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.

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

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

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.

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.

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.

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.

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.

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.

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…

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.

[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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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

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.

[A SAS marco program for batch processing of univariate Cox regression analysis for great database].

PubMed

Yang, Rendong; Xiong, Jie; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

2015-02-01

To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

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.

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.

[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.

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.

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.

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.

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.

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.

Development of a five-year mortality model in systemic sclerosis patients by different analytical approaches.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; Cappiello, Francesca; Chawla, Nitesh V; Vonk, Madelon C; Carreira, Patricia E; Allanore, Yannick; Popa-Diaconu, D A; Cossu, Marta; Bertolotti, Francesca; Ferraccioli, Gianfranco; Mazzone, Antonino; Scorza, Raffaella

2010-01-01

Systemic sclerosis (SSc) is a multiorgan disease with high mortality rates. Several clinical features have been associated with poor survival in different populations of SSc patients, but no clear and reproducible prognostic model to assess individual survival prediction in scleroderma patients has ever been developed. We used Cox regression and three data mining-based classifiers (Naïve Bayes Classifier [NBC], Random Forests [RND-F] and logistic regression [Log-Reg]) to develop a robust and reproducible 5-year prognostic model. All the models were built and internally validated by means of 5-fold cross-validation on a population of 558 Italian SSc patients. Their predictive ability and capability of generalisation was then tested on an independent population of 356 patients recruited from 5 external centres and finally compared to the predictions made by two SSc domain experts on the same population. The NBC outperformed the Cox-based classifier and the other data mining algorithms after internal cross-validation (area under receiving operator characteristic curve, AUROC: NBC=0.759; RND-F=0.736; Log-Reg=0.754 and Cox= 0.724). The NBC had also a remarkable and better trade-off between sensitivity and specificity (e.g. Balanced accuracy, BA) than the Cox-based classifier, when tested on an independent population of SSc patients (BA: NBC=0.769, Cox=0.622). The NBC was also superior to domain experts in predicting 5-year survival in this population (AUROC=0.829 vs. AUROC=0.788 and BA=0.769 vs. BA=0.67). We provide a model to make consistent 5-year prognostic predictions in SSc patients. Its internal validity, as well as capability of generalisation and reduced uncertainty compared to human experts support its use at bedside. Available at: http://www.nd.edu/~nchawla/survival.xls.

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.

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

PubMed

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

2017-12-01

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

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.

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.

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

PubMed

Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

2011-12-01

This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

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.

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.

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.

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.

External validation of a Cox prognostic model: principles and methods

PubMed Central

2013-01-01

Background A prognostic model should not enter clinical practice unless it has been demonstrated that it performs a useful role. External validation denotes evaluation of model performance in a sample independent of that used to develop the model. Unlike for logistic regression models, external validation of Cox models is sparsely treated in the literature. Successful validation of a model means achieving satisfactory discrimination and calibration (prediction accuracy) in the validation sample. Validating Cox models is not straightforward because event probabilities are estimated relative to an unspecified baseline function. Methods We describe statistical approaches to external validation of a published Cox model according to the level of published information, specifically (1) the prognostic index only, (2) the prognostic index together with Kaplan-Meier curves for risk groups, and (3) the first two plus the baseline survival curve (the estimated survival function at the mean prognostic index across the sample). The most challenging task, requiring level 3 information, is assessing calibration, for which we suggest a method of approximating the baseline survival function. Results We apply the methods to two comparable datasets in primary breast cancer, treating one as derivation and the other as validation sample. Results are presented for discrimination and calibration. We demonstrate plots of survival probabilities that can assist model evaluation. Conclusions Our validation methods are applicable to a wide range of prognostic studies and provide researchers with a toolkit for external validation of a published Cox model. PMID:23496923

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

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model.

PubMed

Austin, Peter C

2018-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model

PubMed Central

Austin, Peter C.

2017-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest. PMID:29321694

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.

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.

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.

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.

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.

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.

Validation of a heteroscedastic hazards regression model.

PubMed

Wu, Hong-Dar Isaac; Hsieh, Fushing; Chen, Chen-Hsin

2002-03-01

A Cox-type regression model accommodating heteroscedasticity, with a power factor of the baseline cumulative hazard, is investigated for analyzing data with crossing hazards behavior. Since the approach of partial likelihood cannot eliminate the baseline hazard, an overidentified estimating equation (OEE) approach is introduced in the estimation procedure. It by-product, a model checking statistic, is presented to test for the overall adequacy of the heteroscedastic model. Further, under the heteroscedastic model setting, we propose two statistics to test the proportional hazards assumption. Implementation of this model is illustrated in a data analysis of a cancer clinical trial.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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...

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…

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.

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.

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.

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.

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.

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.

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

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…

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.

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.

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.

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.

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.

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.

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.

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.

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

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

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

Nomogram Prediction of Overall Survival After Curative Irradiation for Uterine Cervical Cancer

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

Seo, YoungSeok; Yoo, Seong Yul; Kim, Mi-Sook

Purpose: The purpose of this study was to develop a nomogram capable of predicting the probability of 5-year survival after radical radiotherapy (RT) without chemotherapy for uterine cervical cancer. Methods and Materials: We retrospectively analyzed 549 patients that underwent radical RT for uterine cervical cancer between March 1994 and April 2002 at our institution. Multivariate analysis using Cox proportional hazards regression was performed and this Cox model was used as the basis for the devised nomogram. The model was internally validated for discrimination and calibration by bootstrap resampling. Results: By multivariate regression analysis, the model showed that age, hemoglobin levelmore » before RT, Federation Internationale de Gynecologie Obstetrique (FIGO) stage, maximal tumor diameter, lymph node status, and RT dose at Point A significantly predicted overall survival. The survival prediction model demonstrated good calibration and discrimination. The bootstrap-corrected concordance index was 0.67. The predictive ability of the nomogram proved to be superior to FIGO stage (p = 0.01). Conclusions: The devised nomogram offers a significantly better level of discrimination than the FIGO staging system. In particular, it improves predictions of survival probability and could be useful for counseling patients, choosing treatment modalities and schedules, and designing clinical trials. However, before this nomogram is used clinically, it should be externally validated.« less

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.

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.

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.

Can We Predict Individual Combined Benefit and Harm of Therapy? Warfarin Therapy for Atrial Fibrillation as a Test Case

PubMed Central

Li, Guowei; Thabane, Lehana; Delate, Thomas; Witt, Daniel M.; Levine, Mitchell A. H.; Cheng, Ji; Holbrook, Anne

2016-01-01

Objectives To construct and validate a prediction model for individual combined benefit and harm outcomes (stroke with no major bleeding, major bleeding with no stroke, neither event, or both) in patients with atrial fibrillation (AF) with and without warfarin therapy. Methods Using the Kaiser Permanente Colorado databases, we included patients newly diagnosed with AF between January 1, 2005 and December 31, 2012 for model construction and validation. The primary outcome was a prediction model of composite of stroke or major bleeding using polytomous logistic regression (PLR) modelling. The secondary outcome was a prediction model of all-cause mortality using the Cox regression modelling. Results We included 9074 patients with 4537 and 4537 warfarin users and non-users, respectively. In the derivation cohort (n = 4632), there were 136 strokes (2.94%), 280 major bleedings (6.04%) and 1194 deaths (25.78%) occurred. In the prediction models, warfarin use was not significantly associated with risk of stroke, but increased the risk of major bleeding and decreased the risk of death. Both the PLR and Cox models were robust, internally and externally validated, and with acceptable model performances. Conclusions In this study, we introduce a new methodology for predicting individual combined benefit and harm outcomes associated with warfarin therapy for patients with AF. Should this approach be validated in other patient populations, it has potential advantages over existing risk stratification approaches as a patient-physician aid for shared decision-making PMID:27513986

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.

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.

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.

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

PubMed

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

2017-04-01

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

Change of plant phenophases explained by survival modeling

NASA Astrophysics Data System (ADS)

Templ, Barbara; Fleck, Stefan; Templ, Matthias

2017-05-01

It is known from many studies that plant species show a delay in the timing of flowering events with an increase in latitude and altitude, and an advance with an increase in temperature. Furthermore, in many locations and for many species, flowering dates have advanced over the long-term. New insights using survival modeling are given based on data collected (1970-2010) along a 3000-km long transect from northern to eastern central Europe. We could clearly observe that in the case of dandelion ( Taraxacum officinale) the risk of flowering time, in other words the probability that flowering occurs, is higher for an earlier day of year in later decades. Our approach assume that temperature has greater influence than precipitation on the timing of flowering. Evaluation of the predictive power of tested models suggests that Cox models may be used in plant phenological research. The applied Cox model provides improved predictions of flowering dates compared to traditional regression methods and gives further insights into drivers of phenological events.

[Establishment of the prediction model for ischemic cardiovascular disease of elderly male population under current health care program].

PubMed

Chen, Jin-hong; Wu, Hai-yun; He, Kun-lun; He, Yao; Qin, Yin-he

2010-10-01

To establish and verify the prediction model for ischemic cardiovascular disease (ICVD) among the elderly population who were under the current health care programs. Statistical analysis on data from physical examination, hospitalization of the past years, from questionnaire and telephone interview was carried out in May, 2003. Data was from a hospital which implementing a health care program. Baseline population with a proportion of 4:1 was randomly selected to generate both module group and verification group. Baseline data was induced to make the verification group into regression model of module group and to generate the predictive value. Distinguished ability with area under ROC curve and the predictive veracity were verified through comparing the predictive incidence rate and actual incidence rate of every deciles group by Hosmer-Lemeshow test. Predictive veracity of the prediction model at population level was verified through comparing the predictive 6-year incidence rates of ICVD with actual 6-year accumulative incidence rates of ICVD with error rate calculated. The samples included 2271 males over the age of 65 with 1817 people for modeling population and 454 for verified population. All of the samples were stratified into two layers to establish hierarchical Cox proportional hazard regression model, including one advanced age group (greater than or equal to 75 years old), and another elderly group (less than 75 years old). Data from the statically analysis showed that the risk factors in aged group were age, systolic blood pressure, serum creatinine level, fasting blood glucose level, while protective factor was high density lipoprotein;in advanced age group, the risk factors were body weight index, systolic blood pressure, serum total cholesterol level, serum creatinine level, fasting blood glucose level, while protective factor was HDL-C. The area under the ROC curve (AUC) and 95%CI were 0.723 and 0.687 - 0.759 respectively. Discriminating power was good. All individual predictive ICVD cumulative incidence and actual incidence were analyzed using Hosmer-Lemeshow test, χ(2) = 1.43, P = 0.786, showing that the predictive veracity was good. The stratified Cox Hazards Regression model was used to establish prediction model of the aged male population under a certain health care program. The common prediction factor of the two age groups were: systolic blood pressure, serum creatinine level, fasting blood glucose level and HDL-C. The area under the ROC curve of the verification group was 0.723, showing that the distinguished ability was good and the predict ability at the individual level and at the group level were also satisfactory. It was feasible to using Cox Proportional Hazards Regression Model for predicting the population groups.

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.

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.

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.

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…

A Case for Transforming the Criterion of a Predictive Validity Study

ERIC Educational Resources Information Center

Patterson, Brian F.; Kobrin, Jennifer L.

2011-01-01

This study presents a case for applying a transformation (Box and Cox, 1964) of the criterion used in predictive validity studies. The goals of the transformation were to better meet the assumptions of the linear regression model and to reduce the residual variance of fitted (i.e., predicted) values. Using data for the 2008 cohort of first-time,…

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.

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

Predicting spatio-temporal failure in large scale observational and micro scale experimental systems

NASA Astrophysics Data System (ADS)

de las Heras, Alejandro; Hu, Yong

2006-10-01

Forecasting has become an essential part of modern thought, but the practical limitations still are manifold. We addressed future rates of change by comparing models that take into account time, and models that focus more on space. Cox regression confirmed that linear change can be safely assumed in the short-term. Spatially explicit Poisson regression, provided a ceiling value for the number of deforestation spots. With several observed and estimated rates, it was decided to forecast using the more robust assumptions. A Markov-chain cellular automaton thus projected 5-year deforestation in the Amazonian Arc of Deforestation, showing that even a stable rate of change would largely deplete the forest area. More generally, resolution and implementation of the existing models could explain many of the modelling difficulties still affecting forecasting.

A Clinical Decision Support System for Breast Cancer Patients

NASA Astrophysics Data System (ADS)

Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

Application of an Individual-Based Transmission Hazard Model for Estimation of Influenza Vaccine Effectiveness in a Household Cohort.

PubMed

Petrie, Joshua G; Eisenberg, Marisa C; Ng, Sophia; Malosh, Ryan E; Lee, Kyu Han; Ohmit, Suzanne E; Monto, Arnold S

2017-12-15

Household cohort studies are an important design for the study of respiratory virus transmission. Inferences from these studies can be improved through the use of mechanistic models to account for household structure and risk as an alternative to traditional regression models. We adapted a previously described individual-based transmission hazard (TH) model and assessed its utility for analyzing data from a household cohort maintained in part for study of influenza vaccine effectiveness (VE). Households with ≥4 individuals, including ≥2 children <18 years of age, were enrolled and followed during the 2010-2011 influenza season. VE was estimated in both TH and Cox proportional hazards (PH) models. For each individual, TH models estimated hazards of infection from the community and each infected household contact. Influenza A(H3N2) infection was laboratory-confirmed in 58 (4%) subjects. VE estimates from both models were similarly low overall (Cox PH: 20%, 95% confidence interval: -57, 59; TH: 27%, 95% credible interval: -23, 58) and highest for children <9 years of age (Cox PH: 40%, 95% confidence interval: -49, 76; TH: 52%, 95% credible interval: 7, 75). VE estimates were robust to model choice, although the ability of the TH model to accurately describe transmission of influenza presents continued opportunity for analyses. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Determinants of U.S. Prescription Drug Utilization using County Level Data.

PubMed

Nianogo, Thierry; Okunade, Albert; Fofana, Demba; Chen, Weiwei

2016-05-01

Prescription drugs are the third largest component of U.S. healthcare expenditures. The 2006 Medicare Part D and the 2010 Affordable Care Act are catalysts for further growths in utilization becuase of insurance expansion effects. This research investigating the determinants of prescription drug utilization is timely, methodologically novel, and policy relevant. Differences in population health status, access to care, socioeconomics, demographics, and variations in per capita number of scripts filled at retail pharmacies across the U.S.A. justify fitting separate econometric models to county data of the states partitioned into low, medium, and high prescription drug users. Given the skewed distribution of per capita number of filled prescriptions (response variable), we fit the variance stabilizing Box-Cox power transformation regression models to 2011 county level data for investigating the correlates of prescription drug utilization separately for low, medium, and high utilization states. Maximum likelihood regression parameter estimates, including the optimal Box-Cox λ power transformations, differ across high (λ = 0.214), medium (λ = 0.942), and low (λ = 0.302) prescription drug utilization models. The estimated income elasticities of -0.634, 0.031, and -0.532 in high, medium, and low utilization models suggest that the economic behavior of prescriptions is not invariant across different utilization levels. Copyright © 2015 John Wiley & Sons, Ltd.

Recurrence risk model for esophageal cancer after radical surgery.

PubMed

Lu, Jincheng; Tao, Hua; Song, Dan; Chen, Cheng

2013-10-01

The aim of the present study was to construct a risk assessment model which was tested by disease-free survival (DFS) of esophageal cancer after radical surgery. A total of 164 consecutive esophageal cancer patients who had undergone radical surgery between January 2005 and December 2006 were retrospectively analyzed. The cutpoint of value at risk (VaR) was inferred by stem-and-leaf plot, as well as by independent-samples t-test for recurrence-free time, further confirmed by crosstab chi-square test, univariate analysis and Cox regression analysis for DFS. The cutpoint of VaR was 0.3 on the basis of our model. The rate of recurrence was 30.3% (30/99) and 52.3% (34/65) in VaR <0.3 and VaR ≥0.3 (chi-square test, (χ) (2) =7.984, P=0.005), respectively. The 1-, 3-, and 5-year DFS of esophageal cancer after radical surgery was 70.4%, 48.7%, and 45.3%, respectively in VaR ≥0.3, whereas 91.5%, 75.8%, and 67.3%, respectively in VaR <0.3 (Log-rank test, (χ) (2) =9.59, P=0.0020), and further confirmed by Cox regression analysis [hazard ratio =2.10, 95% confidence interval (CI): 1.2649-3.4751; P=0.0041]. The model could be applied for integrated assessment of recurrence risk after radical surgery for esophageal cancer.

Recurrence risk model for esophageal cancer after radical surgery

PubMed Central

Tao, Hua; Song, Dan; Chen, Cheng

2013-01-01

Objective The aim of the present study was to construct a risk assessment model which was tested by disease-free survival (DFS) of esophageal cancer after radical surgery. Methods A total of 164 consecutive esophageal cancer patients who had undergone radical surgery between January 2005 and December 2006 were retrospectively analyzed. The cutpoint of value at risk (VaR) was inferred by stem-and-leaf plot, as well as by independent-samples t-test for recurrence-free time, further confirmed by crosstab chi-square test, univariate analysis and Cox regression analysis for DFS. Results The cutpoint of VaR was 0.3 on the basis of our model. The rate of recurrence was 30.3% (30/99) and 52.3% (34/65) in VaR <0.3 and VaR ≥0.3 (chi-square test, χ2 =7.984, P=0.005), respectively. The 1-, 3-, and 5-year DFS of esophageal cancer after radical surgery was 70.4%, 48.7%, and 45.3%, respectively in VaR ≥0.3, whereas 91.5%, 75.8%, and 67.3%, respectively in VaR <0.3 (Log-rank test, χ2 =9.59, P=0.0020), and further confirmed by Cox regression analysis [hazard ratio =2.10, 95% confidence interval (CI): 1.2649-3.4751; P=0.0041]. Conclusions The model could be applied for integrated assessment of recurrence risk after radical surgery for esophageal cancer. PMID:24255579

Replica analysis of overfitting in regression models for time-to-event data

NASA Astrophysics Data System (ADS)

Coolen, A. C. C.; Barrett, J. E.; Paga, P.; Perez-Vicente, C. J.

2017-09-01

Overfitting, which happens when the number of parameters in a model is too large compared to the number of data points available for determining these parameters, is a serious and growing problem in survival analysis. While modern medicine presents us with data of unprecedented dimensionality, these data cannot yet be used effectively for clinical outcome prediction. Standard error measures in maximum likelihood regression, such as p-values and z-scores, are blind to overfitting, and even for Cox’s proportional hazards model (the main tool of medical statisticians), one finds in literature only rules of thumb on the number of samples required to avoid overfitting. In this paper we present a mathematical theory of overfitting in regression models for time-to-event data, which aims to increase our quantitative understanding of the problem and provide practical tools with which to correct regression outcomes for the impact of overfitting. It is based on the replica method, a statistical mechanical technique for the analysis of heterogeneous many-variable systems that has been used successfully for several decades in physics, biology, and computer science, but not yet in medical statistics. We develop the theory initially for arbitrary regression models for time-to-event data, and verify its predictions in detail for the popular Cox model.

Comparison of Cox's and relative survival models when estimating the effects of prognostic factors on disease-specific mortality: a simulation study under proportional excess hazards.

PubMed

Le Teuff, Gwenaël; Abrahamowicz, Michal; Bolard, Philippe; Quantin, Catherine

2005-12-30

In many prognostic studies focusing on mortality of persons affected by a particular disease, the cause of death of individual patients is not recorded. In such situations, the conventional survival analytical methods, such as the Cox's proportional hazards regression model, do not allow to discriminate the effects of prognostic factors on disease-specific mortality from their effects on all-causes mortality. In the last decade, the relative survival approach has been proposed to deal with the analyses involving population-based cancer registries, where the problem of missing information on the cause of death is very common. However, some questions regarding the ability of the relative survival methods to accurately discriminate between the two sources of mortality remain open. In order to systematically assess the performance of the relative survival model proposed by Esteve et al., and to quantify its potential advantages over the Cox's model analyses, we carried out a series of simulation experiments, based on the population-based colon cancer registry in the French region of Burgundy. Simulations showed a systematic bias induced by the 'crude' conventional Cox's model analyses when individual causes of death are unknown. In simulations where only about 10 per cent of patients died of causes other than colon cancer, the Cox's model over-estimated the effects of male gender and oldest age category by about 17 and 13 per cent, respectively, with the coverage rate of the 95 per cent CI for the latter estimate as low as 65 per cent. In contrast, the effect of higher cancer stages was under-estimated by 8-28 per cent. In contrast to crude survival, relative survival model largely reduced such problems and handled well even such challenging tasks as separating the opposite effects of the same variable on cancer-related versus other-causes mortality. Specifically, in all the cases discussed above, the relative bias in the estimates from the Esteve et al.'s model was always below 10 per cent, with the coverage rates above 81 per cent. Copyright 2005 John Wiley & Sons, Ltd.

Added prognostic value of CT characteristics and IASLC/ATS/ERS histologic subtype in surgically resected lung adenocarcinomas.

PubMed

Suh, Young Joo; Lee, Hyun-Ju; Kim, Young Tae; Kang, Chang Hyun; Park, In Kyu; Jeon, Yoon Kyung; Chung, Doo Hyun

2018-06-01

Our study investigates the added value of computed tomography (CT) characteristics, histologic subtype classification of the International Association for the Study of Lung Cancer (IASLC)/the American Thoracic Society (ATS)/the European Respiratory Society (ERS), and genetic mutation for predicting postoperative prognoses of patients who received curative surgical resections for lung adenocarcinoma. We retrospectively enrolled 988 patients who underwent curative resection for invasive lung adenocarcinoma between October 2007 and December 2013. Cox's proportional hazard model was used to explore the risk of recurrence-free survival, based on the combination of conventional prognostic factors, CT characteristics, IASLC/ATS/ERS histologic subtype, and epidermal growth factor receptor (EGFR) mutations. Incremental prognostic values of CT characteristics, histologic subtype, and EGFR mutations over conventional risk factors were measured by C-statistics. During median follow-up period of 44.7 months (25th to 75th percentile 24.6-59.7 months), postoperative recurrence occurred in 248 patients (25.1%). In univariate Cox proportion hazard model, female sex, tumor size and stage, CT characteristics, and predominant histologic subtype were associated with tumor recurrence (P < 0.05). In multivariate Cox regression model adjusted for tumor size and stage, both CT characteristics and histologic subtype were independent tumor recurrence predictors (P < 0.05). Cox proportion hazard models combining CT characteristics or histologic subtype with size and tumor stage showed higher C-indices (0.763 and 0.767, respectively) than size and stage-only models (C-index 0.759, P > 0.05). CT characteristics and histologic subtype have relatively limited added prognostic values over tumor size and stage in surgically resected lung adenocarcinomas. Copyright © 2018 Elsevier B.V. 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

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.

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

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.

A method for analyzing clustered interval-censored data based on Cox's model.

PubMed

Kor, Chew-Teng; Cheng, Kuang-Fu; Chen, Yi-Hau

2013-02-28

Methods for analyzing interval-censored data are well established. Unfortunately, these methods are inappropriate for the studies with correlated data. In this paper, we focus on developing a method for analyzing clustered interval-censored data. Our method is based on Cox's proportional hazard model with piecewise-constant baseline hazard function. The correlation structure of the data can be modeled by using Clayton's copula or independence model with proper adjustment in the covariance estimation. We establish estimating equations for the regression parameters and baseline hazards (and a parameter in copula) simultaneously. Simulation results confirm that the point estimators follow a multivariate normal distribution, and our proposed variance estimations are reliable. In particular, we found that the approach with independence model worked well even when the true correlation model was derived from Clayton's copula. We applied our method to a family-based cohort study of pandemic H1N1 influenza in Taiwan during 2009-2010. Using the proposed method, we investigate the impact of vaccination and family contacts on the incidence of pH1N1 influenza. Copyright © 2012 John Wiley & Sons, Ltd.

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.

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.

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

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.

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.

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.

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

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.

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

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.

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.

REGULARIZATION FOR COX'S PROPORTIONAL HAZARDS MODEL WITH NP-DIMENSIONALITY.

PubMed

Bradic, Jelena; Fan, Jianqing; Jiang, Jiancheng

2011-01-01

High throughput genetic sequencing arrays with thousands of measurements per sample and a great amount of related censored clinical data have increased demanding need for better measurement specific model selection. In this paper we establish strong oracle properties of non-concave penalized methods for non-polynomial (NP) dimensional data with censoring in the framework of Cox's proportional hazards model. A class of folded-concave penalties are employed and both LASSO and SCAD are discussed specifically. We unveil the question under which dimensionality and correlation restrictions can an oracle estimator be constructed and grasped. It is demonstrated that non-concave penalties lead to significant reduction of the "irrepresentable condition" needed for LASSO model selection consistency. The large deviation result for martingales, bearing interests of its own, is developed for characterizing the strong oracle property. Moreover, the non-concave regularized estimator, is shown to achieve asymptotically the information bound of the oracle estimator. A coordinate-wise algorithm is developed for finding the grid of solution paths for penalized hazard regression problems, and its performance is evaluated on simulated and gene association study examples.

Risk stratification personalised model for prediction of life-threatening ventricular tachyarrhythmias in patients with chronic heart failure.

PubMed

Frolov, Alexander Vladimirovich; Vaikhanskaya, Tatjana Gennadjevna; Melnikova, Olga Petrovna; Vorobiev, Anatoly Pavlovich; Guel, Ludmila Michajlovna

2017-01-01

The development of prognostic factors of life-threatening ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD) continues to maintain its priority and relevance in cardiology. The development of a method of personalised prognosis based on multifactorial analysis of the risk factors associated with life-threatening heart rhythm disturbances is considered a key research and clinical task. To design a prognostic and mathematical model to define personalised risk for life-threatening VTA in patients with chronic heart failure (CHF). The study included 240 patients with CHF (mean-age of 50.5 ± 12.1 years; left ventricular ejection fraction 32.8 ± 10.9%; follow-up period 36.8 ± 5.7 months). The participants received basic therapy for heart failure. The elec-trocardiogram (ECG) markers of myocardial electrical instability were assessed including microvolt T-wave alternans, heart rate turbulence, heart rate deceleration, and QT dispersion. Additionally, echocardiography and Holter monitoring (HM) were performed. The cardiovascular events were considered as primary endpoints, including SCD, paroxysmal ventricular tachycardia/ventricular fibrillation (VT/VF) based on HM-ECG data, and data obtained from implantable device interrogation (CRT-D, ICD) as well as appropriated shocks. During the follow-up period, 66 (27.5%) subjects with CHF showed adverse arrhythmic events, including nine SCD events and 57 VTAs. Data from a stepwise discriminant analysis of cumulative ECG-markers of myocardial electrical instability were used to make a mathematical model of preliminary VTA risk stratification. Uni- and multivariate Cox logistic regression analysis were performed to define an individualised risk stratification model of SCD/VTA. A binary logistic regression model demonstrated a high prognostic significance of discriminant function with a classification sensitivity of 80.8% and specificity of 99.1% (F = 31.2; c2 = 143.2; p < 0.0001). The method of personalised risk stratification using Cox logistic regression allows correct classification of more than 93.9% of CHF cases. A robust body of evidence concerning logistic regression prognostic significance to define VTA risk allows inclusion of this method into the algorithm of subsequent control and selection of the optimal treatment modality to treat patients with CHF.

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.

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

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.

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.

On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States

NASA Astrophysics Data System (ADS)

Mallakpour, Iman; Villarini, Gabriele; Jones, Michael P.; Smith, James A.

2017-08-01

The central United States is plagued by frequent catastrophic flooding, such as the flood events of 1993, 2008, 2011, 2013, 2014 and 2016. The goal of this study is to examine whether it is possible to describe the occurrence of flood and heavy precipitation events at the sub-seasonal scale in terms of variations in the climate system. Daily streamflow and precipitation time series over the central United States (defined here to include North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Illinois, West Virginia, Kentucky, Ohio, Indiana, and Michigan) are used in this study. We model the occurrence/non-occurrence of a flood and heavy precipitation event over time using regression models based on Cox processes, which can be viewed as a generalization of Poisson processes. Rather than assuming that an event (i.e., flooding or precipitation) occurs independently of the occurrence of the previous one (as in Poisson processes), Cox processes allow us to account for the potential presence of temporal clustering, which manifests itself in an alternation of quiet and active periods. Here we model the occurrence/non-occurrence of flood and heavy precipitation events using two climate indices as time-varying covariates: the Arctic Oscillation (AO) and the Pacific-North American pattern (PNA). We find that AO and/or PNA are important predictors in explaining the temporal clustering in flood occurrences in over 78% of the stream gages we considered. Similar results are obtained when working with heavy precipitation events. Analyses of the sensitivity of the results to different thresholds used to identify events lead to the same conclusions. The findings of this work highlight that variations in the climate system play a critical role in explaining the occurrence of flood and heavy precipitation events at the sub-seasonal scale over the central United States.

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

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

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.

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.

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

Intra-individual reaction time variability and all-cause mortality over 17 years: a community-based cohort study.

PubMed

Batterham, Philip J; Bunce, David; Mackinnon, Andrew J; Christensen, Helen

2014-01-01

very few studies have examined the association between intra-individual reaction time variability and subsequent mortality. Furthermore, the ability of simple measures of variability to predict mortality has not been compared with more complex measures. a prospective cohort study of 896 community-based Australian adults aged 70+ were interviewed up to four times from 1990 to 2002, with vital status assessed until June 2007. From this cohort, 770-790 participants were included in Cox proportional hazards regression models of survival. Vital status and time in study were used to conduct survival analyses. The mean reaction time and three measures of intra-individual reaction time variability were calculated separately across 20 trials of simple and choice reaction time tasks. Models were adjusted for a range of demographic, physical health and mental health measures. greater intra-individual simple reaction time variability, as assessed by the raw standard deviation (raw SD), coefficient of variation (CV) or the intra-individual standard deviation (ISD), was strongly associated with an increased hazard of all-cause mortality in adjusted Cox regression models. The mean reaction time had no significant association with mortality. intra-individual variability in simple reaction time appears to have a robust association with mortality over 17 years. Health professionals such as neuropsychologists may benefit in their detection of neuropathology by supplementing neuropsychiatric testing with the straightforward process of testing simple reaction time and calculating raw SD or CV.

Factors associated with HIV/AIDS treatment dropouts in a special care unit in the City of Rio de Janeiro, RJ, Brazil.

PubMed

Schilkowsky, Louise Bastos; Portela, Margareth Crisóstomo; Sá, Marilene de Castilho

2011-06-01

This study aimed to identify factors associated with the health care of patients with HIV/AIDS who drop out. The study was developed in a specialized health care unit of a University hospital in Rio de Janeiro, Brazil, considering a stratified sample of adult patients including all dropout cases (155) and 44.0% of 790 cases under regular follow-up. Bivariate analyses were used to identify associations between health care dropout and demographic, socioeconomic and clinical variables. Logistic and Cox regression models were used to identify the independent effects of the explanatory variables on risk for dropout, in the latter by incorporating information on the outcome over time. Patients were, on average, 35 years old, predominantly males (66.4%) and of a low socioeconomic level (45.0%). In both models, health care dropout was consistently associated with being unemployed or having an unstable job, using illicit drugs and having psychiatric background--positive association; and with age, having AIDS, and having used multiple antiretroviral regimens--negative association. In the logistic regression, dropping out was also positively associated with time between diagnosis and the first outpatient visit, while in the Cox model, the hazard for dropping out was positively associated with being single, and negatively associated with a higher educational level. The results of this work allow for the identification of HIV/AIDS patients more likely to drop out from health care.

Association of educational attainment with chronic disease and mortality: the Kidney Early Evaluation Program (KEEP).

PubMed

Choi, Andy I; Weekley, Cristin C; Chen, Shu-Cheng; Li, Suying; Tamura, Manjula Kurella; Norris, Keith C; Shlipak, Michael G

2011-08-01

Recent reports have suggested a close relationship between education and health, including mortality, in the United States. Observational cohort. We studied 61,457 participants enrolled in a national health screening initiative, the National Kidney Foundation's Kidney Early Evaluation Program (KEEP). Self-reported educational attainment. Chronic diseases (hypertension, diabetes, cardiovascular disease, reduced kidney function, and albuminuria) and mortality. We evaluated cross-sectional associations between self-reported educational attainment with the chronic diseases listed using logistic regression models adjusted for demographics, access to care, behaviors, and comorbid conditions. The association of educational attainment with survival was determined using multivariable Cox proportional hazards regression. Higher educational attainment was associated with a lower prevalence of each of the chronic conditions listed. In multivariable models, compared with persons not completing high school, college graduates had a lower risk of each chronic condition, ranging from 11% lower odds of decreased kidney function to 37% lower odds of cardiovascular disease. During a mean follow-up of 3.9 (median, 3.7) years, 2,384 (4%) deaths occurred. In the fully adjusted Cox model, those who had completed college had 24% lower mortality compared with participants who had completed at least some high school. Lack of income data does not allow us to disentangle the independent effects of education from income. In this diverse contemporary cohort, higher educational attainment was associated independently with a lower prevalence of chronic diseases and short-term mortality in all age and race/ethnicity groups. Published by Elsevier Inc.

Maximum likelihood estimation for Cox's regression model under nested case-control sampling.

PubMed

Scheike, Thomas H; Juul, Anders

2004-04-01

Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazards model. The MLE is computed by the EM-algorithm, which is easy to implement in the proportional hazards setting. Standard errors are estimated by a numerical profile likelihood approach based on EM aided differentiation. The work was motivated by a nested case-control study that hypothesized that insulin-like growth factor I was associated with ischemic heart disease. The study was based on a population of 3784 Danes and 231 cases of ischemic heart disease where controls were matched on age and gender. We illustrate the use of the MLE for these data and show how the maximum likelihood framework can be used to obtain information additional to the relative risk estimates of covariates.

Advantage of the modified Lunn-McNeil technique over Kalbfleisch-Prentice technique in competing risks

NASA Astrophysics Data System (ADS)

Lukman, Iing; Ibrahim, Noor A.; Daud, Isa B.; Maarof, Fauziah; Hassan, Mohd N.

2002-03-01

Survival analysis algorithm is often applied in the data mining process. Cox regression is one of the survival analysis tools that has been used in many areas, and it can be used to analyze the failure times of aircraft crashed. Another survival analysis tool is the competing risks where we have more than one cause of failure acting simultaneously. Lunn-McNeil analyzed the competing risks in the survival model using Cox regression with censored data. The modified Lunn-McNeil technique is a simplify of the Lunn-McNeil technique. The Kalbfleisch-Prentice technique is involving fitting models separately from each type of failure, treating other failure types as censored. To compare the two techniques, (the modified Lunn-McNeil and Kalbfleisch-Prentice) a simulation study was performed. Samples with various sizes and censoring percentages were generated and fitted using both techniques. The study was conducted by comparing the inference of models, using Root Mean Square Error (RMSE), the power tests, and the Schoenfeld residual analysis. The power tests in this study were likelihood ratio test, Rao-score test, and Wald statistics. The Schoenfeld residual analysis was conducted to check the proportionality of the model through its covariates. The estimated parameters were computed for the cause-specific hazard situation. Results showed that the modified Lunn-McNeil technique was better than the Kalbfleisch-Prentice technique based on the RMSE measurement and Schoenfeld residual analysis. However, the Kalbfleisch-Prentice technique was better than the modified Lunn-McNeil technique based on power tests measurement.

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

PubMed

Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

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.

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.

[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.

Coronary artery calcium distributions in older persons in the AGES-Reykjavik study

PubMed Central

Gudmundsson, Elias Freyr; Gudnason, Vilmundur; Sigurdsson, Sigurdur; Launer, Lenore J.; Harris, Tamara B.; Aspelund, Thor

2013-01-01

Coronary Artery Calcium (CAC) is a sign of advanced atherosclerosis and an independent risk factor for cardiac events. Here, we describe CAC-distributions in an unselected aged population and compare modelling methods to characterize CAC-distribution. CAC is difficult to model because it has a skewed and zero inflated distribution with over-dispersion. Data are from the AGES-Reykjavik sample, a large population based study [2002-2006] in Iceland of 5,764 persons aged 66-96 years. Linear regressions using logarithmic- and Box-Cox transformations on CAC+1, quantile regression and a Zero-Inflated Negative Binomial model (ZINB) were applied. Methods were compared visually and with the PRESS-statistic, R2 and number of detected associations with concurrently measured variables. There were pronounced differences in CAC according to sex, age, history of coronary events and presence of plaque in the carotid artery. Associations with conventional coronary artery disease (CAD) risk factors varied between the sexes. The ZINB model provided the best results with respect to the PRESS-statistic, R2, and predicted proportion of zero scores. The ZINB model detected similar numbers of associations as the linear regression on ln(CAC+1) and usually with the same risk factors. PMID:22990371

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.

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.

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/.

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

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.

ANCA-Associated Glomerulonephritis: Risk Factors for Renal Relapse.

PubMed

Göçeroğlu, Arda; Berden, Annelies E; Fiocco, Marta; Floßmann, Oliver; Westman, Kerstin W; Ferrario, Franco; Gaskin, Gill; Pusey, Charles D; Hagen, E Christiaan; Noël, Laure-Hélène; Rasmussen, Niels; Waldherr, Rüdiger; Walsh, Michael; Bruijn, Jan A; Jayne, David R W; Bajema, Ingeborg M

2016-01-01

Relapse in ANCA-associated vasculitis (AAV) has been studied previously, but there are few studies on renal relapse in particular. Identifying patients at high risk of renal relapse may aid in optimizing clinical management. We investigated which clinical and histological parameters are risk factors for renal relapse in ANCA-associated glomerulonephritis (AAGN). Patients (n = 174) were newly diagnosed and had mild-moderate or severe renal involvement. Data were derived from two trials of the European Vasculitis Society: MEPEX and CYCAZAREM. The Cox regression model was used to identify parameters increasing the instantaneous risk (= rate) of renal relapse (useful for instant clinical decisions). For identifying predictors of renal relapse during follow-up, we used Fine & Gray's regression model. Competing events were end-stage renal failure and death. The cumulative incidence of renal relapse at 5 years was 9.5% (95% CI: 4.8-14.3%). In the Cox model, sclerotic class AAGN increased the instantaneous risk of renal relapse. In Fine & Gray's model, the absence of interstitial infiltrates at diagnosis was predictive for renal relapse. In this study we used two different models to identify possible relationships between clinical and histopathological parameters at time of diagnosis of AAV with the risk of experiencing renal relapse. Sclerotic class AAGN increased the instantaneous risk of renal relapse. This association is most likely due to the high proportion of sclerosed glomeruli reducing the compensatory capacity. The absence of interstitial infiltrates increased the risk of renal relapse which is a warning sign that patients with a relatively benign onset of disease may also be prone to renal relapse. Renal relapses occurring in patients with sclerotic class AAGN and renal relapses occurring in patients without interstitial infiltrates were mutually exclusive, which may indicate that they are essentially different.

The current contribution of molecular factors to risk estimation in neuroblastoma patients.

