumors.

PubMed

Abdel Raheem, Ali; Shin, Tae Young; Chang, Ki Don; Santok, Glen Denmer R; Alenzi, Mohamed Jayed; Yoon, Young Eun; Ham, Won Sik; Han, Woong Kyu; Choi, Young Deuk; Rha, Koon Ho

2018-06-19

To develop a predictive nomogram for chronic kidney disease-free survival probability in the long term after partial nephrectomy. A retrospective analysis was carried out of 698 patients with T1 renal tumors undergoing partial nephrectomy at a tertiary academic institution. A multivariable Cox regression analysis was carried out based on parameters proven to have an impact on postoperative renal function. Patients with incomplete data, <12 months follow up and preoperative chronic kidney disease stage III or greater were excluded. The study end-points were to identify independent risk factors for new-onset chronic kidney disease development, as well as to construct a predictive model for chronic kidney disease-free survival probability after partial nephrectomy. The median age was 52 years, median tumor size was 2.5 cm and mean warm ischemia time was 28 min. A total of 91 patients (13.1%) developed new-onset chronic kidney disease at a median follow up of 60 months. The chronic kidney disease-free survival rates at 1, 3, 5 and 10 year were 97.1%, 94.4%, 85.3% and 70.6%, respectively. On multivariable Cox regression analysis, age (1.041, P = 0.001), male sex (hazard ratio 1.653, P < 0.001), diabetes mellitus (hazard ratio 1.921, P = 0.046), tumor size (hazard ratio 1.331, P < 0.001) and preoperative estimated glomerular filtration rate (hazard ratio 0.937, P < 0.001) were independent predictors for new-onset chronic kidney disease. The C-index for chronic kidney disease-free survival was 0.853 (95% confidence interval 0.815-0.895). We developed a novel nomogram for predicting the 5-year chronic kidney disease-free survival probability after on-clamp partial nephrectomy. This model might have an important role in partial nephrectomy decision-making and follow-up plan after surgery. External validation of our nomogram in a larger cohort of patients should be considered. © 2018 The Japanese Urological Association.

Prognosis Related to Metastatic Burden Measured by 18F-Fluorocholine PET/CT in Castrate Resistant Prostate Cancer

PubMed Central

Kwee, Sandi A.; Lim, John; Watanabe, Alex; Kromer-Baker, Kathleen; Coel, Marc N.

2015-01-01

This study investigates the prognostic significance of metabolically active tumor volume (MATV) measurements applied to fluorine-18 fluorocholine (FC) PET/CT in castrate-resistant prostate cancer (CRPC). Methods FC PET/CT imaging was performed in 30 patients with CRPC. Metastatic disease was quantified on the basis of maximum standardized uptake value (SUVmax), MATV, and total lesion activity (TLA = MATV × mean SUV). Tumor burden indices derived from whole-body summation of PET tumor volume measurements (ie. net MATV and net TLA) were evaluated as variables in Cox regression and Kaplan-Meier survival analyses. Results Net MATV ranged from 0.12 cm3 to 1543.9 cm3 (median 52.6 cm3). Net TLA ranged from 0.40g to 6688.7g (median 225.1g). PSA level at the time of PET correlated significantly with net MATV (Pearson r = 0.65, p = 0.0001) and net TLA (r = 0.60, p = 0.0005) but not highest lesional SUVmax of each scan. Survivors were followed for a median 23 months (range 6 – 38 months). On Cox regression analyses, overall survival was significantly associated with net MATV (p = 0.0068), net TLA (p = 0.0072), and highest lesion SUVmax (p = 0.0173), and borderline associated with PSA level (p = 0.0458). Only net MATV and net TLA remained significant in univariate-adjusted survival analyses. Kaplan-Meier analysis demonstrated significant differences in survival between groups stratified by median net MATV (log-rank P = 0.0371), net TLA (log-rank P = 0.0371), and highest lesion SUVmax (log-rank P = 0.0223). Conclusions Metastatic prostate cancer detected by FC PET/CT can be quantified based on volumetric measurements of tumor metabolic activity. The prognostic value of FC PET/CT may stem from this capacity to assess whole-body tumor burden. With further clinical validation, FC PET-based indices of global disease activity and mortality risk could prove useful in patient-individualized treatment of CRPC. PMID:24676753

Increased COX-2 expression in epithelial and stromal cells of high mammographic density tissues and in a xenograft model of mammographic density.

PubMed

Chew, G L; Huo, C W; Huang, D; Hill, P; Cawson, J; Frazer, H; Hopper, J L; Haviv, I; Henderson, M A; Britt, K; Thompson, E W

2015-08-01

Mammographic density (MD) adjusted for age and body mass index is one of the strongest known risk factors for breast cancer. Given the high attributable risk of MD for breast cancer, chemoprevention with a safe and available agent that reduces MD and breast cancer risk would be beneficial. Cox-2 has been implicated in MD-related breast cancer risk, and was increased in stromal cells in high MD tissues in one study. Our study assessed differential Cox-2 expression in epithelial and stromal cells in paired samples of high and low MD human breast tissue, and in a validated xenograft biochamber model of MD. We also examined the effects of endocrine treatment upon Cox-2 expression in high and low MD tissues in the MD xenograft model. Paired high and low MD human breast tissue samples were immunostained for Cox-2, then assessed for differential expression and staining intensity in epithelial and stromal cells. High and low MD human breast tissues were separately maintained in biochambers in mice treated with Tamoxifen, oestrogen or placebo implants, then assessed for percentage Cox-2 staining in epithelial and stromal cells. Percentage Cox-2 staining was greater for both epithelial (p = 0.01) and stromal cells (p < 0.0001) of high compared with low MD breast tissues. In high MD biochamber tissues, percentage Cox-2 staining was greater in stromal cells of oestrogen-treated versus placebo-treated tissues (p = 0.05).

Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer.

PubMed

Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro

2015-12-01

In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. Copyright © 2015. Published by Elsevier Ltd.

Immunosensors for quantifying cyclooxygenase 2 pain biomarkers.

PubMed

Noah, Naumih M; Mwilu, Samuel K; Sadik, Omowunmi A; Fatah, Alim A; Arcilesi, Richard D

2011-07-15

Cyclooxygenase 2 (COX-2) is a key enzyme in pain biomarkers, inflammation and cancer cell proliferation. Thus biosensors that can quantify pain mediators based on biochemical mechanism are imperative. Biomolecular recognition and affinity of antigenic COX-2 with the antibody were investigated using surface plasmon resonance (SPR) and ultra-sensitive portable capillary (UPAC) fluorescence sensors. Polyclonal goat anti-COX-2 (human) antibodies were covalently immobilized on gold SPR surface and direct recognition for the COX-2 antigen assessed. The UPAC sensor utilized an indirect sandwich design involving covalently attached goat anti-COX-2 as the capture antibody and rabbit anti-COX-2 (human) antibody as the secondary antibody. UPAC fluorescence signals were directly proportional to COX-2 at a linear range of 7.46×10⁻⁴-7.46×10¹ ng/ml with detection limit of 1.02×10⁻⁴ ng/ml. With SPR a linear range was 3.64×10⁻⁴-3.64×10² ng/ml was recorded and a detection limit of 1.35×10⁻⁴ ng/ml. Validation was achieved in simulated blood samples with percent recoveries of 81.39% and 87.23% for SPR and UPAC respectively. The developed sensors have the potential to provide objective characterization of pain biomarkers for clinical diagnoses. Copyright © 2011 Elsevier B.V. All rights reserved.

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

NASA Astrophysics Data System (ADS)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

The influence of sarcopenia on survival and surgical complications in ovarian cancer patients undergoing primary debulking surgery.

PubMed

Rutten, I J G; Ubachs, J; Kruitwagen, R F P M; van Dijk, D P J; Beets-Tan, R G H; Massuger, L F A G; Olde Damink, S W M; Van Gorp, T

2017-04-01

Sarcopenia, severe skeletal muscle loss, has been identified as a prognostic factor in various malignancies. This study aims to investigate whether sarcopenia is associated with overall survival (OS) and surgical complications in patients with advanced ovarian cancer undergoing primary debulking surgery (PDS). Ovarian cancer patients (n = 216) treated with PDS were enrolled retrospectively. Total skeletal muscle surface area was measured on axial computed tomography at the level of the third lumbar vertebra. Optimum stratification was used to find the optimal skeletal muscle index cut-off to define sarcopenia (≤38.73 cm 2 /m 2 ). Cox-regression and Kaplan-Meier analysis were used to analyse the relationship between sarcopenia and OS. The effect of sarcopenia on the development of major surgical complications was studied with logistic regression. Kaplan-Meier analysis showed a significant survival disadvantage for patients with sarcopenia compared to patients without sarcopenia (p = 0.010). Sarcopenia univariably predicted OS (HR 1.536 (95% CI 1.105-2.134), p = 0.011) but was not significant in multivariable Cox-regression analysis (HR 1.362 (95% CI 0.968-1.916), p = 0.076). Significant predictors for OS in multivariable Cox-regression analysis were complete PDS, treatment in a specialised centre and the development of major complications. Sarcopenia was not predictive of major complications. Sarcopenia was not predictive of OS or major complications in ovarian cancer patients undergoing primary debulking surgery. However a strong trend towards a survival disadvantage for patients with sarcopenia was seen. Future prospective studies should focus on interventions to prevent or reverse sarcopenia and possibly increase ovarian cancer survival. Complete cytoreduction remains the strongest predictor of ovarian cancer survival. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Circulating Tumor Cell Counts Are Prognostic of Overall Survival in SWOG S0421: A Phase III Trial of Docetaxel With or Without Atrasentan for Metastatic Castration-Resistant Prostate Cancer

PubMed Central

Goldkorn, Amir; Ely, Benjamin; Quinn, David I.; Tangen, Catherine M.; Fink, Louis M.; Xu, Tong; Twardowski, Przemyslaw; Van Veldhuizen, Peter J.; Agarwal, Neeraj; Carducci, Michael A.; Monk, J. Paul; Datar, Ram H.; Garzotto, Mark; Mack, Philip C.; Lara, Primo; Higano, Celestia S.; Hussain, Maha; Thompson, Ian Murchie; Cote, Richard J.; Vogelzang, Nicholas J.

2014-01-01

Purpose Circulating tumor cell (CTC) enumeration has not been prospectively validated in standard first-line docetaxel treatment for metastatic castration-resistant prostate cancer. We assessed the prognostic value of CTCs for overall survival (OS) and disease response in S0421, a phase III trial of docetaxel plus prednisone with or without atrasentan. Patients and Methods CTCs were enumerated at baseline (day 0) and before cycle two (day 21) using CellSearch. Baseline counts and changes in counts from day 0 to 21 were evaluated for association with OS, prostate-specific antigen (PSA), and RECIST response using Cox regression as well as receiver operator characteristic (ROC) curves, integrated discrimination improvement (IDI) analysis, and regression trees. Results Median day-0 CTC count was five cells per 7.5 mL, and CTCs < versus ≥ five per 7.5 mL were significantly associated with baseline PSA, bone pain, liver disease, hemoglobin, alkaline phosphatase, and subsequent PSA and RECIST response. Median OS was 26 months for < five versus 13 months for ≥ five CTCs per 7.5 mL at day 0 (hazard ratio [HR], 2.74 [adjusting for covariates]). ROC curves had higher areas under the curve for day-0 CTCs than for PSA, and IDI analysis showed that adding day-0 CTCs to baseline PSA and other covariates increased predictive accuracy for survival by 8% to 10%. Regression trees yielded new prognostic subgroups, and rising CTC count from day 0 to 21 was associated with shorter OS (HR, 2.55). Conclusion These data validate the prognostic utility of CTC enumeration in a large docetaxel-based prospective cohort. Baseline CTC counts were prognostic, and rising CTCs at 3 weeks heralded significantly worse OS, potentially serving as an early metric to help redirect and optimize therapy in this clinical setting. PMID:24616308

Circulating tumor cell counts are prognostic of overall survival in SWOG S0421: a phase III trial of docetaxel with or without atrasentan for metastatic castration-resistant prostate cancer.

PubMed

Goldkorn, Amir; Ely, Benjamin; Quinn, David I; Tangen, Catherine M; Fink, Louis M; Xu, Tong; Twardowski, Przemyslaw; Van Veldhuizen, Peter J; Agarwal, Neeraj; Carducci, Michael A; Monk, J Paul; Datar, Ram H; Garzotto, Mark; Mack, Philip C; Lara, Primo; Higano, Celestia S; Hussain, Maha; Thompson, Ian Murchie; Cote, Richard J; Vogelzang, Nicholas J

2014-04-10

Circulating tumor cell (CTC) enumeration has not been prospectively validated in standard first-line docetaxel treatment for metastatic castration-resistant prostate cancer. We assessed the prognostic value of CTCs for overall survival (OS) and disease response in S0421, a phase III trial of docetaxel plus prednisone with or without atrasentan. CTCs were enumerated at baseline (day 0) and before cycle two (day 21) using CellSearch. Baseline counts and changes in counts from day 0 to 21 were evaluated for association with OS, prostate-specific antigen (PSA), and RECIST response using Cox regression as well as receiver operator characteristic (ROC) curves, integrated discrimination improvement (IDI) analysis, and regression trees. Median day-0 CTC count was five cells per 7.5 mL, and CTCs < versus ≥ five per 7.5 mL were significantly associated with baseline PSA, bone pain, liver disease, hemoglobin, alkaline phosphatase, and subsequent PSA and RECIST response. Median OS was 26 months for < five versus 13 months for ≥ five CTCs per 7.5 mL at day 0 (hazard ratio [HR], 2.74 [adjusting for covariates]). ROC curves had higher areas under the curve for day-0 CTCs than for PSA, and IDI analysis showed that adding day-0 CTCs to baseline PSA and other covariates increased predictive accuracy for survival by 8% to 10%. Regression trees yielded new prognostic subgroups, and rising CTC count from day 0 to 21 was associated with shorter OS (HR, 2.55). These data validate the prognostic utility of CTC enumeration in a large docetaxel-based prospective cohort. Baseline CTC counts were prognostic, and rising CTCs at 3 weeks heralded significantly worse OS, potentially serving as an early metric to help redirect and optimize therapy in this clinical setting.

The role of chemoprevention by selective cyclooxygenase-2 inhibitors in colorectal cancer patients - a population-based study

PubMed Central

2012-01-01

Background There are limited population-based studies focusing on the chemopreventive effects of selective cyclooxygenase-2 (COX-2) inhibitors against colorectal cancer. The purpose of this study is to assess the trends and dose–response effects of various medication possession ratios (MPR) of selective COX-2 inhibitor used for chemoprevention of colorectal cancer. Methods A population-based case–control study was conducted using the Taiwan Health Insurance Research Database (NHIRD). The study comprised 21,460 colorectal cancer patients and 79,331 controls. The conditional logistic regression was applied to estimate the odds ratios (ORs) for COX-2 inhibitors used for several durations (5 years, 3 years, 1 year, 6 months and 3 months) prior to the index date. Results In patients receiving selective COX-2 inhibitors, the OR was 0.51 (95% CI=0.29~0.90, p=0.021) for an estimated 5-year period in developing colorectal cancer. ORs showing significant protection effects were found in 10% of MPRs for 5-year, 3-year, and 1-year usage. Risk reduction against colorectal cancer by selective COX-2 inhibitors was observed as early as 6 months after usage. Conclusion Our results indicate that selective COX-2 inhibitors may reduce the development of colorectal cancer by at least 10% based on the MPRs evaluated. Given the limited number of clinical reports from general populations, our results add to the knowledge of chemopreventive effects of selective COX-2 inhibitors against cancer in individuals at no increased risk of colorectal cancer. PMID:23217168

Combining Gene Signatures Improves Prediction of Breast Cancer Survival

PubMed Central

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

2011-01-01

Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast cancer survival. The presented methodology is broadly applicable to breast cancer risk assessment using any new identified gene set. PMID:21423775

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

A Linguistic Inquiry and Word Count Analysis of the Adult Attachment Interview in Two Large Corpora.

PubMed

Waters, Theodore E A; Steele, Ryan D; Roisman, Glenn I; Haydon, Katherine C; Booth-LaForce, Cathryn

2016-01-01

An emerging literature suggests that variation in Adult Attachment Interview (AAI; George, Kaplan, & Main, 1985) states of mind about childhood experiences with primary caregivers is reflected in specific linguistic features captured by the Linguistic Inquiry Word Count automated text analysis program (LIWC; Pennebaker, Booth, & Francis, 2007). The current report addressed limitations of prior studies in this literature by using two large AAI corpora ( N s = 826 and 857) and a broader range of linguistic variables, as well as examining associations of LIWC-derived AAI dimensions with key developmental antecedents. First, regression analyses revealed that dismissing states of mind were associated with transcripts that were more truncated and deemphasized discussion of the attachment relationship whereas preoccupied states of mind were associated with longer, more conflicted, and angry narratives. Second, in aggregate, LIWC variables accounted for over a third of the variation in AAI dismissing and preoccupied states of mind, with regression weights cross-validating across samples. Third, LIWC-derived dismissing and preoccupied state of mind dimensions were associated with direct observations of maternal and paternal sensitivity as well as infant attachment security in childhood, replicating the pattern of results reported in Haydon, Roisman, Owen, Booth-LaForce, and Cox (2014) using coder-derived dismissing and preoccupation scores in the same sample.

Low-dose aspirin, non-steroidal anti-inflammatory drugs, selective COX-2 inhibitors and breast cancer recurrence

PubMed Central

Cronin-Fenton, Deirdre P; Heide-Jørgensen, Uffe; Ahern, Thomas P; Lash, Timothy L; Christiansen, Peer; Ejlertsen, Bent; Sørensen, Henrik T

2017-01-01

Background Aspirin, non-steroidal anti-inflammatory drugs (NSAIDs), and selective COX-2 inhibitors may improve outcomes in breast cancer patients. We investigated the association of aspirin, NSAIDs, and use of selective COX-2 inhibitors with breast cancer recurrence. Methods We identified incident stage I–III Danish breast cancer patients in the Danish Breast Cancer Cooperative Group registry, who were diagnosed during 1996–2008. Prescriptions for aspirin (>99% low-dose aspirin), NSAIDs, and selective COX-2 inhibitors were ascertained from the National Prescription Registry (NPR). Follow-up began on the date of breast cancer primary surgery and continued until the first of recurrence, death, emigration, or 01/01/2013. We used Cox regression models to compute hazard ratios (HR) and corresponding 95% confidence intervals (95%CI) associating prescriptions with recurrence, adjusting for confounders. Results We identified 34,188 breast cancer patients with 233,130 person-years of follow-up. Median follow-up was 7.1 years; 5,325 patients developed recurrent disease. Use of aspirin, NSAIDs, or selective COX-2 inhibitors was not associated with the rate of recurrence (HRadjusted aspirin=1.0, 95% CI=0.90, 1.1; NSAIDs=0.99, 95% CI=0.92, 1.1; selective COX-2 inhibitors=1.1, 95% CI=0.98, 1.2), relative to non-use. Pre-diagnostic use of the exposure drugs was associated with reduced recurrence rates (HRaspirin=0.92, 95%CI=0.82, 1.0; HRNSAIDs=0.86, 95%CI=0.81, 0.91; HRsCOX-2inhibitors=0.88, 95%CI=0.83, 0.95). Conclusions This prospective cohort study suggests that post-diagnostic prescriptions for aspirin, NSAIDs, and selective COX-2 inhibitors have little or no association with the rate of breast cancer recurrence. Pre-diagnostic use of the drugs was, however, associated with a reduced rate of breast cancer recurrence. PMID:27007644

Anti-inflammatory use may not negatively impact oncologic outcomes following intravesical BCG for high-grade non-muscle-invasive bladder cancer.

PubMed

Singla, Nirmish; Haddad, Ahmed Q; Passoni, Niccolo M; Meissner, Matthew; Lotan, Yair

2017-01-01

To evaluate whether anti-inflammatory agents affect outcomes in patients receiving intravesical BCG therapy for high-grade (HG) non-muscle-invasive bladder cancer (NMIBC). We reviewed the records of 203 patients in a prospective database of HG NMIBC from 2006 to 2012 at a single institution. Patients who had muscle-invasive disease (n = 32), low-grade pathology (n = 4), underwent early cystectomy within 3 months (n = 25), had <3 months of follow-up (n = 11), or did not receive an induction course of intravesical BCG (n = 32) were excluded. Clinicopathologic data were tabulated including demographics, comorbidities, pathologic stage and grades, intravesical therapy, and concomitant use of aspirin, NSAIDs, COX inhibitors, and statins. Multivariate Cox regression analysis explored predictive factors for recurrence, progression (stage progression or progression to cystectomy), cancer-specific survival (CSS), and overall survival (OS). Ninety-nine patients with HG NMIBC who received at least one induction course of intravesical BCG were identified, with median follow-up of 31.4 months. There were 20 (20.2 %) deaths, including 6 (6.1 %) patients with bladder cancer-related mortality. 13 % patients experienced tumor progression and 27 % underwent cystectomy following failure of intravesical therapy. Anti-inflammatory use included statins (65 %), aspirin (63 %), or non-aspirin NSAIDs/COX inhibitors (26 %). Anti-inflammatory use was not significantly predictive of recurrence, progression, or mortality outcomes on Cox regression. CIS stage was associated with higher progression, while age, BMI, and Charlson score were independent predictors of overall mortality. Despite speculation of inhibitory effects on BCG immunomodulation there was no evidence that anti-inflammatory agents impacted oncologic outcomes in patients receiving BCG for HG NMIBC.

Prognostic Impact of Neutrophil/Lymphocyte Ratio, Platelet Count, CRP, and Albumin Levels in Metastatic Colorectal Cancer Patients Treated with FOLFIRI-Bevacizumab.

PubMed

Artaç, Mehmet; Uysal, Mükremin; Karaağaç, Mustafa; Korkmaz, Levent; Er, Zehra; Güler, Tunç; Börüban, Melih Cem; Bozcuk, Hakan

2017-06-01

Metastatic colorectal cancer (mCRC) is a lethal disease and fluorouracil-leucovorin-irinotecan (FOLFIRI) plus bevacizumab (bev) is a standard approach. Hence, there is a strong need for identifying new prognostic factors to show the efficacy of FOLFIRI-bev. This is a retrospective study including patients (n = 90) with mCRC from two centers in Turkey. Neutrophil/lymphocyte (N/L) ratio, platelet count, albumin, and C-reactive protein (CRP) were recorded before FOLFIRI-bev therapy. The efficacy of these factors on progression-free survival (PFS) was analyzed with Kaplan Meier and Cox regression analysis. And the cutoff value of N/L ratio was analyzed with ROC analysis. The median age was 56 years (range 21-80). Forty-seven percent of patients with N/L ratio >2.5 showed progressive disease versus 43 % in patients with N/L ratio <2.5 (p = 0.025). The median PFS was 8.1 months for the patients with N/L ratio >2.5 versus 13.5 months for the patients with N/L ratio <2.5 (p = 0.025). At univariate Cox regression analysis, high baseline neutrophil count, LDH, N/L ratio, and CRP were all significantly associated with poor prognosis. At multivariate Cox regression analysis, CRP was confirmed to be a better independent prognostic factor. CRP variable was divided into above the upper limit of normal (ULN) and normal value. The median PFSs of the patients with normal and above ULN were 11.3 versus 5.8 months, respectively (p = 0.022). CRP and N/L ratio are potential predictors for advanced mCRC treated with FOLFIRI-bev.

Long-term allopurinol use decreases the risk of prostate cancer in patients with gout: a population-based study.

PubMed

Shih, H-J; Kao, M-C; Tsai, P-S; Fan, Y-C; Huang, C-J

2017-09-01

Clinical observations indicated an increased risk of developing prostate cancer in gout patients. Chronic inflammation is postulated to be one crucial mechanism for prostate carcinogenesis. Allopurinol, a widely used antigout agent, possesses potent anti-inflammation capacity. We elucidated whether allopurinol decreases the risk of prostate cancer in gout patients. We analyzed data retrieved from Taiwan National Health Insurance Database between January 2000 and December 2012. Patients diagnosed with gout during the study period with no history of prostate cancer and who had never used allopurinol were selected. Four allopurinol use cohorts (that is, allopurinol use (>365 days), allopurinol use (181-365 days), allopurinol use (91-180 days) and allopurinol use (31-90 days)) and one cohort without using allopurinol (that is, allopurinol use (No)) were included. The study end point was the diagnosis of new-onset prostate cancer. Multivariable Cox proportional hazards regression and propensity score-adjusted Cox regression models were used to estimate the association between the risk of prostate cancer and allopurinol treatment in gout patients after adjusting for potential confounders. A total of 25 770 gout patients (aged between 40 and 100 years) were included. Multivariable Cox regression analyses revealed that the risk of developing prostate cancer in the allopurinol use (>365 days) cohort was significantly lower than the allopurinol use (No) cohort (adjusted hazard ratio (HR)=0.64, 95% confidence interval (CI)=0.45-0.9, P=0.011). After propensity score adjustment, the trend remained the same (adjusted HR=0.66, 95% CI=0.46-0.93, P=0.019). Long-term (more than 1 year) allopurinol use may associate with a decreased risk of prostate cancer in gout patients.

Birth by Caesarean Section and the Risk of Adult Psychosis: A Population-Based Cohort Study

PubMed Central

O’Neill, Sinéad M.; Curran, Eileen A.; Dalman, Christina; Kenny, Louise C.; Kearney, Patricia M.; Clarke, Gerard; Cryan, John F.; Dinan, Timothy G.; Khashan, Ali S.

2016-01-01

Despite the biological plausibility of an association between obstetric mode of delivery and psychosis in later life, studies to date have been inconclusive. We assessed the association between mode of delivery and later onset of psychosis in the offspring. A population-based cohort including data from the Swedish National Registers was used. All singleton live births between 1982 and 1995 were identified (n = 1 345 210) and followed-up to diagnosis at age 16 or later. Mode of delivery was categorized as: unassisted vaginal delivery (VD), assisted VD, elective Caesarean section (CS) (before onset of labor), and emergency CS (after onset of labor). Outcomes included any psychosis; nonaffective psychoses (including schizophrenia only) and affective psychoses (including bipolar disorder only and depression with psychosis only). Cox regression analysis was used reporting partially and fully adjusted hazard ratios (HR) with 95% confidence intervals (CI). Sibling-matched Cox regression was performed to adjust for familial confounding factors. In the fully adjusted analyses, elective CS was significantly associated with any psychosis (HR 1.13, 95% CI 1.03, 1.24). Similar findings were found for nonaffective psychoses (HR 1.13, 95% CI 0.99, 1.29) and affective psychoses (HR 1.17, 95% CI 1.05, 1.31) (χ2 for heterogeneity P = .69). In the sibling-matched Cox regression, this association disappeared (HR 1.03, 95% CI 0.78, 1.37). No association was found between assisted VD or emergency CS and psychosis. This study found that elective CS is associated with an increase in offspring psychosis. However, the association did not persist in the sibling-matched analysis, implying the association is likely due to familial confounding by unmeasured factors such as genetics or environment. PMID:26615187

A comparison between standard methods and structural nested modelling when bias from a healthy worker survivor effect is suspected: an iron-ore mining cohort study.

PubMed

Björ, Ove; Damber, Lena; Jonsson, Håkan; Nilsson, Tohr

2015-07-01

Iron-ore miners are exposed to extremely dusty and physically arduous work environments. The demanding activities of mining select healthier workers with longer work histories (ie, the Healthy Worker Survivor Effect (HWSE)), and could have a reversing effect on the exposure-response association. The objective of this study was to evaluate an iron-ore mining cohort to determine whether the effect of respirable dust was confounded by the presence of an HWSE. When an HWSE exists, standard modelling methods, such as Cox regression analysis, produce biased results. We compared results from g-estimation of accelerated failure-time modelling adjusted for HWSE with corresponding unadjusted Cox regression modelling results. For all-cause mortality when adjusting for the HWSE, cumulative exposure from respirable dust was associated with a 6% decrease of life expectancy if exposed ≥15 years, compared with never being exposed. Respirable dust continued to be associated with mortality after censoring outcomes known to be associated with dust when adjusting for the HWSE. In contrast, results based on Cox regression analysis did not support that an association was present. The adjustment for the HWSE made a difference when estimating the risk of mortality from respirable dust. The results of this study, therefore, support the recommendation that standard methods of analysis should be complemented with structural modelling analysis techniques, such as g-estimation of accelerated failure-time modelling, to adjust for the HWSE. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Sodium Valproate, a Histone Deacetylase Inhibitor, Is Associated With Reduced Stroke Risk After Previous Ischemic Stroke or Transient Ischemic Attack.

PubMed

Brookes, Rebecca L; Crichton, Siobhan; Wolfe, Charles D A; Yi, Qilong; Li, Linxin; Hankey, Graeme J; Rothwell, Peter M; Markus, Hugh S

2018-01-01

A variant in the histone deacetylase 9 ( HDAC9 ) gene is associated with large artery stroke. Therefore, inhibiting HDAC9 might offer a novel secondary preventative treatment for ischemic stroke. The antiepileptic drug sodium valproate (SVA) is a nonspecific inhibitor of HDAC9. We tested whether SVA therapy given after ischemic stroke was associated with reduced recurrent stroke rate. Data were pooled from 3 prospective studies recruiting patients with previous stroke or transient ischemic attack and long-term follow-up: the South London Stroke Register, The Vitamins to Prevent Stroke Study, and the Oxford Vascular Study. Patients receiving SVA were compared with patients who received antiepileptic drugs other than SVA using survival analysis and Cox Regression. A total of 11 949 patients with confirmed ischemic event were included. Recurrent stroke rate was lower in patient taking SVA (17 of 168) than other antiepileptic drugs (105 of 530; log-rank survival analysis P =0.002). On Cox regression, controlling for potential cofounders, SVA remained associated with reduced stroke (hazard ratio=0.44; 95% confidence interval: 0.3-0.7; P =0.002). A similar result was obtained when patients taking SVA were compared with all cases not taking SVA (Cox regression, hazard ratio=0.47; 95% confidence interval: 0.29-0.77; P =0.003). These results suggest that exposure to SVA, an inhibitor of HDAC, may be associated with a lower recurrent stroke risk although we cannot exclude residual confounding in this study design. This supports the hypothesis that HDAC9 is important in the ischemic stroke pathogenesis and that its inhibition, by SVA or a more specific HDAC9 inhibitor, is worthy of evaluation as a treatment to prevent recurrent ischemic stroke. © 2017 The Authors.

Racial differences in the outcome of patients with urothelial carcinoma of the upper urinary tract: an international study.

PubMed

Matsumoto, Kazumasa; Novara, Giacomo; Gupta, Amit; Margulis, Vitaly; Walton, Thomas J; Roscigno, Marco; Ng, Casey; Kikuchi, Eiji; Zigeuner, Richard; Kassouf, Wassim; Fritsche, Hans-Martin; Ficarra, Vincenzo; Martignoni, Guido; Tritschler, Stefan; Rodriguez, Joaquin Carballido; Seitz, Christian; Weizer, Alon; Remzi, Mesut; Raman, Jay D; Bolenz, Christian; Bensalah, Karim; Koppie, Theresa M; Karakiewicz, Pierre I; Wood, Christopher G; Montorsi, Francesco; Iwamura, Masatsugu; Shariat, Shahrokh F

2011-10-01

•To assess the impact of differences in ethnicity on clinico-pathological characteristics and outcomes of patients with upper urinary tract urothelial carcinoma (UTUC) in a large multi-center series of patients treated with radical nephroureterectomy (RNU). •We retrospectively collected the data of 2163 patients treated with RNU at 20 academic centres in America, Asia, and Europe. •Univariable and multivariable Cox regression models addressed recurrence-free survival (RFS) and cancer-specific survival (CSS). •In all, 1794 (83%) patients were Caucasian and 369 (17%) were Japanese. All the main clinical and pathological features were significantly different between the two ethnicities. •The median follow-up of the whole cohort was 36 months. At last follow-up, 554 patients (26%) developed disease recurrence and 461 (21%) were dead from UTUC. •The 5-year RFS and CSS estimates were 71.5% and 74.2%, respectively, for Caucasian patients compared with 68.8% and 75.4%, respectively, for Japanese patients. •On univariable Cox regression analyses, ethnicity was not significantly associated with either RFS (P= 0.231) or CSS (P= 0.752). •On multivariable Cox regression analyses that adjusted for the effects of age, gender, surgical type, T stage, grade, tumour architecture, presence of concomitant carcinoma in situ, lymphovascular invasion, tumour necrosis, and lymph node status, ethnicity was not associated with either RFS (hazard ratio [HR] 1.1; P= 0.447) or CSS (HR 1.0; P= 0.908). •There were major differences in the clinico-pathological characteristics of Caucasian and Japanese patients. •However, RFS and CSS probabilities were not affected by ethnicity and race was not an independent predictor of either recurrence or cancer-related death. © 2011 THE AUTHORS; BJU INTERNATIONAL © 2011 BJU INTERNATIONAL.

Hypoalbuminaemia predicts outcome in adult patients with congenital heart disease

PubMed Central

Kempny, Aleksander; Diller, Gerhard-Paul; Alonso-Gonzalez, Rafael; Uebing, Anselm; Rafiq, Isma; Li, Wei; Swan, Lorna; Hooper, James; Donovan, Jackie; Wort, Stephen J; Gatzoulis, Michael A; Dimopoulos, Konstantinos

2015-01-01

Background In patients with acquired heart failure, hypoalbuminaemia is associated with increased risk of death. The prevalence of hypoproteinaemia and hypoalbuminaemia and their relation to outcome in adult patients with congenital heart disease (ACHD) remains, however, unknown. Methods Data on patients with ACHD who underwent blood testing in our centre within the last 14 years were collected. The relation between laboratory, clinical or demographic parameters at baseline and mortality was assessed using Cox proportional hazards regression analysis. Results A total of 2886 patients with ACHD were included. Mean age was 33.3 years (23.6–44.7) and 50.1% patients were men. Median plasma albumin concentration was 41.0 g/L (38.0–44.0), whereas hypoalbuminaemia (<35 g/L) was present in 13.9% of patients. The prevalence of hypoalbuminaemia was significantly higher in patients with great complexity ACHD (18.2%) compared with patients with moderate (11.3%) or simple ACHD lesions (12.1%, p<0.001). During a median follow-up of 5.7 years (3.3–9.6), 327 (11.3%) patients died. On univariable Cox regression analysis, hypoalbuminaemia was a strong predictor of outcome (HR 3.37, 95% CI 2.67 to 4.25, p<0.0001). On multivariable Cox regression, after adjusting for age, sodium and creatinine concentration, liver dysfunction, functional class and disease complexity, hypoalbuminaemia remained a significant predictor of death. Conclusions Hypoalbuminaemia is common in patients with ACHD and is associated with a threefold increased risk of risk of death. Hypoalbuminaemia, therefore, should be included in risk-stratification algorithms as it may assist management decisions and timing of interventions in the growing ACHD population. PMID:25736048

Empirical and targeted therapy of candidemia with fluconazole versus echinocandins: a propensity score-derived analysis of a population-based, multicentre prospective cohort.

PubMed

López-Cortés, L E; Almirante, B; Cuenca-Estrella, M; Garnacho-Montero, J; Padilla, B; Puig-Asensio, M; Ruiz-Camps, I; Rodríguez-Baño, J

2016-08-01

We compared the clinical efficacy of fluconazole and echinocandins in the treatment of candidemia in real practice. The CANDIPOP study is a prospective, population-based cohort study on candidemia carried out between May 2010 and April 2011 in 29 Spanish hospitals. Using strict inclusion criteria, we separately compared the impact of empirical and targeted therapy with fluconazole or echinocandins on 30-day mortality. Cox regression, including a propensity score (PS) for receiving echinocandins, stratified analysis on the PS quartiles and PS-based matched analyses, were performed. The empirical and targeted therapy cohorts comprised 316 and 421 cases, respectively; 30-day mortality was 18.7% with fluconazole and 33.9% with echinocandins (p 0.02) in the empirical therapy group and 19.8% with fluconazole and 27.7% with echinocandins (p 0.06) in the targeted therapy group. Multivariate Cox regression analysis including PS showed that empirical therapy with fluconazole was associated with better prognosis (adjusted hazard ratio 0.38; 95% confidence interval 0.17-0.81; p 0.01); no differences were found within each PS quartile or in cases matched according to PS. Targeted therapy with fluconazole did not show a significant association with mortality in the Cox regression analysis (adjusted hazard ratio 0.77; 95% confidence interval 0.41-1.46; p 0.63), in the PS quartiles or in PS-matched cases. The results were similar among patients with severe sepsis and septic shock. Empirical or targeted treatment with fluconazole was not associated with increased 30-day mortality compared to echinocandins among adults with candidemia. Copyright © 2016 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Changes in the expression of prostaglandin family members in bovine corpus luteum during the oestrous cycle and pregnancy.

PubMed

Berisha, Bajram; Schams, Dieter; Rodler, Daniela; Sinowatz, Fred; Pfaffl, Michael W

2018-06-06

The aim of this study was to characterize certain prostaglandin family members in the bovine corpus luteum (CL) during the oestrous cycle and pregnancy. The CL tissue was assigned to the following stages of the oestrous cycle: 1-2, 3-4, 5-7, 8-12, 13-16, >18 days (after regression) and of pregnancy: 1-2, 3-4, 6-7 and >8 months. In these samples, we investigated prostaglandin F2alpha (PTGF), prostaglandin E2 (PTGE) and their receptors (PTGFR, PTGER2, PTGER4), cyclooxygenase 2 (COX-2), PTGF synthase (PTGFS) and PTGE synthase (PTGES). The expression of mRNA was measured by RT-qPCR, hormones by EIA and localization by immunohistochemistry. The mRNA expression of COX-2, PTGFS and PTGES in CL during the early luteal phase was high followed by a continuous and significant downregulation afterwards, as well as during all phases of pregnancy. The concentration of PTGF in CL tissue was high during the early luteal phase, decreased significantly in the mid-luteal phase, and increased again afterwards. In contrast, the concentration of PTGE increased significantly during late luteal phase followed by a decrease during regression. The PTGE level increased again during late pregnancy. Immunohistochemically, the large granulose-luteal cells show strong staining for COX-2 and PTGES during the early luteal stage followed by lower activity afterwards. During pregnancy, most of the luteal cells were only weakly positive or negative. In conclusion, our results indicate that the examined prostaglandin family members are involved in the local mechanisms that regulate luteal function, specifically during CL formation, function and regression and during pregnancy in the cow. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

PSHREG: A SAS macro for proportional and nonproportional subdistribution hazards regression

PubMed Central

Kohl, Maria; Plischke, Max; Leffondré, Karen; Heinze, Georg

2015-01-01

We present a new SAS macro %pshreg that can be used to fit a proportional subdistribution hazards model for survival data subject to competing risks. Our macro first modifies the input data set appropriately and then applies SAS's standard Cox regression procedure, PROC PHREG, using weights and counting-process style of specifying survival times to the modified data set. The modified data set can also be used to estimate cumulative incidence curves for the event of interest. The application of PROC PHREG has several advantages, e.g., it directly enables the user to apply the Firth correction, which has been proposed as a solution to the problem of undefined (infinite) maximum likelihood estimates in Cox regression, frequently encountered in small sample analyses. Deviation from proportional subdistribution hazards can be detected by both inspecting Schoenfeld-type residuals and testing correlation of these residuals with time, or by including interactions of covariates with functions of time. We illustrate application of these extended methods for competing risk regression using our macro, which is freely available at: http://cemsiis.meduniwien.ac.at/en/kb/science-research/software/statistical-software/pshreg, by means of analysis of a real chronic kidney disease study. We discuss differences in features and capabilities of %pshreg and the recent (January 2014) SAS PROC PHREG implementation of proportional subdistribution hazards modelling. PMID:25572709

Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description.

PubMed

Voit, E O; Knapp, R G

1997-08-15

The linear-logistic regression model and Cox's proportional hazard model are widely used in epidemiology. Their successful application leaves no doubt that they are accurate reflections of observed disease processes and their associated risks or incidence rates. In spite of their prominence, it is not a priori evident why these models work. This article presents a derivation of the two models from the framework of canonical modeling. It begins with a general description of the dynamics between risk sources and disease development, formulates this description in the canonical representation of an S-system, and shows how the linear-logistic model and Cox's proportional hazard model follow naturally from this representation. The article interprets the model parameters in terms of epidemiological concepts as well as in terms of general systems theory and explains the assumptions and limitations generally accepted in the application of these epidemiological models.

A Validated Clinical Risk Prediction Model for Lung Cancer in Smokers of All Ages and Exposure Types: A HUNT Study.

PubMed

Markaki, Maria; Tsamardinos, Ioannis; Langhammer, Arnulf; Lagani, Vincenzo; Hveem, Kristian; Røe, Oluf Dimitri

2018-05-01

Lung cancer causes >1·6 million deaths annually, with early diagnosis being paramount to effective treatment. Here we present a validated risk assessment model for lung cancer screening. The prospective HUNT2 population study in Norway examined 65,237 people aged >20years in 1995-97. After a median of 15·2years, 583 lung cancer cases had been diagnosed; 552 (94·7%) ever-smokers and 31 (5·3%) never-smokers. We performed multivariable analyses of 36 candidate risk predictors, using multiple imputation of missing data and backwards feature selection with Cox regression. The resulting model was validated in an independent Norwegian prospective dataset of 45,341 ever-smokers, in which 675 lung cancers had been diagnosed after a median follow-up of 11·6years. Our final HUNT Lung Cancer Model included age, pack-years, smoking intensity, years since smoking cessation, body mass index, daily cough, and hours of daily indoors exposure to smoke. External validation showed a 0·879 concordance index (95% CI [0·866-0·891]) with an area under the curve of 0·87 (95% CI [0·85-0·89]) within 6years. Only 22% of ever-smokers would need screening to identify 81·85% of all lung cancers within 6years. Our model of seven variables is simple, accurate, and useful for screening selection. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Nelson, P. I.

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

The importance of employment status in determining exit rates from nursing.

PubMed

Daniels, Frieda; Laporte, Audrey; Lemieux-Charles, Louise; Baumann, Andrea; Onate, Kanecy; Deber, Raisa

2012-01-01

To mitigate nurse shortages, health care decision makers tend to employ retention strategies that assume nurses employed in full-time, part-time, or casual positions and working in different sectors have similar preferences for work. However, this assumption has not been validated in the literature. The relationship between a nurse's propensity to exit the nurse profession in Ontario and employment status was explored by building an extended Cox Proportional Hazards Regression Model using a counting process technique. The differential exit patterns between part-time and casual nurses suggest that the common practice of treating part-time and casual nurses as equivalent is misleading. Health care decision makers should consider nurse retention strategies specifically targeting casual nurses because this segment of the profession is at the greatest risk of leaving. Nurse executives and nurse managers should investigate the different work preferences of part-time and casual nurses to devise tailored rather than "one-size fits all" nurse retention strategies to retain casual nurses.

Outlier identification and visualization for Pb concentrations in urban soils and its implications for identification of potential contaminated land.

PubMed

Zhang, Chaosheng; Tang, Ya; Luo, Lin; Xu, Weilin

2009-11-01

Outliers in urban soil geochemical databases may imply potential contaminated land. Different methodologies which can be easily implemented for the identification of global and spatial outliers were applied for Pb concentrations in urban soils of Galway City in Ireland. Due to its strongly skewed probability feature, a Box-Cox transformation was performed prior to further analyses. The graphic methods of histogram and box-and-whisker plot were effective in identification of global outliers at the original scale of the dataset. Spatial outliers could be identified by a local indicator of spatial association of local Moran's I, cross-validation of kriging, and a geographically weighted regression. The spatial locations of outliers were visualised using a geographical information system. Different methods showed generally consistent results, but differences existed. It is suggested that outliers identified by statistical methods should be confirmed and justified using scientific knowledge before they are properly dealt with.

Neuroendocrine tumors of colon and rectum: validation of clinical and prognostic values of the World Health Organization 2010 grading classifications and European Neuroendocrine Tumor Society staging systems.

PubMed

Shen, Chaoyong; Yin, Yuan; Chen, Huijiao; Tang, Sumin; Yin, Xiaonan; Zhou, Zongguang; Zhang, Bo; Chen, Zhixin

2017-03-28

This study evaluated and compared the clinical and prognostic values of the grading criteria used by the World Health Organization (WHO) and the European Neuroendocrine Tumors Society (ENETS). Moreover, this work assessed the current best prognostic model for colorectal neuroendocrine tumors (CRNETs). The 2010 WHO classifications and the ENETS systems can both stratify the patients into prognostic groups, although the 2010 WHO criteria is more applicable to CRNET patients. Along with tumor location, the 2010 WHO criteria are important independent prognostic parameters for CRNETs in both univariate and multivariate analyses through Cox regression (P<0.05). Data from 192 consecutive patients histopathologically diagnosed with CRNETs and had undergone surgical resection from January 2009 to May 2016 in a single center were retrospectively analyzed. Findings suggest that the WHO classifications are superior over the ENETS classification system in predicting the prognosis of CRNETs. Additionally, the WHO classifications can be widely used in clinical practice.

Survival analysis of heart failure patients: A case study.

PubMed

Ahmad, Tanvir; Munir, Assia; Bhatti, Sajjad Haider; Aftab, Muhammad; Raza, Muhammad Ali

2017-01-01

This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015). All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.

Prediction of all-cause death in hemodialysis patients using elevated postdialysis pulse wave velocity.

PubMed

Fu, Xiaohong; Yang, Jihong; Fan, Zhaoxin; Chen, Xianguang; Wu, Jie; Li, Jie; Wu, Hua

2016-02-01

To identify the relationship between predialysis pulse wave velocity (PWV), postdialysis PWV during 1 hemodialysis (HD) session, and deaths in maintenance HD patients. 43 patients were recruited. PWV was measured before and after one HD session and dialysis- related data were recorded. Clinical data such as blood pressure, blood lipids, and blood glucose, were carefully observed and managed in a 5-year follow-up. The association between all-cause death, predialysis PWV, postdialysis PWV, change of PWV (ΔPWV), and other related variables were analyzed. After 5 years, 17 patients (39.5%) died. Univariate Cox regression analysis showed that all-cause death of the patients significantly correlated with age, postdialysis PWV, and ΔPWV. Multivariate Cox regression analysis revealed that postdialysis PWV was an independent predictor for all-cause death in these patients (HR: 1.377, 95% CI: 1.146 - 1.656, p = 0.001). Elevated postdialysis PWV significantly correlated with and was an independent predictor for all-cause death in maintenance HD patients.

Box–Cox Transformation and Random Regression Models for Fecal egg Count Data

PubMed Central

da Silva, Marcos Vinícius Gualberto Barbosa; Van Tassell, Curtis P.; Sonstegard, Tad S.; Cobuci, Jaime Araujo; Gasbarre, Louis C.

2012-01-01

Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box–Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box–Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated. PMID:22303406

Box-Cox Transformation and Random Regression Models for Fecal egg Count Data.

PubMed

da Silva, Marcos Vinícius Gualberto Barbosa; Van Tassell, Curtis P; Sonstegard, Tad S; Cobuci, Jaime Araujo; Gasbarre, Louis C

2011-01-01

Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated.

Development and Validation of a qRT-PCR Classifier for Lung Cancer Prognosis

PubMed Central

Chen, Guoan; Kim, Sinae; Taylor, Jeremy MG; Wang, Zhuwen; Lee, Oliver; Ramnath, Nithya; Reddy, Rishindra M; Lin, Jules; Chang, Andrew C; Orringer, Mark B; Beer, David G

2011-01-01

Purpose This prospective study aimed to develop a robust and clinically-applicable method to identify high-risk early stage lung cancer patients and then to validate this method for use in future translational studies. Patients and Methods Three published Affymetrix microarray data sets representing 680 primary tumors were used in the survival-related gene selection procedure using clustering, Cox model and random survival forest (RSF) analysis. A final set of 91 genes was selected and tested as a predictor of survival using a qRT-PCR-based assay utilizing an independent cohort of 101 lung adenocarcinomas. Results The RSF model built from 91 genes in the training set predicted patient survival in an independent cohort of 101 lung adenocarcinomas, with a prediction error rate of 26.6%. The mortality risk index (MRI) was significantly related to survival (Cox model p < 0.00001) and separated all patients into low, medium, and high-risk groups (HR = 1.00, 2.82, 4.42). The MRI was also related to survival in stage 1 patients (Cox model p = 0.001), separating patients into low, medium, and high-risk groups (HR = 1.00, 3.29, 3.77). Conclusions The development and validation of this robust qRT-PCR platform allows prediction of patient survival with early stage lung cancer. Utilization will now allow investigators to evaluate it prospectively by incorporation into new clinical trials with the goal of personalized treatment of lung cancer patients and improving patient survival. PMID:21792073

A Long-Term Predictive Validity Study: Can the CDI Short Form be Used to Predict Language and Early Literacy Skills Four Years Later?

ERIC Educational Resources Information Center

Can, Dilara Deniz; Ginsburg-Block, Marika; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

2013-01-01

This longitudinal study examined the predictive validity of the MacArthur Communicative Developmental Inventories-Short Form (CDI-SF), a parent report questionnaire about children's language development (Fenson, Pethick, Renda, Cox, Dale & Reznick, 2000). Data were first gathered from parents on the CDI-SF vocabulary scores for seventy-six…

External validation of sTWEAK as a prognostic noninvasive biomarker for head and neck squamous cell carcinoma.

PubMed

Terra, Ximena; Gómez, David; García-Lorenzo, Jacinto; Flores, Joan Carles; Figuerola, Enric; Mora, Josefina; Chacón, Matilde R; Quer, Miquel; Camacho, Mercedes; León, Xavier; Avilés-Jurado, Francesc Xavier

2016-04-01

The main purpose of this study was to validate the prognostic significance of tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) in head and neck squamous cell carcinoma (HNSCC) using an independent cohort. Data were evaluated from 153 patients with HNSCC in stages III to IV, who received radiotherapy (RT) or chemoradiotherapy. We quantified soluble TWEAK (sTWEAK) in pretreatment samples using enzyme-linked immunosorbent assay. The classification tree revealed a cutoff value of 322 pg/mL for sTWEAK to be ideal for discriminating between patients' disease control. Kaplan-Meier curves indicate that the disease-free survival rate in patients with high sTWEAK was significantly higher than in patients with low levels (p = .006, log-rank test). An independent link was identified between low sTWEAK and poor clinical outcome in Cox regression multivariate analysis (hazard ratio = 1.866; 95% confidence interval [CI] = 1.114-3.125; p = .001). Our study highlights the significance of this noninvasive biomarker in the discrimination according to the disease control achieved by patients who received a nonsurgical organ-preservation treatment. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1358-E1363, 2016. © 2015 Wiley Periodicals, Inc.

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

PubMed Central

2016-01-01

Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096

Prediction of morbidity and mortality in patients with type 2 diabetes.

PubMed

Wells, Brian J; Roth, Rachel; Nowacki, Amy S; Arrigain, Susana; Yu, Changhong; Rosenkrans, Wayne A; Kattan, Michael W

2013-01-01

Introduction. The objective of this study was to create a tool that accurately predicts the risk of morbidity and mortality in patients with type 2 diabetes according to an oral hypoglycemic agent. Materials and Methods. The model was based on a cohort of 33,067 patients with type 2 diabetes who were prescribed a single oral hypoglycemic agent at the Cleveland Clinic between 1998 and 2006. Competing risk regression models were created for coronary heart disease (CHD), heart failure, and stroke, while a Cox regression model was created for mortality. Propensity scores were used to account for possible treatment bias. A prediction tool was created and internally validated using tenfold cross-validation. The results were compared to a Framingham model and a model based on the United Kingdom Prospective Diabetes Study (UKPDS) for CHD and stroke, respectively. Results and Discussion. Median follow-up for the mortality outcome was 769 days. The numbers of patients experiencing events were as follows: CHD (3062), heart failure (1408), stroke (1451), and mortality (3661). The prediction tools demonstrated the following concordance indices (c-statistics) for the specific outcomes: CHD (0.730), heart failure (0.753), stroke (0.688), and mortality (0.719). The prediction tool was superior to the Framingham model at predicting CHD and was at least as accurate as the UKPDS model at predicting stroke. Conclusions. We created an accurate tool for predicting the risk of stroke, coronary heart disease, heart failure, and death in patients with type 2 diabetes. The calculator is available online at http://rcalc.ccf.org under the heading "Type 2 Diabetes" and entitled, "Predicting 5-Year Morbidity and Mortality." This may be a valuable tool to aid the clinician's choice of an oral hypoglycemic, to better inform patients, and to motivate dialogue between physician and patient.

A Novel Approach to Determining Violence Risk in Schizophrenia: Developing a Stepped Strategy in 13,806 Discharged Patients

PubMed Central

Singh, Jay P.; Grann, Martin; Lichtenstein, Paul; Långström, Niklas; Fazel, Seena

2012-01-01

Clinical guidelines recommend that violence risk be assessed in schizophrenia. Current approaches are resource-intensive as they employ detailed clinical assessments of dangerousness for most patients. An alternative approach would be to first screen out patients at very low risk of future violence prior to more costly and time-consuming assessments. In order to implement such a stepped strategy, we developed a simple tool to screen out individuals with schizophrenia at very low risk of violent offending. We merged high quality Swedish national registers containing information on psychiatric diagnoses, socio-demographic factors, and violent crime. A cohort of 13,806 individuals with hospital discharge diagnoses of schizophrenia was identified and followed for up to 33 years for violent crime. Cox regression was used to determine risk factors for violent crime and construct the screening tool, the predictive validity of which was measured using four outcome statistics. The instrument was calibrated on 6,903 participants and cross-validated using three independent replication samples of 2,301 participants each. Regression analyses resulted in a tool composed of five items: male sex, previous criminal conviction, young age at assessment, comorbid alcohol abuse, and comorbid drug abuse. At 5 years after discharge, the instrument had a negative predictive value of 0.99 (95% CI = 0.98–0.99), meaning that very few individuals who the tool screened out (n = 2,359 out of original sample of 6,903) were subsequently convicted of a violent offence. Screening out patients who are at very low risk of violence prior to more detailed clinical assessment may assist the risk assessment process in schizophrenia. PMID:22359622

Corrected score estimation in the proportional hazards model with misclassified discrete covariates

PubMed Central

Zucker, David M.; Spiegelman, Donna

2013-01-01

SUMMARY We consider Cox proportional hazards regression when the covariate vector includes error-prone discrete covariates along with error-free covariates, which may be discrete or continuous. The misclassification in the discrete error-prone covariates is allowed to be of any specified form. Building on the work of Nakamura and his colleagues, we present a corrected score method for this setting. The method can handle all three major study designs (internal validation design, external validation design, and replicate measures design), both functional and structural error models, and time-dependent covariates satisfying a certain ‘localized error’ condition. We derive the asymptotic properties of the method and indicate how to adjust the covariance matrix of the regression coefficient estimates to account for estimation of the misclassification matrix. We present the results of a finite-sample simulation study under Weibull survival with a single binary covariate having known misclassification rates. The performance of the method described here was similar to that of related methods we have examined in previous works. Specifically, our new estimator performed as well as or, in a few cases, better than the full Weibull maximum likelihood estimator. We also present simulation results for our method for the case where the misclassification probabilities are estimated from an external replicate measures study. Our method generally performed well in these simulations. The new estimator has a broader range of applicability than many other estimators proposed in the literature, including those described in our own earlier work, in that it can handle time-dependent covariates with an arbitrary misclassification structure. We illustrate the method on data from a study of the relationship between dietary calcium intake and distal colon cancer. PMID:18219700

Regulatory effect of the AMPK-COX-2 signaling pathway in curcumin-induced apoptosis in HT-29 colon cancer cells.