PubMed

Berthold, F; Sahin, K; Hero, B; Christiansen, H; Gehring, M; Harms, D; Horz, S; Lampert, F; Schwab, M; Terpe, J

1997-10-01

The association of molecular characteristics with prognosis has been reported, but not their relationship with each other and their impact in the context of known clinical risk factors. In this study, data of 1249 consecutive intent-to-treat-neuroblastoma patients with more than 1 year follow-up were examined by multivariate analysis using loglinear and Cox proportional hazard regression models on a stage-related basis (stages 1-3: 600, 4S: 116, 4: 533). In a first step, risk factors were identified from 18 selected clinical variables, and risk groups defined. The second step investigated whether molecular characteristics (MYCN, LOH 1p, del 1p, CD44, N-ras, NGF-R, bcl-2, APO-1 (CD95)) contributed additional prognostic information to the model. The loglinear model demonstrated several interactions between clinical factors. By the Cox regression model, seven independent clinical risk factors were found for stages 1-3, seven for stage 4 and two for stage 4S. By subsequent introduction of all molecular variables, MYCN amplification only added significant prognostic information to the clinical factors in localised and stage 4 neuroblastoma. The models allowed the definition of risk groups for stages 1-3 patients by age (e beta = 5.09) and MYCN (e beta = 4.26), for stage 4 by MYCN (e beta = 2.78) and number of symptoms (e beta = 2.44) and for stage 4S by platelet count (e beta = 3.91) and general condition (e beta = 2.99). Molecular factors and in particular MYCN contribute significantly to risk estimation. In conjunction with clinical factors, they are powerful tools to define risk groups in neuroblastoma.

ANCA-Associated Glomerulonephritis: Risk Factors for Renal Relapse

PubMed Central

Göçeroğlu, Arda; Berden, Annelies E.; Fiocco, Marta; Floßmann, Oliver; Westman, Kerstin W.; Ferrario, Franco; Gaskin, Gill; Pusey, Charles D.; Hagen, E. Christiaan; Noël, Laure-Hélène; Rasmussen, Niels; Waldherr, Rüdiger; Walsh, Michael; Bruijn, Jan A.; Jayne, David R. W.; Bajema, Ingeborg M.

2016-01-01

Relapse in ANCA-associated vasculitis (AAV) has been studied previously, but there are few studies on renal relapse in particular. Identifying patients at high risk of renal relapse may aid in optimizing clinical management. We investigated which clinical and histological parameters are risk factors for renal relapse in ANCA-associated glomerulonephritis (AAGN). Patients (n = 174) were newly diagnosed and had mild–moderate or severe renal involvement. Data were derived from two trials of the European Vasculitis Society: MEPEX and CYCAZAREM. The Cox regression model was used to identify parameters increasing the instantaneous risk (= rate) of renal relapse (useful for instant clinical decisions). For identifying predictors of renal relapse during follow-up, we used Fine & Gray’s regression model. Competing events were end-stage renal failure and death. The cumulative incidence of renal relapse at 5 years was 9.5% (95% CI: 4.8–14.3%). In the Cox model, sclerotic class AAGN increased the instantaneous risk of renal relapse. In Fine & Gray’s model, the absence of interstitial infiltrates at diagnosis was predictive for renal relapse. In this study we used two different models to identify possible relationships between clinical and histopathological parameters at time of diagnosis of AAV with the risk of experiencing renal relapse. Sclerotic class AAGN increased the instantaneous risk of renal relapse. This association is most likely due to the high proportion of sclerosed glomeruli reducing the compensatory capacity. The absence of interstitial infiltrates increased the risk of renal relapse which is a warning sign that patients with a relatively benign onset of disease may also be prone to renal relapse. Renal relapses occurring in patients with sclerotic class AAGN and renal relapses occurring in patients without interstitial infiltrates were mutually exclusive, which may indicate that they are essentially different. PMID:27973575

Markov chains and semi-Markov models in time-to-event analysis.

PubMed

Abner, Erin L; Charnigo, Richard J; Kryscio, Richard J

2013-10-25

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields.

Markov chains and semi-Markov models in time-to-event analysis

PubMed Central

Abner, Erin L.; Charnigo, Richard J.; Kryscio, Richard J.

2014-01-01

A variety of statistical methods are available to investigators for analysis of time-to-event data, often referred to as survival analysis. Kaplan-Meier estimation and Cox proportional hazards regression are commonly employed tools but are not appropriate for all studies, particularly in the presence of competing risks and when multiple or recurrent outcomes are of interest. Markov chain models can accommodate censored data, competing risks (informative censoring), multiple outcomes, recurrent outcomes, frailty, and non-constant survival probabilities. Markov chain models, though often overlooked by investigators in time-to-event analysis, have long been used in clinical studies and have widespread application in other fields. PMID:24818062

[Study on factors influencing survival in patients with advanced gastric carcinoma after resection by Cox's proportional hazard model].

PubMed

Wang, S; Sun, Z; Wang, S

1996-11-01

A prospective follow-up study of 539 advanced gastric carcinoma patients after resection was undertaken between 1 January 1980 and 31 December 1989, with a follow-up rate of 95.36%. A multivariate analysis of possible factors influencing survival of these patients was performed, and their predicting models of survival rates was established by Cox proportional hazard model. The results showed that the major significant prognostic factors influencing survival of these patients were rate and station of lymph node metastases, type of operation, hepatic metastases, size of tumor, age and location of tumor. The most important factor was the rate of lymph node metastases. According to their regression coefficients, the predicting value (PV) of each patient was calculated, then all patients were divided into five risk groups according to PV, their predicting models of survival rates after resection were established in groups. The goodness-fit of estimated predicting models of survival rates were checked by fitting curve and residual plot, and the estimated models tallied with the actual situation. The results suggest that the patients with advanced gastric cancer after resection without lymph node metastases and hepatic metastases had a better prognosis, and their survival probability may be predicted according to the predicting model of survival rates.

[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.

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

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.

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.

Urinary proteomics for prediction of mortality in patients with type 2 diabetes and microalbuminuria.

PubMed

Currie, Gemma E; von Scholten, Bernt Johan; Mary, Sheon; Flores Guerrero, Jose-Luis; Lindhardt, Morten; Reinhard, Henrik; Jacobsen, Peter K; Mullen, William; Parving, Hans-Henrik; Mischak, Harald; Rossing, Peter; Delles, Christian

2018-04-06

The urinary proteomic classifier CKD273 has shown promise for prediction of progressive diabetic nephropathy (DN). Whether it is also a determinant of mortality and cardiovascular disease in patients with microalbuminuria (MA) is unknown. Urine samples were obtained from 155 patients with type 2 diabetes and confirmed microalbuminuria. Proteomic analysis was undertaken using capillary electrophoresis coupled to mass spectrometry to determine the CKD273 classifier score. A previously defined CKD273 threshold of 0.343 for identification of DN was used to categorise the cohort in Kaplan-Meier and Cox regression models with all-cause mortality as the primary endpoint. Outcomes were traced through national health registers after 6 years. CKD273 correlated with urine albumin excretion rate (UAER) (r = 0.481, p = <0.001), age (r = 0.238, p = 0.003), coronary artery calcium (CAC) score (r = 0.236, p = 0.003), N-terminal pro-brain natriuretic peptide (NT-proBNP) (r = 0.190, p = 0.018) and estimated glomerular filtration rate (eGFR) (r = 0.265, p = 0.001). On multivariate analysis only UAER (β = 0.402, p < 0.001) and eGFR (β = - 0.184, p = 0.039) were statistically significant determinants of CKD273. Twenty participants died during follow-up. CKD273 was a determinant of mortality (log rank [Mantel-Cox] p = 0.004), and retained significance (p = 0.048) after adjustment for age, sex, blood pressure, NT-proBNP and CAC score in a Cox regression model. A multidimensional biomarker can provide information on outcomes associated with its primary diagnostic purpose. Here we demonstrate that the urinary proteomic classifier CKD273 is associated with mortality in individuals with type 2 diabetes and MA even when adjusted for other established cardiovascular and renal biomarkers.

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.

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

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.

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

Effect of ionized serum calcium on outcomes in acute kidney injury needing renal replacement therapy: Secondary analysis of the Acute Renal Failure Trial Network Study

PubMed Central

Afshinnia, Farsad; Belanger, Karen; Palevsky, Paul M.; Young, Eric W.

2014-01-01

Background Hypocalcemia is very common in critically ill patients. While the effect of ionized calcium (iCa) on outcome is not well understood, manipulation of iCa in critically ill patients is a common practice. We analyzed all-cause mortality and several secondary outcomes in patients with acute kidney injury (AKI) by categories of serum iCa among participants in the Acute Renal Failure Trial Network (ATN) Study. Methods This is a post hoc secondary analysis of the ATN Study which was not preplanned in the original trial. Risk of mortality and renal recovery by categories of iCa were compared using multiple fixed and adjusted time-varying Cox regression models. Multiple linear regression models were used to explore the impact of baseline iCa on days free from ICU and hospital. Results A total of 685 patients were included in the analysis. Mean age was 60 (SD=15) years. There were 502 male patients (73.3%). Sixty-day all-cause mortality was 57.0%, 54.8%, and 54.4%, in patients with an iCa <1, 1–1.14, and ≥1.15 mmol/L, respectively (P=0.87). Mean of days free from ICU or hospital in all patients and the 28-day renal recovery in survivors to day 28 were not significantly different by categories of iCa. The hazard for death in a fully adjusted time-varying Cox regression survival model was 1.7 (95% CI: 1.3–2.4) comparing iCa <1 to iCa ≥1.15 mmol/L. No outcome was different for levels of iCa >1 mmol/L. Conclusion Severe hypocalcemia with iCa <1 mmol/L independently predicted mortality in patients with AKI needing renal replacement therapy. PMID:23992422

Resting Heart Rate as Predictor for Left Ventricular Dysfunction and Heart Failure: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Opdahl, Anders; Venkatesh, Bharath Ambale; Fernandes, Veronica R. S.; Wu, Colin O.; Nasir, Khurram; Choi, Eui-Young; Almeida, Andre L. C.; Rosen, Boaz; Carvalho, Benilton; Edvardsen, Thor; Bluemke, David A.; Lima, Joao A. C.

2014-01-01

OBJECTIVE To investigate the relationship between baseline resting heart rate and incidence of heart failure (HF) and global and regional left ventricular (LV) dysfunction. BACKGROUND The association of resting heart rate to HF and LV function is not well described in an asymptomatic multi-ethnic population. METHODS Participants in the Multi-Ethnic Study of Atherosclerosis had resting heart rate measured at inclusion. Incident HF was registered (n=176) during follow-up (median 7 years) in those who underwent cardiac MRI (n=5000). Changes in ejection fraction (ΔEF) and peak circumferential strain (Δεcc) were measured as markers of developing global and regional LV dysfunction in 1056 participants imaged at baseline and 5 years later. Time to HF (Cox model) and Δεcc and ΔEF (multiple linear regression models) were adjusted for demographics, traditional cardiovascular risk factors, calcium score, LV end-diastolic volume and mass in addition to resting heart rate. RESULTS Cox analysis demonstrated that for 1 bpm increase in resting heart rate there was a 4% greater adjusted relative risk for incident HF (Hazard Ratio: 1.04 (1.02, 1.06 (95% CI); P<0.001). Adjusted multiple regression models demonstrated that resting heart rate was positively associated with deteriorating εcc and decrease in EF, even in analyses when all coronary heart disease events were excluded from the model. CONCLUSION Elevated resting heart rate is associated with increased risk for incident HF in asymptomatic participants in MESA. Higher heart rate is related to development of regional and global LV dysfunction independent of subclinical atherosclerosis and coronary heart disease. PMID:24412444

The Association between Triglyceride/High-Density Lipoprotein Cholesterol Ratio and All-Cause Mortality in Acute Coronary Syndrome after Coronary Revascularization

PubMed Central

Wan, Ke; Zhao, Jianxun; Huang, Hao; Zhang, Qing; Chen, Xi; Zeng, Zhi; Zhang, Li; Chen, Yucheng

2015-01-01

Aims High triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) are cardiovascular risk factors. A positive correlation between elevated TG/HDL-C ratio and all-cause mortality and cardiovascular events exists in women. However, utility of TG to HDL-C ratio for prediction is unknown among acute coronary syndrome (ACS). Methods Fasting lipid profiles, detailed demographic data, and clinical data were obtained at baseline from 416 patients with ACS after coronary revascularization. Subjects were stratified into three levels of TG/HDL-C. We constructed multivariate Cox-proportional hazard models for all-cause mortality over a median follow-up of 3 years using log TG to HDL-C ratio as a predictor variable and analyzing traditional cardiovascular risk factors. We constructed a logistic regression model for major adverse cardiovascular events (MACEs) to prove that the TG/HDL-C ratio is a risk factor. Results The subject’s mean age was 64 ± 11 years; 54.5% were hypertensive, 21.8% diabetic, and 61.0% current or prior smokers. TG/HDL-C ratio ranged from 0.27 to 14.33. During the follow-up period, there were 43 deaths. In multivariate Cox models after adjusting for age, smoking, hypertension, diabetes, and severity of angiographic coronary disease, patients in the highest tertile of ACS had a 5.32-fold increased risk of mortality compared with the lowest tertile. After adjusting for conventional coronary heart disease risk factors by the logistic regression model, the TG/HDL-C ratio was associated with MACEs. Conclusion The TG to HDL-C ratio is a powerful independent predictor of all-cause mortality and is a risk factor of cardiovascular events. PMID:25880982

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.

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

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.

Discrete mixture modeling to address genetic heterogeneity in time-to-event regression

PubMed Central

Eng, Kevin H.; Hanlon, Bret M.

2014-01-01

Motivation: Time-to-event regression models are a critical tool for associating survival time outcomes with molecular data. Despite mounting evidence that genetic subgroups of the same clinical disease exist, little attention has been given to exploring how this heterogeneity affects time-to-event model building and how to accommodate it. Methods able to diagnose and model heterogeneity should be valuable additions to the biomarker discovery toolset. Results: We propose a mixture of survival functions that classifies subjects with similar relationships to a time-to-event response. This model incorporates multivariate regression and model selection and can be fit with an expectation maximization algorithm, we call Cox-assisted clustering. We illustrate a likely manifestation of genetic heterogeneity and demonstrate how it may affect survival models with little warning. An application to gene expression in ovarian cancer DNA repair pathways illustrates how the model may be used to learn new genetic subsets for risk stratification. We explore the implications of this model for censored observations and the effect on genomic predictors and diagnostic analysis. Availability and implementation: R implementation of CAC using standard packages is available at https://gist.github.com/programeng/8620b85146b14b6edf8f Data used in the analysis are publicly available. Contact: kevin.eng@roswellpark.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24532723

BCL2 genotypes and prostate cancer survival.

PubMed

Renner, Wilfried; Langsenlehner, Uwe; Krenn-Pilko, Sabine; Eder, Petra; Langsenlehner, Tanja

2017-06-01

The antiapoptotic B‑cell lymphoma 2 (BCL2) gene is a key player in cancer development and progression. A functional single-nucleotide polymorphism (c.-938C>A, rs2279115) in the inhibitory P2 BCL2 gene promoter has been associated with clinical outcomes in various types of cancer. Aim of the present study was to analyze the role of BCL2-938C>A genotypes in prostate cancer mortality. The association between BCL2-938C>A (rs2279115) genotypes and prostate cancer outcome was studied within the prospective PROCAGENE study comprising 702 prostate cancer patients. During a median follow-up time of 92 months, 120 (17.1%) patients died. A univariate Cox regression model showed a significant association of the CC genotype with reduced cancer-specific survival (CSS; hazard ratio, HR, 2.13, 95% confidence interval, CI, 1.10-4.12; p = 0.024) and overall survival (OS; HR 2.34, 95% CI 1.58-3.47; p < 0.001). In a multivariate Cox regression model including age at diagnosis, risk group, and androgen deprivation therapy, the CC genotype remained a significant predictor of poor CSS (HR 2.05, 95% CI 1.05-3.99; p = 0.034) and OS (HR 2.25, 95% CI 1.51-3.36; p < 0.001). This study provides evidence that the homozygous BCL2-938 CC genotype is associated with OS and C in prostate cancer patients.

Can risk assessment predict suicide in secondary mental healthcare? Findings from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register.

PubMed

Lopez-Morinigo, Javier-David; Fernandes, Andrea C; Shetty, Hitesh; Ayesa-Arriola, Rosa; Bari, Ashraful; Stewart, Robert; Dutta, Rina

2018-06-02

The predictive value of suicide risk assessment in secondary mental healthcare remains unclear. This study aimed to investigate the extent to which clinical risk assessment ratings can predict suicide among people receiving secondary mental healthcare. Retrospective inception cohort study (n = 13,758) from the South London and Maudsley NHS Foundation Trust (SLaM) (London, UK) linked with national mortality data (n = 81 suicides). Cox regression models assessed survival from the last suicide risk assessment and ROC curves evaluated the performance of risk assessment total scores. Hopelessness (RR = 2.24, 95% CI 1.05-4.80, p = 0.037) and having a significant loss (RR = 1.91, 95% CI 1.03-3.55, p = 0.041) were significantly associated with suicide in the multivariable Cox regression models. However, screening statistics for the best cut-off point (4-5) of the risk assessment total score were: sensitivity 0.65 (95% CI 0.54-0.76), specificity 0.62 (95% CI 0.62-0.63), positive predictive value 0.01 (95% CI 0.01-0.01) and negative predictive value 0.99 (95% CI 0.99-1.00). Although suicide was linked with hopelessness and having a significant loss, risk assessment performed poorly to predict such an uncommon outcome in a large case register of patients receiving secondary mental healthcare.

Influence of enamel preservation on failure rates of porcelain laminate veneers.

PubMed

Gurel, Galip; Sesma, Newton; Calamita, Marcelo A; Coachman, Christian; Morimoto, Susana

2013-01-01

The purpose of this study was to evaluate the failure rates of porcelain laminate veneers (PLVs) and the influence of clinical parameters on these rates in a retrospective survey of up to 12 years. Five hundred eighty laminate veneers were bonded in 66 patients. The following parameters were analyzed: type of preparation (depth and margin), crown lengthening, presence of restoration, diastema, crowding, discoloration, abrasion, and attrition. Survival was analyzed using the Kaplan-Meier method. Cox regression modeling was used to determine which factors would predict PLV failure. Forty-two veneers (7.2%) failed in 23 patients, and an overall cumulative survival rate of 86% was observed. A statistically significant association was noted between failure and the limits of the prepared tooth surface (margin and depth). The most frequent failure type was fracture (n = 20). The results revealed no significant influence of crown lengthening apically, presence of restoration, diastema, discoloration, abrasion, or attrition on failure rates. Multivariable analysis (Cox regression model) also showed that PLVs bonded to dentin and teeth with preparation margins in dentin were approximately 10 times more likely to fail than PLVs bonded to enamel. Moreover, coronal crown lengthening increased the risk of PLV failure by 2.3 times. A survival rate of 99% was observed for veneers with preparations confined to enamel and 94% for veneers with enamel only at the margins. Laminate veneers have high survival rates when bonded to enamel and provide a safe and predictable treatment option that preserves tooth structure.

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

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.

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.

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.

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.

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.

On estimation of linear transformation models with nested case–control sampling

PubMed Central

Liu, Mengling

2011-01-01

Nested case–control (NCC) sampling is widely used in large epidemiological cohort studies for its cost effectiveness, but its data analysis primarily relies on the Cox proportional hazards model. In this paper, we consider a family of linear transformation models for analyzing NCC data and propose an inverse selection probability weighted estimating equation method for inference. Consistency and asymptotic normality of our estimators for regression coefficients are established. We show that the asymptotic variance has a closed analytic form and can be easily estimated. Numerical studies are conducted to support the theory and an application to the Wilms’ Tumor Study is also given to illustrate the methodology. PMID:21912975

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.

The occurrence of Simpson's paradox if site-level effect was ignored in the TREAT Asia HIV Observational Database.

PubMed

Jiamsakul, Awachana; Kerr, Stephen J; Chandrasekaran, Ezhilarasi; Huelgas, Aizobelle; Taecharoenkul, Sineenart; Teeraananchai, Sirinya; Wan, Gang; Ly, Penh Sun; Kiertiburanakul, Sasisopin; Law, Matthew

2016-08-01

In multisite human immunodeficiency virus (HIV) observational cohorts, clustering of observations often occurs within sites. Ignoring clustering may lead to "Simpson's paradox" (SP) where the trend observed in the aggregated data is reversed when the groups are separated. This study aimed to investigate the SP in an Asian HIV cohort and the effects of site-level adjustment through various Cox regression models. Survival time from combination antiretroviral therapy (cART) initiation was analyzed using four Cox models: (1) no site adjustment; (2) site as a fixed effect; (3) stratification through site; and (4) shared frailty on site. A total of 6,454 patients were included from 23 sites in Asia. SP was evident in the year of cART initiation variable. Model (1) shows the hazard ratio (HR) for years 2010-2014 was higher than the HR for 2006-2009, compared to 2003-2005 (HR = 0.68 vs. 0.61). Models (2)-(4) consistently implied greater improvement in survival for those who initiated in 2010-2014 than 2006-2009 contrasting findings from model (1). The effects of other significant covariates on survival were similar across four models. Ignoring site can lead to SP causing reversal of treatment effects. Greater emphasis should be made to include site in survival models when possible. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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.

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

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.

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

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.

A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

PubMed

Chai, Hua; Li, Zi-Na; Meng, De-Yu; Xia, Liang-Yong; Liang, Yong

2017-10-12

Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such information in the censored data, a semi-supervised learning framework (Cox-AFT model) combined with Cox proportional hazard (Cox) and accelerated failure time (AFT) model was used in cancer research, which has better performance than the single Cox or AFT model. This method, however, is easily affected by noise. To alleviate this problem, in this paper we combine the Cox-AFT model with self-paced learning (SPL) method to more effectively employ the information in the censored data in a self-learning way. SPL is a kind of reliable and stable learning mechanism, which is recently proposed for simulating the human learning process to help the AFT model automatically identify and include samples of high confidence into training, minimizing interference from high noise. Utilizing the SPL method produces two direct advantages: (1) The utilization of censored data is further promoted; (2) the noise delivered to the model is greatly decreased. The experimental results demonstrate the effectiveness of the proposed model compared to the traditional Cox-AFT 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.

Risk modeling in prospective diabetes studies: Association and predictive value of anthropometrics.

PubMed

Jafari-Koshki, Tohid; Arsang-Jang, Shahram; Aminorroaya, Ashraf; Mansourian, Marjan; Amini, Masoud

2018-04-03

This study aimed to introduce and apply modern statistical techniques for assessing association and predictive value of risk factors in first-degree relatives (FDR) of patients with diabetes from repeatedly measured diabetes data. We used data from 1319 FDR's of patients with diabetes followed for 8 years. Association and predictive performance of weight (Wt), body mass index (BMI), waist and hip circumferences (WC and HC) and their ratio (WHR), waist-height ratio (WHtR) and a body shape index (ABSI) in relation to future diabetes were evaluated by using Cox regression and joint longitudinal-survival modeling. According to Cox regression, in total sample, WC, HC, Wt, WHtR and BMI had significant direct association with diabetes (all p < 0.01) with the best predictive ability for WHtR (concordance probability estimate = 0.575). Joint modeling suggested direct associations between diabetes and WC, WHR, Wt, WHtR and BMI in total sample (all p < 0.05). According to LPML criterion, WHtR was the best predictor in both total sample and females with LPML of -2666.27 and -2185.67, respectively. However, according to AUC criteria, BMI had the best predictive performance with AUC-JM = 0.7629 and dAUC-JM = 0.5883 in total sample. In females, both AUC criteria indicated that WC was the best predictor followed by WHtR. WC, WHR, Wt, WHtR and BMI are among candidate anthropometric measures to be monitored in diabetes prevention programs. Larger multi-ethnic and multivariate research are warranted to assess interactions and identify the best predictors in subgroups. Copyright © 2018 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Long-term return behavior of Chinese whole blood donors.

PubMed

Guo, Nan; Wang, Jingxing; Yu, Qilu; Yang, Tonghan; Dong, Xiangdong; Wen, Guoxin; Tiemuer, Mei-hei-li; Li, Julin; He, Weilan; Lv, Yunlai; Ma, Hongli; Wen, Xiuqiong; Huang, Mei; Ness, Paul; Liu, Jing; Wright, David J; Nelson, Kenrad; Shan, Hua

2013-09-01

It is important to understand donor return behavior to maintain sufficient numbers of blood donors in developing countries where blood supplies are often inadequate. A total of 54,267 whole blood (WB) donors who donated between January 1 and March 31, 2008, at the five blood centers in China were followed for 2.5 years. Logistic regression was conducted to identify factors associated with their return behavior. A recurrent-event Cox proportional-hazard model was used to evaluate the overall effect of demographic variables and return behavior among first-time donors. Donors with previous donation history were more likely to return and the number of previous returns was positively associated with future return (odds ratios, 3.31, 4.82, and 8.16 for one, two to three, and more than three times compared to none). Thirty-four percent of donors (first-time donor, 21%; repeat donor, 54%) made at least one return donation, with 14% returning in the first 9 months. The multivariable logistic regression model for all WB donors and the Cox proportional hazard model for first-time donors showed consistent predictors for return: female sex, older age (≥ 25 years), larger volume (300 or 400 mL), and donating in satellite collection site. Encouraging first-time donors to make multiple donations is important for keeping adequate blood supply. The finding that first-time and repeat donors shared the same predictors for return indicates that retention strategies on repeat donors may be effective on first-time donors. Studies on motivators and barriers to return are needed, so that successful retention strategies can be tailored. © 2013 American Association of Blood Banks.

Chronic Stenotrophomonas maltophilia infection and mortality or lung transplantation in cystic fibrosis patients.

PubMed

Waters, Valerie; Atenafu, Eshetu G; Lu, Annie; Yau, Yvonne; Tullis, Elizabeth; Ratjen, Felix

2013-09-01

Chronic Stenotrophomonas maltophilia infection is an independent risk factor for severe pulmonary exacerbations in cystic fibrosis (CF) patients. The goal of this study was to determine the effect of chronic S. maltophilia infection on mortality and the need for lung transplantation in a longitudinal study of children and adults with CF. This was a cohort study of CF patients from the Hospital for Sick Children and St Michael's Hospital (Toronto, Canada) from 1997 to 2008. A Cox Regression model was used to estimate the hazard ratio (HR) to time of death or lung transplantation adjusting for age, gender, genotype, pancreatic status, CF related diabetes (CFRD), forced expiratory volume in 1 s (FEV1), body mass index, number of pulmonary exacerbations, Pseudomonas aeruginosa, Burkholderia cepacia complex, Aspergillus and chronic S. maltophilia infection. A total of 687 patients were followed over the 12 year study period; 95 patients underwent a lung transplantation (of which 26 died) and an additional 49 patients died (total 144 events). In a Cox Regression model adjusting for baseline FEV1, baseline infection with B. cepacia complex (HR 1.72, 95% CI 1.09-2.71) and baseline chronic S. maltophilia infection (HR 2.80, 95% CI 1.65-4.76) were significantly associated with death or lung transplant. However, in a time-varying model, infection with B. cepacia complex and chronic S. maltophilia infection were no longer significant. Baseline chronic S. maltophilia infection is associated with an almost three-fold increased risk of death or lung transplant in CF patients. It is still unclear, however, whether chronic S. maltophilia infection is simply a marker of severity of disease and ultimate mortality or whether it is causally related to disease progression. Copyright © 2012 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Hemoglobin Concentration and Risk of Incident Stroke in Community-Living Adults.

PubMed

Panwar, Bhupesh; Judd, Suzanne E; Warnock, David G; McClellan, William M; Booth, John N; Muntner, Paul; Gutiérrez, Orlando M

2016-08-01

In previous observational studies, hemoglobin concentrations have been associated with an increased risk of stroke. However, these studies were limited by a relatively low number of stroke events, making it difficult to determine whether the association of hemoglobin and stroke differed by demographic or clinical factors. Using Cox proportional hazards analysis and Kaplan-Meier plots, we examined the association of baseline hemoglobin concentrations with incident stroke in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, a cohort of black and white adults aged ≥45 years. A total of 518 participants developed stroke over a mean 7±2 years of follow-up. There was a statistically significant interaction between hemoglobin and sex (P=0.05) on the risk of incident stroke. In Cox regression models adjusted for demographic and clinical variables, there was no association of baseline hemoglobin concentration with incident stroke in men, whereas in women, the lowest (<12.4 g/dL) and highest (>14.0 g/dL) quartiles of hemoglobin were associated with higher risk of stroke when compared with the second quartile (12.4-13.2 g/dL; quartile 1: hazard ratio, 1.59; 95% confidence interval, 1.09-2.31; quartile 2: referent; quartile 3: hazard ratio, 0.91; 95% confidence interval, 0.59-1.38; quartile 4: hazard ratio, 1.59; 95% confidence interval, 1.08-2.35). Similar results were observed in models stratified by hemoglobin and sex and when hemoglobin was modeled as a continuous variable using restricted quadratic spline regression. Lower and higher hemoglobin concentrations were associated with a higher risk of incident stroke in women. No such associations were found in men. © 2016 American Heart Association, Inc.

Racial differences in tumor stage and survival for colorectal cancer in an insured population.

PubMed

Doubeni, Chyke A; Field, Terry S; Buist, Diana S M; Korner, Eli J; Bigelow, Carol; Lamerato, Lois; Herrinton, Lisa; Quinn, Virginia P; Hart, Gene; Hornbrook, Mark C; Gurwitz, Jerry H; Wagner, Edward H

2007-02-01

Despite declining death rates from colorectal cancer (CRC), racial disparities have continued to increase. In this study, the authors examined disparities in a racially diverse group of insured patients. This study was conducted among patients who were diagnosed with CRC from 1993 to 1998, when they were enrolled in integrated healthcare systems. Patients were identified from tumor registries and were linked to information in administrative databases. The sample was restricted to non-Hispanic whites (n = 10,585), non-Hispanic blacks (n = 1479), Hispanics (n = 985), and Asians/Pacific Islanders (n = 909). Differences in tumor stage and survival were analyzed by using polytomous and Cox regression models, respectively. In multivariable regression analyses, blacks were more likely than whites to have distant or unstaged tumors. In Cox models that were adjusted for nonmutable factors, blacks had a higher risk of death from CRC (hazard ratio [HR], 1.17; 95% confidence interval [95% CI], 1.06-1.30). Hispanics had a risk of death similar to whites (HR, 1.04; 95% CI, 0.92-1.18), whereas Asians/Pacific Islanders had a lower risk of death from CRC (HR, 0.89; 95% CI, 0.78-1.02). Adjustment for tumor stage decreased the HR to 1.11 for blacks, and the addition of receipt of surgical therapy to the model decreased the HR further to 1.06. The HR among Hispanics and Asians/Pacific Islanders was stable to adjustment for tumor stage and surgical therapy. The relation between race and survival from CRC was complex and appeared to be related to differences in tumor stage and therapy received, even in insured populations. Targeted interventions to improve the use of effective screening and treatment among vulnerable populations may be needed to eliminate disparities in CRC. (c) 2007 American Cancer Society.

Predicting the duration of sickness absence for patients with common mental disorders in occupational health care.

PubMed

Nieuwenhuijsen, Karen; Verbeek, Jos H A M; de Boer, Angela G E M; Blonk, Roland W B; van Dijk, Frank J H

2006-02-01

This study attempted to determine the factors that best predict the duration of absence from work among employees with common mental disorders. A cohort of 188 employees, of whom 102 were teachers, on sick leave with common mental disorders was followed for 1 year. Only information potentially available to the occupational physician during a first consultation was included in the predictive model. The predictive power of the variables was tested using Cox's regression analysis with a stepwise backward selection procedure. The hazard ratios (HR) from the final model were used to deduce a simple prediction rule. The resulting prognostic scores were then used to predict the probability of not returning to work after 3, 6, and 12 months. Calculating the area under the curve from the ROC (receiver operating characteristic) curve tested the discriminative ability of the prediction rule. The final Cox's regression model produced the following four predictors of a longer time until return to work: age older than 50 years [HR 0.5, 95% confidence interval (95% CI) 0.3-0.8], expectation of duration absence longer than 3 months (HR 0.5, 95% CI 0.3-0.8), higher educational level (HR 0.5, 95% CI 0.3-0.8), and diagnosis depression or anxiety disorder (HR 0.7, 95% CI 0.4-0.9). The resulting prognostic score yielded areas under the curves ranging from 0.68 to 0.73, which represent acceptable discrimination of the rule. A prediction rule based on four simple variables can be used by occupational physicians to identify unfavorable cases and to predict the duration of sickness absence.

Calorie intake and patient outcomes in severe acute kidney injury: findings from The Randomized Evaluation of Normal vs. Augmented Level of Replacement Therapy (RENAL) study trial

PubMed Central

2014-01-01

Introduction Current practice in the delivery of caloric intake (DCI) in patients with severe acute kidney injury (AKI) receiving renal replacement therapy (RRT) is unknown. We aimed to describe calorie administration in patients enrolled in the Randomized Evaluation of Normal vs. Augmented Level of Replacement Therapy (RENAL) study and to assess the association between DCI and clinical outcomes. Methods We performed a secondary analysis in 1456 patients from the RENAL trial. We measured the dose and evolution of DCI during treatment and analyzed its association with major clinical outcomes using multivariable logistic regression, Cox proportional hazards models, and time adjusted models. Results Overall, mean DCI during treatment in ICU was low at only 10.9 ± 9 Kcal/kg/day for non-survivors and 11 ± 9 Kcal/kg/day for survivors. Among patients with a lower DCI (below the median) 334 of 729 (45.8%) had died at 90-days after randomization compared with 316 of 727 (43.3%) patients with a higher DCI (above the median) (P = 0.34). On multivariable logistic regression analysis, mean DCI carried an odds ratio of 0.95 (95% confidence interval (CI): 0.91-1.00; P = 0.06) per 100 Kcal increase for 90-day mortality. DCI was not associated with significant differences in renal replacement (RRT) free days, mechanical ventilation free days, ICU free days and hospital free days. These findings remained essentially unaltered after time adjusted analysis and Cox proportional hazards modeling. Conclusions In the RENAL study, mean DCI was low. Within the limits of such low caloric intake, greater DCI was not associated with improved clinical outcomes. Trial registration ClinicalTrials.gov number, NCT00221013 PMID:24629036

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

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.

[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.

Gout in African Americans.

PubMed

Krishnan, Eswar

2014-09-01

African Americans have a substantially higher prevalence of risk factors for gout than Caucasians. The aim of the present study was to compare the risk for incident gout among African Americans and Caucasians. Incidence rates of physician-diagnosed gout among 11,559 Caucasian men and 931 African American men aged 35 to 57 years and at high cardiovascular risk, observed for 7 years as a part of the Multiple Risk Factor Intervention Trial, were analyzed. Cox regression models were used to account for potential confounding by age, body mass index, diuretic use, hypertension and diabetes status, aspirin and alcohol consumption, and kidney disease. At baseline, after accounting for risk factors, African Americans had a 14% lower prevalence of hyperuricemia than Caucasians. Incidence of gout increased with increasing prevalence of risk factors in both Caucasians and African Americans. Ethnic disparities in incidence rates were most apparent among those without other risk factors for gout. In separate Cox regression models, after accounting for risk factors, African American ethnicity was associated with a hazard ratio of 0.78 (95% confidence interval [CI], 0.66-0.93) for physician-diagnosed gout and 0.88 (95% CI, 0.85-0.90) for incident hyperuricemia. Significant interactions were observed; the association was the strongest (hazard ratio 0.47; 0.37-0.60). These associations were unaffected by addition of serum urate as a covariate or by using alternate case definitions for gout. After accounting for the higher prevalence of risk factors, African American ethnicity is associated with a significantly lower risk for gout and hyperuricemia compared with Caucasian ethnicity. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

No evidence of a causal relationship between hypothyroidism and glaucoma: A Danish nationwide register-based cohort study.

PubMed

Thvilum, Marianne; Brandt, Frans; Brix, Thomas Heiberg; Hegedüs, Laszlo

2018-01-01

An interrelationship between hypothyroidism and glaucoma, due to a shared autoimmune background or based on deposition of mucopolysaccharides in the trabecular meshwork in the eye, has been suggested but is at present unsubstantiated. Therefore, our objective was to investigate, at a nationwide and population-based level, whether there is such an association. Observational cohort study using record-linkage data from nationwide Danish health registers. 121,799 individuals diagnosed with a first episode of hypothyroidism were identified and were matched with 4 non-hypothyroid controls according to age and sex. Prevalence of glaucoma was recorded and cases and controls were followed over a mean of 7.1 years (range 0-17). Logistic and Cox regression models were used to assess the risk of glaucoma before and after the diagnosis of hypothyroidism, respectively. Overall, we found a higher prevalence of glaucoma in subjects with hypothyroidism as compared to controls (4.6% vs. 4.3%, p < 0.001). Prior to the diagnosis of hypothyroidism, the odds ratio (OR) was significantly increased for glaucoma [1.09; 95% confidence interval (CI): 1.04-1.13]. Based on the Cox regression model, there was no increased risk of glaucoma after the diagnosis of hypothyroidism [hazard ratio (HR) 1.00; 95% CI: 0.96-1.06], and the HR decreased further after adjusting for pre-existing co-morbidity (0.88; 95% CI: 0.84-0.93). There was an increased risk of glaucoma before but not after the diagnosis of hypothyroidism, suggesting that screening for glaucoma in hypothyroid individuals is unwarranted.

Clinical outcome and predictors of survival in patients with pneumocystis jirovecii pneumonia--results of a tertiary referral centre.

PubMed

Roembke, Felicitas; Heinzow, Hauke Sebastian; Gosseling, Thomas; Heinecke, Achim; Domagk, Dirk; Domschke, Wolfram; Meister, Tobias

2014-01-01

Pneumocystis jirovecii pneumonia also known as pneumocystis pneumonia (PCP) is an opportunistic respiratory infection in human immunodeficiency virus (HIV) patients that may also develop in non-HIV immunocompromised persons. The aim of our study was to evaluate mortality predictors of PCP patients in a tertiary referral centre. Fifty-one patients with symptomatic PCP were enrolled in the study. The patients had either HIV infection (n = 21) or other immunosuppressive conditions (n = 30). Baseline characteristics (e.g. age, sex and underlying disease) were retrieved. Kaplan-Meier analysis was employed to calculate survival. Comparisons were made by log-rank test. A multivariate analysis of factors influencing survival was carried out using the Cox regression model. Chi-squared test and Wilcoxon-Mann-Whitney test was applied as appropriate. The median survival time for the HIV group was >120 months compared with 3 months for the non-HIV group (P = 0.009). Three-month survival probability was also significantly greater in the HIV group compared with the non-HIV group (90% vs 41%, P = 0.002). In univariate log-rank test, intensive care unit (ICU) necessity, HIV negativity, age >50 years, haemoglobin <10g/dl, C-reactive protein >5 mg/dL and multiple comorbidities were significant negative predictors of survival. In the Cox regression model, ICU and HIV statuses turned out to be independent prognostic factors of survival. PCP is a serious problem in non-HIV immunocompromised patients in whom survival outcomes are worse than those in HIV patients. © 2013 John Wiley & Sons Ltd.

Population-based cohort study investigating the correlation of diabetes mellitus with pleural empyema in adults in Taiwan.