PubMed

Lee, Yun-Kyoung; Park, Song Yi; Kim, Young-Min; Park, Ock Jin

2009-08-01

AMP-activated protein kinase (AMPK), a highly conserved protein in eukaryotes, functions as a major metabolic switch to maintain energy homeostasis. It also intrinsically regulates the mammalian cell cycle. Moreover, the AMPK cascade has emerged as an important pathway implicated in cancer control. In this study we investigated the effects of curcumin on apoptosis and the regulatory effect of the AMPK-cyclooxygenase-2 (COX-2) pathway in curcumin-induced apoptosis. Curcumin has shown promise as a chemopreventive agent because of its in vivo regression of various animal-model colon cancers. This study focused on exploiting curcumin to apply antitumorigenic effects through modulation of the AMPK-COX-2 cascade. Curcumin exhibited a potent apoptotic effect on HT-29 colon cancer cells at concentrations of 50 micromol/L and above. These apoptotic effects were correlated with the decrease in pAkt and COX-2, as well as the increase in p-AMPK. Cell cycle analysis showed that curcumin induced G(1)-phase arrest. Further study with AMPK synthetic inhibitor Compound C has shown that increased concentrations of Compound C would abolish AMPK expression, accompanied by a marked increase in COX-2 as well as pAkt expression in curcumin-treated HT-29 cells. By inhibiting AMPK with Compound C, we found that curcumin-treated colon cancer cells were no longer undergoing apoptosis; rather, they were proliferative. These results indicate that AMPK is crucial in apoptosis induced by curcumin and further that the pAkt-AMPK-COX-2 cascade or AMPK-pAkt-COX-2 pathway is important in cell proliferation and apoptosis in colon cancer cells.

Determination of dietary iron requirements by full expression of iron-containing cytochrome c oxidase in the heart of broilers from 22 to 42 d of age.

PubMed

Liao, Xiudong; Ma, Chunyan; Lu, Lin; Zhang, Liyang; Luo, Xugang

2017-10-01

The present study was carried out to determine dietary Fe requirements for the full expression of Fe-containing enzyme in broilers chicks from 22 to 42 d of age. At 22 d of age, 288 Arbor Acres male chicks were randomly assigned to one of six treatments with six replicates and fed a basal maize-soyabean-meal diet (control, containing 47·0 mg Fe/kg) or the basal diet supplemented with 20, 40, 60, 80 or 100 mg Fe/kg from FeSO4.7H2O for 21 d. Regression analysis was performed to estimate the optimal dietary Fe level using quadratic models. Liver cytochrome c oxidase (Cox), heart Cox and kidney succinate dehydrogenase mRNA levels as well as heart COX activity were affected (P<0·08) by dietary Fe level, and COX mRNA level and activity in heart of broilers increased quadratically (P<0·03) as dietary Fe level increased. The estimates of dietary Fe requirements were 110 and 104 mg/kg for the full expression of Cox mRNA and for its activity in the heart of broilers, respectively. The results from this study indicate that COX mRNA level and activity in the heart are new and sensitive criteria to evaluate the dietary Fe requirements of broilers, and the dietary Fe requirements would be 104-110 mg/kg to support the full expression of COX in the heart of broiler chicks from 22 to 42 d of age, which are higher than the current National Research Council Fe requirement (80 mg/kg) of broiler chicks from 1 to 21 d or 22 to 42 d of age.

Preadmission use of nonaspirin nonsteroidal anti-inflammatory drugs and 30-day stroke mortality.

PubMed

Schmidt, Morten; Hováth-Puhó, Erzsébet; Christiansen, Christian Fynbo; Petersen, Karin L; Bøtker, Hans Erik; Sørensen, Henrik Toft

2014-11-25

To examine whether preadmission use of nonaspirin nonsteroidal anti-inflammatory drugs (NSAIDs) influenced 30-day stroke mortality. We conducted a nationwide population-based cohort study. Using medical databases, we identified all first-time stroke hospitalizations in Denmark between 2004 and 2012 (n = 100,043) and subsequent mortality. We categorized NSAID use as current (prescription redemption within 60 days before hospital admission), former, and nonuse. Current use was further classified as new or long-term use. Cox regression was used to compute hazard ratios (HRs) of death within 30 days, controlling for potential confounding through multivariable adjustment and propensity score matching. The adjusted HR of death for ischemic stroke was 1.19 (95% confidence interval [CI]: 1.02-1.38) for current users of selective cyclooxygenase (COX)-2 inhibitors compared with nonusers, driven by the effect among new users (1.42, 95% CI: 1.14-1.77). Comparing the different COX-2 inhibitors, the HR was driven by new use of older traditional COX-2 inhibitors (1.42, 95% CI: 1.14-1.78) among which it was 1.53 (95% CI: 1.02-2.28) for etodolac and 1.28 (95% CI: 0.98-1.68) for diclofenac. The propensity score-matched analysis supported the association between older COX-2 inhibitors and ischemic stroke mortality. There was no association for former users. Mortality from intracerebral hemorrhage was not associated with use of nonselective NSAIDs or COX-2 inhibitors. Preadmission use of COX-2 inhibitors was associated with increased 30-day mortality after ischemic stroke, but not hemorrhagic stroke. Use of nonselective NSAIDs at time of admission was not associated with mortality from ischemic stroke or intracerebral hemorrhage. © 2014 American Academy of Neurology.

An introduction to g methods.

PubMed

Naimi, Ashley I; Cole, Stephen R; Kennedy, Edward H

2017-04-01

Robins' generalized methods (g methods) provide consistent estimates of contrasts (e.g. differences, ratios) of potential outcomes under a less restrictive set of identification conditions than do standard regression methods (e.g. linear, logistic, Cox regression). Uptake of g methods by epidemiologists has been hampered by limitations in understanding both conceptual and technical details. We present a simple worked example that illustrates basic concepts, while minimizing technical complications. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Financial Issues and Relationship Outcomes among Cohabiting Individuals

ERIC Educational Resources Information Center

Dew, Jeffrey

2011-01-01

Few studies have examined how financial relationship issues are associated with cohabiting individuals' risk of union dissolution or marriage. Competing-risks Cox regressions using the cohabiting data in the National Survey of Families and Households (N = 483) found that financial disagreements predicted union dissolution, whereas disagreements…

Prediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus - A population-based retrospective cohort study.

PubMed

Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen

2017-06-01

This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell"'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models. Copyright © 2017 Elsevier Inc. All rights reserved.

Nomograms for predicting graft function and survival in living donor kidney transplantation based on the UNOS Registry.

PubMed

Tiong, H Y; Goldfarb, D A; Kattan, M W; Alster, J M; Thuita, L; Yu, C; Wee, A; Poggio, E D

2009-03-01

We developed nomograms that predict transplant renal function at 1 year (Modification of Diet in Renal Disease equation [estimated glomerular filtration rate]) and 5-year graft survival after living donor kidney transplantation. Data for living donor renal transplants were obtained from the United Network for Organ Sharing registry for 2000 to 2003. Nomograms were designed using linear or Cox regression models to predict 1-year estimated glomerular filtration rate and 5-year graft survival based on pretransplant information including demographic factors, immunosuppressive therapy, immunological factors and organ procurement technique. A third nomogram was constructed to predict 5-year graft survival using additional information available by 6 months after transplantation. These data included delayed graft function, any treated rejection episodes and the 6-month estimated glomerular filtration rate. The nomograms were internally validated using 10-fold cross-validation. The renal function nomogram had an r-square value of 0.13. It worked best when predicting estimated glomerular filtration rate values between 50 and 70 ml per minute per 1.73 m(2). The 5-year graft survival nomograms had a concordance index of 0.71 for the pretransplant nomogram and 0.78 for the 6-month posttransplant nomogram. Calibration was adequate for all nomograms. Nomograms based on data from the United Network for Organ Sharing registry have been validated to predict the 1-year estimated glomerular filtration rate and 5-year graft survival. These nomograms may facilitate individualized patient care in living donor kidney transplantation.

Value of adding the renal pathological score to the kidney failure risk equation in advanced diabetic nephropathy.

PubMed

Yamanouchi, Masayuki; Hoshino, Junichi; Ubara, Yoshifumi; Takaichi, Kenmei; Kinowaki, Keiichi; Fujii, Takeshi; Ohashi, Kenichi; Mise, Koki; Toyama, Tadashi; Hara, Akinori; Kitagawa, Kiyoki; Shimizu, Miho; Furuichi, Kengo; Wada, Takashi

2018-01-01

There have been a limited number of biopsy-based studies on diabetic nephropathy, and therefore the clinical importance of renal biopsy in patients with diabetes in late-stage chronic kidney disease (CKD) is still debated. We aimed to clarify the renal prognostic value of pathological information to clinical information in patients with diabetes and advanced CKD. We retrospectively assessed 493 type 2 diabetics with biopsy-proven diabetic nephropathy in four centers in Japan. 296 patients with stage 3-5 CKD at the time of biopsy were identified and assigned two risk prediction scores for end-stage renal disease (ESRD): the Kidney Failure Risk Equation (KFRE, a score composed of clinical parameters) and the Diabetic Nephropathy Score (D-score, a score integrated pathological parameters of the Diabetic Nephropathy Classification by the Renal Pathology Society (RPS DN Classification)). They were randomized 2:1 to development and validation cohort. Hazard Ratios (HR) of incident ESRD were reported with 95% confidence interval (CI) of the KFRE, D-score and KFRE+D-score in Cox regression model. Improvement of risk prediction with the addition of D-score to the KFRE was assessed using c-statistics, continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI). During median follow-up of 1.9 years, 194 patients developed ESRD. The cox regression analysis showed that the KFRE,D-score and KFRE+D-score were significant predictors of ESRD both in the development cohort and in the validation cohort. The c-statistics of the D-score was 0.67. The c-statistics of the KFRE was good, but its predictive value was weaker than that in the miscellaneous CKD cohort originally reported (c-statistics, 0.78 vs. 0.90) and was not significantly improved by adding the D-score (0.78 vs. 0.79, p = 0.83). Only continuous NRI was positive after adding the D-score to the KFRE (0.4%; CI: 0.0-0.8%). We found that the predict values of the KFRE and the D-score were not as good as reported, and combining the D-score with the KFRE did not significantly improve prediction of the risk of ESRD in advanced diabetic nephropathy. To improve prediction of renal prognosis for advanced diabetic nephropathy may require different approaches with combining clinical and pathological parameters that were not measured in the KFRE and the RPS DN Classification.

Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

ERIC Educational Resources Information Center

Shieh, Gwowen

2009-01-01

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

Exploring selectivity requirements for COX-2 versus COX-1 binding of 2-(5-phenyl-pyrazol-1-yl)-5-methanesulfonylpyridines using topological and physico-chemical parameters.

PubMed

Chakraborty, Santanu; Sengupta, Chandana; Roy, Kunal

2005-04-01

Considering the current need for development of selective cyclooxygenase-2 (COX-2) inhibitors, an attempt has been made to explore physico-chemical requirements of 2-(5-phenyl-pyrazol-1-yl)-5-methanesulfonylpyridines for binding with COX-1 and COX-2 enzyme subtypes and also to explore the selectivity requirements. In this study, E-states of different common atoms of the molecules (calculated according to Kier & Hall), first order valence connectivity and physicochemical parameters (hydrophobicity pi, Hammett sigma and molar refractivity MR of different ring substituents) were used as independent variables along with suitable dummy parameters in the stepwise regression method. The best equation describing COX-1 binding affinity [n = 25, Q2 = 0.606, R(a)2 = 0.702, R2 = 0.752, R = 0.867, s = 0.447, F = 15.2 (df 4, 20)] suggests that the COX-1 binding affinity increases in the presence of a halogen substituent at R1 position and a p-alkoxy or p-methylthio substituent at R2 position. Furthermore, a difluoromethyl group is preferred over a trifluoromethyl group at R position for the COX-1 binding. The best equation describing COX-2 binding affinity [n = 32, Q2 = 0.622, R(a)2= 0.692, R2 = 0.732, R = 0.856, s = 0.265, F = 18.4 (df 4, 27)] shows that the COX-2 binding affinity increases with the presence of a halogen substituent at R1 position and increase of size of R2 substituents. However, it decreases in case of simultaneous presence of 3-chloro and 4-methoxy groups on the phenyl nucleus and in the presence of highly lipophilic R2 substituents. The best selectivity relation [n = 25, Q2 = 0.455, R(a)2 = 0.605, R2 = 0.670, R = 0.819, s = 0.423, F = 10.2 (df 4, 20)] suggests that the COX-2 selectivity decreases in the presence of p-alkoxy group and electron-withdrawing para substituents at R2 position. Again, a trifluoro group is conductive for the selectivity instead of a difluoromethyl group at R position. Furthermore, branching may also play significant role in determining the selectivity as evidenced from the connectivity parameter.

Attrition in Psychotherapy: A Survival Analysis

ERIC Educational Resources Information Center

Roseborough, David John; McLeod, Jeffrey T.; Wright, Florence I.

2016-01-01

Purpose: Attrition is a common problem in psychotherapy and can be defined as clients ending treatment before achieving an optimal response. Method: This longitudinal, archival study utilized data for 3,728 clients, using the Outcome Questionnaire 45.2. A Cox regression proportional hazards (hazard ratios) model was used in order to better…

Severe Pain Predicts Greater Likelihood of Subsequent Suicide

ERIC Educational Resources Information Center

Ilgen, Mark A.; Zivin, Kara; Austin, Karen L.; Bohnert, Amy S. B.; Czyz, Ewa K.; Valenstein, Marcia; Kilbourne, Amy M.

2010-01-01

Using data from the 1999 Large Health Survey of Veterans, Veterans Affairs' medical records, and the National Death Index (N = 260,254), the association between self-reported pain severity and suicide among veterans as examined, after accounting for demographic variables and psychiatric diagnoses. A Cox proportional hazards regression demonstrated…

In vitro chemo-sensitivity assay guided chemotherapy is associated with prolonged overall survival in cancer patients.

PubMed

Udelnow, Andrej; Schönfęlder, Manfred; Würl, Peter; Halloul, Zuhir; Meyer, Frank; Lippert, Hans; Mroczkowski, Paweł

2013-06-01

The overall survival (OS) of patients suffering From various tumour entities was correlated with the results of in vitro-chemosensitivity assay (CSA) of the in vivo applied drugs. Tumour specimen (n=611) were dissected in 514 patients and incubated for primary tumour cell culture. The histocytological regression assay was performed 5 days after adding chemotherapeutic substances to the cell cultures. n=329 patients undergoing chemotherapy were included in the in vitro/in vivo associations. OS was assessed and in vitro response groups compared using survival analysis. Furthermore Cox-regression analysis was performed on OS including CSA, age, TNM classification and treatment course. The growth rate of the primary was 73-96% depending on tumour entity. The in-vitro response rate varied with histology and drugs (e.g. 8-18% for methotrexate and 33-83% for epirubicine). OS was significantly prolonged for patients treated with in vitro effective drugs compared to empiric therapy (log-rank-test, p=0.0435). Cox-regression revealed that application of in vitro effective drugs, residual tumour and postoperative radiotherapy determined the death risk independently. When patients were treated with drugs effective in our CSA, OS was significantly prolonged compared to empiric therapy. CSA guided chemotherapy should be compared to empiric treatment by a prospective randomized trial.

A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data.

PubMed

Lee, MinJae; Rahbar, Mohammad H; Talebi, Hooshang

2018-01-01

We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate using our proposed procedure with that of the Cox Proportional Hazard (PH) model and censored quantile regression model. We also assess the impact of censoring rate and type on the standard error of the estimators of parameters. Finally, we illustrate application of our proposed method to real life data from Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study to test an interaction effect between type of injury and study sites using median time for a trauma patient to receive three units of red blood cells. The results from simulation studies indicate that our procedure performs better than both Cox PH model and censored quantile regression model based on statistical power for detecting the interaction, especially when the number of observations is small. It is also relatively less sensitive to censoring rates or even the presence of conditionally independent censoring that is conditional on the levels of covariates.

Parameter estimation in Cox models with missing failure indicators and the OPPERA study.

PubMed

Brownstein, Naomi C; Cai, Jianwen; Slade, Gary D; Bair, Eric

2015-12-30

In a prospective cohort study, examining all participants for incidence of the condition of interest may be prohibitively expensive. For example, the "gold standard" for diagnosing temporomandibular disorder (TMD) is a physical examination by a trained clinician. In large studies, examining all participants in this manner is infeasible. Instead, it is common to use questionnaires to screen for incidence of TMD and perform the "gold standard" examination only on participants who screen positively. Unfortunately, some participants may leave the study before receiving the "gold standard" examination. Within the framework of survival analysis, this results in missing failure indicators. Motivated by the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study, a large cohort study of TMD, we propose a method for parameter estimation in survival models with missing failure indicators. We estimate the probability of being an incident case for those lacking a "gold standard" examination using logistic regression. These estimated probabilities are used to generate multiple imputations of case status for each missing examination that are combined with observed data in appropriate regression models. The variance introduced by the procedure is estimated using multiple imputation. The method can be used to estimate both regression coefficients in Cox proportional hazard models as well as incidence rates using Poisson regression. We simulate data with missing failure indicators and show that our method performs as well as or better than competing methods. Finally, we apply the proposed method to data from the OPPERA study. Copyright © 2015 John Wiley & Sons, Ltd.

Estimating inverse probability weights using super learner when weight-model specification is unknown in a marginal structural Cox model context.

PubMed

Karim, Mohammad Ehsanul; Platt, Robert W

2017-06-15

Correct specification of the inverse probability weighting (IPW) model is necessary for consistent inference from a marginal structural Cox model (MSCM). In practical applications, researchers are typically unaware of the true specification of the weight model. Nonetheless, IPWs are commonly estimated using parametric models, such as the main-effects logistic regression model. In practice, assumptions underlying such models may not hold and data-adaptive statistical learning methods may provide an alternative. Many candidate statistical learning approaches are available in the literature. However, the optimal approach for a given dataset is impossible to predict. Super learner (SL) has been proposed as a tool for selecting an optimal learner from a set of candidates using cross-validation. In this study, we evaluate the usefulness of a SL in estimating IPW in four different MSCM simulation scenarios, in which we varied the specification of the true weight model specification (linear and/or additive). Our simulations show that, in the presence of weight model misspecification, with a rich and diverse set of candidate algorithms, SL can generally offer a better alternative to the commonly used statistical learning approaches in terms of MSE as well as the coverage probabilities of the estimated effect in an MSCM. The findings from the simulation studies guided the application of the MSCM in a multiple sclerosis cohort from British Columbia, Canada (1995-2008), to estimate the impact of beta-interferon treatment in delaying disability progression. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Gastrointestinal toxicity among patients taking selective COX-2 inhibitors or conventional NSAIDs, alone or combined with proton pump inhibitors: a case-control study.

PubMed

Bakhriansyah, Mohammad; Souverein, Patrick C; de Boer, Anthonius; Klungel, Olaf H

2017-10-01

To assess the risk of gastrointestinal perforation, ulcers, or bleeding (PUB) associated with the use of conventional nonsteroidal anti-inflammatory drugs (NSAIDs) with proton pump inhibitors (PPIs) and selective COX-2 inhibitors, with or without PPIs compared with conventional NSAIDs. A case-control study was performed within conventional NSAIDs and/or selective COX-2 inhibitors users identified from the Dutch PHARMO Record Linkage System in the period 1998-2012. Cases were patients aged ≥18 years with a first hospital admission for PUB. For each case, up to four controls were matched for age and sex at the date a case was hospitalized (index date). Logistic regression analysis was used to calculate odds ratios (ORs). At the index date, 2634 cases and 5074 controls were current users of conventional NSAIDs or selective COX-2 inhibitors. Compared with conventional NSAIDs, selective COX-2 inhibitors with PPIs had the lowest risk of PUB (adjusted OR 0.51, 95% confidence interval [CI]: 0.35-0.73) followed by selective COX-2 inhibitors (adjusted OR 0.66, 95%CI: 0.48-0.89) and conventional NSAIDs with PPIs (adjusted OR 0.79, 95%CI: 0.68-0.92). Compared with conventional NSAIDs, the risk of PUB was lower for those aged ≥75 years taking conventional NSAIDs with PPIs compared with younger patients (adjusted interaction OR 0.79, 95%CI: 0.64-0.99). However, those aged ≥75 years taking selective COX-2 inhibitors, the risk was higher compared with younger patients (adjusted interaction OR 1.22, 95%CI: 1.01-1.47). Selective COX-2 inhibitors with PPIs, selective COX-2 inhibitors, and conventional NSAIDs with PPIs were associated with lower risks of PUB compared with conventional NSAIDs. These effects were modified by age. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

"Selective" switching from non-selective to selective non-steroidal anti-inflammatory drugs.

PubMed

Bennett, Kathleen; Teeling, Mary; Feely, John

2003-11-01

Non-steroidal anti inflammatory drugs (NSAIDs) are thought to account for almost 25% of all reported adverse drug reactions, primarily gastrointestinal (GI) toxicity. Selective cyclo-oxygenase-2 (COX-2) inhibitors have been shown to preferentially inhibit activity of the COX-2 enzyme, which maintains anti-inflammatory activity but reduces GI toxicity. To determine the degree of switching from non-selective NSAIDs to COX-2 inhibitors and to examine the factors that were associated with switching. The General Medical Services prescription database (1.2 million people) was examined for NSAID prescriptions from December 1999 through November 2001. All those receiving non-selective NSAIDs and those switching to selective COX-2 inhibitors after at least 1 month on a non-selective NSAID were identified (non-switchers and switchers, respectively). Age, sex, dose of non-selective NSAID and co-prescribing of anti-peptic ulcer (anti-PU) drugs were considered between switchers and non-switchers, and odds ratios (OR) calculated using logistic regression. The effect of chronic use (> or =3 months prescription of a non-selective NSAID during the study period) on switching was also evaluated. A total of 81,538 of 480,573 patients (17%) initially prescribed non-selective NSAIDs were switched to COX-2 inhibitors during the study. The elderly (65 years or older) were more likely to be switched to a COX-2 inhibitor [OR=1.81, 95% confidence interval (CI) 1.79, 1.84]. Women were also more likely to be switched to COX-2 inhibitor therapy (OR=1.25, 95% CI 1.23, 1.27). Previous but not subsequent prescribing of anti-PU drugs was also associated with switching. Chronic users showed similar switching patterns. Prescribers are more likely to switch older female patients and those with a past history of peptic ulcers from non-selective NSAIDs to COX-2 inhibitors. This suggests that doctors take risk factors into consideration when prescribing NSAIDs. The relatively low rate of switching may suggest that prescribers still have concerns over the place of COX-2 inhibitors and reserve their use to those patients particularly at risk of NSAID-induced GI toxicity.

Relaxing the rule of ten events per variable in logistic and Cox regression.

PubMed

Vittinghoff, Eric; McCulloch, Charles E

2007-03-15

The rule of thumb that logistic and Cox models should be used with a minimum of 10 outcome events per predictor variable (EPV), based on two simulation studies, may be too conservative. The authors conducted a large simulation study of other influences on confidence interval coverage, type I error, relative bias, and other model performance measures. They found a range of circumstances in which coverage and bias were within acceptable levels despite less than 10 EPV, as well as other factors that were as influential as or more influential than EPV. They conclude that this rule can be relaxed, in particular for sensitivity analyses undertaken to demonstrate adequate control of confounding.

Factors associated with Iowa rural hospitals' decision to convert to critical access hospital status.

PubMed

Li, Pengxiang; Ward, Marcia M; Schneider, John E

2009-01-01

The Balanced Budget Act (BBA) of 1997 allowed some rural hospitals meeting certain requirements to convert to Critical Access Hospitals (CAHs) and changed their Medicare reimbursement from prospective to cost-based. Some subsequent CAH-related laws reduced restrictions and increased payments, and the number of CAHs grew rapidly. To examine factors related to hospitals' decisions to convert and time to CAH conversion. Eighty-nine rural hospitals in Iowa were characterized and observed from 1998 to 2005. Cox proportional hazards models were used to identify the determinants of time to CAH conversion. T-test and one-covariate Cox regression indicated that, in 1998, Iowa rural hospitals with more staffed beds, discharges, and acute inpatient days, higher operating margin, lower skilled swing bed days relative to acute days, and located in relatively high density counties were more likely to convert later or not convert before 2006. Multiple Cox regression with baseline covariates indicated that lower number of discharges and average length of stay (ALOS) were significant after controlling all other covariates. Iowa rural hospitals' decisions regarding CAH conversion were influenced by hospital size, financial condition, skilled swing bed days relative to acute days, length of stay, proportion of Medicare acute days, and geographic factors. Although financial concerns are often cited in surveys as the main reason for conversion, lower number of discharges and ALOS are the most prominent factors affecting rural hospitals' decision on when to convert.

Developing and validating a novel metabolic tumor volume risk stratification system for supplementing non-small cell lung cancer staging.

PubMed

Pu, Yonglin; Zhang, James X; Liu, Haiyan; Appelbaum, Daniel; Meng, Jianfeng; Penney, Bill C

2018-06-07

We hypothesized that whole-body metabolic tumor volume (MTVwb) could be used to supplement non-small cell lung cancer (NSCLC) staging due to its independent prognostic value. The goal of this study was to develop and validate a novel MTVwb risk stratification system to supplement NSCLC staging. We performed an IRB-approved retrospective review of 935 patients with NSCLC and FDG-avid tumor divided into modeling and validation cohorts based on the type of PET/CT scanner used for imaging. In addition, sensitivity analysis was conducted by dividing the patient population into two randomized cohorts. Cox regression and Kaplan-Meier survival analyses were performed to determine the prognostic value of the MTVwb risk stratification system. The cut-off values (10.0, 53.4 and 155.0 mL) between the MTVwb quartiles of the modeling cohort were applied to both the modeling and validation cohorts to determine each patient's MTVwb risk stratum. The survival analyses showed that a lower MTVwb risk stratum was associated with better overall survival (all p < 0.01), independent of TNM stage together with other clinical prognostic factors, and the discriminatory power of the MTVwb risk stratification system, as measured by Gönen and Heller's concordance index, was not significantly different from that of TNM stage in both cohorts. Also, the prognostic value of the MTVwb risk stratum was robust in the two randomized cohorts. The discordance rate between the MTVwb risk stratum and TNM stage or substage was 45.1% in the modeling cohort and 50.3% in the validation cohort. This study developed and validated a novel MTVwb risk stratification system, which has prognostic value independent of the TNM stage and other clinical prognostic factors in NSCLC, suggesting that it could be used for further NSCLC pretreatment assessment and for refining treatment decisions in individual patients.

Establishment and Validation of GV-SAPS II Scoring System for Non-Diabetic Critically Ill Patients.

PubMed

Liu, Wen-Yue; Lin, Shi-Gang; Zhu, Gui-Qi; Poucke, Sven Van; Braddock, Martin; Zhang, Zhongheng; Mao, Zhi; Shen, Fei-Xia; Zheng, Ming-Hua

2016-01-01

Recently, glucose variability (GV) has been reported as an independent risk factor for mortality in non-diabetic critically ill patients. However, GV is not incorporated in any severity scoring system for critically ill patients currently. The aim of this study was to establish and validate a modified Simplified Acute Physiology Score II scoring system (SAPS II), integrated with GV parameters and named GV-SAPS II, specifically for non-diabetic critically ill patients to predict short-term and long-term mortality. Training and validation cohorts were exacted from the Multiparameter Intelligent Monitoring in Intensive Care database III version 1.3 (MIMIC-III v1.3). The GV-SAPS II score was constructed by Cox proportional hazard regression analysis and compared with the original SAPS II, Sepsis-related Organ Failure Assessment Score (SOFA) and Elixhauser scoring systems using area under the curve of the receiver operator characteristic (auROC) curve. 4,895 and 5,048 eligible individuals were included in the training and validation cohorts, respectively. The GV-SAPS II score was established with four independent risk factors, including hyperglycemia, hypoglycemia, standard deviation of blood glucose levels (GluSD), and SAPS II score. In the validation cohort, the auROC values of the new scoring system were 0.824 (95% CI: 0.813-0.834, P< 0.001) and 0.738 (95% CI: 0.725-0.750, P< 0.001), respectively for 30 days and 9 months, which were significantly higher than other models used in our study (all P < 0.001). Moreover, Kaplan-Meier plots demonstrated significantly worse outcomes in higher GV-SAPS II score groups both for 30-day and 9-month mortality endpoints (all P< 0.001). We established and validated a modified prognostic scoring system that integrated glucose variability for non-diabetic critically ill patients, named GV-SAPS II. It demonstrated a superior prognostic capability and may be an optimal scoring system for prognostic evaluation in this patient group.

Development and validation of a nomogram predicting recurrence risk in women with symptomatic urinary tract infection.

PubMed

Cai, Tommaso; Mazzoli, Sandra; Migno, Serena; Malossini, Gianni; Lanzafame, Paolo; Mereu, Liliana; Tateo, Saverio; Wagenlehner, Florian M E; Pickard, Robert S; Bartoletti, Riccardo

2014-09-01

To develop and externally validate a novel nomogram predicting recurrence risk probability at 12 months in women after an episode of urinary tract infection. The study included 768 women from Santa Maria Annunziata Hospital, Florence, Italy, affected by urinary tract infections from January 2005 to December 2009. Another 373 women with the same criteria enrolled at Santa Chiara Hospital, Trento, Italy, from January 2010 to June 2012 were used to externally validate and calibrate the nomogram. Univariate and multivariate Cox regression models tested the relationship between urinary tract infection recurrence risk, and patient clinical and laboratory characteristics. The nomogram was evaluated by calculating concordance probabilities, as well as testing calibration of predicted urinary tract infection recurrence with observed urinary tract infections. Nomogram variables included: number of partners, bowel function, type of pathogens isolated (Gram-positive/negative), hormonal status, number of previous urinary tract infection recurrences and previous treatment of asymptomatic bacteriuria. Of the original development data, 261 out of 768 women presented at least one episode of recurrence of urinary tract infection (33.9%). The nomogram had a concordance index of 0.85. The nomogram predictions were well calibrated. This model showed high discrimination accuracy and favorable calibration characteristics. In the validation group (373 women), the overall c-index was 0.83 (P = 0.003, 95% confidence interval 0.51-0.99), whereas the area under the receiver operating characteristic curve was 0.85 (95% confidence interval 0.79-0.91). The present nomogram accurately predicts the recurrence risk of urinary tract infection at 12 months, and can assist in identifying women at high risk of symptomatic recurrence that can be suitable candidates for a prophylactic strategy. © 2014 The Japanese Urological Association.

Development and validation of a radiomics nomogram for progression-free survival prediction in stage IV EGFR-mutant non-small cell lung cancer

NASA Astrophysics Data System (ADS)

Song, Jiangdian; Zang, Yali; Li, Weimin; Zhong, Wenzhao; Shi, Jingyun; Dong, Di; Fang, Mengjie; Liu, Zaiyi; Tian, Jie

2017-03-01

Accurately predict the risk of disease progression and benefit of tyrosine kinase inhibitors (TKIs) therapy for stage IV non-small cell lung cancer (NSCLC) patients with activing epidermal growth factor receptor (EGFR) mutations by current staging methods are challenge. We postulated that integrating a classifier consisted of multiple computed tomography (CT) phenotypic features, and other clinicopathological risk factors into a single model could improve risk stratification and prediction of progression-free survival (PFS) of EGFR TKIs for these patients. Patients confirmed as stage IV EGFR-mutant NSCLC received EGFR TKIs with no resection; pretreatment contrast enhanced CT performed at approximately 2 weeks before the treatment was enrolled. A six-CT-phenotypic-feature-based classifier constructed by the LASSO Cox regression model, and three clinicopathological factors: pathologic N category, performance status (PS) score, and intrapulmonary metastasis status were used to construct a nomogram in a training set of 115 patients. The prognostic and predictive accuracy of this nomogram was then subjected to an external independent validation of 107 patients. PFS between the training and independent validation set is no statistical difference by Mann-Whitney U test (P = 0.2670). PFS of the patients could be predicted with good consistency compared with the actual survival. C-index of the proposed individualized nomogram in the training set (0·707, 95%CI: 0·643, 0·771) and the independent validation set (0·715, 95%CI: 0·650, 0·780) showed the potential of clinical prognosis to predict PFS of stage IV EGFR-mutant NSCLC from EGFR TKIs. The individualized nomogram might facilitate patient counselling and individualise management of patients with this disease.

Validation and Development of a Modified Breast Graded Prognostic Assessment As a Tool for Survival in Patients With Breast Cancer and Brain Metastases.

PubMed

Subbiah, Ishwaria M; Lei, Xiudong; Weinberg, Jeffrey S; Sulman, Erik P; Chavez-MacGregor, Mariana; Tripathy, Debu; Gupta, Rohan; Varma, Ankur; Chouhan, Jay; Guevarra, Richard P; Valero, Vicente; Gilbert, Mark R; Gonzalez-Angulo, Ana M

2015-07-10

Several indices have been developed to predict overall survival (OS) in patients with breast cancer with brain metastases, including the breast graded prognostic assessment (breast-GPA), comprising age, tumor subtype, and Karnofsky performance score. However, number of brain metastases-a highly relevant clinical variable-is less often incorporated into the final model. We sought to validate the existing breast-GPA in an independent larger cohort and refine it integrating number of brain metastases. Data were retrospectively gathered from a prospectively maintained institutional database. Patients with newly diagnosed brain metastases from 1996 to 2013 were identified. After validating the breast-GPA, multivariable Cox regression and recursive partitioning analysis led to the development of the modified breast-GPA. The performances of the breast-GPA and modified breast-GPA were compared using the concordance index. In our cohort of 1,552 patients, the breast-GPA was validated as a prognostic tool for OS (P < .001). In multivariable analysis of the breast-GPA and number of brain metastases (> three v ≤ three), both were independent predictors of OS. We therefore developed the modified breast-GPA integrating a fourth clinical parameter. Recursive partitioning analysis reinforced the prognostic significance of these four factors. Concordance indices were 0.78 (95% CI, 0.77 to 0.80) and 0.84 (95% CI, 0.83 to 0.85) for the breast-GPA and modified breast-GPA, respectively (P < .001). The modified breast-GPA incorporates four simple clinical parameters of high prognostic significance. This index has an immediate role in the clinic as a formative part of the clinician's discussion of prognosis and direction of care and as a potential patient selection tool for clinical trials. © 2015 by American Society of Clinical Oncology.

Predicting prolonged dose titration in patients starting warfarin.

PubMed

Finkelman, Brian S; French, Benjamin; Bershaw, Luanne; Brensinger, Colleen M; Streiff, Michael B; Epstein, Andrew E; Kimmel, Stephen E

2016-11-01

Patients initiating warfarin therapy generally experience a dose-titration period of weeks to months, during which time they are at higher risk of both thromboembolic and bleeding events. Accurate prediction of prolonged dose titration could help clinicians determine which patients might be better treated by alternative anticoagulants that, while more costly, do not require dose titration. A prediction model was derived in a prospective cohort of patients starting warfarin (n = 390), using Cox regression, and validated in an external cohort (n = 663) from a later time period. Prolonged dose titration was defined as a dose-titration period >12 weeks. Predictor variables were selected using a modified best subsets algorithm, using leave-one-out cross-validation to reduce overfitting. The final model had five variables: warfarin indication, insurance status, number of doctor's visits in the previous year, smoking status, and heart failure. The area under the ROC curve (AUC) in the derivation cohort was 0.66 (95%CI 0.60, 0.74) using leave-one-out cross-validation, but only 0.59 (95%CI 0.54, 0.64) in the external validation cohort, and varied across clinics. Including genetic factors in the model did not improve the area under the ROC curve (0.59; 95%CI 0.54, 0.65). Relative utility curves indicated that the model was unlikely to provide a clinically meaningful benefit compared with no prediction. Our results suggest that prolonged dose titration cannot be accurately predicted in warfarin patients using traditional clinical, social, and genetic predictors, and that accurate prediction will need to accommodate heterogeneities across clinical sites and over time. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Lymph nodes ratio based nomogram predicts survival of resectable gastric cancer regardless of the number of examined lymph nodes.

PubMed

Chen, Shangxiang; Rao, Huamin; Liu, Jianjun; Geng, Qirong; Guo, Jing; Kong, Pengfei; Li, Shun; Liu, Xuechao; Sun, Xiaowei; Zhan, Youqing; Xu, Dazhi

2017-07-11

To develop a nomogram to predict the prognosis of gastric cancer patients on the basis of metastatic lymph nodes ratio (mLNR), especially in the patients with total number of examined lymph nodes (TLN) less than 15. The nomogram was constructed based on a retrospective database that included 2,205 patients underwent curative resection in Cancer Center, Sun Yat-sen University (SYSUCC). Resectable gastric cancer (RGC) patients underwent curative resection before December 31, 2008 were assigned as the training set (n=1,470) and those between January 1, 2009 and December 31, 2012 were selected as the internal validation set (n=735). Additional external validations were also performed separately by an independent data set (n=602) from Jiangxi Provincial Cancer Hospital (JXCH) in Jiangxi, China and a data set (n=3,317) from the Surveillance, Epidemiology, and End Results (SEER) database. The Independent risk factors were identified by Multivariate Cox Regression. In the SYSUCC set, TNM (Tumor-node-metastasis) and TRM-based (Tumor-Positive Nodes Ratio-Metastasis) nomograms were constructed respectively. The TNM-based nomogram showed better discrimination than the AJCC-TNM staging system (C-index: 0.73 versus 0.69, p<0.01). When the mLNR was included in the nomogram, the C-index increased to 0.76. Furthermore, the C-index in the TRM-based nomogram was similar between TLN ≥16 (C-index: 0.77) and TLN ≤15 (C-index: 0.75). The discrimination was further ascertained by internal and external validations. We developed and validated a novel TRM-based nomogram that provided more accurate prediction of survival for gastric cancer patients who underwent curative resection, regardless of the number of examined lymph nodes.

Risk score to predict the outcome of patients with cerebral vein and dural sinus thrombosis.

PubMed

Ferro, José M; Bacelar-Nicolau, Helena; Rodrigues, Teresa; Bacelar-Nicolau, Leonor; Canhão, Patrícia; Crassard, Isabelle; Bousser, Marie-Germaine; Dutra, Aurélio Pimenta; Massaro, Ayrton; Mackowiack-Cordiolani, Marie-Anne; Leys, Didier; Fontes, João; Stam, Jan; Barinagarrementeria, Fernando

2009-01-01

Around 15% of patients die or become dependent after cerebral vein and dural sinus thrombosis (CVT). We used the International Study on Cerebral Vein and Dural Sinus Thrombosis (ISCVT) sample (624 patients, with a median follow-up time of 478 days) to develop a Cox proportional hazards regression model to predict outcome, dichotomised by a modified Rankin Scale score >2. From the model hazard ratios, a risk score was derived and a cut-off point selected. The model and the score were tested in 2 validation samples: (1) the prospective Cerebral Venous Thrombosis Portuguese Collaborative Study Group (VENOPORT) sample with 91 patients; (2) a sample of 169 consecutive CVT patients admitted to 5 ISCVT centres after the end of the ISCVT recruitment period. Sensitivity, specificity, c statistics and overall efficiency to predict outcome at 6 months were calculated. The model (hazard ratios: malignancy 4.53; coma 4.19; thrombosis of the deep venous system 3.03; mental status disturbance 2.18; male gender 1.60; intracranial haemorrhage 1.42) had overall efficiencies of 85.1, 84.4 and 90.0%, in the derivation sample and validation samples 1 and 2, respectively. Using the risk score (range from 0 to 9) with a cut-off of >or=3 points, overall efficiency was 85.4, 84.4 and 90.1% in the derivation sample and validation samples 1 and 2, respectively. Sensitivity and specificity in the combined samples were 96.1 and 13.6%, respectively. The CVT risk score has a good estimated overall rate of correct classifications in both validation samples, but its specificity is low. It can be used to avoid unnecessary or dangerous interventions in low-risk patients, and may help to identify high-risk CVT patients. (c) 2009 S. Karger AG, Basel.

Prognostic nomogram and score to predict overall survival in locally advanced untreated pancreatic cancer (PROLAP)

PubMed Central

Vernerey, Dewi; Huguet, Florence; Vienot, Angélique; Goldstein, David; Paget-Bailly, Sophie; Van Laethem, Jean-Luc; Glimelius, Bengt; Artru, Pascal; Moore, Malcolm J; André, Thierry; Mineur, Laurent; Chibaudel, Benoist; Benetkiewicz, Magdalena; Louvet, Christophe; Hammel, Pascal; Bonnetain, Franck

2016-01-01

Background: The management of locally advanced pancreatic cancer (LAPC) patients remains controversial. Better discrimination for overall survival (OS) at diagnosis is needed. We address this issue by developing and validating a prognostic nomogram and a score for OS in LAPC (PROLAP). Methods: Analyses were derived from 442 LAPC patients enrolled in the LAP07 trial. The prognostic ability of 30 baseline parameters was evaluated using univariate and multivariate Cox regression analyses. Performance assessment and internal validation of the final model were done with Harrell's C-index, calibration plot and bootstrap sample procedures. On the basis of the final model, a prognostic nomogram and a score were developed, and externally validated in 106 consecutive LAPC patients treated in Besançon Hospital, France. Results: Age, pain, tumour size, albumin and CA 19-9 were independent prognostic factors for OS. The final model had good calibration, acceptable discrimination (C-index=0.60) and robust internal validity. The PROLAP score has the potential to delineate three different prognosis groups with median OS of 15.4, 11.7 and 8.5 months (log-rank P<0.0001). The score ability to discriminate OS was externally confirmed in 63 (59%) patients with complete clinical data derived from a data set of 106 consecutive LAPC patients; median OS of 18.3, 14.1 and 7.6 months for the three groups (log-rank P<0.0001). Conclusions: The PROLAP nomogram and score can accurately predict OS before initiation of induction chemotherapy in LAPC-untreated patients. They may help to optimise clinical trials design and might offer the opportunity to define risk-adapted strategies for LAPC management in the future. PMID:27404456

Three-Gene Immunohistochemical Panel Adds to Clinical Staging Algorithms to Predict Prognosis for Patients With Esophageal Adenocarcinoma

PubMed Central

Ong, Chin-Ann J.; Shapiro, Joel; Nason, Katie S.; Davison, Jon M.; Liu, Xinxue; Ross-Innes, Caryn; O'Donovan, Maria; Dinjens, Winand N.M.; Biermann, Katharina; Shannon, Nicholas; Worster, Susannah; Schulz, Laura K.E.; Luketich, James D.; Wijnhoven, Bas P.L.; Hardwick, Richard H.; Fitzgerald, Rebecca C.

2013-01-01

Purpose Esophageal adenocarcinoma (EAC) is a highly aggressive disease with poor long-term survival. Despite growing knowledge of its biology, no molecular biomarkers are currently used in routine clinical practice to determine prognosis or aid clinical decision making. Hence, this study set out to identify and validate a small, clinically applicable immunohistochemistry (IHC) panel for prognostication in patients with EAC. Patients and Methods We recently identified eight molecular prognostic biomarkers using two different genomic platforms. IHC scores of these biomarkers from a UK multicenter cohort (N = 374) were used in univariate Cox regression analysis to determine the smallest biomarker panel with the greatest prognostic power with potential therapeutic relevance. This new panel was validated in two independent cohorts of patients with EAC who had undergone curative esophagectomy from the United States and Europe (N = 666). Results Three of the eight previously identified prognostic molecular biomarkers (epidermal growth factor receptor [EGFR], tripartite motif-containing 44 [TRIM44], and sirtuin 2 [SIRT2]) had the strongest correlation with long-term survival in patients with EAC. Applying these three biomarkers as an IHC panel to the validation cohort segregated patients into two different prognostic groups (P < .01). Adjusting for known survival covariates, including clinical staging criteria, the IHC panel remained an independent predictor, with incremental adverse overall survival (OS) for each positive biomarker (hazard ratio, 1.20; 95% CI, 1.03 to 1.40 per biomarker; P = .02). Conclusion We identified and validated a clinically applicable IHC biomarker panel, consisting of EGFR, TRIM44, and SIRT2, that is independently associated with OS and provides additional prognostic information to current survival predictors such as stage. PMID:23509313

Resveratrol promotes regression of renal carcinoma cells via a renin-angiotensin system suppression-dependent mechanism.

PubMed

Li, Jianchang; Qiu, Mingning; Chen, Lieqian; Liu, Lei; Tan, Guobin; Liu, Jianjun

2017-02-01

The aim of the present study was to investigate the effect of resveratrol on renal carcinoma cells and explore possible renin-angiotensin system-associated mechanisms. Subsequent to resveratrol treatment, the cell viability, apoptosis rate, cytotoxicity levels, caspase 3/7 activity and the levels of angiotensin II (AngII), AngII type 1 receptor (AT1R), vascular endothelial growth factor (VEGF) and cyclooxygenase-2 (COX-2) were evaluated in renal carcinoma cells. The effects of AngII, AT1R, VEGF and COX-2 on resveratrol-induced cell growth inhibition and apoptosis were also examined. The results indicated that resveratrol treatment may suppress growth, induce apoptosis, and decrease AngII, AT1R, VEGF and COX-2 levels in renal carcinoma ACHN and A498 cells. In addition, resveratrol-induced cell growth suppression and apoptosis were reversed when co-culturing with AT1R or VEGF. Thus, resveratrol may suppress renal carcinoma cell proliferation and induce apoptosis via an AT1R/VEGF pathway.

Adjuvant radiotherapy after breast conserving surgery - a comparative effectiveness research study.

PubMed

Corradini, Stefanie; Niyazi, Maximilian; Niemoeller, Olivier M; Li, Minglun; Roeder, Falk; Eckel, Renate; Schubert-Fritschle, Gabriele; Scheithauer, Heike R; Harbeck, Nadia; Engel, Jutta; Belka, Claus

2015-01-01

The purpose of this retrospective outcome study was to validate the effectiveness of postoperative radiotherapy in breast conserving therapy (BCT) and to evaluate possible causes for omission of radiotherapy after breast conserving surgery (BCS) in a non-trial population. Data were provided by the population-based Munich Cancer Registry. The study included epidemiological data of 30.811 patients diagnosed with breast cancer from 1998 to 2012. The effect of omitting radiotherapy was analysed using Kaplan-Meier-estimates and Cox proportional hazard regression. Variables predicting omission of radiotherapy were analysed using multivariate logistic regression. Use of postoperative radiotherapy after BCS was associated with significant improvements in local control and survival. 10-year loco-regional recurrence-free-survival was 90.8% with postoperative radiotherapy vs. 77.6% with surgery alone (p<0.001). 10-year overall survival rates were 55.2% with surgery alone vs. 82.2% following postoperative radiotherapy (p<0.001). Variables predicting omission of postoperative radiotherapy included advanced age (women ⩾80 years; OR: 0.082; 95% CI: 0.071-0.094, p<0.001). This study shows a decrease in local control and a survival disadvantage if postoperative radiotherapy after breast conserving surgery is omitted in an unselected cohort of primary breast cancer patients. Due to its epidemiological nature, it cannot answer the question in whom postoperative radiotherapy can be safely omitted. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy.

PubMed

Gerami, Pedram; Cook, Robert W; Russell, Maria C; Wilkinson, Jeff; Amaria, Rodabe N; Gonzalez, Rene; Lyle, Stephen; Jackson, Gilchrist L; Greisinger, Anthony J; Johnson, Clare E; Oelschlager, Kristen M; Stone, John F; Maetzold, Derek J; Ferris, Laura K; Wayne, Jeffrey D; Cooper, Chelsea; Obregon, Roxana; Delman, Keith A; Lawson, David

2015-05-01

A gene expression profile (GEP) test able to accurately identify risk of metastasis for patients with cutaneous melanoma has been clinically validated. We aimed for assessment of the prognostic accuracy of GEP and sentinel lymph node biopsy (SLNB) tests, independently and in combination, in a multicenter cohort of 217 patients. Reverse transcription polymerase chain reaction (RT-PCR) was performed to assess the expression of 31 genes from primary melanoma tumors, and SLNB outcome was determined from clinical data. Prognostic accuracy of each test was determined using Kaplan-Meier and Cox regression analysis of disease-free, distant metastasis-free, and overall survivals. GEP outcome was a more significant and better predictor of each end point in univariate and multivariate regression analysis, compared with SLNB (P < .0001 for all). In combination with SLNB, GEP improved prognostication. For patients with a GEP high-risk outcome and a negative SLNB result, Kaplan-Meier 5-year disease-free, distant metastasis-free, and overall survivals were 35%, 49%, and 54%, respectively. Within the SLNB-negative cohort of patients, overall risk of metastatic events was higher (∼30%) than commonly found in the general population of patients with melanoma. In this study cohort, GEP was an objective tool that accurately predicted metastatic risk in SLNB-eligible patients. Copyright © 2015 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Heightened risk of preterm birth and growth restriction after a first-born son.

PubMed

Bruckner, Tim A; Mayo, Jonathan A; Gould, Jeffrey B; Stevenson, David K; Lewis, David B; Shaw, Gary M; Carmichael, Suzan L

2015-10-01

In Scandinavia, delivery of a first-born son elevates the risk of preterm delivery and intrauterine growth restriction of the next-born infant. External validity of these results remains unclear. We test this hypothesis for preterm delivery and growth restriction using the linked California birth cohort file. We examined the hypothesis separately by race and/or ethnicity. We retrieved data on 2,852,976 births to 1,426,488 mothers with at least two live births. Our within-mother tests applied Cox proportional hazards (preterm delivery, defined as less than 37 weeks gestation) and linear regression models (birth weight for gestational age percentiles). For non-Hispanic whites, Hispanics, Asians, and American Indian and/or Alaska Natives, analyses indicate heightened risk of preterm delivery and growth restriction after a first-born male. The race-specific hazard ratios for preterm delivery range from 1.07 to 1.18. Regression coefficients for birth weight for gestational age percentile range from -0.73 to -1.49. The 95% confidence intervals for all these estimates do not contain the null. By contrast, we could not reject the null for non-Hispanic black mothers. Whereas California findings generally support those from Scandinavia, the null results among non-Hispanic black mothers suggest that we do not detect adverse outcomes after a first-born male in all racial and/or ethnic groups. Copyright © 2015 Elsevier Inc. All rights reserved.

Papillary type 2 versus clear cell renal cell carcinoma: Survival outcomes.

PubMed

Simone, G; Tuderti, G; Ferriero, M; Papalia, R; Misuraca, L; Minisola, F; Costantini, M; Mastroianni, R; Sentinelli, S; Guaglianone, S; Gallucci, M

2016-11-01

To compare the cancer specific survival (CSS) between p2-RCC and a Propensity Score Matched (PSM) cohort of cc-RCC patients. Fifty-five (4.6%) patients with p2-RCC and 920 cc-RCC patients were identified within a prospectively maintained institutional dataset of 1205 histologically proved RCC patients treated with either RN or PN. Univariable and multivariable Cox regression analyses were used to identify predictors of CSS after surgical treatment. A 1:2 PSM analysis based on independent predictors of oncologic outcomes was employed and CSS was compared between PSM selected cc-RCC patients using Kaplan-Meier and Cox regression analysis. Overall, 55 (4.6%) p2-RCC and 920 (76.3%) cc-RCC patients were selected from the database; p2-RCC were significantly larger (p = 0.001), more frequently locally advanced (p < 0.001) and node positive (p < 0.001) and had significantly higher Fuhrman grade (p < 0.001) than cc-RCC. On multivariable Cox regression analysis age (p = 0.025), histologic subtype (p = 0.029), pN stage (p = 0.006), size, pT stage, cM stage, sarcomatoid features and Fuhrman grade (all p < 0.001) were independent predictors of CSS. After applying the PSM, 82 cc-RCC selected cases were comparable to 41 p2-RCC for age (p = 0.81), tumor size (p = 0.39), pT (p = 1.00) and pN (p = 0.62) stages, cM stage (p = 0.71) and Fuhrman grade (p = 1). In this PSM cohort, 5 yr CSS was significantly lower in the p2-RCC (63% vs 72.4%; p = 0.047). At multivariable Cox analysis p2 histology was an independent predictor of CSM (HR 2.46, 95% CI 1.04-5.83; p = 0.041). We confirmed the tendency of p2-RCC to present as locally advanced and metastatic disease more frequently than cc-RCC and demonstrated p2-RCC histology as an independent predictor of worse oncologic outcomes. Copyright © 2016 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Pulmonary artery enlargement and cystic fibrosis pulmonary exacerbations: a cohort study

PubMed Central

Wells, J. Michael; Farris, Roopan F.; Gosdin, Taylor A.; Dransfield, Mark T.; Wood, Michelle E.; Bell, Scott C.; Rowe, Steven M.

2017-01-01

Background Acute pulmonary exacerbations are associated with progressive lung function decline and increased mortality in cystic fibrosis (CF). The role of pulmonary vascular disease in pulmonary exacerbations is unknown. We investigated the association between pulmonary artery enlargement (PA:A>1), a marker of pulmonary vascular disease, and exacerbations. Methods We analyzed clinical, computed tomography (CT), and prospective exacerbation data in a derivation cohort of 74 adult CF patients, measuring the PA:A at the level of the PA bifurcation. We then replicated our findings in a validation cohort of 190 adult CF patients. Patients were separated into groups based on the presence or absence of a PA:A>1 and were followed for 1-year in the derivation cohort and 2-years in the validation cohort. The primary endpoint was developing ≥1 acute pulmonary exacerbation during follow-up. Linear and logistic regression models were used to determine associations between clinical factors, the PA:A ratio, and pulmonary exacerbations. We used Cox regression to determine time to first exacerbation in the validation cohort. Findings We found that PA:A>1 was present in n=37/74 (50%) of the derivation and n=89/190 (47%) of the validation cohort. In the derivation cohort, n=50/74 (68%) had ≥1 exacerbation at 1 year and n=133/190 (70%) in the validation cohort had ≥1 exacerbation after 2 years. PA:A>1 was associated with younger age in both cohorts and with elevated sweat chloride (100.5±10.9 versus 90.4±19.9mmol/L, difference between groups 10.1mmol/L [95%CI 2.5–17.7], P=0.017) in the derivation group. PA:A>1 was associated with exacerbations in the derivation (OR 3.49, 95%CI 1.18–10.3, P=0.023) and validation (OR 2.41, 95%CI 1.06–5.52, P=0.037) cohorts when adjusted for confounders. Time to first exacerbation was shorter in PA:A>1 versus PA:A<1 [HR 1.66 (95%CI 1.18–2.34), P=0.004] in unadjusted analysis, but not when adjusted for sex, BMI, prior exacerbation, positive Pseudomonas status, and FEV1/FVC [HR 1.14 (95%CI 0.80–1.62), P=0.82]). Interpretation PA enlargement is prevalent in adult CF patients and is associated with acute pulmonary exacerbation risk in two well-characterized cohorts. PA:A may be a predictive marker in CF. PMID:27298019

Synthesis and reception of prostaglandins in corpora lutea of domestic cat and lynx.

PubMed

Zschockelt, Lina; Amelkina, Olga; Siemieniuch, Marta J; Kowalewski, Mariusz P; Dehnhard, Martin; Jewgenow, Katarina; Braun, Beate C

2016-08-01

Felids show different reproductive strategies related to the luteal phase. Domestic cats exhibit a seasonal polyoestrus and ovulation is followed by formation of corpora lutea (CL). Pregnant and non-pregnant cycles are reflected by diverging plasma progesterone (P4) profiles. Eurasian and Iberian lynxes show a seasonal monooestrus, in which physiologically persistent CL (perCL) support constantly elevated plasma P4 levels. Prostaglandins (PGs) represent key regulators of reproduction, and we aimed to characterise PG synthesis in feline CL to identify their contribution to the luteal lifespan. We assessed mRNA and protein expression of PG synthases (PTGS2/COX2, PTGES, PGFS/AKR1C3) and PG receptors (PTGER2, PTGER4, PTGFR), and intra-luteal levels of PGE2 and PGF2α Therefore, CL of pregnant (pre-implantation, post-implantation, regression stages) and non-pregnant (formation, development/maintenance, early regression, late regression stages) domestic cats, and prooestrous Eurasian (perCL, pre-mating) and metoestrous Iberian (perCL, freshCL, post-mating) lynxes were investigated. Expression of PTGS2/COX2, PTGES and PTGER4 was independent of the luteal stage in the investigated species. High levels of luteotrophic PGE2 in perCL might be associated with persistence of luteal function in lynxes. Signals for PGFS/AKR1C3 expression were weak in mid and late luteal stages of cats but were absent in lynxes, concomitant with low PGF2α levels in these species. Thus, regulation of CL regression by luteal PGF2α seems negligible. In contrast, expression of PTGFR was evident in nearly all investigated CL of cat and lynxes, implying that luteal regression, e.g. at the end of pregnancy, is triggered by extra-luteal PGF2α. © 2016 Society for Reproduction and Fertility.