PubMed

Lai, Shih-Wei; Lin, Cheng-Li; Liao, Kuan-Fu

2017-09-01

We assessed the association between diabetes mellitus and the risk of pleural empyema in Taiwan.A population-based retrospective cohort study was conducted using the database of the Taiwan National Health Insurance Program. There were 28,802 subjects aged 20 to 84 years who were newly diagnosed with diabetes mellitus from 2000 to 2010 as the diabetes group and 114,916 randomly selected subjects without diabetes mellitus as the non-diabetes group. The diabetes group and the non-diabetes group were matched by sex, age, comorbidities, and the year of index date. The incidence of pleural empyema at the end of 2011 was estimated. A multivariable Cox proportional hazards regression model was used to estimate the hazard ratio (HR) and 95% confidence interval (95% CI) for pleural empyema associated with diabetes mellitus.The overall incidence of pleural empyema was 1.65-fold higher in the diabetes group than that in the non-diabetes group (1.58 vs 0.96 per 10,000 person-years, 95% CI 1.57-1.72). After adjusting for confounders, a multivariable Cox proportional hazards regression model revealed that the adjusted HR of pleural empyema was 1.71 in subjects with diabetes mellitus (95% CI 1.16-2.51), compared with those without diabetes mellitus. In further analysis, even in the absence of any comorbidity, the adjusted HR was 1.99 for subjects with diabetes mellitus alone (95% CI 1.18-3.38).Diabetic patients confer a 1.71-fold increased hazard of developing pleural empyema. Even in the absence of any comorbidity, the risk remains existent.

Evaluation of clinical and histopathologic prognostic factors for survival in canine osteosarcoma of the extracranial flat and irregular bones.

PubMed

Kruse, M A; Holmes, E S; Balko, J A; Fernandez, S; Brown, D C; Goldschmidt, M H

2013-07-01

Osteosarcoma is the most common bone tumor in dogs. However, current literature focuses primarily on appendicular osteosarcoma. This study examined the prognostic value of histological and clinical factors in flat and irregular bone osteosarcomas and hypothesized that clinical factors would have a significant association with survival time while histological factors would not. All osteosarcoma biopsy samples of the vertebra, rib, sternum, scapula, or pelvis were reviewed while survival information and clinical data were obtained from medical records, veterinarians, and owners. Forty-six dogs were included in the analysis of histopathological variables and 27 dogs with complete clinical data were included in the analysis of clinical variables. In the histopathologic cox regression model, there was no significant association between any histologic feature of osteosarcoma, including grade, and survival time. In the clinical cox regression model, there was a significant association between the location of the tumor and survival time as well as between the percent elevation of alkaline phosphatase (ALP) above normal and survival time. Controlling for ALP elevation, dogs with osteosarcoma located in the scapula had a significantly greater hazard for death (2.8) compared to dogs with tumors in other locations. Controlling for tumor location, every 100% increase in ALP from normal increased the hazard for death by 1.7. For canine osteosarcomas of the flat and irregular bones, histopathological features, including grade do not appear to be rigorous predictors of survival. Clinical variables such as increased ALP levels and tumor location in the scapula were associated with decreased survival times.

Comparison between alcohol- and hepatitis C virus-related hepatocellular carcinoma: clinical presentation, treatment and outcome.

PubMed

Bucci, L; Garuti, F; Camelli, V; Lenzi, B; Farinati, F; Giannini, E G; Ciccarese, F; Piscaglia, F; Rapaccini, G L; Di Marco, M; Caturelli, E; Zoli, M; Borzio, F; Sacco, R; Maida, M; Felder, M; Morisco, F; Gasbarrini, A; Gemini, S; Foschi, F G; Missale, G; Masotto, A; Affronti, A; Bernardi, M; Trevisani, F

2016-02-01

Hepatitis C virus (HCV) and alcohol abuse are the main risk factors for hepatocellular carcinoma (HCC) in Western countries. To investigate the role of alcoholic aetiology on clinical presentation, treatment and outcome of HCC as well as on each Barcelona Clinic Liver Cancer (BCLC) stage, as compared to HCV-related HCCs. A total of 1642 HCV and 573 alcoholic patients from the Italian Liver Cancer (ITA.LI.CA) database, diagnosed with HCC between January 2000 and December 2012 were compared for age, gender, type of diagnosis, tumour burden, portal vein thrombosis (PVT), oesophageal varices, liver function tests, alpha-fetoprotein, BCLC, treatment and survival. Aetiology was tested as predictor of survival in multivariate Cox regression models and according to HCC stages. Cirrhosis was present in 96% of cases in both groups. Alcoholic patients were younger, more likely male, with HCC diagnosed outside surveillance, in intermediate/terminal BCLC stage and had worse liver function. After adjustment for the lead-time, median (95% CI) overall survival (OS) was 27.4 months (21.5-33.2) in alcoholic and 33.6 months (30.7-36.5) in HCV patients (P = 0.021). The prognostic role of aetiology disappeared when survival was assessed in each BCLC stage and in the Cox regression multivariate models. Alcoholic aetiology affects survival of HCC patients through its negative effects on secondary prevention and cancer presentation but not through a greater cancer aggressiveness or worse treatment result. In fact, survival adjusted for confounding factors was similar in alcoholic and HCV patients. © 2015 John Wiley & Sons Ltd.

Determination of Dietary Iron Requirements by Full Expression of Iron-Containing Enzymes in Various Tissues of Broilers.

PubMed

Ma, Xinyan; Liao, Xiudong; Lu, Lin; Li, Sufen; Zhang, Liyang; Luo, Xugang

2016-11-01

The current dietary iron requirement (80 mg/kg) of broilers is mainly based on growth, hemoglobin concentration, or hematocrit data obtained in a few early studies; however, expressions of iron-containing enzymes might be more sensitive novel criteria to evaluate dietary iron requirements. The objective of this study was to determine dietary iron requirements of broilers for the full expression of succinate dehydrogenase (SDH), catalase, and cytochrome c oxidase (COX) in various tissues. A total of 336 1-d-old Arbor Acres male chicks were randomly assigned to 1 of 7 treatments with 6 replicates and fed a basal corn and soybean-meal diet (control, containing 67 mg Fe/kg) and the basal diet supplemented with 20, 40, 60, 80, 100, or 120 mg Fe/kg from FeSO 4 ⋅ 7H 2 O for 21 d. Regression analysis was performed to estimate the optimal dietary iron concentration with the use of broken-line or quadratic models. SDH activity in the liver and heart, COX and catalase activity in the liver, Sdh mRNA levels in the liver, and Cox mRNA levels in the liver and heart of broilers were affected (P < 0.027) by supplemental iron concentration, and increased quadratically (P < 0.004) as dietary iron concentration increased. Dietary iron requirements estimated on the basis of fitted broken-line or quadratic-curve models (P < 0.005) of the above indexes were 97-136 mg/kg. SDH activity in the liver and heart, COX and catalase activity in the liver, Sdh mRNA levels in the liver, and Cox mRNA levels in the liver and heart are, to our knowledge, new and sensitive criteria to evaluate the dietary iron requirements of broilers, and the dietary iron requirements would be 97-136 mg/kg to support the full expression of the above iron-containing enzymes in various tissues of broiler chicks from 1 to 21 d of age, which are higher than the current NRC iron requirement. © 2016 American Society for Nutrition.

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

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.

Combined Endoscopic/Sonographic-Based Risk Matrix Model for Predicting One-Year Risk of Surgery: A Prospective Observational Study of a Tertiary Center Severe/Refractory Crohn's Disease Cohort.

PubMed

Rispo, Antonio; Imperatore, Nicola; Testa, Anna; Bucci, Luigi; Luglio, Gaetano; De Palma, Giovanni Domenico; Rea, Matilde; Nardone, Olga Maria; Caporaso, Nicola; Castiglione, Fabiana

2018-03-08

In the management of Crohn's Disease (CD) patients, having a simple score combining clinical, endoscopic and imaging features to predict the risk of surgery could help to tailor treatment more effectively. AIMS: to prospectively evaluate the one-year risk factors for surgery in refractory/severe CD and to generate a risk matrix for predicting the probability of surgery at one year. CD patients needing a disease re-assessment at our tertiary IBD centre underwent clinical, laboratory, endoscopy and bowel sonography (BS) examinations within one week. The optimal cut-off values in predicting surgery were identified using ROC curves for Simple Endoscopic Score for CD (SES-CD), bowel wall thickness (BWT) at BS, and small bowel CD extension at BS. Binary logistic regression and Cox's regression were then carried out. Finally, the probabilities of surgery were calculated for selected baseline levels of covariates and results were arranged in a prediction matrix. Of 100 CD patients, 30 underwent surgery within one year. SES-CD©9 (OR 15.3; p<0.001), BWT©7 mm (OR 15.8; p<0.001), small bowel CD extension at BS©33 cm (OR 8.23; p<0.001) and stricturing/penetrating behavior (OR 4.3; p<0.001) were the only independent factors predictive of surgery at one-year based on binary logistic and Cox's regressions. Our matrix model combined these risk factors and the probability of surgery ranged from 0.48% to 87.5% (sixteen combinations). Our risk matrix combining clinical, endoscopic and ultrasonographic findings can accurately predict the one-year risk of surgery in patients with severe/refractory CD requiring a disease re-evaluation. This tool could be of value in clinical practice, serving as the basis for a tailored management of CD patients.

Outcome of Acute Prosthetic Joint Infections Due to Gram-Negative Bacilli Treated with Open Debridement and Retention of the Prosthesis▿

PubMed Central

Martínez-Pastor, Juan C.; Muñoz-Mahamud, Ernesto; Vilchez, Félix; García-Ramiro, Sebastián; Bori, Guillem; Sierra, Josep; Martínez, José A.; Font, Lluis; Mensa, Josep; Soriano, Alex

2009-01-01

The aim of our study was to evaluate the outcome of acute prosthetic joint infections (PJIs) due to gram-negative bacilli (GNB) treated without implant removal. Patients with an acute PJI due to GNB diagnosed from 2000 to 2007 were prospectively registered. Demographics, comorbidity, type of implant, microbiology data, surgical treatment, antimicrobial therapy, and outcome were recorded. Classification and regression tree analysis, the Kaplan-Meier survival method, and the Cox regression model were applied. Forty-seven patients were included. The mean age was 70.7 years, and there were 15 hip prostheses and 32 knee prostheses. The median number of days from the time of arthroplasty was 20. The most frequent pathogens were members of the Enterobacteriaceae family in 41 cases and Pseudomonas spp. in 20 cases. Among the Enterobacteriaceae, 14 were resistant to ciprofloxacin, while all Pseudomonas aeruginosa isolates were susceptible to ciprofloxacin. The median durations of intravenous and oral antibiotic treatment were 14 and 64 days, respectively. A total of 35 (74.5%) patients were in remission after a median follow-up of 463 days (interquartile range, 344 to 704) days. By use of the Kaplan-Meier survival curve, a C-reactive protein (CRP) concentration of ≤15 mg/dl (P = 0.03) and receipt of a fluoroquinolone, when all GNB isolated were susceptible (P = 0.0009), were associated with a better outcome. By use of a Cox regression model, a CRP concentration of ≤15 mg/dl (odds ratio [OR], 3.57; 95% confidence interval [CI], 1.05 to 12.5; P = 0.043) and receipt of a fluoroquinolone (OR, 9.09; 95% CI, 1.96 to 50; P = 0.005) were independently associated with better outcomes. Open debridement without removal of the implant had a success rate of 74.5%, and the factors associated with good prognosis were a CRP concentration at the time of diagnosis ≤15 mg/dl and treatment with a fluoroquinolone. PMID:19687237

Prevalence and Evolution of Renal Impairment in People Living With HIV in Rural Tanzania.

PubMed

Mapesi, Herry; Kalinjuma, Aneth V; Ngerecha, Alphonce; Franzeck, Fabian; Hatz, Christoph; Tanner, Marcel; Mayr, Michael; Furrer, Hansjakob; Battegay, Manuel; Letang, Emilio; Weisser, Maja; Glass, Tracy R

2018-04-01

We assessed the prevalence, incidence, and predictors of renal impairment among people living with HIV (PLWHIV) in rural Tanzania. In a cohort of PLWHIV aged ≥15 years enrolled from January 2013 to June 2016, we assessed the association between renal impairment (estimated glomerural filtration rate < 90 mL/min/1.73 m 2 ) at enrollment and during follow-up with demographic and clinical characteristcis using logistic regression and Cox proportional hazards models. Of 1093 PLWHIV, 172 (15.7%) had renal impairment at enrollment. Of 921 patients with normal renal function at baseline, 117 (12.7%) developed renal impairment during a median follow-up (interquartile range) of 6.2 (0.4-14.7) months. The incidence of renal impairment was 110 cases per 1000 person-years (95% confidence interval [CI], 92-132). At enrollment, logistic regression identified older age (adjusted odds ratio [aOR], 1.79; 95% CI, 1.52-2.11), hypertension (aOR, 1.84; 95% CI, 1.08-3.15), CD4 count <200 cells/mm 3 (aOR, 1.80; 95% CI, 1.23-2.65), and World Health Organization (WHO) stage III/IV (aOR, 3.00; 95% CI, 1.96-4.58) as risk factors for renal impairment. Cox regression model confirmed older age (adjusted hazard ratio [aHR], 1.85; 95% CI, 1.56-2.20) and CD4 count <200 cells/mm 3 (aHR, 2.05; 95% CI, 1.36-3.09) to be associated with the development of renal impairment. Our study found a low prevalence of renal impairment among PLWHIV despite high usage of tenofovir and its association with age, hypertension, low CD4 count, and advanced WHO stage. These important and reassuring safety data stress the significance of noncommunicable disease surveillance in aging HIV populations in sub-Saharan Africa.

Outcome of acute prosthetic joint infections due to gram-negative bacilli treated with open debridement and retention of the prosthesis.

PubMed

Martínez-Pastor, Juan C; Muñoz-Mahamud, Ernesto; Vilchez, Félix; García-Ramiro, Sebastián; Bori, Guillem; Sierra, Josep; Martínez, José A; Font, Lluis; Mensa, Josep; Soriano, Alex

2009-11-01

The aim of our study was to evaluate the outcome of acute prosthetic joint infections (PJIs) due to gram-negative bacilli (GNB) treated without implant removal. Patients with an acute PJI due to GNB diagnosed from 2000 to 2007 were prospectively registered. Demographics, comorbidity, type of implant, microbiology data, surgical treatment, antimicrobial therapy, and outcome were recorded. Classification and regression tree analysis, the Kaplan-Meier survival method, and the Cox regression model were applied. Forty-seven patients were included. The mean age was 70.7 years, and there were 15 hip prostheses and 32 knee prostheses. The median number of days from the time of arthroplasty was 20. The most frequent pathogens were members of the Enterobacteriaceae family in 41 cases and Pseudomonas spp. in 20 cases. Among the Enterobacteriaceae, 14 were resistant to ciprofloxacin, while all Pseudomonas aeruginosa isolates were susceptible to ciprofloxacin. The median durations of intravenous and oral antibiotic treatment were 14 and 64 days, respectively. A total of 35 (74.5%) patients were in remission after a median follow-up of 463 days (interquartile range, 344 to 704) days. By use of the Kaplan-Meier survival curve, a C-reactive protein (CRP) concentration of < or = 15 mg/dl (P = 0.03) and receipt of a fluoroquinolone, when all GNB isolated were susceptible (P = 0.0009), were associated with a better outcome. By use of a Cox regression model, a CRP concentration of < or = 15 mg/dl (odds ratio [OR], 3.57; 95% confidence interval [CI], 1.05 to 12.5; P = 0.043) and receipt of a fluoroquinolone (OR, 9.09; 95% CI, 1.96 to 50; P = 0.005) were independently associated with better outcomes. Open debridement without removal of the implant had a success rate of 74.5%, and the factors associated with good prognosis were a CRP concentration at the time of diagnosis < or = 15 mg/dl and treatment with a fluoroquinolone.

[Survival analysis of patients with pneumoconiosis from 1956 to 2010 in Changsha].

PubMed

Xue, Jing; Chen, Lizhang

2012-01-01

To investigate the survival rate and life expectancy of patients with pneumoconiosis and influence factors in Changsha from 1956 to 2010. A total of 3685 patients with pneumoconiosis were diagnosed and reported from 1956 to 2010 in Changsha. The fatality rate and life expectancy were analyzed by life table and the cause of death was analyzed by Kaplan-Meier method and Cox regression model. The death rate increased obviously with age. Age and accumulation death probability showed linearity (Ŷ=1.271+0.041X, r=0.989). The life expectancy was 60.12 years. The first cause of death was pulmonary tuberculosis in patients with pneumoconiosis. Ruling out the influence of pulmonary tuberculosis, pneumoconiosis, and lung source heart disease, the life expectancy of patients with pneumoconiosis averagely extended 0.83, 0.99, and 0.02 years. The death rate of pneumoconiosis-tuberculosis had significant difference with that of the pneumoconiosisnontuberculosis (P<0.01). Cox regression analysis revealed that the main risk factors for the survival of patients with pneumoconiosis included type of work (smashing worker), complication with tuberculosis, type of pneumoconiosis (silicosis). The death hazard ratio or relative risk caused by them was 1.927, 1.749, and 1.609, respectively. Prevention of pneumoconiosis should focus on smashing workers in Changsha, while its the treatment primarily attaches importance to complication of tuberculosis and lung infection.

Investigation of standardized administration of anti-platelet drugs and its effect on the prognosis of patients with coronary heart disease.

PubMed

Ding, Chao; Zhang, Jianhua; Li, Rongcheng; Wang, Jiacai; Hu, Yongcang; Chen, Yanyan; Li, Xiannan; Xu, Yan

2017-10-01

The aim of the present study was to explore the effect of adherence to standardized administration of anti-platelet drugs on the prognosis of patients with coronary heart disease. A total of 144 patients newly diagnosed with coronary heart disease at Lu'an Shili Hospital of Anhui Province (Lu'an, China) between June 2010 and June 2012 were followed up. Kaplan-Meier curves and the Cox regression model were used to evaluate the effects of standardized administration of anti-platelet drugs on primary and secondary end-point events. Of the patients with coronary heart disease, 109 (76%) patients took standard anti-platelet drugs following discharge. Kaplan-Meier curve and Cox regression analysis showed that standardized administration of anti-platelet drugs reduced the risk of primary end-point events (including all-cause mortality, non-lethal myocardial infarction and stroke) of patients with coronary heart disease [hazard ratio (HR)=0.307; 95% confidence interval (CI): 0.099-0.953; P=0.041) and all-cause mortality (HR=0.162; 95% CI: 0.029-0.890; P=0.036); however, standardized administration had no predictive value with regard to secondary end-point events. Standardized administration of anti-platelet drugs obviously reduced the risk of primary end-point events in patients with coronary heart disease, and further analysis showed that only all-cause mortality exhibited a statistically significant reduction.

Predictive factors for the regression of canine transmissible venereal tumor during vincristine therapy.

PubMed

Scarpelli, Karime C; Valladão, Maria L; Metze, Konradin

2010-03-01

Canine transmissible venereal tumor (CTVT) is a neoplasm transmitted by transplantation. Monochemotherapy with vincristine is considered to be effective, but treatment time until complete clinical remission may vary. The aim of this study was to determine which clinical data at diagnosis could predict the responsiveness of CTVT to vincristine chemotherapy. One hundred dogs with CTVT entered this prospective study. The animals were treated with vincristine sulfate (0.025 mg/kg) at weekly intervals until the tumor had macroscopically disappeared. The time to complete remission was recorded. A multivariate Cox regression model indicated that larger tumor mass, increased age and therapy during hot and rainy months were independent significant unfavorable predictive factors retarding remission, whereas sex, weight, status as owned dog or breed were of no predictive relevance. Further studies are necessary to investigate whether these results are due to changes in immunological response mechanisms in animals with a diminished immune surveillance, resulting in delays in tumor regression. 2008 Elsevier Ltd. All rights reserved.

Effect of late HIV diagnosis on HIV-related mortality among adults in general hospitals of Central Zone Tigray, northern Ethiopia: a retrospective cohort study.

PubMed

Belay, Hadera; Alemseged, Fessahaye; Angesom, Teklit; Hintsa, Solomon; Abay, Mebrahtu

2017-01-01

The global incidence of HIV infection is not significantly decreasing, especially in sub-Saharan African countries, including Ethiopia. Though there is availability and accessibility of free HIV services, people are not being diagnosed early for HIV, and hence patients are still dying of HIV-related causes. This research is aimed at verifying the effect of late diagnosis of HIV on HIV-related mortality in Central Zone Tigray, Ethiopia. A retrospective cohort study among adult (≥15 years old) HIV patients in three general hospitals of Tigray was conducted. Record reviews were carried out retrospectively from 2010 to 2015. Sample size was determined using stpower Cox in Stata software. Data were entered into EpiData version 3.1 software and transferred to Stata version 12 for analysis. Both bivariable and multivariable analyses were performed using Cox regression model to compare the HIV-related mortality of exposed (cluster of differentiation 4 cells count <350 cells/mm 3 ) and nonexposed (≥350 cells/mm 3 ) patients using adjusted hazard ratio (AHR) at 95% confidence interval (CI). In all, 638 HIV patients were analyzed, contributing 2,105.6 person-years. Forty-eight (7.5%) patients died of HIV-related causes with a mortality rate of 2.28 per 100 person-years. In the multivariable Cox regression model, patients with late diagnosis of HIV had a higher risk of mortality (AHR =3.22, 95% CI: 1.17-8.82) than patients with early diagnosis of HIV. Rural residence (AHR =1.96, 95% CI: 1.05-3.68), unemployment (AHR =2.70, 95% CI: 1.03-7.08), bedridden patients (AHR =2.98, 95% CI: 1.45-6.13), ambulatory patients (AHR =2.54, 95% CI: 1.05-6.15), and baseline hemoglobin level of <11 mg/dL (AHR =3.06, 95% CI: 1.51-6.23) were other independent predictors of mortality. Late diagnosis of HIV increased HIV-related mortality. Rural residence, unemployment, bedridden and ambulatory patients, and baseline hemoglobin level <11 mg/dL were also independent predictors of HIV-related mortality.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log–log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata). PMID:29307954

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

Regression of endometrial explants in a rat model of endometriosis treated with melatonin.

PubMed

Güney, Mehmet; Oral, Baha; Karahan, Nermin; Mungan, Tamer

2008-04-01

To determine the antioxidant, antiinflammatory, and immunomodulatory effects of melatonin on endometrial explants, the distribution of cyclooxygenase-2 (COX-2), the activity of antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT), and levels of malondialdehyde (MDA) in the rat endometriosis model. Prospective, placebo-controlled experimental study. Experimental surgery laboratory in a university department. Twenty-five rats with experimentally induced endometriosis. Endometriosis was surgically induced in 25 rats by transplanting an autologous fragment of endometrial tissue onto the inner surface of the abdominal wall. Four weeks later, three rats were killed and the remaining 22 rats given second-look laparotomies to identify and measure ectopic uterine tissue in three dimensions. After the second laparotomy, 4 weeks of vehicle and melatonin treatment were administered, then all of the rats were given a third laparotomy and killed. The volume and weight of the implants were measured. The remaining rats were randomly divided into two groups. In control group (group 1; n = 11) no medication was given. To the rats in melatonin-treated group (group 2; n = 11), 10 mg/kg a day of melatonin was administered intraperitoneally. Four weeks later, after the second laparotomy, the endometrial explants were reevaluated morphologically, and COX-2 expression was evaluated immunohistochemically and histologically. In addition, endometrial explants were analyzed for the antioxidant enzymes SOD, CAT, and MDA, a marker of lipid peroxidation. A scoring system was used to evaluate expression of COX-2 and preservation of epithelia. The pretreatment and posttreatment volumes within the control group were 135.9 +/- 31.5 and 129.4 +/- 28.7, respectively. The mean explant volume was 141.4 +/- 34.4 within the melatonin group before the treatment and 42.9 +/- 14.0 after 4 weeks of treatment. There was a statistically significant difference in spherical volumes (129.4 +/- 28.7 versus 42.9 +/- 14.0 mm(3)) of explant weights (155.8 +/- 27.1 versus 49.6 +/- 19.5 mg) and COX-2 positivity (91% versus 18.1%) between groups after the third laparotomy. In the melatonin-treated group, the endometrial explant levels of MDA statistically significantly decreased and activities of SOD and CAT significantly increased when compared with the control group. The epithelia showed statistically significantly better preservation in the control group when compared with the melatonin-treated group (2.54 +/- 0.52 versus 0.63 +/- 0.50). Melatonin causes regression and atrophy of the endometriotic lesions in rats.

Comparing of Cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes.

PubMed

Kargarian-Marvasti, Sadegh; Rimaz, Shahnaz; Abolghasemi, Jamileh; Heydari, Iraj

2017-01-01

Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model ( P < 0.20) were entered into the multivariate Cox and parametric models ( P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Using Kaplan-Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy ( P < 0.05). According to AIC, "log-normal" model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model.

Sequential cohort design applying propensity score matching to analyze the comparative effectiveness of atorvastatin and simvastatin in preventing cardiovascular events.

PubMed

Helin-Salmivaara, Arja; Lavikainen, Piia; Aarnio, Emma; Huupponen, Risto; Korhonen, Maarit Jaana

2014-01-01

Sequential cohort design (SCD) applying matching for propensity scores (PS) in accrual periods has been proposed to mitigate bias caused by channeling when calendar time is a proxy for strong confounders. We studied the channeling of patients according to atorvastatin and simvastatin initiation in Finland, starting from the market introduction of atorvastatin in 1998, and explored the SCD PS approach to analyzing the comparative effectiveness of atorvastatin versus simvastatin in the prevention of cardiovascular events (CVE). Initiators of atorvastatin or simvastatin use in the 45-75-year age range in 1998-2006 were characterized by their propensity of receiving atorvastatin over simvastatin, as estimated for 17 six-month periods. Atorvastatin (10 mg) and simvastatin (20 mg) initiators were matched 1∶1 on the PS, as estimated for the whole cohort and within each period. Cox regression models were fitted conventionally, and also for the PS matched cohort and the periodically PS matched cohort, to estimate the hazard ratios (HR) for CVEs. Atorvastatin (10 mg) was associated with a 11%-12% lower incidence of CVE in comparison with simvastatin (20 mg). The HR estimates were the same for a conventional Cox model (0.88, 95% confidence interval 0.85-0.91), for the analysis in which the PS was used to match across all periods and the Cox model was adjusted for strong confounders (0.89, 0.85-0.92), and for the analysis in which PS matching was applied within sequential periods (0.88, 0.84-0.92). The HR from a traditional PS matched analysis was 0.80 (0.77-0.83). The SCD PS approach produced effect estimates similar to those obtained in matching for PS within the whole cohort and adjusting the outcome model for strong confounders, but at the cost of efficiency. A traditional PS matched analysis without further adjustment in the outcome model produced estimates further away from unity.

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

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

Thrombosis Is Reduced by Inhibition of COX-1, but Unaffected by Inhibition of COX-2, in an Acute Model of Platelet Activation in the Mouse

PubMed Central

Armstrong, Paul C.; Kirkby, Nicholas S.; Zain, Zetty N.; Emerson, Michael; Mitchell, Jane A.; Warner, Timothy D.

2011-01-01

Background Clinical use of selective inhibitors of cyclooxygenase (COX)-2 appears associated with increased risk of thrombotic events. This is often hypothesised to reflect reduction in anti-thrombotic prostanoids, notably PGI2, formed by COX-2 present within endothelial cells. However, whether COX-2 is actually expressed to any significant extent within endothelial cells is controversial. Here we have tested the effects of acute inhibition of COX on platelet reactivity using a functional in vivo approach in mice. Methodology/Principal Findings A non-lethal model of platelet-driven thromboembolism in the mouse was used to assess the effects of aspirin (7 days orally as control) diclofenac (1 mg.kg−1, i.v.) and parecoxib (0.5 mg.kg−1, i.v.) on thrombus formation induced by collagen or the thromboxane (TX) A2-mimetic, U46619. The COX inhibitory profiles of the drugs were confirmed in mouse tissues ex vivo. Collagen and U46619 caused in vivo thrombus formation with the former, but not latter, sensitive to oral dosing with aspirin. Diclofenac inhibited COX-1 and COX-2 ex vivo and reduced thrombus formation in response to collagen, but not U46619. Parecoxib inhibited only COX-2 and had no effect upon thrombus formation caused by either agonist. Conclusions/Significance Inhibition of COX-1 by diclofenac or aspirin reduced thrombus formation induced by collagen, which is partly dependent upon platelet-derived TXA2, but not that induced by U46619, which is independent of platelet TXA2. These results are consistent with the model demonstrating the effects of COX-1 inhibition in platelets, but provide no support for the hypothesis that acute inhibition of COX-2 in the circulation increases thrombosis. PMID:21629780

Clinicopathological Features to Predict Progression of IgA Nephropathy with Mild Proteinuria.

PubMed

Chen, Ding; Liu, Jian; Duan, Shuwei; Chen, Pu; Tang, Li; Zhang, Li; Feng, Zhe; Cai, Guangyan; Wu, Jie; Chen, Xiangmei

2018-03-06

In the past, little attention has been paid to patients with IgA nephropathy (IgAN) who had minimal proteinuria upon the onset. The aim of this study was to analyze the clinicopathological features and the prognostic factors in patients with IgA nephropathy. Data of patients that had their first renal biopsy in our hospital and were diagnosed with primary IgAN with proteinuria <1 g/d from January 1995 to December 2014 were retrospectively examined. Clinical records of the clinicopathological features, renal function, and proteinuria were collected and investigated. The factors affecting the renal function and proteinuria were analyzed by Cox regression. The predictive efficiencies of clinical and pathological models were evaluated by Harrell concordance index (C-index). A total of 506 patients with IgA nephropathy were included in this study. (1) Baseline proteinuria greater than 0.5 g/d was positively associated with Oxford M, S, and T lesions. eGFR less than 90 mL/min/1.73 m2 were positively associated with Oxford T. (2) In the follow-up with a median of 50 months, 82 patients (16.2%) achieved complete clinical remission (CCR), whereas 54 patients (10.6%) showed an increase in creatinine by more than 50% (not progressing to end-stage renal disease). The cumulative proportion of creatinine increased >50%, and the values obtained by life-table analysis in 10, 15, and 20 years were 15%, 21%, and 22%, respectively. Significant differences were found in baseline age, proteinuria, and Oxford T between the group of creatinine increase >50% and the CCR group. (4) Multivariate COX regression showed that baseline age and proteinuria > 0.5 g/d were independent risk factors of adverse outcome. C-index suggested that the clinical model was more effective than the pathological models in predicting endpoint events. (5) Effect of the mean value during the follow-up on adverse endpoint events: Multivariate COX regression found that the mean proteinuria during follow-up was an independent influencing factor for the increase of creatinine by more than 50%. (1) Proteinuria > 0.5g/d and eGFR < 90 mL/min/1.73 m2 may predict more severe pathological changes; (2) With the increase in age and baseline proteinuria, the risks of adverse endpoint events would increase significantly; (3) Pathology could roughly predict the adverse endpoint events but is less efficient than the clinical indicators; (4) Data during follow-up suggested that the patients should regularly test their renal function and proactively control their proteinuria. © 2018 The Author(s). Published by S. Karger AG, Basel.

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

Lung cancer incidence and survival among HIV-infected and uninfected women and men.

PubMed

Hessol, Nancy A; Martínez-Maza, Otoniel; Levine, Alexandra M; Morris, Alison; Margolick, Joseph B; Cohen, Mardge H; Jacobson, Lisa P; Seaberg, Eric C

2015-06-19

To determine the lung cancer incidence and survival time among HIV-infected and uninfected women and men. Two longitudinal studies of HIV infection in the United States. Data from 2549 women in the Women's Interagency HIV Study (WIHS) and 4274 men in the Multicenter AIDS Cohort Study (MACS), all with a history of cigarette smoking, were analyzed. Lung cancer incidence rates and incidence rate ratios were calculated using Poisson regression analyses. Survival time was assessed using Kaplan-Meier and Cox proportional-hazard analyses. Thirty-seven women and 23 men developed lung cancer (46 HIV-infected and 14 HIV-uninfected) during study follow-up. In multivariable analyses, the factors that were found to be independently associated with a higher lung cancer incidence rate ratios were older age, less education, 10 or more pack-years of smoking, and a prior diagnosis of AIDS pneumonia (vs. HIV-uninfected women). In an adjusted Cox model that allowed different hazard functions for each cohort, a history of injection drug use was associated with shorter survival, and a lung cancer diagnosis after 2001 was associated with longer survival. In an adjusted Cox model restricted to HIV-infected participants, nadir CD4 lymphocyte cell count less than 200 was associated with shorter survival time. Our data suggest that pulmonary damage and inflammation associated with HIV infection may be causative for the increased risk of lung cancer. Encouraging and assisting younger HIV-infected smokers to quit and to sustain cessation of smoking is imperative to reduce the lung cancer burden in this population.

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.

Real-world impact of non-breast cancer-specific death on overall survival in resectable breast cancer.

PubMed

Fu, Jianfei; Wu, Lunpo; Jiang, Mengjie; Li, Dan; Jiang, Ting; Fu, Wei; Wang, Liangjing; Du, Jinlin

2017-07-01

The real-world occurrence rate of non-breast cancer-specific death (non-BCSD) and its impact on patients with breast cancer are poorly recognized. Women with resectable breast cancer from 1990 to 2007 in the Surveillance, Epidemiology, and End Results database (n = 199,963) were analyzed. The outcome events of breast cancer were classified as breast cancer-specific death (BCSD), non-BCSD, or survival. Binary logistics was used to estimate the occurrence rates of non-BCSD and BCSD with different clinicopathological factors. The Gray method was used to measure the cumulative incidence of non-BCSD and BCSD. The ratio of non-BCSDs to all causes of death and stacked cumulative incidence function plots were used to present the impact of non-BCSD on overall survival (OS). Models of Cox proportional hazards regression and competing risk regression were compared to highlight the suitable model. There were 12,879 non-BCSDs (6.44%) and 28,784 BCSDs (14.39%). The oldest age group (>62 years), black race, and a single or divorced marital status were associated with more non-BCSDs. With adjustments for age, a hormone receptor-positive (HoR+) status was no longer related to increased non-BCSDs. In patients with grade 1, stage I disease and an HoR+ status as well as the oldest subgroup, a great dilution of non-BCSD on all causes of death could be observed, and this led to incorrect interpretations. The inaccuracy, caused by the commonly used Cox proportional hazards model, could be corrected by a competing risk model. OS was largely impaired by non-BCSD during early breast cancer. For some future clinical trial planning, especially for the oldest patients and those with HoR+ breast cancer, non-BCSD should be considered a competing risk event. Cancer 2017;123:2432-43. © 2017 American Cancer Society. © 2017 American Cancer Society.

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.

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.

Sudden cardiac death in non-dialysis chronic kidney disease patients.

PubMed

Caravaca, Francisco; Chávez, Edgar; Alvarado, Raúl; García-Pino, Guadalupe; Luna, Enrique

2016-01-01

A relatively high proportion of deaths in dialysis patients occur suddenly and unexpectedly. The incidence of sudden cardiac death (SCD) in non-dialysis advanced chronic kidney disease (CKD) stages has been less well investigated. This study aims to determine the incidence and predictors of SCD in a cohort of 1078 patients with CKD not yet on dialysis. Prospective observational cohort study, which included patients with advanced CKD not yet on dialysis (stage 4-5). The association between baseline variables and SCD was assessed using Cox and competing-risk (Fine and Grey) regression models. Demographic, clinical information, medication use, and baseline biochemical parameters of potential interest were included as covariates. During the study period (median follow-up time 12 months), 210 patients died (19%), and SCD occurred in 34 cases (16% of total deaths). All-cause mortality and SCD incidence rates were 113 (95% CI: 99-128), and 18 (95% CI: 13-26) events per 1000 patients/year, respectively. By Cox regression analysis, covariates significantly associated with SCD were: Age, comorbidity index, and treatment with antiplatelet drugs. This latter covariate showed a beneficial effect over the development of SCD. By competing-risk regression, in which the competing event was non-sudden death from any cause, only age and comorbidity index remained significantly associated with SCD. SCD is relatively common in non-dialysis advanced CKD patients. SCD was closely related to age and comorbidity, and some indirect data from this study suggest that unrecognised or undertreated cardiovascular disease may predispose to a higher risk of SCD. Copyright © 2016 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

A stratification approach using logit-based models for confounder adjustment in the study of continuous outcomes.

PubMed

Tan, Chuen Seng; Støer, Nathalie C; Chen, Ying; Andersson, Marielle; Ning, Yilin; Wee, Hwee-Lin; Khoo, Eric Yin Hao; Tai, E-Shyong; Kao, Shih Ling; Reilly, Marie

2017-01-01

The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.

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.

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

The comparison of landslide ratio-based and general logistic regression landslide susceptibility models in the Chishan watershed after 2009 Typhoon Morakot

NASA Astrophysics Data System (ADS)

WU, Chunhung

2015-04-01

The research built the original logistic regression landslide susceptibility model (abbreviated as or-LRLSM) and landslide ratio-based ogistic regression landslide susceptibility model (abbreviated as lr-LRLSM), compared the performance and explained the error source of two models. The research assumes that the performance of the logistic regression model can be better if the distribution of landslide ratio and weighted value of each variable is similar. Landslide ratio is the ratio of landslide area to total area in the specific area and an useful index to evaluate the seriousness of landslide disaster in Taiwan. The research adopted the landside inventory induced by 2009 Typhoon Morakot in the Chishan watershed, which was the most serious disaster event in the last decade, in Taiwan. The research adopted the 20 m grid as the basic unit in building the LRLSM, and six variables, including elevation, slope, aspect, geological formation, accumulated rainfall, and bank erosion, were included in the two models. The six variables were divided as continuous variables, including elevation, slope, and accumulated rainfall, and categorical variables, including aspect, geological formation and bank erosion in building the or-LRLSM, while all variables, which were classified based on landslide ratio, were categorical variables in building the lr-LRLSM. Because the count of whole basic unit in the Chishan watershed was too much to calculate by using commercial software, the research took random sampling instead of the whole basic units. The research adopted equal proportions of landslide unit and not landslide unit in logistic regression analysis. The research took 10 times random sampling and selected the group with the best Cox & Snell R2 value and Nagelkerker R2 value as the database for the following analysis. Based on the best result from 10 random sampling groups, the or-LRLSM (lr-LRLSM) is significant at the 1% level with Cox & Snell R2 = 0.190 (0.196) and Nagelkerke R2 = 0.253 (0.260). The unit with the landslide susceptibility value > 0.5 (≦ 0.5) will be classified as a predicted landslide unit (not landslide unit). The AUC, i.e. the area under the relative operating characteristic curve, of or-LRLSM in the Chishan watershed is 0.72, while that of lr-LRLSM is 0.77. Furthermore, the average correct ratio of lr-LRLSM (73.3%) is better than that of or-LRLSM (68.3%). The research analyzed in detail the error sources from the two models. In continuous variables, using the landslide ratio-based classification in building the lr-LRLSM can let the distribution of weighted value more similar to distribution of landslide ratio in the range of continuous variable than that in building the or-LRLSM. In categorical variables, the meaning of using the landslide ratio-based classification in building the lr-LRLSM is to gather the parameters with approximate landslide ratio together. The mean correct ratio in continuous variables (categorical variables) by using the lr-LRLSM is better than that in or-LRLSM by 0.6 ~ 2.6% (1.7% ~ 6.0%). Building the landslide susceptibility model by using landslide ratio-based classification is practical and of better performance than that by using the original logistic regression.