Bootstrapping Cox’s Regression Model.

DTIC Science & Technology

1985-11-01

crucial points a multivariate martingale central limit theorem. Involved in this is a p x p covariance matrix Z with elements T j2= f {2(s8 ) - s(l)( s ,8o...1980). The statistical analaysis of failure time data. Wiley, New York. Meyer, P.-A. (1971). Square integrable martingales, a survey. Lecture Notes

Adolescent Suicide Attempters: What Predicts Future Suicidal Acts?

ERIC Educational Resources Information Center

Groholt, Berit; Ekeberg, Oivind; Haldorsen, Tor

2006-01-01

Predictors for repetition of suicide attempts were evaluated among 92 adolescent suicide attempters 9 years after an index suicide attempt (90% females). Five were dead, two by suicide. Thirty-one (42%) of 73 had repeated a suicide attempt. In multiple Cox regression analysis, four factors had an independent predictive effect: comorbid disorders,…

The reproductive outcome of female patients with myotonic dystrophy type 1 (DM1) undergoing PGD is not affected by the size of the expanded CTG repeat tract

PubMed Central

Seneca, Sara; De Rademaeker, Marjan; Sermon, Karen; De Rycke, Martine; De Vos, Michel; Haentjens, Patrick; Devroey, Paul; Liebaers, Ingeborg

2010-01-01

Purpose This study aims to analyze the relationship between trinucleotide repeat length and reproductive outcome in a large cohort of DM1 patients undergoing ICSI and PGD. Methods Prospective cohort study. The effect of trinucleotide repeat length on reproductive outcome per patient was analyzed using bivariate analysis (T-test) and multivariate analysis using Kaplan-Meier and Cox regression analysis. Results Between 1995 and 2005, 205 cycles of ICSI and PGD were carried out for DM1 in 78 couples. The number of trinucleotide repeats does not have an influence on reproductive outcome when adjusted for age, BMI, basal FSH values, parity, infertility status and male or female affected. Cox regression analysis indicates that cumulative live birth rate is not influenced by the number of trinucleotide repeats. The only factor with a significant effect is age (p < 0.05). Conclusion There is no evidence of an effect of trinucleotide repeat length on reproductive outcome in patients undergoing ICSI and PGD. PMID:20221684

Serum Uric Acid Levels and Risk of Incident Hypertriglyceridemia: A Longitudinal Population-based Epidemiological Study.

PubMed

Zheng, Rongjiong; Ren, Ping; Chen, Qingmei; Yang, Tianmeng; Chen, Changxi; Mao, Yushan

2017-09-01

Hypertriglyceridemia is one of lipid metabolism abnormalities; however, it is still debatable whether serum uric acid is a cause or a consequence of hypertriglyceridemia. We performed the study to investigate the longitudinal association between serum uric acid levels and hypertriglyceridemia. The study included 4190 subjects without hypertriglyceridemia. The subjects had annual health examinations for 8 years to assess incident hyperglyceridemia, and the subjects were divided into groups based on the serum uric acid quartile. Cox regression models were used to analyze the risk factors of development hypertriglyceridemia. During follow-up, 1461 (34.9%) subjects developed hypertriglyceridemia over 8 years of follow-up. The cumulative incidence of hypertriglyceridemia was 28.2%, 29.1%, 36.9%, and 45.6% in quartile 1,2,3 and 4, respectively ( P for trend <0.001). Cox regression analyses indicated that serum uric acid levels were independently and positively associated with the risk of incident hypertriglyceridemia. Hypertriglyceridemia has become a serious public health problem. This longitudinal study demonstrates that high serum uric acid levels increase the risk of hypertriglyceridemia. © 2017 by the Association of Clinical Scientists, Inc.

Triglyceride and glucose (TyG) index as a predictor of incident hypertension: a 9-year longitudinal population-based study.

PubMed

Zheng, Rongjiong; Mao, Yushan

2017-09-13

Hypertension and the triglyceride and glucose index both have been associated with insulin resistance; however, the longitudinal association remains unclear. This study was designed to investigate the longitudinal association between the triglyceride and glucose index and incident hypertension among the Chinese population. We studied 4686 subjects (3177 males and 1509 females) and followed up for 9 years. The subjects were divided into four groups based on the triglyceride and glucose index. Univariate and multivariate Cox regression models were used to analyse the risk factors of hypertension. After 9 years of follow-up, 2047 subjects developed hypertension. The overall 9-year cumulative incidence of hypertension was 43.7%, ranging from 28.5% in quartile 1 to 36.9% in quartile 2, 49.2% in quartile 3 and 59.8% in quartile 4 (p for trend < 0.001). Cox regression analyses indicated that higher triglyceride and glucose index was associated with an increased risk of subsequent incident hypertension. The triglyceride and glucose index can predict the incident hypertension among the Chinese population.

Time to detection of circulating microbubbles as a risk factor for symptoms of altitude decompression sickness

NASA Technical Reports Server (NTRS)

Kumar, K. V.; Calkins, Dick S.; Waligora, James M.; Gilbert, John H., III; Powell, Michael R.

1992-01-01

This study investigated the association between time at onset of circulating microbubbles (CMB) and symptoms of altitude decompression sickness (DCS), using Cox proportional hazard regression models. The study population consisted of 125 individuals who participated in direct ascent, simulated extravehicular activities profiles. Using individual CMB status as a time-dependent variable, we found that the hazard for symptoms increased significantly (at the end of 180 min at altitude) in the presence of CMB (Hazard Ratio = 29.59; 95 percent confidence interval (95 percent CI) = 7.66-114.27), compared to no CMB. Further examination was conducted on the subgroup of individuals who developed microbubbles during the test (n = 49), by using Cox regression. Individuals with late onset of CMB (greater than 60 min at altitude) showed a significantly reduced risk of symptoms (hazard ratio = 0.92; 95 percent CI = 0.89-0.95), compared to those with early onset (equal to or less than 60 min), while controlling for other risk factors. We conclude that time to detection of circulating microbubbles is an independent determinant of symptoms of DCS.

Validation of the ICON-S staging for HPV-associated oropharyngeal carcinoma using a pre-defined treatment policy.

PubMed

Porceddu, Sandro V; Milne, Rob; Brown, Elizabeth; Bernard, Anne; Rahbari, Reza; Cartmill, Bena; Foote, Matthew; McGrath, Margaret; Coward, Jermaine; Panizza, Benedict

2017-03-01

To determine whether the International Collaboration on Oropharyngeal cancer Network for Staging (ICON-S) for HPV associated oropharyngeal carcinoma (HPV+OPC) is a better discriminator of overall survival (OS), compared with the 7th edition (7th Ed) AJCC/UICC TNM staging following curative radiotherapy (RT). The 5-year OS for all patients with non-metastatic (M0) p16-confirmed OPC treated between 2005 and 2015 was determined and grouped based on the 7th Ed AJCC/UICC TNM and ICON-S staging. A total of 279 patients met the inclusion criteria. The 5-year OS with the 7th Ed TNM classification were Stage I/II 88.9% (95% CI; 70.6-100%), Stage III 93.8% (95% CI; 85.9-100%), Stage IVa 86.4% (95% CI; 81.6-91.5%) and Stage IVb 62.3% (95% CI; 46.8-82.8%). On multivariate Cox regression analysis there was no statistically significant OS difference when comparing Stage I/II with, Stage III (p=0.98, HR=0.97, 95% CI; 0.11-8.64), IVa (p=0.67, HR=1.56, 95% CI; 0.2-11.94) and IVb (p=0.11, HR=5.54, 95% CI; 0.69-44.52), respectively. The 5-year OS with ICON-S staging were Stage I 93.6% (95% CI; 89.4-98.0%), Stage II 81.9% (95% CI; 73.7-91.1%) and Stage III 69.1% (95%; 57.9-82.6%). There was a consistent decrease of OS with increasing stage. On multivariate Cox regression analysis, when compared to Stage I, OS was significantly lower for stage II (p=0.007, HR=2.84, 95% CI; 1.33-6.05) and stage III (p<0.001, HR=3.78, 95% CI; 1.81-7.92), respectively. The ICON-S staging provides better OS stratification for HPV+OPC following RT compared with the 7th Ed TNM staging. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prognosis Related to Metastatic Burden Measured by ¹⁸F-Fluorocholine PET/CT in Castration-Resistant Prostate Cancer.

PubMed

Kwee, Sandi A; Lim, John; Watanabe, Alex; Kromer-Baker, Kathleen; Coel, Marc N

2014-06-01

This study investigated the prognostic significance of metabolically active tumor volume (MATV) measurements applied to (18)F-fluorocholine PET/CT in castration-resistant prostate cancer (CRPC). (18)F-fluorocholine PET/CT imaging was performed on 30 patients with CRPC. Metastatic disease was quantified on the basis of maximum standardized uptake value (SUV(max)), MATV, and total lesion activity (TLA = MATV × mean standardized uptake value). Tumor burden indices derived from whole-body summation of PET tumor volume measurements (i.e., net MATV and net TLA) were evaluated as variables in Cox regression and Kaplan-Meier survival analyses. Net MATV ranged from 0.12 cm(3) to 1,543.9 cm(3) (median, 52.6 cm(3)). Net TLA ranged from 0.40 to 6,688.7 g (median, 225.1 g). Prostate-specific antigen level at the time of PET correlated significantly with net MATV (Pearson r = 0.65, P = 0.0001) and net TLA (r = 0.60, P = 0.0005) but not highest lesional SUV(max) of each scan. Survivors were followed for a median 23 mo (range, 6-38 mo). On Cox regression analyses, overall survival had a significant association with net MATV (P = 0.0068), net TLA (P = 0.0072), and highest lesion SUV(max) (P = 0.0173) and a borderline association with prostate-specific antigen level (P = 0.0458). Only net MATV and net TLA remained significant in univariate-adjusted survival analyses. Kaplan-Meier analysis demonstrated significant differences in survival between groups stratified by median net MATV (log-rank P = 0.0371), net TLA (log-rank P = 0.0371), and highest lesion SUV(max) (log-rank P = 0.0223). Metastatic prostate cancer detected by (18)F-fluorocholine PET/CT can be quantified on the basis of volumetric measurements of tumor metabolic activity. The prognostic value of (18)F-fluorocholine PET/CT may stem from this capacity to assess whole-body tumor burden. With further clinical validation, (18)F-fluorocholine PET-based indices of global disease activity and mortality risk could prove useful in patient-individualized treatment of CRPC. © 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Prognostic Impact of 21-Gene Recurrence Score in Patients With Stage IV Breast Cancer: TBCRC 013

PubMed Central

Lyman, Jaclyn P.; Gonen, Mithat; Voci, Amy; De Brot, Marina; Boafo, Camilla; Sing, Amy Pratt; Hwang, E. Shelley; Alvarado, Michael D.; Liu, Minetta C.; Boughey, Judy C.; McGuire, Kandace P.; Van Poznak, Catherine H.; Jacobs, Lisa K.; Meszoely, Ingrid M.; Krontiras, Helen; Babiera, Gildy V.; Norton, Larry; Morrow, Monica; Hudis, Clifford A.

2016-01-01

Purpose The objective of this study was to determine whether the 21-gene Recurrence Score (RS) provides clinically meaningful information in patients with de novo stage IV breast cancer enrolled in the Translational Breast Cancer Research Consortium (TBCRC) 013. Patients and Methods TBCRC 013 was a multicenter prospective registry that evaluated the role of surgery of the primary tumor in patients with de novo stage IV breast cancer. From July 2009 to April 2012, 127 patients from 14 sites were enrolled; 109 (86%) patients had pretreatment primary tumor samples suitable for 21-gene RS analysis. Clinical variables, time to first progression (TTP), and 2-year overall survival (OS) were correlated with the 21-gene RS by using log-rank, Kaplan-Meier, and Cox regression. Results Median patient age was 52 years (21 to 79 years); the majority had hormone receptor–positive/human epidermal growth factor receptor 2 (HER2)–negative (72 [66%]) or hormone receptor–positive/HER2-positive (20 [18%]) breast cancer. At a median follow-up of 29 months, median TTP was 20 months (95% CI, 16 to 26 months), and median survival was 49 months (95% CI, 40 months to not reached). An RS was generated for 101 (93%) primary tumor samples: 22 (23%) low risk (< 18), 29 (28%) intermediate risk (18 to 30); and 50 (49%) high risk (≥ 31). For all patients, RS was associated with TTP (P = .01) and 2-year OS (P = .04). In multivariable Cox regression models among 69 patients with estrogen receptor (ER)–positive/HER2-negative cancer, RS was independently prognostic for TTP (hazard ratio, 1.40; 95% CI, 1.05 to 1.86; P = .02) and 2-year OS (hazard ratio, 1.83; 95% CI, 1.14 to 2.95; P = .013). Conclusion The 21-gene RS is independently prognostic for both TTP and 2-year OS in ER–positive/HER2-negative de novo stage IV breast cancer. Prospective validation is needed to determine the potential role for this assay in the clinical management of this patient subset. PMID:27001590

Prognostic Impact of 21-Gene Recurrence Score in Patients With Stage IV Breast Cancer: TBCRC 013.

PubMed

King, Tari A; Lyman, Jaclyn P; Gonen, Mithat; Voci, Amy; De Brot, Marina; Boafo, Camilla; Sing, Amy Pratt; Hwang, E Shelley; Alvarado, Michael D; Liu, Minetta C; Boughey, Judy C; McGuire, Kandace P; Van Poznak, Catherine H; Jacobs, Lisa K; Meszoely, Ingrid M; Krontiras, Helen; Babiera, Gildy V; Norton, Larry; Morrow, Monica; Hudis, Clifford A

2016-07-10

The objective of this study was to determine whether the 21-gene Recurrence Score (RS) provides clinically meaningful information in patients with de novo stage IV breast cancer enrolled in the Translational Breast Cancer Research Consortium (TBCRC) 013. TBCRC 013 was a multicenter prospective registry that evaluated the role of surgery of the primary tumor in patients with de novo stage IV breast cancer. From July 2009 to April 2012, 127 patients from 14 sites were enrolled; 109 (86%) patients had pretreatment primary tumor samples suitable for 21-gene RS analysis. Clinical variables, time to first progression (TTP), and 2-year overall survival (OS) were correlated with the 21-gene RS by using log-rank, Kaplan-Meier, and Cox regression. Median patient age was 52 years (21 to 79 years); the majority had hormone receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative (72 [66%]) or hormone receptor-positive/HER2-positive (20 [18%]) breast cancer. At a median follow-up of 29 months, median TTP was 20 months (95% CI, 16 to 26 months), and median survival was 49 months (95% CI, 40 months to not reached). An RS was generated for 101 (93%) primary tumor samples: 22 (23%) low risk (< 18), 29 (28%) intermediate risk (18 to 30); and 50 (49%) high risk (≥ 31). For all patients, RS was associated with TTP (P = .01) and 2-year OS (P = .04). In multivariable Cox regression models among 69 patients with estrogen receptor (ER)-positive/HER2-negative cancer, RS was independently prognostic for TTP (hazard ratio, 1.40; 95% CI, 1.05 to 1.86; P = .02) and 2-year OS (hazard ratio, 1.83; 95% CI, 1.14 to 2.95; P = .013). The 21-gene RS is independently prognostic for both TTP and 2-year OS in ER-positive/HER2-negative de novo stage IV breast cancer. Prospective validation is needed to determine the potential role for this assay in the clinical management of this patient subset. © 2016 by American Society of Clinical Oncology.

Behavioural disorders in 6-year-old children and pyrethroid insecticide exposure: the PELAGIE mother-child cohort.

PubMed

Viel, Jean-François; Rouget, Florence; Warembourg, Charline; Monfort, Christine; Limon, Gwendolina; Cordier, Sylvaine; Chevrier, Cécile

2017-03-01

The potential impact of environmental exposure to pyrethroid insecticides on child neurodevelopment has only just started to receive attention despite their widespread use. We investigated the associations between prenatal and childhood exposure to pyrethroid insecticides and behavioural skills in 6-year-olds. The PELAGIE cohort enrolled 3421 pregnant women from Brittany, France between 2002 and 2006. 428 mothers were randomly selected for the study when their children turned 6, and 287 (67%) agreed to participate. Children's behaviour was assessed using the Strengths and Difficulties Questionnaire (SDQ). Three subscales (prosocial behaviour, internalising disorders and externalising disorders) were considered. Five pyrethroid metabolites were measured in maternal and child urine samples collected between 6 and 19 gestational weeks and at 6 years of age, respectively. Logistic regression and reverse-scale Cox regression models were used to estimate the associations between SDQ scores and urinary pyrethroid metabolite concentrations, adjusting for organophosphate metabolite concentrations and potential confounders. Increased prenatal cis -3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (DCCA) concentrations were associated with internalising difficulties (Cox p value=0.05). For childhood 3-phenoxybenzoic acid (PBA) concentrations, a positive association was observed with externalising difficulties (Cox p value=0.04) and high ORs were found for abnormal or borderline social behaviour (OR 2.93, 95% CI 1.27 to 6.78, and OR 1.91, 95% CI 0.80 to 4.57, for the intermediate and highest metabolite categories, respectively). High childhood trans -DCCA concentrations were associated with reduced externalising disorders (Cox p value=0.03). The present study suggests that exposure to certain pyrethroids, at environmental levels, may negatively affect neurobehavioral development by 6 years of age. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Effect of a community intervention programme promoting social interactions on functional disability prevention for older adults: propensity score matching and instrumental variable analyses, JAGES Taketoyo study.

PubMed

Hikichi, Hiroyuki; Kondo, Naoki; Kondo, Katsunori; Aida, Jun; Takeda, Tokunori; Kawachi, Ichiro

2015-09-01

The efficacy of promoting social interactions to improve the health of older adults is not fully established due to residual confounding and selection bias. The government of Taketoyo town, Aichi Prefecture, Japan, developed a resident-centred community intervention programme called 'community salons', providing opportunities for social interactions among local older residents. To evaluate the impact of the programme, we conducted questionnaire surveys for all older residents of Taketoyo. We carried out a baseline survey in July 2006 (prior to the introduction of the programme) and assessed the onset of functional disability during March 2012. We analysed the data of 2421 older people. In addition to the standard Cox proportional hazard regression, we conducted Cox regression with propensity score matching (PSM) and an instrumental variable (IV) analysis, using the number of community salons within a radius of 350 m from the participant's home as an instrument. In the 5 years after the first salon was launched, the salon participants showed a 6.3% lower incidence of functional disability compared with non-participants. Even adjusting for sex, age, equivalent income, educational attainment, higher level activities of daily living and depression, the Cox adjusted HR for becoming disabled was 0.49 (95% CI 0.33 to 0.72). Similar results were observed using PSM (HR 0.52, 95% CI 0.33 to 0.83) and IV-Cox analysis (HR 0.50, 95% CI 0.34 to 0.74). A community health promotion programme focused on increasing social interactions among older adults may be effective in preventing the onset of disability. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Cystic Fibrosis Associated with Worse Survival After Liver Transplantation.

PubMed

Black, Sylvester M; Woodley, Frederick W; Tumin, Dmitry; Mumtaz, Khalid; Whitson, Bryan A; Tobias, Joseph D; Hayes, Don

2016-04-01

Survival in cystic fibrosis patients after liver transplantation and liver-lung transplantation is not well studied. To discern survival rates after liver transplantation and liver-lung transplantation in patients with and without cystic fibrosis. The United Network for Organ Sharing database was queried from 1987 to 2013. Univariate Cox proportional hazards, multivariate Cox models, and propensity score matching were performed. Liver transplant and liver-lung transplant were performed in 212 and 53 patients with cystic fibrosis, respectively. Univariate Cox proportional hazards regression identified lower survival in cystic fibrosis after liver transplant compared to a reference non-cystic fibrosis liver transplant cohort (HR 1.248; 95 % CI 1.012, 1.541; p = 0.039). Supplementary analysis found graft survival was similar across the 3 recipient categories (log-rank test: χ(2) 2.68; p = 0.262). Multivariate Cox models identified increased mortality hazard among cystic fibrosis patients undergoing liver transplantation (HR 2.439; 95 % CI 1.709, 3.482; p < 0.001) and liver-lung transplantation (HR 2.753; 95 % CI 1.560, 4.861; p < 0.001). Propensity score matching of cystic fibrosis patients undergoing liver transplantation to non-cystic fibrosis controls identified a greater mortality hazard in the cystic fibrosis cohort using a Cox proportional hazards model stratified on matched pairs (HR 3.167; 95 % CI 1.265, 7.929, p = 0.014). Liver transplantation in cystic fibrosis is associated with poorer long-term patient survival compared to non-cystic fibrosis patients, although the difference is not due to graft survival.

The antagonistic effect between STAT1 and Survivin and its clinical significance in gastric cancer.

PubMed

Deng, Hao; Zhen, Hongyan; Fu, Zhengqi; Huang, Xuan; Zhou, Hongyan; Liu, Lijiang

2012-01-01

In previous studies, we observed that STAT1 and Survivin correlated negatively with gastric cancer tissues, and that the functions of the IFN-γ-STAT1 pathway and Survivin in gastric cancer are the same as those reported for other types of cancer. In this study, the SGC7901 gastric cancer cell line and 83 gastric cancer specimens were used to confirm the relationship between STAT1 and Survivin, as well as the clinical significance of this relationship in gastric cancer. IFN-γ and STAT1 and Survivin antisense oligonucleotides (ASONs) were used to knock down the expression in SGC7901 cells. The protein expression of STAT1 and Survivin was tested by immunocytochemical and image analysis methods. A gastric cancer tissue microarray was prepared and tested by immunohistochemical methods. Data were analyzed by the Spearman's rank correlation analysis, the χ(2) test and Cox's multivariate regression analysis. Upon knockdown of IFN-γ, STAT1 and Survivin expression by ASON in the SGC7901 cell line, an antagonistic effect was observed between STAT1 and Survivin. In gastric cancer tissues, STAT1 showed a negative correlation with depth of invasion (p<0.05) in gastric cancer tissues exhibiting a negative Survivin protein expression. Furthermore, in tissues exhibiting a negative STAT1 protein expression, Survivin correlated negatively with N stage (p<0.05). Pathological and molecular markers were used to conduct Cox's multivariate regression analysis, and depth of invasion and N stage were found to be prognostic factors (p<0.05). On the other hand, in tissues exhibiting a negative Survivin protein expression, Cox's multivariate regression analysis revealed that the differentiation type and STAT1 protein expression were prognostic factors (p<0.05). There is an antagonistic effect between STAT1 and Survivin in gastric cancer, and this antagonistic effect is of clinical significance in gastric cancer.

Sodium Valproate, a Histone Deacetylase Inhibitor, Is Associated With Reduced Stroke Risk After Previous Ischemic Stroke or Transient Ischemic Attack

PubMed Central

Brookes, Rebecca L.; Crichton, Siobhan; Wolfe, Charles D.A.; Yi, Qilong; Li, Linxin; Hankey, Graeme J.; Rothwell, Peter M.

2018-01-01

Background and Purpose— A variant in the histone deacetylase 9 (HDAC9) gene is associated with large artery stroke. Therefore, inhibiting HDAC9 might offer a novel secondary preventative treatment for ischemic stroke. The antiepileptic drug sodium valproate (SVA) is a nonspecific inhibitor of HDAC9. We tested whether SVA therapy given after ischemic stroke was associated with reduced recurrent stroke rate. Methods— Data were pooled from 3 prospective studies recruiting patients with previous stroke or transient ischemic attack and long-term follow-up: the South London Stroke Register, The Vitamins to Prevent Stroke Study, and the Oxford Vascular Study. Patients receiving SVA were compared with patients who received antiepileptic drugs other than SVA using survival analysis and Cox Regression. Results— A total of 11 949 patients with confirmed ischemic event were included. Recurrent stroke rate was lower in patient taking SVA (17 of 168) than other antiepileptic drugs (105 of 530; log-rank survival analysis P=0.002). On Cox regression, controlling for potential cofounders, SVA remained associated with reduced stroke (hazard ratio=0.44; 95% confidence interval: 0.3–0.7; P=0.002). A similar result was obtained when patients taking SVA were compared with all cases not taking SVA (Cox regression, hazard ratio=0.47; 95% confidence interval: 0.29–0.77; P=0.003). Conclusions— These results suggest that exposure to SVA, an inhibitor of HDAC, may be associated with a lower recurrent stroke risk although we cannot exclude residual confounding in this study design. This supports the hypothesis that HDAC9 is important in the ischemic stroke pathogenesis and that its inhibition, by SVA or a more specific HDAC9 inhibitor, is worthy of evaluation as a treatment to prevent recurrent ischemic stroke. PMID:29247141

Birth by Caesarean Section and the Risk of Adult Psychosis: A Population-Based Cohort Study.

PubMed

O'Neill, Sinéad M; Curran, Eileen A; Dalman, Christina; Kenny, Louise C; Kearney, Patricia M; Clarke, Gerard; Cryan, John F; Dinan, Timothy G; Khashan, Ali S

2016-05-01

Despite the biological plausibility of an association between obstetric mode of delivery and psychosis in later life, studies to date have been inconclusive. We assessed the association between mode of delivery and later onset of psychosis in the offspring. A population-based cohort including data from the Swedish National Registers was used. All singleton live births between 1982 and 1995 were identified (n= 1,345,210) and followed-up to diagnosis at age 16 or later. Mode of delivery was categorized as: unassisted vaginal delivery (VD), assisted VD, elective Caesarean section (CS) (before onset of labor), and emergency CS (after onset of labor). Outcomes included any psychosis; nonaffective psychoses (including schizophrenia only) and affective psychoses (including bipolar disorder only and depression with psychosis only). Cox regression analysis was used reporting partially and fully adjusted hazard ratios (HR) with 95% confidence intervals (CI). Sibling-matched Cox regression was performed to adjust for familial confounding factors. In the fully adjusted analyses, elective CS was significantly associated with any psychosis (HR 1.13, 95% CI 1.03, 1.24). Similar findings were found for nonaffective psychoses (HR 1.13, 95% CI 0.99, 1.29) and affective psychoses (HR 1.17, 95% CI 1.05, 1.31) (χ(2)for heterogeneityP= .69). In the sibling-matched Cox regression, this association disappeared (HR 1.03, 95% CI 0.78, 1.37). No association was found between assisted VD or emergency CS and psychosis. This study found that elective CS is associated with an increase in offspring psychosis. However, the association did not persist in the sibling-matched analysis, implying the association is likely due to familial confounding by unmeasured factors such as genetics or environment. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

PubMed

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. PMID:26080057

Applying Additive Hazards Models for Analyzing Survival in Patients with Colorectal Cancer in Fars Province, Southern Iran

PubMed

Madadizadeh, Farzan; Ghanbarnejad, Amin; Ghavami, Vahid; Zare Bandamiri, Mohammad; Mohammadianpanah, Mohammad

2017-04-01

Introduction: Colorectal cancer (CRC) is a commonly fatal cancer that ranks as third worldwide and third and the fifth in Iranian women and men, respectively. There are several methods for analyzing time to event data. Additive hazards regression models take priority over the popular Cox proportional hazards model if the absolute hazard (risk) change instead of hazard ratio is of primary concern, or a proportionality assumption is not made. Methods: This study used data gathered from medical records of 561 colorectal cancer patients who were admitted to Namazi Hospital, Shiraz, Iran, during 2005 to 2010 and followed until December 2015. The nonparametric Aalen’s additive hazards model, semiparametric Lin and Ying’s additive hazards model and Cox proportional hazards model were applied for data analysis. The proportionality assumption for the Cox model was evaluated with a test based on the Schoenfeld residuals and for test goodness of fit in additive models, Cox-Snell residual plots were used. Analyses were performed with SAS 9.2 and R3.2 software. Results: The median follow-up time was 49 months. The five-year survival rate and the mean survival time after cancer diagnosis were 59.6% and 68.1±1.4 months, respectively. Multivariate analyses using Lin and Ying’s additive model and the Cox proportional model indicated that the age of diagnosis, site of tumor, stage, and proportion of positive lymph nodes, lymphovascular invasion and type of treatment were factors affecting survival of the CRC patients. Conclusion: Additive models are suitable alternatives to the Cox proportionality model if there is interest in evaluation of absolute hazard change, or no proportionality assumption is made. Creative Commons Attribution License

Utilization of nonsteroidal anti-inflammatory drugs and antisecretory agents: a managed care claims analysis.

PubMed

Ofman, Joshua J; Badamgarav, Enkhe; Henning, James M; Knight, Kevin; Laine, Loren

2004-06-15

To describe patients initiating nonsteroidal anti-inflammatory drug (NSAID) therapy with regard to gastrointestinal and cardiac risks and patterns of antisecretory agent use, and to explore the relation between therapy type and subsequent outcomes. We studied patients aged 18 years or older who had continuous coverage from 1998 to 2001 and who had initiated treatment with cyclooxygenase-2 (COX-2) selective inhibitors or nonselective NSAIDs. Patients were categorized with respect to gastrointestinal and cardiac risk profiles. Proton pump inhibitor use within 15 days of initiating NSAID therapy was considered prophylactic. Logistic regression analysis was used to evaluate associations between treatment and hospitalization events, cardiac events, and health care costs. We identified 106,564 eligible NSAID initiators: 65.2% used COX-2 inhibitors and 34.8% used traditional NSAIDs. Users of COX-2 inhibitors were more likely to be at higher risk of gastrointestinal bleeding and cardiac events than were NSAID users. Proton pump inhibitor prophylaxis was most common among users of COX-2 inhibitors, but was only 11% in patients at high risk of gastrointestinal bleeding. There were no differences among treatment groups in terms of gastrointestinal or cardiac events. Initiation of COX-2 inhibitor therapy was associated with greater total health care costs. Although we found that COX-2 inhibitors were used more frequently than were traditional NSAIDs in certain groups of patients with varying cardiac or gastrointestinal risk, we did not find that their use resulted in reductions in clinical events, cotherapy with proton pump inhibitors, or costs, suggesting that a better understanding of the relation between NSAID treatment strategies and outcomes in patients with differing risk characteristics is needed.

Evaluation and validity of a LORETA normative EEG database.

PubMed

Thatcher, R W; North, D; Biver, C

2005-04-01

To evaluate the reliability and validity of a Z-score normative EEG database for Low Resolution Electromagnetic Tomography (LORETA), EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) were acquired from 106 normal subjects, and the cross-spectrum was computed and multiplied by the Key Institute's LORETA 2,394 gray matter pixel T Matrix. After a log10 transform or a Box-Cox transform the mean and standard deviation of the *.lor files were computed for each of the 2394 gray matter pixels, from 1 to 30 Hz, for each of the subjects. Tests of Gaussianity were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of a Z-score database was computed by measuring the approximation to a Gaussian distribution. The validity of the LORETA normative database was evaluated by the degree to which confirmed brain pathologies were localized using the LORETA normative database. Log10 and Box-Cox transforms approximated Gaussian distribution in the range of 95.64% to 99.75% accuracy. The percentage of normative Z-score values at 2 standard deviations ranged from 1.21% to 3.54%, and the percentage of Z-scores at 3 standard deviations ranged from 0% to 0.83%. Left temporal lobe epilepsy, right sensory motor hematoma and a right hemisphere stroke exhibited maximum Z-score deviations in the same locations as the pathologies. We conclude: (1) Adequate approximation to a Gaussian distribution can be achieved using LORETA by using a log10 transform or a Box-Cox transform and parametric statistics, (2) a Z-Score normative database is valid with adequate sensitivity when using LORETA, and (3) the Z-score LORETA normative database also consistently localized known pathologies to the expected Brodmann areas as an hypothesis test based on the surface EEG before computing LORETA.

WebDISCO: a web service for distributed cox model learning without patient-level data sharing.

PubMed

Lu, Chia-Lun; Wang, Shuang; Ji, Zhanglong; Wu, Yuan; Xiong, Li; Jiang, Xiaoqian; Ohno-Machado, Lucila

2015-11-01

The Cox proportional hazards model is a widely used method for analyzing survival data. To achieve sufficient statistical power in a survival analysis, it usually requires a large amount of data. Data sharing across institutions could be a potential workaround for providing this added power. The authors develop a web service for distributed Cox model learning (WebDISCO), which focuses on the proof-of-concept and algorithm development for federated survival analysis. The sensitive patient-level data can be processed locally and only the less-sensitive intermediate statistics are exchanged to build a global Cox model. Mathematical derivation shows that the proposed distributed algorithm is identical to the centralized Cox model. The authors evaluated the proposed framework at the University of California, San Diego (UCSD), Emory, and Duke. The experimental results show that both distributed and centralized models result in near-identical model coefficients with differences in the range [Formula: see text] to [Formula: see text]. The results confirm the mathematical derivation and show that the implementation of the distributed model can achieve the same results as the centralized implementation. The proposed method serves as a proof of concept, in which a publicly available dataset was used to evaluate the performance. The authors do not intend to suggest that this method can resolve policy and engineering issues related to the federated use of institutional data, but they should serve as evidence of the technical feasibility of the proposed approach.Conclusions WebDISCO (Web-based Distributed Cox Regression Model; https://webdisco.ucsd-dbmi.org:8443/cox/) provides a proof-of-concept web service that implements a distributed algorithm to conduct distributed survival analysis without sharing patient level data. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Palliative care and prognosis in COPD: a systematic review with a validation cohort.

PubMed

Almagro, Pere; Yun, Sergi; Sangil, Ana; Rodríguez-Carballeira, Mónica; Marine, Meritxell; Landete, Pedro; Soler-Cataluña, Juan José; Soriano, Joan B; Miravitlles, Marc

2017-01-01

Current recommendations to consider initiation of palliative care (PC) in COPD patients are often based on an expected poor prognosis. However, this approach is not evidence-based, and which and when COPD patients should start PC is controversial. We aimed to assess whether current suggested recommendations for initiating PC were sufficiently reliable. We identified prognostic variables proposed in the literature for initiating PC; then, we ascertained their relationship with 1-year mortality, and finally, we validated their utility in our cohort of 697 patients hospitalized for COPD exacerbation. From 24 articles of 499 screened, we selected 20 variables and retrieved 48 original articles in which we were able to calculate the relationship between each of them and 1-year mortality. The number of studies where 1-year mortality was detailed for these variables ranged from 9 for previous hospitalizations or FEV 1 ≤30% to none for albumin ≤25 mg/dL. The percentage of 1-year mortality in the literature for these variables ranged from 5% to 60%. In the validation cohort study, the prevalence of these proposed variables ranged from 8% to 64%; only 10 of the 18 variables analyzed in our cohort reached statistical significance with Cox regression analysis, and none overcame an area under the curve ≥0.7. We conclude that none of the suggested criteria for initiating PC based on an expected poor vital prognosis in COPD patients in the short or medium term offers sufficient reliability, and consequently, they should be avoided as exclusive criteria for considering PC or at least critically appraised.

Palliative care and prognosis in COPD: a systematic review with a validation cohort

PubMed Central

Almagro, Pere; Yun, Sergi; Sangil, Ana; Rodríguez-Carballeira, Mónica; Marine, Meritxell; Landete, Pedro; Soler-Cataluña, Juan José; Soriano, Joan B; Miravitlles, Marc

2017-01-01

Current recommendations to consider initiation of palliative care (PC) in COPD patients are often based on an expected poor prognosis. However, this approach is not evidence-based, and which and when COPD patients should start PC is controversial. We aimed to assess whether current suggested recommendations for initiating PC were sufficiently reliable. We identified prognostic variables proposed in the literature for initiating PC; then, we ascertained their relationship with 1-year mortality, and finally, we validated their utility in our cohort of 697 patients hospitalized for COPD exacerbation. From 24 articles of 499 screened, we selected 20 variables and retrieved 48 original articles in which we were able to calculate the relationship between each of them and 1-year mortality. The number of studies where 1-year mortality was detailed for these variables ranged from 9 for previous hospitalizations or FEV1 ≤30% to none for albumin ≤25 mg/dL. The percentage of 1-year mortality in the literature for these variables ranged from 5% to 60%. In the validation cohort study, the prevalence of these proposed variables ranged from 8% to 64%; only 10 of the 18 variables analyzed in our cohort reached statistical significance with Cox regression analysis, and none overcame an area under the curve ≥0.7. We conclude that none of the suggested criteria for initiating PC based on an expected poor vital prognosis in COPD patients in the short or medium term offers sufficient reliability, and consequently, they should be avoided as exclusive criteria for considering PC or at least critically appraised. PMID:28652724

Predictive Mortality Index for Community-Dwelling Elderly Koreans

PubMed Central

Kim, Nan H.; Cho, Hyun J.; Kim, Soriul; Seo, Ji H.; Lee, Hyun J.; Yu, Ji H.; Chung, Hye S.; Yoo, Hye J.; Seo, Ji A.; Kim, Sin Gon; Baik, Sei Hyun; Choi, Dong Seop; Shin, Chol; Choi, Kyung Mook

2016-01-01

Abstract There are very few predictive indexes for long-term mortality among community-dwelling elderly Asian individuals, despite its importance, given the rapid and continuous increase in this population. We aimed to develop 10-year predictive mortality indexes for community-dwelling elderly Korean men and women based on routinely collected clinical data. We used data from 2244 elderly individuals (older than 60 years of age) from the southwest Seoul Study, a prospective cohort study, for the development of a prognostic index. An independent longitudinal cohort of 679 elderly participants was selected from the Korean Genome Epidemiology Study in Ansan City for validation. During a 10-year follow-up, 393 participants (17.5%) from the development cohort died. Nine risk factors were identified and weighed in the Cox proportional regression model to create a point scoring system: age, male sex, smoking, diabetes, systolic blood pressure, triglyceride, total cholesterol, white blood cell count, and hemoglobin. In the development cohort, the 10-year mortality risk was 6.6%, 14.8%, 18.2%, and 38.4% among subjects with 1 to 4, 5 to 7, 8 to 9, and ≥10 points, respectively. In the validation cohort, the 10-year mortality risk was 5.2%, 12.0%, 16.0%, and 16.0% according to these categories. The C-statistic for the point system was 0.73 and 0.67 in the development and validation cohorts, respectively. The present study provides valuable information for prognosis among elderly Koreans and may guide individualized approaches for appropriate care in a rapidly aging society. PMID:26844511

Regression of experimentally induced endometriosis with a new selective cyclooxygenase-2 enzyme inhibitor.

PubMed

Kilico, Ismail; Kokcu, Arif; Kefeli, Mehmet; Kandemir, Bedri

2014-01-01

Cyclooxygenase-2 (COX-2) levels increase in women with endometriosis. COX-2, via increasing prostaglandin E2, contributes to an increase in vascular endothelial growth factor. In this way, COX-2 may contribute to the progression and continuity of endometriosis. We investigated the effect of dexketoprofen trometamol, a new selective COX-2 enzyme inhibitor, on experimentally induced endometriotic cysts. Experimental endometriotic cysts were created in 60 adult female Wistar albino rats. The rats were randomized to 2 equal groups, a control (group Con) and a dexketoprofen (group Dex) group. Six weeks later, cyst volumes were measured as in vivo (volume 1). Following volume 1 measurement, for 4 weeks group Con received 0.1 ml distilled water; group Dex received 0.375 mg dexketoprofen trometamol/0.1 ml distilled water, intramuscularly, twice a day. At the end of administration, the cyst volumes were remeasured (volume 2), and the cysts totally excised and weighed. Glandular (GT) and stromal tissues (ST) and natural killer (NK) cell contents in the cyst wall were scored. NK cell content and volume 1 were not different between the 2 groups. Volume 2, cyst weight, and GT and ST contents in group Dex were significantly lower than those in group Con. Dexketoprofen trometamol significantly reduced the development of experimentally induced endometriotic cysts both macroscopically and microscopically.

Rutin inhibits B[a]PDE-induced cyclooxygenase-2 expression by targeting EGFR kinase activity.

PubMed

Choi, Seunghwan; Lim, Tae-Gyu; Hwang, Mun Kyung; Kim, Yoon-A; Kim, Jiyoung; Kang, Nam Joo; Jang, Tae Su; Park, Jun-Seong; Yeom, Myeong Hun; Lee, Ki Won

2013-11-15

Rutin is a well-known flavonoid that exists in various natural sources. Accumulative studies have represented the biological effects of rutin, such as anti-oxidative and anti-inflammatory effects. However, the underlying mechanisms of rutin and its direct targets are not understood. We investigated whether rutin reduced B[a]PDE-induced-COX-2 expression. The transactivation of AP-1 and NF-κB were inhibited by rutin. Rutin also attenuated B[a]PDE-induced Raf/MEK/ERK and Akt activation, but had no effect on the phosphorylation of EGFR. An in vitro kinase assay revealed rutin suppressed EGFR kinase activity. We also confirmed direct binding between rutin and EGFR, and found that the binding was regressed by ATP. The EGFR inhibitor also inhibited the B[a]PDE-induced MEK/ERK and Akt signaling pathways and subsequently, suppressed COX-2 expression and promoter activity, in addition to suppressing the transactivation of AP-1 and NF-κB. In EGFR(-/-)mouse embryonic fibroblast cells, B[a]PDE-induced COX-2 expression was also diminished. Collectively, rutin inhibits B[a]PDE-induced COX-2 expression by suppressing the Raf/MEK/ERK and Akt signaling pathways. EGFR appeared to be the direct target of rutin. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantifying risk of early relapse in patients with first demyelinating events: Prediction in clinical practice.

PubMed

Spelman, Tim; Meyniel, Claire; Rojas, Juan Ignacio; Lugaresi, Alessandra; Izquierdo, Guillermo; Grand'Maison, Francois; Boz, Cavit; Alroughani, Raed; Havrdova, Eva; Horakova, Dana; Iuliano, Gerardo; Duquette, Pierre; Terzi, Murat; Grammond, Pierre; Hupperts, Raymond; Lechner-Scott, Jeannette; Oreja-Guevara, Celia; Pucci, Eugenio; Verheul, Freek; Fiol, Marcela; Van Pesch, Vincent; Cristiano, Edgardo; Petersen, Thor; Moore, Fraser; Kalincik, Tomas; Jokubaitis, Vilija; Trojano, Maria; Butzkueven, Helmut

2017-09-01

Characteristics at clinically isolated syndrome (CIS) examination assist in identification of patient at highest risk of early second attack and could benefit the most from early disease-modifying drugs (DMDs). To examine determinants of second attack and validate a prognostic nomogram for individualised risk assessment of clinical conversion. Patients with CIS were prospectively followed up in the MSBase Incident Study. Predictors of clinical conversion were analysed using Cox proportional hazards regression. Prognostic nomograms were derived to calculate conversion probability and validated using concordance indices. A total of 3296 patients from 50 clinics in 22 countries were followed up for a median (inter-quartile range (IQR)) of 1.92 years (0.90, 3.71). In all, 1953 (59.3%) patients recorded a second attack. Higher Expanded Disability Status Scale (EDSS) at baseline, first symptom location, oligoclonal bands and various brain and spinal magnetic resonance imaging (MRI) metrics were all predictors of conversion. Conversely, older age and DMD exposure post-CIS were associated with reduced rates. Prognostic nomograms demonstrated high concordance between estimated and observed conversion probabilities. This multinational study shows that age at CIS onset, DMD exposure, EDSS, multiple brain and spinal MRI criteria and oligoclonal bands are associated with shorter time to relapse. Nomogram assessment may be useful in clinical practice for estimating future clinical conversion.

Early tumor shrinkage is independently associated with improved overall survival among patients with metastatic renal cell carcinoma: a validation study using the COMPARZ cohort.

PubMed

Grünwald, Viktor; Dietrich, Marion; Pond, Gregory R

2018-04-13

Early tumor shrinkage (eTS) has prognostic value in metastatic renal cell carcinoma (mRCC). We aimed to validate the role of eTS in first line treatment from the COMPARZ study (NCT00720941). 1100 patients treated with sunitinib or pazopanib were analyzed for tumor response according to RECIST 1.0. eTS was defined as tumor shrinkage by ≥ 10%. A landmark analysis was performed on day (d) 42 and 90 and Cox proportional hazards regression was computed for the prognostic effect of eTS. In patients with eTS median OS was 34.1 [CI 95% 28.4; not reached (NR)] and 33.6 (CI 95% 30.1; NR) months (mo) at d 42 and 90, respectively, compared to 19.6 (CI 95% 14.0; 28.9) and 15.1 (CI 95% 12.4; 18.7) mo for patients without eTS. There was no interaction between type of treatment and eTS (d 42 p = 0.79; d 90 p = 0.37). eTS ≥ 10% remained an independent prognostic marker in multivariable analyses at both d 42 and 90. Similar results were found for eTS at the 42 and 90 days landmarks. eTS ≥ 10% has prognostic relevance in mRCC and reflects a putative tool to guide future clinical treatment.

Serum total hCGβ level is an independent prognostic factor in transitional cell carcinoma of the urothelial tract.

PubMed

Douglas, J; Sharp, A; Chau, C; Head, J; Drake, T; Wheater, M; Geldart, T; Mead, G; Crabb, S J

2014-04-02

Serum total human chorionic gonadotrophin β subunit (hCGβ) level might have prognostic value in urothelial transitional cell carcinoma (TCC) but has not been investigated for independence from other prognostic variables. We utilised a clinical database of patients receiving chemotherapy between 2005 and 2011 for urothelial TCC and an independent cohort of radical cystectomy patients for validation purposes. Prognostic variables were tested by univariate Kaplan-Meier analyses and log-rank tests. Statistically significant variables were then assessed by multivariate Cox regression. Total hCGβ level was dichotomised at < vs ≥2 IU l(-1). A total of 235 chemotherapy patients were eligible. For neoadjuvant chemotherapy, established prognostic factors including low ECOG performance status, normal haemoglobin, lower T stage and suitability for cisplatin-based chemotherapy were associated with favourable survival in univariate analyses. In addition, low hCGβ level was favourable when assessed either before (median survival not reached vs 1.86 years, P=0.001) or on completion of chemotherapy (4.27 vs 0.42 years, P=0.000002). This was confirmed in multivariate analyses and in patients receiving first- and second-line palliative chemotherapy, and in a radical cystectomy validation set. Serum total hCGβ level is an independent prognostic factor in patients receiving chemotherapy for urothelial TCC in both curative and palliative settings.

An 8-gene qRT-PCR-based gene expression score that has prognostic value in early breast cancer

PubMed Central

2010-01-01

Background Gene expression profiling may improve prognostic accuracy in patients with early breast cancer. Our objective was to demonstrate that it is possible to develop a simple molecular signature to predict distant relapse. Methods We included 153 patients with stage I-II hormonal receptor-positive breast cancer. RNA was isolated from formalin-fixed paraffin-embedded samples and qRT-PCR amplification of 83 genes was performed with gene expression assays. The genes we analyzed were those included in the 70-Gene Signature, the Recurrence Score and the Two-Gene Index. The association among gene expression, clinical variables and distant metastasis-free survival was analyzed using Cox regression models. Results An 8-gene prognostic score was defined. Distant metastasis-free survival at 5 years was 97% for patients defined as low-risk by the prognostic score versus 60% for patients defined as high-risk. The 8-gene score remained a significant factor in multivariate analysis and its performance was similar to that of two validated gene profiles: the 70-Gene Signature and the Recurrence Score. The validity of the signature was verified in independent cohorts obtained from the GEO database. Conclusions This study identifies a simple gene expression score that complements histopathological prognostic factors in breast cancer, and can be determined in paraffin-embedded samples. PMID:20584321

Inflammatory potential of diet, weight gain, and incidence of overweight/obesity: The SUN cohort.

PubMed

Ramallal, Raúl; Toledo, Estefanía; Martínez, J Alfredo; Shivappa, Nitin; Hébert, James R; Martínez-González, Miguel A; Ruiz-Canela, Miguel

2017-06-01

This study prospectively assessed the association of the inflammatory potential of a diet using the dietary inflammatory index (DII) with average yearly weight changes and incident overweight/obesity. Seven thousand and twenty-seven university graduates with body mass index <25 from the Seguimiento Universidad de Navarra (SUN) cohort were followed up during a median of 8.1 years. The DII, a validated tool based on scientific evidence to appraise the relationship between dietary parameters and inflammatory biomarkers, was used. A validated food-frequency questionnaire was used to assess intake of total energy, food, and nutrients, from which DII scores were calculated at baseline and after 10 years of follow-up. After a median follow-up of 8.1 years, 1,433 incident cases of overweight or obesity were observed. Hazard ratios for overweight/obesity were calculated, including multivariable time-dependent Cox regression models with repeated measures of diet. The hazard ratio for subjects in the highest quartile (most pro-inflammatory diet) was 1.32 (95% confidence interval 1.08-1.60) compared with participants in the lowest quartile (most anti-inflammatory diet), with a significant linear dose-response relationship (P = 0.004). Consistently, increases in average yearly weight gains were significantly associated with proinflammatory diets. A proinflammatory diet was significantly associated with a higher annual weight gain and higher risk of developing new-onset overweight or obesity. © 2017 The Obesity Society.

Depression and incident dementia. An 8-year population-based prospective study.

PubMed

Luppa, Melanie; Luck, Tobias; Ritschel, Franziska; Angermeyer, Matthias C; Villringer, Arno; Riedel-Heller, Steffi G

2013-01-01

The aim of the study was to investigate the impact of depression (categorical diagnosis; major depression, MD) and depressive symptoms (dimensional diagnosis and symptom patterns) on incident dementia in the German general population. Within the Leipzig Longitudinal Study of the Aged (LEILA 75+), a representative sample of 1,265 individuals aged 75 years and older were interviewed every 1.5 years over 8 years (mean observation time 4.3 years; mean number of visits 4.2). Cox proportional hazards and binary logistic regressions were used to estimate the effect of baseline depression and depressive symptoms on incident dementia. The incidence of dementia was 48 per 1,000 person-years (95% confidence interval (CI) 45-51). Depressive symptoms (Hazard ratio HR 1.03, 95% CI 1.01-1.05), and in particular mood-related symptoms (HR 1.08, 95% CI 1.03-1.14), showed a significant impact on the incidence of dementia only in univariate analysis, but not after adjustment for cognitive and functional impairment. MD showed only a significant impact on incidence of dementia in Cox proportional hazards regression, but not in binary logistic regression models. The present study using different diagnostic measures of depression on future dementia found no clear significant associations of depression and incident dementia. Further in-depth investigation would help to understand the nature of depression in the context of incident dementia.

Impact of Pacemaker Lead Characteristics on Pacemaker Related Infection and Heart Perforation: A Nationwide Population-Based Cohort Study.

PubMed

Lin, Yu-Sheng; Chen, Tien-Hsing; Hung, Sheng-Ping; Chen, Dong Yi; Mao, Chun-Tai; Tsai, Ming-Lung; Chang, Shih-Tai; Wang, Chun-Chieh; Wen, Ming-Shien; Chen, Mien-Cheng

2015-01-01

Several risk factors for pacemaker (PM) related complications have been reported. However, no study has investigated the impact of lead characteristics on pacemaker-related complications. Patients who received a new pacemaker implant from January 1997 to December 2011 were selected from the Taiwan National Health Insurance Database. This population was grouped according to the pacemaker lead characteristics in terms of fixation and insulation. The impact of the characteristics of leads on early heart perforation was analyzed by multivariable logistic regression analysis, while the impact of the lead characteristics on early and late infection and late heart perforation over a three-year period were analyzed using Cox regression. This study included 36,104 patients with a mean age of 73.4±12.5 years. In terms of both early and late heart perforations, there were no significant differences between groups across the different types of fixation and insulations. In the multivariable Cox regression analysis, the pacemaker-related infection rate was significantly lower in the active fixation only group compared to either the both fixation (OR, 0.23; 95% CI, 0.07-0.80; P = 0.020) or the passive fixation group (OR, 0.26; 95% CI, 0.08-0.83; P = 0.023). There was no difference in heart perforation between active and passive fixation leads. Active fixation leads were associated with reduced risk of pacemaker-related infection.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample

PubMed Central

Wang, Ching-Yun; Song, Xiao

2017-01-01

SUMMARY Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women’s Health Initiative. PMID:27546625

Serum Uric Acid Is Associated with Poor Outcome in Black Africans in the Acute Phase of Stroke

PubMed Central

Ayeah, Chia Mark; Ba, H.; Mbahe, Salomon

2017-01-01

Background Prognostic significance of serum uric acid (SUA) in acute stroke still remains controversial. Objectives To determine the prevalence of hyperuricemia and its association with outcome of stroke patients in the Douala General Hospital (DGH). Methods This was a hospital based prospective cohort study which included acute stroke patients with baseline SUA levels and 3-month poststroke follow-up data. Associations between high SUA levels and stroke outcomes were analyzed using multiple logistic regression and survival analysis (Cox regression and Kaplan-Meier). Results A total of 701 acute stroke patients were included and the prevalence of hyperuricemia was 46.6% with a mean SUA level of 68.625 ± 24 mg/l. Elevated SUA after stroke was associated with death (OR = 2.067; 95% CI: 1.449–2.950; p < 0.001) but did not predict this issue. However, an independent association between increasing SUA concentration and mortality was noted in a Cox proportional hazards regression model (adjusted HR = 1.740; 95% CI: 1.305–2.320; p < 0.001). Furthermore, hyperuricemia was an independent predictor of poor functional outcome within 3 months after stroke (OR = 2.482; 95% CI: 1.399–4.404; p = 0.002). Conclusion The prevalence of hyperuricemia in black African stroke patients is quite high and still remains a predictor of poor outcome. PMID:29082062

Modeling the safety impacts of driving hours and rest breaks on truck drivers considering time-dependent covariates.

PubMed

Chen, Chen; Xie, Yuanchang

2014-12-01

Driving hours and rest breaks are closely related to driver fatigue, which is a major contributor to truck crashes. This study investigates the effects of driving hours and rest breaks on commercial truck driver safety. A discrete-time logistic regression model is used to evaluate the crash odds ratios of driving hours and rest breaks. Driving time is divided into 11 one hour intervals. These intervals and rest breaks are modeled as dummy variables. In addition, a Cox proportional hazards regression model with time-dependent covariates is used to assess the transient effects of rest breaks, which consists of a fixed effect and a variable effect. Data collected from two national truckload carriers in 2009 and 2010 are used. The discrete-time logistic regression result indicates that only the crash odds ratio of the 11th driving hour is statistically significant. Taking one, two, and three rest breaks can reduce drivers' crash odds by 68%, 83%, and 85%, respectively, compared to drivers who did not take any rest breaks. The Cox regression result shows clear transient effects for rest breaks. It also suggests that drivers may need some time to adjust themselves to normal driving tasks after a rest break. Overall, the third rest break's safety benefit is very limited based on the results of both models. The findings of this research can help policy makers better understand the impact of driving time and rest breaks and develop more effective rules to improve commercial truck safety. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

Are low wages risk factors for hypertension?