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.

A prospective 10-year study of metal ceramic single crowns and fixed dental prosthesis retainers in private practice settings.

PubMed

Reitemeier, Bernd; Hänsel, Kristina; Kastner, Christian; Weber, Anke; Walter, Michael H

2013-03-01

Metal ceramic restorations are widely used in prosthodontics, but long-term data on their clinical performance in private practice settings based on prospective trials are sparse. This clinical trial was designed to provide realistic long-term survival rates for different outcomes related to tooth loss, crown loss, and metal ceramic defect. Ninety-five participants were provided with 190 noble metal ceramic single crowns and 138 participants with 276 fixed dental prosthesis retainer crowns on vital posterior teeth. Follow-up examinations were scheduled 2 weeks after insertion, annually up to 8 years, and after 10 years. Kaplan-Meier survival analyses, Mantel-Cox logrank tests, and Cox regression analyses were conducted. Because of variations in the time of the last examinations, the maximum observation period was 12.1 years. For the primary outcome 'loss of crown or tooth', the Kaplan-Meier survival rate was 94.3% ±1.8% (standard error) at 8.0 years (last outcome event) for single crowns and 94.4% ±1.5% at 11.0 years for fixed dental prosthesis retainer crowns. The difference between the survival functions was not significant (P>.05). For the secondary outcome 'metal ceramic defect', the survival rate was 88.8% ±3.2% at 11.0 years for single crowns and 81.7% ±3.5% at 11.0 years for fixed dental prosthesis retainer crowns. In Cox regression models, the only significant covariates for the outcome event 'metal ceramic defect' were bruxism in the medical history (single crowns) and signs and symptoms of bruxism (fixed dental prosthesis retainer crowns) with hazard ratios of 3.065 (95% CI 1.063 - 8.832) and 2.554 (95% CI 1.307 - 4.992). Metal ceramic crowns provided in private practice settings show good longevity. Bruxism appears to indicate a risk for metal ceramic defects. Copyright © 2013 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

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.

Sparse kernel methods for high-dimensional survival data.

PubMed

Evers, Ludger; Messow, Claudia-Martina

2008-07-15

Sparse kernel methods like support vector machines (SVM) have been applied with great success to classification and (standard) regression settings. Existing support vector classification and regression techniques however are not suitable for partly censored survival data, which are typically analysed using Cox's proportional hazards model. As the partial likelihood of the proportional hazards model only depends on the covariates through inner products, it can be 'kernelized'. The kernelized proportional hazards model however yields a solution that is dense, i.e. the solution depends on all observations. One of the key features of an SVM is that it yields a sparse solution, depending only on a small fraction of the training data. We propose two methods. One is based on a geometric idea, where-akin to support vector classification-the margin between the failed observation and the observations currently at risk is maximised. The other approach is based on obtaining a sparse model by adding observations one after another akin to the Import Vector Machine (IVM). Data examples studied suggest that both methods can outperform competing approaches. Software is available under the GNU Public License as an R package and can be obtained from the first author's website http://www.maths.bris.ac.uk/~maxle/software.html.

Malignant Peritoneal Mesothelioma: Prognostic Factors and Oncologic Outcome Analysis

PubMed Central

Magge, Deepa; Zenati, Mazen S.; Austin, Frances; Mavanur, Arun; Sathaiah, Magesh; Ramalingam, Lekshmi; Jones, Heather; Zureikat, Amer H.; Holtzman, Matthew; Ahrendt, Steven; Pingpank, James; Zeh, Herbert J.; Bartlett, David L.; Choudry, Haroon A.

2014-01-01

Background Most patients with malignant peritoneal mesothelioma (MPM) present with late-stage, unresectable disease that responds poorly to systemic chemotherapy while, at the same time, effective targeted therapies are lacking. We assessed the efficacy of cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemoperfusion (HIPEC) in MPM. Methods We prospectively analyzed 65 patients with MPM undergoing CRS/HIPEC between 2001 and 2010. Kaplan–Meier survival curves and multivariate Cox-regression models identified prognostic factors affecting oncologic outcomes. Results Adequate CRS was achieved in 56 patients (CC-0 = 35; CC-1 = 21), and median simplified peritoneal cancer index (SPCI) was 12. Pathologic assessment revealed predominantly epithelioid histology (81 %) and biphasic histology (8 %), while lymph node involvement was uncommon (8 %). Major postoperative morbidity (grade III/IV) occurred in 23 patients (35 %), and 60-day mortality rate was 6 %. With median follow-up of 37 months, median overall survival was 46.2 months, with 1-, 2-, and 5-year overall survival probability of 77, 57, and 39 %, respectively. Median progression-free survival was 13.9 months, with 1-, 2-, and 5-year disease failure probability of 47, 68, and 83 %, respectively. In a multivariate Cox-regression model, age at surgery, SPCI >15, incomplete cytoreduction (CC-2/3), aggressive histology (epithelioid, biphasic), and postoperative sepsis were joint significant predictors of poor survival (chi square = 42.8; p = 0.00001), while age at surgery, SPCI >15, incomplete cytoreduction (CC-2/3), and aggressive histology (epithelioid, biphasic) were joint significant predictors of disease progression (Chi square = 30.6; p = 0.00001). Conclusions Tumor histology, disease burden, and the ability to achieve adequate surgical cytoreduction are essential prognostic factors in MPM patients undergoing CRS/HIPEC. PMID:24322529

Physiological growth hormone replacement and rate of recurrence of craniopharyngioma: the Genentech National Cooperative Growth Study.

PubMed

Smith, Timothy R; Cote, David J; Jane, John A; Laws, Edward R

2016-10-01

OBJECTIVE The object of this study was to establish recurrence rates in patients with craniopharyngioma postoperatively treated with recombinant human growth hormone (rhGH) as a basis for determining the risk of rhGH therapy in the development of recurrent tumor. METHODS The study included 739 pediatric patients with craniopharyngioma who were naïve to GH upon entering the Genentech National Cooperative Growth Study (NCGS) for treatment. Reoperation for tumor recurrence was documented as an adverse event. Cox proportional-hazards regression models were developed for time to recurrence, using age as the outcome and enrollment date as the predictor. Patients without recurrence were treated as censored. Multivariate logistic regression was used to examine the incidence of recurrence with adjustment for the amount of time at risk. RESULTS Fifty recurrences in these 739 surgically treated patients were recorded. The overall craniopharyngioma recurrence rate in the NCGS was 6.8%, with a median follow-up time of 4.3 years (range 0.7-6.4 years.). Age at the time of study enrollment was statistically significant according to both Cox (p = 0.0032) and logistic (p < 0.001) models, with patients under 9 years of age more likely to suffer recurrence (30 patients [11.8%], 0.025 recurrences/yr of observation, p = 0.0097) than those ages 9-13 years (17 patients [6.0%], 0.17 recurrences/yr of observation) and children older than 13 years (3 patients [1.5%], 0.005 recurrences/yr of observation). CONCLUSIONS Physiological doses of GH do not appear to increase the recurrence rate of craniopharyngioma after surgery in children, but long-term follow-up of GH-treated patients is required to establish a true natural history in the GH treatment era.

The effect of green tea extract supplementation on sputum smear conversion and weight changes in pulmonary TB patients: A randomized controlled trial

PubMed Central

Honarvar, Mohammad Reza; Eghtesadi, Shahryar; Gill, Pooria; Jazayeri, Shima; Vakili, Mohammad Ali; Shamsardekani, Mohammad Reza; Abbasi, Abdollah

2016-01-01

Background: Acceleration in sputum smear conversion helps faster improvement and decreased probability of the transfer of TB. In this study, we aimed to investigate the effect of green tea extract supplementation on sputum smear conversion and weight changes in smear positive pulmonary TB patients in Iran. Methods: In this double blind clinical study, TB patients were divided into intervention, (n=43) receiving 500 mg green tea extract (GTE), and control groups (n=40) receiving placebo for two months, using balanced randomization. Random allocation and allocation concealment were observed. Height and weight were measured at the beginning, and two and six months post-treatment. Evaluations were performed on three slides, using the ZiehlNeelsen method. Independent and paired t test, McNemar’s, Wilcoxon, Kaplan-Meier, Cox regression model and Log-Rank test were utilized. Statistical significance was set at p<0.05. This trial was registered under IRCT201212232602N11. Results: The interventional changes and the interactive effect of intervention on weight were not significant (p>0.05). In terms of shortening the duration of conversion, the case to control proportion showed a significant difference (p=0.032). Based on the Cox regression model, the hazard ratio of the relative risk of delay in sputum smear conversion was 3.7 (p=0.002) in the higher microbial load group compared to the placebo group and 0.54 (95% CI: 0.31-0.94) in the intervention compared to the placebo group. Conclusion: GTE decreases the risk of delay in sputum smear conversion, but has no effect on weight gain. Moreover, it may be used as an adjuvant therapy for faster rehabilitation for pulmonary TB patients. PMID:27493925

The IFNL3/4 ΔG variant increases susceptibility to cytomegalovirus retinitis among HIV-infected patients.

PubMed

Bibert, Stéphanie; Wojtowicz, Agnieszka; Taffé, Patrick; Manuel, Oriol; Bernasconi, Enos; Furrer, Hansjakob; Günthard, Huldrych F; Hoffmann, Matthias; Kaiser, Laurent; Osthoff, Michael; Cavassini, Matthias; Bochud, Pierre-Yves

2014-08-24

Cytomegalovirus (CMV) retinitis is a major cause of visual impairment and blindness among patients with uncontrolled HIV infections. Whereas polymorphisms in interferon-lambda 3 (IFNL3, previously named IL28B) strongly influence the clinical course of hepatitis C, few studies examined the role of such polymorphisms in infections due to viruses other than hepatitis C virus. To analyze the association of newly identified IFNL3/4 variant rs368234815 with susceptibility to CMV-associated retinitis in a cohort of HIV-infected patients. This retrospective longitudinal study included 4884 white patients from the Swiss HIV Cohort Study, among whom 1134 were at risk to develop CMV retinitis (CD4 nadir < 00 /μl and positive CMV serology). The association of CMV-associated retinitis with rs368234815 was assessed by cumulative incidence curves and multivariate Cox regression models, using the estimated date of HIV infection as a starting point, with censoring at death and/or lost follow-up. A total of 40 individuals among 1134 patients at risk developed CMV retinitis. The minor allele of rs368234815 was associated with a higher risk of CMV retinitis (log-rank test P = 0.007, recessive mode of inheritance). The association was still significant in a multivariate Cox regression model (hazard ratio 2.31, 95% confidence interval 1.09-4.92, P = 0.03), after adjustment for CD4 nadir and slope, HAART and HIV-risk groups. We reported for the first time an association between an IFNL3/4 polymorphism and susceptibility to AIDS-related CMV retinitis. IFNL3/4 may influence immunity against viruses other than HCV.

Reformed smokers have survival benefits after head and neck cancer.

PubMed

Cao, Wei; Liu, Zheqi; Gokavarapu, Sandhya; Chen, YiMing; Yang, Rong; Ji, Tong

2016-09-01

Smoking tobacco is the main risk factor for head and neck cancer, is proportional to the number of pack years (number of packs smoked/day x number of years of smoking), and is reduced when the patient stops smoking. Current molecular evidence has suggested that tobacco-related cancers could be clinically more aggressive than cancers in non-smokers, particularly in the head and neck. However, clinical studies have not uniformly reproduced the relation between survival and tobacco, possibly because they ignore the health benefit that reformed smokers obtain during the period between giving up smoking and the diagnosis of cancer, which is not shared by those who continue to smoke and develop cancer. We have investigated the survival of reformed smokers, non-smokers, and continuing smokers after a diagnosis of head and neck cancer. The data of patients with head and neck cancer from 1992 -2013 from the Cancer Genome Atlas database were analysed using a multivariate Cox's regression model for survival, and Kaplan-Meier curves were produced for smoking history. A total of 521 patients were treated for head and neck cancer, and there was a significant difference in survival between reformed and non-smokers on the one hand, and current smokers on the other (p=0.02). The significance increased when reformed smokers were grouped according to their duration of abstinence and time of diagnosis of cancer (>15 and ≤15 years, p<0.01). Smoking history was a significant prognostic factor in the multivariate Cox's regression model when analysed with age, stage, grade, and site. We conclude that reformed smokers have a survival benefit in head and neck cancer. Copyright © 2016 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

No evidence of a causal relationship between hypothyroidism and glaucoma: A Danish nationwide register-based cohort study

PubMed Central

2018-01-01

Background An interrelationship between hypothyroidism and glaucoma, due to a shared autoimmune background or based on deposition of mucopolysaccharides in the trabecular meshwork in the eye, has been suggested but is at present unsubstantiated. Therefore, our objective was to investigate, at a nationwide and population-based level, whether there is such an association. Subjects and methods Observational cohort study using record-linkage data from nationwide Danish health registers. 121,799 individuals diagnosed with a first episode of hypothyroidism were identified and were matched with 4 non-hypothyroid controls according to age and sex. Prevalence of glaucoma was recorded and cases and controls were followed over a mean of 7.1 years (range 0–17). Logistic and Cox regression models were used to assess the risk of glaucoma before and after the diagnosis of hypothyroidism, respectively. Results Overall, we found a higher prevalence of glaucoma in subjects with hypothyroidism as compared to controls (4.6% vs. 4.3%, p < 0.001). Prior to the diagnosis of hypothyroidism, the odds ratio (OR) was significantly increased for glaucoma [1.09; 95% confidence interval (CI): 1.04–1.13]. Based on the Cox regression model, there was no increased risk of glaucoma after the diagnosis of hypothyroidism [hazard ratio (HR) 1.00; 95% CI: 0.96–1.06], and the HR decreased further after adjusting for pre-existing co-morbidity (0.88; 95% CI: 0.84–0.93). Conclusions There was an increased risk of glaucoma before but not after the diagnosis of hypothyroidism, suggesting that screening for glaucoma in hypothyroid individuals is unwarranted. PMID:29444121

The effect of preexisting respiratory co-morbidities on burn outcomes☆

PubMed Central

Knowlin, Laquanda T.; Stanford, Lindsay B.; Cairns, Bruce A.; Charles, Anthony G.

2018-01-01

Introduction Burns cause physiologic changes in multiple organ systems in the body. Burn mortality is usually attributable to pulmonary complications, which can occur in up to 41% of patients admitted to the hospital after burn. Patients with preexisting comorbidities such as chronic lung diseases may be more susceptible. We therefore sought to examine the impact of preexisting respiratory disease on burn outcomes. Methods A retrospective analysis of patients admitted to a regional burn center from 2002–2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA, pre-existing comorbidities, smoker status, length of hospital stay, and days of mechanical ventilation. Bivariate analysis was performed and Cox regression modeling using significant variables was utilized to estimate hazard of progression to mechanical ventilation and mortality. Results There were a total of 7640 patients over the study period. Overall survival rate was 96%. 8% (n=672) had a preexisting respiratory disease. Chronic lung disease patients had a higher mortality rate (7%) compared to those without lung disease (4%, p<0.01). The adjusted Cox regression model to estimate the hazard of progression to mechanical ventilation in patients with respiratory disease was 21% higher compared to those without respiratory disease (HR=1.21, 95% CI=1.01–1.44). The hazard of progression to mortality is 56% higher (HR=1.56, 95% CI=1.10–2.19) for patients with pre-existing respiratory disease compared to those without respiratory disease after controlling for patient demographics and injury characteristics. Conclusion Preexisting chronic respiratory disease significantly increases the hazard of progression to mechanical ventilation and mortality in patients following burn. Given the increasing number of Americans with chronic respiratory diseases, there will likely be a greater number of individuals at risk for worse outcomes following burn. PMID:28341260

The effect of preexisting respiratory co-morbidities on burn outcomes.

PubMed

Knowlin, Laquanda T; Stanford, Lindsay B; Cairns, Bruce A; Charles, Anthony G

2017-03-01

Burns cause physiologic changes in multiple organ systems in the body. Burn mortality is usually attributable to pulmonary complications, which can occur in up to 41% of patients admitted to the hospital after burn. Patients with preexisting comorbidities such as chronic lung diseases may be more susceptible. We therefore sought to examine the impact of preexisting respiratory disease on burn outcomes. A retrospective analysis of patients admitted to a regional burn center from 2002-2012. Independent variables analyzed included basic demographics, burn mechanism, presence of inhalation injury, TBSA, pre-existing comorbidities, smoker status, length of hospital stay, and days of mechanical ventilation. Bivariate analysis was performed and Cox regression modeling using significant variables was utilized to estimate hazard of progression to mechanical ventilation and mortality. There were a total of 7640 patients over the study period. Overall survival rate was 96%. 8% (n=672) had a preexisting respiratory disease. Chronic lung disease patients had a higher mortality rate (7%) compared to those without lung disease (4%, p<0.01). The adjusted Cox regression model to estimate the hazard of progression to mechanical ventilation in patients with respiratory disease was 21% higher compared to those without respiratory disease (HR=1.21, 95% CI=1.01-1.44). The hazard of progression to mortality is 56% higher (HR=1.56, 95% CI=1.10-2.19) for patients with pre-existing respiratory disease compared to those without respiratory disease after controlling for patient demographics and injury characteristics. Preexisting chronic respiratory disease significantly increases the hazard of progression to mechanical ventilation and mortality in patients following burn. Given the increasing number of Americans with chronic respiratory diseases, there will likely be a greater number of individuals at risk for worse outcomes following burn. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.

A Questionnaire-Wide Association Study of Personality and Mortality: The Vietnam Experience Study

PubMed Central

Weiss, Alexander; Gale, Catharine R.; Batty, G. David; Deary, Ian J.

2013-01-01

Objective We examined the association between the Minnesota Multiphasic Personality Inventory (MMPI) and all-cause mortality in 4462 middle-aged Vietnam-era veterans. Methods We split the study population into half samples. In each half, we used proportional hazards (Cox) regression to test the 550 MMPI items’ associations with mortality over 15 years. In all participants, we subjected significant (p < .01) items in both halves to principal-components analysis (PCA). We used Cox regression to test whether these components predicted mortality when controlling for other predictors (demographics, cognitive ability, health behaviors, mental/physical health). Results Eighty-nine items were associated with mortality in both half-samples. PCA revealed Neuroticism/Negative Affectivity, Somatic Complaints, Psychotic/Paranoia, and Antisocial components, and a higher-order component, Personal Disturbance. Individually, Neuroticism/Negative Affectivity (HR = 1.55, 95% CI = 1.39,1.72), Somatic Complaints (HR = 1.66; 95% CI = 1.52,1.80), Psychotic/Paranoid (HR = 1.44; 95% CI = 1.32,1.57), Antisocial (HR = 1.79; 95% CI = 1.59,2.01), and Personal Disturbance (HR = 1.74; 95% CI = 1.58,1.91) were associated with risk. Including covariates attenuated these associations (28.4 to 54.5%), though they were still significant. After entering Personal Disturbance into models with each component, Neuroticism/Negative Affectivity and Somatic Complaints were significant, although Neuroticism/Negative Affectivity’s were now protective (HR = 0.73, 95% CI = 0.58,0.92). When the four components were entered together with or without covariates, Somatic Complaints and Antisocial were significant risk factors. Conclusions Somatic Complaints and Personal Disturbance are associated with increased mortality risk. Other components’ effects varied as a function of variables in the model. PMID:23731751

Genetic polymorphisms in pre-miRNAs predict the survival of non-small-cell lung cancer in Chinese population: a cohort study and a meta-analysis

PubMed Central

Xia, Lingzi; Yin, Zhihua; Li, Xuelian; Ren, Yangwu; Zhang, Haibo; Zhao, Yuxia; Zhou, Baosen

2017-01-01

Background To explore the association of genetic polymorphisms in pre-miRNA 30c-1 rs928508 and pre-miRNA 27a rs895819 with non-small-cell lung cancer prognosis. Materials and Methods 480 patients from five hospitals were enrolled in this prospective cohort study. They were followed up for five years. The association between genotypes and overall survival was assessed by Cox proportional hazards regression models. A meta-analysis was conducted to provide evidence for the effect of microRNA 27a rs895819 on cancer survival. Results G-allele containing genotypes of microRNA 30c-1 polymorphisms and C-allele containing genotypes of microRNA 27a were significantly associated with poorer overall survival. Multivariate Cox regression models indicated that these genetic polymorhpisms were independently predictive factors of poorer overall survival. In stratified analysis, the effect was observed in many strata. The significant joint effect was also observed in our study. Patients with G allele of microRNA 30c-1 rs928508 and C allele of microRNA 27a rs895819 had the poorer overall survival than patients with C allele of rs928508 and T allele of rs895819. The effect of the microRNA 27a rs895819 on non-small cell lung cancer overall survival was supported by the meta-analysis results. Conclusions The two single nucleotide polymorphisms in microRNA 30c-1 and microRNA 27a can predict the outcome of non-small cell lung cancer patients and they may decrease the sensitivity to anti-cancer drugs. PMID:29100439

Place of upbringing in early childhood as related to inflammatory bowel diseases in adulthood: a population-based cohort study in Northern Europe.

PubMed

Timm, Signe; Svanes, Cecilie; Janson, Christer; Sigsgaard, Torben; Johannessen, Ane; Gislason, Thorarinn; Jogi, Rain; Omenaas, Ernst; Forsberg, Bertil; Torén, Kjell; Holm, Mathias; Bråbäck, Lennart; Schlünssen, Vivi

2014-06-01

The two inflammatory bowel diseases (IBD), ulcerative colitis and Crohn's disease, has increased rapidly during the twentieth century, but the aetiology is still poorly understood. Impaired immunological competence due to decreasing biodiversity and altered microbial stimulation is a suggested explanation. Place of upbringing was used as a proxy for the level and diversity of microbial stimulation to investigate the effects on the prevalence of IBD in adulthood. Respiratory Health in Northern Europe (RHINE) III is a postal follow-up questionnaire of the European Community Respiratory Health Survey (ECRHS) cohorts established in 1989-1992. The study population was 10,864 subjects born 1945-1971 in Denmark, Norway, Sweden, Iceland and Estonia, who responded to questionnaires in 2000-2002 and 2010-2012. Data were analysed in logistic and Cox regression models taking age, sex, smoking and body mass index into consideration. Being born and raised on a livestock farm the first 5 years of life was associated with a lower risk of IBD compared to city living in logistic (OR 0.54, 95 % CI 0.31; 0.94) and Cox regression models (HR 0.55, 95 % CI 0.31; 0.98). Random-effect meta-analysis did not identify geographical difference in this association. Furthermore, there was a significant trend comparing livestock farm living, village and city living (p < 0.01). Sub-analyses showed that the protective effect was only present among subjects born after 1952 (OR 0.25, 95 % CI 0.11; 0.61). This study suggests a protective effect from livestock farm living in early childhood on the occurrence of IBD in adulthood, however only among subjects born after 1952. We speculate that lower microbial diversity is an explanation for the findings.

Stress Hyperglycemia and Prognosis of Minor Ischemic Stroke and Transient Ischemic Attack: The CHANCE Study (Clopidogrel in High-Risk Patients With Acute Nondisabling Cerebrovascular Events).

PubMed

Pan, Yuesong; Cai, Xueli; Jing, Jing; Meng, Xia; Li, Hao; Wang, Yongjun; Zhao, Xingquan; Liu, Liping; Wang, David; Johnston, S Claiborne; Wei, Tiemin; Wang, Yilong

2017-11-01

We aimed to determine the association between stress hyperglycemia and risk of new stroke in patients with a minor ischemic stroke or transient ischemic attack. A subgroup of 3026 consecutive patients from 73 prespecified sites of the CHANCE trial (Clopidogrel in High-Risk Patients With Acute Nondisabling Cerebrovascular Events) were analyzed. Stress hyperglycemia was measured by glucose/glycated albumin (GA) ratio. Glucose/GA ratio was calculated by fasting plasma glucose divided by GA and categorized into 4 even groups according to the quartiles. The primary outcome was a new stroke (ischemic or hemorrhagic) at 90 days. We assessed the association between glucose/GA ratio and risk of stroke by multivariable Cox regression models adjusted for potential covariates. Among 3026 patients included, a total of 299 (9.9%) new stroke occurred at 3 months. Compared with patients with the lowest quartile, patients with the highest quartile of glucose/GA ratio was associated with an increased risk of stroke at 3 months after adjusted for potential covariates (12.0% versus 9.2%; adjusted hazard ratio, 1.46; 95% confidence interval, 1.06-2.01). Similar results were observed after further adjusted for fasting plasma glucose. We also observed that higher level of glucose/GA ratio was associated with an increased risk of stroke with a threshold of 0.29 using a Cox regression model with restricted cubic spline. Stress hyperglycemia, measured by glucose/GA ratio, was associated with an increased risk of stroke in patients with a minor ischemic stroke or transient ischemic attack. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00979589. © 2017 American Heart Association, Inc.

Adiponectin and Mortality in Smokers and Non-Smokers of the Ludwigshafen Risk and Cardiovascular Health (LURIC) Study.

PubMed

Delgado, Graciela E; Siekmeier, Rüdiger; März, Winfried; Kleber, Marcus E

2016-01-01

Cardiovascular diseases (CVD) are an important cause of morbidity and mortality worldwide. A decreased concentration of adiponectin has been reported in smokers. The aim of this study was to analyze the effect of cigarette smoking on the concentration of adiponectin and potassium in active smokers (AS) and life-time non-smokers (NS) of the Ludwigshafen Risk and Cardiovascular Health (LURIC) Study, and the use of these two markers for risk prediction. Smoking status was assessed by a questionnaire and measurement of plasma cotinine concentration. The serum concentration of adiponectin was measured by ELISA. Adiponectin was binned into tertiles separately for AS and NS and the Cox regression was used to assess the effect on mortality. There were 777 AS and 1178 NS among the LURIC patients. Within 10 years (median) of follow-up 221 AS and 302 NS died. In unadjusted analyses, AS had lower concentrations of adiponectin. However, after adjustment for age and gender there was no significant difference in adiponectin concentration between AS and NS. In the Cox regression model adjusted for age and gender, adiponectin was significantly associated with mortality in AS, but not in NS, with hazard ratio (95 % CI) of 1.60 (1.14-2.24) comparing the third with first tertile. In a model further adjusted for the risk factors, such as diabetes mellitus, hypertension, coronary artery disease, body mass index, LDL-cholesterol and HDL-cholesterol, adiponectin was significantly associated with mortality with hazard ratio of 1.83 (1.28-2.62) and 1.56 (1.15-2.11) for AS and NS, respectively. We conclude that increased adiponectin is a strong and independent predictor of mortality in both AS and NS. The determination of adiponectin concentration could be used to identify individuals at increased mortality risk.

Knowledge of HIV seropositivity is a predictor for initiation of illicit drug use: incidence of drug use initiation among female sex workers in a high HIV-prevalence area of China

PubMed Central

Wang, Haibo; Brown, Katherine S.; Wang, Guixiang; Ding, Guowei; Zang, Chunpeng; Wang, Junjie; Reilly, Kathleen H.; Chen, Helen; Wang, Ning

2012-01-01

Background Drug use and sex work have had facilitative roles in the transmission of HIV/AIDS in China. Stopping drug use among sex workers may help to control the growth of the HIV/AIDS epidemic among Chinese sex workers. Methods From March 2006 to November 2009, female sex workers (FSW) in Kaiyuan City, Yunnan, China were recruited into an open cohort study. Participants were interviewed and tested for drug use and HIV/sexually transmitted infection (STI) prevalence. Follow-up surveys were conducted every six months. Multivariate Cox proportional hazards regression model with time dependent variables was used to measure the associations between independent variables and drug initiation. Results During the course of the study, 66 (8.8%) FSWs initiated drug use yielding an overall incidence of 6.0 per 100 person years (PY) (95% confidence interval [CI], 4.67–7.58). In the multivariate Cox proportional hazards regression model, being HIV-positive and aware of positive serostatus (adjusted hazard ratio [AHR] 2.6, 95% CI 1.24–5.55), age at initiation of commercial sex work <20 years (AHR 1.8, 95% CI 1.12–3.01), and working in a high-risk establishment (AHR 1.9, 95% CI 1.14–3.04) were associated with illicit drug initiation. Conclusions Being HIV-positive and aware of positive serostatus was the most salient predictor for the initiation of illicit drug use. Interventions offering sources of education, treatment, support, and counseling to HIV-positive FSWs need to be implemented in order to help promote self-efficacy and safe behaviors among this group of high-risk women. PMID:21402453

Impact of neonatal intensive care bed configuration on rates of late-onset bacterial sepsis and methicillin-resistant Staphylococcus aureus colonization

PubMed Central

Julian, Samuel; Burnham, Carey-Ann D.; Sellenriek, Patricia; Shannon, William D.; Hamvas, Aaron; Tarr, Phillip I.; Warner, Barbara B.

2016-01-01

Objectives Infections cause significant morbidity and mortality in neonatal intensive care units (NICUs). The association between nursery design and nosocomial infections has not been delineated. We hypothesized that rates of colonization by methicillin-resistant Staphylococcus aureus (MRSA), late-onset sepsis, and mortality are reduced in single-patient rooms. Design Retrospective cohort study. Setting NICU in a tertiary referral center. Methods Our NICU is organized into single-patient and open-unit rooms. Clinical datasets including bed location and microbiology results were examined over a 29-month period. Differences in outcomes between bed configurations were determined by Chi-square and Cox regression. Patients All NICU patients. Results Among 1823 patients representing 55,166 patient-days, single-patient and open-unit models had similar incidences of MRSA colonization and MRSA colonization-free survival times. Average daily census was associated with MRSA colonization rates only in single-patient rooms (hazard ratio 1.31, p=0.039), while hand hygiene compliance on room entry and exit was associated with lower colonization rates independent of bed configuration (hazard ratios 0.834 and 0.719 per 1% higher compliance, respectively). Late-onset sepsis rates were similar in single-patient and open-unit models as were sepsis-free survival and the combined outcome of sepsis or death. After controlling for demographic, clinical and unit-based variables, multivariate Cox regression demonstrated that bed configuration had no effect on MRSA colonization, late-onset sepsis, or mortality. Conclusions MRSA colonization rate was impacted by hand hygiene compliance, regardless of room configuration, while average daily census only affected infants in single-patient rooms. Single-patient rooms did not reduce the rates of MRSA colonization, late-onset sepsis or death. PMID:26108888

Herpes zoster correlates with increased risk of Parkinson's disease in older people

PubMed Central

Lai, Shih-Wei; Lin, Chih-Hsueh; Lin, Hsien-Feng; Lin, Cheng-Li; Lin, Cheng-Chieh; Liao, Kuan-Fu

2017-01-01

Abstract Little is known on the relationship between herpes zoster and Parkinson's disease in older people. This study aimed to explore whether herpes zoster could be associated with Parkinson's disease in older people in Taiwan. We conducted a retrospective cohort study using the claim data of the Taiwan National Health Insurance Program. There were 10,296 subjects aged 65 years and older with newly diagnosed herpes zoster as the herpes zoster group and 39,405 randomly selected subjects aged 65 years and older without a diagnosis of herpes zoster as the nonherpes zoster group from 1998 to 2010. Both groups were followed up until subjects received a diagnosis of Parkinson's disease. This follow-up design would explore whether subjects with herpes zoster were at an increased risk of Parkinson's disease. Relative risks were estimated by adjusted hazard ratio (HR) and 95% confidence interval (CI) using the multivariable Cox proportional hazards regression model. The incidence of Parkinson's disease was higher in the herpes zoster group than that in the nonherpes zoster group (4.86 vs 4.00 per 1000 person-years, 95% CI 1.14, 1.29). After adjustment for confounding factors, the multivariable Cox proportional hazards regression model revealed that the adjusted HR of Parkinson's disease was 1.17 for the herpes zoster group (95% CI 1.10, 1.25), compared with the nonherpes zoster group. Older people with herpes zoster confer a slightly increased hazard of developing Parkinson's disease when compared to those without herpes zoster. We think that herpes zoster correlates with increased risk of Parkinson's disease in older people. When older people with herpes zoster seek help, clinicians should pay more attention to the development of the cardinal symptoms of Parkinson's disease. PMID:28207515

Aggressive Management of Peritoneal Carcinomatosis from Mucinous Appendiceal Neoplasms

PubMed Central

Austin, Frances; Mavanur, Arun; Sathaiah, Magesh; Steel, Jennifer; Lenzner, Diana; Ramalingam, Lekshmi; Holtzman, Matthew; Ahrendt, Steven; Pingpank, James; Zeh, Herbert J.; Bartlett, David L.; Choudry, Haroon A.

2014-01-01

Background Peritoneal carcinomatosis (PC) in the setting of mucinous appendiceal neoplasms is characterized by the intraperitoneal accumulation of mucinous ascites and mucin-secreting epithelial cells that leads to progressive compression of intra-abdominal organs, morbidity, and eventual death. We assessed postoperative and oncologic outcomes after aggressive surgical management by experienced surgeons. Methods We analyzed clinicopathologic, perioperative, and oncologic outcome data in 282 patients with PC from appendiceal adenocarcinomas between 2001 and 2010 from a prospective database. Kaplan–Meier survival curves and multivariate Cox-regression models were used to identify prognostic factors affecting oncologic outcomes. Results Adequate cytoreduction was achieved in 82% of patients (completeness of cytoreduction score (CC)-0: 49%; CC-1: 33%). Median simplified peritoneal cancer index (SPCI), operative time, and estimated blood loss were 14 (range, 0–21), 483.5 min (range, 46–1,402), and 800 ml (range, 0–14,000), respectively. Pathology assessment demonstrated high-grade tumors in 36% of patients and lymph node involvement in 23% of patients. Major postoperative morbidity occurred in 70 (25%) patients. Median overall survival was 6.72 years (95% confidence interval (CI), 4.17 years not reached), with 5 year overall survival probability of 52.7% (95% CI, 42.4, 62%). In a multivariate Cox-regression model, tumor grade, age, preoperative SPCI and chemo-naïve status at surgery were joint significant predictors of overall survival. Tumor grade, postoperative CC-score, prior chemotherapy, and preoperative SPCI were joint significant predictors of time to progression. Conclusions Aggressive management of PC from mucinous appendiceal neoplasms, by experienced surgeons, to achieve complete cytoreduction provides long-term survival with low major morbidity. PMID:22302270

Long-term pediatric skin eruption-related hospitalizations in offspring conceived via fertility treatment.

PubMed

Krieger, Yuval; Wainstock, Tamar; Sheiner, Eyal; Harlev, Avi; Landau, Daniella; Horev, Amir; Bogdanov-Berezovsky, Alexander; Walfisch, Asnat

2018-03-01

Although concerns have been raised regarding the long-term health risks of offspring conceived following fertility treatments, limited information is available regarding their health status beyond the neonatal period. We aimed to evaluate the risk of long-term eruptive dermatological morbidity among children born following fertility treatments as compared to those conceived spontaneously. A population-based cohort study was conducted, including all singleton deliveries occurring between the years 1991 and 2014 at a single tertiary medical center. Fetuses with congenital malformations and multiple gestations were excluded. Children delivered following fertility treatment pregnancies and spontaneous pregnancies were compared. Hospitalizations of the offspring up to the age of 18 years involving cutaneous eruptions were evaluated. A Kaplan-Meier survival curve was used to compare cumulative morbidity incidence and a Cox regression model to control for confounders. During the study period, 242,187 singleton deliveries met the inclusion criteria, 1.8% of which were following fertility treatments (n = 4324). Eruptive dermatological morbidity of the offspring up to the age of 18 years was significantly more common in the fertility treatment group (1.5%) as compared to spontaneous pregnancies (1.1%; P = 0.023). The Kaplan-Meier survival curve demonstrated a significantly higher cumulative incidence of eruptive dermatological morbidity following fertility treatments (log-rank P = 0.007). Using the Cox regression model, while controlling for multiple confounders, fertility treatment was noted as an independent risk factor for long-term pediatric eruptive dermatological morbidity (adjusted HR = 1.43, CI 1.12-1.83, P = 0.004). Singletons conceived via fertility treatments appear to be at an increased risk for long-term eruptive dermatological morbidity. © 2018 The International Society of Dermatology.

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.

Nosocomial colonization due to imipenem-resistant Pseudomonas aeruginosa epidemiologically linked to breast milk feeding in a neonatal intensive care unit.

PubMed

Mammina, Caterina; Di Carlo, Paola; Cipolla, Domenico; Casuccio, Alessandra; Tantillo, Matilde; Plano, Maria Rosa Anna; Mazzola, Angela; Corsello, Giovanni

2008-12-01

We describe a one-year investigation of colonization by imipenemresistant, metallo-beta-lactamase (MBL) producing Pseudomonas aeruginosa in a neonatal intensive care unit (NICU) of the University Hospital of Palermo, Italy. A prospective epidemiological investigation was conducted in the period 2003 January to 2004 January. Rectal swabs were collected twice a week from all neonates throughout their NICU stay. MBL production by imipenem-resistant strains of P aeruginosa was detected by phenotypic and molecular methods. Pulsed field gel electrophoresis (PFGE) was carried out on all isolates of P aeruginosa. The association between risk factors and colonization by imipenem-resistant, imipenem-susceptible P aeruginosa isolates and other multidrug-resistant Gram negative (MDRGN) organisms was analyzed for variables present at admission and during the NICU stay. Data analysis was carried out by the Cox proportional hazards regression model. Twentytwo of 210 neonates were colonized with imipenem-resistant, MBL-producing P aeruginosa isolates and 14 by imipenem-susceptible P aeruginosa isolates. A single pulsotype, named A, was shared by all imipenem-resistant isolates. Colonization by P aeruginosa of pulsotype A was positively correlated with breast milk feeding and administration of ampicillin-sulbactam, and inversely correlated with exclusive feeding by formula. In the Cox proportional hazards regression model, birthweight of more than 2500 g and breast milk feeding were independently associated with an increased risk of colonization by MBL producing P aeruginosa. The results strongly support an association between colonization by a well-defined imipenem-resistant, MBL producing P aeruginosa strain and breast milk feeding. Such a study may highlight the need for implementation of strategies to prevent expressed breast milk from becoming a vehicle of health care-associated infections.

Complex association of serum alanine aminotransferase with the risk of future cardiovascular disease in type 2 diabetes.

PubMed

Afarideh, Mohsen; Aryan, Zahra; Ghajar, Alireza; Noshad, Sina; Nakhjavani, Manouchehr; Baber, Usman; Mechanick, Jeffrey I; Esteghamati, Alireza

2016-11-01

We aimed to determine the prospective association between baseline serum levels of alanine aminotransferase (ALT) and the incident cardiovascular disease (CVD) in people with type 2 diabetes. In an open cohort setting, people with type 2 diabetes were followed for their first ever CVD presentation from 1995 to 2015. Statistical methods included Cox regression analysis for reporting of hazard ratios (HRs), artificial neural network modelings, and risk reclassification analyses. We found a nearly constant CVD hazard with baseline serum ALT levels below the 30 IU/L mark, whereas baseline serum ALT levels ≥ 30 IU/L remained an independent predictor of lower CVD rates in patients with type 2 diabetes in the final multivariate Cox proportional hazards regression model (HR: 0.204, 95%CI [0.060-0.689], p for trend value = 0.006). Age, male gender and fasting plasma insulin levels independently predicted baseline serum ALT ≥ 30 IU/L among the population cohort. Augmentation of serum ALT into the weighted Framingham risk score resulted in a considerable net reclassification improvement (NRI) of coronary heart disease (CHD) risk prediction in the study population (NRI = 9.05% (8.01%-10.22%), p value < 0.05). Serum ALT could successfully reclassify about 9% of the population with type 2 diabetes across the CHD-affected and CHD-free categories. Overall, our findings demonstrate a complex and nonlinear relationship for the risk of future CVD by baseline serum ALT levels in patients with type 2 diabetes. Further studies are warranted to confirm whether this complex association could be translated into a clearly visible U or J-shaped figure. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

[Relationship between inflammatory markers and the risk of colorectal cancer in Kailuan male cohort].

PubMed

Wang, G; Xu, W G; Li, F; Su, K; Li, N; Lü, Z Y; Feng, X S; Wei, L P; Chen, H D; Chen, Y H; Guo, L W; Cui, H; Yang, W J; Li, Z F; Ren, J S; Wu, S L; Shi, J F; Dai, M; He, J

2017-10-31

Objective: To investigate whether elevated levels of high sensitivity C-Reactive Protein (hsCRP) and neutrophil (NE) at baseline are associated with an increased risk of colorectal cancer in Kailuan male cohort. Methods: Since May 2006, males from Kailuan cohort were included in this study. Information on demographics, medical history, anthropometry, hsCRP and NE were collectedat baseline for all subjects. Multivariable Cox proportional hazards regression models were used to calculate hazard ratios ( HR ) of association between baseline hsCRP and NE and colorectal cancer risk. Results: By December 31, 2015, a total of 73 869 participants were enrolled in this study. During the follow-up, 336 incident colorectal cancer cases were identified. All participants were divided into three groups according to the level of hsCRP (<1 mg/L, 1-3 mg/L and >3 mg/L). The cumulative incidence of colorectal cancer were 456/10(5,) 510/10(5) and 746/10(5) in these 3 groups, respectively (χ(2)=10.79, P =0.005). Compared with participants with lower hsCRP levels (<1 mg/L), individuals with the highest hsCRP (>3 mg/L) levels had significant increased risks of colorectal cancer ( HR =1.38, 95% CI: 1.05-1.81, P =0.020)after adjusting for age, gender, smoking, drinking, BMI, diabetes and income. Furthermore, subjects were divided into two groups according to the level of NE (≤ 4.08×10(9)/L and > 4.08×10(9)/L). Multivariable Cox proportional hazards regression models indicated that there is no statistical significance of association between NE and colorectal cancer. Conclusions: Elevated levels of hsCRP at baseline might increase the risk of colorectal cancer in males.

Minimal percentage of dose received by 90% of the urethra (%UD90) is the most significant predictor of PSA bounce in patients who underwent low-dose-rate brachytherapy (LDR-brachytherapy) for prostate cancer.

PubMed

Tanaka, Nobumichi; Asakawa, Isao; Fujimoto, Kiyohide; Anai, Satoshi; Hirayama, Akihide; Hasegawa, Masatoshi; Konishi, Noboru; Hirao, Yoshihiko

2012-09-14

To clarify the significant clinicopathological and postdosimetric parameters to predict PSA bounce in patients who underwent low-dose-rate brachytherapy (LDR-brachytherapy) for prostate cancer. We studied 200 consecutive patients who received LDR-brachytherapy between July 2004 and November 2008. Of them, 137 patients did not receive neoadjuvant or adjuvant androgen deprivation therapy. One hundred and forty-two patients were treated with LDR-brachytherapy alone, and 58 were treated with LDR-brachytherapy in combination with external beam radiation therapy. The cut-off value of PSA bounce was 0.1 ng/mL. The incidence, time, height, and duration of PSA bounce were investigated. Clinicopathological and postdosimetric parameters were evaluated to elucidate independent factors to predict PSA bounce in hormone-naïve patients who underwent LDR-brachytherapy alone. Fifty patients (25%) showed PSA bounce and 10 patients (5%) showed PSA failure. The median time, height, and duration of PSA bounce were 17 months, 0.29 ng/mL, and 7.0 months, respectively. In 103 hormone-naïve patients treated with LDR-brachytherapy alone, and univariate Cox proportional regression hazard model indicated that age and minimal percentage of the dose received by 30% and 90% of the urethra were independent predictors of PSA bounce. With a multivariate Cox proportional regression hazard model, minimal percentage of the dose received by 90% of the urethra was the most significant parameter of PSA bounce. Minimal percentage of the dose received by 90% of the urethra was the most significant predictor of PSA bounce in hormone-naïve patients treated with LDR-brachytherapy alone.

DNA mismatch repair gene polymorphisms affect survival in pancreatic cancer.

PubMed

Dong, Xiaoqun; Li, Yanan; Hess, Kenneth R; Abbruzzese, James L; Li, Donghui

2011-01-01

DNA mismatch repair (MMR) maintains genomic stability and mediates cellular response to DNA damage. We aim to demonstrate whether MMR genetic variants affect overall survival (OS) in pancreatic cancer. Using the Sequenom method in genomic DNA, we retrospectively genotyped 102 single-nucleotide polymorphisms (SNPs) of 13 MMR genes from 706 patients with pancreatic adenocarcinoma seen at The University of Texas MD Anderson Cancer Center. Association between genotype and OS was evaluated using multivariable Cox proportional hazard regression models. At a false discovery rate of 1% (p ≤ .0015), 15 SNPs of EXO1, MLH1, MSH2, MSH3, MSH6, PMS2, PMS2L3, TP73, and TREX1 in patients with localized disease (n = 333) and 6 SNPs of MSH3, MSH6, and TP73 in patients with locally advanced or metastatic disease (n = 373) were significantly associated with OS. In multivariable Cox proportional hazard regression models, SNPs of EXO1, MSH2, MSH3, PMS2L3, and TP73 in patients with localized disease, MSH2, MSH3, MSH6, and TP73 in patients with locally advanced or metastatic disease, and EXO1, MGMT, MSH2, MSH3, MSH6, PMS2L3, and TP73 in all patients remained significant predictors for OS (p ≤ .0015) after adjusting for all clinical predictors and all SNPs with p ≤ .0015 in single-locus analysis. Sixteen haplotypes of EXO1, MLH1, MSH2, MSH3, MSH6, PMS2, PMS2L3, RECQL, TP73, and TREX1 significantly correlated with OS in all patients (p ≤ .001). MMR gene variants may have potential value as prognostic markers for OS in pancreatic cancer patients.

Urbanization factors associated with childhood asthma and prematurity: a population-based analysis aged from 0 to 5 years in Taiwan by using Cox regression within a hospital cluster model.

PubMed

Lin, Sheng-Chieh; Lin, Hui-Wen

2015-04-01

Childhood asthma and premature birth are both common; however, no studies have reported urbanization association between asthma and prematurity and the duration of prematurity affect asthma development. We use Taiwan Longitudinal Health Insurance Database (LHID) to explore association between asthma and prematurity among children by using a population-based analysis. This is a retrospective cohort study with registration data derived from Taiwan LHID. We evaluated prematurely born infants and children aged <5 years (n = 532) and age-matched control patients (n = 60505) using Cox proportional hazard regression analysis within a hospital cluster model. Of the 61 037 examinees, 14 012 experienced asthma during the 5-year follow-up, including 161 (72.26 per 1000 person-years) infants and children born prematurely and 13 851 (40.27 per 1000 person-years) controls. The hazard ratio for asthma during 5-year follow-up period was 1.95 (95% confidence interval = 1.67-2.28) among children born prematurely. Boys born prematurely aged 0-2 years were associated with higher asthma rates compared with girls in non-premature and premature groups. Living in urban areas, those born prematurely were associated with higher rates of asthma compared with non-prematurity. Those born prematurely lived in northern region had higher asthma hazard ratio than other regions. Our analyses indicated that sex, age, urbanization level, and geographic region are significantly associated with prematurity and asthma. Based on cumulative asthma-free survival curve generated using the Kaplan-Meier method, infants born prematurely should be closely monitored to see if they would develop asthma until the age of 6 years.

Smoking, body weight, physical exercise, and risk of lower limb total joint replacement in a population-based cohort of men.

PubMed

Mnatzaganian, George; Ryan, Philip; Norman, Paul E; Davidson, David C; Hiller, Janet E

2011-08-01

To assess the associations of smoking, body weight, and physical activity with risk of undergoing total joint replacement (TJR) in a population-based cohort of men. A cohort study of 11,388 men that integrated clinical data with hospital morbidity data and mortality records was undertaken. The risk of undergoing TJR was modeled on baseline weight, height, comorbidity, socioeconomic status, years of smoking, and exercise in 3 separate age groups, using Cox proportional hazards regressions and competing risk regressions (CRRs). Dose-response relationships between weight and risk of TJR and between smoking and risk of TJR were observed. Being overweight independently increased the risk of TJR, while smoking lowered the risk. The decreased risk among smokers was demonstrated in both Cox and CRR models and became apparent after 23 years of exposure. Men who were in the highest quartile (≥48 years of smoking) were 42-51% less likely to undergo TJR than men who had never smoked. Tests for trend in the log hazard ratios (HRs) across both smoking and weight quantiles yielded significant P values. Vigorous exercise increased the hazard of TJR; however, the association reached statistical significance only in the 70-74-year-old age group (adjusted HR 1.64 [95% confidence interval 1.19-2.24]). Adjusting for Deyo-Charlson Index or Elixhauser's comorbidity measures did not eliminate these associations. Our findings indicate that being overweight and reporting vigorous physical activity increase the risk of TJR. This study is the first to demonstrate a strong inverse dose-response relationship between duration of smoking and risk of TJR. More research is needed to better understand the role of smoking in the pathogenesis of osteoarthritis. Copyright © 2011 by the American College of Rheumatology.

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.

A questionnaire-wide association study of personality and mortality: the Vietnam Experience Study.

PubMed

Weiss, Alexander; Gale, Catharine R; Batty, G David; Deary, Ian J

2013-06-01

We examined the association between the Minnesota Multiphasic Personality Inventory (MMPI) and all-cause mortality in 4462 middle-aged Vietnam-era veterans. We split the study population into half-samples. In each half, we used proportional hazards (Cox) regression to test the 550 MMPI items' associations with mortality over 15years. In all participants, we subjected significant (p<.01) items in both halves to principal-components analysis (PCA). We used Cox regression to test whether these components predicted mortality when controlling for other predictors (demographics, cognitive ability, health behaviors, and mental/physical health). Eighty-nine items were associated with mortality in both half-samples. PCA revealed Neuroticism/Negative Affectivity, Somatic Complaints, Psychotic/Paranoia, and Antisocial components, and a higher-order component, Personal Disturbance. Individually, Neuroticism/Negative Affectivity (HR=1.55; 95% CI=1.39, 1.72), Somatic Complaints (HR=1.66; 95% CI=1.52, 1.80), Psychotic/Paranoid (HR=1.44; 95% CI=1.32, 1.57), Antisocial (HR=1.79; 95% CI=1.59, 2.01), and Personal Disturbance (HR=1.74; 95% CI=1.58, 1.91) were associated with risk. Including covariates attenuated these associations (28.4 to 54.5%), though they were still significant. After entering Personal Disturbance into models with each component, Neuroticism/Negative Affectivity and Somatic Complaints were significant, although Neuroticism/Negative Affectivity's were now protective (HR=0.73; 95% CI=0.58, 0.92). When the four components were entered together with or without covariates, Somatic Complaints and Antisocial were significant risk factors. Somatic Complaints and Personal Disturbance are associated with increased mortality risk. Other components' effects varied as a function of variables in the model. Copyright © 2013 Elsevier Inc. All rights reserved.

Association of nutritional status as measured by the Mini-Nutritional Assessment Short Form with changes in mobility, institutionalization and death after hip fracture.

PubMed

Nuotio, M; Tuominen, P; Luukkaala, T

2016-03-01

We examined the association of nutritional status as measured by the Mini-Nutritional Assessment Short Form (MNA-SF) with changes in mobility, institutionalization and death after hip fracture. Population-based prospective data were collected on 472 out of 693 consecutive hip fracture patients aged 65 years and over between January 2010 and December 2012. Declined vs same or improved mobility level, institutionalization and death during the 4-month follow-up were the outcomes. Age, gender, American Society of Anesthesiologists scores, pre-fracture diagnosis of a memory disorder, mobility level, living arrangements and MNA-SF scores at baseline were the independent variables. Age-adjusted and multivariate logistic regression and Cox proportional hazards models were conducted. At baseline, 41 (9%) patients were malnourished and 200 (42%) patients at risk of malnutrition according to the MNA-SF. During the follow-up, 90 (19%) had died. In the multivariate Cox proportional hazards model, malnutrition (hazard ratio 2.16; 95% confidence interval (CI) 1.07-4.34) was associated with mortality. In the multivariate binary logistic regression analyses, risk of malnutrition (odds ratios (OR) 2.42; 95% CI 1.25-4.66) and malnutrition (OR 6.10;95% CI 2.01-18.5) predicted institutionalization. Risk of malnutrition (OR 2.03; 95% CI 1.24-3.31) was associated with decline in the mobility level. Malnutrition or risk of malnutrition as measured by the MNA-SF were independent predictors of negative outcomes after hip fracture. Patients classified as being at risk of malnutrition by the MNA-SF may constitute a patient population with mild-to-moderate malnutrition and may require specific attention when nutritional interventions are designed after hip fracture.

Predictors of running-related injuries in novice runners enrolled in a systematic training program: a prospective cohort study.

PubMed

Buist, Ida; Bredeweg, Steef W; Lemmink, Koen A P M; van Mechelen, Willem; Diercks, Ron L

2010-02-01

The popularity of running is still growing. As participation increases, running-related injuries also increase. Until now, little is known about the predictors for injuries in novice runners. Predictors for running-related injuries (RRIs) will differ between male and female novice runners. Cohort study; Level of evidence, 2. Participants were 532 novice runners (226 men, 306 women) preparing for a recreational 4-mile (6.7-km) running event. After completing a baseline questionnaire and undergoing an orthopaedic examination, they were followed during the training period of 13 weeks. An RRI was defined as any self-reported running-related musculoskeletal pain of the lower extremity or back causing a restriction of running for at least 1 week. Twenty-one percent of the novice runners had at least one RRI during follow-up. The multivariate adjusted Cox regression model for male participants showed that body mass index (BMI) (hazard ratio [HR], 1.15; 95% confidence interval [CI], 1.05-1.26), previous injury in the past year (HR, 2.7; 95% CI, 1.36-5.55), and previous participation in sports without axial load (HR, 2.05; 95% CI, 1.03-4.11) were associated with RRI. In female participants, only navicular drop (HR, 0.85; 95% CI, 0.75-0.97) remained a significant predictor for RRI in the multivariate Cox regression modeling. Type A behavior and range of motion (ROM) of the hip and ankle did not affect risk. Male and female novice runners have different risk profiles. Higher BMI, previous injury, and previous sports participation without axial loading are important predictors for RRI in male participants. Further research is needed to detect more predictors for female novice runners.

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.

Do repeated assessments of performance status improve predictions for risk of death among patients with cancer? A population-based cohort study.

PubMed

Su, Jiandong; Barbera, Lisa; Sutradhar, Rinku

2015-06-01

Prior work has utilized longitudinal information on performance status to demonstrate its association with risk of death among cancer patients; however, no study has assessed whether such longitudinal information improves the predictions for risk of death. To examine whether the use of repeated performance status assessments improve predictions for risk of death compared to using only performance status assessment at the time of cancer diagnosis. This was a population-based longitudinal study of adult outpatients who had a cancer diagnosis and had at least one assessment of performance status. To account for each patient's changing performance status over time, we implemented a Cox model with a time-varying covariate for performance status. This model was compared to a Cox model using only a time-fixed (baseline) covariate for performance status. The regression coefficients of each model were derived based on a randomly selected 60% of patients, and then, the predictive ability of each model was assessed via concordance probabilities when applied to the remaining 40% of patients. Our study consisted of 15,487 cancer patients with over 53,000 performance status assessments. The utilization of repeated performance status assessments improved predictions for risk of death compared to using only the performance status assessment taken at diagnosis. When studying the hazard of death among patients with cancer, if available, researchers should incorporate changing information on performance status scores, instead of simply baseline information on performance status. © The Author(s) 2015.

Analysis of occlusal variables, dental attrition, and age for distinguishing healthy controls from female patients with intracapsular temporomandibular disorders.

PubMed

Seligman, D A; Pullinger, A G

2000-01-01

Confusion about the relationship of occlusion to temporomandibular disorders (TMD) persists. This study attempted to identify occlusal and attrition factors plus age that would characterize asymptomatic normal female subjects. A total of 124 female patients with intracapsular TMD were compared with 47 asymptomatic female controls for associations to 9 occlusal factors, 3 attrition severity measures, and age using classification tree, multiple stepwise logistic regression, and univariate analyses. Models were tested for accuracy (sensitivity and specificity) and total contribution to the variance. The classification tree model had 4 terminal nodes that used only anterior attrition and age. "Normals" were mainly characterized by low attrition levels, whereas patients had higher attrition and tended to be younger. The tree model was only moderately useful (sensitivity 63%, specificity 94%) in predicting normals. The logistic regression model incorporated unilateral posterior crossbite and mediotrusive attrition severity in addition to the 2 factors in the tree, but was slightly less accurate than the tree (sensitivity 51%, specificity 90%). When only occlusal factors were considered in the analysis, normals were additionally characterized by a lack of anterior open bite, smaller overjet, and smaller RCP-ICP slides. The log likelihood accounted for was similar for both the tree (pseudo R(2) = 29.38%; mean deviance = 0.95) and the multiple logistic regression (Cox Snell R(2) = 30.3%, mean deviance = 0.84) models. The occlusal and attrition factors studied were only moderately useful in differentiating normals from TMD patients.

Microarray analysis of gene expression in the cyclooxygenase knockout mice - a connection to autism spectrum disorder.

PubMed

Rai-Bhogal, Ravneet; Ahmad, Eizaaz; Li, Hongyan; Crawford, Dorota A

2018-03-01

The cellular and molecular events that take place during brain development play an important role in governing function of the mature brain. Lipid-signalling molecules such as prostaglandin E 2 (PGE 2 ) play an important role in healthy brain development. Abnormalities along the COX-PGE 2 signalling pathway due to genetic or environmental causes have been linked to autism spectrum disorder (ASD). This study aims to evaluate the effect of altered COX-PGE 2 signalling on development and function of the prenatal brain using male mice lacking cyclooxygenase-1 and cyclooxygenase-2 (COX-1 -/- and COX-2 -/- ) as potential model systems of ASD. Microarray analysis was used to determine global changes in gene expression during embryonic days 16 (E16) and 19 (E19). Gene Ontology: Biological Process (GO:BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were implemented to identify affected developmental genes and cellular processes. We found that in both knockouts the brain at E16 had nearly twice as many differentially expressed genes, and affected biological pathways containing various ASD-associated genes important in neuronal function. Interestingly, using GeneMANIA and Cytoscape we also show that the ASD-risk genes identified in both COX-1 -/- and COX-2 -/- models belong to protein-interaction networks important for brain development despite of different cellular localization of these enzymes. Lastly, we identified eight genes that belong to the Wnt signalling pathways exclusively in the COX-2 -/- mice at E16. The level of PKA-phosphorylated β-catenin (S552), a major activator of the Wnt pathway, was increased in this model, suggesting crosstalk between the COX-2-PGE 2 and Wnt pathways during early brain development. Overall, these results provide further molecular insight into the contribution of the COX-PGE 2 pathways to ASD and demonstrate that COX-1 -/- and COX-2 -/- animals might be suitable new model systems for studying the disorders. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The COX-2 inhibitor meloxicam prevents pregnancy when administered as an emergency contraceptive to nonhuman primates.

PubMed

McCann, Nicole C; Lynch, Terrie J; Kim, Soon Ok; Duffy, Diane M

2013-12-01

Cyclooxygenase-2 (COX-2) inhibitors reduce prostaglandin synthesis and disrupt essential reproductive processes. Ultrasound studies in women demonstrated that oral COX-2 inhibitors can delay or prevent follicle collapse associated with ovulation. The goal of this study was to determine if oral administration of a COX-2 inhibitor can inhibit reproductive function with sufficient efficacy to prevent pregnancy in primates. The COX-2 inhibitor meloxicam (or vehicle) was administered orally to proven fertile female cynomolgus macaques using one emergency contraceptive model and three monthly contraceptive models. In the emergency contraceptive model, females were bred with a proven fertile male once 2±1 days before ovulation, returned to the females' home cage, and then received 5 days of meloxicam treatment. In the monthly contraceptive models, females were co-caged for breeding with a proven fertile male for a total of 5 days beginning 2±1 days before ovulation. Animals received meloxicam treatment (1) cycle days 5-22, or (2) every day, or (3) each day of the 5-day breeding period. Female were then assessed for pregnancy. The pregnancy rate with meloxicam administration using the emergency contraception model was 6.5%, significantly lower than the pregnancy rate of 33.3% when vehicle without meloxicam was administered. Pregnancy rates with the three monthly contraceptive models (75%-100%) were not consistent with preventing pregnancy. Oral COX-2 inhibitor administration can prevent pregnancy after a single instance of breeding in primates. While meloxicam may be ineffective for regular contraception, pharmacological inhibition of COX-2 may be an effective method of emergency contraception for women. COX-2 inhibitors can interfere with ovulation, but the contraceptive efficacy of drugs of this class has not been directly tested. This study, conducted in nonhuman primates, is the first to suggest that a COX-2 inhibitor may be effective as an emergency contraceptive. © 2013.

Association of tRNA methyltransferase NSUN2/IGF-II molecular signature with ovarian cancer survival.

PubMed

Yang, Jia-Cheng; Risch, Eric; Zhang, Meiqin; Huang, Chan; Huang, Huatian; Lu, Lingeng

2017-09-01

To investigate the association between NSUN2/IGF-II signature and ovarian cancer survival. Using a publicly accessible dataset of RNA sequencing and clinical follow-up data, we performed Classification and Regression Tree and survival analyses. Patients with NSUN2 high IGF-II low had significantly superior overall and disease progression-free survival, followed by NSUN2 low IGF-II low , NSUN2 high IGF-II high and NSUN2 low IGF-II high (p < 0.0001 for overall, p = 0.0024 for progression-free survival, respectively). The associations of NSUN2/IGF-II signature with the risks of death and relapse remained significant in multivariate Cox regression models. Random-effects meta-analyses show the upregulated NSUN2 and IGF-II expression in ovarian cancer versus normal tissues. The NSUN2/IGF-II signature associates with heterogeneous outcome and may have clinical implications in managing ovarian cancer.

Fetal exposure to nonsteroidal anti-inflammatory drugs and spontaneous abortions

PubMed Central

Daniel, Sharon; Koren, Gideon; Lunenfeld, Eitan; Bilenko, Natalya; Ratzon, Ronit; Levy, Amalia

2014-01-01

Background: Spontaneous abortion is the most common complication of pregnancy. Non-steroidal anti-inflammatory drugs (NSAIDs) are widely used during pregnancy. Published data are inconsistent regarding the risk of spontaneous abortion following exposure to NSAIDs. Methods: We performed a historical cohort study involving all women who conceived between January 2003 and December 2009 and who were admitted for delivery or spontaneous abortion at Soroka Medical Center, Clalit Health Services, Israel. A computerized database of medication dispensation was linked with 2 computerized databases containing information on births and spontaneous abortions. We constructed time-varying Cox regression models and adjusted for maternal age, diabetes mellitus, hypothyroidism, obesity, hypercoagulation or inflammatory conditions, recurrent miscarriage, in vitro fertilization of the current pregnancy, intrauterine contraceptive device, ethnic background, tobacco use and year of admission. Results: The cohort included 65 457 women who conceived during the study period; of these, 58 949 (90.1%) were admitted for a birth and 6508 (9.9%) for spontaneous abortion. A total of 4495 (6.9%) pregnant women were exposed to NSAIDs during the study period. Exposure to NSAIDs was not an independent risk factor for spontaneous abortion (nonselective cyclooxygenase [COX] inhibitors: adjusted hazard ratio [HR] 1.10, 95% confidence interval [CI] 0.99–1.22; selective COX-2 inhibitors: adjusted HR 1.43, 95% CI 0.79–2.59). There was no increased risk for specific NSAID drugs, except for a significantly increased risk with exposure to indomethacin (adjusted HR 2.8, 95% CI 1.70–4.69). We found no dose–response effect. Interpretation: We found no increased risk of spontaneous abortion following exposure to NSAIDs. Further research is needed to assess the risk following exposure to selective COX-2 inhibitors. PMID:24491470

Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies.

PubMed

Karim, Mohammad Ehsanul; Petkau, John; Gustafson, Paul; Platt, Robert W; Tremlett, Helen

2018-06-01

In longitudinal studies, if the time-dependent covariates are affected by the past treatment, time-dependent confounding may be present. For a time-to-event response, marginal structural Cox models are frequently used to deal with such confounding. To avoid some of the problems of fitting marginal structural Cox model, the sequential Cox approach has been suggested as an alternative. Although the estimation mechanisms are different, both approaches claim to estimate the causal effect of treatment by appropriately adjusting for time-dependent confounding. We carry out simulation studies to assess the suitability of the sequential Cox approach for analyzing time-to-event data in the presence of a time-dependent covariate that may or may not be a time-dependent confounder. Results from these simulations revealed that the sequential Cox approach is not as effective as marginal structural Cox model in addressing the time-dependent confounding. The sequential Cox approach was also found to be inadequate in the presence of a time-dependent covariate. We propose a modified version of the sequential Cox approach that correctly estimates the treatment effect in both of the above scenarios. All approaches are applied to investigate the impact of beta-interferon treatment in delaying disability progression in the British Columbia Multiple Sclerosis cohort (1995-2008).

Proportional exponentiated link transformed hazards (ELTH) models for discrete time survival data with application

PubMed Central

Joeng, Hee-Koung; Chen, Ming-Hui; Kang, Sangwook

2015-01-01

Discrete survival data are routinely encountered in many fields of study including behavior science, economics, epidemiology, medicine, and social science. In this paper, we develop a class of proportional exponentiated link transformed hazards (ELTH) models. We carry out a detailed examination of the role of links in fitting discrete survival data and estimating regression coefficients. Several interesting results are established regarding the choice of links and baseline hazards. We also characterize the conditions for improper survival functions and the conditions for existence of the maximum likelihood estimates under the proposed ELTH models. An extensive simulation study is conducted to examine the empirical performance of the parameter estimates under the Cox proportional hazards model by treating discrete survival times as continuous survival times, and the model comparison criteria, AIC and BIC, in determining links and baseline hazards. A SEER breast cancer dataset is analyzed in details to further demonstrate the proposed methodology. PMID:25772374

PREDICTION OF MALIGNANT BREAST LESIONS FROM MRI FEATURES: A COMPARISON OF ARTIFICIAL NEURAL NETWORK AND LOGISTIC REGRESSION TECHNIQUES

PubMed Central

McLaren, Christine E.; Chen, Wen-Pin; Nie, Ke; Su, Min-Ying

2009-01-01

Rationale and Objectives Dynamic contrast enhanced MRI (DCE-MRI) is a clinical imaging modality for detection and diagnosis of breast lesions. Analytical methods were compared for diagnostic feature selection and performance of lesion classification to differentiate between malignant and benign lesions in patients. Materials and Methods The study included 43 malignant and 28 benign histologically-proven lesions. Eight morphological parameters, ten gray level co-occurrence matrices (GLCM) texture features, and fourteen Laws’ texture features were obtained using automated lesion segmentation and quantitative feature extraction. Artificial neural network (ANN) and logistic regression analysis were compared for selection of the best predictors of malignant lesions among the normalized features. Results Using ANN, the final four selected features were compactness, energy, homogeneity, and Law_LS, with area under the receiver operating characteristic curve (AUC) = 0.82, and accuracy = 0.76. The diagnostic performance of these 4-features computed on the basis of logistic regression yielded AUC = 0.80 (95% CI, 0.688 to 0.905), similar to that of ANN. The analysis also shows that the odds of a malignant lesion decreased by 48% (95% CI, 25% to 92%) for every increase of 1 SD in the Law_LS feature, adjusted for differences in compactness, energy, and homogeneity. Using logistic regression with z-score transformation, a model comprised of compactness, NRL entropy, and gray level sum average was selected, and it had the highest overall accuracy of 0.75 among all models, with AUC = 0.77 (95% CI, 0.660 to 0.880). When logistic modeling of transformations using the Box-Cox method was performed, the most parsimonious model with predictors, compactness and Law_LS, had an AUC of 0.79 (95% CI, 0.672 to 0.898). Conclusion The diagnostic performance of models selected by ANN and logistic regression was similar. The analytic methods were found to be roughly equivalent in terms of predictive ability when a small number of variables were chosen. The robust ANN methodology utilizes a sophisticated non-linear model, while logistic regression analysis provides insightful information to enhance interpretation of the model features. PMID:19409817

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

Association of dipeptidyl peptidase 4 inhibitors with risk of metastases in patients with type 2 diabetes and breast, prostate or digestive system cancer.

PubMed

Rathmann, Wolfgang; Kostev, Karel

2017-04-01

Experimental and animal studies have supported the hypothesis that dipeptidyl peptidase-4 inhibitors (DPP-4i) may accelerate tumor metastasis. The aim was to analyze the relationships between DPP-4i therapy with risk of metastases in type 2 diabetes patients with breast, prostate and digestive organ cancers. Type 2 diabetes patients with first diagnoses of breast, prostate or digestive organ cancer were selected in general and internal medicine practices (Disease Analyzer Germany: 01/2008-12/2014). Propensity score matching between DPP-4i users and non-users was carried out for age, sex, diabetes duration, and metformin use. Time-dependent Cox regression models were used to estimate hazard ratios (HR) for metastases further adjusting for HbA1c, body mass index, comorbidity and co-therapy with glucose-lowering drugs (3-4years follow-up). 668 patients with newly diagnosed breast cancer, 906 with prostate cancer and 908 with digestive organ cancer were analyzed. In Cox regression, use of DPP-4i was not associated with an increased risk of metastases in patients with breast (adjusted HR, 95%CI: 1.00, 0.49-2.02), prostate (0.98, 0.54-1.77) or digestive organ cancers (0.97, 0.57-1.66). This first observational study in patients with type 2 diabetes and breast, prostate or digestive organ cancer found no increased risk of metastases in DPP-4i users. Copyright © 2017 Elsevier Inc. All rights reserved.

Transplant center volume and outcomes in lung transplantation for cystic fibrosis.

PubMed

Hayes, Don; Sweet, Stuart C; Benden, Christian; Kopp, Benjamin T; Goldfarb, Samuel B; Visner, Gary A; Mallory, George B; Tobias, Joseph D; Tumin, Dmitry

2017-04-01

Transplant volume represents lung transplant (LTx) expertise and predicts outcomes, so we sought to determine outcomes related to center volumes in cystic fibrosis (CF). United Network for Organ Sharing data were queried for patients with CF in the United States (US) receiving bilateral LTx from 2005 to 2015. Multivariable Cox regression was used to model survival to 1 year and long-term (>1 year) survival, conditional on surviving at least 1 year. A total of 2025 patients and 67 centers were included in the analysis. The median annual LTx volumes were three in CF [interquartile range (IQR): 2, 6] and 17 in non-CF (IQR: 8, 33). Multivariable Cox regression in cases with complete data and surviving at least 1 year (n = 1510) demonstrated that greater annual CF LTx volume (HR per 10 LTx = 0.66; 95% CI: 0.49, 0.89; P = 0.006) but not greater non-CF LTx volume (HR = 1.00; 95% CI: 0.96, 1.05; P = 0.844) was associated with improved long-term survival in LTx recipients with CF. A Wald interaction test confirmed that CF LTx volume was more strongly associated with long-term outcomes than non-CF LTx volume (P = 0.012). In a US cohort, center volume was not associated with 1-year survival. CF-specific expertise predicted improved long-term outcomes of LTx for CF, whereas general LTx expertise was unassociated with CF patients' survival. © 2016 Steunstichting ESOT.

Multicenter retrospective analysis of cardiovascular risk factors affecting long-term outcome of de novo cardiac transplant recipients.

PubMed

Kobashigawa, Jon A; Starling, Randall C; Mehra, Mandeep R; Kormos, Robert L; Bhat, Geetha; Barr, Mark L; Sigouin, Chris S; Kolesar, June; Fitzsimmons, William

2006-09-01

Previous risk factor studies in cardiac transplant patients have analyzed pre-transplant risk factors as they relate to outcomes. This study is the first in-depth multicenter assessment of ongoing post-transplant risk factors in heart transplant patients and their impact on 5-year outcomes. We reviewed 280 heart transplant patients who survived > 1 year for the impact of post-transplant risk factors (hyperlipidemia, hypertension, diabetes, body mass index [BMI] and renal dysfunction: 8 to 18 possible measurements over 5 years) on outcomes, including death, cardiac allograft vasculopathy (CAV) and non-fatal major adverse cardiac events (NF-MACE). Upon multivariate Cox regression analysis, significant findings were high total-cholesterol for NF-MACE (relative risk [RR] = 4.34, confidence interval [CI] 1.35 to 13.98, p = 0.01), presence of diabetes for NF-MACE (RR = 3.96, CI 1.24 to 12.65, p = 0.02) and high serum creatinine for graft death (RR = 1.59, CI 1.35 to 1.87, p < 0.001). No covariates were found to be significant for CAV. Other significant risk factors by univariate Cox regression models with time-dependent covariates included BMI > or = 33 for graft death. Post-transplant risk factors of hypercholesterolemia and diabetes are associated with NF-MACE, whereas high serum creatinine and BMI > or = 33 are associated with graft death. Risk factor modification, including direct therapy to minimize risk factors, should be considered.

Association between participation in outdoor play and sport at 10 years old with physical activity in adulthood.

PubMed

Smith, Lee; Gardner, Benjamin; Aggio, Daniel; Hamer, Mark

2015-05-01

This study aimed to investigate whether active outdoor play and/or sports at age 10 is associated with sport/physical activity at 32 year follow-up using a birth cohort study. Data were from the 1970 British Cohort Study, a longitudinal observational study. The present paper included data from the age 10 years and age 42 years surveys. At age 10 the participant's mother provided information regarding how often their child played sports, and played outside on streets, parks or playgrounds. At age 42 participants reported frequency of participation in physical activities and sports. Associations between participation in sport/active outdoor play at age 10 years and adult sport/physical activity were investigated using adjusted (gender, fathers socio-occupational class, child's BMI, father's BMI, self-rated health at age 42, assessment of own weight at age 42, participant's education) Cox regression. Final adjusted Cox regression models showed that participants (n=6458) who often participated in sports at age 10 were significantly more likely to participate in sport/physical activity at age 42 (RR 1.10; 95% CI 1.01 to 1.19). Active outdoor play at age 10 was not associated with participation in sport/physical activity at age 42 (RR 0.99; 95% CI 0.91 to 1.07). Childhood activity interventions might best achieve lasting change by promoting engagement in sport rather than active outdoor play. Copyright © 2015. Published by Elsevier Inc.

Premature Atrial Contractions on the Screening Electrocardiogram and Risk of Ischemic Stroke: The Reasons for Geographic and Racial Differences in Stroke Study.

PubMed

O'Neal, Wesley T; Kamel, Hooman; Kleindorfer, Dawn; Judd, Suzanne E; Howard, George; Howard, Virginia J; Soliman, Elsayed Z

2016-01-01

It is currently unknown if premature atrial contractions (PACs) detected on the routine screening electrocardiogram are associated with an increased risk of ischemic stroke. We examined the association between PACs and ischemic stroke in 22,975 (mean age 64 ± 9.2; 56% women; 40% black) participants from the Reasons for Geographic and Racial Differences in Stroke study. Participants who were free of stroke at baseline were included. PACs were detected from centrally read electrocardiograms at baseline. Cox regression was used to examine the association between PACs and ischemic stroke events through March 31, 2014. PACs were present in 1,687 (7.3%) participants at baseline. In a Cox regression model adjusted for stroke risk factors and potential confounders, PACs were associated with an increased risk of ischemic stroke (hazards ratio (HR) 1.34, 95% CI 1.04-1.74). The relationship was limited to non-lacunar infarcts (HR 1.42, 95% CI 1.08-1.87), and not lacunar strokes (HR 1.01, 95% CI 0.51-2.03). An interaction by sex was detected, with the association between PACs and ischemic stroke being stronger among women (HR 1.82, 95% CI 1.29-2.56) than men (HR 1.03, 95% CI 0.69-1.52; p-interaction = 0.0095). PACs detected on the routine electrocardiogram are associated with an increased risk for non-lacunar ischemic strokes, especially in women. © 2016 S. Karger AG, Basel.

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.

Effects of chemical immobilization on survival of African buffalo in the Kruger National Park

USGS Publications Warehouse

Oosthuizen, W.C.; Cross, P.C.; Bowers, J.A.; Hay, C.; Ebinger, M.R.; Buss, P.; Hofmeyr, M.; Cameron, E.Z.

2009-01-01

Capturing, immobilizing, and fitting radiocollars are common practices in studies of large mammals, but success is based on the assumptions that captured animals are representative of the rest of the population and that the capture procedure has negligible effects. We estimated effects of chemical immobilization on mortality rates of African buffalo (Syncerus caffer) in the Kruger National Park, South Africa. We used a Cox proportional hazards approach to test for differences in mortality among age, sex, and capture classes of repeatedly captured radiocollared buffalo. Capture variables did not improve model fit and the Cox regression did not indicate increased risk of death for captured individuals up to 90 days postcapture [exp (??) = 1.07]. Estimated confidence intervals, however, span from a halving to a doubling of the mortality rate (95% CI = 0.56-2.02). Therefore, capture did not influence survival of captured individuals using data on 875 captures over a 5-year period. Consequently, long-term research projects on African buffalo involving immobilization, such as associated with research on bovine tuberculosis, should result in minimal capture mortality, but monitoring of possible effects should continue.

Long QT syndrome in African-Americans.

PubMed

Fugate, Thomas; Moss, Arthur J; Jons, Christian; McNitt, Scott; Mullally, Jamie; Ouellet, Gregory; Goldenberg, Ilan; Zareba, Wojciech; Robinson, Jennifer L

2010-01-01

We evaluated the risk factors and clinical course of Long QT syndrome (LQTS) in African-American patients. The study involved 41 African-Americans and 3456 Caucasians with a QTc > or = 450 ms from the U.S. portion of the International LQTS Registry. Data included information about the medical history and clinical course of the LQTS patients with end points relating to the occurrence of syncope, aborted cardiac arrest, or LQTS-related sudden cardiac death from birth through age 40 years. The statistical analyses involved Kaplan-Meier time to event graphs and Cox regression models for multivariable risk factor evaluation. The QTc was 29 ms longer in African-Americans than Caucasians. Multivarite Cox analyses with adjustment for decade of birth revealed that the cardiac event rate was similar in African-Americans and Caucasians with LQTS and that beta-blockers were equally effective in reducing cardiac events in the two racial groups. The clinical course of LQTS in African-Americans is similar to that of Caucasians with comparable risk factors and benefit from beta-blocker therapy in the two racial groups.

A novel risk score for mortality in renal transplant recipients beyond the first posttransplant year.