PubMed Central

Du, Juan

2012-01-01

Objective: Socio-economic status (SES) is strongly correlated with hypertension. But SES has several components, including income and correlations in cross-sectional data need not imply SES is a risk factor. This study investigates whether wages—the largest category within income—are risk factors. Methods: We analysed longitudinal, nationally representative US data from four waves (1999, 2001, 2003 and 2005) of the Panel Study of Income Dynamics. The overall sample was restricted to employed persons age 25–65 years, n = 17 295. Separate subsamples were constructed of persons within two age groups (25–44 and 45–65 years) and genders. Hypertension incidence was self-reported based on physician diagnosis. Our study was prospective since data from three base years (1999, 2001, 2003) were used to predict newly diagnosed hypertension for three subsequent years (2001, 2003, 2005). In separate analyses, data from the first base year were used to predict time-to-reporting hypertension. Logistic regressions with random effects and Cox proportional hazards regressions were run. Results: Negative and strongly statistically significant correlations between wages and hypertension were found both in logistic and Cox regressions, especially for subsamples containing the younger age group (25–44 years) and women. Correlations were stronger when three health variables—obesity, subjective measures of health and number of co-morbidities—were excluded from regressions. Doubling the wage was associated with 25–30% lower chances of hypertension for persons aged 25–44 years. Conclusions: The strongest evidence for low wages being risk factors for hypertension among working people were for women and persons aged 25–44 years. PMID:22262559

Are low wages risk factors for hypertension?

PubMed

Leigh, J Paul; Du, Juan

2012-12-01

Socio-economic status (SES) is strongly correlated with hypertension. But SES has several components, including income and correlations in cross-sectional data need not imply SES is a risk factor. This study investigates whether wages-the largest category within income-are risk factors. We analysed longitudinal, nationally representative US data from four waves (1999, 2001, 2003 and 2005) of the Panel Study of Income Dynamics. The overall sample was restricted to employed persons age 25-65 years, n = 17 295. Separate subsamples were constructed of persons within two age groups (25-44 and 45-65 years) and genders. Hypertension incidence was self-reported based on physician diagnosis. Our study was prospective since data from three base years (1999, 2001, 2003) were used to predict newly diagnosed hypertension for three subsequent years (2001, 2003, 2005). In separate analyses, data from the first base year were used to predict time-to-reporting hypertension. Logistic regressions with random effects and Cox proportional hazards regressions were run. Negative and strongly statistically significant correlations between wages and hypertension were found both in logistic and Cox regressions, especially for subsamples containing the younger age group (25-44 years) and women. Correlations were stronger when three health variables-obesity, subjective measures of health and number of co-morbidities-were excluded from regressions. Doubling the wage was associated with 25-30% lower chances of hypertension for persons aged 25-44 years. The strongest evidence for low wages being risk factors for hypertension among working people were for women and persons aged 25-44 years.

Sarcopenia as a predictor of mortality in elderly blunt trauma patients: Comparing the masseter to the psoas using computed tomography.

PubMed

Wallace, James D; Calvo, Richard Y; Lewis, Paul R; Brill, Jason B; Shackford, Steven R; Sise, Michael J; Sise, C Beth; Bansal, Vishal

2017-01-01

Sarcopenia, or age-related loss of muscle mass, is measurable by computed tomography (CT). In elderly trauma patients, increased mortality is associated with decreased psoas muscle cross-sectional area (P-Area) on abdominal CT. Fall is the leading cause of injury in the elderly, and head CT is more often obtained. Masseter muscle cross-sectional area (M-Area) is readily measured on head CT. Hypothesizing that M-Area is a satisfactory surrogate for P-Area, we compared the two as markers of sarcopenia and increased mortality in elderly trauma patients. All blunt-injured patients aged 65 years or older admitted to our trauma center during 2010 were included. Two-year postdischarge mortality was identified by matching records to county, state, and national death indices. Bilateral M-Area was measured on admission head CT at 2 cm below the zygomatic arch. Bilateral P-Area was measured on abdominal CT at the fourth vertebral body. Average M-Area and P-Area values were calculated for each patient. Cox proportional hazards models evaluated the relationship of M-Area and P-Area with mortality. Model predictive performance was calculated using concordance statistics. Among 487 patients, 357 with M-Area and 226 with P-Area were identified. Females had smaller M-Area (3.43 cm vs 4.18 cm; p < 0.050) and P-Area (6.50 cm vs 10.9 cm; p < 0.050) than males. Masseter muscle cross-sectional area correlated with P-Area (rho, 0.38; p < 0.001). Adjusted Cox regression models revealed decreased survival associated with declining M-Area (hazard ratio, 0.76; 95% confidence interval, 0.60-0.96) and P-Area (hazard ratio, 0.68; 95% confidence interval, 0.46-1.00). Masseter muscle cross-sectional area and P-Area discriminated equally well in best-fit models. In elderly trauma patients, M-Area is an equally valid and more readily available marker of sarcopenia and 2-year mortality than P-Area. Future study should validate M-Area as a metric to identify at-risk patients who may benefit from early intervention. Prognostic study, level III.

Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method

PubMed Central

Zhang, Tingting; Kou, S. C.

2010-01-01

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure. PMID:21258615

Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method.

PubMed

Zhang, Tingting; Kou, S C

2010-01-01

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.

Predictors of survival among hemodialysis patients: effect of perceived family support.

PubMed

Christensen, A J; Wiebe, J S; Smith, T W; Turner, C W

1994-11-01

The authors examined the role of perceived family support and symptoms of depression as predictors of survival in a sample of 78 in-center hemodialysis patients. Cox regression analysis revealed significant effects for family support (p < .005), blood urea nitrogen (p < .01), and age (p < .005). The effect for depression was not significant. The Cox model indicated that a 1-point increase on the family support measure was associated with a 13% reduction in the hazard rate (i.e., mortality). Estimated 5-year mortality rates among low family support patients were approximately 3 times higher than estimated mortality for high support patients. Differences in patient adherence to the dietary and medication regimens failed to explain the significant effect of family support.

A prospective analysis of the association between dietary fiber intake and prostate cancer risk in EPIC.

PubMed

Suzuki, Reiko; Allen, Naomi E; Key, Timothy J; Appleby, Paul N; Tjønneland, Anne; Johnsen, Nina Føns; Jensen, Majken K; Overvad, Kim; Boeing, Heiner; Pischon, Tobias; Kaaks, Rudolf; Rohrmann, Sabine; Trichopoulou, Antonia; Misirli, Gesthimani; Trichopoulos, Dimitrios; Bueno-de-Mesquita, H Bas; van Duijnhoven, Fränzel; Sacerdote, Carlotta; Pala, Valeria; Palli, Domenico; Tumino, Rosario; Ardanaz, Eva; Quirós, José Ramón; Larrañaga, Nerea; Sánchez, Maria-José; Tormo, María-José; Jakszyn, Paula; Johansson, Ingegerd; Stattin, Pär; Berglund, Göran; Manjer, Jonas; Bingham, Sheila; Khaw, Kay-Tee; Egevad, Lars; Ferrari, Pietro; Jenab, Mazda; Riboli, Elio

2009-01-01

Few studies have examined the association between dietary fiber intake and prostate cancer risk. We evaluated the association between dietary fiber intake and the risk of prostate cancer among 142,590 men in the European Prospective Investigation into Cancer and Nutrition (EPIC). Consumption of dietary fiber (total, cereal, fruit and vegetable fiber) was estimated by validated dietary questionnaires and calibrated using 24-hr dietary recalls. Incidence rate ratios were estimated using Cox regression and adjusted for potential confounding factors. During an average of 8.7 years follow-up, prostate cancer was diagnosed in 2,747 men. Overall, there was no association between dietary fiber intake (total, cereal, fruit or vegetable fiber) and prostate cancer risk, although calibrated intakes of total fiber and fruit fiber were associated with nonstatistically significant reductions in risk. There was no association between fiber derived from cereals or vegetables and risk and no evidence for heterogeneity in any of the risk estimates by stage or grade of disease. Our results suggest that dietary fiber intake is not associated with prostate cancer risk.

Econometric models of road use, accidents, and road investment decisions. Volume 2 : an econometric model of car ownership, road use, accidents, and their severity (Essay 3)

DOT National Transportation Integrated Search

1999-11-01

Using a fairly large cross-section/time-series data base, covering all provinces of Norway and all months between January 1973 and December 1994, we estimate non-linear (Box-Cox) regression equations explaining aggregate car ownership, road use, seat...

Improving Your Data Transformations: Applying the Box-Cox Transformation

ERIC Educational Resources Information Center

Osborne, Jason W.

2010-01-01

Many of us in the social sciences deal with data that do not conform to assumptions of normality and/or homoscedasticity/homogeneity of variance. Some research has shown that parametric tests (e.g., multiple regression, ANOVA) can be robust to modest violations of these assumptions. Yet the reality is that almost all analyses (even nonparametric…

The Transfer Velocity Project: A Comprehensive Look at the Transfer Function

ERIC Educational Resources Information Center

Hayward, Craig

2011-01-01

The 1999-2000 Transfer Velocity Project (TVP) cohort of 147,207 community college students is used to develop both a college-level endogenous model, appropriate for applied research and guidance for campus action, and a student-level model. Survival analysis (Cox regression) is employed to evaluate the relative contribution of 53 student-level…

Faster Remission of Chronic Depression with Combined Psychotherapy and Medication than with Each Therapy Alone

ERIC Educational Resources Information Center

Manber, Rachel; Kraemer, Helena C.; Arnow, Bruce A.; Trivedi, Madhukar H.; Rush, A. John; Thase, Michael E.; Rothbaum, Barbara O.; Klein, Daniel N.; Kocsis, James H.; Gelenberg, Alan J.; Keller, Martin E.

2008-01-01

The main aim of the present novel reanalysis of archival data was to compare the time to remission during 12 weeks of treatment of chronic depression following antidepressant medication (n = 218), psychotherapy (n = 216), and their combination (n = 222). Cox regression survival analyses revealed that the combination of medication and psychotherapy…

An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

PubMed

Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

2017-05-22

PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40. The PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer.

[Establishing a noninvasive prediction model for type 2 diabetes mellitus based on a rural Chinese population].

PubMed

Zhang, H Y; Shi, W H; Zhang, M; Yin, L; Pang, C; Feng, T P; Zhang, L; Ren, Y C; Wang, B Y; Yang, X Y; Zhou, J M; Han, C Y; Zhao, Y; Zhao, J Z; Hu, D S

2016-05-01

To provide a noninvasive type 2 diabetes mellitus (T2DM) prediction model for a rural Chinese population. From July to August, 2007 and July to August, 2008, a total of 20 194 participants aged ≥18 years were selected by cluster sampling technique from a rural population in two townships of Henan province, China. Data were collected by questionnaire interview, anthropometric measurement, and fasting plasma glucose and lipid profile examination. A total 17 265 participants were followed up from July to August, 2013 and July to October, 2014. Finally, 12 285 participants were selected for analysis. Data for these participants were randomly divided into a derivation group (derivation dataset, n= 6 143) and validation group (validation dataset, n=6 142) by 1∶1, respectively. Randomization was carried out by the use of computer-generated random numbers. A Cox regression model was used to analyze risk factors of T2DM in the derivation dataset. A T2DM prediction model was established by multiplying β by 10 for each significant variable. After the total score was calculated by the model, analysis of the receiver operating characteristic (ROC) curve was performed. The area under the ROC curve (AUC) was used for evaluating model predictability. Furthermore, the model's predictability was validated in the validation dataset and compared with the Finnish Diabetes Risk Score (FINDRISC) model. A total 779 of 12 285 participants developed T2DM during the 6-year study period. The incidence rate was 6.12% in the derivation dataset (n=376) and 6.56% in the validation dataset (n=403). The difference was not statistically significant (χ(2)=1.00, P=0.316). A total of four noninvasive T2DM prediction models were established using the Cox regression model. The ROCs of the risk score calculated by the prediction models indicated that the AUCs of these models were similar (0.67-0.70). The AUC and Youden index of model 4 was the highest. The optimal cut-off value, sensitivity, specificity, and Youden index were scores of 25, 65.96%, 66.47%, and 0.32, respectively. Age, sleep time, BMI, waist circumference, and hypertension were selected as predictive variables. Using age<30 years as reference, β values were 1.07, 1.58, and 1.67 and assigned scores were 11, 16, and 17 for age groups 30-44, 45-59, and ≥60 years, respectively. Using sleep time<8.0 h/d as reference, the β value and assigned score were 0.27 and 3, respectively, for sleep time ≥10.0 h/d. Using BMI 18.5-23.9 kg/m(2) as reference, β values were 0.53 and 1.00 and assigned scores 5 and 10, respectively, for BMI 24.0-27.9 kg/m(2), and ≥28.0 kg/m(2). Using waist circumference <85 cm for males/< 80 cm for females as reference, β values were 0.44 and 0.65 and assigned scores 4 and 7, respectively, for 85 cm ≤ waist circumference <90 cm for males/80 cm≤ waist circumference <85 cm for females, and waist circumference ≥90 cm for males/≥85 cm for females. Using nonhypertension as reference, the respective β value and assigned score were 0.34 and 3 for hypertension. The AUC performance of this model and the FINDRISC model was 0.66 and 0.64 (P=0.135), respectively, in the validation dataset. Based on this cohort study, a noninvasive prediction model that included age, sleep time, BMI, waist circumference, and hypertension was established, which is equivalent to the FINDRISC model and applicable to a rural Chinese population.

Post-approval safety issues with innovative drugs: a European cohort study.

PubMed

Mol, Peter G M; Arnardottir, Arna H; Motola, Domenico; Vrijlandt, Patrick J; Duijnhoven, Ruben G; Haaijer-Ruskamp, Flora M; de Graeff, Pieter A; Denig, Petra; Straus, Sabine M J M

2013-11-01

At time of approval, knowledge of the full benefit risk of any drug is limited, in particular with regards to safety. Post-approval surveillance of potential drug safety concerns is recognized as an important task of regulatory agencies. For innovative, often first-in-class drugs, safety knowledge at time of approval is often even less extensive and these may require tighter scrutiny post approval. We evaluated whether more post-approval serious safety issues were identified for drugs with a higher level of innovation. A cohort study was performed that included all new active substances approved under the European Centralized Procedure and for which serious safety issues were identified post-approval from 1 January 1999 to 1 January 2012. Serious safety issues were defined as issues requiring a Direct Healthcare Professional Communication to alert individual healthcare professionals of a new serious safety issue, or a safety-related drug withdrawal. Data were retrieved from publicly available websites of the Dutch Medicines Evaluation Board and the European Medicines Agency. The level of innovation was scored using a validated algorithm, grading drugs as important (A), moderate (B) or modest (C) innovations or as pharmacological or technological (pharm/tech) innovations. The data were analyzed using appropriate descriptive statistics and Kaplan-Meier analysis, with a Mantel-Cox log-rank test, and Cox-regression models correcting for follow-up duration, to identify a possible trend in serious safety issues with an increasing level of innovation. In Europe, 279 new drugs were approved between 1999 and 2011. Fifty-nine (21 %) were graded as important, 63 (23 %) moderate, or 34 (12 %) modest innovations and 123 (44 %) as non-innovative (pharm/tech), while 15 (25 %), 13 (21 %), 8 (24 %) and 17 (14 %) had post-approval safety issues, respectively (p = 0.06, linear-by-linear test). Five drugs were withdrawn from the market. The Kaplan-Meier-derived probability for having a first serious safety issue was statistically significant, log-rank (Mantel-Cox) p = 0.036. In the final adjusted Cox proportional hazard model there was no statistically significant difference in occurrence of a first serious safety issue for important, moderate and modest innovations versus non-innovative drugs; hazard ratios 1.76 (95 % CI 0.82-3.77), 1.61 (95 % CI 0.76-3.41)], and 1.25 (95 % CI 0.51-3.06), respectively. A higher level of innovation was not clearly related to an increased risk of serious safety issues identified after approval.

Dual oxidase 1: A predictive tool for the prognosis of hepatocellular carcinoma patients.

PubMed

Chen, Shengsen; Ling, Qingxia; Yu, Kangkang; Huang, Chong; Li, Ning; Zheng, Jianming; Bao, Suxia; Cheng, Qi; Zhu, Mengqi; Chen, Mingquan

2016-06-01

Dual oxidase 1 (DUOX1), which is the main source of reactive oxygen species (ROS) production in the airway, can be silenced in human lung cancer and hepatocellular carcinomas. However, the prognostic value of DUOX1 expression in hepatocellular carcinoma patients is still unclear. We investigated the prognostic value of DUOX1 expression in liver cancer patients. DUOX1 mRNA expression was determined in tumor tissues and non-tumor tissues by real‑time PCR. For evaluation of the prognostic value of DUOX1 expression, Kaplan-Meier method and Cox's proportional hazards model (univariate analysis and multivariate analysis) were employed. A simple risk score was devised by using significant variables obtained from the Cox's regression analysis to further predict the HCC patient prognosis. We observed a reduced DUOX1 mRNA level in the cancer tissues in comparison to the non‑cancer tissues. More importantly, Kaplan-Meier analysis showed that patients with high DUOX1 expression had longer disease-free survival and overall survival compared with those with low expression of DUOX1. Cox's regression analysis indicated that DUOX1 expression, age, and intrahepatic metastasis may be significant prognostic factors for disease-free survival and overall survival. Finally, we found that patients with total scores of >2 and >1 were more likely to relapse and succumb to the disease than patients whose total scores were ≤2 and ≤1. In conclusion, DUOX1 expression in liver tumors is a potential prognostic tool for patients. The risk scoring system is useful for predicting the survival of liver cancer patients after tumor resection.

Nomogram-based prediction of survival in patients with advanced oesophagogastric adenocarcinoma receiving first-line chemotherapy: a multicenter prospective study in the era of trastuzumab.

PubMed

Custodio, A; Carmona-Bayonas, A; Jiménez-Fonseca, P; Sánchez, M L; Viudez, A; Hernández, R; Cano, J M; Echavarria, I; Pericay, C; Mangas, M; Visa, L; Buxo, E; García, T; Rodríguez Palomo, A; Álvarez Manceñido, F; Lacalle, A; Macias, I; Azkarate, A; Ramchandani, A; Fernández Montes, A; López, C; Longo, F; Sánchez Bayona, R; Limón, M L; Díaz-Serrano, A; Hurtado, A; Madero, R; Gómez, C; Gallego, J

2017-06-06

To develop and validate a nomogram and web-based calculator to predict overall survival (OS) in Caucasian-advanced oesophagogastric adenocarcinoma (AOA) patients undergoing first-line combination chemotherapy. Nine hundred twenty-four AOA patients treated at 28 Spanish teaching hospitals from January 2008 to September 2014 were used as derivation cohort. The result of an adjusted-Cox proportional hazards regression was represented as a nomogram and web-based calculator. The model was validated in 502 prospectively recruited patients treated between October 2014 and December 2016. Harrell's c-index was used to evaluate discrimination. The nomogram includes seven predictors associated with OS: HER2-positive tumours treated with trastuzumab, Eastern Cooperative Oncology Group performance status, number of metastatic sites, bone metastases, ascites, histological grade, and neutrophil-to-lymphocyte ratio. Median OS was 5.8 (95% confidence interval (CI), 4.5-6.6), 9.4 (95% CI, 8.5-10.6), and 14 months (95% CI, 11.8-16) for high-, intermediate-, and low-risk groups, respectively (P<0.001), in the derivation set and 4.6 (95% CI, 3.3-8.1), 12.7 (95% CI, 11.3-14.3), and 18.3 months (95% CI, 14.6-24.2) for high-, intermediate-, and low-risk groups, respectively (P<0.001), in the validation set. The nomogram is well-calibrated and reveals acceptable discriminatory capacity, with optimism-corrected c-indices of 0.618 (95% CI, 0.591-0.631) and 0.673 (95% CI, 0.636-0.709) in derivation and validation groups, respectively. The AGAMENON nomogram outperformed the Royal Marsden Hospital (c-index=0.583; P=0.00046) and Japan Clinical Oncology Group prognostic indices (c-index=0.611; P=0.03351). We developed and validated a straightforward model to predict survival in Caucasian AOA patients initiating first-line polychemotherapy. This model can contribute to inform clinical decision-making and optimise clinical trial design.

Cyclooxygenase inhibitory compounds from Gymnosporia heterophylla aerial parts.

PubMed

Ochieng, Charles O; Opiyo, Sylvia A; Mureka, Edward W; Ishola, Ismail O

2017-06-01

Gymnosporia heterophylla (Celastraceae) is an African medicinal plants used to treat painful and inflammatory diseases with partial scientific validation. Solvent extractions followed by repeated chromatographic purification of the G. heterophylla aerial parts led to the isolation of one new β-dihydroagarofuran sesquiterpene alkaloid (1), and two triterpenes (2-3). In addition, eight known compounds including one β-dihydroagarofuran sesquiterpene alkaloid (4), and six triterpenes (5-10) were isolated. All structures were determined through extensive analysis of the NMR an MS data as well as by comparison with literature data. These compounds were evaluated for the anti-inflammatory activities against COX-1 and -2 inhibitory potentials. Most of the compound isolated showed non selective COX inhibitions except for 3-Acetoxy-1β-hydroxyLupe-20(29)-ene (5), Lup-20(29)-ene-1β,3β-diol (6) which showed COX-2 selective inhibition at 0.54 (1.85), and 0.45 (2.22) IC 50 , in mM (Selective Index), respectively. The results confirmed the presence of anti-inflammatory compounds in G. heterophylla which are important indicators for development of complementary medicine for inflammatory reactions; however, few could be useful as selective COX-2 inhibitor. Copyright © 2017 Elsevier B.V. All rights reserved.

Vitual screening and binding mode elucidation of curcumin analogues on Cyclooxygenase-2 using AYO_COX2_V1.1 protocol

NASA Astrophysics Data System (ADS)

Mulatsari, E.; Mumpuni, E.; Herfian, A.

2017-05-01

Curcumin is yellow colored phenolic compounds contained in Curcuma longa. Curcumin is known to have biological activities as anti-inflammatory, antiviral, antioxidant, and anti-infective agent [1]. Synthesis of curcumin analogue compounds has been done and some of them had biological activity like curcumin. In this research, the virtual screening of curcumin analogue compounds has been conducted. The purpose of this research was to determine the activity of these compounds as selective Cyclooxygenase-2inhibitors in in-silico. Binding mode elucidation was made by active and inactive representative compounds to see the interaction of the amino acids in the binding site of the compounds. This research used AYO_COX2_V.1.1, a structure-based virtual screening protocol (SBVS) that has been validated by Mumpuni E et al, 2014 [2]. AYO_COX2_V.1.1 protocol using a variety of integrated applications such as SPORES, PLANTS, BKchem, OpenBabel and PyMOL. The results of virtual screening conducted on 49 curcumin analogue compounds obtained 8 compounds with 4 active amino acid residues (GLY340, ILE503, PHE343, and PHE367) that were considered active as COX-2 inhibitor.

Polymorphism in COX-2 modifies the inverse association between Helicobacter pylori seropositivity and esophageal squamous cell carcinoma risk in Taiwan: a case control study

PubMed Central

2009-01-01

Background Overexpression of Cyclooxygenase-2 (COX-2) was observed in many types of cancers, including esophageal squamous cell carcinoma (ESCC). One functional SNP, COX-2 -1195G/A, has been reported to mediate susceptibility of ESCC in Chinese populations. In our previous study, the presence of Helicobacter pylori (H. pylori) was found to play a protective role in development of ESCC. The interaction of COX-2 and H. pylori in gastric cancer was well investigated. However, literature on their interaction in ESCC risk is scarce. The purpose of this study was to evaluate the association and interaction between COX-2 single nucleotide polymorphism (SNP), H. pylori infection and the risk of developing ESCC. Methods One hundred and eighty patients with ESCC and 194 controls were enrolled in this study. Personal data regarding related risk factors, including alcohol consumption, smoking habits and betel quid chewing, were collected via questionnaire. Genotypes of the COX-2 -1195 polymorphism were determined by PCR-based restriction fragment length polymorphism. H. pylori seropositivity was defined by immunochromatographic screening test. Data was analyzed by chi-squared tests and polytomous logistics regression. Results In analysis adjusting for the covariates and confounders, H. pylori seropositivity was found to be inversely association with the ESCC development (adjusted OR: 0.5, 95% CI: 0.3 – 0.9). COX-2 -1195 AA homozygous was associated with an increased risk of contracting ESCC in comparison with the non-AA group, especially among patients with H. pylori seronegative (adjusted OR ratio: 2.9, 95% CI: 1.2 – 7.3). The effect was strengthened among patients with lower third ESCC (adjusted OR ratio: 6.9, 95% CI 2.1 – 22.5). Besides, H. pylori seropositivity conveyed a notably inverse effect among patients with COX-2 AA polymorphism (AOR ratio: 0.3, 95% CI: 0.1 – 0.9), and the effect was observed to be enhanced for the lower third ESCC patients (AOR ratio: 0.09, 95% CI: 0.02 – 0.47, p for multiplicative interaction 0.008) Conclusion H. pylori seropositivity is inversely associated with the risk of ESCC in Taiwan, and COX-2 -1195 polymorphism plays a role in modifying the influence between H. pylori and ESCC, especially in lower third esophagus. PMID:19463183

Polymorphism in COX-2 modifies the inverse association between Helicobacter pylori seropositivity and esophageal squamous cell carcinoma risk in Taiwan: a case control study.

PubMed

Hu, Huang-Ming; Kuo, Chao-Hung; Lee, Chien-Hung; Wu, I-Chen; Lee, Ka-Wo; Lee, Jang-Ming; Goan, Yih-Gang; Chou, Shah-Hwa; Kao, Ein-Long; Wu, Ming-Tsang; Wu, Deng-Chyang

2009-05-23

Overexpression of Cyclooxygenase-2 (COX-2) was observed in many types of cancers, including esophageal squamous cell carcinoma (ESCC). One functional SNP, COX-2 -1195G/A, has been reported to mediate susceptibility of ESCC in Chinese populations. In our previous study, the presence of Helicobacter pylori (H. pylori) was found to play a protective role in development of ESCC. The interaction of COX-2 and H. pylori in gastric cancer was well investigated. However, literature on their interaction in ESCC risk is scarce. The purpose of this study was to evaluate the association and interaction between COX-2 single nucleotide polymorphism (SNP), H. pylori infection and the risk of developing ESCC. One hundred and eighty patients with ESCC and 194 controls were enrolled in this study. Personal data regarding related risk factors, including alcohol consumption, smoking habits and betel quid chewing, were collected via questionnaire. Genotypes of the COX-2 -1195 polymorphism were determined by PCR-based restriction fragment length polymorphism. H. pylori seropositivity was defined by immunochromatographic screening test. Data was analyzed by chi-squared tests and polytomous logistics regression. In analysis adjusting for the covariates and confounders, H. pylori seropositivity was found to be inversely association with the ESCC development (adjusted OR: 0.5, 95% CI: 0.3 - 0.9). COX-2 -1195 AA homozygous was associated with an increased risk of contracting ESCC in comparison with the non-AA group, especially among patients with H. pylori seronegative (adjusted OR ratio: 2.9, 95% CI: 1.2 - 7.3). The effect was strengthened among patients with lower third ESCC (adjusted OR ratio: 6.9, 95% CI 2.1 - 22.5). Besides, H. pylori seropositivity conveyed a notably inverse effect among patients with COX-2 AA polymorphism (AOR ratio: 0.3, 95% CI: 0.1 - 0.9), and the effect was observed to be enhanced for the lower third ESCC patients (AOR ratio: 0.09, 95% CI: 0.02 - 0.47, p for multiplicative interaction 0.008) H. pylori seropositivity is inversely associated with the risk of ESCC in Taiwan, and COX-2 -1195 polymorphism plays a role in modifying the influence between H. pylori and ESCC, especially in lower third esophagus.

Comparison of the AJCC, MSTS, and Modified Spanier Systems for Clinical and Pathologic Staging of Osteosarcoma.

PubMed

Cates, Justin M M

2017-03-01

The prognostic performance of the 2 most commonly used staging systems for skeletal sarcoma (the American Joint Committee on Cancer [AJCC] and Musculoskeletal Tumor Society [MSTS] systems) have never been compared analytically. Another staging system originally proposed by Spanier has not yet been validated. Given the recent release of the 8th edition of the AJCC Cancer Staging Manual, this study was designed to directly compare these anatomic staging systems in a series of 153 high-grade, intramedullary osteosarcomas. Kaplan-Meier curves were plotted and pairwise comparisons between each stage category were performed. Predictive accuracy of each staging system for determining 5-year disease-free survival was evaluated by comparing areas under receiver-operating characteristic curves generated from logistic regression analysis. Multiple concordance indices were calculated using bootstrapping methods (200 replications). ρk and R were estimated as measures of the variation in survival outcomes explained by the regression models. The AJCC, MSTS, and a modified version of the Spanier staging systems showed similar discriminatory abilities and no significant differences in the levels of contrast between different tumor stages across staging systems. Addition of T-category information from each staging system contributed significant prognostic information compared with a Cox proportional hazard regression model consisting only of the presence or absence of metastatic disease as a measure of disease extent. Concordance indices and predictive accuracy for 5-year disease-free survival were not significantly different among the different staging systems either. Similar findings were observed after accounting for other important prognostic variables. Additional studies are necessary to determine performance parameters of each staging system for other types of skeletal sarcoma. Prognostic performance of osteosarcoma staging systems would also be improved by incorporating nonanatomic prognostic variables into staging algorithms.

Risk model for estimating the 1-year risk of deferred lesion intervention following deferred revascularization after fractional flow reserve assessment.

PubMed

Depta, Jeremiah P; Patel, Jayendrakumar S; Novak, Eric; Gage, Brian F; Masrani, Shriti K; Raymer, David; Facey, Gabrielle; Patel, Yogesh; Zajarias, Alan; Lasala, John M; Amin, Amit P; Kurz, Howard I; Singh, Jasvindar; Bach, Richard G

2015-02-21

Although lesions deferred revascularization following fractional flow reserve (FFR) assessment have a low risk of adverse cardiac events, variability in risk for deferred lesion intervention (DLI) has not been previously evaluated. The aim of this study was to develop a prediction model to estimate 1-year risk of DLI for coronary lesions where revascularization was not performed following FFR assessment. A prediction model for DLI was developed from a cohort of 721 patients with 882 coronary lesions where revascularization was deferred based on FFR between 10/2002 and 7/2010. Deferred lesion intervention was defined as any revascularization of a lesion previously deferred following FFR. The final DLI model was developed using stepwise Cox regression and validated using bootstrapping techniques. An algorithm was constructed to predict the 1-year risk of DLI. During a mean (±SD) follow-up period of 4.0 ± 2.3 years, 18% of lesions deferred after FFR underwent DLI; the 1-year incidence of DLI was 5.3%, while the predicted risk of DLI varied from 1 to 40%. The final Cox model included the FFR value, age, current or former smoking, history of coronary artery disease (CAD) or prior percutaneous coronary intervention, multi-vessel CAD, and serum creatinine. The c statistic for the DLI prediction model was 0.66 (95% confidence interval, CI: 0.61-0.70). Patients deferred revascularization based on FFR have variation in their risk for DLI. A clinical prediction model consisting of five clinical variables and the FFR value can help predict the risk of DLI in the first year following FFR assessment. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.

Isopropanolic black cohosh extract and recurrence-free survival after breast cancer.

PubMed

Henneicke-von Zepelin, H H; Meden, H; Kostev, K; Schröder-Bernhardi, D; Stammwitz, U; Becher, H

2007-03-01

To investigate the influence of an isopropanolic Cimicifuga racemosa extract (iCR) on recurrence-free survival after breast cancer, including estrogen-dependent tumors. This pharmacoepidemiologic observational retrospective cohort study examined breast cancer patients treated at general, gynecological and internal facilities linked to a medical database in Germany. The main endpoint was disease-free survival following a diagnosis of breast cancer. The impact of treatment with iCR following diagnosis was analyzed by Cox-proportional hazards models, controlling for age and other confounders. Of 18,861 patients, a total of 1,102 had received an iCR therapy. The mean overall observation time was 3.6 years. Results showed that iCR was not associated with an increase in the risk of recurrence but associated with prolonged disease-free survival. After 2 years following initial diagnosis, 14% of the control group had developed a recurrence, while the iCR group reached this proportion after 6.5 years. The primary Cox regression model controlling for age, tamoxifen use and other confounders demonstrated a protractive effect of iCR on the rate of recurrence (hazard ratio 0.83, 95% confidence interval 0.69 0.99). This effect remained consistent throughout all variations of the statistical model, including subgroup analyses. TNM status was unknown but did not bias the iCR treatment decision as investigated separately. Hence, it was assumed to be equally distributed between treatment groups. Correlation analyses showed good internal and external validity of the database. An increase in the risk of breast cancer recurrence for women having had iCR treatment, compared to women not treated with iCR is unlikely.

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

PubMed

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

2011-07-01

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

Disease Activity in Rheumatoid Arthritis and the Risk of Cardiovascular Events

PubMed Central

Solomon, DH; Reed, G; Kremer, JM; Curtis, JR; Farkouh, ME; Harrold, LR; Hochberg, MC; Tsao, P; Greenberg, J

2015-01-01

Background Use of several immunomodulatory agents has been associated with reduced cardiovascular (CV) events in epidemiologic studies of rheumatoid arthritis (RA). However, it is unknown whether time-averaged disease activity in RA correlates with CV events. Methods We studied patients with RA followed in a longitudinal US-based registry. Time-averaged disease activity was assessed using the area under the curve of the Clinical Disease Activity Index, a validated measure of rheumatoid arthritis disease activity, assessed during follow-up. Age, gender, diabetes, hypertension, hyperlipidemia, body mass index, family history of myocardial infarction (MI), aspirin use, NSAID use presence of CV disease, and baseline immunomodulator use were assessed at baseline. Cox proportional hazards regression models were examined to determine the risk of a composite CV endpoint that included MI, stroke, and CV death. Results 24,989 subjects followed for a median of 2.7 years were included in these analyses. During follow-up, we observed 422 confirmed CV endpoints for an incidence rate of 9.08 (95% confidence interval, CI, 7.90 – 10.26) per 1,000 person-years. In models adjusting for variables noted above, a 10-point reduction in time-averaged Clinical Disease Activity Index was associated with a 26% reduction in CV risk (95% confidence interval 17-34%). These results were robust in subgroup analyses stratified by presence of CV disease, use of corticosteroids, use of non-steroidal anti-inflammatory drugs or selective COX-2 inhibitors, change in RA treatment, and also when restricted to events adjudicated as definite or probable. Conclusions Reduced time-averaged disease activity in RA is associated with fewer CV events. PMID:25776112

Applicability of Monte Carlo cross validation technique for model development and validation using generalised least squares regression

NASA Astrophysics Data System (ADS)

Haddad, Khaled; Rahman, Ataur; A Zaman, Mohammad; Shrestha, Surendra

2013-03-01

SummaryIn regional hydrologic regression analysis, model selection and validation are regarded as important steps. Here, the model selection is usually based on some measurements of goodness-of-fit between the model prediction and observed data. In Regional Flood Frequency Analysis (RFFA), leave-one-out (LOO) validation or a fixed percentage leave out validation (e.g., 10%) is commonly adopted to assess the predictive ability of regression-based prediction equations. This paper develops a Monte Carlo Cross Validation (MCCV) technique (which has widely been adopted in Chemometrics and Econometrics) in RFFA using Generalised Least Squares Regression (GLSR) and compares it with the most commonly adopted LOO validation approach. The study uses simulated and regional flood data from the state of New South Wales in Australia. It is found that when developing hydrologic regression models, application of the MCCV is likely to result in a more parsimonious model than the LOO. It has also been found that the MCCV can provide a more realistic estimate of a model's predictive ability when compared with the LOO.

Ethnicity and excess mortality in severe mental illness: a cohort study.

PubMed

Das-Munshi, Jayati; Chang, Chin-Kuo; Dutta, Rina; Morgan, Craig; Nazroo, James; Stewart, Robert; Prince, Martin J

2017-05-01

Excess mortality in severe mental illness (defined here as schizophrenia, schizoaffective disorders, and bipolar affective disorders) is well described, but little is known about this inequality in ethnic minorities. We aimed to estimate excess mortality for people with severe mental illness for five ethnic groups (white British, black Caribbean, black African, south Asian, and Irish) and to assess the association of ethnicity with mortality risk. We conducted a longitudinal cohort study of individuals with a valid diagnosis of severe mental illness between Jan 1, 2007, and Dec 31, 2014, from the case registry of the South London and Maudsley Trust (London, UK). We linked mortality data from the UK Office for National Statistics for the general population in England and Wales to our cohort, and determined all-cause and cause-specific mortality by ethnicity, standardised by age and sex to this population in 2011. We used Cox proportional hazards regression to estimate hazard ratios and a modified Cox regression, taking into account competing risks to derive sub-hazard ratios, for the association of ethnicity with all-cause and cause-specific mortality. We identified 18 201 individuals with a valid diagnosis of severe mental illness (median follow-up 6·36 years, IQR 3·26-9·92), of whom 1767 died. Compared with the general population, age-and-sex-standardised mortality ratios (SMRs) in people with severe mental illness were increased for a range of causes, including suicides (7·65, 95% CI 6·43-9·04), non-suicide unnatural causes (4·01, 3·34-4·78), respiratory disease (3·38, 3·04-3·74), cardiovascular disease (2·65, 2·45-2·86), and cancers (1·45, 1·32-1·60). SMRs were broadly similar in different ethnic groups with severe mental illness, although the south Asian group had a reduced SMR for cancer mortality (0·49, 0·21-0·96). Within the cohort with severe mental illness, hazard ratios for all-cause mortality and sub-hazard ratios for natural-cause and unnatural-cause mortality were lower in most ethnic minority groups relative to the white British group. People with severe mental illness have excess mortality relative to the general population irrespective of ethnicity. Among those with severe mental illness, some ethnic minorities have lower mortality than the white British group, for which the reasons deserve further investigation. UK Health Foundation and UK Academy of Medical Sciences. Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

All-cause mortality of elderly Australian veterans using COX-2 selective or non-selective NSAIDs: a longitudinal study

PubMed Central

Kerr, Stephen J; Rowett, Debra S; Sayer, Geoffrey P; Whicker, Susan D; Saltman, Deborah C; Mant, Andrea

2011-01-01

AIM To determine hazard ratios for all-cause mortality in elderly Australian veterans taking COX-2 selective and non-selective NSAIDs. METHODS Patient cohorts were constructed from claims databases (1997 to 2007) for veterans and dependants with full treatment entitlement irrespective of military service. Patients were grouped by initial exposure: celecoxib, rofecoxib, meloxicam, diclofenac, non-selective NSAID. A reference group was constructed of patients receiving glaucoma/hypothyroid medications and none of the study medications. Univariate and multivariate analyses were performed using Cox proportional hazards regression models. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated for each exposure group against each of the reference group. The final model was adjusted for age, gender and co-prescription as a surrogate for cardiovascular risk. Patients were censored if the gap in supply of study prescription exceeded 30 days or if another study medication was initiated. The outcome measure in all analyses was death. RESULTS Hazard ratios and 95% CIs, adjusted for age, gender and cardiovascular risk, for each group relative to the reference group were: celecoxib 1.39 (1.25, 1.55), diclofenac 1.44 (1.28, 1.62), meloxicam 1.49 (1.25, 1.78), rofecoxib 1.58 (1.39, 1.79), non-selective NSAIDs 1.76 (1.59, 1.94). CONCLUSIONS In this large cohort of Australian veterans exposed to COX-2 selective and non-selective NSAIDs, there was a significant increased mortality risk for those exposed to either COX-2-selective or non-selective NSAIDs relative to those exposed to unrelated (glaucoma/hypothyroid) medications. PMID:21276041

Prognostic factors in multiple myeloma: selection using Cox's proportional hazard model.

PubMed

Pasqualetti, P; Collacciani, A; Maccarone, C; Casale, R

1996-01-01

The pretreatment characteristics of 210 patients with multiple myeloma, observed between 1980 and 1994, were evaluated as potential prognostic factors for survival. Multivariate analysis according to Cox's proportional hazard model identified in the 160 dead patients with myeloma, among 26 different single prognostic variables, the following factors in order of importance: beta 2-microglobulin; bone marrow plasma cell percentage, hemoglobinemia, degree of lytic bone lesions, serum creatinine, and serum albumin. By analysis of these variables a prognostic index (PI), that considers the regression coefficients derived by Cox's model of all significant factors, was obtained. Using this it was possible to separate the whole patient group into three stages: stage I (PI < 1.485, 67 patients), stage II (PI: 1.485-2.090, 76 patients), and stage III (PI > 2.090, 67 patients), with a median survivals of 68, 36 and 13 months (P < 0.0001), respectively. Also the responses to therapy (P < 0.0001) and the survival curves (P < 0.00001) presented significant differences among the three subgroups. Knowledge of these factors could be of value in predicting prognosis and in planning therapy in patients with multiple myeloma.

Subjective Global Assessment-Dialysis Malnutrition Score and cardiovascular risk in hemodialysis patients: an observational cohort study.

PubMed

Spatola, Leonardo; Finazzi, Silvia; Calvetta, Albania; Reggiani, Francesco; Morenghi, Emanuela; Santostasi, Silvia; Angelini, Claudio; Badalamenti, Salvatore; Mugnai, Giacomo

2018-06-23

Malnutrition is an important risk factor for cardiovascular mortality in hemodialysis (HD) patients. However, current malnutrition biomarkers seem unable to accurately estimate the role of malnutrition in predicting cardiovascular risk. Our aim was to investigate the role of the Subjective Global Assessment-Dialysis Malnutrition Score (SGA-DMS) compared to two well-recognized comorbidity scores-Charlson Comorbidity Index (CCI) and modified CCI (excluding age-factor) (mCCI)-in predicting cardiovascular events in HD patients. In 86 maintenance HD patients followed from June 2015 to June 2017, we analyzed biohumoral data and clinical scores as risk factors for cardiovascular events (acute heart failure, acute coronary syndrome and stroke). Their impact on outcome was investigated by linear regression, Cox regression models and ROC analysis. Cardiovascular events occurred in 26/86 (30%) patients during the 2-year follow-up. Linear regression showed only age and dialysis vintage to be positively related to SGA-DMS: B 0.21 (95% CI 0.01; 0.30) p 0.05, and B 0.24 (0.09; 0.34) p 0.02, respectively, while serum albumin, normalized protein catabolic rate (nPCR) and dialysis dose (Kt/V) were negatively related to SGA-DMS: B - 1.29 (- 3.29; - 0.81) p 0.02; B - 0.08 (- 1.52; - 0.35) p 0.04 and B - 2.63 (- 5.25; - 0.22) p 0.03, respectively. At Cox regression analysis, SGA-DMS was not a risk predictor for cardiovascular events: HR 1.09 (0.9; 1.22), while both CCI and mCCI were significant predictors: HR 1.43 (1.13; 1.87) and HR 1.57 (1.20; 2.06) also in Cox adjusted models. ROC analysis reported similar AUCs for CCI and mCCI: 0.72 (0.60; 0.89) p 0.00 and 0.70 (0.58; 0.82) p 0.00, respectively, compared to SGA-DMS 0.56 (0.49; 0.72) p 0.14. SGA-DMS is not a superior and significant prognostic tool compared to CCI and mCCI in assessing cardiovascular risk in HD patients, even it allows to appraise both malnutrition and comorbidity status.

Cognition and Incident Coronary Heart Disease in Late Midlife: The Whitehall II Study

ERIC Educational Resources Information Center

Singh-Manoux, Archana; Sabia, Severine; Kivimaki, Mika; Shipley, Martin J.; Ferrie, Jane E.; Marmot, Michael G.

2009-01-01

The purpose of this study was to investigate whether cognitive function in midlife predicts incident coronary heart disease (CHD), followed up over 6 years. Data on 5292 (28% women, mean age 55) individuals free from CHD at baseline were drawn from the British Whitehall II study. We used Cox regression to model the association between cognition…

The Role of Inhibitory Control in the Development of Human Figure Drawing in Young Children

ERIC Educational Resources Information Center

Riggs, Kevin J.; Jolley, Richard P.; Simpson, Andrew

2013-01-01

We investigated the role of inhibitory control in young children's human figure drawing. We used the Bear-Dragon task as a measure of inhibitory control and used the classification system devised by Cox and Parkin to measure the development of human figure drawing. We tested 50 children aged between 40 and 64 months. Regression analysis showed…

The Association of Administrative Segregation Placement and Other Risk Factors with the Self-Injury-Free Time of Male Prisoners

ERIC Educational Resources Information Center

Lanes, Eric

2009-01-01

The current study examined the relationship between risk factors for prisoner self-injurious behavior (SIB) and the amount of time male prisoners function without engaging in SIB (SIB-free time), and obtained estimates of SIB-free time for selected SIB prisoner subgroups dependent on their housing status. Conditional Cox regression analysis…

Kawasaki Disease Increases the Incidence of Myopia.

PubMed

Kung, Yung-Jen; Wei, Chang-Ching; Chen, Liuh An; Chen, Jiin Yi; Chang, Ching-Yao; Lin, Chao-Jen; Lim, Yun-Ping; Tien, Peng-Tai; Chen, Hsuan-Ju; Huang, Yong-San; Lin, Hui-Ju; Wan, Lei

2017-01-01

The prevalence of myopia has rapidly increased in recent decades and has led to a considerable global public health concern. In this study, we elucidate the relationship between Kawasaki disease (KD) and the incidence of myopia. We used Taiwan's National Health Insurance Research Database to conduct a population-based cohort study. We identified patients diagnosed with KD and individuals without KD who were selected by frequency matched based on sex, age, and the index year. The Cox proportional hazards regression model was used to estimate the hazard ratio and 95% confidence intervals for the comparison of the 2 cohorts. The log-rank test was used to test the incidence of myopia in the 2 cohorts. A total of 532 patients were included in the KD cohort and 2128 in the non-KD cohort. The risk of myopia (hazard ratio, 1.31; 95% confidence interval, 1.08-1.58; P < 0.01) was higher among patients with KD than among those in the non-KD cohort. The Cox proportional hazards regression model showed that irrespective of age, gender, and urbanization, Kawasaki disease was an independent risk factor for myopia. Patients with Kawasaki disease exhibited a substantially higher risk for developing myopia.

Prognostic significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with stage III and IV colorectal cancer

PubMed Central

Kim, Jae Hyun; Lee, Jun Yeop; Kim, Hae Koo; Lee, Jin Wook; Jung, Sung Gyu; Jung, Kyoungwon; Kim, Sung Eun; Moon, Won; Park, Moo In; Park, Seun Ja

2017-01-01

AIM To evaluate the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in patients with colorectal cancer (CRC). METHODS Between April 1996 and December 2010, medical records from a total of 1868 patients with CRC were retrospectively reviewed. The values of simple inflammatory markers including NLR and PLR in predicting the long-term outcomes of these patients were evaluated using Kaplan-Meier curves and Cox regression models. RESULTS The median follow-up duration was 46 mo (interquartile range, 22-73). The estimation of NLR and PLR was based on the time of diagnosis. In multivariate Cox regression analysis, high NLR (≥ 3.0) and high PLR (≥ 160) were independent risk factors predicting poor long-term outcomes in patients with stage III and IV CRC. However, high NLR and high PLR were not prognostic factors in patients with stage I and II CRC. CONCLUSION In this study, we identified that high NLR (≥ 3.0) and high PLR (≥ 160) are useful prognostic factors to predict long-term outcomes in patients with stage III and IV CRC. PMID:28210087

Aspergillus Colonization of the Lung Allograft is a Risk Factor for Bronchiolitis Obliterans Syndrome

PubMed Central

Weigt, S. Samuel; Elashoff, Robert M.; Huang, Cathy; Ardehali, Abbas; Gregson, Aric L.; Kubak, Bernard; Fishbein, Michael C.; Saggar, Rajeev; Keane, Michael P.; Saggar, Rajan; Lynch, Joseph P.; Zisman, David A.; Ross, David J.; Belperio, John A.

2014-01-01

Multiple infections have been linked with the development of bronchiolitis obliterans syndrome (BOS) post-lung transplantation. Lung allograft airway colonization by Aspergillus species is common among lung transplant recipients. We hypothesized that Aspergillus colonization may promote the development of BOS and may decrease survival post-lung transplantation. We reviewed all lung transplant recipients transplanted in our center between 1/2000 and 6/2006. Bronchoscopy was performed according to a surveillance protocol and when clinically indicated. Aspergillus colonization was defined as a positive culture from bronchoalveolar lavage or two sputum cultures positive for the same Aspergillus species, in the absence of invasive pulmonary Aspergillosis. We found that Aspergillus colonization was strongly associated with BOS and BOS related mortality in Cox regression analyses. Aspergillus colonization typically preceded the development of BOS by a median of 261 days (95% CI 87 to 520). Furthermore, in a multivariate Cox regression model, Aspergillus colonization was a distinct risk factor for BOS, independent of acute rejection. These data suggest a potential causative role for Aspergillus colonization in the development of BOS post-lung transplantation and raise the possibility that strategies aimed to prevent Aspergillus colonization may help delay or reduce the incidence of BOS. PMID:19459819

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

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

2016-01-01

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

Disadvantage of survival outcomes in widowed patients with colorectal neuroendocrine neoplasm: an analysis of surveillance, epidemiology and end results database.

PubMed

Li, Jing; Wang, Ying; Han, Fang; Wang, Zhu; Xu, Lichun; Tong, Jiandong

2016-12-13

Marital status correlates with health. Our goal was to examine the impact of marital status on the survival outcomes of patients with colorectal neuroendocrine neoplasms (NENs). The Surveillance, Epidemiology and End Results program was used to identify 1,289 eligible patients diagnosed between 2004 and 2010 with colorectal NENs. Statistical analyses were performed using Chi-square, Kaplan-Meier, and Cox regression proportional hazards methods. Patients in the widowed group had the highest proportion of larger tumor (>2cm), and higher ratio of poor grade (Grade III and IV) and more tumors at advanced stage (P<0.05). The 5-year cause specific survival (CSS) was 76% in the married group, 51% in the widowed group, 73% in the single group, and 72% in the divorced/separated group, which manifest statistically significant difference in the univariate log-rank test and Cox regression model (P<0.05). Furthermore, marital status was an independent prognostic factor only in Distant stage (P<0.001). In conclusion, patients in widowed group were at greater risk of cancer specific mortality from colorectal NENs and social support may lead to improved outcomes for patients with NENs.

Randomized Trial of Intensive Housing Placement and Community Transition Services for Episodic and Recidivist Homeless Families

PubMed Central

Mitchell, Kristen; Pareti, Lauren; DeGenova, Joe; Heller, Anne; Hannigan, Anthony; Gholston, Jennifer

2013-01-01

Objectives. We compared Home to Stay, a pilot of intensive housing placement and community transition services for episodic and recidivist homeless families, with a standard services approach. Methods. Using intention-to-treat analyses, we conducted a modified randomized trial of 138 Home to Stay client families and a control group of 192 client families receiving standard shelter services. Results. Home to Stay clients exited shelter more quickly than clients in the control group (Cox regression, P < .001), more commonly exited shelter with housing subsidies (75% vs 56%), stayed out of shelter longer (Cox regression, P = .011), and spent fewer total days in shelter (376 days vs 449 days). Home to Stay performed best with clients who entered shelter within 180 days of the pilot’s start date and had less impact on clients entering shelter before that time. Conclusions. Relative to standard services, Home to Stay services can accelerate exit from shelter and reduce return to shelter and total sheltered days for episodic and recidivist homeless families. Standard shelter services may be able to narrow this performance gap by incentivizing work with all episodic and recidivist homeless families. PMID:24148053

Misspecification of Cox regression models with composite endpoints

PubMed Central

Wu, Longyang; Cook, Richard J

2012-01-01

Researchers routinely adopt composite endpoints in multicenter randomized trials designed to evaluate the effect of experimental interventions in cardiovascular disease, diabetes, and cancer. Despite their widespread use, relatively little attention has been paid to the statistical properties of estimators of treatment effect based on composite endpoints. We consider this here in the context of multivariate models for time to event data in which copula functions link marginal distributions with a proportional hazards structure. We then examine the asymptotic and empirical properties of the estimator of treatment effect arising from a Cox regression model for the time to the first event. We point out that even when the treatment effect is the same for the component events, the limiting value of the estimator based on the composite endpoint is usually inconsistent for this common value. We find that in this context the limiting value is determined by the degree of association between the events, the stochastic ordering of events, and the censoring distribution. Within the framework adopted, marginal methods for the analysis of multivariate failure time data yield consistent estimators of treatment effect and are therefore preferred. We illustrate the methods by application to a recent asthma study. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22736519

Adverse Clinical Outcome Associated With Mutations That Typify African American Colorectal Cancers.

PubMed

Wang, Zhenghe; Li, Li; Guda, Kishore; Chen, Zhengyi; Barnholtz-Sloan, Jill; Park, Young Soo; Markowitz, Sanford D; Willis, Joseph

2016-12-01

African Americans have the highest incidence and mortality from colorectal cancer (CRC) of any US racial group. We recently described a panel of 15 genes that are statistically significantly more likely to be mutated in CRCs from African Americans than in Caucasians (AA-CRC genes). The current study investigated the outcomes associated with these mutations in African American CRCs (AA-CRCs). In a cohort of 66 patients with stage I-III CRCs, eight of 27 CRCs with AA-CRC gene mutations (Mut+) developed metastatic disease vs only four of 39 mutation-negative (Mut-) cases (P = .03, Cox regression model with two-sided Wald test). Moreover, among stage III cases (n = 33), Mut+ cancers were nearly three times more likely to relapse as Mut- cases (7 of 15 Mut+ vs 3 of 18 Mut-; P = .03, Cox regression model with two-sided Wald test). AA-CRC mutations may thus define a high-risk subset of CRCs that contributes to the overall disparity in CRC outcomes observed in African Americans. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Low Survival Rates of Oral and Oropharyngeal Squamous Cell Carcinoma

PubMed Central

da Silva Júnior, Francisco Feliciano; dos Santos, Karine de Cássia Batista; Ferreira, Stefania Jeronimo

2017-01-01

Aim To assess the epidemiological and clinical factors that influence the prognosis of oral and oropharyngeal squamous cell carcinoma (SCC). Methods One hundred and twenty-one cases of oral and oropharyngeal SCC were selected. The survival curves for each variable were estimated using the Kaplan-Meier method. The Cox regression model was applied to assess the effect of the variables on survival. Results Cancers at an advanced stage were observed in 103 patients (85.1%). Cancers on the tongue were more frequent (23.1%). The survival analysis was 59.9% in one year, 40.7% in two years, and 27.8% in 5 years. There was a significant low survival rate linked to alcohol intake (p = 0.038), advanced cancer staging (p = 0.003), and procedures without surgery (p < 0.001). When these variables were included in the Cox regression model only surgery procedures (p = 0.005) demonstrated a significant effect on survival. Conclusion The findings suggest that patients who underwent surgery had a greater survival rate compared with those that did not. The low survival rates and the high percentage of patients diagnosed at advanced stages demonstrate that oral and oropharyngeal cancer patients should receive more attention. PMID:28638410

[Negative prognostic impact of female gender on oncological outcomes following radical cystectomy].

PubMed

Dabi, Y; Rouscoff, Y; Delongchamps, N B; Sibony, M; Saighi, D; Zerbib, M; Peyraumore, M; Xylinas, E

2016-02-01

To confirm gender specific differences in pathologic factors and survival rates of urothelial bladder cancer patients treated with radical cystectomy. We conducted a retrospective monocentric study on 701 patients treated with radical cystectomy and pelvic lymphadenectomy for muscle invasive bladder cancer. Impact of gender on recurrence rate, specific and non-specific mortality rate were evaluated using Cox regression models in univariate and multivariate analysis. We collected data on 553 males (78.9%) and 148 females (21.1%) between 1998 and 2011. Both groups were comparable at inclusion regarding age, pathologic stage, nodal status and lymphovascular invasion. Mean follow-up time was 45 months (interquartile 23-73) and by that time, 163 patients (23.3%) had recurrence of their tumor and 127 (18.1%) died from their disease. In multivariable Cox regression analyses, female gender was independently associated with disease recurrence (RR: 1.73; 95% CI 1.22-2.47; P=0.02) and cancer-specific mortality (RR=2.50, 95% CI=1.71-3.68; P<0.001). We confirmed female gender to be an independent negative prognosis factor for patients following a radical cystectomy and lymphadenectomy for an invasive muscle bladder cancer. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Criterion for evaluating the predictive ability of nonlinear regression models without cross-validation.