PubMed

Hernández, Domingo; Sánchez-Fructuoso, Ana; González-Posada, José Manuel; Arias, Manuel; Campistol, Josep María; Rufino, Margarita; Morales, José María; Moreso, Francesc; Pérez, Germán; Torres, Armando; Serón, Daniel

2009-09-27

All-cause mortality is high after kidney transplantation (KT), but no prognostic index has focused on predicting mortality in KT using baseline and emergent comorbidity after KT. A total of 4928 KT recipients were used to derive a risk score predicting mortality. Patients were randomly assigned to two groups: a modeling population (n=2452), used to create a new index, and a testing population (n=2476), used to test this index. Multivariate Cox regression model coefficients of baseline (age, weight, time on dialysis, diabetes, hepatitis C, and delayed graft function) and emergent comorbidity within the first posttransplant year (diabetes, proteinuria, renal function, and immunosuppressants) were used to weigh each variable in the calculation of the score and allocated into risk quartiles. The probability of death at 3 years, estimated by baseline cumulative hazard function from the Cox model [P (death)=1-0.993592764 (exp(score/100)], increased from 0.9% in the lowest-risk quartile (score=40) to 4.7% in the highest risk-quartile (score=200). The observed incidence of death increased with increasing risk quartiles in testing population (log-rank analysis, P<0.0001). The overall C-index was 0.75 (95% confidence interval: 0.72-0.78) and 0.74 (95% confidence interval: 0.70-0.77) in both populations, respectively. This new index is an accurate tool to identify high-risk patients for mortality after KT.

Cyclooxygenase metabolites mediate glomerular monocyte chemoattractant protein-1 formation and monocyte recruitment in experimental glomerulonephritis.

PubMed

Schneider, A; Harendza, S; Zahner, G; Jocks, T; Wenzel, U; Wolf, G; Thaiss, F; Helmchen, U; Stahl, R A

1999-02-01

Monocyte chemoattractant protein-1 (MCP-1) has been shown to play a significant role in the recruitment of monocytes/macrophages in experimental glomerulonephritis. Whereas a number of inflammatory mediators have been characterized that are involved in the expression of MCP-1 in renal disease, little is known about repressors of chemokine formation in vivo. We hypothesized that cyclooxygenase (COX) products influence the formation of MCP-1 and affect inflammatory cell recruitment in glomerulonephritis. The effect of COX inhibitors was evaluated in the antithymocyte antibody model and an anti-glomerular basement membrane model of glomerulonephritis. Rats were treated with the COX-1/COX-2 inhibitor indomethacin and the selective COX-2 inhibitors meloxicam and SC 58125. Animals were studied at 1 hour, 24 hours, and 5 days after induction of the disease. Indomethacin, to a lesser degree the selective COX-2 inhibitors, enhanced glomerular MCP-1 and RANTES mRNA levels. Indomethacin enhanced glomerular monocyte chemoattractant activity an the infiltration of monocytes/macrophages at 24 hours and 5 days. Our studies demonstrate that COX products may serve as endogenous repressors of MCP-1 formation in experimental glomerulonephritis. The data suggest that COX-1 and COX-2 products mediate these effects differently because the selective COX-2 inhibitors had less influence on chemokine expression.

An artificial neural network improves prediction of observed survival in patients with laryngeal squamous carcinoma.

PubMed

Jones, Andrew S; Taktak, Azzam G F; Helliwell, Timothy R; Fenton, John E; Birchall, Martin A; Husband, David J; Fisher, Anthony C

2006-06-01

The accepted method of modelling and predicting failure/survival, Cox's proportional hazards model, is theoretically inferior to neural network derived models for analysing highly complex systems with large datasets. A blinded comparison of the neural network versus the Cox's model in predicting survival utilising data from 873 treated patients with laryngeal cancer. These were divided randomly and equally into a training set and a study set and Cox's and neural network models applied in turn. Data were then divided into seven sets of binary covariates and the analysis repeated. Overall survival was not significantly different on Kaplan-Meier plot, or with either test model. Although the network produced qualitatively similar results to Cox's model it was significantly more sensitive to differences in survival curves for age and N stage. We propose that neural networks are capable of prediction in systems involving complex interactions between variables and non-linearity.

COX-1 Inhibitors: Beyond Structure Toward Therapy.

PubMed

Vitale, Paola; Panella, Andrea; Scilimati, Antonio; Perrone, Maria Grazia

2016-07-01

Biosynthesis of prostaglandins from arachidonic acid (AA) is catalyzed by cyclooxygenase (COX), which exists as COX-1 and COX-2. AA is in turn released from the cell membrane upon neopathological stimuli. COX inhibitors interfere in this catalytic and disease onset process. The recent prominent discovery involvements of COX-1 are mainly in cancer and inflammation. Five classes of COX-1 inhibitors are known up to now and this classification is based on chemical features of both synthetic compounds and substances from natural sources. Physicochemical interactions identification between such molecules and COX-1 active site was achieved through X-ray, mutagenesis experiments, specific assays and docking investigations, as well as through a pharmacometric predictive model building. All these insights allowed the design of new highly selective COX-1 inhibitors to be tested into those disease models in which COX-1 is involved. Particularly, COX-1 is expressed at high levels in the early to advanced stages of human epithelial ovarian cancer, and it also seems to play a pivotal role in cancer progression. The refinement of COX-1 selective inhibitor structure has progressed to the stage that some of the inhibitors described in this review could be considered as promising active principle ingredients of drugs and hence part of specific therapeutic protocols. This review aims to outline achievements, in the last 5 years, dealing with the identification of highly selective synthetic and from plant extracts COX-1 inhibitors and their theranostic use in neuroinflammation and ovarian cancer. Their gastrotoxic effect is also discussed. © 2016 Wiley Periodicals, Inc.

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

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

PubMed

Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

2015-01-01

Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

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.

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.

Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.

PubMed

Nowak, Christoph; Carlsson, Axel C; Östgren, Carl Johan; Nyström, Fredrik H; Alam, Moudud; Feldreich, Tobias; Sundström, Johan; Carrero, Juan-Jesus; Leppert, Jerzy; Hedberg, Pär; Henriksen, Egil; Cordeiro, Antonio C; Giedraitis, Vilmantas; Lind, Lars; Ingelsson, Erik; Fall, Tove; Ärnlöv, Johan

2018-05-24

Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes. We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swedish National Diabetes Register risk model would improve the prediction of MACE in the separate 25% test subsample. Of 1211 adults with type 2 diabetes (32% women), 211 experienced a MACE over a mean (±SD) of 6.4 ± 2.3 years. We replicated associations (<5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit α (IL-27a), kidney injury molecule (KIM)-1, fibroblast growth factor (FGF)-23, protein S100-A12, TNF receptor (TNFR)-1, TNFR-2 and TNF-related apoptosis-inducing ligand receptor (TRAIL-R)2. Addition of the 80-protein assay to established risk factors improved discrimination in the separate test sample from 0.686 (95% CI 0.682, 0.689) to 0.748 (95% CI 0.746, 0.751). A sparse model of 20 added proteins achieved a C statistic of 0.747 (95% CI 0.653, 0.842) in the test sample. We identified eight protein biomarkers, four of which are novel, for risk of MACE in community residents with type 2 diabetes, and found improved risk prediction by combining multiplex proteomics with an established risk model. Multiprotein arrays could be useful in identifying individuals with type 2 diabetes who are at highest risk of a cardiovascular event.

Outcome of acute myeloid leukemia and high-risk myelodysplastic syndrome according to health insurance status.

PubMed

Al-Ameri, Ali; Anand, Ankit; Abdelfatah, Mohamed; Kanaan, Zeyad; Hammonds, Tracy; Haller, Nairmeen; Cherry, Mohamad

2014-12-01

Age, cytogenetic status, and molecular features are the most important prognostic factors in acute myeloid leukemia (AML). This study aimed to analyze the outcomes of patients with AML or high-risk myelodysplastic syndrome (MDS) according to insurance status. A retrospective chart review was performed, covering all patients with AML and high-risk MDS evaluated and treated at Akron General Medical Center between 2002 and 2012. A Cox regression model was analyzed to account for survival over time, adjusted for insurance type, while controlling for patient age at diagnosis and patient risk of mortality. A total of 130 adult patients (age ≥ 18 years) were identified. Insurance information was available for 97 patients enrolled in the study; 3 were excluded because of self-pay status. Cox regression analysis with insurance type as the predictor found that overall survival declines over time and that the rate of decline may be influenced by insurance type (χ(2)(2) = 6.4; P = .044). The likelihood of survival in patients with Medicaid or Medicare without supplemental insurance was .552 (95% CI, .338-.903; P = .018) times the likelihood in patients who had Medicare with supplemental insurance. To explain the difference, variables of age, gender, and risk of mortality were added to the model. Age and risk of mortality were found to be significant predictors of survival. The addition of insurance type to the model did not significantly contribute (χ(2)(3) = 3.83; P = .147). No significant difference in overall survival was observed when patients with AML or high-risk MDS were analyzed according to their health insurance status. The overall survival was low in this study compared with the national average. Early referral to a specialized center or possible clinical trial enrollment may be a good alternative to improve outcome. Copyright © 2014 Elsevier Inc. All rights reserved.

Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

PubMed

Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

2016-03-01

One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi-supervised learning model is one more appropriate tool for survival analysis in clinical cancer research.

Long Term Exposure to NO2 and Diabetes Incidence in the Black Women's Health Study

PubMed Central

Coogan, Patricia F.; White, Laura F.; Yu, Jeffrey; Burnett, Richard T.; Marshall, Julian D.; Seto, Edmund; Brook, Robert D.; Palmer, Julie R.; Rosenberg, Lynn; Jerrett, Michael

2016-01-01

While laboratory studies show that air pollutants can potentiate insulin resistance, the epidemiologic evidence regarding the association of air pollution with diabetes incidence is conflicting. The purpose of the present study was to assess the association of the traffic-related nitrogen dioxide (NO2) with the incidence of diabetes in a longitudinal cohort study of African American women. We used Cox proportional hazards models to calculate hazard ratios and 95% confidence intervals (CI) for diabetes associated with exposure to NO2 among 43,003 participants in the Black Women's Health Study (BWHS). Pollutant levels at participant residential locations were estimated with 1) a land use regression model for participants living in 56 metropolitan areas, and 2) a dispersion model for participants living in 27 of the cities. From 1995-2011, 4387 cases of diabetes occurred. The hazard ratios per interquartile range of NO2 (9.7 ppb), adjusted for age, metropolitan area, education, vigorous exercise, body mass index, smoking, and diet, were 0.96 (95% CI 0.88-1.06) using the land use regression model estimates and 0.94 (95% CI 0.80, 1.10) using the dispersion model estimates. The present results do not support the hypothesis that exposure to NO2 contributes to diabetes incidence in African American women. PMID:27124624

Preventing land loss in coastal Louisiana: estimates of WTP and WTA.

PubMed

Petrolia, Daniel R; Kim, Tae-Goun

2011-03-01

A dichotomous-choice contingent-valuation survey was conducted in the State of Louisiana (USA) to estimate compensating surplus (CS) and equivalent surplus (ES) welfare measures for the prevention of future coastal wetland losses in Louisiana. Valuations were elicited using both willingness to pay (WTP) and willingness to accept compensation (WTA) payment vehicles. Mean CS (WTP) estimates based on a probit model using a Box-Cox specification on income was $825 per household annually, and mean ES (WTA) was estimated at $4444 per household annually. Regression results indicate that the major factors influencing support for land-loss prevention were income (positive, WTP model only), perceived hurricane protection benefits (positive), environmental and recreation protection (positive), distrust of government (negative), age (positive, WTA model only), and race (positive for whites). Copyright © 2010 Elsevier Ltd. All rights reserved.

KRAS polymorphisms are associated with survival of CRC in Chinese population.

PubMed

Dai, Qiong; Wei, Hui Lian; Huang, Juan; Zhou, Tie Jun; Chai, Li; Yang, Zhi-Hui

2016-04-01

rs12245, rs12587, rs9266, rs1137282, rs61764370, and rs712 of KRAS oncogene are characterized in the 3'UTR. The study highlights the important role of these polymorphisms playing in the susceptibility, oxaliplatin-based chemotherapy sensitivity, progression, and prognosis of CRC. Improved multiplex ligation detection reaction (iMLDR) technique is used for genotyping. An unconditional logistic regression model was used to estimate the association of certain polymorphism and CRC risk. The Kaplan-Meier method, log-rank test, and Cox regression model were used to evaluate the effects of polymorphisms on survival analysis. Results demonstrated that TT genotype and T allele of rs712 were associated with the increased risk of CRC; the patients with GG genotype and G allele of rs61764370 had a shorter survival and a higher risk of relapse or metastasis of CRC. Our studies supported the conclusions that rs61764370 and rs712 polymorphisms of the KRAS are functional and it may play an important role in the development of CRC and oxaliplatin-based chemotherapy efficiency and prognosis of CRC.

Usefulness of overnight pulse oximeter as the sleep assessment tool to assess the 6-year risk of road traffic collision: evidence from the Taiwan Bus Driver Cohort Study.

PubMed

Wu, Wei-Te; Tsai, Su-Shan; Liao, Hui-Yi; Lin, Yu-Jen; Lin, Ming-Hsiu; Wu, Trong-Neng; Shih, Tung-Sheng; Liou, Saou-Hsing

2017-02-01

In order to support health service organizations in arranging a system for prevention of road traffic collisions (RTC), it is important to study the usefulness of sleep assessment tools. A cohort study was used to evaluate the effectiveness of subjective and objective sleep assessment tools to assess for the 6-year risk of both first RTC event only and recurrent RTC events. The Taiwan Bus Driver Cohort Study (TBDCS) recruited 1650 professional drivers from a large bus company in Taiwan in 2005. The subjects were interviewed in person, completed the sleep assessment questionnaires and had an overnight pulse oximeter survey. Moreover, this cohort of drivers was linked to the National Traffic Accident Database (NTAD) and researchers found 139 new RTC events from 2005 to 2010. Primary outcomes were traffic collisions from NTAD, nocturnal oxygen desaturation index (ODI) from pulse oximeter, Pittsburg sleeping quality score, Epworth daytime sleepiness score, Snore Outcomes Survey score and working patterns from questionnaires. A Cox proportional hazards model and an extended Cox regression model for repeated events were performed to estimate the hazard ratio for RTC. The RTC drivers had increased ODI4 levels (5.77 ± 4.72 vs 4.99 ± 6.68 events/h; P  = 0.008) and ODI3 levels (8.68 ± 6.79 vs 7.42 ± 7.94 events/h; P  = 0.007) in comparison with non-RTC drivers. These results were consistent regardless of whether ODI was evaluated as a continuous or a categorical variable. ODI4 and ODI3 levels increased the 6-year RTC risks among professional drivers even after adjusting for age, education, history of cardiovascular disease, caffeine intake, sleeping pills used, bus driving experience and shift modes. Moreover, there was an increased trend for ODI between the stratification of the number of RTCs in comparison with the non-RTC group. In the extended Cox regression models for repeated RTC events with the Anderson and Gill intensity model and Prentice-Williams-Petersen model, measurement of ODI increased hazards of the subsequent RTC events. This study showed that an increase in the 6-year risk of RTC was associated with objective measurement of ODI for a sign of sleep-disordered breathing (SDB), but was not associated with self-reported sleeping quality or daytime sleepiness. Therefore, the overnight pulse oximeter is an effective sleep assessment tool for assessing the risk of RTC. Further research should be conducted regarding measures to prevent against SDB among professional drivers. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

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.

Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients.

PubMed

Kim, Yun Hak; Jeong, Dae Cheon; Pak, Kyoungjune; Goh, Tae Sik; Lee, Chi-Seung; Han, Myoung-Eun; Kim, Ji-Young; Liangwen, Liu; Kim, Chi Dae; Jang, Jeon Yeob; Cha, Wonjae; Oh, Sae-Ock

2017-09-29

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients.

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.

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

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.

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

Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients

PubMed Central

Kim, Yun Hak; Jeong, Dae Cheon; Pak, Kyoungjune; Goh, Tae Sik; Lee, Chi-Seung; Han, Myoung-Eun; Kim, Ji-Young; Liangwen, Liu; Kim, Chi Dae; Jang, Jeon Yeob; Cha, Wonjae; Oh, Sae-Ock

2017-01-01

Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients. PMID:29100405

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.

Validation of a two-tier grading system in an unselected, consecutive cohort of serous ovarian cancer patients.

PubMed

Battista, Marco Johannes; Cotarelo, Cristina; Almstedt, Katrin; Heimes, Anne-Sophie; Makris, Georgios-Marios; Weyer, Veronika; Schmidt, Marcus

2016-09-01

New insights into the carcinogenesis of ovarian cancer (OC) lead to the definition of low-grade and high-grade serous OC. In this study, we validated the MD Anderson Cancer Center (MDACC) two-tier grading system and compared it with the traditional three-tier grading system as suggested by the International Federation of Gynecology and Obstetrics (FIGO). Consecutive patients with serous OC were enrolled. These two grading systems were assessed independently from each other. Kaplan-Meier estimates and Cox-regression analyses were performed to validate and compare their prognostic impact. 143 consecutive patients entered the study. According to the Kaplan-Meier estimates, the MDACC grading system (p = 0.001) predicted the progression free survival (PFS) more precisely than the FIGO system (p = 0.025). The MDACC grading system (p = 0.008) but not the FIGO system (p = 0.329) showed a statistically significant difference in terms of disease specific survival (DSS). Multivariable Cox-regression analyses revealed an independent prognostic impact of the MDACC grading system but not of the FIGO system for PFS (HR 1.570; 95 % CI 1.007-2.449; p = 0.047, and HR 0.712; 95 % CI 0.476-1.066; p = 0.099, respectively). Concerning DSS, the two-tier grading system but not the FIGO system showed a prognostic impact in a univariable Cox-regression analysis (HR 2.152; 95 % CI 1.207-3.835; p = 0.009, and HR 1.258; 95 % CI 0.801-1.975; p = 0.319, respectively). We were able to validate the MDACC grading system in serous OC. Moreover, this grading system was stronger associated with survival than the FIGO system.

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.

Cyclooxygenase-2 regulated by the nuclear factor-κB pathway plays an important role in endometrial breakdown in a female mouse menstrual-like model.

PubMed

Xu, Xiangbo; Chen, Xihua; Li, Yunfeng; Cao, Huizi; Shi, Cuige; Guan, Shuo; Zhang, Shucheng; He, Bin; Wang, Jiedong

2013-08-01

The role of prostaglandins (PGs) in menstruation has long been proposed. Although evidence from studies on human and nonhuman primates supports the involvement of PGs in menstruation, whether PGs play an obligatory role in the process remains unclear. Although cyclooxygenase (COX) inhibitors have been used in the treatment of irregular uterine bleeding, the mechanism involved has not been elucidated. In this study, we used a recently established mouse menstrual-like model for investigating the role of COX in endometrial breakdown and its regulation. Administration of the nonspecific COX inhibitor indomethacin and the COX-2 selective inhibitor DuP-697 led to inhibition of the menstrual-like process. Furthermore, immunostaining analysis showed that the nuclear factor (NF)κB proteins P50, P65, and COX-2 colocalized in the outer decidual stroma at 12 to 16 hours after progesterone withdrawal. Chromatin immunoprecipitation analysis showed that NFκB binding to the Cox-2 promoter increased at 12 hours after progesterone withdrawal in vivo, and real-time PCR analysis showed that the NFκB inhibitors pyrrolidine dithiocarbamate and MG-132 inhibited Cox-2 mRNA expression in vivo and in vitro, respectively. Furthermore, COX-2 and NFκB inhibitors similarly reduced endometrial breakdown, suggesting that NFκB/COX-2-derived PGs play a critical role in this process. In addition, the CD45(+) leukocyte numbers were sharply reduced following indomethacin (COX-1 and COX-2 inhibitor), DuP-697 (COX-2 inhibitor), and pyrrolidine dithiocarbamate (NFκB inhibitor) treatment. Collectively, these data indicate that NFκB/COX-2-induced PGs regulate leukocyte influx, leading to endometrial breakdown.

[A case-control study on the influencing factors to mild cognitive impairment among the community-based elderly population].

PubMed

Ma, Fei; Wang, Ting; Yin, Jiong; Bai, Xu-Jing; Zhang, Xiao-Dong; Meng, Jun; Qu, Cheng-Yi

2008-09-01

To explore the influencing factors on mild cognitive impairment among the community-based elderly population. A 'n : m' matched case-control study was conducted to analyze the risk factors. Cox regression model of survival analysis was selected to deal with non-geometric proportional matched data which was difficult to analyze by logistic regression model. Four hundred and twenty-three cases together with nine hundred and twenty-five controls were interviewed with an uniformed questionnaire. Through univariate and multivariate cox regression analysis, the odds ratio and 95% CI of these risk factors appeared to be: physical labor as 1.396 (1.092-1.785); smoking as 1.551 (1.021-2.359); higher level of blood glucose as 1.354 (1.102-1.664); HDL-C in the serum as 1.543 (1.232-1.932); LDL-C in the serum as 1.299 (1.060-1.592); lower level of estrogen in the serum as 1.263 (1.031-1.547); hypertension as 1.967 (1.438-2.689); diabete: 1.381 (1.139-1.675); depressive disorder: 1.406 (1.110-1.780); cerebral thrombosis as 1.593 (1.307-1.943); higher SBP as 1.331 (1.129-1.569) and ApoEepsilon 4 carrier as 1.462 (1.140-1.873) respectively. Odds ratio and 95% CI on protection factors appeared to be: reading newspaper frequently as 0.610 (0.503-0.740); frequently doing housework as 0.804 (0.665-0.973); frequently engaging in social activities as 0.617 (0.502-0.757); reemployment after formal retirement as 0.759 (0.636-0.906); having acumen olfaction as 0.900 (0.845-0.958); having extrovert personality as 0.829 (0.699-0.984); being decisive as 0.811 (0.662-0.993). The major measures to prevent MCI seemed to be including the following factors as: being intellectuals, engaging in healthy life style and decreasing the risk in developing hypertension, diabetes, depressive disorder and cerebrovascular disease. However, olfactory hypoesthesia, cowardice and having introvert character, ApoEepsilon 4 carrier etc could be treated as early indications to signify MCI.

Coastal Storm Surge Analysis: Storm Forcing. Report 3. Intermediate Submission No. 1.3

DTIC Science & Technology

2013-07-01

No. 1.3 C oa st al a n d H yd ra u lic s La b or at or y Peter Vickery, Dhiraj Wadhera, Andrew Cox, Vince Cardone , Jeffrey Hanson, and Brian...Andrew Cox and Vince Cardone Oceanweather, Inc 5 River Road, Suite 1 Cos Cob, CT 06807 Jeffrey L. Hanson Field Research Facility US Army Engineer...Zou Modeling Mesh Modeling Mesh Modeling Mesh Elizabeth City State University Jinchun Yuan Web/GIS Oceanweather Vince Cardone Andrew Cox Wind

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.

A FORTRAN program for multivariate survival analysis on the personal computer.

PubMed

Mulder, P G

1988-01-01

In this paper a FORTRAN program is presented for multivariate survival or life table regression analysis in a competing risks' situation. The relevant failure rate (for example, a particular disease or mortality rate) is modelled as a log-linear function of a vector of (possibly time-dependent) explanatory variables. The explanatory variables may also include the variable time itself, which is useful for parameterizing piecewise exponential time-to-failure distributions in a Gompertz-like or Weibull-like way as a more efficient alternative to Cox's proportional hazards model. Maximum likelihood estimates of the coefficients of the log-linear relationship are obtained from the iterative Newton-Raphson method. The program runs on a personal computer under DOS; running time is quite acceptable, even for large samples.

Nimesulide, a COX-2 inhibitor, does not reduce lesion size or number in a nude mouse model of endometriosis.

PubMed

Hull, M L; Prentice, A; Wang, D Y; Butt, R P; Phillips, S C; Smith, S K; Charnock-Jones, D S

2005-02-01

Women with endometriosis have elevated levels of cyclooxygenase-2 (COX-2) in peritoneal macrophages and endometriotic tissue. Inhibition of COX-2 has been shown to reduce inflammation, angiogenesis and cellular proliferation. It may also downregulate aromatase activity in ectopic endometrial lesions. Ectopic endometrial establishment and growth are therefore likely to be suppressed in the presence of COX-2 inhibitors. We hypothesized that COX-2 inhibition would reduce the size and number of ectopic human endometrial lesions in a nude mouse model of endometriosis. The selective COX-2 inhibitor, nimesulide, was administered to estrogen-supplemented nude mice implanted with human endometrial tissue. Ten days after implantation, the number and size of ectopic endometrial lesions were evaluated and compared with lesions from a control group. Immunohistochemical assessment of vascular development and macrophage and myofibroblast infiltration in control and treated lesions was performed. There was no difference in the number or size of ectopic endometrial lesions in control and nimesulide-treated nude mice. Nimesulide did not induce a visually identifiable difference in blood vessel development or macrophage or myofibroblast infiltration in nude mouse explants. The hypothesized biological properties of COX-2 inhibition did not influence lesion number or size in the nude mouse model of endometriosis.

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.

Predictive Ability of the SVS WIfI Classification System Following Infrapopliteal Endovascular Interventions for CLI

PubMed Central

Darling, Jeremy D.; McCallum, John C.; Soden, Peter A.; Meng, Yifan; Wyers, Mark C.; Hamdan, Allen D.; Verhagen, Hence H.J.; Schermerhorn, Marc L.

2016-01-01

OBJECTIVES The Society for Vascular Surgery (SVS) Lower Extremity Guidelines Committee has composed a new threatened lower extremity classification system that reflects the three major factors that impact amputation risk and clinical management: wound, ischemia, and foot infection (WIfI). Our goal was to evaluate the predictive ability of this scale following any infrapopliteal endovascular intervention for critical limb ischemia (CLI). METHODS From 2004 to 2014, a single institution, retrospective chart review was performed at the Beth Israel Deaconess Medical Center for all patients undergoing an infrapopliteal angioplasty for CLI. Throughout these years, 673 limbs underwent an infrapopliteal endovascular intervention for tissue loss (77%), rest pain (13%), stenosis of a previously treated vessel (5%), acute limb ischemia (3%), or claudication (2%). Limbs missing a grade in any WIfI component were excluded. Limbs were stratified into clinical stages 1 to 4 based on the SVS WIfI classification for 1-year amputation risk, as well as a novel WIfI composite score from 0 to 9. Outcomes included patient functional capacity, living status, wound healing, major amputation, major adverse limb events (MALE), RAS events (reintervention, major amputation, or stenosis [>3.5x step-up by duplex]), amputation-free survival (AFS), and mortality. Predictors were identified using Kaplan-Meier survival estimates and Cox regression models. RESULTS Of the 596 limbs with CLI, 551 were classified in all three WIfI domains on a scale of 0 (least severe) to 3 (most severe). Of these 551, 84% were treated for tissue loss and 16% for rest pain. A Cox regression model illustrated that an increase in clinical stage increases the rate of major amputation (Hazard Ratio (HR), 1.6; 95% Confidence Interval [CI], 1.1–2.3). Separate regression models showed that a one-unit increase in the WIfI composite score is associated with a decrease in wound healing (1.2 [1.1–1.4]) and an increase in the rate of RAS events (1.2 [1.1–1.4]) and major amputations (1.4 [1.2–1.8]). CONCLUSIONS This study supports the ability of the SVS WIfI classification system to predict 1-year amputation, RAS events, and wound healing in patients with CLI undergoing endovascular infrapopliteal revascularization procedures. PMID:27380993

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.

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).

Binding Energy Calculation of Patchouli Alcohol Isomer Cyclooxygenase Complexes Suggested as COX-1/COX-2 Selective Inhibitor

PubMed Central

Mahdi, Chanif; Nurdiana, Nurdiana; Kikuchi, Takheshi; Fatchiyah, Fatchiyah

2014-01-01

To understand the structural features that dictate the selectivity of the two isoforms of the prostaglandin H2 synthase (PGHS/COX), the three-dimensional (3D) structure of COX-1/COX-2 was assessed by means of binding energy calculation of virtual molecular dynamic with using ligand alpha-Patchouli alcohol isomers. Molecular interaction studies with COX-1 and COX-2 were done using the molecular docking tools by Hex 8.0. Interactions were further visualized by using Discovery Studio Client 3.5 software tool. The binding energy of molecular interaction was calculated by AMBER12 and Virtual Molecular Dynamic 1.9.1 software. The analysis of the alpha-Patchouli alcohol isomer compounds showed that all alpha-Patchouli alcohol isomers were suggested as inhibitor of COX-1 and COX-2. Collectively, the scoring binding energy calculation (with PBSA Model Solvent) of alpha-Patchouli alcohol isomer compounds (CID442384, CID6432585, CID3080622, CID10955174, and CID56928117) was suggested as candidate for a selective COX-1 inhibitor and CID521903 as nonselective COX-1/COX-2. PMID:25484897

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…

COX-2 expression and function in the hyperalgesic response to paw inflammation in mice

PubMed Central

Jain, Naveen K.; Ishikawa, Tomo-o; Spigelman, Igor; Herschman, Harvey R.

2009-01-01

Peripheral inflammation and edema are often accompanied by primary and secondary hyperalgesia which are mediated by both peripheral and central mechanisms. The role of cyclooxygenase-2 (COX-2)-mediated prostanoid production in hyperalgesia is a topic of substantial current interest. We have established a murine foot-pad inflammation model in which both pharmacologic and genetic tools can be used to characterize the role of COX-2 in hyperalgesia. Zymosan, an extract from yeast, injected into the plantar surface of the hind paw induces an edema response and an increase in COX-2 expression in the hindpaw, spinal cord and brain. Zymosan-induced primary hyperalgesia, measured as a decrease in hindpaw withdrawal latency in response to a thermal stimulus, is long-lasting and is not inhibited by pre-treatment with the systemic COX-2 selective inhibitor, parecoxib (20 mg/kg). In contrast, the central component of hyperalgesia, measured as a reduction in tail flick latency in response to heat, is reduced by parecoxib. Zymosan-induced primary hyperalgesia in Cox-2−/− mice is similar to that of their Cox-2+/+ littermate controls. However, the central component of hyperalgesia is substantially reduced in Cox-2−/− versus Cox-2+/+ mice, and returns to baseline values much more rapidly. Thus pharmacological data suggest, and genetic experiments confirm, (i) that primary hyperalgesia in response to zymosan inflammation in the mouse paw is not mediated by COX-2 function and (ii) that COX-2 function plays a major role in the central component of hyperalgesia in this model of inflammation. PMID:18829279

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.

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.

Quantifying parameter uncertainty in stochastic models using the Box Cox transformation

NASA Astrophysics Data System (ADS)

Thyer, Mark; Kuczera, George; Wang, Q. J.

2002-08-01

The Box-Cox transformation is widely used to transform hydrological data to make it approximately Gaussian. Bayesian evaluation of parameter uncertainty in stochastic models using the Box-Cox transformation is hindered by the fact that there is no analytical solution for the posterior distribution. However, the Markov chain Monte Carlo method known as the Metropolis algorithm can be used to simulate the posterior distribution. This method properly accounts for the nonnegativity constraint implicit in the Box-Cox transformation. Nonetheless, a case study using the AR(1) model uncovered a practical problem with the implementation of the Metropolis algorithm. The use of a multivariate Gaussian jump distribution resulted in unacceptable convergence behaviour. This was rectified by developing suitable parameter transformations for the mean and variance of the AR(1) process to remove the strong nonlinear dependencies with the Box-Cox transformation parameter. Applying this methodology to the Sydney annual rainfall data and the Burdekin River annual runoff data illustrates the efficacy of these parameter transformations and demonstrate the value of quantifying parameter uncertainty.

Comparative pharmacogenetic analysis of risk polymorphisms in Caucasian and Vietnamese children with acute lymphoblastic leukemia: prediction of therapeutic outcome?

PubMed

Hoang, Phuong Thu Vu; Ambroise, Jérôme; Dekairelle, Anne-France; Durant, Jean-François; Butoescu, Valentina; Chi, Vu Luan Dang; Huynh, Nghia; Nguyen, Tan Binh; Robert, Annie; Vermylen, Christiane; Gala, Jean-Luc

2015-03-01

Acute lymphoblastic leukemia (ALL) is the most common of all paediatric cancers. Aside from predisposing to ALL, polymorphisms could also be associated with poor outcome. Indeed, genetic variations involved in drug metabolism could, at least partially, be responsible for heterogeneous responses to standardized leukemia treatments, hence requiring more personalized therapy. The aims of this study were to (a) to determine the prevalence of seven common genetic polymorphisms including those that affect the folate and/or thiopurine metabolic pathways, i.e. cyclin D1 (CCND1-G870A), γ-glutamyl hydrolase (GGH-C452T), methylenetetrahydrofolate reductase (MTHFR-C677T and MTHFR-A1298C), thymidylate synthase promoter (TYMS-TSER), thiopurine methyltransferase (TPMT*3A and TPMT*3C) and inosine triphosphate pyrophosphatase (ITPA-C94A), in Caucasian (n = 94, age < 20) and Vietnamese (n = 141, age < 16 years) childhood ALL and (b) to assess the impact of a multilocus genetic risk score (MGRS) on relapse-free survival (RFS) using a Cox proportional-hazards regression model. The prevalence of MTHFR-677TT genotype was significantly higher in Caucasians (P = 0.008), in contrast to the prevalence of TYMS-TSER*3R/3R and ITPA-94AA/AC genotypes which were significantly higher in Vietnamese (P < 0.001 and P = 0.02, respectively). Compared with children with a low MGRS (≤ 3), those with a high MGRS (≥ 4) were 2.06 (95% CI = 1.01, 4.22; P = 0.04) times more likely to relapse. Adding MGRS into a multivariate Cox regression model with race/ethnicity and four clinical variables improved the predictive accuracy of the model (AUC from 0.682 to 0.709 at 24 months). Including MGRS into a clinical model improved the predictive accuracy of short and medium term prognosis, hence confirming the association between well determined pharmacogenotypes and outcome of paediatric ALL. Whether variants on other genes associated with folate metabolism can substantially improve the predictive value of current MGRS is not known but deserves further evaluation. © 2014 The British Pharmacological Society.

Comparative pharmacogenetic analysis of risk polymorphisms in Caucasian and Vietnamese children with acute lymphoblastic leukemia: prediction of therapeutic outcome?

PubMed Central

Vu Hoang, Phuong Thu; Ambroise, Jérôme; Dekairelle, Anne-France; Durant, Jean-François; Butoescu, Valentina; Dang Chi, Vu Luan; Huynh, Nghia; Nguyen, Tan Binh; Robert, Annie; Vermylen, Christiane; Gala, Jean-Luc

2015-01-01

Aims Acute lymphoblastic leukemia (ALL) is the most common of all paediatric cancers. Aside from predisposing to ALL, polymorphisms could also be associated with poor outcome. Indeed, genetic variations involved in drug metabolism could, at least partially, be responsible for heterogeneous responses to standardized leukemia treatments, hence requiring more personalized therapy. The aims of this study were to (a) to determine the prevalence of seven common genetic polymorphisms including those that affect the folate and/or thiopurine metabolic pathways, i.e. cyclin D1 (CCND1-G870A), γ-glutamyl hydrolase (GGH-C452T), methylenetetrahydrofolate reductase (MTHFR-C677T and MTHFR-A1298C), thymidylate synthase promoter (TYMS-TSER), thiopurine methyltransferase (TPMT*3A and TPMT*3C) and inosine triphosphate pyrophosphatase (ITPA-C94A), in Caucasian (n = 94, age < 20) and Vietnamese (n = 141, age < 16 years) childhood ALL and (b) to assess the impact of a multilocus genetic risk score (MGRS) on relapse-free survival (RFS) using a Cox proportional-hazards regression model. Results The prevalence of MTHFR-677TT genotype was significantly higher in Caucasians (P = 0.008), in contrast to the prevalence of TYMS-TSER*3R/3R and ITPA-94AA/AC genotypes which were significantly higher in Vietnamese (P < 0.001 and P = 0.02, respectively). Compared with children with a low MGRS (≤3), those with a high MGRS (≥4) were 2.06 (95% CI = 1.01, 4.22; P = 0.04) times more likely to relapse. Adding MGRS into a multivariate Cox regression model with race/ethnicity and four clinical variables improved the predictive accuracy of the model (AUC from 0.682 to 0.709 at 24 months). Conclusion Including MGRS into a clinical model improved the predictive accuracy of short and medium term prognosis, hence confirming the association between well determined pharmacogenotypes and outcome of paediatric ALL. Whether variants on other genes associated with folate metabolism can substantially improve the predictive value of current MGRS is not known but deserves further evaluation. PMID:25099492

Genetic risk score and cardiovascular mortality in a southern european population with coronary artery disease.

PubMed

Pereira, Andreia; Mendonca, Maria Isabel; Sousa, Ana Célia; Borges, Sofia; Freitas, Sónia; Henriques, Eva; Rodrigues, Mariana; Freitas, Ana Isabel; Guerra, Graça; Ornelas, Ilídio; Pereira, Décio; Brehm, António; Palma Dos Reis, Roberto

2017-06-01

Several genetic risk scores (GRS) have been associated with cardiovascular disease; their role, however, in survival from proven coronary artery disease (CAD) have yielded conflicting results. The objective of this study was to evaluate long-term cardiovascular mortality according to the genetic risk score in a Southern European population with CAD. A cohort of 1464 CAD patients with angiographic proven CAD were followed up prospectively for up to 58.3 (interquartile range: 25.8-88.1) months. Genotyping of 32 single-nucleotide polymorphisms previously associated with CAD was performed using oligonucleotides probes marked with fluorescence for each allele. GRS was constructed according to the additive model assuming codominance and categorised using the median (=26). Cox Regression analysis was performed to determine independent multivariate predictors of cardiovascular mortality. Kaplan-Meier survival curves compared high vs low GRS using log-rank test. C-index was done for our population, as a measure of discrimination in survival analysis model. During a mean follow-up of 58.3 months, 156 patients (10.7%) died, 107 (7.3%) of CV causes. High GRS (≥26) was associated with reduced cardiovascular survival. Survival analysis with Cox regression model adjusted for 8 variables showed that high GRS, dyslipidemia, diabetes and 3-vessel disease were independent risk factors for cardiovascular mortality (HR=1.53, P=.037; HR=3.64, P=.012; HR=1.75, P=.004; HR=2.97, P<.0001, respectively). At the end of follow-up, the estimated survival probability was 70.8% for high GRS and 80.8% for low GRS (Log-rank test 5.6; P=.018). C-Index of 0.71 was found when GRS was added to a multivariate survival model of diabetes, dyslipidemia, smoking, hypertension and 3 vessel disease, stable angina and dual antiplatelet therapy. Besides the classical risk factors management, this work highlights the relevance of the genetic profile in survival from CAD. It is expected that new therapies will be dirsected to gene targets with proven value in cardiovascular survival. © 2017 John Wiley & Sons Ltd.

African American Race is an Independent Risk Factor in Survival from Initially Diagnosed Localized Breast Cancer

PubMed Central

Wieder, Robert; Shafiq, Basit; Adam, Nabil

2016-01-01

BACKGROUND: African American race negatively impacts survival from localized breast cancer but co-variable factors confound the impact. METHODS: Data sets were analyzed from the Surveillance, Epidemiology and End Results (SEER) directories from 1973 to 2011 consisting of patients with designated diagnosis of breast adenocarcinoma, race as White or Caucasian, Black or African American, Asian, American Indian or Alaskan Native, Native Hawaiian or Pacific Islander, age, stage I, II or III, grade 1, 2 or 3, estrogen receptor or progesterone receptor positive or negative, marital status as single, married, separated, divorced or widowed and laterality as right or left. The Cox Proportional Hazards Regression model was used to determine hazard ratios for survival. Chi square test was applied to determine the interdependence of variables found significant in the multivariable Cox Proportional Hazards Regression analysis. Cells with stratified data of patients with identical characteristics except African American or Caucasian race were compared. RESULTS: Age, stage, grade, ER and PR status and marital status significantly co-varied with race and with each other. Stratifications by single co-variables demonstrated worse hazard ratios for survival for African Americans. Stratification by three and four co-variables demonstrated worse hazard ratios for survival for African Americans in most subgroupings with sufficient numbers of values. Differences in some subgroupings containing poor prognostic co-variables did not reach significance, suggesting that race effects may be partly overcome by additional poor prognostic indicators. CONCLUSIONS: African American race is a poor prognostic indicator for survival from breast cancer independent of 6 associated co-variables with prognostic significance. PMID:27698895

Persistent disparities in obesity risk among public schoolchildren from childhood through adolescence.

PubMed

Chen, Danhong; Thomsen, Michael R; Nayga, Rodolfo M; Bennett, Judy L

2016-08-01

Arkansas is among the poorest states and has high rates of childhood obesity. In 2003, it became the first state to systematically screen public schoolchildren for unhealthy weight status. This study aims to examine the socioeconomic disparities in Body Mass Index (BMI) growth and the risk of the onset of obesity from childhood through adolescence. This study analyzed (in 2015) the data for a large cohort of Arkansas public schoolchildren for whom BMIs were measured from school years 2003/2004 through 2009/2010. A linear growth curve model was used to assess how child-level sociodemographics and neighborhood characteristics were associated with growth in BMI z-scores. Cox regression was subsequently used to investigate how these factors were associated with the onset of obesity. Because children might be classified as obese in multiple years, sensitivity analysis was conducted using recurrent event Cox regression. Survival analysis indicated that the risk of onset of obesity rose sharply between ages of 5 and 10 and then again after age 15. The socioeconomic disparities in obesity risk persisted from kindergarten through adolescence. While better access to full service restaurants was associated with lower risk of the onset of obesity (Hazard Ratio (HR)=0.98, 95% CI=0.97-0.99), proximity to fast food restaurants was related to increased risk of the onset of obesity (HR=1.01, 95% CI=1.00-1.01). This analysis stresses the need for policies to narrow the socioeconomic gradient and identifies important time periods for preventative interventions in childhood obesity. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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

The Prognostic Value of Epithelial Membrane Protein 1 (EMP-1) in Patients with Laryngeal Carcinoma

PubMed Central

Liu, Chang; Wei, Xiaojun; Li, Feng; Wang, Li; Ruan, Xinjian; Jia, Jia; Zhang, Xia

2017-01-01

Background In the present study, we aimed to investigate the prognostic value of epithelial membrane protein 1 (EMP-1) gene in patients diagnosed with laryngeal carcinoma (LC). Material/Methods Patients who were pathologically diagnosed with LC were enrolled in the present study. The expression levels of EMP-1 in tumor tissues and corresponding normal tissues collected from the LC patients were detected by semi-reverse transcriptase polymerase chain reaction (semi-RT-PCR). Chi-square analysis was used to evaluate the relationship between EMP-1 expression level and clinical characteristics. Survival analysis for the study population was analyzed by Kaplan-Meier method with log rank test. Additionally, Cox regression model was applied to evaluate the prognostic value of EMP-1 in LC patients. Results 106 LC patients, including 55 men and 51 women, were enrolled in the present study. Semi-RT-PCR demonstrated that the expression level of EMP-1 was decreased in tumor tissues, compared with adjacent normal tissues (p<0.001). Moreover, the level was significantly associated with lymph node metastasis, histological grade, and clinical stage (p<0.05 for all). In addition, low levels of EMP-1 was significantly correlated with poor survival rate (log rank test, p=0.020). Cox regression analysis indicated that EMP-1 was an independent marker for LC prognosis (HR=2.755, 95% CI=1.123–6.760, p=0.027). Conclusions The abnormal expression of EMP-1 may be associated with progression of LC and the gene may act as a prognostic marker for LC. PMID:28779068

The Prognostic Value of Epithelial Membrane Protein 1 (EMP-1) in Patients with Laryngeal Carcinoma.

PubMed

Liu, Chang; Wei, Xiaojun; Li, Feng; Wang, Li; Ruan, Xinjian; Jia, Jia; Zhang, Xia

2017-08-05

BACKGROUND In the present study, we aimed to investigate the prognostic value of epithelial membrane protein 1 (EMP-1) gene in patients diagnosed with laryngeal carcinoma (LC). MATERIAL AND METHODS Patients who were pathologically diagnosed with LC were enrolled in the present study. The expression levels of EMP-1 in tumor tissues and corresponding normal tissues collected from the LC patients were detected by semi-reverse transcriptase polymerase chain reaction (semi-RT-PCR). Chi-square analysis was used to evaluate the relationship between EMP-1 expression level and clinical characteristics. Survival analysis for the study population was analyzed by Kaplan-Meier method with log rank test. Additionally, Cox regression model was applied to evaluate the prognostic value of EMP-1 in LC patients. RESULTS 106 LC patients, including 55 men and 51 women, were enrolled in the present study. Semi-RT-PCR demonstrated that the expression level of EMP-1 was decreased in tumor tissues, compared with adjacent normal tissues (p<0.001). Moreover, the level was significantly associated with lymph node metastasis, histological grade, and clinical stage (p<0.05 for all). In addition, low levels of EMP-1 was significantly correlated with poor survival rate (log rank test, p=0.020). Cox regression analysis indicated that EMP-1 was an independent marker for LC prognosis (HR=2.755, 95% CI=1.123-6.760, p=0.027). CONCLUSIONS The abnormal expression of EMP-1 may be associated with progression of LC and the gene may act as a prognostic marker for LC.

Marijuana use and risk of lung cancer: a 40-year cohort study.

PubMed

Callaghan, Russell C; Allebeck, Peter; Sidorchuk, Anna

2013-10-01

Cannabis (marijuana) smoke and tobacco smoke contain many of the same potent carcinogens, but a critical-yet unresolved-medical and public-health issue is whether cannabis smoking might facilitate the development of lung cancer. The current study aimed to assess the risk of lung cancer among young marijuana users. A population-based cohort study examined men (n = 49,321) aged 18-20 years old assessed for cannabis use and other relevant variables during military conscription in Sweden in 1969-1970. Participants were tracked until 2009 for incident lung cancer outcomes in nationwide linked medical registries. Cox regression modeling assessed relationships between cannabis smoking, measured at conscription, and the hazard of subsequently receiving a lung cancer diagnosis. At the baseline conscription assessment, 10.5 % (n = 5,156) reported lifetime use of marijuana and 1.7 % (n = 831) indicated lifetime use of more than 50 times, designated as "heavy" use. Cox regression analyses (n = 44,284) found that such "heavy" cannabis smoking was significantly associated with more than a twofold risk (hazard ratio 2.12, 95 % CI 1.08-4.14) of developing lung cancer over the 40-year follow-up period, even after statistical adjustment for baseline tobacco use, alcohol use, respiratory conditions, and socioeconomic status. Our primary finding provides initial longitudinal evidence that cannabis use might elevate the risk of lung cancer. In light of the widespread use of marijuana, especially among adolescents and young adults, our study provides important data for informing the risk-benefit calculus of marijuana smoking in medical, public-health, and drug-policy settings.

[Survival following the first admission in an integrated dual disorders treatment ward (IDDTW): preliminary results from a cohort study].

PubMed

Gimelfarb, Yuri; Becatel, Ety; Wolf, Aviva; Baruch, Yehuda

2014-01-01

Dual disorders (co-occurring severe mental illness [SMI] and substance abuse disorders in the same person) are extremely common among patients receiving mental health services. Dual disorders are associated with increased all-cause mortality, as compared with patients with SMI. Scientific evidence is lacking on the survival of dual disorders subjects, who had psychiatric inpatient care. To determine the long term survival rates of patients after the first admission in an IDDTW and to identify their baseline predictors. The charts of 258 subjects admitted to IDDTW during the period 2002-2004 were assessed at least 8 years after the first admission. Psychiatric diagnoses were established and grouped according to the International Statistical Classification of Diseases and Related Health Problems 10th edition (ICD-10). The Kaplan-Meier survival analysis was used to estimate the cumulative survival rates, and the predictive values of different variables were assessed by Cox proportional-hazards regression model. The cumulative 1-, 2-, 4-, 6- and 8-year survival rates of all subjects were 98.06%, 96.51%, 91.47, 86.43% and 81.78%, respectively, without statistically significant differences between subgroups of psychiatric diagnoses. Multivariate Cox regression analysis revealed that the age at death was the only independent predictor of all-cause mortality (hazard ratio = .96; 95% confidence interval .93 to .99; p < .009). Those of young age are at a particularly low risk of long term survival. More targeted health care is required to address the specific needs of this vulnerable subgroup. Further research of survival into specific risk groups is required.

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.

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

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.

Survival analysis in hematologic malignancies: recommendations for clinicians

PubMed Central

Delgado, Julio; Pereira, Arturo; Villamor, Neus; López-Guillermo, Armando; Rozman, Ciril

2014-01-01

The widespread availability of statistical packages has undoubtedly helped hematologists worldwide in the analysis of their data, but has also led to the inappropriate use of statistical methods. In this article, we review some basic concepts of survival analysis and also make recommendations about how and when to perform each particular test using SPSS, Stata and R. In particular, we describe a simple way of defining cut-off points for continuous variables and the appropriate and inappropriate uses of the Kaplan-Meier method and Cox proportional hazard regression models. We also provide practical advice on how to check the proportional hazards assumption and briefly review the role of relative survival and multiple imputation. PMID:25176982

Transgenic expression of cyclooxygenase-2 (COX2) causes premature aging phenotypes in mice.

PubMed

Kim, Joohwee; Vaish, Vivek; Feng, Mingxiao; Field, Kevin; Chatzistamou, Ioulia; Shim, Minsub

2016-10-07

Cyclooxygenase (COX) is a key enzyme in the biosynthesis of prostanoids, lipid signaling molecules that regulate various physiological processes. COX2, one of the isoforms of COX, is highly inducible in response to a wide variety of cellular and environmental stresses. Increased COX2 expression is thought to play a role in the pathogenesis of many age-related diseases. COX2 expression is also reported to be increased in the tissues of aged humans and mice, which suggests the involvement of COX2 in the aging process. However, it is not clear whether the increased COX2 expression is causal to or a result of aging. We have now addressed this question by creating an inducible COX2 transgenic mouse model. Here we show that post-natal expression of COX2 led to a panel of aging-related phenotypes. The expression of p16, p53, and phospho-H2AX was increased in the tissues of COX2 transgenic mice. Additionally, adult mouse lung fibroblasts from COX2 transgenic mice exhibited increased expression of the senescence-associated β-galactosidase. Our study reveals that the increased COX2 expression has an impact on the aging process and suggests that modulation of COX2 and its downstream signaling may be an approach for intervention of age-related disorders.

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…

Role of phosphorylated extracellular signal-regulated kinase, calcitonin gene-related peptide and cyclooxygenase-2 in experimental rat models of migraine

PubMed Central

DONG, XIAOMENG; HU, YAOZHI; JING, LONG; CHEN, JINBO

2015-01-01

Although migraine is a common neurological condition, the pathomechanism is not yet fully understood. Activation of the trigeminovascular system (TVS) has an important function in this disorder and neurogenic inflammation and central sensitization are important mechanisms underlying this condition. Nitroglycerin (NTG) infusion in rats closely mimics a universally accepted human model of migraine. Electrical stimulation of the trigeminal ganglion (ESTG) of rats can also activate TVS during a migraine attack. Numerous studies have revealed that phosphorylated extracellular signal-regulated kinase (p-ERK), calcitonin gene-related peptide (CGRP) and cyclooxygenase-2 (COX-2) are involved in pain and nociceptive pathways. However, few studies have examined whether p-ERK, CGRP and COX-2 are involved in neurogenic inflammation and central sensitization. In the present study, the expression of p-ERK, CGRP and COX-2 was detected in the dura mater, trigeminal ganglion (TG) and spinal trigeminal nucleus caudalis in NTG-induced rats and ESTG models by immunohistochemistry. The three areas considered were crucial components of the TVS. The selective COX-2 inhibitor nimesulide was used in ESTG rats to examine the association between p-ERK, CGRP and COX-2. The results demonstrated that p-ERK, CGRP and COX-2 mediated neurogenic inflammation and central sensitization in migraine. In addition, the expression of p-ERK and CGRP was attenuated by the COX-2 inhibitor. PMID:25892078

Indomethacin treatment prior to pentylenetetrazole-induced seizures downregulates the expression of il1b and cox2 and decreases seizure-like behavior in zebrafish larvae.

PubMed

Barbalho, Patrícia Gonçalves; Lopes-Cendes, Iscia; Maurer-Morelli, Claudia Vianna

2016-03-09

It has been demonstrated that the zebrafish model of pentylenetetrazole (PTZ)-evoked seizures and the well-established rodent models of epilepsy are similar pertaining to behavior, electrographic features, and c-fos expression. Although this zebrafish model is suitable for studying seizures, to date, inflammatory response after seizures has not been investigated using this model. Because a relationship between epilepsy and inflammation has been established, in the present study we investigated the transcript levels of the proinflammatory cytokines interleukin-1 beta (il1b) and cyclooxygenase-2 (cox2a and cox2b) after PTZ-induced seizures in the brain of zebrafish 7 days post fertilization. Furthermore, we exposed the fish to the nonsteroidal anti-inflammatory drug indomethacin prior to PTZ, and we measured its effect on seizure latency, number of seizure behaviors, and mRNA expression of il1b, cox2b, and c-fos. We used quantitative real-time PCR to assess the mRNA expression of il1b, cox2a, cox2b, and c-fos, and visual inspection was used to monitor seizure latency and the number of seizure-like behaviors. We found a short-term upregulation of il1b, and we revealed that cox2b, but not cox2a, was induced after seizures. Indomethacin treatment prior to PTZ-induced seizures downregulated the mRNA expression of il1b, cox2b, and c-fos. Moreover, we observed that in larvae exposed to indomethacin, seizure latency increased and the number of seizure-like behaviors decreased. This is the first study showing that il1b and cox-2 transcripts are upregulated following PTZ-induced seizures in zebrafish. In addition, we demonstrated the anticonvulsant effect of indomethacin based on (1) the inhibition of PTZ-induced c-fos transcription, (2) increase in seizure latency, and (3) decrease in the number of seizure-like behaviors. Furthermore, anti-inflammatory effect of indomethacin is clearly demonstrated by the downregulation of the mRNA expression of il1b and cox2b. Our results are supported by previous evidences suggesting that zebrafish is a suitable alternative for studying inflammation, seizures, and the effect of anti-inflammatory compounds on seizure suppression.

Identification of Ganoderma Disease Resistance Loci Using Natural Field Infection of an Oil Palm Multiparental Population

PubMed Central

Tisné, Sébastien; Pomiès, Virginie; Riou, Virginie; Syahputra, Indra; Cochard, Benoît; Denis, Marie

2017-01-01

Multi-parental populations are promising tools for identifying quantitative disease resistance loci. Stem rot caused by Ganoderma boninense is a major threat to palm oil production, with yield losses of up to 80% prompting premature replantation of palms. There is evidence of genetic resistance sources, but the genetic architecture of Ganoderma resistance has not yet been investigated. This study aimed to identify Ganoderma resistance loci using an oil palm multi-parental population derived from nine major founders of ongoing breeding programs. A total of 1200 palm trees of the multi-parental population was planted in plots naturally infected by Ganoderma, and their health status was assessed biannually over 25 yr. The data were treated as survival data, and modeled using the Cox regression model, including a spatial effect to take the spatial component in the spread of Ganoderma into account. Based on the genotypes of 757 palm trees out of the 1200 planted, and on pedigree information, resistance loci were identified using a random effect with identity-by-descent kinship matrices as covariance matrices in the Cox model. Four Ganoderma resistance loci were identified, two controlling the occurrence of the first Ganoderma symptoms, and two the death of palm trees, while favorable haplotypes were identified among a major gene pool for ongoing breeding programs. This study implemented an efficient and flexible QTL mapping approach, and generated unique valuable information for the selection of oil palm varieties resistant to Ganoderma disease. PMID:28592650

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.

Maternal and Neonatal Birth Factors Affecting the Age of ASD Diagnosis.

PubMed

Darcy-Mahoney, Ashley; Minter, Bonnie; Higgins, Melinda; Guo, Ying; Zauche, Lauren Head; Hirst, Jessica

2016-12-01

Early diagnosis of autism spectrum disorders (ASD) enables early intervention that improves long term functioning of children with ASD but is often delayed until age of school entry. Few studies have identified factors that affect timely diagnosis. This study addressed how maternal education, race, age, marital status as well as neonatal birth factors affect the age at which a child is diagnosed with ASD. This study involved a retrospective analysis of 664 records of children treated at one of the largest autism treatment centers in the United States from March 1, 2009 to December 30, 2010. Logistic regression and Cox proportional hazards regression were used to identify maternal and neonatal factors associated with age of diagnosis. Infant gender, maternal race, marital status, and maternal age were identified as significant factors for predicting the age of ASD diagnosis. In the Cox proportional hazards regression model, only maternal race and marital status were included. Median survival age till diagnosis of children born to married mothers was 53.4 months compared to 57.8 months and 63.7 months of children born to single and divorced or widowed mothers respectively. Median survival age till diagnosis for children of African American mothers was 53.8 months compared to 57.2 months for children of Caucasian mothers. No statistically significant difference of timing of ASD diagnosis was found for children of varying gestational age. Children born to older or married mothers and mothers of minority races were more likely to have an earlier ASD diagnosis. No statistically significant differences in timing of ASD diagnosis were found for children born at varying gestational ages. Identification of these factors has the potential to inform public health outreach aimed at promoting timely ASD diagnosis. This work could enhance clinical practice for timelier diagnoses of ASD by supporting parents and clinicians around the world in identifying risk factors beyond gender and SES and developing strategies to recognize earlier signs of ASD and contribute to improved development outcomes in children with ASD.

Serum Wisteria floribunda agglutinin-positive Mac-2-binding protein evaluates liver function and predicts prognosis in liver cirrhosis.

PubMed

Xu, Wen Ping; Wang, Ze Rui; Zou, Xia; Zhao, Chen; Wang, Rui; Shi, Pei Mei; Yuan, Zong Li; Yang, Fang; Zeng, Xin; Wang, Pei Qin; Sultan, Sakhawat; Zhang, Yan; Xie, Wei Fen

2018-04-01

Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA + -M2BP) is a novel glycobiomarker for evaluating liver fibrosis, but less is known about its role in liver cirrhosis (LC). This study aimed to investigate the utility of WFA + -M2BP in evaluating liver function and predicting prognosis of cirrhotic patients. We retrospectively included 197 patients with LC between 2013 and 2016. Serum WFA + -M2BP and various biochemical parameters were measured in all patients. With a median follow-up of 23 months, liver-related complications and deaths of 160 patients were recorded. The accuracy of WFA + -M2BP in evaluating liver function, predicting decompensation and mortality were measured by the receiver operating characteristic (ROC) curve, logistic and Cox's regression analyses, respectively. WFA + -M2BP levels increased with elevated Child-Pugh classification, especially in patients with hepatitis B virus (HBV) infection. ROC analysis confirmed the high reliability of WFA + -M2BP for the assessment of liver function using Child-Pugh classification. WFA + -M2BP was also significantly positively correlated with the model for end-stage liver disease (MELD) score. Multivariate logistic regression analysis indicated WFA + -M2BP as an independent predictor of clinical decompensation for compensated patients (odds ratio 11.958, 95% confidence interval [CI] 1.876-76.226, P = 0.009), and multivariate Cox's regression analysis verified WFA + -M2BP as an independent risk factor for liver-related death in patients with HBV infection (hazards ratio 10.596, 95% CI 1.356-82.820, P = 0.024). Serum WFA + -M2BP is a reliable predictor of liver function and prognosis in LC and could be incorporated into clinical surveillance strategies for LC patients, especially those with HBV infection. © 2018 Chinese Medical Association Shanghai Branch, Chinese Society of Gastroenterology, Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.

Operating room-to-incision interval and neonatal outcome in emergency caesarean section: a retrospective 5-year cohort study.

PubMed

Palmer, E; Ciechanowicz, S; Reeve, A; Harris, S; Wong, D J N; Sultan, P

2018-07-01

We conducted a 5-year retrospective cohort study on women undergoing caesarean section to investigate factors influencing the operating room-to-incision interval. Time-to-event analysis was performed for category-1 caesarean section using a Cox proportional hazards regression model. Covariates included: anaesthetic technique; body mass index; age; parity; time of delivery; and gestational age. Binary logistic regression was performed for 5-min Apgar score ≥ 7. There were 677 women who underwent category-1 caesarean section and who met the entry criteria. Unadjusted median (IQR [range]) operating room-to-incision intervals were: epidural top-up 11 (7-17 [0-87]) min; general anaesthesia 6 (4-11 [0-69]) min; spinal 13 (10-20 [0-83]) min; and combined spinal-epidural 24 (13-35 [0-75]) min. Cox regression showed general anaesthesia to be the most rapid method with a hazard ratio (95%CI) of 1.97 (1.60-2.44; p < 0.0001), followed by epidural top-up (reference group), spinal anaesthesia 0.79 (0.65-0.96; p = 0.02) and combined spinal-epidural 0.48 (0.35-0.67; p < 0.0001). Underweight and overweight body mass indexes were associated with longer operating room-to-incision intervals. General anaesthesia was associated with fewer 5-min Apgar scores ≥ 7 with an odds ratio (95%CI) of 0.28 (0.11-0.68; p < 0.01). There was no difference in neonatal outcomes between the first and fifth quintiles for operating room-to-incision intervals. General anaesthesia is associated with the most rapid operating room-to-incision interval for category-1 caesarean section, but is also associated with worse short term neonatal outcomes. Longer operating room-to-incision intervals were not associated with worse neonatal outcomes. © 2018 The Association of Anaesthetists of Great Britain and Ireland.

Angiotensin-converting enzyme inhibitors delay the occurrence of renal involvement and are associated with a decreased risk of disease activity in patients with systemic lupus erythematosus--results from LUMINA (LIX): a multiethnic US cohort.

PubMed

Durán-Barragán, S; McGwin, G; Vilá, L M; Reveille, J D; Alarcón, G S

2008-07-01

To examine if angiotensin-converting enzyme (ACE) inhibitor use delays the occurrence of renal involvement and decreases the risk of disease activity in SLE patients. SLE patients (Hispanics, African Americans and Caucasians) from the lupus in minorities: nature vs nurture (LUMINA) cohort were studied. Renal involvement was defined as ACR criterion and/or biopsy-proven lupus nephritis. Time-to-renal involvement was examined by univariable and multivariable Cox proportional hazards regression analyses. Disease activity was examined with a case-crossover design and a conditional logistic regression model; in the case intervals, a decrease in the SLAM-R score >or=4 points occurred but not in the control intervals. Eighty of 378 patients (21%) were ACE inhibitor users; 298 (79%) were not. The probability of renal involvement free-survival at 10 yrs was 88.1% for users and 75.4% for non-users (P = 0.0099, log rank test). Users developed persistent proteinuria and/or biopsy-proven lupus nephritis (7.1%) less frequently than non-users (22.9%), P = 0.016. By multivariable Cox proportional hazards regression analyses, ACE inhibitors use [hazard ratio (HR) 0.27; 95% CI 0.09, 0.78] was associated with a longer time-to-renal involvement occurrence whereas African American ethnicity (HR 3.31; 95% CI 1.44, 7.61) was with a shorter time. ACE inhibitor use (54/288 case and 254/1148 control intervals) was also associated with a decreased risk of disease activity (HR 0.56; 95% CI 0.34, 0.94). ACE inhibitor use delays the development of renal involvement and associates with a decreased risk of disease activity in SLE; corroboration of these findings in other lupus cohorts is desirable before practice recommendations are formulated.

Training to Provide Psychiatric Genetic Counseling: How Does It Impact Recent Graduates' and Current Students' Readiness to Provide Genetic Counseling for Individuals with Psychiatric Illness and Attitudes towards this Population?

PubMed

Low, Ashley; Dixon, Shannan; Higgs, Amanda; Joines, Jessica; Hippman, Catriona

2018-02-01

Mental illness is extremely common and genetic counselors frequently see patients with mental illness. Genetic counselors report discomfort in providing psychiatric genetic counseling (GC), suggesting the need to look critically at training for psychiatric GC. This study aimed to investigate psychiatric GC training and its impact on perceived preparedness to provide psychiatric GC (preparedness). Current students and recent graduates were invited to complete an anonymous survey evaluating psychiatric GC training and outcomes. Bivariate correlations (p<.10) identified variables for inclusion in a logistic regression model to predict preparedness. Data were checked for assumptions underlying logistic regression. The logistic regression model for the 286 respondents [χ 2 (8)=84.87, p<.001] explained between 37.1% (Cox & Snell R 2 =.371) and 49.7% (Nagelkerke R 2 =.497) of the variance in preparedness scores. More frequent psychiatric GC instruction (OR=5.13), more active methods for practicing risk assessment (OR=4.43), and education on providing resources for mental illness (OR=4.99) made uniquely significant contributions to the model (p<.001). Responses to open-ended questions revealed interest in further psychiatric GC training, particularly enabling "hands on" experience. This exploratory study suggests that enriching GC training through more frequent psychiatric GC instruction and more active opportunities to practice psychiatric GC skills will support students in feeling more prepared to provide psychiatric GC after graduation.

Low-level laser therapy (LLLT) reduces the COX-2 mRNA expression in both subplantar and total brain tissues in the model of peripheral inflammation induced by administration of carrageenan.

PubMed

Prianti, Antonio Carlos Guimarães; Silva, José Antonio; Dos Santos, Regiane Feliciano; Rosseti, Isabela Bueno; Costa, Maricilia Silva

2014-07-01

In the classical model of edema formation and hyperalgesia induced by carrageenan administration in rat paw, the increase in prostaglandin E2 (PGE2) production in the central nervous system (CNS) contributes to the severity of the inflammatory and pain responses. Prostaglandins are generated by the cyclooxygenase (COX). There are two distinct COX isoforms, COX-1 and COX-2. In inflammatory tissues, COX-2 is greatly expressed producing proinflammatory prostaglandins (PGs). Low-level laser therapy (LLLT) has been used in the treatment of inflammatory pathologies, reducing both pain and acute inflammatory process. Herein we studied the effect of LLLT on both COX-2 and COX-1 messenger RNA (mRNA) expression in either subplantar or brain tissues taken from rats treated with carrageenan. The experiment was designed as follows: A1 (saline), A2 (carrageenan-0.5 mg/paw), A3 (carrageenan-0.5 mg/paw + LLLT), A4 (carrageenan-1.0 mg/paw), and A5 (carrageenan-1.0 mg/paw + LLLT). Animals from the A3 and A5 groups were irradiated at 1 h after carrageenan administration, using a diode laser with an output power of 30 mW and a wavelength of 660 nm. The laser beam covered an area of 0.785 cm(2), resulting in an energy dosage of 7.5 J/cm(2). Both COX-2 and COX-1 mRNAs were measured by RT-PCR. Six hours after carrageenan administration, COX-2 mRNA expression was significantly increased both in the subplantar (2.2-4.1-fold) and total brain (8.65-13.79-fold) tissues. COX-1 mRNA expression was not changed. LLLT (7.5 J/cm(2)) reduced significantly the COX-2 mRNA expression both in the subplantar (~2.5-fold) and brain (4.84-9.67-fold) tissues. The results show that LLLT is able to reduce COX-2 mRNA expression. It is possible that the mechanism of LLLT decreasing hyperalgesia is also related to its effect in reducing the COX-2 expression in the CNS.

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.

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

Impact of Insecticide-Treated Net Ownership on All-Cause Child Mortality in Malawi, 2006-2010.

PubMed

Florey, Lia S; Bennett, Adam; Hershey, Christine L; Bhattarai, Achuyt; Nielsen, Carrie F; Ali, Doreen; Luhanga, Misheck; Taylor, Cameron; Eisele, Thomas P; Yé, Yazoume

2017-09-01

Insecticide-treated nets (ITNs) have been shown to be highly effective at reducing malaria morbidity and mortality in children. However, there are limited studies that assess the association between increasing ITN coverage and child mortality over time, at the national level, and under programmatic conditions. Two analytic approaches were used to examine this association: a retrospective cohort analysis of individual children and a district-level ecologic analysis. To evaluate the association between household ITN ownership and all-cause child mortality (ACCM) at the individual level, data from the 2010 Demographic and Health Survey (DHS) were modeled in a Cox proportional hazards framework while controlling for numerous environmental, household, and individual confounders through the use of exact matching. To evaluate population-level association between ITN ownership and ACCM between 2006 and 2010, program ITN distribution data and mortality data from the 2006 Multiple Indicator Cluster Survey and the 2010 DHS were aggregated at the district level and modeled using negative binomial regression. In the Cox model controlling for household, child and maternal health factors, children between 1 and 59 months in households owning an ITN had significantly lower mortality compared with those without an ITN (hazard ratio = 0.75, 95% confidence interval [CI] = 0.62-90). In the district-level model, higher ITN ownership was significantly associated with lower ACCM (incidence rate ratio = 0.77; 95% CI = 0.60-0.98). These findings suggest that increasing ITN ownership may have contributed to the decline in ACCM during 2006-2010 in Malawi and represent a novel use of district-level data from nationally representative surveys.

Comparison of the risk factors effects between two populations: two alternative approaches illustrated by the analysis of first and second kidney transplant recipients

PubMed Central

2013-01-01

Background Whereas the prognosis of second kidney transplant recipients (STR) compared to the first ones has been frequently analyzed, no study has addressed the issue of comparing the risk factor effects on graft failure between both groups. Methods Here, we propose two alternative strategies to study the heterogeneity of risk factors between two groups of patients: (i) a multiplicative-regression model for relative survival (MRS) and (ii) a stratified Cox model (SCM) specifying the graft rank as strata and assuming subvectors of the explicatives variables. These developments were motivated by the analysis of factors associated with time to graft failure (return-to-dialysis or patient death) in second kidney transplant recipients (STR) compared to the first ones. Estimation of the parameters was based on partial likelihood maximization. Monte-Carlo simulations associated with bootstrap re-sampling was performed to calculate the standard deviations for the MRS. Results We demonstrate, for the first time in renal transplantation, that: (i) male donor gender is a specific risk factor for STR, (ii) the adverse effect of recipient age is enhanced for STR and (iii) the graft failure risk related to donor age is attenuated for STR. Conclusion While the traditional Cox model did not provide original results based on the renal transplantation literature, the proposed relative and stratified models revealed new findings that are useful for clinicians. These methodologies may be of interest in other medical fields when the principal objective is the comparison of risk factors between two populations. PMID:23915191

Primary gastric mucosa associated lymphoid tissue lymphoma: Clinical data predicted treatment outcome

PubMed Central

Todorovic, Milena; Balint, Bela; Jevtic, Miodrag; Suvajdzic, Nada; Ceric, Amela; Stamatovic, Dragana; Markovic, Olivera; Perunicic, Maja; Marjanovic, Slobodan; Krstic, Miodrag

2008-01-01

AIM: To determine clinical characteristics and treatment outcome of gastric lymphoma after chemotherapy and immuno-chemotherapy. METHODS: Thirty four patients with primary gastric mucosa associated lymphoid tissue (MALT) lymphoma (Ann Arbor stages I to IV) were enrolled. All had upper gastric endoscopy, abdominal ultrasonography, CT and H pylori status assessment (histology and serology). After anti-H pylori treatment and initial chemotherapy, patients were re-examined every 4 mo. RESULTS: Histological regression of the lymphoma was complete in 22/34 (64.7%) and partial in 9 (26.5%) patients. Median follow up time for these 31 responders was 60 mo (range 48-120). No regression was noted in 3 patients. Among the 25 (73.5%) H pylori positive patients, the eradication rate was 100%. CONCLUSION: Using univariate analysis, predictive factors for overall survival were international prognostic index (IPI) score, hemoglobin level, erythrocyte sedimentation rate (ESR), and platelet numbers (P < 0.005). In addition to this, Cox proportion hazard model differentiate IPI score, ESR, and platelets as predictors of survival. PMID:18416467

Variable selection in semiparametric cure models based on penalized likelihood, with application to breast cancer clinical trials.

PubMed

Liu, Xiang; Peng, Yingwei; Tu, Dongsheng; Liang, Hua

2012-10-30

Survival data with a sizable cure fraction are commonly encountered in cancer research. The semiparametric proportional hazards cure model has been recently used to analyze such data. As seen in the analysis of data from a breast cancer study, a variable selection approach is needed to identify important factors in predicting the cure status and risk of breast cancer recurrence. However, no specific variable selection method for the cure model is available. In this paper, we present a variable selection approach with penalized likelihood for the cure model. The estimation can be implemented easily by combining the computational methods for penalized logistic regression and the penalized Cox proportional hazards models with the expectation-maximization algorithm. We illustrate the proposed approach on data from a breast cancer study. We conducted Monte Carlo simulations to evaluate the performance of the proposed method. We used and compared different penalty functions in the simulation studies. Copyright © 2012 John Wiley & Sons, Ltd.

Evaluation of long-term survival: use of diagnostics and robust estimators with Cox's proportional hazards model.

PubMed

Valsecchi, M G; Silvestri, D; Sasieni, P

1996-12-30

We consider methodological problems in evaluating long-term survival in clinical trials. In particular we examine the use of several methods that extend the basic Cox regression analysis. In the presence of a long term observation, the proportional hazard (PH) assumption may easily be violated and a few long term survivors may have a large effect on parameter estimates. We consider both model selection and robust estimation in a data set of 474 ovarian cancer patients enrolled in a clinical trial and followed for between 7 and 12 years after randomization. Two diagnostic plots for assessing goodness-of-fit are introduced. One shows the variation in time of parameter estimates and is an alternative to PH checking based on time-dependent covariates. The other takes advantage of the martingale residual process in time to represent the lack of fit with a metric of the type 'observed minus expected' number of events. Robust estimation is carried out by maximizing a weighted partial likelihood which downweights the contribution to estimation of influential observations. This type of complementary analysis of long-term results of clinical studies is useful in assessing the soundness of the conclusions on treatment effect. In the example analysed here, the difference in survival between treatments was mostly confined to those individuals who survived at least two years beyond randomization.

Keeping data continuous when analyzing the prognostic impact of a tumor marker: an example with cathepsin D in breast cancer.

PubMed

Bossard, N; Descotes, F; Bremond, A G; Bobin, Y; De Saint Hilaire, P; Golfier, F; Awada, A; Mathevet, P M; Berrerd, L; Barbier, Y; Estève, J

2003-11-01

The prognostic value of cathepsin D has been recently recognized, but as many quantitative tumor markers, its clinical use remains unclear partly because of methodological issues in defining cut-off values. Guidelines have been proposed for analyzing quantitative prognostic factors, underlining the need for keeping data continuous, instead of categorizing them. Flexible approaches, parametric and non-parametric, have been proposed in order to improve the knowledge of the functional form relating a continuous factor to the risk. We studied the prognostic value of cathepsin D in a retrospective hospital cohort of 771 patients with breast cancer, and focused our overall survival analysis, based on the Cox regression, on two flexible approaches: smoothing splines and fractional polynomials. We also determined a cut-off value from the maximum likelihood estimate of a threshold model. These different approaches complemented each other for (1) identifying the functional form relating cathepsin D to the risk, and obtaining a cut-off value and (2) optimizing the adjustment for complex covariate like age at diagnosis in the final multivariate Cox model. We found a significant increase in the death rate, reaching 70% with a doubling of the level of cathepsin D, after the threshold of 37.5 pmol mg(-1). The proper prognostic impact of this marker could be confirmed and a methodology providing appropriate ways to use markers in clinical practice was proposed.

Preventive dental management of osteonecrosis of the jaws related to zoledronic acid treatment.

PubMed

Coello-Suanzes, J A; Rollon-Ugalde, V; Castaño-Seiquer, A; Lledo-Villar, E; Herce-Lopez, J; Infante-Cossio, P; Rollon-Mayordomo, A

2018-02-07

To evaluate the effect of preventive dental management on reducing the incidence and delaying the onset of bisphosphonate-related osteonecrosis of the jaw (BRONJ) in patients treated with intravenous zoledronic acid (ZA). This single-center clinical study included 255 cancer patients monitored over a 6-year period. Patients received dental treatment prior (Group A) or after (Group B) the initiation of ZA therapy. Dental treatments performed, incidence proportion (IP) and incidence rate (IR) in both groups were analyzed using significance tests. BRONJ onset were estimated using the Kaplan-Meier estimator and log-rank test. Independent risk factors to develop BRONJ were evaluated using Cox regression analysis models. 37 patients suffered from BRONJ (IP=14.5%), 7.3% in group A and 36.5% in group B (p=0.000). The IR was 0.007 patients/month in group B and 0.004 in group A. BRONJ free survival at 3 years were 97% in group A and 66% in group B. Survival curves were significant (p=0.056) according to log-rank test. Multivariate Cox models showed that dental extractions (p=0.000) were significant. BRONJ occurred significantly in patients who underwent dental extractions after the initiation of ZA and did not accomplish a preventive dental program. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Association of Periodontitis and Subsequent Depression: A Nationwide Population-Based Study.

PubMed

Hsu, Chih-Chao; Hsu, Yi-Chao; Chen, Hsuan-Ju; Lin, Che-Chen; Chang, Kuang-Hsi; Lee, Chang-Yin; Chong, Lee-Won; Kao, Chia-Hung

2015-12-01

Periodontitis is a systemic and chronic inflammatory disease associated with multiple physical conditions. Distress and depression are other problems affecting the progression of periodontitis. However, the causal relationship between depression and periodontitis has not been adequately investigated. This aim of this study was to determine the association between periodontitis and the subsequent development of depression.We identified 12,708 patients with newly diagnosed periodontitis from 2000 to 2005 and 50,832 frequency-matched individuals without periodontitis. Both groups were followed until diagnosed with depression, withdrawal from the National Health Insurance program, or the end of 2011. The association between periodontitis and depressio was analyzed using Cox proportional hazard regression models.The incidence density rate of depression was higher in the periodontitis group than in the nonperiodontitis group, with an adjusted hazard ratio of 1.73 (95% confidence interval 1.58-1.89) when adjusting for sex, age, and comorbidity. Cox models revealed that periodontitis was an independent risk factor for depression in patients, except for comorbidities of diabetes mellitus (DM), alcohol abuse, and cancer.Periodontitis may increase the risk of subsequent depression and was suggested an independent risk factor regardless of sex, age, and most comorbidities. However, DM, alcohol abuse, and cancer may prevent the development of subsequent depression because of DM treatment, the paradoxical effect of alcohol, and emotional distress to cancer, respectively. Prospective studies on the relationship between periodontitis and depression are warranted.