PubMed

Kaneko, Hiromasa; Funatsu, Kimito

2013-09-23

We propose predictive performance criteria for nonlinear regression models without cross-validation. The proposed criteria are the determination coefficient and the root-mean-square error for the midpoints between k-nearest-neighbor data points. These criteria can be used to evaluate predictive ability after the regression models are updated, whereas cross-validation cannot be performed in such a situation. The proposed method is effective and helpful in handling big data when cross-validation cannot be applied. By analyzing data from numerical simulations and quantitative structural relationships, we confirm that the proposed criteria enable the predictive ability of the nonlinear regression models to be appropriately quantified.

Donor Hemodynamics as a Predictor of Outcomes After Kidney Transplantation From Donors After Cardiac Death.

PubMed

Allen, M B; Billig, E; Reese, P P; Shults, J; Hasz, R; West, S; Abt, P L

2016-01-01

Donation after cardiac death is an important source of transplantable organs, but evidence suggests donor warm ischemia contributes to inferior outcomes. Attempts to predict recipient outcome using donor hemodynamic measurements have not yielded statistically significant results. We evaluated novel measures of donor hemodynamics as predictors of delayed graft function and graft failure in a cohort of 1050 kidneys from 566 donors. Hemodynamics were described using regression line slopes, areas under the curve, and time beyond thresholds for systolic blood pressure, oxygen saturation, and shock index (heart rate divided by systolic blood pressure). A logistic generalized estimation equation model showed that area under the curve for systolic blood pressure was predictive of delayed graft function (above median: odds ratio 1.42, 95% confidence interval [CI] 1.06-1.90). Multivariable Cox regression demonstrated that slope of oxygen saturation during the first 10 minutes after extubation was associated with graft failure (below median: hazard ratio 1.30, 95% CI 1.03-1.64), with 5-year graft survival of 70.0% (95%CI 64.5%-74.8%) for donors above the median versus 61.4% (95%CI 55.5%-66.7%) for those below the median. Among older donors, increased shock index slope was associated with increased hazard of graft failure. Validation of these findings is necessary to determine the utility of characterizing donor warm ischemia to predict recipient outcome. © Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons.

Use of Hundreds of Electrocardiograhpic Biomarkers for Prediction of Mortality in Post-Menopausal Women: The Women’s Health Initiative

PubMed Central

Gorodeski, Eiran Z.; Ishwaran, Hemant; Kogalur, Udaya B.; Blackstone, Eugene H.; Hsich, Eileen; Zhang, Zhu-ming; Vitolins, Mara Z.; Manson, JoAnn E.; Curb, J. David; Martin, Lisa W.; Prineas, Ronald J.; Lauer, Michael S.

2013-01-01

Background Simultaneous contribution of hundreds of electrocardiographic biomarkers to prediction of long-term mortality in post-menopausal women with clinically normal resting electrocardiograms (ECGs) is unknown. Methods and Results We analyzed ECGs and all-cause mortality in 33,144 women enrolled in Women’s Health Initiative trials, who were without baseline cardiovascular disease or cancer, and had normal ECGs by Minnesota and Novacode criteria. Four hundred and seventy seven ECG biomarkers, encompassing global and individual ECG findings, were measured using computer algorithms. During a median follow-up of 8.1 years (range for survivors 0.5–11.2 years), 1,229 women died. For analyses cohort was randomly split into derivation (n=22,096, deaths=819) and validation (n=11,048, deaths=410) subsets. ECG biomarkers, demographic, and clinical characteristics were simultaneously analyzed using both traditional Cox regression and Random Survival Forest (RSF), a novel algorithmic machine-learning approach. Regression modeling failed to converge. RSF variable selection yielded 20 variables that were independently predictive of long-term mortality, 14 of which were ECG biomarkers related to autonomic tone, atrial conduction, and ventricular depolarization and repolarization. Conclusions We identified 14 ECG biomarkers from amongst hundreds that were associated with long-term prognosis using a novel random forest variable selection methodology. These were related to autonomic tone, atrial conduction, ventricular depolarization, and ventricular repolarization. Quantitative ECG biomarkers have prognostic importance, and may be markers of subclinical disease in apparently healthy post-menopausal women. PMID:21862719

Predicting survival time in noncurative patients with advanced cancer: a prospective study in China.

PubMed

Cui, Jing; Zhou, Lingjun; Wee, B; Shen, Fengping; Ma, Xiuqiang; Zhao, Jijun

2014-05-01

Accurate prediction of prognosis for cancer patients is important for good clinical decision making in therapeutic and care strategies. The application of prognostic tools and indicators could improve prediction accuracy. This study aimed to develop a new prognostic scale to predict survival time of advanced cancer patients in China. We prospectively collected items that we anticipated might influence survival time of advanced cancer patients. Participants were recruited from 12 hospitals in Shanghai, China. We collected data including demographic information, clinical symptoms and signs, and biochemical test results. Log-rank tests, Cox regression, and linear regression were performed to develop a prognostic scale. Three hundred twenty patients with advanced cancer were recruited. Fourteen prognostic factors were included in the prognostic scale: Karnofsky Performance Scale (KPS) score, pain, ascites, hydrothorax, edema, delirium, cachexia, white blood cell (WBC) count, hemoglobin, sodium, total bilirubin, direct bilirubin, aspartate aminotransferase (AST), and alkaline phosphatase (ALP) values. The score was calculated by summing the partial scores, ranging from 0 to 30. When using the cutoff points of 7-day, 30-day, 90-day, and 180-day survival time, the scores were calculated as 12, 10, 8, and 6, respectively. We propose a new prognostic scale including KPS, pain, ascites, hydrothorax, edema, delirium, cachexia, WBC count, hemoglobin, sodium, total bilirubin, direct bilirubin, AST, and ALP values, which may help guide physicians in predicting the likely survival time of cancer patients more accurately. More studies are needed to validate this scale in the future.

Functional form diagnostics for Cox's proportional hazards model.

PubMed

León, Larry F; Tsai, Chih-Ling

2004-03-01

We propose a new type of residual and an easily computed functional form test for the Cox proportional hazards model. The proposed test is a modification of the omnibus test for testing the overall fit of a parametric regression model, developed by Stute, González Manteiga, and Presedo Quindimil (1998, Journal of the American Statistical Association93, 141-149), and is based on what we call censoring consistent residuals. In addition, we develop residual plots that can be used to identify the correct functional forms of covariates. We compare our test with the functional form test of Lin, Wei, and Ying (1993, Biometrika80, 557-572) in a simulation study. The practical application of the proposed residuals and functional form test is illustrated using both a simulated data set and a real data set.

Use of the Box-Cox Transformation in Detecting Changepoints in Daily Precipitation Data Series

NASA Astrophysics Data System (ADS)

Wang, X. L.; Chen, H.; Wu, Y.; Pu, Q.

2009-04-01

This study integrates a Box-Cox power transformation procedure into two statistical tests for detecting changepoints in Gaussian data series, to make the changepoint detection methods applicable to non-Gaussian data series, such as daily precipitation amounts. The detection power aspects of transformed methods in a common trend two-phase regression setting are assessed by Monte Carlo simulations for data of a log-normal or Gamma distribution. The results show that the transformed methods have increased the power of detection, in comparison with the corresponding original (untransformed) methods. The transformed data much better approximate to a Gaussian distribution. As an example of application, the new methods are applied to a series of daily precipitation amounts recorded at a station in Canada, showing satisfactory detection power.

Sieve estimation of Cox models with latent structures.

PubMed

Cao, Yongxiu; Huang, Jian; Liu, Yanyan; Zhao, Xingqiu

2016-12-01

This article considers sieve estimation in the Cox model with an unknown regression structure based on right-censored data. We propose a semiparametric pursuit method to simultaneously identify and estimate linear and nonparametric covariate effects based on B-spline expansions through a penalized group selection method with concave penalties. We show that the estimators of the linear effects and the nonparametric component are consistent. Furthermore, we establish the asymptotic normality of the estimator of the linear effects. To compute the proposed estimators, we develop a modified blockwise majorization descent algorithm that is efficient and easy to implement. Simulation studies demonstrate that the proposed method performs well in finite sample situations. We also use the primary biliary cirrhosis data to illustrate its application. © 2016, The International Biometric Society.

Aircraft Fire Safety held in Sintra (Portugal) on 22-26 May 1989

DTIC Science & Technology

1989-10-01

range of building fire problems including the stable species of CO, and H.O. Figure 4 illustrates predictions of the JASMINE model, here applied to a...Validation of JASMINE , Transport and Road Research Laboratory Contractor Report No. 28, 1986. 16. Liew, S.K., Bray, K.N.C. and Moss, J.B. A...Mange and Air Cleaning Conf, US Dept of Energy, Conf 840806, 1985, 629. L4 17-8 [11]Kumar-S, Hoffmann N and Cox G, "Some validation of JASMINE for

Universality of the helimagnetic transition in cubic chiral magnets: Small angle neutron scattering and neutron spin echo spectroscopy studies of FeCoSi

NASA Astrophysics Data System (ADS)

Bannenberg, L. J.; Kakurai, K.; Falus, P.; Lelièvre-Berna, E.; Dalgliesh, R.; Dewhurst, C. D.; Qian, F.; Onose, Y.; Endoh, Y.; Tokura, Y.; Pappas, C.

2017-04-01

We present a comprehensive small angle neutron scattering and neutron spin echo spectroscopy study of the structural and dynamical aspects of the helimagnetic transition in Fe1 -xCoxSi with x =0.30 . In contrast to the sharp transition observed in the archetype chiral magnet MnSi, the transition in Fe1 -xCoxSi is gradual, and long-range helimagnetic ordering coexists with short-range correlations over a wide temperature range. The dynamics are more complex than in MnSi and involve long relaxation times with a stretched exponential relaxation which persists even under magnetic field. These results in conjunction with an analysis of the hierarchy of the relevant length scales show that the helimagnetic transition in Fe1 -xCoxSi differs substantially from the transition in MnSi and question the validity of a universal approach to the helimagnetic transition in chiral magnets.

Chemopreventive effects of NSAIDs as inhibitors of cyclooxygenase-2 and inducers of apoptosis in experimental lung carcinogenesis.

PubMed

Setia, Shruti; Vaish, Vivek; Sanyal, Sankar Nath

2012-07-01

Roles of cyclooxygenase (COX) enzyme and intrinsic pathway of apoptosis have been explored for the chemopreventive effects of non-steroidal anti-inflammatory drugs (NSAIDs) on 9,10-dimethyl benz(a)anthracene (DMBA)-induced lung cancer in rat model. 16 weeks after the administration of DMBA, morphological analysis revealed the occurrences of tumours and lesions, which were regressed considerably with the co-administration of indomethacin and etoricoxib, the two NSAIDs under investigation. DMBA group was marked by hyperplasia and dysplasia as observed by histological examination, and these features were corrected to a large extent by the two NSAIDs. Elevated levels of COX-2 were seen in the DMBA group, the enzyme responsible for prostaglandin synthesis during inflammation and cancer, whilst the expression of the constitutive isoform, COX-1, was equally expressed in all the groups. Apoptosis was quantified by studying the activities of apaf-1, caspase-9, and 3 by immunofluorescence and western blots. Their activities were found to diminish in the DMBA-treated animals as compared to the other groups. Fluorescent co-staining of the isolated broncho-alveolar lavage cells showed reduced number of apoptotic cells in the DMBA group, indicating decrease in apoptosis after carcinogen administration. The present results thus suggest that the mechanism of cancer chemoprevention of NSAIDs may include the suppression of COX-2 and the induction of apoptosis.

Reconstruction of the Foot and Ankle Using Pedicled or Free Flaps: Perioperative Flap Survival Analysis

PubMed Central

Li, Xiucun; Cui, Jianli; Maharjan, Suraj; Lu, Laijin; Gong, Xu

2016-01-01

Objective The purpose of this study is to determine the correlation between non-technical risk factors and the perioperative flap survival rate and to evaluate the choice of skin flap for the reconstruction of foot and ankle. Methods This was a clinical retrospective study. Nine variables were identified. The Kaplan-Meier method coupled with a log-rank test and a Cox regression model was used to predict the risk factors that influence the perioperative flap survival rate. The relationship between postoperative wound infection and risk factors was also analyzed using a logistic regression model. Results The overall flap survival rate was 85.42%. The necrosis rates of free flaps and pedicled flaps were 5.26% and 20.69%, respectively. According to the Cox regression model, flap type (hazard ratio [HR] = 2.592; 95% confidence interval [CI] (1.606, 4.184); P < 0.001) and postoperative wound infection (HR = 0.266; 95% CI (0.134, 0.529); P < 0.001) were found to be statistically significant risk factors associated with flap necrosis. Based on the logistic regression model, preoperative wound bed inflammation (odds ratio [OR] = 11.371,95% CI (3.117, 41.478), P < 0.001) was a statistically significant risk factor for postoperative wound infection. Conclusion Flap type and postoperative wound infection were both independent risk factors influencing the flap survival rate in the foot and ankle. However, postoperative wound infection was a risk factor for the pedicled flap but not for the free flap. Microvascular anastomosis is a major cause of free flap necrosis. To reconstruct complex or wide soft tissue defects of the foot or ankle, free flaps are safer and more reliable than pedicled flaps and should thus be the primary choice. PMID:27930679

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study.

PubMed

Shi, Xiao; Zhang, Ting-Ting; Hu, Wei-Ping; Ji, Qing-Hai

2017-04-25

The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187-1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266-1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role.

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study

PubMed Central

Shi, Xiao; Zhang, Ting-ting; Hu, Wei-ping; Ji, Qing-hai

2017-01-01

Background The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Results Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187–1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266–1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). Materials and Methods 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Conclusions Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role. PMID:28415710

Duration of Mechanical Ventilation in the Emergency Department.

PubMed

Angotti, Lauren B; Richards, Jeremy B; Fisher, Daniel F; Sankoff, Jeffrey D; Seigel, Todd A; Al Ashry, Haitham S; Wilcox, Susan R

2017-08-01

Due to hospital crowding, mechanically ventilated patients are increasingly spending hours boarding in emergency departments (ED) before intensive care unit (ICU) admission. This study aims to evaluate the association between time ventilated in the ED and in-hospital mortality, duration of mechanical ventilation, ICU and hospital length of stay (LOS). This was a multi-center, prospective, observational study of patients ventilated in the ED, conducted at three academic Level I Trauma Centers from July 2011 to March 2013. All consecutive adult patients on invasive mechanical ventilation were eligible for enrollment. We performed a Cox regression to assess for a mortality effect for mechanically ventilated patients with each hour of increasing LOS in the ED and multivariable regression analyses to assess for independently significant contributors to in-hospital mortality. Our primary outcome was in-hospital mortality, with secondary outcomes of ventilator days, ICU LOS and hospital LOS. We further commented on use of lung protective ventilation and frequency of ventilator changes made in this cohort. We enrolled 535 patients, of whom 525 met all inclusion criteria. Altered mental status without respiratory pathology was the most common reason for intubation, followed by trauma and respiratory failure. Using iterated Cox regression, a mortality effect occurred at ED time of mechanical ventilation > 7 hours, and the longer ED stay was also associated with a longer total duration of intubation. However, adjusted multivariable regression analysis demonstrated only older age and admission to the neurosciences ICU as independently associated with increased mortality. Of interest, only 23.8% of patients ventilated in the ED for over seven hours had changes made to their ventilator. In a prospective observational study of patients mechanically ventilated in the ED, there was a significant mortality benefit to expedited transfer of patients into an appropriate ICU setting.

Determining delayed admission to intensive care unit for mechanically ventilated patients in the emergency department.

PubMed

Hung, Shih-Chiang; Kung, Chia-Te; Hung, Chih-Wei; Liu, Ber-Ming; Liu, Jien-Wei; Chew, Ghee; Chuang, Hung-Yi; Lee, Wen-Huei; Lee, Tzu-Chi

2014-08-23

The adverse effects of delayed admission to the intensive care unit (ICU) have been recognized in previous studies. However, the definitions of delayed admission varies across studies. This study proposed a model to define "delayed admission", and explored the effect of ICU-waiting time on patients' outcome. This retrospective cohort study included non-traumatic adult patients on mechanical ventilation in the emergency department (ED), from July 2009 to June 2010. The primary outcomes measures were 21-ventilator-day mortality and prolonged hospital stays (over 30 days). Models of Cox regression and logistic regression were used for multivariate analysis. The non-delayed ICU-waiting was defined as a period in which the time effect on mortality was not statistically significant in a Cox regression model. To identify a suitable cut-off point between "delayed" and "non-delayed", subsets from the overall data were made based on ICU-waiting time and the hazard ratio of ICU-waiting hour in each subset was iteratively calculated. The cut-off time was then used to evaluate the impact of delayed ICU admission on mortality and prolonged length of hospital stay. The final analysis included 1,242 patients. The time effect on mortality emerged after 4 hours, thus we deduced ICU-waiting time in ED > 4 hours as delayed. By logistic regression analysis, delayed ICU admission affected the outcomes of 21 ventilator-days mortality and prolonged hospital stay, with odds ratio of 1.41 (95% confidence interval, 1.05 to 1.89) and 1.56 (95% confidence interval, 1.07 to 2.27) respectively. For patients on mechanical ventilation at the ED, delayed ICU admission is associated with higher probability of mortality and additional resource expenditure. A benchmark waiting time of no more than 4 hours for ICU admission is recommended.

A difference in systolic blood pressure between arms is a novel predictor of the development and progression of diabetic nephropathy in patients with type 2 diabetes.

PubMed

Okada, Hiroshi; Fukui, Michiaki; Tanaka, Muhei; Matsumoto, Shinobu; Iwase, Hiroya; Kobayashi, Kanae; Asano, Mai; Yamazaki, Masahiro; Hasegawa, Goji; Nakamura, Naoto

2013-10-01

Recent studies have suggested that a difference in systolic blood pressure (SBP) between arms is associated with both vascular disease and mortality. The aim of this study was to investigate the relationship between a difference in SBP between arms and change in urinary albumin excretion or development of albuminuria in patients with type 2 diabetes. We measured SBP in 408 consecutive patients with type 2 diabetes, and calculated a difference in SBP between arms. We performed follow-up study to assess change in urinary albumin excretion or development of albuminuria, mean interval of which was 4.6 ± 1.7 years. We then evaluated the relationship of a difference in SBP between arms to diabetic nephropathy using multiple regression analysis and multiple Cox regression model. Multiple regression analyses demonstrated that a difference in SBP between arms was independently associated with change in urinary albumin excretion (β = 0.1869, P = 0.0010). Adjusted Cox regression analyses demonstrated that a difference in SBP between arms was associated with an increased hazard of development of albuminuria; hazard ratio was 1.215 (95% confidence interval 1.077-1.376). Moreover, the risk of development of albuminuria was increased in patients with a difference in SBP of equal to or more than 10 mmHg between arms; hazard ratio was 4.168 (95% confidence interval 1.478-11.70). A difference in SBP between arms could be a novel predictor of the development and progression of diabetic nephropathy in patients with type 2 diabetes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Lung Cancer Prognosis in Elderly Solid Organ Transplant Recipients

PubMed Central

Sigel, Keith; Veluswamy, Rajwanth; Krauskopf, Katherine; Mehrotra, Anita; Mhango, Grace; Sigel, Carlie; Wisnivesky, Juan

2015-01-01

Background Treatment-related immunosuppression in organ transplant recipients has been linked to increased incidence and risk of progression for several malignancies. Using a population-based cancer cohort, we evaluated whether organ transplantation was associated with worse prognosis in elderly patients with non-small cell lung cancer (NSCLC). Methods Using the Surveillance, Epidemiology and End Results registry linked to Medicare claims we identified 597 patients age ≥65 with NSCLC who had received organ transplants (kidney, liver, heart or lung) prior to cancer diagnosis. These cases were compared to 114,410 untransplanted NSCLC patients. We compared overall survival (OS) by transplant status using Kaplan-Meier methods and Cox regression. To account for an increased risk of non-lung cancer death (competing risks) in transplant recipients, we used conditional probability function (CPF) analyses. Multiple CPF regression was used to evaluate lung cancer prognosis in organ transplant recipients while adjusting for confounders. Results Transplant recipients presented with earlier stage lung cancer (p=0.002) and were more likely to have squamous cell carcinoma (p=0.02). Cox regression analyses showed that having received a non-lung organ transplant was associated with poorer OS (p<0.05) while lung transplantation was associated with no difference in prognosis. After accounting for competing risks of death using CPF regression, no differences in cancer-specific survival were noted between non-lung transplant recipients and non-transplant patients. Conclusions Non-lung solid organ transplant recipients who developed NSCLC had worse OS than non-transplant recipients due to competing risks of death. Lung cancer-specific survival analyses suggest that NSCLC tumor behavior may be similar in these two groups. PMID:25839704

Topical Application of a Bioadhesive Black Raspberry Gel Modulates Gene Expression and Reduces Cyclooxygenase 2 Protein in Human Premalignant Oral Lesions

PubMed Central

Mallery, Susan R.; Zwick, Jared C.; Pei, Ping; Tong, Meng; Larsen, Peter E.; Shumway, Brian S.; Lu, Bo; Fields, Henry W.; Mumper, Russell J.; Stoner, Gary D.

2010-01-01

Reduced expression of proapoptotic and terminal differentiation genes in conjunction with increased levels of the proinflammatory and angiogenesis-inducing enzymes, cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS), correlate with malignant transformation of oral intraepithelial neoplasia (IEN). Accordingly, this study investigated the effects of a 10% (w/w) freeze-dried black raspberry gel on oral IEN histopathology, gene expression profiles, intraepithelial COX-2 and iNOS proteins, and microvascular densities. Our laboratories have shown that freeze-dried black raspberries possess antioxidant properties and also induce keratinocyte apoptosis and terminal differentiation. Oral IEN tissues were hemisected to provide samples for pretreatment diagnoses and establish baseline biochemical and molecular variables. Treatment of the remaining lesional tissue (0.5 g gel applied four times daily for 6 weeks) began 1 week after the initial biopsy. RNA was isolated from snap-frozen IEN lesions for microarray analyses, followed by quantitative reverse transcription-PCR validation. Additional epithelial gene-specific quantitative reverse transcription-PCR analyses facilitated the assessment of target tissue treatment effects. Surface epithelial COX-2 and iNOS protein levels and microvascular densities were determined by image analysis quantified immunohistochemistry. Topical berry gel application uniformly suppressed genes associated with RNA processing, growth factor recycling, and inhibition of apoptosis. Although the majority of participants showed posttreatment decreases in epithelial iNOS and COX-2 proteins, only COX-2 reductions were statistically significant. These data show that berry gel application modulated oral IEN gene expression profiles, ultimately reducing epithelial COX-2 protein. In a patient subset, berry gel application also reduced vascular densities in the superficial connective tissues and induced genes associated with keratinocyte terminal differentiation. PMID:18559542

Molecular docking, molecular modeling, and molecular dynamics studies of azaisoflavone as dual COX-2 inhibitors and TP receptor antagonists.

PubMed

Hadianawala, Murtuza; Mahapatra, Amarjyoti Das; Yadav, Jitender K; Datta, Bhaskar

2018-02-26

Designed multi-target ligand (DML) is an emerging strategy for the development of new drugs and involves the engagement of multiple targets with the same moiety. In the context of NSAIDs it has been suggested that targeting the thromboxane prostanoid (TP) receptor along with cyclooxygenase-2 (COX-2) may help to overcome cardiovascular (CVS) complications associated with COXIBs. In the present work, azaisoflavones were studied for their COX-2 and TP receptor binding activities using structure based drug design (SBDD) techniques. Flavonoids were selected as a starting point based on their known COX-2 inhibitory and TP receptor antagonist activity. Iterative design and docking studies resulted in the evolution of a new class scaffold replacing the benzopyran-4-one ring of flavonoids with quinolin-4-one. The docking and binding parameters of these new compounds are found to be promising in comparison to those of selective COX-2 inhibitors, such as SC-558 and celecoxib. Owing to the lack of structural information, a model for the TP receptor was generated using a threading base alignment method with loop optimization performed using an ab initio method. The model generated was validated against known antagonists for TP receptor using docking/MMGBSA. Finally, the molecules that were designed for selective COX-2 inhibition were docked into the active site of the TP receptor. Iterative structural modifications and docking on these molecules generated a series which displays optimum docking scores and binding interaction for both targets. Molecular dynamics studies on a known TP receptor antagonist and a designed molecule show that both molecules remain in contact with protein throughout the simulation and interact in similar binding modes. Graphical abstract ᅟ.

A new predictive indicator for development of pressure ulcers in bedridden patients based on common laboratory tests results.

PubMed

Hatanaka, N; Yamamoto, Y; Ichihara, K; Mastuo, S; Nakamura, Y; Watanabe, M; Iwatani, Y

2008-04-01

Various scales have been devised to predict development of pressure ulcers on the basis of clinical and laboratory data, such as the Braden Scale (Braden score), which is used to monitor activity and skin conditions of bedridden patients. However, none of these scales facilitates clinically reliable prediction. To develop a clinical laboratory data-based predictive equation for the development of pressure ulcers. Subjects were 149 hospitalised patients with respiratory disorders who were monitored for the development of pressure ulcers over a 3-month period. The proportional hazards model (Cox regression) was used to analyse the results of 12 basic laboratory tests on the day of hospitalisation in comparison with Braden score. Pressure ulcers developed in 38 patients within the study period. A Cox regression model consisting solely of Braden scale items showed that none of these items contributed to significantly predicting pressure ulcers. Rather, a combination of haemoglobin (Hb), C-reactive protein (CRP), albumin (Alb), age, and gender produced the best model for prediction. Using the set of explanatory variables, we created a new indicator based on a multiple logistic regression equation. The new indicator showed high sensitivity (0.73) and specificity (0.70), and its diagnostic power was higher than that of Alb, Hb, CRP, or the Braden score alone. The new indicator may become a more useful clinical tool for predicting presser ulcers than Braden score. The new indicator warrants verification studies to facilitate its clinical implementation in the future.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample.

PubMed

Wang, Ching-Yun; Song, Xiao

2016-11-01

Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women's Health Initiative. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Vitex negundo inhibits cyclooxygenase-2 inflammatory cytokine-mediated inflammation on carrageenan-induced rat hind paw edema

PubMed Central

Chattopadhyay, Pronobesh; Hazarika, Soilyadhar; Dhiman, Sunil; Upadhyay, Aadesh; Pandey, Anurag; Karmakar, Sanjeev; Singh, Lokendra

2012-01-01

Background: Vitex negundo L. (Verbenaceae) is a hardy plant widely distributed in the Indian subcontinent and used for treatment of a wide spectrum of health disorders in traditional and folk medicine, some of which have been experimentally validated. In present study, we aimed to investigate the anti-inflammatory effects of V. negundo in carrageenan-induced paw edema in rats, and to investigate the probable mechanism of anti-inflammatory action. Materials and Methods: Paw edema was produced by injecting 1% solution of carrageenan, and the paw volume was measured before and after carrageenan injection up to 5 h. V. negundo leaf oil was extracted using a Clevenger apparatus and administered by a trans-dermal route to Wistar rats and the percentage of inhibition of inflammation was observed using a Plethysmometer by comparing a compound aerosol-based formulation with 1 mg diclofinac diethylamine BP and 7 mg methyl salicylate IP/kg body weight served as a standard drug whereas paraffin oil served as the placebo group. After withdrawing of blood, serum was separated and cyclooxygenase (COX)-1 and COX-2 inhibitory activities were measured by the enzyme immuno assay (EIA) method by using a COX inhibitor screening assay kit. Results and Discussion: V. negundo leaf oil significantly (P < 0.05) reduced the carrageenan-induced paw edema as compared to the placebo group (paraffin oil) and 1 mg diclofinac diethylamine BP and 7 mg methyl salicylate IP showed the maximum inhibition of paw edema as compared to the V. negundo leaf oil treated group and the control group. Also in the present study V. negundo leaf oil showed significantly (P < 0.05) inhibits COX-1 pathways rather than COX-2 pathways as compared to the V. negundo leaf oil treated group. Conclusion: It is suggested that the V. negundo leaf oil is a potent anti-inflammatory agent and acts via inhibition of COX-2 without much interfering COX-1 pathways. PMID:22923950

Anti-inflammatory, anticholinesterase, antioxidant and phytochemical properties of medicinal plants used for pain-related ailments in South Africa.

PubMed

Fawole, O A; Amoo, S O; Ndhlala, A R; Light, M E; Finnie, J F; Van Staden, J

2010-02-03

Extracts of seven South African medicinal plants used traditionally for the treatment of pain-related ailments were evaluated. The study was aimed at evaluating medicinal and therapeutic potentials of the investigated traditional medicinal plants. Plant extracts were evaluated for anti-inflammatory activity and other pharmacological properties such as anticholinesterase and antioxidant activities. Phytochemical analysis of total phenolic contents, condensed tannins, gallotannins and flavonoids in the aqueous methanol extracts of the medicinal plants were also carried out. The evaluation of anti-inflammatory activity of 50% methanol (50% MeOH), petroleum ether (PE), dichloromethane (DCM) and ethanol (EtOH) plant extracts was done against cyclooxygenase-1 and -2 (COX-1 and COX-2) enzymes. 50% MeOH, PE, DCM and EtOH extracts were tested for acetylcholinesterase (AChE) inhibition, while 50% MeOH extracts were tested for 2,2-diphenyl-1-picryl hydrazyl (DPPH) radical scavenging activity and ferric-reducing power in the antioxidant assays. Total phenolic compounds, condensed tannins, gallotannins and flavonoids were quantitatively determined using spectrophotometric methods. At the screening assay concentration (0.25 microg/microl), 13 extracts showed good COX-1 inhibitory activity (>50%), while good activity was observed in 15 extracts against COX-2 enzyme. All the extracts of Crinum moorei (bulbs) showed good inhibition against both COX-1 and COX-2 enzymes. Though not significantly different (P=0.05), the highest COX-1 percentage inhibition (100%) was shown by Aloe ferox leaf PE and Colocasia antiquorum tuber DCM extracts, while Colocasia antiquorum tuber PE extract exhibited the highest (92.7%) percentage inhibition against COX-2. Crinum moorei bulb DCM extract showed the lowest EC(50) value (2.9 microg/ml) in the AChE assay. In addition, good to moderate bioactivities were observed in some extracts of Aloe ferox (leaves), Crinum moorei (bulbs) and Pycnostachys reticulata (leaves) in all the assays. The presence and/or amounts of phenolic compounds varied with plant species. The results obtained in this study validate the use of the investigated medicinal plants in South African traditional medicine for pain-related ailments. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery.

PubMed

Mao, Qixing; Xia, Wenjie; Dong, Gaochao; Chen, Shuqi; Wang, Anpeng; Jin, Guangfu; Jiang, Feng; Xu, Lin

2018-04-01

Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction. A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center. A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores. This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Validation of the 16-Gene Recurrence Score in patients with locoregional, high-risk renal cell carcinoma from a phase 3 trial of adjuvant sunitinib.

PubMed

Rini, Brian I; Escudier, Bernard; Martini, Jean-Francois; Magheli, Ahmed; Svedman, Christer; Lopatin, Margarita; Knezevic, Dejan; Goddard, Audrey D; Febbo, Phillip G; Li, Rachel; Lin, Xun; Valota, Olga; Staehler, Michael; Motzer, Robert J; Ravaud, Alain

2018-05-17

Adjuvant sunitinib prolonged disease-free survival (DFS) (hazard ratio [HR] 0.76) in patients with locoregional high-risk renal cell carcinoma (RCC) in the S-TRAC trial (ClinicalTrials.gov NCT00375674). The 16-gene Recurrence Score (RS) assay was previously developed and validated to estimate risk for disease recurrence in patients with RCC post-nephrectomy. This analysis further validated the prognostic value of RS assay in patients from S-TRAC and explored association of RS results with prediction of sunitinib benefit. The analysis was prospectively designed with prespecified genes, algorithm, endpoints, and analytical methods. Primary RCC was available from 212 patients with informed consent; primary analysis focused on patients with T3 RCC. Gene expression was quantitated by RT-PCR. Time to recurrence (TTR), DFS, and renal cancer-specific survival (RCSS) were analyzed using Cox proportional hazards regression. Results: Baseline characteristics were similar between patients with and without RS results, and between the sunitinib and placebo arms among patients with RS results. RS results predicted TTR, DFS, and RCSS in both arms, with the strongest results observed in the placebo arm. When high versus low RS groups were compared, HR for recurrence was 9.18 (95% CI, 2.15-39.24; P < 0.001) in the placebo arm; interaction of RS results with treatment was not significant. Conclusions: The strong prognostic performance of the 16-gene RS assay was confirmed in S-TRAC, and the RS assay is now supported by level IB evidence. RS results may help identify patients at high risk for recurrence who may derive higher absolute benefit from adjuvant therapy. Copyright ©2018, American Association for Cancer Research.

SU-F-R-24: Identifying Prognostic Imaging Biomarkers in Early Stage Lung Cancer Using Radiomics

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

Zeng, X; Wu, J; Cui, Y

2016-06-15

Purpose: Patients diagnosed with early stage lung cancer have favorable outcomes when treated with surgery or stereotactic radiotherapy. However, a significant proportion (∼20%) of patients will develop metastatic disease and eventually die of the disease. The purpose of this work is to identify quantitative imaging biomarkers from CT for predicting overall survival in early stage lung cancer. Methods: In this institutional review board-approved HIPPA-compliant retrospective study, we retrospectively analyzed the diagnostic CT scans of 110 patients with early stage lung cancer. Data from 70 patients were used for training/discovery purposes, while those of remaining 40 patients were used for independentmore » validation. We extracted 191 radiomic features, including statistical, histogram, morphological, and texture features. Cox proportional hazard regression model, coupled with the least absolute shrinkage and selection operator (LASSO), was used to predict overall survival based on the radiomic features. Results: The optimal prognostic model included three image features from the Law’s feature and wavelet texture. In the discovery cohort, this model achieved a concordance index or CI=0.67, and it separated the low-risk from high-risk groups in predicting overall survival (hazard ratio=2.72, log-rank p=0.007). In the independent validation cohort, this radiomic signature achieved a CI=0.62, and significantly stratified the low-risk and high-risk groups in terms of overall survival (hazard ratio=2.20, log-rank p=0.042). Conclusion: We identified CT imaging characteristics associated with overall survival in early stage lung cancer. If prospectively validated, this could potentially help identify high-risk patients who might benefit from adjuvant systemic therapy.« less

Dual Kidney Allocation Score: A Novel Algorithm Utilizing Expanded Donor Criteria for the Allocation of Dual Kidneys in Adults.

PubMed

Johnson, Adam P; Price, Thea P; Lieby, Benjamin; Doria, Cataldo

2016-09-08

BACKGROUND Dual kidney transplantation (DKT) of expanded-criteria donors is a cost-intensive procedure that aims to increase the pool of available deceased organ donors and has demonstrated equivalent outcomes to expanded-criteria single kidney transplantation (eSKT). The objective of this study was to develop an allocation score based on predicted graft survival from historical dual and single kidney donors. MATERIAL AND METHODS We analyzed United Network for Organ Sharing (UNOS) data for 1547 DKT and 26 381 eSKT performed between January 1994 and September 2013. We utilized multivariable Cox regression to identify variables independently associated with graft survival in dual and single kidney transplantations. We then derived a weighted multivariable product score from calculated hazard ratios to model the benefit of transplantation as dual kidneys. RESULTS Of 36 donor variables known at the time of listing, 13 were significantly associated with graft survival. The derived dual allocation score demonstrated good internal validity with strong correlation to improved survival in dual kidney transplants. Donors with scores less than 2.1 transplanted as dual kidneys had a worsened median survival of 594 days (24%, p-value 0.031) and donors with scores greater than 3.9 had improved median survival of 1107 days (71%, p-value 0.002). There were 17 733 eSKT (67%) and 1051 DKT (67%) with scores in between these values and no differences in survival (p-values 0.676 and 0.185). CONCLUSIONS We have derived a dual kidney allocation score (DKAS) with good internal validity. Future prospective studies will be required to demonstrate external validity, but this score may help to standardize organ allocation for dual kidney transplantation.

Australian validation of the Cancer of the Prostate Risk Assessment Post-Surgical score to predict biochemical recurrence after radical prostatectomy.

PubMed

Beckmann, Kerri; O'Callaghan, Michael; Vincent, Andrew; Roder, David; Millar, Jeremy; Evans, Sue; McNeil, John; Moretti, Kim

2018-03-01

The Cancer of the Prostate Risk Assessment Post-Surgical (CAPRA-S) score is a simple post-operative risk assessment tool predicting disease recurrence after radical prostatectomy, which is easily calculated using available clinical data. To be widely useful, risk tools require multiple external validations. We aimed to validate the CAPRA-S score in an Australian multi-institutional population, including private and public settings and reflecting community practice. The study population were all men on the South Australian Prostate Cancer Clinical Outcomes Collaborative Database with localized prostate cancer diagnosed during 1998-2013, who underwent radical prostatectomy without adjuvant therapy (n = 1664). Predictive performance was assessed via Kaplan-Meier and Cox proportional regression analyses, Harrell's Concordance index, calibration plots and decision curve analysis. Biochemical recurrence occurred in 342 (21%) cases. Five-year recurrence-free probabilities for CAPRA-S scores indicating low (0-2), intermediate (3-5) and high risk were 95, 79 and 46%, respectively. The hazard ratio for CAPRA-S score increments was 1.56 (95% confidence interval 1.49-1.64). The Concordance index for 5-year recurrence-free survival was 0.77. The calibration plot showed good correlation between predicted and observed recurrence-free survival across scores. Limitations include the retrospective nature and small numbers with higher CAPRA-S scores. The CAPRA-S score is an accurate predictor of recurrence after radical prostatectomy in our cohort, supporting its utility in the Australian setting. This simple tool can assist in post-surgical selection of patients who would benefit from adjuvant therapy while avoiding morbidity among those less likely to benefit. © 2017 Royal Australasian College of Surgeons.

Biologic determinants of tumor recurrence in stage II colon cancer: validation study of the 12-gene recurrence score in cancer and leukemia group B (CALGB) 9581.

PubMed

Venook, Alan P; Niedzwiecki, Donna; Lopatin, Margarita; Ye, Xing; Lee, Mark; Friedman, Paula N; Frankel, Wendy; Clark-Langone, Kim; Millward, Carl; Shak, Steven; Goldberg, Richard M; Mahmoud, Najjia N; Warren, Robert S; Schilsky, Richard L; Bertagnolli, Monica M

2013-05-10

A greater understanding of the biology of tumor recurrence should improve adjuvant treatment decision making. We conducted a validation study of the 12-gene recurrence score (RS), a quantitative assay integrating stromal response and cell cycle gene expression, in tumor specimens from patients enrolled onto Cancer and Leukemia Group B (CALGB) 9581. CALGB 9581 randomly assigned 1,713 patients with stage II colon cancer to treatment with edrecolomab or observation and found no survival difference. The analysis reported here included all patients with available tissue and recurrence (n = 162) and a random (approximately 1:3) selection of nonrecurring patients. RS was assessed in 690 formalin-fixed paraffin-embedded tumor samples with quantitative reverse transcriptase polymerase chain reaction by using prespecified genes and a previously validated algorithm. Association of RS and recurrence was analyzed by weighted Cox proportional hazards regression. Continuous RS was significantly associated with risk of recurrence (P = .013) as was mismatch repair (MMR) gene deficiency (P = .044). In multivariate analyses, RS was the strongest predictor of recurrence (P = .004), independent of T stage, MMR, number of nodes examined, grade, and lymphovascular invasion. In T3 MMR-intact (MMR-I) patients, prespecified low and high RS groups had average 5-year recurrence risks of 13% (95% CI, 10% to 16%) and 21% (95% CI, 16% to 26%), respectively. The 12-gene RS predicts recurrence in stage II colon cancer in CALGB 9581. This is consistent with the importance of stromal response and cell cycle gene expression in colon tumor recurrence. RS appears to be most discerning for patients with T3 MMR-I tumors, although markers such as grade and lymphovascular invasion did not add value in this subset of patients.

Validation study of a quantitative multigene reverse transcriptase-polymerase chain reaction assay for assessment of recurrence risk in patients with stage II colon cancer.

PubMed

Gray, Richard G; Quirke, Philip; Handley, Kelly; Lopatin, Margarita; Magill, Laura; Baehner, Frederick L; Beaumont, Claire; Clark-Langone, Kim M; Yoshizawa, Carl N; Lee, Mark; Watson, Drew; Shak, Steven; Kerr, David J

2011-12-10

We developed quantitative gene expression assays to assess recurrence risk and benefits from chemotherapy in patients with stage II colon cancer. We sought validation by using RNA extracted from fixed paraffin-embedded primary colon tumor blocks from 1,436 patients with stage II colon cancer in the QUASAR (Quick and Simple and Reliable) study of adjuvant fluoropyrimidine chemotherapy versus surgery alone. A recurrence score (RS) and a treatment score (TS) were calculated from gene expression levels of 13 cancer-related genes (n = 7 recurrence genes and n = 6 treatment benefit genes) and from five reference genes with prespecified algorithms. Cox proportional hazards regression models and log-rank methods were used to analyze the relationship between the RS and risk of recurrence in patients treated with surgery alone and between TS and benefits of chemotherapy. Risk of recurrence was significantly associated with RS (hazard ratio [HR] per interquartile range, 1.38; 95% CI, 1.11 to 1.74; P = .004). Recurrence risks at 3 years were 12%, 18%, and 22% for predefined low, intermediate, and high recurrence risk groups, respectively. T stage (HR, 1.94; P < .001) and mismatch repair (MMR) status (HR, 0.31; P < .001) were the strongest histopathologic prognostic factors. The continuous RS was associated with risk of recurrence (P = .006) beyond these and other covariates. There was no trend for increased benefit from chemotherapy at higher TS (P = .95). The continuous 12-gene RS has been validated in a prospective study for assessment of recurrence risk in patients with stage II colon cancer after surgery and provides prognostic value that complements T stage and MMR. The TS was not predictive of chemotherapy benefit.

Serum microRNAs as biomarkers for recurrence in melanoma

PubMed Central

2012-01-01

Background Identification of melanoma patients at high risk for recurrence and monitoring for recurrence are critical for informed management decisions. We hypothesized that serum microRNAs (miRNAs) could provide prognostic information at the time of diagnosis unaccounted for by the current staging system and could be useful in detecting recurrence after resection. Methods We screened 355 miRNAs in sera from 80 melanoma patients at primary diagnosis (discovery cohort) using a unique quantitative reverse transcription-PCR (qRT-PCR) panel. Cox proportional hazard models and Kaplan-Meier recurrence-free survival (RFS) curves were used to identify a miRNA signature with prognostic potential adjusting for stage. We then tested the miRNA signature in an independent cohort of 50 primary melanoma patients (validation cohort). Logistic regression analysis was performed to determine if the miRNA signature can determine risk of recurrence in both cohorts. Selected miRNAs were measured longitudinally in subsets of patients pre-/post-operatively and pre-/post-recurrence. Results A signature of 5 miRNAs successfully classified melanoma patients into high and low recurrence risk groups with significant separation of RFS in both discovery and validation cohorts (p = 0.0036, p = 0.0093, respectively). Significant separation of RFS was maintained when a logistic model containing the same signature set was used to predict recurrence risk in both discovery and validation cohorts (p < 0.0001, p = 0.033, respectively). Longitudinal expression of 4 miRNAs in a subset of patients was dynamic, suggesting miRNAs can be associated with tumor burden. Conclusion Our data demonstrate that serum miRNAs can improve accuracy in identifying primary melanoma patients with high recurrence risk and in monitoring melanoma tumor burden over time. PMID:22857597

ATM/RB1 mutations predict shorter overall survival in urothelial cancer.

PubMed

Yin, Ming; Grivas, Petros; Emamekhoo, Hamid; Mendiratta, Prateek; Ali, Siraj; Hsu, JoAnn; Vasekar, Monali; Drabick, Joseph J; Pal, Sumanta; Joshi, Monika

2018-03-30

Mutations of DNA repair genes, e.g. ATM/RB1 , are frequently found in urothelial cancer (UC) and have been associated with better response to cisplatin-based chemotherapy. Further external validation of the prognostic value of ATM/RB1 mutations in UC can inform clinical decision making and trial designs. In the discovery dataset, ATM/RB1 mutations were present in 24% of patients and were associated with shorter OS (adjusted HR 2.67, 95% CI, 1.45-4.92, p = 0.002). There was a higher mutation load in patients carrying ATM/RB1 mutations (median mutation load: 6.7 versus 5.5 per Mb, p = 0.072). In the validation dataset, ATM/RB1 mutations were present in 22.2% of patients and were non-significantly associated with shorter OS (adjusted HR 1.87, 95% CI, 0.97-3.59, p = 0.06) and higher mutation load (median mutation load: 8.1 versus 7.2 per Mb, p = 0.126). Exome sequencing data of 130 bladder UC patients from The Cancer Genome Atlas (TCGA) dataset were analyzed as a discovery cohort to determine the prognostic value of ATM/RB1 mutations. Results were validated in an independent cohort of 81 advanced UC patients. Cox proportional hazard regression analysis was performed to calculate the hazard ratio (HR) and 95% confidence interval (CI) to compare overall survival (OS). ATM/RB1 mutations may be a biomarker of poor prognosis in unselected UC patients and may correlate with higher mutational load. Further studies are required to determine factors that can further stratify prognosis and evaluate predictive role of ATM/RB1 mutation status to immunotherapy and platinum-based chemotherapy.

Risk Factors for Upper Gastrointestinal Bleeding in Patients Taking Selective COX-2 Inhibitors: A Nationwide Population-Based Cohort Study.

PubMed

Lin, Xi-Hsuan; Young, Shih-Hao; Luo, Jiing-Chyuan; Peng, Yen-Ling; Chen, Ping-Hsien; Lin, Chung-Chi; Chen, Wei-Ming; Hou, Ming-Chih; Lee, Fa-Yauh

2018-02-01

Cyclooxygenase-2 inhibitors (coxibs) are associated with less upper gastrointestinal bleeding (UGIB) than traditional nonsteroidal anti-inflammatory drugs (tNSAIDs). However, they also increase the risk of UGIB in high-risk patients. We aimed to identify the risk factors of UGIB in coxibs users. Retrospective cohort study. 2000-2010 National Health Insurance Research Database of Taiwan. Patients taking coxibs as the study group and patients not taking any coxibs as controls. After age, gender, and comorbidity matching by propensity score, 12,145 coxibs users and 12,145 matched controls were extracted for analysis. The primary end point was the occurrence of UGIB. Cox multivariate proportional hazard regression models were used to determine the risk factors for UGIB among all the enrollees and coxibs users. During a mean follow-up of three years, coxibs users had significantly higher incidence of UGIB than matched controls (P < 0.001, log-rank test). Cox regression analysis showed that coxibs increased risk of UGIB in all participants (hazard ratio = 1.37, 95% confidence interval = 1.19-1.55, P < 0.001). Independent risk factors for UGIB among coxibs users were age, male gender, diabetes, chronic renal disease, cirrhosis, history of peptic ulcer disease, PU bleeding (PUB), Helicobacter pylori (H. pylori) infection, and concomitant use of tNSAIDs, acetylsalicylic acid, or thienopyridines. Among coxibs users, H. pylori infection and history of PUB were especially important risk factors for UGIB. Further studies are needed to determine whether proton pump inhibitors might play a protective role in these at-risk patients. © 2017 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Transition from a multiport technique to a single-port technique for lung cancer surgery: is lymph node dissection inferior using the single-port technique?†.

PubMed

Liu, Chia-Chuan; Shih, Chih-Shiun; Pennarun, Nicolas; Cheng, Chih-Tao

2016-01-01

The feasibility and radicalism of lymph node dissection for lung cancer surgery by a single-port technique has frequently been challenged. We performed a retrospective cohort study to investigate this issue. Two chest surgeons initiated multiple-port thoracoscopic surgery in a 180-bed cancer centre in 2005 and shifted to a single-port technique gradually after 2010. Data, including demographic and clinical information, from 389 patients receiving multiport thoracoscopic lobectomy or segmentectomy and 149 consecutive patients undergoing either single-port lobectomy or segmentectomy for primary non-small-cell lung cancer were retrieved and entered for statistical analysis by multivariable linear regression models and Box-Cox transformed multivariable analysis. The mean number of total dissected lymph nodes in the lobectomy group was 28.5 ± 11.7 for the single-port group versus 25.2 ± 11.3 for the multiport group; the mean number of total dissected lymph nodes in the segmentectomy group was 19.5 ± 10.8 for the single-port group versus 17.9 ± 10.3 for the multiport group. In linear multivariable and after Box-Cox transformed multivariable analyses, the single-port approach was still associated with a higher total number of dissected lymph nodes. The total number of dissected lymph nodes for primary lung cancer surgery by single-port video-assisted thoracoscopic surgery (VATS) was higher than by multiport VATS in univariable, multivariable linear regression and Box-Cox transformed multivariable analyses. This study confirmed that highly effective lymph node dissection could be achieved through single-port VATS in our setting. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Late Results of Cox Maze III Procedure in Patients with Atrial Fibrillation Associated with Structural Heart Disease

PubMed Central

Gomes, Gustavo Gir; Gali, Wagner Luis; Sarabanda, Alvaro Valentim Lima; da Cunha, Claudio Ribeiro; Kessler, Iruena Moraes; Atik, Fernando Antibas

2017-01-01

Background Cox-Maze III procedure is one of the surgical techniques used in the surgical treatment of atrial fibrillation (AF). Objectives To determine late results of Cox-Maze III in terms of maintenance of sinus rhythm, and mortality and stroke rates. Methods Between January 2006 and January 2013, 93 patients were submitted to the cut-and-sew Cox-Maze III procedure in combination with structural heart disease repair. Heart rhythm was determined by 24-hour Holter monitoring. Procedural success rates were determined by longitudinal methods and recurrence predictors by multivariate Cox regression models. Results Thirteen patients that obtained hospital discharge alive were excluded due to lost follow-up. The remaining 80 patients were aged 49.9 ± 12 years and 47 (58.7%) of them were female. Involvement of mitral valve and rheumatic heart disease were found in 67 (83.7%) and 63 (78.7%) patients, respectively. Seventy patients (87.5%) had persistent or long-standing persistent AF. Mean follow-up with Holter monitoring was 27.5 months. There were no hospital deaths. Sinus rhythm maintenance rates were 88%, 85.1% and 80.6% at 6 months, 24 months and 36 months, respectively. Predictors of late recurrence of AF were female gender (HR 3.52; 95% CI 1.21-10.25; p = 0.02), coronary artery disease (HR 4.73 95% CI 1.37-16.36; p = 0.01) and greater left atrium diameter (HR 1.05; 95% CI 1.01-1.09; p = 0.02). Actuarial survival was 98.5% at 12, 24 and 48 months and actuarial freedom from stroke was 100%, 100% and 97.5% in the same time frames. Conclusions The Cox-Maze III procedure, in our experience, is efficacious for sinus rhythm maintenance, with very low late mortality and stroke rates. PMID:28678926

Influence of the Cyclooxygenase-2 Gene -765G/C and -1195G/A Polymorphisms on Development of Ischemic Stroke.

PubMed

Wu, Guangliang; Cai, Haiyan; Cai, Haobin; Chen, Zhao; Tan, Lei; Qin, Xiurong; Cai, Yefeng

2016-09-01

Many studies have investigated the association between the cyclooxygenase-2 (COX-2) gene polymorphism and ischemic stroke. However, results of these studies still remain controversial. To better explain the association between COX-2 polymorphisms (-765G/C and -1195G/A) and ischemic stroke risk, a meta-analysis was performed. Relevant studies were identified from 4 Chinese databases (Chinese Biological Medical Literature database, Chinese National Knowledge Infrastructure database, Chongqing VIP database, and Chinese WANFANG database), PUBMED and EMBASE prior to December 2015. The strength of association between COX-2 polymorphism and ischemic stroke was evaluated by the odds ratio (OR) with 95% confidence interval (CI). Inconsistency index (I(2)) and the Cochran's Q statistic were used to check heterogeneity. Publication bias was evaluated by funnel plots and Egger's regression test. A total of 4086 ischemic stroke cases and 4747 controls were identified. Significant association between COX-2 -765G/C polymorphism and the risk of ischemic stroke was found in Brazilians and the African-Americans. The OR of (CC+GC versus GG) for the Brazilians and African-Americans were (6.328, 95% CI = 2.295-17.448) and (1.644, 95% CI = 1.060-2.551). In addition, the recessive model of the Brazilians gave an OR of 3.621 (95% CI: 1.519-8.630). Furthermore, the (GC versus GG) and the allele model of the African-Americans were (OR: 1.615, 95% CI = 1.015-2.572) and (OR: 1.422, 95% CI = 1.033-1.957). Significant association was also observed for COX-2 -1195G/A polymorphism in the subtypes of small vessel disease (SVD) of ischemic stroke. Our study suggests that COX-2 -765G/C and -1195G/A polymorphisms may contribute to susceptibility of ischemic stroke, specifically in Brazilians and the African-Americans, and those of SVD. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Identification of subgroups by risk of graft failure after paediatric renal transplantation: application of survival tree models on the ESPN/ERA-EDTA Registry.

PubMed

Lofaro, Danilo; Jager, Kitty J; Abu-Hanna, Ameen; Groothoff, Jaap W; Arikoski, Pekka; Hoecker, Britta; Roussey-Kesler, Gwenaelle; Spasojević, Brankica; Verrina, Enrico; Schaefer, Franz; van Stralen, Karlijn J

2016-02-01

Identification of patient groups by risk of renal graft loss might be helpful for accurate patient counselling and clinical decision-making. Survival tree models are an alternative statistical approach to identify subgroups, offering cut-off points for covariates and an easy-to-interpret representation. Within the European Society of Pediatric Nephrology/European Renal Association-European Dialysis and Transplant Association (ESPN/ERA-EDTA) Registry data we identified paediatric patient groups with specific profiles for 5-year renal graft survival. Two analyses were performed, including (i) parameters known at time of transplantation and (ii) additional clinical measurements obtained early after transplantation. The identified subgroups were added as covariates in two survival models. The prognostic performance of the models was tested and compared with conventional Cox regression analyses. The first analysis included 5275 paediatric renal transplants. The best 5-year graft survival (90.4%) was found among patients who received a renal graft as a pre-emptive transplantation or after short-term dialysis (<45 days), whereas graft survival was poorest (51.7%) in adolescents transplanted after long-term dialysis (>2.2 years). The Cox model including both pre-transplant factors and tree subgroups had a significantly better predictive performance than conventional Cox regression (P < 0.001). In the analysis including clinical factors, graft survival ranged from 97.3% [younger patients with estimated glomerular filtration rate (eGFR) >30 mL/min/1.73 m(2) and dialysis <20 months] to 34.7% (adolescents with eGFR <60 mL/min/1.73 m(2) and dialysis >20 months). Also in this case combining tree findings and clinical factors improved the predictive performance as compared with conventional Cox model models (P < 0.0001). In conclusion, we demonstrated the tree model to be an accurate and attractive tool to predict graft failure for patients with specific characteristics. This may aid the evaluation of individual graft prognosis and thereby the design of measures to improve graft survival in the poor prognosis groups. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Cox Proportional Hazards Models for Modeling the Time to Onset of Decompression Sickness in Hypobaric Environments

NASA Technical Reports Server (NTRS)

Thompson, Laura A.; Chhikara, Raj S.; Conkin, Johnny

2003-01-01

In this paper we fit Cox proportional hazards models to a subset of data from the Hypobaric Decompression Sickness Databank. The data bank contains records on the time to decompression sickness (DCS) and venous gas emboli (VGE) for over 130,000 person-exposures to high altitude in chamber tests. The subset we use contains 1,321 records, with 87% censoring, and has the most recent experimental tests on DCS made available from Johnson Space Center. We build on previous analyses of this data set by considering more expanded models and more detailed model assessments specific to the Cox model. Our model - which is stratified on the quartiles of the final ambient pressure at altitude - includes the final ambient pressure at altitude as a nonlinear continuous predictor, the computed tissue partial pressure of nitrogen at altitude, and whether exercise was done at altitude. We conduct various assessments of our model, many of which are recently developed in the statistical literature, and conclude where the model needs improvement. We consider the addition of frailties to the stratified Cox model, but found that no significant gain was attained above a model that does not include frailties. Finally, we validate some of the models that we fit.

Establishment and Validation of GV-SAPS II Scoring System for Non-Diabetic Critically Ill Patients

PubMed Central

Liu, Wen-Yue; Lin, Shi-Gang; Zhu, Gui-Qi; Poucke, Sven Van; Braddock, Martin; Zhang, Zhongheng; Mao, Zhi; Shen, Fei-Xia

2016-01-01

Background and Aims Recently, glucose variability (GV) has been reported as an independent risk factor for mortality in non-diabetic critically ill patients. However, GV is not incorporated in any severity scoring system for critically ill patients currently. The aim of this study was to establish and validate a modified Simplified Acute Physiology Score II scoring system (SAPS II), integrated with GV parameters and named GV-SAPS II, specifically for non-diabetic critically ill patients to predict short-term and long-term mortality. Methods Training and validation cohorts were exacted from the Multiparameter Intelligent Monitoring in Intensive Care database III version 1.3 (MIMIC-III v1.3). The GV-SAPS II score was constructed by Cox proportional hazard regression analysis and compared with the original SAPS II, Sepsis-related Organ Failure Assessment Score (SOFA) and Elixhauser scoring systems using area under the curve of the receiver operator characteristic (auROC) curve. Results 4,895 and 5,048 eligible individuals were included in the training and validation cohorts, respectively. The GV-SAPS II score was established with four independent risk factors, including hyperglycemia, hypoglycemia, standard deviation of blood glucose levels (GluSD), and SAPS II score. In the validation cohort, the auROC values of the new scoring system were 0.824 (95% CI: 0.813–0.834, P< 0.001) and 0.738 (95% CI: 0.725–0.750, P< 0.001), respectively for 30 days and 9 months, which were significantly higher than other models used in our study (all P < 0.001). Moreover, Kaplan-Meier plots demonstrated significantly worse outcomes in higher GV-SAPS II score groups both for 30-day and 9-month mortality endpoints (all P< 0.001). Conclusions We established and validated a modified prognostic scoring system that integrated glucose variability for non-diabetic critically ill patients, named GV-SAPS II. It demonstrated a superior prognostic capability and may be an optimal scoring system for prognostic evaluation in this patient group. PMID:27824941

Survival analysis: Part I — analysis of time-to-event

PubMed Central

2018-01-01

Length of time is a variable often encountered during data analysis. Survival analysis provides simple, intuitive results concerning time-to-event for events of interest, which are not confined to death. This review introduces methods of analyzing time-to-event. The Kaplan-Meier survival analysis, log-rank test, and Cox proportional hazards regression modeling method are described with examples of hypothetical data. PMID:29768911

Reduction of Racial Disparities in Prostate Cancer

DTIC Science & Technology

2007-12-01

anti-inflammatory medication, COX-2 inhibitors, aspirin, anti-TNF medications), and other medications of interest (testosterone, finasteride , alpha...compared to control-patients (mean 123) P=0.01. There were 14 (7%) control-patients who had Finasteride use, with an average of 398.6 doses per...individual. None of the prosate cancer patients had prior finasteride use. In a multiple logistic regression model (Table 2), after adjustment for the

Adherence to oral anticoagulants in patients with atrial fibrillation-a population-based retrospective cohort study linking health information systems in the Valencia region, Spain: a study protocol.

PubMed

Sanfélix-Gimeno, G; Rodríguez-Bernal, C L; Hurtado, I; Baixáuli-Pérez, C; Librero, J; Peiró, S

2015-10-19

Adherence to oral anticoagulation (OAC) treatment, vitamin K antagonists or new oral anticoagulants, is an essential element for effectiveness. Information on adherence to OAC in atrial fibrillation (AF) and the impact of adherence on clinical outcomes using real-world data barely exists. We aim to describe the patterns of adherence to OAC over time in patients with AF, estimate the associated factors and their impact on clinical events, and assess the same issues with conventional measures of primary and secondary adherence-proportion of days covered (PDC) and persistence-in routine clinical practice. This is a population-based retrospective cohort study including all patients with AF treated with OAC from 2010 to date in Valencia, Spain; data will be obtained from diverse electronic records of the Valencia Health Agency. adherence trajectories. (1) primary non-adherence; (2) secondary adherence: (a) PDC, (b) persistence. Clinical outcomes: hospitalisation for haemorrhagic or thromboembolic events and death during follow-up. (1) description of baseline characteristics, adherence patterns (trajectory models or latent class growth analysis models) and conventional adherence measures; (2) logistic or Cox multivariate regression models, to assess the associations between adherence measures and the covariates, and logistic multinomial regression models, to identify characteristics associated with each trajectory; (3) Cox proportional hazard models, to assess the relationship between adherence and clinical outcomes, with propensity score adjustment applied to further control for potential confounders; (4) to estimate the importance of different healthcare levels in the variations of adherence, logistic or Cox multilevel regression models. This study has been approved by the corresponding Clinical Research Ethics Committee. We plan to disseminate the project's findings through peer-reviewed publications and presentations at relevant health conferences. Policy reports will also be prepared in order to promote the translation of our findings into policy and clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Corona Enhancement and Mosaic Architecture for Prognosis and Selection Between of Liver Resection Versus Transcatheter Arterial Chemoembolization in Single Hepatocellular Carcinomas >5 cm Without Extrahepatic Metastases

PubMed Central

Li, Meng; Xin, Yongjie; Fu, Sirui; Liu, Zaiyi; Li, Yong; Hu, Baoshan; Chen, Shuting; Liang, Changhong; Lu, Ligong

2016-01-01

Abstract Corona enhancement and mosaic architecture are 2 radiologic features of hepatocellular carcinoma (HCC). However, neither their prognostic values nor their impacts on the selection of liver resection (LR) versus transcatheter arterial chemoembolization (TACE) as treatment modalities have been established. We retrospectively analyzed 275 patients with a single HCC lesion >5 cm without extrahepatic metastasis treated with LR or TACE. In LR patients, the overall survival (OS) and time to progression (TTP) were compared between corona enhancement negative (corona−) versus positive (corona+) and mosaic architecture negative (mosaic−) versus positive (mosaic+) patients. Furthermore, by the combination of corona and mosaic, LR patients were divided into negative for both corona and mosaic patterns (LR−/−), positive for only 1 feature (LR+/−), and positive for both (LR+/+); their OS and TTP were compared to those of the TACE group. Cox regression was performed to identify independent factors for OS. In the survival plots for LR, corona− had better OS and TTP than corona+, and mosaic− had better OS than mosaic+. There was no significant difference in TTP between the subgroups. On Cox regression analysis, corona enhancement, but not mosaic architecture, was a significant factor for OS, whereas neither were a significant factor for TTP. In TACE patients, neither corona nor mosaic patterns had significant correlations with OS or TTP. In the whole population, LR−/ and LR+/− subgroups had similar OS, which was better than the LR+/+ and TACE groups. Moreover, LR−/− and LR+/− patients had better TTP than TACE patients, but there were no differences between the LR−/− versus LR+/−, LR−/ versus LR+/+, LR+/− versus LR+/+, and LR+/+ versus TACE groups. On Cox regression analysis, the presence of corona/mosaic patterns was an independent prognostic factor for OS. Our results showed that, for patients with a single HCC >5 cm without extrahepatic metastasis, corona and mosaic patterns are indicators of limited LR efficacy. When both of the features are present, TACE can be used instead of LR with no negative influence on survival. PMID:26765441

Corona Enhancement and Mosaic Architecture for Prognosis and Selection Between of Liver Resection Versus Transcatheter Arterial Chemoembolization in Single Hepatocellular Carcinomas >5 cm Without Extrahepatic Metastases: An Imaging-Based Retrospective Study.

PubMed

Li, Meng; Xin, Yongjie; Fu, Sirui; Liu, Zaiyi; Li, Yong; Hu, Baoshan; Chen, Shuting; Liang, Changhong; Lu, Ligong

2016-01-01

Corona enhancement and mosaic architecture are 2 radiologic features of hepatocellular carcinoma (HCC). However, neither their prognostic values nor their impacts on the selection of liver resection (LR) versus transcatheter arterial chemoembolization (TACE) as treatment modalities have been established.We retrospectively analyzed 275 patients with a single HCC lesion >5 cm without extrahepatic metastasis treated with LR or TACE. In LR patients, the overall survival (OS) and time to progression (TTP) were compared between corona enhancement negative (corona-) versus positive (corona+) and mosaic architecture negative (mosaic-) versus positive (mosaic+) patients. Furthermore, by the combination of corona and mosaic, LR patients were divided into negative for both corona and mosaic patterns (LR-/-), positive for only 1 feature (LR+/-), and positive for both (LR+/+); their OS and TTP were compared to those of the TACE group. Cox regression was performed to identify independent factors for OS.In the survival plots for LR, corona- had better OS and TTP than corona+, and mosaic- had better OS than mosaic+. There was no significant difference in TTP between the subgroups. On Cox regression analysis, corona enhancement, but not mosaic architecture, was a significant factor for OS, whereas neither were a significant factor for TTP. In TACE patients, neither corona nor mosaic patterns had significant correlations with OS or TTP. In the whole population, LR-/ and LR+/- subgroups had similar OS, which was better than the LR+/+ and TACE groups. Moreover, LR-/- and LR+/- patients had better TTP than TACE patients, but there were no differences between the LR-/- versus LR+/-, LR-/ versus LR+/+, LR+/- versus LR+/+, and LR+/+ versus TACE groups. On Cox regression analysis, the presence of corona/mosaic patterns was an independent prognostic factor for OS.Our results showed that, for patients with a single HCC >5 cm without extrahepatic metastasis, corona and mosaic patterns are indicators of limited LR efficacy. When both of the features are present, TACE can be used instead of LR with no negative influence on survival.

The Short-term Prognostic Value of the Triglyceride-to-high-density Lipoprotein Cholesterol Ratio in Acute Ischemic Stroke

PubMed Central

Wang, Huan; Lei, Leix; Zhang, Han-Qing; Gu, Zheng-Tian; Xing, Fang-Lan; Yan, Fu-Ling

2018-01-01

The triglyceride (TG)-to-high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) is a simple approach to predicting unfavorable outcomes in cardiovascular disease. The influence of TG/HDL-C on acute ischemic stroke remains elusive. The purpose of this study was to investigate the precise effect of TG/HDL-C on 3-month mortality after acute ischemic stroke (AIS). Patients with AIS were enrolled in the present study from 2011 to 2017. A total of 1459 participants from a single city in China were divided into retrospective training and prospective test cohorts. Medical records were collected periodically to determine the incidence of fatal events. All participants were followed for 3 months. Optimal cutoff values were determined using X-tile software to separate the training cohort patients into higher and lower survival groups based on their lipid levels. A survival analysis was conducted using Kaplan-Meier curves and a Cox proportional hazards regression model. A total of 1459 patients with AIS (median age 68.5 years, 58.5% male) were analyzed. Univariate Cox regression analysis confirmed that TG/HDL-C was a significant prognostic factor for 3-month survival. X-tile identified 0.9 as an optimal cutoff for TG/HDL-C. In the univariate analysis, the prognosis of the TG/HDL-C >0.9 group was markedly superior to that of TG/HDL-C ≤0.9 group (P<0.001). A multivariate Cox regression analysis showed that TG/HDL-C was independently correlated with a reduced risk of mortality (hazard ratio [HR], 0.39; 95% confidence interval [CI], 0.24-0.62; P<0.001). These results were confirmed in the 453 patients in the test cohort. A nomogram was constructed to predict 3-month case-fatality, and the c-indexes of predictive accuracy were 0.684 and 0.670 in the training and test cohorts, respectively (P<0.01). The serum TG/HDL-C ratio may be useful for predicting short-term mortality after AIS. PMID:29896437

The Short-term Prognostic Value of the Triglyceride-to-high-density Lipoprotein Cholesterol Ratio in Acute Ischemic Stroke.

PubMed

Deng, Qi-Wen; Li, Shuo; Wang, Huan; Lei, Leix; Zhang, Han-Qing; Gu, Zheng-Tian; Xing, Fang-Lan; Yan, Fu-Ling

2018-06-01

The triglyceride (TG)-to-high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) is a simple approach to predicting unfavorable outcomes in cardiovascular disease. The influence of TG/HDL-C on acute ischemic stroke remains elusive. The purpose of this study was to investigate the precise effect of TG/HDL-C on 3-month mortality after acute ischemic stroke (AIS). Patients with AIS were enrolled in the present study from 2011 to 2017. A total of 1459 participants from a single city in China were divided into retrospective training and prospective test cohorts. Medical records were collected periodically to determine the incidence of fatal events. All participants were followed for 3 months. Optimal cutoff values were determined using X-tile software to separate the training cohort patients into higher and lower survival groups based on their lipid levels. A survival analysis was conducted using Kaplan-Meier curves and a Cox proportional hazards regression model. A total of 1459 patients with AIS (median age 68.5 years, 58.5% male) were analyzed. Univariate Cox regression analysis confirmed that TG/HDL-C was a significant prognostic factor for 3-month survival. X-tile identified 0.9 as an optimal cutoff for TG/HDL-C. In the univariate analysis, the prognosis of the TG/HDL-C >0.9 group was markedly superior to that of TG/HDL-C ≤0.9 group (P<0.001). A multivariate Cox regression analysis showed that TG/HDL-C was independently correlated with a reduced risk of mortality (hazard ratio [HR], 0.39; 95% confidence interval [CI], 0.24-0.62; P<0.001). These results were confirmed in the 453 patients in the test cohort. A nomogram was constructed to predict 3-month case-fatality, and the c-indexes of predictive accuracy were 0.684 and 0.670 in the training and test cohorts, respectively (P<0.01). The serum TG/HDL-C ratio may be useful for predicting short-term mortality after AIS.

Ethnicity matching and outcomes after kidney transplantation in the United Kingdom.

PubMed

Pisavadia, Bhavini; Arshad, Adam; Chappelow, Imogen; Nightingale, Peter; Anderson, Benjamin; Nath, Jay; Sharif, Adnan

2018-01-01

Kidneys from non-white donors have inferior outcomes, but it is unclear if ethnicity matching between donors and recipients achieves better post kidney transplant outcomes. We undertook a retrospective, population cohort study utilising UK Transplant Registry data. The cohort comprised adult, kidney-alone, transplant recipients receiving their first kidney transplant between 2003-2015, with data censored at 1st October 2016. We included 27,970 recipients stratified into white (n = 23,215), black (n = 1,679) and south Asian (n = 3,076) ethnicity, with median post-transplant follow-up of 1,676 days (IQR 716-2,869 days). Unadjusted and adjusted Cox regression survival analyses were performed to investigate ethnicity effect on risk for graft loss and mortality. In unadjusted analyses, matched ethnicity between donors-recipients resulted in better outcomes for delayed graft function, one-year creatinine, graft and patient survival but these differed by ethnicity matches. Compared to white-to-white transplants, risk for death-censored graft loss was higher in black-to-black and similar among Asian-to-Asian transplants, but mortality risk was lower for both black-to-black and Asian-to-Asian transplants. In Cox regression models, compared to white donors, we observed higher risk for graft loss with both south Asian (HR 1.38, 95%CI 1.12-1.70, p = 0.003) and black (HR 1.66, 95%CI 1.30-2.11, p<0.001) donated kidneys independent of recipient ethnicity. We observed no mortality difference with south Asian donated kidneys but increased mortality with black donated kidneys (HR 1.68, 95%CI 1.21-2.35, p = 0.002). Matching ethnicities made no significant difference in any Cox regression model. Similar results were observed after stratifying our analysis by living and deceased-donor kidney transplantation. Our data confirm inferior outcomes associated with non-white kidney donors for kidney transplant recipients of any ethnicity in a risk-adjusted model for the United Kingdom population. However, contrary to non-renal transplant literature, we did not identify any survival benefits associated with donor-recipient ethnicity matching.

Using Marginal Structural Measurement-Error Models to Estimate the Long-term Effect of Antiretroviral Therapy on Incident AIDS or Death

PubMed Central

Cole, Stephen R.; Jacobson, Lisa P.; Tien, Phyllis C.; Kingsley, Lawrence; Chmiel, Joan S.; Anastos, Kathryn

2010-01-01

To estimate the net effect of imperfectly measured highly active antiretroviral therapy on incident acquired immunodeficiency syndrome or death, the authors combined inverse probability-of-treatment-and-censoring weighted estimation of a marginal structural Cox model with regression-calibration methods. Between 1995 and 2007, 950 human immunodeficiency virus–positive men and women were followed in 2 US cohort studies. During 4,054 person-years, 374 initiated highly active antiretroviral therapy, 211 developed acquired immunodeficiency syndrome or died, and 173 dropped out. Accounting for measured confounders and determinants of dropout, the weighted hazard ratio for acquired immunodeficiency syndrome or death comparing use of highly active antiretroviral therapy in the prior 2 years with no therapy was 0.36 (95% confidence limits: 0.21, 0.61). This association was relatively constant over follow-up (P = 0.19) and stronger than crude or adjusted hazard ratios of 0.75 and 0.95, respectively. Accounting for measurement error in reported exposure using external validation data on 331 men and women provided a hazard ratio of 0.17, with bias shifted from the hazard ratio to the estimate of precision as seen by the 2.5-fold wider confidence limits (95% confidence limits: 0.06, 0.43). Marginal structural measurement-error models can simultaneously account for 3 major sources of bias in epidemiologic research: validated exposure measurement error, measured selection bias, and measured time-fixed and time-varying confounding. PMID:19934191

Dietary Intake of α-Linolenic Acid Is Not Appreciably Associated with Risk of Ischemic Stroke among Middle-Aged Danish Men and Women.

PubMed

Bork, Christian S; Venø, Stine K; Lundbye-Christensen, Søren; Jakobsen, Marianne U; Tjønneland, Anne; Schmidt, Erik B; Overvad, Kim

2018-06-01

Intake of the plant-derived omega-3 (n-3) fatty acid α-linolenic acid (ALA) may reduce the risk of ischemic stroke. We have investigated the associations between dietary intake of ALA and the risk of ischemic stroke and ischemic stroke subtypes. This was a follow-up study. A total of 57,053 participants aged 50-64 y were enrolled into the Danish Diet, Cancer and Health cohort between 1993 and 1997. Intake of ALA was assessed by a validated semiquantitative food frequency questionnaire. Potential incident cases of ischemic stroke were identified in the Danish National Patient Register, validated, and classified into subtypes based on assumed etiology. Statistical analyses were performed via Cox proportional hazard regression with adjustment for established ischemic stroke risk factors. A total of 1859 ischemic stroke cases were identified during a median of 13.5 y of follow-up. In multivariable analyses using restricted cubic splines adjusting for traditional risk factors for ischemic stroke, we observed no clear associations between dietary intake of ALA and the risk of total ischemic stroke or any of its subtypes including ischemic stroke due to large artery atherosclerosis, ischemic stroke due to small-vessel occlusion, and ischemic stroke due to cardio-embolism. Dietary intake of ALA was neither consistently nor appreciably associated with the risk of ischemic stroke or ischemic stroke subtypes among middle-aged Danish men and women. This study was registered at clinicaltrials.gov as NCT03258983.

A prognostic mutation panel for predicting cancer recurrence in stages II and III colorectal cancer.

PubMed

Sho, Shonan; Court, Colin M; Winograd, Paul; Russell, Marcia M; Tomlinson, James S

2017-12-01

Approximately 20-40% of stage II/III colorectal cancer (CRC) patients develop relapse. Clinicopathological factors alone are limited in detecting these patients, resulting in potential under/over-treatment. We sought to identify a prognostic tumor mutational profile that could predict CRC recurrence. Whole-exome sequencing data were obtained for 207 patients with stage II/III CRC from The Cancer Genome Atlas. Mutational landscape in relapse-free versus relapsed cohort was compared using Fisher's exact test, followed by multivariate Cox regression to identify genes associated with cancer recurrence. Bootstrap-validation was used to examine internal/external validity. We identified five prognostic genes (APAF1, DIAPH2, NTNG1, USP7, and VAV2), which were combined to form a prognostic mutation panel. Patients with ≥1 mutation(s) within this five-gene panel had worse prognosis (3-yr relapse-free survival [RFS]: 53.0%), compared to patients with no mutation (3-yr RFS: 84.3%). In multivariate analysis, the five-gene panel remained prognostic for cancer recurrence independent of stage and high-risk features (hazard ratio 3.63, 95%CI [1.93-6.83], P < 0.0001). Furthermore, its prognostic accuracy was superior to the American Joint Commission on Cancer classification (concordance-index: 0.70 vs 0.54). Our proposed mutation panel identifies CRC patients at high-risk for recurrence, which may help guide adjuvant therapy and post-operative surveillance protocols. © 2017 Wiley Periodicals, Inc.

The prognostic role of body mass index on mortality amongst the middle-aged and elderly: a competing risk analysis.

PubMed

Ghaem Maralani, Haleh; Tai, Bee Choo; Wong, Tien Y; Tai, E Shyong; Li, Jialiang; Wang, Jie Jin; Mitchell, Paul

2014-01-01

To determine the relationship between body mass index (BMI) including its 5-year changes and mortality, and compare the results obtained using Cox and competing risks models. Our study subjects included 2216 persons aged ≥49 years who participated in the Blue Mountains Eye Study, Australia between 1992 and 1994, and returned for further follow-up examinations between 1997 and 1999. We examined the relationship between BMI and mortality using cubic spline. The Cox and competing risks models were used to assess the associations between baseline BMI and its 5-year changes with all-cause and cause-specific mortality. Amongst subjects aged ≤70 years, the relationship between BMI and all-cause mortality was U-shaped. For those aged >70 years, an L-shaped relationship was seen with no elevation in risk amongst the overweight/obese. Based on the competing risks model, obesity at baseline was associated with increased risk of cardiovascular death and reduction in BMI at 5-year was linked to an increase risk of cancer death amongst those aged ≤70 years. The cause-specific Cox model showed that reduction in BMI at 5-year was associated with cancer-death regardless of age, and with cardiovascular deaths among subjects aged ≤70 years. Cox regression model showed larger magnitude of effect with wider confidence interval as compared with competing risks model. Conditions associated with obesity are more likely to affect mortality among subjects aged ≤70 years, but not among those aged over 70 years. Cox model shows larger magnitude of effect in comparison with competing risks model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

On the comparison of population-level estimates of haplotype and nucleotide diversity: a case study using the gene cox1 in animals.

PubMed

Goodall-Copestake, W P; Tarling, G A; Murphy, E J

2012-07-01

Estimates of genetic diversity represent a valuable resource for biodiversity assessments and are increasingly used to guide conservation and management programs. The most commonly reported estimates of DNA sequence diversity in animal populations are haplotype diversity (h) and nucleotide diversity (π) for the mitochondrial gene cytochrome c oxidase subunit I (cox1). However, several issues relevant to the comparison of h and π within and between studies remain to be assessed. We used population-level cox1 data from peer-reviewed publications to quantify the extent to which data sets can be re-assembled, to provide a standardized summary of h and π estimates, to explore the relationship between these metrics and to assess their sensitivity to under-sampling. Only 19 out of 42 selected publications had archived data that could be unambiguously re-assembled; this comprised 127 population-level data sets (n ≥ 15) from 23 animal species. Estimates of h and π were calculated using a 456-base region of cox1 that was common to all the data sets (median h=0.70130, median π=0.00356). Non-linear regression methods and Bayesian information criterion analysis revealed that the most parsimonious model describing the relationship between the estimates of h and π was π=0.0081 h(2). Deviations from this model can be used to detect outliers due to biological processes or methodological issues. Subsampling analyses indicated that samples of n>5 were sufficient to discriminate extremes of high from low population-level cox1 diversity, but samples of n ≥ 25 are recommended for greater accuracy.

COX-2 inhibitor and non-selective NSAID use in those at increased risk of NSAID-related adverse events: a retrospective database study.

PubMed

Gadzhanova, Svetla; Ilomäki, Jenni; Roughead, Elizabeth E

2013-01-01

Adverse events related to analgesic use represent a challenge for optimizing treatment of pain in older people. The aim of this study was to determine whether non-selective non-steroidal anti-inflammatory drug (NS-NSAID) and cyclo-oxygenase (COX)-2 inhibitor use is appropriately targeted in those with a prior history of gastrointestinal (GI) events, myocardial infarction (MI) or stroke. A retrospective study of pharmacy claims data from the Australian Government Department of Veterans' Affairs was conducted, involving 288,912 veterans aged 55 years and over. Analgesic utilization from 2007 to 2009 was assessed. Three risk cohorts (veterans with prior hospitalization for GI bleed, MI or stroke) and a low-risk cohort were identified. Poisson regression was applied to test for a linear trend over the study period. The prevalence of analgesics dispensed in the overall study population was approximately 34 % between 2007 and 2009. COX-2 inhibitors were more widely dispensed than NS-NSAIDs in all those at risk of NSAID-related adverse events. At the end of 2009, the ratio was 5.1 % to 2.5 % in the GI cohort, 3.6 % to 3.2 % in the MI cohort and 3.6 % to 2.6 % in the stroke cohort. Although COX-2 inhibitors appeared to be preferred over NS-NSAIDs in those with a prior history of GI events, 2.5 % of patients were still using an NS-NSAID at the end of the study period. Consistent with treatment guidelines, in most of these cases, these drugs were co-dispensed with proton pump inhibitors. COX-2 inhibitors were used at slightly higher rates than NS-NSAIDs in those with a prior history of MI or stroke, which is not consistent with guidelines recommending NS-NSAID use.

Late Results of Cox Maze III Procedure in Patients with Atrial Fibrillation Associated with Structural Heart Disease.

PubMed

Gomes, Gustavo Gir; Gali, Wagner Luis; Sarabanda, Alvaro Valentim Lima; Cunha, Claudio Ribeiro da; Kessler, Iruena Moraes; Atik, Fernando Antibas

2017-07-01

Cox-Maze III procedure is one of the surgical techniques used in the surgical treatment of atrial fibrillation (AF). To determine late results of Cox-Maze III in terms of maintenance of sinus rhythm, and mortality and stroke rates. Between January 2006 and January 2013, 93 patients were submitted to the cut-and-sew Cox-Maze III procedure in combination with structural heart disease repair. Heart rhythm was determined by 24-hour Holter monitoring. Procedural success rates were determined by longitudinal methods and recurrence predictors by multivariate Cox regression models. Thirteen patients that obtained hospital discharge alive were excluded due to lost follow-up. The remaining 80 patients were aged 49.9 ± 12 years and 47 (58.7%) of them were female. Involvement of mitral valve and rheumatic heart disease were found in 67 (83.7%) and 63 (78.7%) patients, respectively. Seventy patients (87.5%) had persistent or long-standing persistent AF. Mean follow-up with Holter monitoring was 27.5 months. There were no hospital deaths. Sinus rhythm maintenance rates were 88%, 85.1% and 80.6% at 6 months, 24 months and 36 months, respectively. Predictors of late recurrence of AF were female gender (HR 3.52; 95% CI 1.21-10.25; p = 0.02), coronary artery disease (HR 4.73 95% CI 1.37-16.36; p = 0.01) and greater left atrium diameter (HR 1.05; 95% CI 1.01-1.09; p = 0.02). Actuarial survival was 98.5% at 12, 24 and 48 months and actuarial freedom from stroke was 100%, 100% and 97.5% in the same time frames. The Cox-Maze III procedure, in our experience, is efficacious for sinus rhythm maintenance, with very low late mortality and stroke rates. A operação de Cox-Maze III é uma das variantes técnicas no tratamento cirúrgico da fibrilação atrial (FA). Estudar os resultados tardios da operação de Cox-Maze III, quanto à eficácia na manutenção de ritmo sinusal e taxas de mortalidade e acidente vascular cerebral (AVC). Entre janeiro de 2006 a janeiro de 2013, 93 pacientes foram submetidos a operação de Cox-Maze III por corte e sutura associada a correção de cardiopatias estruturais. Avaliação do ritmo cardíaco ocorreu por Holter 24 horas. Taxas de sucesso da operação foram estudadas por métodos longitudinais e os preditores de recorrência por análise de regressão de Cox multivariada. Foram excluídos 13 pacientes sobreviventes ao período intra-hospitalar cujo seguimento tardio não foi possível. Os 80 pacientes restantes tinham idade média de 49,9 ± 12 anos e 47 (58,75%) eram do sexo feminino. Acometimento da valva mitral ocorreu em 67 pacientes (83,7%). Valvopatia reumática ocorreu em 63 (78,7%). Setenta pacientes (87,5%) tinham fibrilação atrial persistente ou persistente de longa duração. O tempo médio de seguimento clínico com avaliação de Holter foi de 27,5 meses. Não houve óbitos intra-hospitalares. As taxas de manutenção de ritmo sinusal foram 88%, 85,1% e 80,6% aos 6 meses, 24 meses e 36 meses, respectivamente. Os preditores de recorrência tardia foram sexo feminino (RR 3,52; IC 95% 1,21-10,25; p = 0,02), doença arterial coronária (RR 4,73; IC 95% 1,37-16,36; p = 0,01) e maior diâmetro de átrio esquerdo (RR 1,05; IC 95% 1,01-1,09; p = 0,02). A sobrevida atuarial aos 12, 24 e 48 meses foi de 98,5% e as taxas atuariais livres de AVC nos mesmos períodos de 100%, 100% e 97,5%. A operação de Cox-Maze III, na nossa experiência, é eficaz na manutenção do ritmo sinusal, com baixíssimos índices de mortalidade e de AVC tardios.

Effects of Response Style on the Polarity and Validity of Two-Dimensional Mood Models.

DTIC Science & Technology

1985-08-01

McNair, D.M. & Fisher, S. (1982). Evidence for bipolar mood states. Journal of Personality Assessment , 46, 432-436. Lorr, M. & Shea, T. (1979). Are mood...states bipolar? Journal of Personality Assessment , 43, 468-472. Mackay, C., Cox, T., Burrows, G. & Lazzerini, T. (1978). An inventory for

Revision of the taxonomic status of Aphis floridanae Tissot (Hemiptera:Aphididae) using morphological and molecular insight

USDA-ARS?s Scientific Manuscript database

Three Aphis species are involved in this study. Aphis floridanae Tissot, 1933 and A. nasturtii Kaltenbach, 1843 are currently treated as synonym, and A. impatientis Thomas, 1878 has a valid taxonomic status. Morphological and cytochrome oxidase 1 (Cox1) data show that Aphis floridanae is not synonym...

Validation of the alternating conditional estimation algorithm for estimation of flexible extensions of Cox's proportional hazards model with nonlinear constraints on the parameters.

PubMed

Wynant, Willy; Abrahamowicz, Michal

2016-11-01

Standard optimization algorithms for maximizing likelihood may not be applicable to the estimation of those flexible multivariable models that are nonlinear in their parameters. For applications where the model's structure permits separating estimation of mutually exclusive subsets of parameters into distinct steps, we propose the alternating conditional estimation (ACE) algorithm. We validate the algorithm, in simulations, for estimation of two flexible extensions of Cox's proportional hazards model where the standard maximum partial likelihood estimation does not apply, with simultaneous modeling of (1) nonlinear and time-dependent effects of continuous covariates on the hazard, and (2) nonlinear interaction and main effects of the same variable. We also apply the algorithm in real-life analyses to estimate nonlinear and time-dependent effects of prognostic factors for mortality in colon cancer. Analyses of both simulated and real-life data illustrate good statistical properties of the ACE algorithm and its ability to yield new potentially useful insights about the data structure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gender-Related and Age-Related Differences in Implantable Defibrillator Recipients: Results From the Pacemaker and Implantable Defibrillator Leads Survival Study ("PAIDLESS").

PubMed

Feldman, Alyssa M; Kersten, Daniel J; Chung, Jessica A; Asheld, Wilbur J; Germano, Joseph; Islam, Shahidul; Cohen, Todd J

2015-12-01

The purpose of this study was to investigate the influences of gender and age on defibrillator lead failure and patient mortality. The specific influences of gender and age on defibrillator lead failure have not previously been investigated. This study analyzed the differences in gender and age in relation to defibrillator lead failure and mortality of patients in the Pacemaker and Implantable Defibrillator Leads Survival Study ("PAIDLESS"). PAIDLESS includes all patients at Winthrop University Hospital who underwent defibrillator lead implantation between February 1, 1996 and December 31, 2011. Male and female patients were compared within each age decile, beginning at 15 years old, to analyze lead failure and patient mortality. Statistical analyses were performed using Wilcoxon rank-sum test, Fisher's exact test, Kaplan-Meier analysis, and multivariable Cox regression models. P<.05 was considered statistically significant. No correction for multiple comparisons was performed for the subgroup analyses. A total of 3802 patients (2812 men and 990 women) were included in the analysis. The mean age was 70 ± 13 years (range, 15-94 years). Kaplan-Meier analysis found that between 45 and 54 years of age, leads implanted in women failed significantly faster than in men (P=.03). Multivariable Cox regression models were built to validate this finding, and they confirmed that male gender was an independent protective factor of lead failure in the 45 to 54 years group (for male gender: HR, 0.37; 95% confidence interval, 0.14-0.96; P=.04). Lead survival time for women in this age group was 13.4 years (standard error, 0.6), while leads implanted in men of this age group survived 14.7 years (standard error, 0.3). Although there were significant differences in lead failure, no differences in mortality between the genders were found for any ages or within each decile. This study is the first to compare defibrillator lead failure and patient mortality in relation to gender and age deciles at a single large implanting center. Within the 45 to 54 years group, leads implanted in women failed faster than in men. Male gender was found to be an independent protective factor in lead survival. This study emphasizes the complex interplay between gender and age with respect to implantable defibrillator lead failure and mortality.

TU-D-207B-02: Delta-Radiomics: The Prognostic Value of Therapy-Induced Changes in Radiomics Features for Stage III Non-Small Cell Lung Cancer Patients

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

Fave, X; Court, L; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX

Purpose: To determine how radiomics features change during radiation therapy and whether those changes (delta-radiomics features) can improve prognostic models built with clinical factors. Methods: 62 radiomics features, including histogram, co-occurrence, run-length, gray-tone difference, and shape features, were calculated from pretreatment and weekly intra-treatment CTs for 107 stage III NSCLC patients (5–9 images per patient). Image preprocessing for each feature was determined using the set of pretreatment images: bit-depth resample and/or a smoothing filter were tested for their impact on volume-correlation and significance of each feature in univariate cox regression models to maximize their information content. Next, the optimized featuresmore » were calculated from the intratreatment images and tested in linear mixed-effects models to determine which features changed significantly with dose-fraction. The slopes in these significant features were defined as delta-radiomics features. To test their prognostic potential multivariate cox regression models were fitted, first using only clinical features and then clinical+delta-radiomics features for overall-survival, local-recurrence, and distant-metastases. Leave-one-out cross validation was used for model-fitting and patient predictions. Concordance indices(c-index) and p-values for the log-rank test with patients stratified at the median were calculated. Results: Approximately one-half of the 62 optimized features required no preprocessing, one-fourth required smoothing, and one-fourth required smoothing and resampling. From these, 54 changed significantly during treatment. For overall-survival, the c-index improved from 0.52 for clinical factors alone to 0.62 for clinical+delta-radiomics features. For distant-metastases, the c-index improved from 0.53 to 0.58, while for local-recurrence it did not improve. Patient stratification significantly improved (p-value<0.05) for overallsurvival and distant-metastases when delta-radiomics features were included. The delta-radiomics versions of autocorrelation, kurtosis, and compactness were selected most frequently in leave-one-out iterations. Conclusion: Weekly changes in radiomics features can potentially be used to evaluate treatment response and predict patient outcomes. High-risk patients could be recommended for dose escalation or consolidation chemotherapy. This project was funded in part by grants from the National Cancer Institute (NCI) and the Cancer Prevention Research Institute of Texas (CPRIT).« less

Optimal tumor shrinkage predicts long-term outcome in advanced nonsmall cell lung cancer (NSCLC) treated with target therapy: Result from 3 clinical trials of advanced NSCLC by 1 institution.

PubMed

He, Xiaobo; Zhang, Yang; Ma, Yuxiang; Zhou, Ting; Zhang, Jianwei; Hong, Shaodong; Sheng, Jin; Zhang, Zhonghan; Yang, Yunpeng; Huang, Yan; Zhang, Li; Zhao, Hongyun

2016-08-01

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are used as standard therapies for advanced nonsmall cell lung cancer (NSCLC) patients with EGFR mutation positive. Because these targeted therapies could cause tumor necrosis and shrinkage, the purpose of the study is to search for a value of optimal tumor shrinkage as an appropriate indicator of outcome for advanced NSCLC.A total of 88 NSCLC enrollees of 3 clinical trials (IRESSA registration clinical trial, TRUST study and ZD6474 study), who received Gefitinib (250 mg, QD), Erlotinib (150 mg, QD), and ZD6474 (100 mg, QD), respectively, during December 2003 and October 2007, were retrospectively analyzed. The response evaluation criteria in solid tumors (RECIST) were used to identify responders, who had complete response (CR) or partial responses (PR) and nonresponders who had stable disease (SD) or progressive disease (PD). Receiver operating characteristics (ROC) analysis was used to find the optimal tumor shrinkage as an indicator for tumor therapeutic outcome. Univariate and multivariate Cox regression analyses were performed to compare the progression-free survival (PFS) and overall survival (OS) between responders and nonresponders stratified based on radiologic criteria.Among the 88 NSCLC patients, 26 were responders and 62 were nonresponders based on RECIST 1.0. ROC indicated that 8.32% tumor diameter shrinkage in the sum of the longest tumor diameter (SLD) was the cutoff point of tumor shrinkage outcomes, resulting in 46 responders (≤8.32%) and 42 nonresponders (≥8.32%). Univariate and multivariate Cox regression analyses indicated that (1) the responders (≤8.32%) and nonresponders (≥ -8.32%) were significantly different in median PFS (13.40 vs 1.17 months, P < 0.001) and OS (19.80 vs 7.90 months, P < 0.001) and (2) -8.32% in SLD could be used as the optimal threshold for PFS (hazard ratio [HR], 8.11, 95% CI, 3.75 to 17.51, P < 0.001) and OS (HR, 2.36, 95% CI, 1.41 to 3.96, P = 0.001).However, 8.32% tumor diameter shrinkage is validated as a reliable outcome predictor of advanced NSCLC patients receiving EGFR-TKIs therapies and may provide a practical measure to guide therapeutic decisions.

Novel harmonic regularization approach for variable selection in Cox's proportional hazards model.

PubMed

Chu, Ge-Jin; Liang, Yong; Wang, Jia-Xuan

2014-01-01

Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2 < q < 1) regularizations, to select key risk factors in the Cox's proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL), the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods.

Cerebral autoregulation in the preterm newborn using near-infrared spectroscopy: a comparison of time-domain and frequency-domain analyses

NASA Astrophysics Data System (ADS)

Eriksen, Vibeke R.; Hahn, Gitte H.; Greisen, Gorm

2015-03-01

The aim was to compare two conventional methods used to describe cerebral autoregulation (CA): frequency-domain analysis and time-domain analysis. We measured cerebral oxygenation (as a surrogate for cerebral blood flow) and mean arterial blood pressure (MAP) in 60 preterm infants. In the frequency domain, outcome variables were coherence and gain, whereas the cerebral oximetry index (COx) and the regression coefficient were the outcome variables in the time domain. Correlation between coherence and COx was poor. The disagreement between the two methods was due to the MAP and cerebral oxygenation signals being in counterphase in three cases. High gain and high coherence may arise spuriously when cerebral oxygenation decreases as MAP increases; hence, time-domain analysis appears to be a more robust-and simpler-method to describe CA.

Independent validation of the prognostic capacity of the ISUP prostate cancer grade grouping system for radiation treated patients with long-term follow-up.

PubMed

Spratt, D E; Jackson, W C; Abugharib, A; Tomlins, S A; Dess, R T; Soni, P D; Lee, J Y; Zhao, S G; Cole, A I; Zumsteg, Z S; Sandler, H; Hamstra, D; Hearn, J W; Palapattu, G; Mehra, R; Morgan, T M; Feng, F Y

2016-09-01

There has been a recent proposal to change the grading system of prostate cancer into a five-tier grade grouping system. The prognostic impact of this has been demonstrated in regards only to biochemical recurrence-free survival (bRFS) with short follow-up (3 years). Between 1990 and 2013, 847 consecutive men were treated with definitive external beam radiation therapy at a single academic center. To validate the new grade grouping system, bRFS, distant metastases-free survival (DMFS) and prostate cancer-specific survival (PCSS) were calculated. Adjusted Kaplan-Meier and multivariable Cox regression analyses were performed to assess the independent impact of the new grade grouping system. Discriminatory analyses were performed to compare the commonly used three-tier Gleason score system (6, 7 and 8-10) to the new system. The median follow-up of our cohort was 88 months. The 5-grade groups independently validated differing risks of bRFS (group 1 as reference; adjusted hazard ratio (aHR) 1.35, 2.16, 1.79 and 3.84 for groups 2-5, respectively). Furthermore, a clear stratification was demonstrated for DMFS (aHR 2.03, 3.18, 3.62 and 13.77 for groups 2-5, respectively) and PCSS (aHR 3.00, 5.32, 6.02 and 39.02 for groups 2-5, respectively). The 5-grade group system had improved prognostic discrimination for all end points compared with the commonly used three-tiered system (that is, Gleason score 6, 7 and 8-10). In a large independent radiotherapy cohort with long-term follow-up, we have validated the bRFS benefit of the proposed five-tier grade grouping system. Furthermore, we have demonstrated that the system is highly prognostic for DMFS and PCSS. Grade group 5 had markedly worse outcomes for all end points, and future work is necessary to improve outcomes in these patients.

Independent surgical validation of the new prostate cancer grade-grouping system.

PubMed

Spratt, Daniel E; Cole, Adam I; Palapattu, Ganesh S; Weizer, Alon Z; Jackson, William C; Montgomery, Jeffrey S; Dess, Robert T; Zhao, Shuang G; Lee, Jae Y; Wu, Angela; Kunju, Lakshmi P; Talmich, Emily; Miller, David C; Hollenbeck, Brent K; Tomlins, Scott A; Feng, Felix Y; Mehra, Rohit; Morgan, Todd M

2016-11-01

To report the independent prognostic impact of the new prostate cancer grade-grouping system in a large external validation cohort of patients treated with radical prostatectomy (RP). Between 1994 and 2013, 3 694 consecutive men were treated with RP at a single institution. To investigate the performance of and validate the grade-grouping system, biochemical recurrence-free survival (bRFS) rates were assessed using Kaplan-Meier tests, Cox-regression modelling, and discriminatory comparison analyses. Separate analyses were performed based on biopsy and RP grade. The median follow-up was 52.7 months. The 5-year actuarial bRFS for biopsy grade groups 1-5 were 94.2%, 89.2%, 73.1%, 63.1%, and 54.7%, respectively (P < 0.001). Similarly, the 5-year actuarial bRFS based on RP grade groups was 96.1%, 93.0%, 74.0%, 64.4%, and 49.9% for grade groups 1-5, respectively (P < 0.001). The adjusted hazard ratios for bRFS relative to biopsy grade group 1 were 1.98, 4.20, 5.57, and 9.32 for groups 2, 3, 4, and 5, respectively (P < 0.001), and for RP grade groups were 2.09, 5.27, 5.86, and 10.42 (P < 0.001). The five-grade-group system had a higher prognostic discrimination compared with the commonly used three-tier system (Gleason score 6 vs 7 vs 8-10). In an independent surgical cohort, we have validated the prognostic benefit of the new prostate cancer grade-grouping system for bRFS, and shown that the benefit is maintained after adjusting for important clinicopathological variables. The greater predictive accuracy of the new system will improve risk stratification in the clinical setting and aid in patient counselling. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

Validation of the 12-gene colon cancer recurrence score as a predictor of recurrence risk in stage II and III rectal cancer patients.

PubMed

Reimers, Marlies S; Kuppen, Peter J K; Lee, Mark; Lopatin, Margarita; Tezcan, Haluk; Putter, Hein; Clark-Langone, Kim; Liefers, Gerrit Jan; Shak, Steve; van de Velde, Cornelis J H

2014-11-01

The 12-gene Recurrence Score assay is a validated predictor of recurrence risk in stage II and III colon cancer patients. We conducted a prospectively designed study to validate this assay for prediction of recurrence risk in stage II and III rectal cancer patients from the Dutch Total Mesorectal Excision (TME) trial. RNA was extracted from fixed paraffin-embedded primary rectal tumor tissue from stage II and III patients randomized to TME surgery alone, without (neo)adjuvant treatment. Recurrence Score was assessed by quantitative real time-polymerase chain reaction using previously validated colon cancer genes and algorithm. Data were analysed by Cox proportional hazards regression, adjusting for stage and resection margin status. All statistical tests were two-sided. Recurrence Score predicted risk of recurrence (hazard ratio [HR] = 1.57, 95% confidence interval [CI] = 1.11 to 2.21, P = .01), risk of distant recurrence (HR = 1.50, 95% CI = 1.04 to 2.17, P = .03), and rectal cancer-specific survival (HR = 1.64, 95% CI = 1.15 to 2.34, P = .007). The effect of Recurrence Score was most prominent in stage II patients and attenuated with more advanced stage (P(interaction) ≤ .007 for each endpoint). In stage II, five-year cumulative incidence of recurrence ranged from 11.1% in the predefined low Recurrence Score group (48.5% of patients) to 43.3% in the high Recurrence Score group (23.1% of patients). The 12-gene Recurrence Score is a predictor of recurrence risk and cancer-specific survival in rectal cancer patients treated with surgery alone, suggesting a similar underlying biology in colon and rectal cancers. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Two-protein signature of novel serological markers apolipoprotein-A2 and serum amyloid alpha predicts prognosis in patients with metastatic renal cell cancer and improves the currently used prognostic survival models.

PubMed

Vermaat, J S; van der Tweel, I; Mehra, N; Sleijfer, S; Haanen, J B; Roodhart, J M; Engwegen, J Y; Korse, C M; Langenberg, M H; Kruit, W; Groenewegen, G; Giles, R H; Schellens, J H; Beijnen, J H; Voest, E E

2010-07-01

In metastatic renal cell cancer (mRCC), the Memorial Sloan-Kettering Cancer Center (MSKCC) risk model is widely used for clinical trial design and patient management. To improve prognostication, we applied proteomics to identify novel serological proteins associated with overall survival (OS). Sera from 114 mRCC patients were screened by surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS). Identified proteins were related to OS. Three proteins were subsequently validated with enzyme-linked immunosorbent assays and immunoturbidimetry. Prognostic models were statistically bootstrapped to correct for overestimation. SELDI-TOF MS detected 10 proteins associated with OS. Of these, apolipoprotein A2 (ApoA2), serum amyloid alpha (SAA) and transthyretin were validated for their association with OS (P = 5.5 x 10(-9), P = 1.1 x 10(-7) and P = 0.0004, respectively). Combining ApoA2 and SAA yielded a prognostic two-protein signature [Akaike's Information Criteria (AIC) = 732, P = 5.2 x 10(-7)]. Including previously identified prognostic factors, multivariable Cox regression analysis revealed ApoA2, SAA, lactate dehydrogenase, performance status and number of metastasis sites as independent factors for survival. Using these five factors, categorization of patients into three risk groups generated a novel protein-based model predicting patient prognosis (AIC = 713, P = 4.3 x 10(-11)) more robustly than the MSKCC model (AIC = 729, P = 1.3 x 10(-7)). Applying this protein-based model instead of the MSKCC model would have changed the risk group in 38% of the patients. Proteomics and subsequent validation yielded two novel prognostic markers and survival models which improved prediction of OS in mRCC patients over commonly used risk models. Implementation of these models has the potential to improve current risk stratification, although prospective validation will still be necessary.

CpG Methylation Signature Predicts Recurrence in Early-Stage Hepatocellular Carcinoma: Results From a Multicenter Study.

PubMed

Qiu, Jiliang; Peng, Baogang; Tang, Yunqiang; Qian, Yeben; Guo, Pi; Li, Mengfeng; Luo, Junhang; Chen, Bin; Tang, Hui; Lu, Canliang; Cai, Muyan; Ke, Zunfu; He, Wei; Zheng, Yun; Xie, Dan; Li, Binkui; Yuan, Yunfei

2017-03-01

Purpose Early-stage hepatocellular carcinoma (E-HCC) is being diagnosed increasingly, and in one half of diagnosed patients, recurrence will develop. Thus, it is urgent to identify recurrence-related markers. We investigated the effectiveness of CpG methylation in predicting recurrence for patients with E-HCCs. Patients and Methods In total, 576 patients with E-HCC from four independent centers were sorted by three phases. In the discovery phase, 66 tumor samples were analyzed using the Illumina Methylation 450k Beadchip. Two algorithms, Least Absolute Shrinkage and Selector Operation and Support Vector Machine-Recursive Feature Elimination, were used to select significant CpGs. In the training phase, penalized Cox regression was used to further narrow CpGs into 140 samples. In the validation phase, candidate CpGs were validated using an internal cohort (n = 141) and two external cohorts (n = 191 and n =104). Results After combining the 46 CpGs selected by the Least Absolute Shrinkage and Selector Operation and the Support Vector Machine-Recursive Feature Elimination algorithms, three CpGs corresponding to SCAN domain containing 3, Src homology 3-domain growth factor receptor-bound 2-like interacting protein 1, and peptidase inhibitor 3 were highlighted as candidate predictors in the training phase. On the basis of the three CpGs, a methylation signature for E-HCC (MSEH) was developed to classify patients into high- and low-risk recurrence groups in the training cohort ( P < .001). The performance of MSEH was validated in the internal cohort ( P < .001) and in the two external cohorts ( P < .001; P = .002). Furthermore, a nomogram comprising MSEH, tumor differentiation, cirrhosis, hepatitis B virus surface antigen, and antivirus therapy was generated to predict the 5-year recurrence-free survival in the training cohort, and it performed well in the three validation cohorts (concordance index: 0.725, 0.697, and 0.693, respectively). Conclusion MSEH, a three-CpG-based signature, is useful in predicting recurrence for patients with E-HCC.

Psychometric Analysis of the Heart Failure Somatic Perception Scale as a Measure of Patient Symptom Perception.

PubMed

Jurgens, Corrine Y; Lee, Christopher S; Riegel, Barbara

Symptoms are known to predict survival among patients with heart failure (HF), but discrepancies exist between patients' and health providers' perceptions of HF symptom burden. The purpose of this study is to quantify the internal consistency, validity, and prognostic value of patient perception of a broad range of HF symptoms using an HF-specific physical symptom measure, the 18-item HF Somatic Perception Scale v. 3. Factor analysis of the HF Somatic Perception Scale was conducted in a convenience sample of 378 patients with chronic HF. Convergent validity was examined using the Physical Limitation subscale of the Kansas City Cardiomyopathy Questionnaire. Divergent validity was examined using the Self-care of HF Index self-care management score. One-year survival based on HF Somatic Perception Scale scores was quantified using Cox regression controlling for Seattle HF Model scores to account for clinical status, therapeutics, and lab values. The sample was 63% male, 85% white, 67% functionally compromised (New York Heart Association class III-IV) with a mean (SD) age of 63 (12.8) years. Internal consistency of the HF Somatic Perception Scale was α = .90. Convergent (r = -0.54, P < .0001) and divergent (r = 0.18, P > .05) validities were supported. Controlling for Seattle HF scores, HF Somatic Perception Scale was a significant predictor of 1-year survival, with those most symptomatic having worse survival (hazard ratio, 1.012; 95% confidence interval, 1.001-1.024; P = .038). Perception of HF symptom burden as measured by the HF Somatic Perception Scale is a significant predictor of survival, contributing additional prognostic value over and above objective Seattle HF Risk Model scores. This analysis suggests that assessment of a broad range of HF symptoms, or those related to dyspnea or early and subtle symptoms, may be useful in evaluating therapeutic outcomes and predicting event-free survival.

The Bronchiectasis Severity Index. An International Derivation and Validation Study

PubMed Central

Goeminne, Pieter; Aliberti, Stefano; McDonnell, Melissa J.; Lonni, Sara; Davidson, John; Poppelwell, Lucy; Salih, Waleed; Pesci, Alberto; Dupont, Lieven J.; Fardon, Thomas C.; De Soyza, Anthony; Hill, Adam T.

2014-01-01

Rationale: There are no risk stratification tools for morbidity and mortality in bronchiectasis. Identifying patients at risk of exacerbations, hospital admissions, and mortality is vital for future research. Objectives: This study describes the derivation and validation of the Bronchiectasis Severity Index (BSI). Methods: Derivation of the BSI used data from a prospective cohort study (Edinburgh, UK, 2008–2012) enrolling 608 patients. Cox proportional hazard regression was used to identify independent predictors of mortality and hospitalization over 4-year follow-up. The score was validated in independent cohorts from Dundee, UK (n = 218); Leuven, Belgium (n = 253); Monza, Italy (n = 105); and Newcastle, UK (n = 126). Measurements and Main Results: Independent predictors of future hospitalization were prior hospital admissions, Medical Research Council dyspnea score greater than or equal to 4, FEV1 < 30% predicted, Pseudomonas aeruginosa colonization, colonization with other pathogenic organisms, and three or more lobes involved on high-resolution computed tomography. Independent predictors of mortality were older age, low FEV1, lower body mass index, prior hospitalization, and three or more exacerbations in the year before the study. The derived BSI predicted mortality and hospitalization: area under the receiver operator characteristic curve (AUC) 0.80 (95% confidence interval, 0.74–0.86) for mortality and AUC 0.88 (95% confidence interval, 0.84–0.91) for hospitalization, respectively. There was a clear difference in exacerbation frequency and quality of life using the St. George’s Respiratory Questionnaire between patients classified as low, intermediate, and high risk by the score (P < 0.0001 for all comparisons). In the validation cohorts, the AUC for mortality ranged from 0.81 to 0.84 and for hospitalization from 0.80 to 0.88. Conclusions: The BSI is a useful clinical predictive tool that identifies patients at risk of future mortality, hospitalization, and exacerbations across healthcare systems. PMID:24328736

Predicting long-term survival after coronary artery bypass graft surgery.

PubMed

Karim, Md N; Reid, Christopher M; Huq, Molla; Brilleman, Samuel L; Cochrane, Andrew; Tran, Lavinia; Billah, Baki

2018-02-01

To develop a model for predicting long-term survival following coronary artery bypass graft surgery. This study included 46 573 patients from the Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZCTS) registry, who underwent isolated coronary artery bypass graft surgery between 2001 and 2014. Data were randomly split into development (23 282) and validation (23 291) samples. Cox regression models were fitted separately, using the important preoperative variables, for 4 'time intervals' (31-90 days, 91-365 days, 1-3 years and >3 years), with optimal predictors selected using the bootstrap bagging technique. Model performance was assessed both in validation data and in combined data (development and validation samples). Coefficients of all 4 final models were estimated on the combined data adjusting for hospital-level clustering. The Kaplan-Meier mortality rates estimated in the sample were 1.7% at 90 days, 2.8% at 1 year, 4.4% at 2 years and 6.1% at 3 years. Age, peripheral vascular disease, respiratory disease, reduced ejection fraction, renal dysfunction, arrhythmia, diabetes, hypercholesterolaemia, cerebrovascular disease, hypertension, congestive heart failure, steroid use and smoking were included in all 4 models. However, their magnitude of effect varied across the time intervals. Harrell's C-statistics was 0.83, 0.78, 0.75 and 0.74 for 31-90 days, 91-365 days, 1-3 years and >3 years models, respectively. Models showed excellent discrimination and calibration in validation data. Models were developed for predicting long-term survival at 4 time intervals after isolated coronary artery bypass graft surgery. These models can be used in conjunction with the existing 30-day mortality prediction model. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Finding Risk Groups by Optimizing Artificial Neural Networks on the Area under the Survival Curve Using Genetic Algorithms.

PubMed

Kalderstam, Jonas; Edén, Patrik; Ohlsson, Mattias

2015-01-01

We investigate a new method to place patients into risk groups in censored survival data. Properties such as median survival time, and end survival rate, are implicitly improved by optimizing the area under the survival curve. Artificial neural networks (ANN) are trained to either maximize or minimize this area using a genetic algorithm, and combined into an ensemble to predict one of low, intermediate, or high risk groups. Estimated patient risk can influence treatment choices, and is important for study stratification. A common approach is to sort the patients according to a prognostic index and then group them along the quartile limits. The Cox proportional hazards model (Cox) is one example of this approach. Another method of doing risk grouping is recursive partitioning (Rpart), which constructs a decision tree where each branch point maximizes the statistical separation between the groups. ANN, Cox, and Rpart are compared on five publicly available data sets with varying properties. Cross-validation, as well as separate test sets, are used to validate the models. Results on the test sets show comparable performance, except for the smallest data set where Rpart's predicted risk groups turn out to be inverted, an example of crossing survival curves. Cross-validation shows that all three models exhibit crossing of some survival curves on this small data set but that the ANN model manages the best separation of groups in terms of median survival time before such crossings. The conclusion is that optimizing the area under the survival curve is a viable approach to identify risk groups. Training ANNs to optimize this area combines two key strengths from both prognostic indices and Rpart. First, a desired minimum group size can be specified, as for a prognostic index. Second, the ability to utilize non-linear effects among the covariates, which Rpart is also able to do.

PD-L1 promoter methylation is a prognostic biomarker for biochemical recurrence-free survival in prostate cancer patients following radical prostatectomy.

PubMed

Gevensleben, Heidrun; Holmes, Emily Eva; Goltz, Diane; Dietrich, Jörn; Sailer, Verena; Ellinger, Jörg; Dietrich, Dimo; Kristiansen, Glen

2016-11-29

The rapid development of programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors has generated an urgent need for biomarkers assisting the selection of patients eligible for therapy. The use of PD-L1 immunohistochemistry, which has been suggested as a predictive biomarker, however, is confounded by multiple unresolved issues. The aim of this study therefore was to quantify PD-L1 DNA methylation (mPD-L1) in prostate tissue samples and to evaluate its potential as a biomarker in prostate cancer (PCa). In the training cohort, normal tissue showed significantly lower levels of mPD-L1 compared to tumor tissue. High mPD-L1 in PCa was associated with biochemical recurrence (BCR) in univariate Cox proportional hazards (hazard ratio (HR)=2.60 [95%CI: 1.50-4.51], p=0.001) and Kaplan-Meier analyses (p<0.001). These results were corroborated in an independent validation cohort in univariate Cox (HR=1.24 [95%CI: 1.08-1.43], p=0.002) and Kaplan-Meier analyses (p=0.029). Although mPD-L1 and PD-L1 protein expression did not correlate in the validation cohort, both parameters added significant prognostic information in bivariate Cox analysis (HR=1.22 [95%CI: 1.05-1.42], p=0.008 for mPD-L1 and HR=2.58 [95%CI: 1.43-4.63], p=0.002 for PD-L1 protein expression). mPD-L1 was analyzed in a training cohort from The Cancer Genome Atlas (n=498) and was subsequently measured in an independent validation cohort (n=299) by quantitative methylation-specific real-time PCR. All patients had undergone radical prostatectomy. mPD-L1 is a promising biomarker for the risk stratification of PCa patients and might offer additional relevant prognostic information to the implemented clinical parameters, particularly in the setting of immune checkpoint inhibition.

The Cox proportional Hazard model on duration of birth process

NASA Astrophysics Data System (ADS)

Wuryandari, Triastuti; Haryatmi Kartiko, Sri; Danardono

2018-05-01

The duration of birth process, which is measured from the birth sign until baby born, is one important factor to the whole outcome of delivery process. There is a method of birth process that given relaxing and gentle treatment to the mother caled as gentlebirth. Gentlebirth is a method of birth process that combines brain science, birth science and technology to empower positive birth without pain. However the effect of method to the duration of birth process is still need empirical investigations. Therefore, the objective of this paper is to analyze the duration of birth process using the appropriate statistical methods for durational data, survival data or time to event data. Since there are many variables or factor that may affect the duration, a regression model is considerated. The flexibility of the Cox Proportional Hazard Model in the sense that there is no distributional assumption required, makes the Cox Model as the appropriate model and method to analyze the duration birth process. It is concluded that the Gentlebirth method affects on duration of birth process, with Hazard Ratio of 2.073, showing that the duration of birth process with gentlebirth method is faster than the other method.

Optimization of Acid Orange 7 Degradation in Heterogeneous Fenton-like Reaction Using Fe3-xCoxO4 Catalyst

NASA Astrophysics Data System (ADS)

Ibrahim, M. Z.; Alrozi, R.; Zubir, N. A.; Bashah, N. A.; Ali, S. A. Md; Ibrahim, N.

2018-05-01

The oxidation process such as heterogeneous Fenton and/or Fenton-like reactions is considered as an effective and efficient method for treatment of dye degradation. In this study, the degradation of Acid Orange 7 (AO7) was investigated by using Fe3-xCoxO4 as a heterogeneous Fenton-like catalyst. Response surface methodology (RSM) was used to optimize the operational parameters condition and the interaction of two or more parameters. The parameter studies were catalyst dosage (X1 ), pH (X2 ) and H2O2 concentration (X3 ) towards AO7 degradation. Based on analysis of variance (ANOVA), the derived quadratic polynomial model was significant whereby the predicted values matched the experimental values with regression coefficient of R2 = 0.9399. The optimum condition for AO7 degradation was obtained at catalyst dosage of 0.84 g/L, pH of 3 and H2O2 concentration of 46.70 mM which resulted in 86.30% removal of AO7 dye. These findings present new insights into the influence of operational parameters in the heterogeneous Fenton-like oxidation of AO7 using Fe3-xCoxO4 catalyst.

Impact of referral source and study applicants' preference for randomly assigned service on research enrollment, service engagement, and evaluative outcomes.

PubMed

Macias, Cathaleene; Barreira, Paul; Hargreaves, William; Bickman, Leonard; Fisher, William; Aronson, Elliot

2005-04-01

The inability to blind research participants to their experimental conditions is the Achilles' heel of mental health services research. When one experimental condition receives more disappointed participants, or more satisfied participants, research findings can be biased in spite of random assignment. The authors explored the potential for research participants' preference for one experimental program over another to compromise the generalizability and validity of randomized controlled service evaluations as well as cross-study comparisons. Three Cox regression analyses measured the impact of applicants' service assignment preference on research project enrollment, engagement in assigned services, and a service-related outcome, competitive employment. A stated service preference, referral by an agency with a low level of continuity in outpatient care, and willingness to switch from current services were significant positive predictors of research enrollment. Match to service assignment preference was a significant positive predictor of service engagement, and mismatch to assignment preference was a significant negative predictor of both service engagement and employment outcome. Referral source type and service assignment preference should be routinely measured and statistically controlled for in all studies of mental health service effectiveness to provide a sound empirical base for evidence-based practice.

Coffee Intake and Risk of Colorectal Cancer Among Chinese in Singapore: The Singapore Chinese Health Study

PubMed Central

Peterson, Sabrina; Yuan, Jian-Min; Koh, Woon-Puay; Sun, Can-Lan; Wang, Renwei; Turesky, Robert J.; Yu, Mimi C.

2012-01-01

We prospectively investigated whether coffee consumption was associated with decreased risk of colorectal cancer and whether cigarette smoking and stage of disease modify the association in the Singapore Chinese Health Study. During the first 12 years of follow-up, 961 colorectal cancer cases occurred in the cohort of over 60,000 middle-aged or older Chinese men and women living in Singapore. Baseline dietary exposures were assessed through in-person interviews using a validated food frequency questionnaire. The relation between coffee consumption and colorectal cancer risk was assessed by proportional hazards (Cox) regression. No overall association between coffee intake and colorectal cancer was observed. However, in analysis by subsite and stage restricted to ever smokers, the coffee–colon cancer association became statistically significant for advanced disease (P for trend = 0.01). The hazard ratio was 0.56 (95% confidence interval = 0.35–0.90) for advanced colon cancer in drinkers of 2 or more cups per day compared with those who drank no coffee or less than 1 cup per day. Although there is a null association between coffee intake and risk of colorectal cancer overall, coffee may protect against smoking related advanced colon cancer. PMID:20043256

Identification of Candidate B-Lymphoma Genes by Cross-Species Gene Expression Profiling

PubMed Central

Tompkins, Van S.; Han, Seong-Su; Olivier, Alicia; Syrbu, Sergei; Bair, Thomas; Button, Anna; Jacobus, Laura; Wang, Zebin; Lifton, Samuel; Raychaudhuri, Pradip; Morse, Herbert C.; Weiner, George; Link, Brian; Smith, Brian J.; Janz, Siegfried

2013-01-01

Comparative genome-wide expression profiling of malignant tumor counterparts across the human-mouse species barrier has a successful track record as a gene discovery tool in liver, breast, lung, prostate and other cancers, but has been largely neglected in studies on neoplasms of mature B-lymphocytes such as diffuse large B cell lymphoma (DLBCL) and Burkitt lymphoma (BL). We used global gene expression profiles of DLBCL-like tumors that arose spontaneously in Myc-transgenic C57BL/6 mice as a phylogenetically conserved filter for analyzing the human DLBCL transcriptome. The human and mouse lymphomas were found to have 60 concordantly deregulated genes in common, including 8 genes that Cox hazard regression analysis associated with overall survival in a published landmark dataset of DLBCL. Genetic network analysis of the 60 genes followed by biological validation studies indicate FOXM1 as a candidate DLBCL and BL gene, supporting a number of studies contending that FOXM1 is a therapeutic target in mature B cell tumors. Our findings demonstrate the value of the “mouse filter” for genomic studies of human B-lineage neoplasms for which a vast knowledge base already exists. PMID:24130802

Negative methylation status of Vimentin predicts improved prognosis in pancreatic carcinoma

PubMed Central

Zhou, Yi-Feng; Xu, Wei; Wang, Xia; Sun, Jin-Shan; Xiang, Jing-Jing; Li, Zhao-Shen; Zhang, Xiao-Feng

2014-01-01

AIM: To determine the existence of a potential relationship between the methylation state of the Vimentin gene and its prognostic value in pancreatic cancer. METHODS: Sixty-four primary tumor specimens and normal tissues were collected consecutively from pancreatic cancer patients during surgery at Hangzhou First People’s Hospital and Affiliated Hospital of the Logistics University of the Chinese People’s Armed Police Force. DNA was extracted from the samples and subsequently quantitative methylation-specific polymerase chain reaction was used to detect the Vimentin methylation status of the samples. All of the patients were followed up to December 2012. χ2 test, Kaplan-Meier survival and Cox regression statistical models were used. RESULTS: Out of 64 pancreatic cancer tissues, 21 were marked as Vimentin methylation-positive, and 43 were marked as Vimentin methylation-negative. The location of pancreatic carcinoma was related to the Vimentin methylation state. The pathological T staging (P < 0.001), adjuvant chemotherapy (P = 0.003) and the Vimentin methylation state (P = 0.037) were independent prognostic factors. CONCLUSION: In our study, Vimentin methylation status can predict the prognosis of pancreatic cancer patients. However, additional experiments and clinical trials are needed to accurately validate this observation. PMID:25278713

Statistical analysis of donation--transfusion data with complex correlation.

PubMed

Reilly, Marie; Szulkin, Robert

2007-12-30

Blood-borne transmission of disease is estimated from linked data records from blood donors and transfusion recipients. However, such data are characterized by complex correlation due to donors typically contributing many donations and recipients being transfused with multiple units of blood product. In this paper, we present a method for analysing such data, by using a modification of a nested case-control design. For recipients who develop the disease of interest (cases) and their matched controls, all donors who contributed blood to these individuals define clusters or 'families' of related individuals. Using a Cox regression model for the hazard of the individuals within clusters of donors, we estimate the risk of transmission, and a bootstrap step provides valid standard errors provided the clusters are independent. As an illustration, we apply the method to the analysis of a large database of Swedish donor and recipient records linked to the population cancer register. We investigate whether there is an increased risk of cancer in recipients transfused with blood from donors who develop cancer after donating. Our method provides a powerful alternative to the small 'look-back' studies typical of transfusion medicine and can make an important contribution to haemovigilance efforts. Copyright (c) 2007 John Wiley & Sons, Ltd.

Predicting risk of nonmelanoma skin cancer and premalignant skin lesions in renal transplant recipients.

PubMed

Urwin, Helen R; Jones, Peter W; Harden, Paul N; Ramsay, Helen M; Hawley, Carmel M; Nicol, David L; Fryer, Anthony A

2009-06-15

Nonmelanoma skin cancer (NMSC) and associated premalignant lesions represent a major complication after transplantation, particularly in areas with high ultraviolet radiation (UVR) exposure. The American Society of Transplantation has proposed annual NMSC screening for all renal transplant recipients. The aim of this study was to develop a predictive index (PI) that could be used in targeted screening. Data on patient demographics, UVR exposure, and other clinical parameters were collected on 398 adult recipients recruited from the Princess Alexandra Hospital, Brisbane. Structured interview, skin examination, biopsy of lesions, and review of medical/pathologic records were performed. Time to presentation with the first NMSC was assessed using Cox's regression models and Kaplan-Meier estimates used to assess detection of NMSC during screening. Stepwise selection identified age, outdoor UVR exposure, living in a hot climate, pretransplant NMSC, childhood sunburning, and skin type as predictors. The PI generated was used to allocate patients into three screening groups (6 months, 2 years, and 5 years). The survival curves of these groups were significantly different (P<0.0001). Jack-knife validation correctly allocated all patients into the appropriate group. We have developed a simple PI to enable development of targeted NMSC surveillance strategies.

Beneficial effect of azathioprine and prediction of prognosis in primary biliary cirrhosis. Final results of an international trial.

PubMed

Christensen, E; Neuberger, J; Crowe, J; Altman, D G; Popper, H; Portmann, B; Doniach, D; Ranek, L; Tygstrup, N; Williams, R

1985-11-01

The effect of azathioprine on survival of patients with primary biliary cirrhosis was studied prospectively in a multinational, double-blind, randomized clinical trial including 248 patients of whom 127 received azathioprine and 121 placebo. There were 57 deaths in the azathioprine group and 62 in the placebo group. The actual survival was slightly longer during azathioprine than during placebo treatment. Using Cox multiple regression analysis and adjusting for slight imbalance between the two treatment groups, the therapeutic effect of azathioprine was statistically significant (p = 0.01), with azathioprine reducing the risk of dying to 59% of that observed during placebo treatment (95% confidence interval 40%-90%) or improving survival time by 20 mo in the average patient. Furthermore, azathioprine slowed down progressing incapacitation. Side effects of azathioprine were relatively few. The analysis revealed that the following five variables independently implied poor prognosis: high serum bilirubin, old age, cirrhosis, low serum albumin, and central cholestasis. These factors were combined to a "prognostic index" for prediction of outcome in new patients. The index was validated on independent patient data. On the basis of these results we recommend azathioprine as a routine treatment of primary biliary cirrhosis.

Predicting survival in AIDS: refining the model.

PubMed

Hutchinson, S J; Brettle, R P; Gore, S M

1997-11-01

We tested the validity of a previously-published AIDS staging system by examining AIDS-defining diseases (ADDs) and CD4 counts as prognostic factors for survival of the 248 AIDS patients in the Edinburgh City Hospital Cohort, of whom 56% were injecting drug-users (IDUs). Cox regression was used to model the proportionality of risk of death as the CD4 count declined and more ADDs were experienced, and dependence upon post-AIDS treatment. Using the system of Mocroft et al. (Lancet 1995; 346:12-17) to grade severity, our data were well enough modelled, but we suggest: (i) regrading of HIV dementia (RR 3.9, 95% CI 2.5-6.0), mainly attributed to the drug users, to a very severe ADD; (ii) reduction in risk from zidovudine (RR 0.7, 95% CI 0.5-1.0) during AIDS follow-up for patients starting treatment at or after AIDS diagnosis; (iii) improved management of first mild ADDs (from 1987-89 to 1994-95: 40% reduction in IDUs appearing with mild index diseases, and an approximate three-fold reduction in risk associated with a mild ADD). This study supports previous findings on the significance of ADDs and lowest CD4 count in predicting the lifetime of AIDS patients.

The effect of first chromosome long arm duplication on survival of endometrial carcinoma.

PubMed

Sever, Erman; Doğer, Emek; Çakıroğlu, Yiğit; Sünnetçi, Deniz; Çine, Naci; Savlı, Hakan; Yücesoy, İzzet

2014-12-01

The aim of this study is to investigate the effect of first chromosome long arm duplication (dup(1q)) in cases with endometrial carcinoma detected with array based comperative genomic hybridization (aCGH) on survival from the cancer. A total of 53 patients with the diagnosis of endometrial carcinom due to endometrial biopsy and who have been operated for this reason have been allocated in the study. Frozen section biopsy and staging surgery have been performed for all the cases. Samples obtained from the tumoral mass have been investigated for chromosomal aberrations with aCGH method. Kaplan-Meier and Cox-regression analysis have been performed for survival analysis. Among 53 cases with endometrial carcinomas, dup(1q) was diagnosed in 14 (26.4%) of the cases. For the patient group that has been followed-up for 24 months (3-33 months), dup(1q) (p=.01), optimal cytoreduction (p<.001), lymph node positivity (p=.006), tumor stage >1 (p=.006) and presence of high risk tumor were the factors that were associated with survival. Cox-regression analysis has revealed that optimal cytoreduction was the most important prognostic factor (p=.02). Presence of 1q duplication can be used as a prognostic factor in the preoperative period.

The effect of first chromosome long arm duplication on survival of endometrial carcinoma

PubMed Central

Sever, Erman; Doğer, Emek; Çakıroğlu, Yiğit; Sünnetçi, Deniz; Çine, Naci; Savlı, Hakan; Yücesoy, İzzet

2014-01-01

Objective: The aim of this study is to investigate the effect of first chromosome long arm duplication (dup(1q)) in cases with endometrial carcinoma detected with array based comperative genomic hybridization (aCGH) on survival from the cancer. Materials and Methods: A total of 53 patients with the diagnosis of endometrial carcinom due to endometrial biopsy and who have been operated for this reason have been allocated in the study. Frozen section biopsy and staging surgery have been performed for all the cases. Samples obtained from the tumoral mass have been investigated for chromosomal aberrations with aCGH method. Kaplan-Meier and Cox-regression analysis have been performed for survival analysis. Results: Among 53 cases with endometrial carcinomas, dup(1q) was diagnosed in 14 (26.4%) of the cases. For the patient group that has been followed-up for 24 months (3-33 months), dup(1q) (p=.01), optimal cytoreduction (p<.001), lymph node positivity (p=.006), tumor stage >1 (p=.006) and presence of high risk tumor were the factors that were associated with survival. Cox-regression analysis has revealed that optimal cytoreduction was the most important prognostic factor (p=.02). Conclusion: Presence of 1q duplication can be used as a prognostic factor in the preoperative period. PMID:28913021

Mastl overexpression is associated with epithelial to mesenchymal transition and predicts a poor clinical outcome in gastric cancer.

PubMed

Sun, Xian-Jun; Li, Yan-Liang; Wang, Long-Gang; Liu, Li-Qing; Ma, Heng; Hou, Wen-Hong; Yu, Jin-Ming

2017-12-01

Microtubule-associated serine/threonine kinase like (Mastl) is deregulated in a number of types of human malignancy and may be a kinase target for cancer treatment. The aim of the present study was to determine the Mastl expression in gastric cancer and to clarify its clinical and prognostic significance. Immunohistochemistry was performed on a cohort of 126 postoperative gastric cancer samples to detect the expression of Mastl and two epithelial to mesenchymal transition (EMT) markers, epithelial-cadherin and Vimentin. The χ 2 test, Kaplan-Meier estimator analysis and Cox's regression model were used to analyze the data. Upregulated Mastl protein expression was observed in the gastric cancer tissues compared with that in the adjacent non-cancerous gastric tissues. Increased Mastl expression was identified in 54/126 (42.9%) gastric cancer samples, and was significantly associated with lymph node metastasis, tumor relapse, EMT status and poor overall survival. Additional analysis demonstrated that the Mastl expression level stratified the patient outcome in stage III, but not stage II tumor subgroups. Cox's regression analysis revealed that increased Mastl expression was an independent prognostic factor for patients with gastric cancer. Mastl expression may be a valuable prognostic marker and a potential target for patients with gastric cancer.

White donor, younger donor and double lung transplant are associated with better survival in sarcoidosis patients.

PubMed

Salamo, Oriana; Roghaee, Shiva; Schweitzer, Michael D; Mantero, Alejandro; Shafazand, Shirin; Campos, Michael; Mirsaeidi, Mehdi

2018-05-03

Sarcoidosis commonly affects the lung. Lung transplantation (LT) is required when there is a severe and refractory involvement. We compared post-transplant survival rates of sarcoidosis patients with chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF). We also explored whether the race and age of the donor, and double lung transplant have any effect on the survival in the post transplant setting. We analyzed 9,727 adult patients with sarcoidosis, COPD, and IPF who underwent LT worldwide between 2005-2015 based on United Network for Organ Sharing (UNOS) database. Survival rates were compared with Kaplan-Meier, and risk factors were investigated by Cox-regression analysis. 469 (5%) were transplanted because of sarcoidosis, 3,688 (38%) for COPD and 5,570 (57%) for IPF. Unadjusted survival analysis showed a better post-transplant survival rate for patients with sarcoidosis (p < 0.001, Log-rank test). In Cox-regression analysis, double lung transplant and white race of the lung donor showed to have a significant survival advantage. Since double lung transplant, those who are younger and have lower Lung Allocation Score (LAS) at the time of transplant have a survival advantage, we suggest double lung transplant as the procedure of choice, especially in younger sarcoidosis subjects and with lower LAS scores.

Assessing the prediction accuracy of a cure model for censored survival data with long-term survivors: Application to breast cancer data.

PubMed

Asano, Junichi; Hirakawa, Akihiro

2017-01-01

The Cox proportional hazards cure model is a survival model incorporating a cure rate with the assumption that the population contains both uncured and cured individuals. It contains a logistic regression for the cure rate, and a Cox regression to estimate the hazard for uncured patients. A single predictive model for both the cure and hazard can be developed by using a cure model that simultaneously predicts the cure rate and hazards for uncured patients; however, model selection is a challenge because of the lack of a measure for quantifying the predictive accuracy of a cure model. Recently, we developed an area under the receiver operating characteristic curve (AUC) for determining the cure rate in a cure model (Asano et al., 2014), but the hazards measure for uncured patients was not resolved. In this article, we propose novel C-statistics that are weighted by the patients' cure status (i.e., cured, uncured, or censored cases) for the cure model. The operating characteristics of the proposed C-statistics and their confidence interval were examined by simulation analyses. We also illustrate methods for predictive model selection and for further interpretation of variables using the proposed AUCs and C-statistics via application to breast cancer data.

Prediction of non-biochemical recurrence rate after radical prostatectomy in a Japanese cohort: development of a postoperative nomogram.

PubMed

Okubo, Hidenori; Ohori, Makoto; Ohno, Yoshio; Nakashima, Jun; Inoue, Rie; Nagao, Toshitaka; Tachibana, Masaaki

2014-05-01

To develop a nomogram based on postoperative factors and prostate-specific antigen levels to predict the non-biochemical recurrence rate after radical prostatectomy ina Japanese cohort. A total of 606 Japanese patients with T1-3N0M0 prostate cancer who underwent radical prostatectomy and pelvic lymph node dissection at Tokyo Medical University hospital from 2000 to 2010 were studied. A nomogram was constructed based on Cox hazard regression analysis evaluating the prognostic significance of serum prostate-specific antigen and pathological factors in the radical prostatectomy specimens. The discriminating ability of the nomogram was assessed by the concordance index (C-index), and the predicted and actual outcomes were compared with a bootstrapped calibration plot. With a mean follow up of 60.0 months, a total of 187 patients (30.9%) experienced biochemical recurrence, with a 5-year non-biochemical recurrence rate of 72.3%. Based on a Cox hazard regression model, a nomogram was constructed to predict non-biochemical recurrence using serum prostate-specific antigen level and pathological features in radical prostatectomy specimens. The concordance index was 0.77, and the calibration plots appeared to be accurate. The postoperative nomogram described here can provide valuable information regarding the need for adjuvant/salvage radiation or hormonal therapy in patients after radical prostatectomy.

Community-Based Management of Child Malnutrition in Zambia: HIV/AIDS Infection and Other Risk Factors on Child Survival.

PubMed

Moramarco, Stefania; Amerio, Giulia; Ciarlantini, Clarice; Chipoma, Jean Kasengele; Simpungwe, Matilda Kakungu; Nielsen-Saines, Karin; Palombi, Leonardo; Buonomo, Ersilia

2016-07-01

(1) BACKGROUND: Supplementary feeding programs (SFPs) are effective in the community-based treatment of moderate acute malnutrition (MAM) and prevention of severe acute malnutrition (SAM); (2) METHODS: A retrospective study was conducted on a sample of 1266 Zambian malnourished children assisted from 2012 to 2014 in the Rainbow Project SFPs. Nutritional status was evaluated according to WHO/Unicef methodology. We performed univariate and multivariate Cox proportional risk regression to identify the main predictors of mortality. In addition, a time-to event analysis was performed to identify predictors of failure and time to cure events; (3) RESULTS: The analysis included 858 malnourished children (19 months ± 9.4; 49.9% males). Program outcomes met international standards with a better performance for MAM compared to SAM. Cox regression identified SAM (3.8; 2.1-6.8), HIV infection (3.1; 1.7-5.5), and WAZ <-3 (3.1; 1.6-5.7) as predictors of death. Time to event showed 80% of children recovered by SAM/MAM at 24 weeks. (4) CONCLUSIONS: Preventing deterioration of malnutrition, coupled to early detection of HIV/AIDS with adequate antiretroviral treatment, and extending the duration of feeding supplementation, could be crucial elements for ensuring full recovery and improve child survival in malnourished Zambian children.

Expression of multi-drug resistance-related genes MDR3 and MRP as prognostic factors in clinical liver cancer patients.

PubMed

Yu, Zheng; Peng, Sun; Hong-Ming, Pan; Kai-Feng, Wang

2012-01-01

To investigate the expression of multi-drug resistance-related genes, MDR3 and MRP, in clinical specimens of primary liver cancer and their potential as prognostic factors in liver cancer patients. A total of 26 patients with primary liver cancer were enrolled. The expression of MDR3 and MRP genes was measured by real-time PCR and the association between gene expression and the prognosis of patients was analyzed by the Kaplan-Meier method and COX regression model. This study showed that increases in MDR3 gene expression were identified in cholangiocellular carcinoma, cirrhosis and HBsAg-positive patients, while MRP expression increased in hepatocellular carcinoma, non-cirrhosis and HBsAg-negative patients. Moreover, conjugated bilirubin and total bile acid in the serum were significantly reduced in patients with high MRP expression compared to patients with low expression. The overall survival tended to be longer in patients with high MDR3 and MRP expression compared to the control group. MRP might be an independent prognostic factor in patients with liver cancer by COX regression analysis. MDR3 and MRP may play important roles in liver cancer patients as prognostic factors and their underlying mechanisms in liver cancer are worthy of further investigation.

The Poor Survival among Pulmonary Tuberculosis Patients in Chiapas, Mexico: The Case of Los Altos Region

PubMed Central

Nájera-Ortiz, J. C.; Sánchez-Pérez, H. J.; Ochoa-Díaz-López, H.; Leal-Fernández, G.; Navarro-Giné, A.

2012-01-01

Objective. To analyse survival in patients with pulmonary tuberculosis (PTB) and factors associated with such survival. Design. Study of a cohort of patients aged over 14 years diagnosed with PTB from January 1, 1998 to July 31, 2005. During 2004–2006 a home visit was made to each patient and, during 2008-2009, they were visited again. During these visits a follow-up interview was administered; when the patient had died, a verbal autopsy was conducted with family members. Statistical analysis consisted of survival tests, Kaplan-Meier log-rank test and Cox regression. Results. Of 305 studied patients, 68 had died due to PTB by the time of the first evaluation, 237 were followed-up for a second evaluation, and 10 of them had died of PTB. According to the Cox regression, age (over 45 years) and treatment duration (under six months) were associated with a poorer survival. When treatment duration was excluded, the association between poorer survival with age persisted, whereas with having been treated via DOTS strategy, was barely significant. Conclusions. In the studied area it is necessary that patients receive a complete treatment scheme, and to give priority to patients aged over 45 years. PMID:22701170

Abdominal Circumference Versus Body Mass Index as Predictors of Lower Extremity Overuse Injury Risk.

PubMed

Nye, Nathaniel S; Kafer, Drew S; Olsen, Cara; Carnahan, David H; Crawford, Paul F

2018-02-01

Abdominal circumference (AC) is superior to body mass index (BMI) as a measure of risk for various health outcomes. Our objective was to compare AC and BMI as predictors of lower extremity overuse injury (LEOI) risk. Retrospective review of electronic medical records of 79,868 US Air Force personnel over a 7-year period (2005-2011) for incidence of new LEOI. Subjects were stratified by BMI and AC. Injury risk for BMI/AC subgroups was calculated using Kaplan-Meier curves and Cox proportional-hazards regression. Receiver operating characteristic curves with area under the curve were used to compare each model's predictive value. Cox proportional-hazards regression showed significant risk association between elevated BMI, AC, and all injury types, with hazard ratios ranging 1.230-3.415 for obese versus normal BMI and 1.665-3.893 for high-risk versus low-risk AC (P < .05 for all measures). Receiver operating characteristic curves with area under the curve showed equivalent performance between BMI and AC for predicting all injury types. However, the combined model (AC and BMI) showed improved predictive ability over either model alone for joint injury, overall LEOI, and most strongly for osteoarthritis. Although AC and BMI alone performed similarly well, a combined approach using BMI and AC together improved risk estimation for LEOI.

Changes in survival patterns in urban Chinese patients with liver cancer

PubMed Central

Hao, Xi-Shan; Chen, Ke-Xin; Wang, Peizhong Peter; Rohan, Tom

2003-01-01

AIM: To examine the survival patterns and determinants of primary liver cancer in a geographically defined Chinese population. METHODS: Primary liver cancer cases (n = 13685) diagnosed between 1981 and 2000 were identified by the Tianjin Cancer Registry. Age-adjusted and age-specific incidence rates were examined in both males and females. Proportional hazards (Cox) regression was utilized to explore the effects of time of diagnosis, sex, age, occupation, residence, and hospital of diagnosis on survival. RESULTS: Crude and age-adjusted incidence rates in the study period were: 27.4/100000 and 26.3/100000 in males; and 11.5/100000 and 10.4/100000 in females, respectively. Cox regression analyses indicated that there was a significant improvement in survival rates over time. Industrial workers and older people had relatively poor survival rates. The hospital in which the liver cancer was diagnosed was a statistically significant predictor of survival; patients diagnosed in city hospitals were more likely to have better survival than those diagnosed in community/district hospitals. CONCLUSION: Patients diagnosed in recent years appeared to have a better outcome than those diagnosed in early times. There were also significant survival disparities with respect to occupation and hospital of diagnosis, which suggest that socioeconomic status may play an important role in determining prognosis. PMID:12800226

Association Between Metabolic Syndrome and the Serum Uric Acid: a Cohort Study.

PubMed

Ren, Ping; Gao, Mengna

2018-05-01

Metabolic syndrome (MS) consists of a cluster of metabolic diseases, and the association between serum uric acid (SUA) and MS has recently been reported in several studies; however, whether SUA is a susceptibility or risk biomarker for the development of MS among Chinese adults is unclear. This study was designed to investigate the relationship between SUA and MS. This study involved 4,988 subjects who were followed up for 9 years. Cox regression model was used to analyze the risk factors of MS. Of the 4,988 subjects, 1,192 subjects developed MS over 9 years of follow-up. The overall 9-year cumulative incidence of MS was 23.9%, ranging from 16.6% in quartile 1 to 35.1% in quartile 4 (p for trend < 0.001). Cox regression analyses indicated that SUA was significantly associated with incident MS (HR comparing quartile 2, 3, and 4 vs. quartile 1, 1.11, 1.33, and 1.78, respectively; p < 0.001) after adjusting for multiple associated parameters. In receiver operating characteristic curve analysis, the cutoff levels for SUA to predict incident MS were 350 μmol/L and 268 μmol/L in males and females, respectively. The results of this study demonstrated that high SUA concentrations may increase the risk of MS among Chinese adults.

Predictors for spontaneous pregnancy after microsurgical subinguinal varicocelectomy: a prospective cohort study.

PubMed

Zhang, Jian-Wei; Xu, Quan-Quan; Kuang, You-Lin; Wang, Yan; Xu, Feng; Tian, Yu-Dong

2017-06-01

The purpose of this study is to determine the possible preoperative predictors of spontaneous pregnancy (SPR) for infertile males with varicocele after microsurgical subinguinal varicocelectomy (MVL) performed in two medical centers in a prospective cohort study. A total of 120 males with varicocele that underwent MVL between June 2013 and June 2014 in two medical centers were documented. Related data, including male and female partner age, male body mass index (BMI), female BMI, preoperative semen parameters, hormone levels, testicular volume, grade and side of varicocele, were collected and analyzed. The follow-up assessment was also conducted within a 2-year period after the surgery. The outcome measure was SPR within the 2-year follow-up reported. The possible determinants of SPR were also analyzed and indentified using Cox regression analysis. Of the 110 patients that accomplished the 2-year follow-up, 42 patients reported pregnancy outcome. Using Cox regression analysis, total motile sperm count [TMC; RR (95% CI) = 1.362 (1.120-1.560), p = 0.003] and follicle-stimulating hormone [FSH; RR (95% CI) = 0.726 (0.541-0.980), p = 0.020] levels posed significant determinants for SPR. Our study indicated that males who underwent MVL with higher TMC and lower FSH preoperatively have higher possibility of pregnancy postoperatively.

Marginal regression analysis of recurrent events with coarsened censoring times.

PubMed

Hu, X Joan; Rosychuk, Rhonda J

2016-12-01

Motivated by an ongoing pediatric mental health care (PMHC) study, this article presents weakly structured methods for analyzing doubly censored recurrent event data where only coarsened information on censoring is available. The study extracted administrative records of emergency department visits from provincial health administrative databases. The available information of each individual subject is limited to a subject-specific time window determined up to concealed data. To evaluate time-dependent effect of exposures, we adapt the local linear estimation with right censored survival times under the Cox regression model with time-varying coefficients (cf. Cai and Sun, Scandinavian Journal of Statistics 2003, 30, 93-111). We establish the pointwise consistency and asymptotic normality of the regression parameter estimator, and examine its performance by simulation. The PMHC study illustrates the proposed approach throughout the article. © 2016, The International Biometric Society.

Cross-validation pitfalls when selecting and assessing regression and classification models.

PubMed

Krstajic, Damjan; Buturovic, Ljubomir J; Leahy, David E; Thomas, Simon

2014-03-29

We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. A key operational component of the proposed methods is cloud computing which enables routine use of previously infeasible approaches. We describe in detail an algorithm for repeated grid-search V-fold cross-validation for parameter tuning in classification and regression, and we define a repeated nested cross-validation algorithm for model assessment. As regards variable selection and parameter tuning we define two algorithms (repeated grid-search cross-validation and double cross-validation), and provide arguments for using the repeated grid-search in the general case. We show results of our algorithms on seven QSAR datasets. The variation of the prediction performance, which is the result of choosing different splits of the dataset in V-fold cross-validation, needs to be taken into account when selecting and assessing classification and regression models. We demonstrate the importance of repeating cross-validation when selecting an optimal model, as well as the importance of repeating nested cross-validation when assessing a prediction error.

Collagen Triple Helix Repeat Containing-1 (CTHRC1) Expression in Oral Squamous Cell Carcinoma (OSCC): Prognostic Value and Clinico-Pathological Implications

PubMed Central

Lee, Chia Ee; Vincent-Chong, Vui King; Ramanathan, Anand; Kallarakkal, Thomas George; Karen-Ng, Lee Peng; Ghani, Wan Maria Nabillah; Rahman, Zainal Ariff Abdul; Ismail, Siti Mazlipah; Abraham, Mannil Thomas; Tay, Keng Kiong; Mustafa, Wan Mahadzir Wan; Cheong, Sok Ching; Zain, Rosnah Binti

2015-01-01

BACKGROUND: Collagen Triple Helix Repeat Containing 1 (CTHRC1) is a protein often found to be over-expressed in various types of human cancers. However, correlation between CTHRC1 expression level with clinico-pathological characteristics and prognosis in oral cancer remains unclear. Therefore, this study aimed to determine mRNA and protein expression of CTHRC1 in oral squamous cell carcinoma (OSCC) and to evaluate the clinical and prognostic impact of CTHRC1 in OSCC. METHODS: In this study, mRNA and protein expression of CTHRC1 in OSCCs were determined by quantitative PCR and immunohistochemistry, respectively. The association between CTHRC1 and clinico-pathological parameters were evaluated by univariate and multivariate binary logistic regression analyses. Correlation between CTHRC1 protein expressions with survival were analysed using Kaplan-Meier and Cox regression models. RESULTS: Current study demonstrated CTHRC1 was significantly overexpressed at the mRNA level in OSCC. Univariate analyses indicated a high-expression of CTHRC1 that was significantly associated with advanced stage pTNM staging, tumour size ≥ 4 cm and positive lymph node metastasis (LNM). However, only positive LNM remained significant after adjusting with other confounder factors in multivariate logistic regression analyses. Kaplan-Meier survival analyses and Cox model demonstrated that patients with high-expression of CTHRC1 protein were associated with poor prognosis and is an independent prognostic factor in OSCC. CONCLUSION: This study indicated that over-expression of CTHRC1 potentially as an independent predictor for positive LNM and poor prognosis in OSCC. PMID:26664254

Variability in CKD stage in outpatients followed in two large renal clinics.

PubMed

Sikaneta, Tabo; Abdolell, Mohamed; Taskapan, Hulya; Roscoe, Janet; Fung, Jason; Nagai, Gordon; Ting, Robert H; Ng, Paul; Wu, George; Oreopoulos, Dimitrios; Tam, Paul Y

2012-10-01

Chronic kidney disease (CKD) is staged by glomerular filtration rate (GFR). CKD stages sometimes vary between routine office visits, and it is unknown if this impacts renal and patient survival separately from a cross-sectional CKD stage value. We quantified and categorized CKD stage variability in a large group of outpatients and correlated this with clinical and demographic features and with renal and patient survival. All estimated GFRs were staged in the first observation period. CKD stages were then categorized as static, improving, worsening, or fluctuating. Logistic regression analysis was performed to identify clinical variables associated with CKD stage variability. Death and dialysis progression rates were then collected and analyzed using Cox proportional regression. During a 1.1-year observation period, 1,262 patients (mean age 71.25 years) had a mean 5 eGFR's. CKD stages were static in 60.4%, worsened in 14.4%, improved in 7.4%, and fluctuated in 17.2% of patients. Secondary analysis revealed heavy proteinuria and East Asian ethnicity to be negatively, and diabetes mellitus and previous acute kidney injury to be positively associated with improving CKD stages. Cox proportional regression of 902 patients analyzed 2.3 years later revealed a negative association with improving CKD stage and subsequent need for dialysis. CKD stage changed in 40% of 1,262 elderly patients when determined 5 times in just over 1 year. Improving CKD stage was the only variability pattern significantly associated with any of the clinical outcomes when assessed 2.3 years later, being unlikely to be linked with subsequent need for dialysis.

Parametric Model Based On Imputations Techniques for Partly Interval Censored Data

NASA Astrophysics Data System (ADS)

Zyoud, Abdallah; Elfaki, F. A. M.; Hrairi, Meftah

2017-12-01

The term ‘survival analysis’ has been used in a broad sense to describe collection of statistical procedures for data analysis. In this case, outcome variable of interest is time until an event occurs where the time to failure of a specific experimental unit might be censored which can be right, left, interval, and Partly Interval Censored data (PIC). In this paper, analysis of this model was conducted based on parametric Cox model via PIC data. Moreover, several imputation techniques were used, which are: midpoint, left & right point, random, mean, and median. Maximum likelihood estimate was considered to obtain the estimated survival function. These estimations were then compared with the existing model, such as: Turnbull and Cox model based on clinical trial data (breast cancer data), for which it showed the validity of the proposed model. Result of data set indicated that the parametric of Cox model proved to be more superior in terms of estimation of survival functions, likelihood ratio tests, and their P-values. Moreover, based on imputation techniques; the midpoint, random, mean, and median showed better results with respect to the estimation of survival function.

Modeling Group Differences in OLS and Orthogonal Regression: Implications for Differential Validity Studies

ERIC Educational Resources Information Center

Kane, Michael T.; Mroch, Andrew A.

2010-01-01

In evaluating the relationship between two measures across different groups (i.e., in evaluating "differential validity") it is necessary to examine differences in correlation coefficients and in regression lines. Ordinary least squares (OLS) regression is the standard method for fitting lines to data, but its criterion for optimal fit…

Percutaneous radiofrequency ablation for early hepatocellular carcinoma: Risk factors for survival

PubMed Central

Kikuchi, Luciana; Menezes, Marcos; Chagas, Aline L; Tani, Claudia M; Alencar, Regiane SSM; Diniz, Marcio A; Alves, Venâncio AF; D’Albuquerque, Luiz Augusto Carneiro; Carrilho, Flair José

2014-01-01

AIM: To evaluate outcomes of radiofrequency ablation (RFA) therapy for early hepatocellular carcinoma (HCC) and identify survival- and recurrence-related factors. METHODS: Consecutive patients diagnosed with early HCC by computed tomography (CT) or magnetic resonance imaging (MRI) (single nodule of ≤ 5 cm, or multi- (up to 3) nodules of ≤ 3 cm each) and who underwent RFA treatment with curative intent between January 2010 and August 2011 at the Instituto do Câncer do Estado de São Paulo, Brazil were enrolled in the study. RFA of the liver tumors (with 1.0 cm ablative margin) was carried out under CT-fluoro scan and ultrasonic image guidance of the percutaneous ablation probes. Procedure-related complications were recorded. At 1-mo post-RFA and 3-mo intervals thereafter, CT and MRI were performed to assess outcomes of complete response (absence of enhancing tissue at the tumor site) or incomplete response (enhancing tissue remaining at the tumor site). Overall survival and disease-free survival rates were estimated by the Kaplan-Meier method and compared by the log rank test or simple Cox regression. The effect of risk factors on survival was assessed by the Cox proportional hazard model. RESULTS: A total of 38 RFA sessions were performed during the study period on 34 patients (age in years: mean, 63 and range, 49-84). The mean follow-up time was 22 mo (range, 1-33). The study population showed predominance of male sex (76%), less severe liver disease (Child-Pugh A, n = 26; Child-Pugh B, n = 8), and single tumor (65%). The maximum tumor diameters ranged from 10 to 50 mm (median, 26 mm). The initial (immediately post-procedure) rate of RFA-induced complete tumor necrosis was 90%. The probability of achieving complete response was significantly greater in patients with a single nodule (vs patients with multi-nodules, P = 0.04). Two patients experienced major complications, including acute pulmonary edema (resolved with intervention) and intestinal perforation (led to death). The 1- and 2-year overall survival rates were 82% and 71%, respectively. Sex, tumor size, initial response, and recurrence status influenced survival, but did not reach the threshold of statistical significance. Child-Pugh class and the model for end-stage liver disease score were identified as predictors of survival by simple Cox regression, but only Child-Pugh class showed a statistically significant association to survival in multiple Cox regression analysis (HR = 15; 95%CI: 3-76 mo; P = 0.001). The 1- and 2-year cumulative disease-free survival rates were 65% and 36%, respectively. CONCLUSION: RFA is an effective therapy for local tumor control of early HCC, and patients with preserved liver function are the best candidates. PMID:24587635

Perineural invasion is associated with increased relapse after external beam radiotherapy for men with low-risk prostate cancer and may be a marker for occult, high-grade cancer.

PubMed

Beard, C J; Chen, M H; Cote, K; Loffredo, M; Renshaw, A A; Hurwitz, M; D'Amico, A V

2004-01-01

To investigate the risk of postradiotherapy prostate-specific antigen (PSA) failure on the basis of pretreatment risk factors in prostate cancer patients with and without perineural invasion (PNI) in prostate biopsy specimens and to explain the observation that otherwise low-risk patients with PNI experience decreased freedom from PSA failure after external beam radiotherapy (RT). The study cohort consisted of 381 patients who underwent RT between 1989 and 2000 for clinically localized prostate cancer. A single genitourinary pathologist scored the absence or presence of PNI on all prostate biopsy specimens. Patients were divided into low-, intermediate- and high-risk subgroups on the basis of their 1992 American Joint Committee on Cancer T-stage, pretreatment PSA level, and Gleason score. Cox regression uni- and multivariate analyses were performed to evaluate whether the presence or absence of PNI in the biopsy specimen was a predictor of the time to post-RT PSA failure for patients in each pretreatment risk group. PSA failure was defined using the American Society for Therapeutic Radiology and Oncology consensus definition. Actuarial PSA failure-free survival was estimated using the Kaplan-Meier method, and comparisons were performed using the log-rank test. Cox regression univariate analysis revealed that PNI was a significant predictor of the time to PSA failure in the low-risk (p = 0.04) and high-risk (p = 0.03) cohorts. The 5-year PSA failure-free survival rate was 50% vs. 80% (p = 0.04) in low-risk patients, 70% vs. 75% (p = 0.72) in intermediate-risk patients, and 29% vs. 53% (p = 0.03) in high-risk patients with and without PNI, respectively. Cox regression multivariate analysis within the high-risk group revealed that a PSA level > or =20 ng/mL (p = 0.01) and Gleason score > or =8 (p = 0.02), but not PNI, were the only significant predictors of the time to PSA failure after RT. However, an association was found between the presence of PNI in the needle biopsy specimen and a biopsy Gleason score of 8-10 (p = 0.06). The association was stronger between the presence of PNI in the needle biopsy specimen and a biopsy Gleason score of 7-10 (p = 0. 033). A decrement in PSA outcome after RT for low-risk patients with PNI-positive biopsy specimens was found. The association between PNI and high Gleason score provides a possible explanation for the loss of statistical significance of PNI in the Cox regression multivariate analysis of the high-risk cohort. The data suggest that PNI found in the biopsy specimen of an otherwise low-risk patient predicts for occult high-grade disease that is missed owing to the sampling error associated with prostate biopsy. The association between PNI and a high Gleason score argues for the use of more aggressive therapy, such as hormonal therapy with RT and/or dose escalation, in these select patients.

Prognostic Estimation of Advanced Heart Failure With Low Left Ventricular Ejection Fraction and Wide QRS Interval.

PubMed

Oh, Changmyung; Chang, Hyuk-Jae; Sung, Ji Min; Kim, Ji Ye; Yang, Wooin; Shim, Jiyoung; Kang, Seok-Min; Ha, Jongwon; Rim, Se-Joong; Chung, Namsik

2012-10-01

Cardiac resynchronization therapy (CRT) has been known to improve the outcome of advanced heart failure (HF) but is still underutilized in clinical practice. We investigated the prognosis of patients with advanced HF who were suitable for CRT but were treated with conventional strategies. We also developed a risk model to predict mortality to improve the facilitation of CRT. Patients with symptomatic HF with left ventricular ejection fraction ≤35% and QRS interval >120 ms were consecutively enrolled at cardiovascular hospital. After excluding those patients who had received device therapy, 239 patients (160 males, mean 67±11 years) were eventually recruited. During a follow-up of 308±236 days, 56 (23%) patients died. Prior stroke, heart rate >90 bpm, serum Na ≤135 mEq/L, and serum creatinine ≥1.5 mg/dL were identified as independent factors using Cox proportional hazards regression. Based on the risk model, points were assigned to each of the risk factors proportional to the regression coefficient, and patients were stratified into three risk groups: low- (0), intermediate-(1-5), and high-risk (>5 points). The 2-year mortality rates of each risk group were 5, 31, and 64 percent, respectively. The C statistic of the risk model was 0.78, and the model was validated in a cohort from a different institution where the C statistic was 0.80. The mortality of patients with advanced HF who were managed conventionally was effectively stratified using a risk model. It may be useful for clinicians to be more proactive about adopting CRT to improve patient prognosis.

Integrated proteomics identified novel activation of dynein IC2-GR-COX-1 signaling in neurofibromatosis type I (NF1) disease model cells.

PubMed

Hirayama, Mio; Kobayashi, Daiki; Mizuguchi, Souhei; Morikawa, Takashi; Nagayama, Megumi; Midorikawa, Uichi; Wilson, Masayo M; Nambu, Akiko N; Yoshizawa, Akiyasu C; Kawano, Shin; Araki, Norie

2013-05-01

Neurofibromatosis type 1 (NF1) tumor suppressor gene product, neurofibromin, functions in part as a Ras-GAP, and though its loss is implicated in the neuronal abnormality of NF1 patients, its precise cellular function remains unclear. To study the molecular mechanism of NF1 pathogenesis, we prepared NF1 gene knockdown (KD) PC12 cells, as a NF1 disease model, and analyzed their molecular (gene and protein) expression profiles with a unique integrated proteomics approach, comprising iTRAQ, 2D-DIGE, and DNA microarrays, using an integrated protein and gene expression analysis chart (iPEACH). In NF1-KD PC12 cells showing abnormal neuronal differentiation after NGF treatment, of 3198 molecules quantitatively identified and listed in iPEACH, 97 molecules continuously up- or down-regulated over time were extracted. Pathway and network analysis further revealed overrepresentation of calcium signaling and transcriptional regulation by glucocorticoid receptor (GR) in the up-regulated protein set, whereas nerve system development was overrepresented in the down-regulated protein set. The novel up-regulated network we discovered, "dynein IC2-GR-COX-1 signaling," was then examined in NF1-KD cells. Validation studies confirmed that NF1 knockdown induces altered splicing and phosphorylation patterns of dynein IC2 isomers, up-regulation and accumulation of nuclear GR, and increased COX-1 expression in NGF-treated cells. Moreover, the neurite retraction phenotype observed in NF1-KD cells was significantly recovered by knockdown of the dynein IC2-C isoform and COX-1. In addition, dynein IC2 siRNA significantly inhibited nuclear translocation and accumulation of GR and up-regulation of COX-1 expression. These results suggest that dynein IC2 up-regulates GR nuclear translocation and accumulation, and subsequently causes increased COX-1 expression, in this NF1 disease model. Our integrated proteomics strategy, which combines multiple approaches, demonstrates that NF1-related neural abnormalities are, in part, caused by up-regulation of dynein IC2-GR-COX-1 signaling, which may be a novel therapeutic target for NF1.

Regression Discontinuity and Beyond: Options for Studying External Validity in an Internally Valid Design

ERIC Educational Resources Information Center

Wing, Coady; Bello-Gomez, Ricardo A.

2018-01-01

Treatment effect estimates from a "regression discontinuity design" (RDD) have high internal validity. However, the arguments that support the design apply to a subpopulation that is narrower and usually different from the population of substantive interest in evaluation research. The disconnect between RDD population and the…

Double Cross-Validation in Multiple Regression: A Method of Estimating the Stability of Results.

ERIC Educational Resources Information Center

Rowell, R. Kevin

In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is…

Association between Stereotactic Radiotherapy and Death from Brain Metastases of Epithelial Ovarian Cancer: a Gliwice Data Re-Analysis with Penalization

PubMed

Tukiendorf, Andrzej; Mansournia, Mohammad Ali; Wydmański, Jerzy; Wolny-Rokicka, Edyta

2017-04-01

Background: Clinical datasets for epithelial ovarian cancer brain metastatic patients are usually small in size. When adequate case numbers are lacking, resulting estimates of regression coefficients may demonstrate bias. One of the direct approaches to reduce such sparse-data bias is based on penalized estimation. Methods: A re- analysis of formerly reported hazard ratios in diagnosed patients was performed using penalized Cox regression with a popular SAS package providing additional software codes for a statistical computational procedure. Results: It was found that the penalized approach can readily diminish sparse data artefacts and radically reduce the magnitude of estimated regression coefficients. Conclusions: It was confirmed that classical statistical approaches may exaggerate regression estimates or distort study interpretations and conclusions. The results support the thesis that penalization via weak informative priors and data augmentation are the safest approaches to shrink sparse data artefacts frequently occurring in epidemiological research. Creative Commons Attribution License

Nomogram-based prediction of survival in patients with advanced oesophagogastric adenocarcinoma receiving first-line chemotherapy: a multicenter prospective study in the era of trastuzumab

PubMed Central

Custodio, A; Carmona-Bayonas, A; Jiménez-Fonseca, P; Sánchez, M L; Viudez, A; Hernández, R; Cano, J M; Echavarria, I; Pericay, C; Mangas, M; Visa, L; Buxo, E; García, T; Rodríguez Palomo, A; Álvarez Manceñido, F; Lacalle, A; Macias, I; Azkarate, A; Ramchandani, A; Fernández Montes, A; López, C; Longo, F; Sánchez Bayona, R; Limón, M L; Díaz-Serrano, A; Hurtado, A; Madero, R; Gómez, C; Gallego, J

2017-01-01

Background: To develop and validate a nomogram and web-based calculator to predict overall survival (OS) in Caucasian-advanced oesophagogastric adenocarcinoma (AOA) patients undergoing first-line combination chemotherapy. Methods: Nine hundred twenty-four AOA patients treated at 28 Spanish teaching hospitals from January 2008 to September 2014 were used as derivation cohort. The result of an adjusted-Cox proportional hazards regression was represented as a nomogram and web-based calculator. The model was validated in 502 prospectively recruited patients treated between October 2014 and December 2016. Harrell's c-index was used to evaluate discrimination. Results: The nomogram includes seven predictors associated with OS: HER2-positive tumours treated with trastuzumab, Eastern Cooperative Oncology Group performance status, number of metastatic sites, bone metastases, ascites, histological grade, and neutrophil-to-lymphocyte ratio. Median OS was 5.8 (95% confidence interval (CI), 4.5–6.6), 9.4 (95% CI, 8.5–10.6), and 14 months (95% CI, 11.8–16) for high-, intermediate-, and low-risk groups, respectively (P<0.001), in the derivation set and 4.6 (95% CI, 3.3–8.1), 12.7 (95% CI, 11.3–14.3), and 18.3 months (95% CI, 14.6–24.2) for high-, intermediate-, and low-risk groups, respectively (P<0.001), in the validation set. The nomogram is well-calibrated and reveals acceptable discriminatory capacity, with optimism-corrected c-indices of 0.618 (95% CI, 0.591–0.631) and 0.673 (95% CI, 0.636–0.709) in derivation and validation groups, respectively. The AGAMENON nomogram outperformed the Royal Marsden Hospital (c-index=0.583; P=0.00046) and Japan Clinical Oncology Group prognostic indices (c-index=0.611; P=0.03351). Conclusions: We developed and validated a straightforward model to predict survival in Caucasian AOA patients initiating first-line polychemotherapy. This model can contribute to inform clinical decision-making and optimise clinical trial design. PMID:28463962

Novel Harmonic Regularization Approach for Variable Selection in Cox's Proportional Hazards Model

PubMed Central

Chu, Ge-Jin; Liang, Yong; Wang, Jia-Xuan

2014-01-01

Variable selection is an important issue in regression and a number of variable selection methods have been proposed involving nonconvex penalty functions. In this paper, we investigate a novel harmonic regularization method, which can approximate nonconvex Lq  (1/2 < q < 1) regularizations, to select key risk factors in the Cox's proportional hazards model using microarray gene expression data. The harmonic regularization method can be efficiently solved using our proposed direct path seeking approach, which can produce solutions that closely approximate those for the convex loss function and the nonconvex regularization. Simulation results based on the artificial datasets and four real microarray gene expression datasets, such as real diffuse large B-cell lymphoma (DCBCL), the lung cancer, and the AML datasets, show that the harmonic regularization method can be more accurate for variable selection than existing Lasso series methods. PMID:25506389

Eminence, IQ, physical and mental health, and achievement domain : Cox's 282 Geniuses revisited.

PubMed

Simonton, Dean Keith; Song, Anna V

2009-04-01

Catharine Cox published two studies of highly eminent creators and leaders, the first in 1926 as the second volume of Terman's landmark Genetic Studies of Genius and the second in 1936 as a coauthored article. The former publication concentrated on the relation between IQ and achieved eminence, and the latter focused on early physical and mental health. Taking advantage of unpublished data from the second study, we examined, for the first time, the relationships among achieved eminence, IQ, early physical and mental health, and achievement domain. The correlation and regression analyses showed, for these 282 individuals, that eminence is a positive function of IQ and that IQ is a positive function of mental health and a negative function of physical health, implying an indirect effect of physical and mental health on eminence. Furthermore, levels of early physical and mental health vary across 10 specific domains of achievement.

Diagnostic and Prognostic Value of Long-Axis Strain and Myocardial Contraction Fraction Using Standard Cardiovascular MR Imaging in Patients with Nonischemic Dilated Cardiomyopathies.

PubMed

Arenja, Nisha; Riffel, Johannes H; Fritz, Thomas; André, Florian; Aus dem Siepen, Fabian; Mueller-Hennessen, Matthias; Giannitsis, Evangelos; Katus, Hugo A; Friedrich, Matthias G; Buss, Sebastian J

2017-06-01

Purpose To assess the utility of established functional markers versus two additional functional markers derived from standard cardiovascular magnetic resonance (MR) images for their incremental diagnostic and prognostic information in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods Approval was obtained from the local ethics committee. MR images from 453 patients with NIDCM and 150 healthy control subjects were included between 2005 and 2013 and were analyzed retrospectively. Myocardial contraction fraction (MCF) was calculated by dividing left ventricular (LV) stroke volume by LV myocardial volume, and long-axis strain (LAS) was calculated from the distances between the epicardial border of the LV apex and the midpoint of a line connecting the origins of the mitral valve leaflets at end systole and end diastole. Receiver operating characteristic curve, Kaplan-Meier method, Cox regression, and classification and regression tree (CART) analyses were performed for diagnostic and prognostic performances. Results LAS (area under the receiver operating characteristic curve [AUC] = 0.93, P < .001) and MCF (AUC = 0.92, P < .001) can be used to discriminate patients with NIDCM from age- and sex-matched control subjects. A total of 97 patients reached the combined end point during a median follow-up of 4.8 years. In multivariate Cox regression analysis, only LV ejection fraction (EF) and LAS independently indicated the combined end point (hazard ratio = 2.8 and 1.9, respectively; P < .001 for both). In a risk stratification approach with classification and regression tree analysis, combined LV EF and LAS cutoff values were used to stratify patients into three risk groups (log-rank test, P < .001). Conclusion Cardiovascular MR-derived MCF and LAS serve as reliable diagnostic and prognostic markers in patients with NIDCM. LAS, as a marker for longitudinal contractile function, is an independent parameter for outcome and offers incremental information beyond LV EF and the presence of myocardial fibrosis. © RSNA, 2017 Online supplemental material is available for this article.

Body mass index in relation to serum prostate-specific antigen levels and prostate cancer risk.

PubMed

Bonn, Stephanie E; Sjölander, Arvid; Tillander, Annika; Wiklund, Fredrik; Grönberg, Henrik; Bälter, Katarina

2016-07-01

High Body mass index (BMI) has been directly associated with risk of aggressive or fatal prostate cancer. One possible explanation may be an effect of BMI on serum levels of prostate-specific antigen (PSA). To study the association between BMI and serum PSA as well as prostate cancer risk, a large cohort of men without prostate cancer at baseline was followed prospectively for prostate cancer diagnoses until 2015. Serum PSA and BMI were assessed among 15,827 men at baseline in 2010-2012. During follow-up, 735 men were diagnosed with prostate cancer with 282 (38.4%) classified as high-grade cancers. Multivariable linear regression models and natural cubic linear regression splines were fitted for analyses of BMI and log-PSA. For risk analysis, Cox proportional hazards regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) and natural cubic Cox regression splines producing standardized cancer-free probabilities were fitted. Results showed that baseline Serum PSA decreased by 1.6% (95% CI: -2.1 to -1.1) with every one unit increase in BMI. Statistically significant decreases of 3.7, 11.7 and 32.3% were seen for increasing BMI-categories of 25 < 30, 30 < 35 and ≥35 kg/m(2), respectively, compared to the reference (18.5 < 25 kg/m(2)). No statistically significant associations were seen between BMI and prostate cancer risk although results were indicative of a positive association to incidence rates of high-grade disease and an inverse association to incidence of low-grade disease. However, findings regarding risk are limited by the short follow-up time. In conclusion, BMI was inversely associated to PSA-levels. BMI should be taken into consideration when referring men to a prostate biopsy based on serum PSA-levels. © 2016 UICC.

Soccer and sexual health education: a promising approach for reducing adolescent births in Haiti.

PubMed

Kaplan, Kathryn C; Lewis, Judy; Gebrian, Bette; Theall, Katherine

2015-05-01

To explore the effect of an innovative, integrative program in female sexual reproductive health (SRH) and soccer (or fútbol, in Haitian Creole) in rural Haiti by measuring the rate of births among program participants 15-19 years old and their nonparticipant peers. A retrospective cohort study using 2006-2009 data from the computerized data-tracking system of the Haitian Health Foundation (HHF), a U.S.-based nongovernmental organization serving urban and rural populations in Haiti, was used to assess births among girls 15-19 years old who participated in HHF's GenNext program, a combination education-soccer program for youth, based on SRH classes HHF nurses and community workers had been conducting in Haiti for mothers, fathers, and youth; girl-centered health screenings; and an all-female summer soccer league, during 2006-2009 (n = 4 251). Bivariate and multiple logistic regression analyses were carried out to assess differences in the rate of births among program participants according to their level of participation (SRH component only ("EDU") versus both the SRH and soccer components ("SO") compared to their village peers who did not participate. Hazard ratios (HRs) of birth rates were estimated using Cox regression analysis of childbearing data for the three different groups. In the multiple logistic regression analysis, only the girls in the "EDU" group had significantly fewer births than the nonparticipants after adjusting for confounders (odds ratio = 0.535; 95% confidence interval (CI) = 0.304, 0.940). The Cox regression analysis demonstrated that those in the EDU group (HR = 0.893; 95% CI = 0.802, 0.994) and to a greater degree those in the SO group (HR = 0.631; 95% CI = 0.558, 0.714) were significantly protected against childbearing between the ages of 15 and 19 years. HHF's GenNext program demonstrates the effectiveness of utilizing nurse educators, community mobilization, and youth participation in sports, education, and structured youth groups to promote and sustain health for adolescent girls and young women.

Validation of post-operative residual contrast enhancing tumor volume as an independent prognostic factor for overall survival in newly diagnosed glioblastoma.

PubMed

Ellingson, Benjamin M; Abrey, Lauren E; Nelson, Sarah J; Kaufmann, Timothy J; Garcia, Josep; Chinot, Olivier; Saran, Frank; Nishikawa, Ryo; Henriksson, Roger; Mason, Warren P; Wick, Wolfgang; Butowski, Nicholas; Ligon, Keith L; Gerstner, Elizabeth R; Colman, Howard; de Groot, John; Chang, Susan; Mellinghoff, Ingo; Young, Robert J; Alexander, Brian M; Colen, Rivka; Taylor, Jennie W; Arrillaga-Romany, Isabel; Mehta, Arnav; Huang, Raymond Y; Pope, Whitney B; Reardon, David; Batchelor, Tracy; Prados, Michael; Galanis, Evanthia; Wen, Patrick Y; Cloughesy, Timothy F

2018-04-05

In the current study, we pooled imaging data in newly diagnosed GBM patients from international multicenter clinical trials, single institution databases, and multicenter clinical trial consortiums to identify the relationship between post-operative residual enhancing tumor volume and overall survival (OS). Data from 1,511 newly diagnosed GBM patients from 5 data sources were included in the current study: 1) a single institution database from UCLA (N=398; Discovery); 2) patients from the Ben and Cathy Ivy Foundation for Early Phase Clinical Trials Network Radiogenomics Database (N=262 from 8 centers; Confirmation); 3) the chemoradiation placebo arm from an international phase III trial (AVAglio; N=394 from 120 locations in 23 countries; Validation); 4) the experimental arm from AVAglio examining chemoradiation plus bevacizumab (N=404 from 120 locations in 23 countries; Exploratory Set 1); and 5) an Alliance (N0874) Phase I/II trial of vorinostat plus chemoradiation (N=53; Exploratory Set 2). Post-surgical, residual enhancing disease was quantified using T1 subtraction maps. Multivariate Cox regression models were used to determine influence of clinical variables, MGMT status, and residual tumor volume on OS. A log-linear relationship was observed between post-operative, residual enhancing tumor volume and OS in newly diagnosed GBM treated with standard chemoradiation. Post-operative tumor volume is a prognostic factor for OS (P<0.01), regardless of therapy, age, and MGMT promoter methylation status. Post-surgical, residual contrast-enhancing disease significantly negatively influences survival in patients with newly diagnosed glioblastoma treated with chemoradiation with or without concomitant experimental therapy.

External validation of the modified Glasgow prognostic score for renal cancer

PubMed Central

Tai, Caroline G.; Johnson, Timothy V.; Abbasi, Ammara; Herrell, Lindsey; Harris, Wayne B.; Kucuk, Omer; Canter, Daniel J.; Ogan, Kenneth; Pattaras, John G.; Nieh, Peter T.; Master, Viraj A.

2014-01-01

Purpose: The modified Glasgow prognostic Score (mGPS) incorporates C-reactive protein and albumin as a clinically useful marker of tumor behavior. The ability of the mGPS to predict metastasis in localized renal cell carcinoma (RCC) remains unknown in an external validation cohort. Patients and Methods: Patients with clinically localized clear cell RCC were followed for 1 year post-operatively. Metastases were identified radiologically. Patients were categorized by mGPS score as low-risk (mGPS = 0 points), intermediate-risk (mGPS = 1 point) and high-risk (mGPS = 2 points). Univariate, Kaplan-Meier and multivariate Cox regression analyses examined Recurrence -free survival (RFS) across patient and disease characteristics. Results: Of the 129 patients in this study, 23.3% developed metastases. Of low, intermediate and high risk patients, 10.1%, 38.9% and 89.9% recurred during the study. After accounting for various patient and tumor characteristics in multivariate analysis including stage and grade, only mGPS was significantly associated with RFS. Compared with low-risk patients, intermediate- and high-risk patients experienced a 4-fold (hazard ratios [HR]: 4.035, 95% confidence interval [CI]: 1.312-12.415, P = 0.015) and 7-fold (HR: 7.012, 95% CI: 2.126-23.123 P < 0.001) risk of metastasis, respectively. Conclusions: mGPS is a robust predictor of metastasis following potentially curative nephrectomy for localized RCC. Clinicians may consider mGPS as an adjunct to identify high-risk patients for possible enrollment into clinical trials or for patient counseling PMID:24497679

A Prognostic Model to Predict Mortality among Non-Small-Cell Lung Cancer Patients in the U.S. Military Health System.

PubMed

Lin, Jie; Carter, Corey A; McGlynn, Katherine A; Zahm, Shelia H; Nations, Joel A; Anderson, William F; Shriver, Craig D; Zhu, Kangmin

2015-12-01

Accurate prognosis assessment after non-small-cell lung cancer (NSCLC) diagnosis is an essential step for making effective clinical decisions. This study is aimed to develop a prediction model with routinely available variables to assess prognosis in patients with NSCLC in the U.S. Military Health System. We used the linked database from the Department of Defense's Central Cancer Registry and the Military Health System Data Repository. The data set was randomly and equally split into a training set to guide model development and a testing set to validate the model prediction. Stepwise Cox regression was used to identify predictors of survival. Model performance was assessed by calculating area under the receiver operating curves and construction of calibration plots. A simple risk scoring system was developed to aid quick risk score calculation and risk estimation for NSCLC clinical management. The study subjects were 5054 patients diagnosed with NSCLC between 1998 and 2007. Age, sex, tobacco use, tumor stage, histology, surgery, chemotherapy, peripheral vascular disease, cerebrovascular disease, and diabetes mellitus were identified as significant predictors of survival. Calibration showed high agreement between predicted and observed event rates. The area under the receiver operating curves reached 0.841, 0.849, 0.848, and 0.838 during 1, 2, 3, and 5 years, respectively. This is the first NSCLC prognosis model for quick risk assessment within the Military Health System. After external validation, the model can be translated into clinical use both as a web-based tool and through mobile applications easily accessible to physicians, patients, and researchers.

Evaluation of the proposed International Association for the Study of Lung Cancer (IASLC)/International Thymic Malignancies Interest Group (ITMIG) staging revisions in thymic well-differentiated neuroendocrine carcinoma patients.

PubMed

Zhao, Yang; Shi, Jianxin; Fan, Limin; Yang, Jun; Hu, Dingzhong; Zhao, Heng

2016-02-01

In 2014, the International Association for the Study of Lung Cancer (IASLC)/International Thymic Malignancies Interest Group (ITMIG) launched a worldwide Tumor Node Metastasis (TNM) staging proposal for the next edition of thymic tumours. The objective of the current study was to evaluate the proposed new staging system specific to the thymic well-differentiated neuroendocrine carcinoma (TWDNC). From November 2003 to July 2014, 61 consecutive patients were enrolled in this study with pathologically confirmed TWDNC in Shanghai Chest Hospital. Clinical and pathological data were retrospectively reviewed. Survival analysis was performed using the Kaplan-Meier and log-rank tests. Validity evaluation was addressed by Cox proportional hazards regression model, after adjusting for potential confounders and visually assessing the distinction of curves generated based on the staging system of Masaoka-Koga and the proposed TNM ones. Thymic carcinoids made up 4% of total thymic tumours in our institution. The 5-year overall survival (OS) rate and the disease-free survival (DFS) rate were 72 and 41%, respectively. Neither Masaoka-Koga staging system nor the proposed TNM system showed ordered appropriateness visually in survival curves and the prognostic demarcation between stages was poor on both OS and DFS. The IASLC/ITMIG suggested that the TNM and Masaoka-Koga staging systems fail to predict the clinical course of TWDNC patients. Collaborative effort is needed in the future staging validation as ITMIG recommended. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Expression profiles analysis of long non-coding RNAs identified novel lncRNA biomarkers with predictive value in outcome of cutaneous melanoma.

PubMed

Ma, Xu; He, Zhijuan; Li, Ling; Yang, Daping; Liu, Guofeng

2017-09-29

Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5 ) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.

Transcriptome-wide analyses indicate mitochondrial responses to particulate air pollution exposure.

PubMed

Winckelmans, Ellen; Nawrot, Tim S; Tsamou, Maria; Den Hond, Elly; Baeyens, Willy; Kleinjans, Jos; Lefebvre, Wouter; Van Larebeke, Nicolas; Peusens, Martien; Plusquin, Michelle; Reynders, Hans; Schoeters, Greet; Vanpoucke, Charlotte; de Kok, Theo M; Vrijens, Karen

2017-08-18

Due to their lack of repair capacity mitochondria are critical targets for environmental toxicants. We studied genes and pathways reflecting mitochondrial responses to short- and medium-term PM 10 exposure. Whole genome gene expression was measured in peripheral blood of 98 adults (49% women). We performed linear regression analyses stratified by sex and adjusted for individual and temporal characteristics to investigate alterations in gene expression induced by short-term (week before blood sampling) and medium-term (month before blood sampling) PM 10 exposure. Overrepresentation analyses (ConsensusPathDB) were performed to identify enriched mitochondrial associated pathways and gene ontology sets. Thirteen Human MitoCarta genes were measured by means of quantitative real-time polymerase chain reaction (qPCR) along with mitochondrial DNA (mtDNA) content in an independent validation cohort (n = 169, 55.6% women). Overrepresentation analyses revealed significant pathways (p-value <0.05) related to mitochondrial genome maintenance and apoptosis for short-term exposure and to the electron transport chain (ETC) for medium-term exposure in women. For men, medium-term PM 10 exposure was associated with the Tri Carbonic Acid cycle. In an independent study population, we validated several ETC genes, including UQCRH and COX7C (q-value <0.05), and some genes crucial for the maintenance of the mitochondrial genome, including LONP1 (q-value: 0.07) and POLG (q-value: 0.04) in women. In this exploratory study, we identified mitochondrial genes and pathways associated with particulate air pollution indicating upregulation of energy producing pathways as a potential mechanism to compensate for PM-induced mitochondrial damage.

Are classic predictors of voltage valid in cardiac amyloidosis? A contemporary analysis of electrocardiographic findings.

PubMed

Sperry, Brett W; Vranian, Michael N; Hachamovitch, Rory; Joshi, Hariom; McCarthy, Meghann; Ikram, Asad; Hanna, Mazen

2016-07-01

Low voltage electrocardiography (ECG) coupled with increased ventricular wall thickness is the hallmark of cardiac amyloidosis. However, patient characteristics influencing voltage in the general population, including bundle branch block, have not been evaluated in amyloid heart disease. A retrospective analysis was performed of patients with newly diagnosed cardiac amyloidosis from 2002 to 2014. ECG voltage was calculated using limb (sum of QRS complex in leads I, II and III) and precordial (Sokolow: S in V1 plus R in V5-V6) criteria. The associations between voltage and clinical variables were tested using multivariable linear regression. A Cox model assessed the association of voltage with mortality. In 389 subjects (transthyretin ATTR 186, light chain AL 203), 30% had conduction delay (QRS >120ms). In those with narrow QRS, 68% met low limb, 72% low Sokolow and 57% both criteria, with lower voltages found in AL vs ATTR. LV mass index as well as other typical factors that impact voltage (age, sex, race, hypertension, BSA, and smoking) in the general population were not associated with voltage in this cardiac amyloidosis cohort. Patients with LBBB and IVCD had similar voltages when compared to those with narrow QRS. Voltage was significantly associated with mortality (p<0.001 for both criteria) after multivariable adjustment. Classic predictors of ECG voltage in the general population are not valid in cardiac amyloidosis. In this cohort, the prevalence estimates of ventricular conduction delay and low voltage are higher than previously reported. Voltage predicts mortality after multivariable adjustment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

External validation of the PROFUND index in polypathological patients from internal medicine and acute geriatrics departments in Aragón.

PubMed

Díez-Manglano, Jesús; Cabrerizo García, José Luis; García-Arilla Calvo, Ernesto; Jimeno Saínz, Araceli; Calvo Beguería, Eva; Martínez-Álvarez, Rosa M; Bejarano Tello, Esperanza; Caudevilla Martínez, Aránzazu

2015-12-01

The objective of the study was to validate externally and prospectively the PROFUND index to predict survival of polypathological patients after a year. An observational, prospective and multicenter study was performed. Polypathological patients admitted to an internal medicine or geriatrics department and attended by investigators consecutively between March 1 and June 30, 2011 were included. Data concerning age, gender, comorbidity, Barthel and Lawton-Brody indexes, Pfeiffer questionnaire, socio-familial Gijon scale, delirium, number of drugs and number of admissions during the previous year were gathered for each patient. The PROFUND index was calculated. The follow-up lasted 1 year. A Cox proportional regression model was calculated, and was used to analyze the association of the variables to mortality and C-statistic. 465 polypathological patients, 333 from internal medicine and 132 from geriatrics, were included. One-year mortality is associated with age [hazard ratio (HR) 1.52 95 % CI 1.04-2.12; p = 0.01], presence of neoplasia [HR 2.68 95 % CI 1.71-4.18; p = 0.0001] and dependence for basic activities of daily living [HR 2.34 95 % CI 1.61-3.40; p = 0.0009]. In predicting mortality, the PROFUND index shows good discrimination in patients from internal medicine (C-statistics 0.725 95 % CI 0.670-0.781), but a poor one in those from geriatrics (0.546 95 % CI 0.448-0.644). The PROFUND index is a reliable tool for predicting mortality in internal medicine PP patients.

SELF-RATED EXPECTATIONS OF SUICIDAL BEHAVIOR PREDICT FUTURE SUICIDE ATTEMPTS AMONG ADOLESCENT AND YOUNG ADULT PSYCHIATRIC EMERGENCY PATIENTS.

PubMed

Czyz, Ewa K; Horwitz, Adam G; King, Cheryl A

2016-06-01

This study's purpose was to examine the predictive validity and clinical utility of a brief measure assessing youths' own expectations of their future risk of suicidal behavior, administered in a psychiatric emergency (PE) department; and determine if youths' ratings improve upon a clinician-administered assessment of suicidal ideation severity. The outcome was suicide attempts up to 18 months later. In this medical record review study, 340 consecutively presenting youths (ages 13-24) seeking PE services over a 7-month period were included. Subsequent PE visits and suicide attempts were retrospectively tracked for up to 18 months. The 3-item scale assessing patients' perception of their own suicidal behavior risk and the clinician-administered ideation severity scale were used routinely at the study site. Cox regression results showed that youths' expectations of suicidal behavior were independently associated with increased risk of suicide attempts, even after adjusting for key covariates. Results were not moderated by sex, suicide attempt history, or age. Receiver-operating characteristic (ROC) analyses indicated that self-assessed expectations of risk improved the predictive accuracy of the clinician-administered suicidal ideation measure. Youths' ratings indicative of lower confidence in maintaining safety uniquely predicted follow-up attempts and provided incremental validity over and above the clinician-administered assessment and improved its accuracy, suggesting their potential for augmenting suicide risk formulation. Assessing youths' own perceptions of suicide risk appears to be clinically useful, feasible to implement in PE settings, and, if replicated, promising for improving identification of youth at risk for suicidal behavior. © 2016 Wiley Periodicals, Inc.

Predictors of Recurrent Falls in People with Parkinson's Disease and Proposal for a Predictive Tool.

PubMed

Almeida, Lorena R S; Valenca, Guilherme T; Negreiros, Nádja N; Pinto, Elen B; Oliveira-Filho, Jamary

2017-01-01

Falls are a debilitating problem for people with Parkinson's disease (PD). To compare clinical and functional characteristics of non-fallers, single and recurrent fallers (≥2 falls); to determine predictors of time to second fall; and to develop a predictive tool for identifying people with PD at different categories of falls risk. Participants (n = 229) were assessed by disease-specific, self-report and balance measures and followed up for 12 months. Area under the receiver operating characteristic curves (AUC), Kaplan-Meier curves and log-rank test were performed. Selected predictors with p < 0.10 in univariate analysis were chosen to be entered into the Cox regression model. Eighty-four (37%) participants had ≥2 falls during the follow-up. Recurrent fallers significantly differed from single fallers. The final Cox model included history of ≥2 falls in the past year (Hazard Ratio [HR] = 3.94; 95% confidence interval [CI] 2.26-6.86), motor fluctuations (HR = 1.91; 95% CI 1.12-3.26), UPDRS activities of daily living (ADL) (HR = 1.10 per 1 point increase; 95% CI 1.06-1.14) and levodopa equivalent dose (LED) (HR = 1.09 per 100 mg increase; 95% CI 1.02-1.16). A 3-predictor tool included history of ≥2 falls in the past year, motor fluctuations and UPDRS ADL >12 points (AUC = 0.84; 95% CI 0.78-0.90). By adding LED >700 mg/day and Berg balance scale ≤49 points, a 5-predictor tool was developed (AUC = 0.86; 95% CI 0.81-0.92). Two predictive tools with moderate-to-high accuracy may identify people with PD at low, medium and high risk of falling recurrently within the next year. However, future studies to address external validation are required.

The effect of rheumatoid arthritis-associated autoantibodies on the incidence of cardiovascular events in a large inception cohort of early inflammatory arthritis.

PubMed

Barra, Lillian J; Pope, Janet E; Hitchon, Carol; Boire, Gilles; Schieir, Orit; Lin, Daming; Thorne, Carter J; Tin, Diane; Keystone, Edward C; Haraoui, Boulos; Jamal, Shahin; Bykerk, Vivian P

2017-05-01

. RA is associated with an increased risk of cardiovascular events (CVEs). The objective was to estimate independent effects of RA autoantibodies on the incident CVEs in patients with early RA. Patients were enrolled in the Canadian Early Inflammatory Arthritis Cohort, a prospective multicentre inception cohort. Incident CVEs, including acute coronary syndromes and cerebrovascular events, were self-reported by the patient and partially validated by medical chart review. Seropositive status was defined as either RF or ACPA positive. Multivariable Cox proportional hazards survival analysis was used to estimate the effects of seropositive status on incident CVEs, controlling for RA clinical variables and traditional cardiovascular risk factors. . A total of 2626 patients were included: the mean symptom duration at diagnosis was 6.3 months ( s . d . 4.6), the mean age was 53 years ( s . d . 15), 72% were female and 86% met classification criteria for RA. Forty-six incident CVEs occurred over 6483 person-years [incidence rate 7.1/1000 person-years (95% confidence interval 5.3, 9.4)]. The CVE rate did not differ in seropositive vs seronegative subjects and seropositivity was not associated with incident CVEs in multivariable Cox regression models. Baseline covariates independently associated with incident CVEs were older age, a history of hypertension and a longer duration of RA symptoms prior to diagnosis. The rate of CVEs early in the course of inflammatory arthritis was low; however, delays in the diagnosis of arthritis increased the rate of CVEs. Hypertension was the strongest independent risk factor for CVEs. Results support early aggressive management of RA disease activity and co-morbidities to prevent severe complications. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Development and validation of primary human myometrial cell culture models to study pregnancy and labour.

PubMed

Mosher, Andrea A; Rainey, Kelly J; Bolstad, Seunghwa S; Lye, Stephen J; Mitchell, Bryan F; Olson, David M; Wood, Stephen L; Slater, Donna M

2013-01-01

The development of the in vitro cell culture model has greatly facilitated the ability to study gene expression and regulation within human tissues. Within the human uterus, the upper (fundal) segment and the lower segment may provide distinct functions throughout pregnancy and during labour. We have established primary cultured human myometrial cells, isolated from both upper and lower segment regions of the pregnant human uterus, and validated them for the purpose of studying human pregnancy and labour. The specific objectives of this study were to monitor the viability and characterize the expression profile using selected cellular, contractile and pregnancy associated markers in the primary cultured human myometrial cells. Labour has been described as an inflammatory process; therefore, the ability of these cells to respond to an inflammatory stimulus was also investigated. Myometrial cells isolated from paired upper segment (US) and lower segment (LS) biopsies, obtained from women undergoing Caesarean section deliveries at term prior to the onset of labour, were used to identify expression of; α smooth muscle actin, calponin, caldesmon, connexin 43, cyclo-oxygenase-2 (COX-2), oxytocin receptor, tropomyosin and vimentin, by RT-PCR and/or immunocytochemistry. Interleukin (IL)-1β was used to treat cells, subsequently expression of COX-2 mRNA and release of interleukin-8 (CXCL8), were measured. ANOVA followed by Bonferroni's multiple comparisons test was performed. We demonstrate that US and LS human myometrial cells stably express all markers examined to at least passage ten (p10). Connexin 43, COX-2 and vimentin mRNA expression were significantly higher in LS cells compared to US cells. Both cell populations respond to IL-1β, demonstrated by a robust release of CXCL8 and increased expression of COX-2 mRNA from passage one (p1) through to p10. Isolated primary myometrial cells maintain expression of smooth muscle and pregnancy-associated markers and retain their ability to respond to an inflammatory stimulus. These distinct myometrial cell models will provide a useful tool to investigate mechanisms underlying the process of human labour and the concept of functional regionalization of the pregnant uterus.

Long survival in Leigh syndrome: new cases and review of literature.

PubMed

Aulbert, Wiebke; Weigt-Usinger, Katharina; Thiels, Charlotte; Köhler, Cornelia; Vorgerd, Matthias; Schreiner, Anja; Hoffjan, Sabine; Rothoeft, Tobias; Wortmann, Saskia Brigitte; Heyer, Christoph Malte; Podskarbi, Teodor; Lücke, Thomas

2014-12-01

Leigh syndrome (MIM 25600), also known as infantile subacute necrotizing encephalomyelopathy, is a neurodegenerative disorder with characteristic bilateral symmetric lesions in basal ganglia and subcortical brain regions. It is commonly associated with systemic cytochrome c oxidase (COX) deficiency and mutations in the SURF1 gene (MIM 185620), encoding a putative assembly or maintenance factor of COX. The clinical course is dominated by neurodevelopmental regression, brain stem, and basal ganglia involvement (e.g., dystonia, apnea) with death often occurring before the age of 10 years. Herein, we present three sisters carrying a previously reported homozygous SURF1 mutation (c.868_869insT) that is predicted to result in a truncated protein with loss of function. Our patients show heterogeneous clinical findings with different distribution patterns of metabolic lesions in brain magnetic resonance imaging (MRI) as well as a Chiari malformation with hydrocephalus in one patient. However, all three siblings show an unusual long survival (12 years and>16 years). COX activity was not detectable in one patient and strongly reduced in the other two. We discuss these findings with respect to a review of the literature. A total of 15 additional patients with survival>14 years have been reported so far. Overall, no clear genotype-phenotype correlations are detectable among these patients. Georg Thieme Verlag KG Stuttgart · New York.

Sublobar resection is equivalent to lobectomy for clinical stage 1A lung cancer in solid nodules.

PubMed

Altorki, Nasser K; Yip, Rowena; Hanaoka, Takaomi; Bauer, Thomas; Aye, Ralph; Kohman, Leslie; Sheppard, Barry; Thurer, Richard; Andaz, Shahriyour; Smith, Michael; Mayfield, William; Grannis, Fred; Korst, Robert; Pass, Harvey; Straznicka, Michaela; Flores, Raja; Henschke, Claudia I

2014-02-01

A single randomized trial established lobectomy as the standard of care for the surgical treatment of early-stage non-small cell lung cancer. Recent advances in imaging/staging modalities and detection of smaller tumors have once again rekindled interest in sublobar resection for early-stage disease. The objective of this study was to compare lung cancer survival in patients with non-small cell lung cancer with a diameter of 30 mm or less with clinical stage 1 disease who underwent lobectomy or sublobar resection. We identified 347 patients diagnosed with lung cancer who underwent lobectomy (n = 294) or sublobar resection (n = 53) for non-small cell lung cancer manifesting as a solid nodule in the International Early Lung Cancer Action Program from 1993 to 2011. Differences in the distribution of the presurgical covariates between sublobar resection and lobectomy were assessed using unadjusted P values determined by logistic regression analysis. Propensity scoring was performed using the same covariates. Differences in the distribution of the same covariates between sublobar resection and lobectomy were assessed using adjusted P values determined by logistic regression analysis with adjustment for the propensity scores. Lung cancer-specific survival was determined by the Kaplan-Meier method. Cox survival regression analysis was used to compare sublobar resection with lobectomy, adjusted for the propensity scores, surgical, and pathology findings, when adjusted and stratified by propensity quintiles. Among 347 patients, 10-year Kaplan-Meier for 53 patients treated by sublobar resection compared with 294 patients treated by lobectomy was 85% (95% confidence interval, 80-91) versus 86% (confidence interval, 75-96) (P = .86). Cox survival analysis showed no significant difference between sublobar resection and lobectomy when adjusted for propensity scores or when using propensity quintiles (P = .62 and P = .79, respectively). For those with cancers 20 mm or less in diameter, the 10-year rates were 88% (95% confidence interval, 82-93) versus 84% (95% confidence interval, 73-96) (P = .45), and Cox survival analysis showed no significant difference between sublobar resection and lobectomy using either approach (P = .42 and P = .52, respectively). Sublobar resection and lobectomy have equivalent survival for patients with clinical stage IA non-small cell lung cancer in the context of computed tomography screening for lung cancer. Copyright © 2014 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

Pharmacological effects of a C-phycocyanin-based multicomponent nutraceutical in an in-vitro canine chondrocyte model of osteoarthritis

PubMed Central

Martinez, Stephanie E.; Chen, Yufei; Ho, Emmanuel A.; Martinez, Steven A.; Davies, Neal M.

2015-01-01

Multicomponent nutraceuticals are becoming increasingly popular treatments or adjunctive therapies for osteoarthritis in veterinary medicine despite lack of evidence of efficacy for many products. The objective of this study was to evaluate the anti-inflammatory and antioxidant activities of a commercially available C-phycocyanin-based nutraceutical and select constituent ingredients in an in-vitro model of canine osteoarthritis. Normal canine articular chondrocytes were used in an in-vitro model of osteoarthritis. Inflammatory conditions were induced using interleukin-1β. The nutraceutical preparation as a whole, its individual constituents, as well as carprofen were evaluated at concentrations of 0 to 250 μg/mL for reduction of the following inflammatory mediators and indicators of catabolism of the extracellular matrix: prostaglandin E2 (PGE2), tumor necrosis factor-α (TFN-α), interleukin-6 (IL-6), metalloproteinase-3 (MMP-3), nitric oxide, and sulfated glycosaminoglycans (sGAGs). Validated, commercially available assay kits were used for quantitation of inflammatory mediators. The antioxidant capacities, as well as cyclooxygenase-1 (COX-1), cyclooxygenase-2 (COX-2), and lipoxygenase (LOX) inhibitory activities of the whole nutraceutical preparation and select constituents, were also assessed using validated commercially available assay kits. The antioxidant capacity of the nutraceutical and constituents was concentration-dependent. The nutraceutical and constituents appear to display anti-inflammatory activity primarily through the inhibition of COX-2. The nutraceutical displayed similar strength to carprofen in reducing TNF-α, IL-6, MMP-3, nitric oxide, and sGAGs at select concentration ranges. The C-phycocyanin (CPC)-based nutraceutical and constituents may be able to mediate 3 primary pathogenic mechanisms of osteoarthritis: inflammation, chondral degeneration, and oxidative stress in vitro. The nutraceutical may be clinically useful in veterinary medicine and its efficacy should be further investigated in vivo. PMID:26130858

Pre-silencing of genes involved in the electron transport chain (ETC) pathway is associated with responsiveness to abatacept in rheumatoid arthritis.

PubMed

Derambure, C; Dzangue-Tchoupou, G; Berard, C; Vergne, N; Hiron, M; D'Agostino, M A; Musette, P; Vittecoq, O; Lequerré, T

2017-05-25

In the current context of personalized medicine, one of the major challenges in the management of rheumatoid arthritis (RA) is to identify biomarkers that predict drug responsiveness. From the European APPRAISE trial, our main objective was to identify a gene expression profile associated with responsiveness to abatacept (ABA) + methotrexate (MTX) and to understand the involvement of this signature in the pathophysiology of RA. Whole human genome microarrays (4 × 44 K) were performed from a first subset of 36 patients with RA. Data validation by quantitative reverse-transcription (qRT)-PCR was performed from a second independent subset of 32 patients with RA. Gene Ontology and WikiPathways database allowed us to highlight the specific biological mechanisms involved in predicting response to ABA/MTX. From the first subset of 36 patients with RA, a combination including 87 transcripts allowed almost perfect separation between responders and non-responders to ABA/MTX. Next, the second subset of patients 32 with RA allowed validation by qRT-PCR of a minimal signature with only four genes. This latter signature categorized 81% of patients with RA with 75% sensitivity, 85% specificity and 85% negative predictive value. This combination showed a significant enrichment of genes involved in electron transport chain (ETC) pathways. Seven transcripts from ETC pathways (NDUFA6, NDUFA4, UQCRQ, ATP5J, COX7A2, COX7B, COX6A1) were significantly downregulated in responders versus non-responders to ABA/MTX. Moreover, dysregulation of these genes was independent of inflammation and was specific to ABA response. Pre-silencing of ETC genes is associated with future response to ABA/MTX and might be a crucial key to susceptibility to ABA response.

[Value of the albumin to globulin ratio in predicting severity and prognosis in myasthenia gravis patients].

PubMed

Yang, D H; Su, Z Q; Chen, Y; Chen, Z B; Ding, Z N; Weng, Y Y; Li, J; Li, X; Tong, Q L; Han, Y X; Zhang, X

2016-03-08

To assess the predictive value of the albumin to globulin ratio (AGR) in evaluation of disease severity and prognosis in myasthenia gravis patients. A total of 135 myasthenia gravis (MG) patients were enrolled between February 2009 and March 2015. The AGR was detected on the first day of hospitalization and ranked from lowest to highest, and the patients were divided into three equal tertiles according to the AGR values, which were T1 (AGR <1.34), T2 (1.34≤AGR≤1.53) and T3 (AGR>1.53). The Kaplan-Meier curve was used to evaluate the prognostic value of AGR. Cox model analysis was used to evaluate the relevant factors. Multivariate Logistic regression analysis was used to find the predictors of myasthenia crisis during hospitalization. The median length of hospital stay for each tertile was: for the T1 21 days (15-35.5), T2 18 days (14-27.5), and T3 16 days (12-22.5) (P<0.01), and Kaplan-Meier curves showed significant difference among the three groups. In the univariate model, serum albumin, creatinine, AGR and MGFA clinical classification were related to prognosis of myasthenia gravis. At the multivariate Cox regression analysis, the AGR (P<0.001) and MGFA clinical classification (P<0.001) were independent predictive factors of disease severity and prognosis in myasthenia gravis patients. Respectively, the hazard ratio (HR) were 4.655 (95% CI: 2.355-9.202) and 0.596 (95% CI: 0.492-0.723). Multivariate Logistic regression analysis showed the AGR (P<0.001) and MGFA clinical classification were related to myasthenia crisis. The AGR may represent a simple, potentially useful predictive biomarker for evaluating the disease severity and prognosis of patients with myasthenia gravis.

Asthma exacerbations in children immediately following stressful life events: a Cox's hierarchical regression.

PubMed

Sandberg, S; Järvenpää, S; Penttinen, A; Paton, J Y; McCann, D C

2004-12-01

A recent prospective study of children with asthma employing a within subject, over time analysis using dynamic logistic regression showed that severely negative life events significantly increased the risk of an acute exacerbation during the subsequent 6 week period. The timing of the maximum risk depended on the degree of chronic psychosocial stress also present. A hierarchical Cox regression analysis was undertaken to examine whether there were any immediate effects of negative life events in children without a background of high chronic stress. Sixty children with verified chronic asthma were followed prospectively for 18 months with continuous monitoring of asthma by daily symptom diaries and peak flow measurements, accompanied by repeated interview assessments of life events. The key outcome measures were asthma exacerbations and severely negative life events. An immediate effect evident within the first 2 days following a severely negative life event increased the risk of a new asthma attack by a factor of 4.69, 95% confidence interval 2.33 to 9.44 (p<0.001) [corrected] In the period 3-10 days after a severe event there was no increased risk of an asthma attack (p = 0.5). In addition to the immediate effect, an increased risk of 1.81 (95% confidence interval 1.24 to 2.65) [corrected] was found 5-7 weeks after a severe event (p = 0.002). This is consistent with earlier findings. There was a statistically significant variation due to unobserved factors in the incidence of asthma attacks between the children. The use of statistical methods capable of investigating short time lags showed that stressful life events significantly increase the risk of a new asthma attack immediately after the event; a more delayed increase in risk was also evident 5-7 weeks later.

Updating prognosis of cirrhosis by Cox's regression model using Child-Pugh score and aminopyrine breath test as time-dependent covariates.

PubMed

Merkel, C; Morabito, A; Sacerdoti, D; Bolognesi, M; Angeli, P; Gatta, A

1998-06-01

The determination of aminopyrine breath test on entry into the study was recently shown to improve the accuracy of prediction of death based on the Child-Pugh classification, but the possible usefulness of serial determinations of both parameters has not been assessed. In the present study, we aimed at evaluating whether serial determinations of aminopyrine breath test and Child-Pugh score improve prognostic accuracy in patients with cirrhosis, compared with determinations obtained only on admission. In 74 patients with liver cirrhosis aminopyrine breath test and Child-Pugh score were obtained upon entry into the study. Patients were followed with sequential aminopyrine breath tests and assessments of the Child-Pugh score every 4-6 months. A total number of 232 determinations were obtained. During follow-up 45 patients died, on average after 12 months of follow-up. Child-Pugh score improved in the beginning of follow-up, and then remained fairly constant; aminopyrine breath test showed no improvement in the beginning of follow-up, but rather a slowly progressive decline. In patients who died, both the Child-Pugh score and the metabolism of aminopyrine were significantly more impaired in the last year preceding death (p < 0.05). Applying Cox's regression model with time-dependent covariates, Child-Pugh score and aminopyrine breath test were independent significant predictors of survival. The model with time-dependent covariates explained the observed survival much better than the model with time-fixed covariates (chi-sq. explained by regression = 31.45 vs 11.97; d.f. = 2; p = 0.0000001 vs 0.003). These data suggest that serial determinations of Child-Pugh score and aminopyrine breath test can be used to efficiently update prognosis of cirrhosis.

Predictors of discontinuation of antipsychotic medication and subsequent outcomes in the European First Episode Schizophrenia Trial (EUFEST).

PubMed

Landolt, Karin; Rössler, Wulf; Ajdacic-Gross, Vladeta; Derks, Eske M; Libiger, Jan; Kahn, René S; Fleischhacker, W Wolfgang

2016-04-01

This study had two aims: to describe patients suffering from first-episode schizophrenia who had stopped taking any antipsychotic medication, and to gain information on the predictors of successful discontinuation. We investigated data from the European First Episode Schizophrenia Trial (EUFEST). From the 325 patients included, 15.7% discontinued all antipsychotic medication. In a first analysis, clinical and sociodemographical predictors of discontinuing any antipsychotic medication were identified, using Cox regression. In the second analysis, logistic regression was used to determine variables associated with those patients who had stopped taking antipsychotic medication and had a favourable outcome, i.e., successful discontinuation. A good outcome was defined as a) having had no relapse within the whole observation period (80.6%), and b) having had no relapse and symptomatic remission at 12-month-follow-up (37.2%). Cox regression revealed that a higher proportion of patients from Western European countries and Israel stopped antipsychotic medication than from Central and Eastern European countries, that relapse was associated with discontinuation, and that discontinuers had lower compliance and higher quality of life. Predictors of successful discontinuation differed with the outcome definition used. Using definition b), successful discontinuers had a better baseline prognosis and better baseline social integration. Using definition a), successful discontinuers more often were from Western European countries. Region and clinical factors were associated with discontinuation. Prognosis and social integration played an important role in predicting successful discontinuation. As this study had several limitations, for example the observational design regarding discontinuation, further studies are needed to identify predictors of successful discontinuation. Copyright © 2016 Elsevier B.V. All rights reserved.

A long-recommended but seldom-used method of analysis for fall injuries found a unique pattern of risk factors in the youngest-old.

PubMed

Legrand, Helen; Pihlsgård, Mats; Nordell, Eva; Elmståhl, Sölve

2015-08-01

Few studies on fall risk factors use long-recommended methods for analysis of recurrent events. Previous falls are the biggest risk factor for future falls, but few fall studies focus on the youngest-old. This study's objective was to apply Cox regression for recurrent events to identify factors associated with injurious falls in the youngest-old. Participants were community-dwelling residents of southern Sweden (n = 1,133), aged 59-67 at baseline (median 61.2), from the youngest cohorts of the larger Good Aging in Skåne (GÅS) study. Exposure variable data were collected from baseline study visits and medical records. Injurious falls, defined as emergency, inpatient, or specialist visits associated with ICD-10 fall codes during the follow-up period (2001-2011), were gathered from national and regional registries. Analysis was conducted using time to event Cox Regression for recurrent events. A majority (77.1 %) of injurious falls caused serious injuries such as fractures and open wounds. Exposure to nervous system medications [hazard ratio (HR) 1.40, 95 % confidence interval (CI) 1.03-1.89], central nervous system disease (HR 1.79, CI 1.18-2.70), and previous injurious fall(s) (HR 2.00, CI 1.50-2.68) were associated with increased hazard of injurious fall. Regression for recurrent events is feasible with typical falls' study data. The association of certain exposures with increased hazard of injurious falls begins earlier than previously studied. Different patterns of risk factors by age can provide insight into the progression of frailty. Tailored fall prevention screening and intervention may be of value in populations younger than those traditionally screened.

Predictors of pharmacological treatment outcomes with atomoxetine or methylphenidate in patients with attention-deficit/hyperactivity disorder from China, Egypt, Lebanon, Russian Federation, Taiwan, and United Arab Emirates.

PubMed

Treuer, T; Feng, Q; Desaiah, D; Altin, M; Wu, S; El-Shafei, A; Serebryakova, E; Gado, M; Faries, D

2014-09-01

The reduced availability of data from non-Western countries limits our ability to understand attention-deficit/hyperactivity disorder (ADHD) treatment outcomes, specifically, adherence and persistence of ADHD in children and adolescents. This analysis assessed predictors of treatment outcomes in a non-Western cohort of patients with ADHD treated with atomoxetine or methylphenidate. Data from a 12-month, prospective, observational study in outpatients aged 6-17 years treated with atomoxetine (N = 234) or methylphenidate (N = 221) were analysed post hoc to determine potential predictors of treatment outcomes. Participating countries included the Russian Federation, China, Taiwan, Egypt, United Arab Emirates and Lebanon. Factors associated with remission were analysed with stepwise multiple logistic regression and classification and regression trees (CART). Cox proportional hazards models with propensity score adjustment assessed differences in atomoxetine persistence among initial-dose cohorts. In patients treated with atomoxetine who had available dosing information (N = 134), Cox proportional hazards revealed lower (< 0.5 mg/kg) initial dose was significantly associated with shorter medication persistence (p < 0.01). multiple logistic regression analysis revealed greater rates of remission for atomoxetine-treated patients were associated with age (older), country (United Arab Emirates) and gender (female) (all p < 0.05). CART analysis confirmed older age and lack of specific phobias were associated with greater remission rates. For methylphenidate, greater baseline weight (highly correlated with the age factor found for atomoxetine) and prior atomoxetine use were associated with greater remission rates. These findings may help clinicians assess factors upon initiation of ADHD treatment to improve course prediction, proper dosing and treatment adherence and persistence. Observational study, therefore no registration. © 2014 John Wiley & Sons Ltd.

Cell cycle-related genes as modifiers of age of onset of colorectal cancer in Lynch syndrome: a large-scale study in non-Hispanic white patients.

PubMed

Chen, Jinyun; Pande, Mala; Huang, Yu-Jing; Wei, Chongjuan; Amos, Christopher I; Talseth-Palmer, Bente A; Meldrum, Cliff J; Chen, Wei V; Gorlov, Ivan P; Lynch, Patrick M; Scott, Rodney J; Frazier, Marsha L

2013-02-01

Heterogeneity in age of onset of colorectal cancer in individuals with mutations in DNA mismatch repair genes (Lynch syndrome) suggests the influence of other lifestyle and genetic modifiers. We hypothesized that genes regulating the cell cycle influence the observed heterogeneity as cell cycle-related genes respond to DNA damage by arresting the cell cycle to provide time for repair and induce transcription of genes that facilitate repair. We examined the association of 1456 single nucleotide polymorphisms (SNPs) in 128 cell cycle-related genes and 31 DNA repair-related genes in 485 non-Hispanic white participants with Lynch syndrome to determine whether there are SNPs associated with age of onset of colorectal cancer. Genotyping was performed on an Illumina GoldenGate platform, and data were analyzed using Kaplan-Meier survival analysis, Cox regression analysis and classification and regression tree (CART) methods. Ten SNPs were independently significant in a multivariable Cox proportional hazards regression model after correcting for multiple comparisons (P < 5 × 10(-4)). Furthermore, risk modeling using CART analysis defined combinations of genotypes for these SNPs with which subjects could be classified into low-risk, moderate-risk and high-risk groups that had median ages of colorectal cancer onset of 63, 50 and 42 years, respectively. The age-associated risk of colorectal cancer in the high-risk group was more than four times the risk in the low-risk group (hazard ratio = 4.67, 95% CI = 3.16-6.92). The additional genetic markers identified may help in refining risk groups for more tailored screening and follow-up of non-Hispanic white patients with Lynch syndrome.

Cell cycle–related genes as modifiers of age of onset of colorectal cancer in Lynch syndrome: a large-scale study in non-Hispanic white patients

PubMed Central

Chen, Jinyun; Pande, Mala

2013-01-01

Heterogeneity in age of onset of colorectal cancer in individuals with mutations in DNA mismatch repair genes (Lynch syndrome) suggests the influence of other lifestyle and genetic modifiers. We hypothesized that genes regulating the cell cycle influence the observed heterogeneity as cell cycle–related genes respond to DNA damage by arresting the cell cycle to provide time for repair and induce transcription of genes that facilitate repair. We examined the association of 1456 single nucleotide polymorphisms (SNPs) in 128 cell cycle–related genes and 31 DNA repair–related genes in 485 non-Hispanic white participants with Lynch syndrome to determine whether there are SNPs associated with age of onset of colorectal cancer. Genotyping was performed on an Illumina GoldenGate platform, and data were analyzed using Kaplan–Meier survival analysis, Cox regression analysis and classification and regression tree (CART) methods. Ten SNPs were independently significant in a multivariable Cox proportional hazards regression model after correcting for multiple comparisons (P < 5×10–4). Furthermore, risk modeling using CART analysis defined combinations of genotypes for these SNPs with which subjects could be classified into low-risk, moderate-risk and high-risk groups that had median ages of colorectal cancer onset of 63, 50 and 42 years, respectively. The age-associated risk of colorectal cancer in the high-risk group was more than four times the risk in the low-risk group (hazard ratio = 4.67, 95% CI = 3.16–6.92). The additional genetic markers identified may help in refining risk groups for more tailored screening and follow-up of non-Hispanic white patients with Lynch syndrome. PMID:23125224

Predictors of unsuccessful outcome in cemented femoral revisions using bone impaction grafting; Cox regression analysis of 208 cases.

PubMed

Te Stroet, Martijn A J; Rijnen, Wim H C; Gardeniers, Jean W M; Schreurs, B Willem; Hannink, Gerjon

2016-09-29

Despite improvements in the technique of femoral impaction bone grafting, reconstruction failures still can occur. Therefore, the aim of our study was to determine risk factors for the endpoint re-revision for any reason. We used prospectively collected demographic, clinical and surgical data of all 202 patients who underwent 208 femoral revisions using the X-change Femoral Revision System (Stryker-Howmedica), fresh-frozen morcellised allograft and a cemented polished Exeter stem in our department from 1991 to 2007. Univariable and multivariable Cox regression analyses were performed to identify potential factors associated with re-revision. The mean follow-up was 10.6 (5-21) years. The cumulative re-revision rate was 6.3% (13/208). After univariable selection, sex, age, body mass index (BMI), American Association of Anesthesiologists (ASA) classification, type of removed femoral component, and mesh used for reconstruction were included in multivariable regression analysis.In the multivariable analysis, BMI was the only factor that was significantly associated with the risk of re-revision after bone impaction grafting (BMI ≥30 vs. BMI <30, HR = 6.54 [95% CI 1.89-22.65]; p = 0.003). BMI was the only factor associated with the risk of re-revision for any reason. Besides BMI also other factors, such as Endoklinik score and the type of removed femoral component, can provide guidance in the process of preclinical decision making. With the knowledge obtained from this study, preoperative patient selection, informed consent, and treatment protocols can be better adjusted to the individual patient who needs to undergo a femoral revision with impaction bone grafting.

Hospital of diagnosis and probability of having surgical treatment for resectable gastric cancer.

PubMed

van Putten, M; Verhoeven, R H A; van Sandick, J W; Plukker, J T M; Lemmens, V E P P; Wijnhoven, B P L; Nieuwenhuijzen, G A P

2016-02-01

Gastric cancer surgery is increasingly being centralized in the Netherlands, whereas the diagnosis is often made in hospitals where gastric cancer surgery is not performed. The aim of this study was to assess whether hospital of diagnosis affects the probability of undergoing surgery and its impact on overall survival. All patients with potentially curable gastric cancer according to stage (cT1/1b-4a, cN0-2, cM0) diagnosed between 2005 and 2013 were selected from The Netherlands Cancer Registry. Multilevel logistic regression was used to examine the probability of undergoing surgery according to hospital of diagnosis. The effect of variation in probability of undergoing surgery among hospitals of diagnosis on overall survival during the intervals 2005-2009 and 2010-2013 was examined by using Cox regression analysis. A total of 5620 patients with potentially curable gastric cancer, diagnosed in 91 hospitals, were included. The proportion of patients who underwent surgery ranged from 53.1 to 83.9 per cent according to hospital of diagnosis (P < 0.001); after multivariable adjustment for patient and tumour characteristics it ranged from 57.0 to 78.2 per cent (P < 0.001). Multivariable Cox regression showed that patients diagnosed between 2010 and 2013 in hospitals with a low probability of patients undergoing curative treatment had worse overall survival (hazard ratio 1.21; P < 0.001). The large variation in probability of receiving surgery for gastric cancer between hospitals of diagnosis and its impact on overall survival indicates that gastric cancer decision-making is suboptimal. © 2015 BJS Society Ltd Published by John Wiley & Sons Ltd.

Gastric Bypass Surgery Produces a Durable Reduction in Cardiovascular Disease Risk Factors and Reduces the Long-Term Risks of Congestive Heart Failure.

PubMed

Benotti, Peter N; Wood, G Craig; Carey, David J; Mehra, Vishal C; Mirshahi, Tooraj; Lent, Michelle R; Petrick, Anthony T; Still, Christopher; Gerhard, Glenn S; Hirsch, Annemarie G

2017-05-23

Obesity and its association with reduced life expectancy are well established, with cardiovascular disease as one of the major causes of fatality. Metabolic surgery is a powerful intervention for severe obesity, resulting in improvement in comorbid diseases and in cardiovascular risk factors. This study investigates the relationship between metabolic surgery and long-term cardiovascular events. A cohort of Roux-en-Y gastric bypass surgery (RYGB) patients was tightly matched by age, body mass index, sex, Framingham Risk Score, smoking history, use of antihypertension medication, diabetes mellitus status, and calendar year with a concurrent cohort of nonoperated control patients. The primary study end points of major cardiovascular events (myocardial infarction, stroke, and congestive heart failure) were evaluated using Cox regression. Secondary end points of longitudinal cardiovascular risk factors were evaluated using repeated-measures regression. The RYGB and matched controls (N=1724 in each cohort) were followed for up to 12 years after surgery (overall median of 6.3 years). Kaplan-Meier analysis revealed a statistically significant reduction in incident major composite cardiovascular events ( P =0.017) and congestive heart failure (0.0077) for the RYGB cohort. Adjusted Cox regression models confirmed the reductions in severe composite cardiovascular events in the RYGB cohort (hazard ratio=0.58, 95% CI=0.42-0.82). Improvements of cardiovascular risk factors (eg, 10-year cardiovascular risk score, total cholesterol, high-density lipoprotein, systolic blood pressure, and diabetes mellitus) were observed within the RYGB cohort after surgery. Gastric bypass is associated with a reduced risk of major cardiovascular events and the development of congestive heart failure. © 2017 The Authors and Geisinger Clinic. Published on behalf of the American Heart Association, Inc., by Wiley.