Association of Periodontitis and Subsequent Depression

PubMed Central

Hsu, Chih-Chao; Hsu, Yi-Chao; Chen, Hsuan-Ju; Lin, Che-Chen; Chang, Kuang-Hsi; Lee, Chang-Yin; Chong, Lee-Won; Kao, Chia-Hung

2015-01-01

Abstract Periodontitis is a systemic and chronic inflammatory disease associated with multiple physical conditions. Distress and depression are other problems affecting the progression of periodontitis. However, the causal relationship between depression and periodontitis has not been adequately investigated. This aim of this study was to determine the association between periodontitis and the subsequent development of depression. We identified 12,708 patients with newly diagnosed periodontitis from 2000 to 2005 and 50,832 frequency-matched individuals without periodontitis. Both groups were followed until diagnosed with depression, withdrawal from the National Health Insurance program, or the end of 2011. The association between periodontitis and depressio was analyzed using Cox proportional hazard regression models. The incidence density rate of depression was higher in the periodontitis group than in the nonperiodontitis group, with an adjusted hazard ratio of 1.73 (95% confidence interval 1.58–1.89) when adjusting for sex, age, and comorbidity. Cox models revealed that periodontitis was an independent risk factor for depression in patients, except for comorbidities of diabetes mellitus (DM), alcohol abuse, and cancer. Periodontitis may increase the risk of subsequent depression and was suggested an independent risk factor regardless of sex, age, and most comorbidities. However, DM, alcohol abuse, and cancer may prevent the development of subsequent depression because of DM treatment, the paradoxical effect of alcohol, and emotional distress to cancer, respectively. Prospective studies on the relationship between periodontitis and depression are warranted. PMID:26705230

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.

Compensatory Hypertrophy Induced by Ventricular Cardiomyocyte Specific COX-2 Expression in Mice

PubMed Central

Streicher, John M.; Kamei, Kenichiro; Ishikawa, Tomo-o; Herschman, Harvey; Wang, Yibin

2010-01-01

Cyclooxygenase-2 (COX-2) is an important mediator of inflammation in stress and disease states. Recent attention has focused on the role of COX-2 in human heart failure and diseases, due to the finding that highly specific COX-2 inhibitors (i.e. Vioxx) increased the risk of myocardial infarction and stroke in chronic users. However, the specific impact of COX-2 expression in the intact heart remains to be determined. We report here the development of a transgenic mouse model, using a loxP-Cre approach, that displays robust COX-2 overexpression and subsequent prostaglandin synthesis specifically in ventricular myocytes. Histological, functional and molecular analyses showed that ventricular myocyte specific COX-2 overexpression led to cardiac hypertrophy and fetal gene marker activation, but with preserved cardiac function. Therefore, specific induction of COX-2 and prostaglandin in vivo is sufficient to induce compensated hypertrophy and molecular remodeling. PMID:20170663

COX-2 and Prostate Cancer Angiogenesis

DTIC Science & Technology

2001-03-01

the optimal dosing and timing of a COX-2 inhibitor (NS398) in an animal model of human prostate cancer, (2)and (3) the mechanisms underlying the...cancer tissues (14) and that a COX-2 inhibitor selectively induces apoptosis in a prostate cancer cell line (15). We also demonstrated that treatment of...human prostate tumor-bearing mice with a selective COX-2 inhibitor (NS-398) significantly reduces tumor size, microvessel density and levels of a

Targeting Estrogen-Induced COX-2 Activity in Lymphangioleiomyomatosis (LAM)

DTIC Science & Technology

2014-12-01

production was also increased in TSC2-deficient cells. In preclinical models, both Celecoxib and aspirin reduced tumor development. LAM patients had...increased by aspirin treatment, indicative of functional COX-2 expression in the LAM airway. In vitro, 15-epi-lipoxin-A4 reduced the proliferation of...inhibit COX-2 pharmacologically, we treated TSC2-deficient cells with aspirin or NS398, and found that both agents reduced COX-2 protein levels and

Plasma and serum L-selectin and clinical and subclinical the Multi-Ethnic Study of Atherosclerosis (MESA)cardiovascular disease

PubMed Central

BERARDI, CECILIA; DECKER, PAUL A.; KIRSCH, PHILLIP S.; DE ANDRADE, MARIZA; TSAI, MICHAEL Y.; PANKOW, JAMES S.; SALE, MICHELE M.; SICOTTE, HUGUES; TANG, WEIHONG; HANSON, NAOMI; POLAK, JOSEPH F.; BIELINSKI, SUZETTE J.

2014-01-01

L-selectin has been suggested to play a role in atherosclerosis. Previous studies on cardiovascular disease (CVD) and serum or plasma L-selectin are inconsistent. The association of serum L-selectin (sL-selectin) with carotid intima-media thickness, coronary artery calcium, ankle-brachial index (subclinical CVD) and incident CVD was assessed within 2403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Regression analysis and the Tobit model were used to study subclinical disease; Cox Proportional Hazards regression for incident CVD. Mean age was 63 ± 10, 47% were males; mean sL-selectin was significantly different across ethnicities. Within each race/ethnicity, sL-selectin was associated with age and sex; among Caucasians and African Americans, it was associated with smoking status and current alcohol use. sL-selectin levels did not predict subclinical or clinical CVD after correction for multiple comparisons. Conditional logistic regression models were used to study plasma L-selectin and CVD within 154 incident CVD cases, occurred in a median follow up of 8.5 years, and 306 age-, sex-, and ethnicity-matched controls. L-selectin levels in plasma were significantly lower than in serum and the overall concordance was low. Plasma levels were not associated with CVD. In conclusion, this large multi-ethnic population, soluble L-selectin levels did not predict clinical or subclinical CVD. PMID:24631064

A medicinal extract of Scutellaria baicalensis and Acacia catechu acts as a dual inhibitor of cyclooxygenase and 5-lipoxygenase to reduce inflammation.

PubMed

Burnett, B P; Jia, Q; Zhao, Y; Levy, R M

2007-09-01

A mixed extract containing two naturally occurring flavonoids, baicalin from Scutellaria baicalensis and catechin from Acacia catechu, was tested for cyclooxygenase (COX) and 5-lipoxygenase (5-LOX) inhibition via enzyme, cellular, and in vivo models. The 50% inhibitory concentration for inhibition of both ovine COX-1 and COX-2 peroxidase enzyme activities was 15 microg/mL, while the mixed extract showed a value for potato 5-LOX enzyme activity of 25 microg/mL. Prostaglandin E2 generation was inhibited by the mixed extract in human osteosarcoma cells expressing COX-2, while leukotriene production was inhibited in both human cell lines, immortalized THP-1 monocyte and HT-29 colorectal adenocarcinoma. In an arachidonic acid-induced mouse ear swelling model, the extract decreased edema in a dose-dependent manner. When arachidonic acid was injected directly into the intra-articular space of mouse ankle joints, the mixed extract abated the swelling and restored function in a rotary drum walking model. These results suggest that this natural, flavonoid mixture acts via "dual inhibition" of COX and LOX enzymes to reduce production of pro-inflammatory eicosanoids and attenuate edema in an in vivo model of inflammation.

Unilateral robotic hybrid mini-maze: a novel experimental approach.

PubMed

Moslemi, Mohammad; Rawashdeh, Badi; Meyer, Mark; Nguyen, Duy; Poston, Robert; Gharagozloo, Farid

2016-03-01

A complete Cox maze IV procedure is difficult to accomplish using current endoscopic and minimally invasive techniques. These techniques are hampered by inability to adequately dissect the posterior structures of the heart and place all necessary lesions. We present a novel approach, using robotic technology, that achieves placement of all the lesions of the complete maze procedure. In three cadaveric human models, the technical feasibility of using robotic instruments through the right chest to dissect the posterior structures of the heart and place all Cox maze lesions was performed. The entire posterior aspect of the heart was dissected in the cadaveric model facilitating successful placement of all Cox maze IV lesions with robotic assistance through minimally invasive incisions. The robotic Cox maze IV procedure through the novel right thoracic approach is feasible. This obviates the need for sternotomy and avoids the associated morbidity of the conventional Cox-maze procedure. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Outcomes of Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemoperfusion in Patients with High-Grade, High-Volume Disseminated Mucinous Appendiceal Neoplasms.

PubMed

Polanco, Patricio M; Ding, Ying; Knox, Jordan M; Ramalingam, Lekshmi; Jones, Heather; Hogg, Melissa E; Zureikat, Amer H; Holtzman, Matthew P; Pingpank, James; Ahrendt, Steven; Zeh, Herbert J; Bartlett, David L; Choudry, Haroon A

2016-02-01

High-grade (HG) mucinous appendiceal neoplasms (MAN) have a worse prognosis than low-grade histology. Our objective was to assess the safety and efficacy of cytoreductive surgery with hyperthermic intraperitoneal chemoperfusion (CRS/HIPEC) in patients with high-grade, high-volume (HG-HV) peritoneal metastases in whom the utility of this aggressive approach is controversial. Prospectively collected perioperative data were compared between patients with peritoneal metastases from HG-HV MAN, defined as simplified peritoneal cancer index (SPCI) ≥12, and those with high-grade, low-volume (HG-LV; SPCI <12) disease. Kaplan-Meier curves and multivariate Cox regression models identified prognostic factors affecting oncologic outcomes. Overall, 54 patients with HG-HV and 43 with HG-LV peritoneal metastases underwent CRS/HIPEC. The HG-HV group had longer operative time, increased blood loss/transfusion, and increased intensive care unit length of stay (p < 0.05). Incomplete macroscopic cytoreduction (CC-1/2/3) was higher in the HG-HV group compared with the HG-LV group (68.5 vs. 32.6 %; p = 0.005). Patients with HG-HV disease demonstrated worse survival than those with HG-LV disease (overall survival [OS] 17 vs. 42 m, p = 0.009; time to progression (TTP) 10 vs. 14 m, p = 0.024). However, when complete macroscopic resection (CC-0) was achieved, the OS and progression-free survival of patients with HG-HV disease were comparable with HG-LV disease (OS 56 vs. 52 m, p = 0.728; TTP 20 vs. 19 m, p = 0.393). In a multivariate Cox proportional hazard regression model, CC-0 resection was the only significant predictor of improved survival for patients with HG-HV disease. Although patients with HG-HV peritoneal metastases from MAN have worse prognosis compared with patients with HG-LV disease, their survival is comparable when complete macroscopic cytoreduction is achieved.

[Study on incidence of HIV infection among heroin addicts receiving methadone maintenance treatment in Dehong prefecture, Yunnan province].

PubMed

Duan, Song; Yang, Yue-cheng; Han, Jing; Yang, Shun-sheng; Yang, Ying-bo; Long, Yu-cun; Li, Guo-qiang; Yin, Jin-song; Xiang, Li-fen; Ye, Run-hua; Gao, Jie; Tang, Ren-hai; Pang, Lin; Rou, Ke-ming; Wu, Zun-you; He, Na

2011-12-01

To determine the incidence and risk factors of HIV infection among heroin addicts receiving methadone maintenance treatment (MMT) in Dehong prefecture, Yunnan province. All heroin addicts who were HIV negative at the initiation of MMT in June 2005 and through June 2011, in Dehong prefecture were included in the cohort analysis. HIV incidence was calculated and related risk factors determined by using Cox proportional hazard regression model. A total of 3154 MMT clinic attendants were qualified for this cohort study. By June 2011, 1023 (32.4%) of them had never received any follow-up HIV testing so were thus referred as loss to follow-up. The other 2131 (67.6%) members had received at least one follow-up HIV testing and were observed for a total of 4615.86 person-years. During the period, 22 new HIV infections or seroconverters were identified, making the overall HIV incidence as 0.48/100 person-years. The HIV incidence was higher among those who were unemployed, never married, self-reported being injecting drug users (IDUs) and HCV positive at entry into the MMT program. None of those who were always negative on follow-up-urine-testing of morphine was discovered as HIV newly infected during the follow-up period. Data from multiple regression analysis under Cox proportional hazard model indicated that after controlling for confounding variables, non-IDUs at the entry point for the MMT program, were less likely to be HIV newly-infected or seroconverted than IDUs (HR = 0.29, 95%CI: 0.11 - 0.76). MMT program in Dehong prefecture was demonstrated to be fairly effective in reducing HIV transmission through drug use. Those HIV negative attendants at the MMT clinic who were IDUs or keep using drugs during the treatment, were at higher risk of HIV seroconvertion. More efforts were needed to improve the follow-up and HIV testing programs for the MMT clinic attendants.

Brachytherapy Improves Survival in Stage III Endometrial Cancer With Cervical Involvement

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

Bingham, Brian; Orton, Andrew; Boothe, Dustin

Purpose: To evaluate the survival benefit of adding vaginal brachytherapy (BT) to pelvic external beam radiation therapy (EBRT) in women with stage III endometrial cancer. Methods and Materials: The National Cancer Data Base was used to identify patients with stage III endometrial cancer from 2004 to 2013. Only women who received adjuvant EBRT were analyzed. Women were grouped according to receipt of BT. Logistic regression modeling was used to identify predictors of receiving BT. Log–rank statistics were used to compare survival outcomes. Cox proportional hazards modeling was used to evaluate the effect of BT on survival. A propensity score–matched analysismore » was also conducted among women with cervical involvement. Results: We evaluated 12,988 patients with stage III endometrial carcinoma, 39% of whom received EBRT plus BT. Women who received BT were more likely to have endocervical or cervical stromal involvement (odds ratios 2.03 and 1.77; P<.01, respectively). For patients receiving EBRT alone, the 5-year survival was 66% versus 69% with the addition of BT at 5 years (P<.01). Brachytherapy remained significantly predictive of decreased risk of death (hazard ratio 0.86; P<.01) on multivariate Cox regression. The addition of BT to EBRT did not affect survival among women without cervical involvement (P=.84). For women with endocervical or cervical stromal invasion, the addition of BT significantly improved survival (log–rank P<.01). Receipt of EBRT plus BT was associated with improved survival in women with positive and negative surgical margins, and receiving chemotherapy did not alter the benefit of BT. Propensity score–matched analysis results confirmed the benefit of BT among women with cervical involvement (hazard ratio 0.80; P=.01). Conclusions: In this population of women with stage III endometrial cancer the addition of BT to EBRT was associated with an improvement in survival for women with endocervical or cervical stromal invasion.« less

A comparison of the effects of C2-cyclosporine and C0-tacrolimus on renal function and cardiovascular risk factors in kidney transplant recipients.

PubMed

Kim, S Joseph; Prasad, G V Ramesh; Huang, Michael; Nash, Michelle M; Famure, Olusegun; Park, Joseph; Thenganatt, Mary Ann; Chowdhury, Nizamuddin; Cole, Edward H; Fenton, Stanley S A; Cattran, Daniel C; Zaltzman, Jeffrey S; Cardella, Carl J

2006-10-15

There are few data directly comparing the effects of two-hour postingestion monitored cyclosporine (C2-CsA) vs. trough-monitored tacrolimus (C0-Tac) on renal function and cardiovascular risk factors. We studied 378 (202 C2-CsA vs. 176 C0-Tac) incident kidney transplant recipients in Toronto, Canada, from August 1, 2000 and December 31, 2003. Outcomes included changes in estimated glomerular filtration rate (eGFR at 1 and 6 months by modification of diet in renal disease four-variable equation), mean arterial pressure (MAP), total cholesterol (TC), and new-onset diabetes mellitus (NODM) at six months posttransplant. The independent effect of treatment/monitoring strategies on continuous outcomes and time-to-NODM was modeled using linear and Cox regression, respectively. Mean eGFR was 59.5 vs. 62.9 ml/min at one month and 50.6 vs. 61.2 ml/min at six months for C2-CsA vs. C0-Tac, respectively. Multiple linear regression revealed the slope of eGFR to be 0.93 ml/min/month lower in C2-CsA patients. This was equivalent to an adjusted average eGFR difference of 4.64 ml/min between months one and six posttransplant. There was no significant difference in average MAP and TC. In a stepwise multivariable Cox model and a propensity score analysis, there was no significant association between the type of treatment/monitoring strategy and time-to-NODM. There was a greater decline in eGFR for patients on C2-CsA (vs. C0-Tac) between one and six months posttransplant. However, MAP, TC, and the risk of NODM were comparable in both treatment/monitoring groups. The long-term impact of short-term reductions in eGFR as a function of the type of treatment/monitoring strategy requires further study.

Will Rogers revisited: prospective observational study of survival of 3592 patients with colorectal cancer according to number of nodes examined by pathologists

PubMed Central

George, S; Primrose, J; Talbot, R; Smith, J; Mullee, M; Bailey, D; du Boulay, C; Jordan, H

2006-01-01

To investigate the relationship between survival in colorectal cancer patients and the number of lymph nodes examined by a pathologist, previously attributed to stage migration, we used data from a cohort of 5174 colorectal cancer patients recruited between September 1991 and August 1994, and followed-up for 5 years. We selected cases with data present on all prognostic variables, and stratified them into three groups by number of nodes examined. We made a multivariate survival comparison using a Cox regression model. In all, there were 3592 cases with data present on all prognostic variables. Patients who had >10 nodes identified had a significant survival advantage over those who had 5–10 identified, who had in turn a similar advantage over those with 0–4 identified (P<0.001). This effect was present in the whole group and at all Dukes' stages, although statistically significant only in stages B (P=0.004) and C (P=0.019). The effect remained after adjustment in a Cox regression model in which the mean number of nodes taken out by each surgical firm did not predict survival. In a sub-group with data on lymphocytic infiltration into the primary tumour a survival advantage was noted in those with prominent rather than mild infiltration (P<0.001): the former also tended to have more nodes found (P=0.015). Stage migration alone cannot explain these results, as survival advantages are noted across the whole population independent of stage. Lymphocytic infiltration into the primary tumour is prognostically important, and is associated with the number of nodes found. Reactive enlargement of lymph nodes in the mesentery may make them easier to find, reflect immune response to the tumour, and thus indirectly impact upon survival. PMID:16969342

Combined effect of individual and neighbourhood socioeconomic status on mortality of rheumatoid arthritis patients under universal health care coverage system.

PubMed

Chen, Cheng-Hsin; Huang, Kuang-Yung; Wang, Jen-Yu; Huang, Hsien-Bin; Chou, Pesus; Lee, Ching-Chih

2015-02-01

The National Health Insurance program in Taiwan is a public insurance system for the entire population of Taiwan initiated since March 1995. However, the association of socioeconomic status (SES) and prognosis of rheumatoid arthritis (RA) patients under this program has not been identified. Using the National Health Insurance Research Database in Taiwan, we aimed to examine the combined effect of individual and neighbourhood SES on the mortality rates of RA patients under a universal health care coverage system. A study population included patients with RA from 2004 to 2008. The primary end point was the 5-year overall mortality rate. Individual SES was categorized into low, moderate and high levels based on the income-related insurance payment amount. Neighbourhood SES was defined by household income and neighbourhoods were grouped as an 'advantaged' area or a 'disadvantaged' area. The Cox proportional hazards regression model was used to compare outcomes between different SES categories. A two-sided P value < 0.05 was considered statistically significant. Medical data of 23900 RA patients from 2004 to 2008 were reviewed. Analysis of the combined effect of individual SES and neighbourhood SES revealed that 5-year mortality rates were worse among RA patients with a low individual SES compared to those with a high SES (P < 0.001). In the Cox proportional hazards regression model, RA patients with low individual SES in disadvantaged neighbourhoods incurred the highest risk of mortality (Hazard ratio = 1.64; 95% confidence interval, 1.26-2.13, P < 0.001). RA patients with a low SES have a higher overall mortality rate than those with a higher SES, even with a universal health care system. It is crucial that more public policy and health care efforts be put into alleviating the health disadvantages, besides providing treatment payment coverage. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

HMGB1 is an independent predictor of death and heart transplantation in heart failure.

PubMed

Volz, H C; Laohachewin, D; Schellberg, D; Wienbrandt, A R; Nelles, M; Zugck, C; Kaya, Z; Katus, H A; Andrassy, M

2012-06-01

High-Mobility-Group Box 1 (HMGB1) has been established as an important mediator of myocardial inflammation and associated with progression of heart failure (HF). The aim of this study was to analyze the prognostic value of systemic HMGB1 levels in HF patients with ischemic and non-ischemic cardiomyopathy. We conducted an analysis (median follow-up time 2.5 years) of HMGB1 plasma concentration in 154 patients with systolic HF and correlated the results with disease severity and prognosis. HMGB1 in HF patients with severe symptoms (NYHA III/IV; 5.35 ng/ml; interquartile range (IQR) = 3.48-8.42 ng/ml) was significantly elevated compared with that in patients with mild symptoms (NYHA I/II; 3.37 ng/ml, IQR = 2.31-5.22 ng/ml, p < 0.0001) and with controls (3.25 ng/ml, IQR = 3.04-3.67 ng/ml, p < 0.0001). HMGB1 levels correlated with other markers of heart failure indicating an association of HMGB1 with disease severity in HF. In a univariate cox regression model for the combined endpoint of death and heart transplantation, HMGB1 proved to be a predictor at cut-off values based on HMGB1 terciles of either 3.4 or 6.1 ng/ml (p = 0.001 and p < 0.0001, respectively). In a multivariate cox regression model, which included NT-proBNP, creatinine, age, NYHA class, white blood cell count, anemia, and age, HMGB1 remained an independent predictor of the combined endpoint (hazard ratio (HR) = 2.48, 95% confidence interval (CI) = 1.06-5.83, p = 0.037 and HR = 2.48, 95% CI = 1.31-4.71, p = 0.005, respectively). Our findings demonstrate that HMGB1 plasma concentration is elevated in HF and correlates with disease severity and that is an independent predictor of the combined endpoint death and heart transplantation in HF patients.

The effect of prior upper abdominal surgery on outcomes after liver transplantation for hepatocellular carcinoma: An analysis of the database of the organ procurement transplant network.

PubMed

Silva, Jack P; Berger, Nicholas G; Yin, Ziyan; Liu, Ying; Tsai, Susan; Christians, Kathleen K; Clarke, Callisia N; Mogal, Harveshp; Gamblin, T Clark

2018-05-01

Orthotopic liver transplantation (OLT) is the preferred treatment for hepatocellular carcinoma (HCC) in select patients. Many patients listed for OLT have a history of prior upper abdominal surgery (UAS). Repeat abdominal surgery increases operative complexity and may cause a greater incidence of complication. This study sought to compare outcomes after liver transplantation for patients with and without prior UAS. Adult HCC patients undergoing OLT were identified using the database from the Organ Procurement and Transplantation Network (1987-2015). Patients were separated by presence of prior UAS into 2 propensity-matched cohorts. Overall survival (OS) and graft survival (GS) were analyzed by log-rank test and graphed using Kaplan-Meier method. Recipient and donor demographic and clinical characteristics were also studied using Cox regression models. A total of 15,043 patients were identified, of whom 6,205 had prior UAS (41.2%). After 1:1 propensity score matching, cohorts (UAS versus no UAS) contained 4,669 patients. UAS patients experienced shorter GS (122 months vs 129 months; P < .001) and shorter OS (130 months vs 141 months; P < .001). Median duration of stay for both cohorts was 8 days. Multivariate Cox regression models revealed that prior UAS was associated with an increased hazard ratio (HR) for GS (HR 1.14; 95% confidence interval (CI) 1.06-1.22; P < .001) and OS (HR 1.14; 95% CI 1.06-1.23; P < .001). Prior UAS is an independent negative predictor of GS and OS after OLT for HCC. OLT performed in patients with UAS remains a well-tolerated and effective treatment for select HCC patients but may alter expected outcomes and influence follow-up protocols. Copyright © 2017 Elsevier Inc. All rights reserved.

Rapid risk household screening by neonatal arm circumference: results from a cohort study in rural Burkina Faso.

PubMed

Benzler, J; Sauerborn, R

1998-12-01

Neonatal arm circumference (NAC) and other attributes of the newborn and its household were analysed as potential predictors of child death in a cohort of 1367 newborn children representing the majority of births in a rural area of Burkina Faso from 1992 to 1994. During 3872 person years observed 264 children died, resulting in an average mortality rate of 6.8% per year. 90 mm was chosen as the best cut-off to differentiate low NAC associated with high mortality from normal NAC. The hazard ratio of children with low NAC (15.7%) compared to others was 1.7 (P < 0.001) in Cox regression. Kaplan-Meier curves of cumulative survival showed that this higher risk lasted throughout the first two years of life. Multivariate Cox regression comparing NAC with other variables known or suspected to influence child survival yielded a model including mother's death, twin birth, affiliation to a particular health centre, home delivery and birth during the rainy or harvest season as other significant risk factors beside NAC. Protective factors were mother's participation in antenatal care despite considerable distance to the health centre, medium household size (5-7 members) and household cash crop production. We propose a simple risk score for rapid household screening in rural Burkina Faso and comparable settings elsewhere for identifying households at risk of experiencing child death. As much of the other variables' contribution to the explanation of survival pattern is absorbed by NAC in more parsimonious models, even simpler screening strategies based on NAC make sense. In the study area risk households will be offered periodical home visits by the local nurse promoting immunization, treatment of illness and strengthening the mothers' competence to recognize and manage frequent health problems of their children as part of a 'Shared Care' concept.

Effect of hyperlipidemia on the incidence of cardio-cerebrovascular events in patients with type 2 diabetes.

PubMed

Fan, Dabei; Li, Li; Li, Zhizhen; Zhang, Ying; Ma, Xiaojun; Wu, Lina; Qin, Guijun

2018-05-08

This study was to explore the effect of hyperlipidemia on the incidence of cardio-cerebrovascular diseases in patients with type 2 diabetes. Three hundred ninety five patients with type 2 diabetes in our hospital from January 2012 to January 2016 were followed up with an average of 3.8 years. The incidence of cardio-cerebrovascular diseases between diabetes combined with hyperlipidemia group (195 patients) and diabetes group (200 patients) were made a comparison. Multivariable Cox's proportional hazards regression model was used to analyze the effect of hyperlipidemia on the incidence of cardio-cerebrovascular diseases in patients with type 2 diabetes. Diastolic blood pressure, systolic blood pressure, high-density lipoprotein, low-density lipoprotein, body mass index and hyper-sensitive C-reactive protein were higher in diabetes combined with hyperlipidemia group than in diabetes group (P < 0.05). At the end of the follow-up period, all-cause mortality, cardio-cerebrovascular diseases mortality, and the incidence of myocardial infarction, cerebral infarction, cerebral hemorrhage and total cardiovascular events were significantly higher in diabetes combined with hyperlipidemia group than in diabetes group (P < 0.05). The analysis results of multivariable Cox's proportional hazards regression model showed that the risks of myocardial infarction and total cardiovascular events in diabetes combined with hyperlipidemia group were respectively 1.54 times (95%CI 1.13-2.07) and 1.68 times (95%CI 1.23-2.24) higher than those in diabetes group. Population attributable risk percent of all-cause mortality and total cardiovascular events in patients with type 2 diabetes combined with hyperlipidemia was 9.6% and 26.8%, respectively. Hyperlipidemia may promote vascular endothelial injury, increasing the risk of cardio-cerebrovascular diseases in patients with type 2 diabetes. Medical staffs should pay attention to the control of blood lipids in patients with type 2 diabetes to delay the occurrence of cardio-cerebrovascular diseases.

Pretreatment oral hygiene habits and survival of head and neck squamous cell carcinoma (HNSCC) patients.

PubMed

Friemel, Juliane; Foraita, Ronja; Günther, Kathrin; Heibeck, Mathias; Günther, Frauke; Pflueger, Maren; Pohlabeln, Hermann; Behrens, Thomas; Bullerdiek, Jörn; Nimzyk, Rolf; Ahrens, Wolfgang

2016-03-11

The survival time of patients with head and neck squamous cell carcinoma (HNSCC) is related to health behavior, such as tobacco smoking and alcohol consumption. Poor oral health (OH), dental care (DC) and the frequent use of mouthwash have been shown to represent independent risk factors for head and neck cancerogenesis, but their impact on the survival of HNSCC patients has not been systematically investigated. Two hundred seventy-six incident HNSCC cases recruited for the ARCAGE study were followed through a period of 6-10 years. Interview-based information on wearing of dentures, gum bleeding, teeth brushing, use of floss and dentist visits were grouped into weighted composite scores, i.e. oral health (OH) and dental care (DH). Use of mouthwash was assessed as frequency per day. Also obtained were other types of health behavior, such as smoking, alcohol drinking and diet, appreciated as both confounding and study variables. Endpoints were progression-free survival, overall survival and tumor-specific survival. Prognostic values were estimated using Kaplan-Meier analysis and Cox proportional hazards regression models. A good dental care score, summarizing annual dental visits, daily teeth cleaning and use of floss was associated with longer overall survival time (p = .001). The results of the Cox regression models similarly suggested a higher risk of tumor progression and shortened overall survival in patients with poor dental care, but the results lost their statistical significance after other types of health behavior had been controlled for. Frequent use of mouthwash (≥ 2 times/day) significantly increased the risk of tumor-specific death (HR = 2.26; CI = 1.19-4.32). Alcohol consumption and tobacco smoking were dose-dependently associated with tumor progression and shorter overall survival. Frequent mouthwash use of ≥ 2 times/day seems to elevate the risk of tumor-specific death in HNSCC patients. Good dental care scores are associated with longer overall survival.

Multivariate analysis of prognostic factors in male breast cancer in Serbia.

PubMed

Sipetic-Grujicic, Sandra Branko; Murtezani, Zafir Hajdar; Neskovic-Konstatinovic, Zora Borivoje; Marinkovic, Jelena Milutin; Kovcin, Vladimir Nikola; Andric, Zoran Gojko; Kostic, Sanja Vladeta; Ratkov, Isidora Stojan; Maksimovic, Jadranka Milutin

2014-01-01

The aim of this study was to analyze the demographic and clinical characteristics of male breast cancer patients in Serbia, and furthermore to determine overall survival and predictive factors for prognosis. In the period of 1996-2006 histopathological diagnosis of breast cancer was made in 84 males at the Institute for Oncology and Radiology of Serbia. For statistical analyses the Kaplan-Meier method, long-rank test and Cox proportional hazards regression model were used. The mean age at diagnosis with breast cancer was 64.3±10.5 years with a range from 35-84 years. Nearly 80% of the tumors showed ductal histology. About 44% had early tumor stages (I and II) whereas 46.4% and 9.5% of the male exhibited stages III and IV, respectively. Only 7.1% of male patients were grade one. One-fifth of all patients had tumors measuring ≤2 cm, and 14.3% larger than 5 cm. Lymph node metastasis was recorded in 40.4% patients and 47% relapse. Estrogen and progesterone receptor expression was positive in 66.7% and 58.3%, respectively. Among 14.3% of individuals tumor was HER2 positive. About two-thirds of all male patients had radical mastectomy (66.7%). Adjuvant hormonal (tamoxifene), systematic chemotherapy (CMF or FAC) and adjuvant radiotherapy were given to 59.5%, 35.7% and 29.8% patients respectively. Overall survival rates at five and ten years for male breast cancer were 55.0% and 43.9%, respectively. According to the multivariate Cox regression predictive model, a lower initial disease stage, a lower tumor grade, application of adjuvant hormone therapy and no relapse occurrence were significant independent predictors for good overall survival. Results of the treatment would be better if disease is discovered earlier and therefore health education and screening are an imperative in solving this problem.

Does adding antibiotics to cement reduce the need for early revision in total knee arthroplasty?

PubMed

Bohm, Eric; Zhu, Naisu; Gu, Jing; de Guia, Nicole; Linton, Cassandra; Anderson, Tammy; Paton, David; Dunbar, Michael

2014-01-01

There is considerable debate about whether antibiotic-loaded bone cement should be used for fixation of TKAs. While antibiotics offer the theoretical benefit of lowering early revision due to infection, they may weaken the cement and thus increase the likelihood of aseptic loosening, perhaps resulting in a higher revision rate. We (1) compared the frequency of early knee revision arthroplasty in patients treated with antibiotic-loaded or non-antibiotic-loaded cement for initial fixation, (2) determined effects of age, sex, comorbidities, and surgeons' antibiotic-loaded cement usage patterns on revision rate, and (3) compared causes of revision (aseptic or septic) between groups. Our study sample was taken from the Canadian Joint Replacement Registry and Canada's Hospital Morbidity Database and included cemented TKAs performed between April 1, 2003, and March 31, 2008, including 20,016 TKAs inserted with non-antibiotic-loaded cement and 16,665 inserted with antibiotic-loaded cement. Chi-square test was used to compare the frequency of early revisions between groups. Cox regression modeling was used to determine whether revision rate would change by age, sex, comorbidities, or use of antibiotic-loaded cement. Similar Cox regression modeling was used to compare cause of revision between groups. Two-year revision rates were similar between the groups treated with non-antibiotic-loaded cement and antibiotic-loaded cement (1.40% versus 1.51%, p = 0.41). When controlling for age, sex, comorbidities, diabetes, and surgeons' antibiotic-loaded cement usage patterns, the revision risk likewise was similar between groups. Revision rates for infection were similar between groups; however, there were more revisions for aseptic loosening in the group treated with non-antibiotic-loaded cement (p = 0.02). The use of antibiotic-loaded cement in TKAs performed for osteoarthritis has no clinically significant effect on reducing revision within 2 years in patients who received perioperative antibiotics. Longer followup and confirmation of these findings with other national registries are warranted.

Differences in the rate of carbapenem-resistant Enterobacteriaceae colonisation or Clostridium difficile infection following frontline treatment with tigecycline vs. meropenem for intra-abdominal infections.

PubMed

Bartoletti, Michele; Tedeschi, Sara; Pascale, Renato; Raumer, Luigi; Maraolo, Alberto Enrico; Palmiero, Giulia; Tumietto, Fabio; Cristini, Francesco; Ambretti, Simone; Giannella, Maddalena; Lewis, Russell Edward; Viale, Pierluigi

2018-03-01

We hypothesised that treatment with a tigecycline-based antimicrobial regimen for intra-abdominal infection (IAI) could be associated with lower rates of subsequent carbapenem-resistant Enterobacteriaceae (CRE) colonisation or Clostridium difficile infection (CDI) compared with a meropenem-based regimen. We performed a retrospective, single-centre, matched (1:1) cohort analysis of all patients who received at least 5 days of empirical or targeted tigecycline (TIG)- or meropenem (MER)-based treatment regimens for IAI over a 50-month period. Patients with previous CRE colonisation and CDI were excluded. Risk factors for CRE and CDI were assessed with a Cox regression model that included treatment duration as a time-dependent variable. Thirty-day mortality was assessed with Kaplan-Meier curves. We identified 168 TIG-treated and 168 MER-treated patients. The cumulative incidence rate ratio of CDI was 10-fold lower in TIG-treated vs. MER-treated patients (incidence rate ratio [IRR] 0.10/1000 patient-days, 95%CI 0.002-0.72, P = 0.007), but similar incidence rates were found for CRE colonisation (IRR 1.39/1000 patient-days, 95%CI 0.68-2.78, P = 0.36). In a multivariate Cox regression model, the receipt of a TIG- vs. MER-based regimen was associated with significantly lower rates of CDI (HR 0.07, 95%CI 0.03-0.71, P = 0.02), but not CRE (HR 1.12, 95% CI 0.45-2.83, P = 0.80). All-cause 30-day mortality was similar in the two groups (P = 0.46). TIG-based regimens for IAI were associated with a 10-fold lower incidence of CDI compared with MER-based regimens, but there was no difference in the incidence of CRE colonisation. Copyright © 2018 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

In vitro enantioselective pharmacodynamics of Carprofen and Flunixin-meglumine in feedlot cattle.

PubMed

Miciletta, M; Cuniberti, B; Barbero, R; Re, G

2014-02-01

The activity of the anti-inflammatory agents Flunixin-meglumine (FLU), RS (±) Carprofen (CPF) and S (+) CPF on bovine cyclooxygenases (COXs) has been characterized in feedlot calves using an in vitro whole blood model. The drugs showed equivalent efficacy in their inhibitory activity on COXs, and the rank order of potency for both COX-1 and COX-2 inhibition was FLU > S (+) CPF > RS (±) CPF. Our results indicated that FLU is a nonselective inhibitor of bovine COXs, whereas RS (±) CPF and S (+) CPF exhibited different degrees of preferential inhibition of COX-2 isoenzyme. The rank order of IC50 COX-1: IC50 COX-2 potency ratios was in fact S (+) CPF (51.882) > RS (±) CPF (13.964) > FLU (0.606), and the calculated percentage inhibition of COX-1 corresponding to COX-2 inhibition values comprised between 80% and 95% was comprised between 57.697 and 79.865 for FLU, 33.373 and 51.319 for RS (±) CPF, and 0.230 and 4.622 for S (+) CPF, respectively. These findings are discussed in relation to the prediction of the clinical relevance of COX inhibition by the test drugs in cattle. © 2013 John Wiley & Sons Ltd.

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.

Inverse odds ratio-weighted estimation for causal mediation analysis.

PubMed

Tchetgen Tchetgen, Eric J

2013-11-20

An important scientific goal of studies in the health and social sciences is increasingly to determine to what extent the total effect of a point exposure is mediated by an intermediate variable on the causal pathway between the exposure and the outcome. A causal framework has recently been proposed for mediation analysis, which gives rise to new definitions, formal identification results and novel estimators of direct and indirect effects. In the present paper, the author describes a new inverse odds ratio-weighted approach to estimate so-called natural direct and indirect effects. The approach, which uses as a weight the inverse of an estimate of the odds ratio function relating the exposure and the mediator, is universal in that it can be used to decompose total effects in a number of regression models commonly used in practice. Specifically, the approach may be used for effect decomposition in generalized linear models with a nonlinear link function, and in a number of other commonly used models such as the Cox proportional hazards regression for a survival outcome. The approach is simple and can be implemented in standard software provided a weight can be specified for each observation. An additional advantage of the method is that it easily incorporates multiple mediators of a categorical, discrete or continuous nature. Copyright © 2013 John Wiley & Sons, Ltd.

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.

Use of Diuretics is not associated with mortality in patients admitted to the emergency department: results from a cross-sectional study.

PubMed

Haider, Dominik G; Lindner, Gregor; Wolzt, Michael; Leichtle, Alexander Benedikt; Fiedler, Georg-Martin; Sauter, Thomas C; Fuhrmann, Valentin; Exadaktylos, Aristomenis K

2016-02-01

Patients with diuretic therapy are at risk for drug-induced adverse reactions. It is unknown if presence of diuretic therapy at hospital emergency room admission is associated with mortality. In this cross sectional analysis, all emergency room patients 2010 and 2011 at the Inselspital Bern, Switzerland were included. A multivariable logistic regression model was performed to assess the association between pre-existing diuretic medication and 28 day mortality. Twenty-two thousand two hundred thirty-nine subjects were included in the analysis. A total of 8.5%, 2.5%, and 0.4% of patients used one, two, or three or more diuretics. In univariate analysis spironolactone, torasemide and chlortalidone use were associated with 28 day mortality (all p < 0.05). In a multivariate cox regression model no association with mortality was detectable (p > 0.05). No difference existed between patients with or without diuretic therapy (P > 0.05). Age and creatinine were independent risk factors for mortaliy (both p < 0.05). Use of diuretics is not associated with mortality in an unselected cohort of patients presenting in an emergency room.

Covariate Measurement Error Correction Methods in Mediation Analysis with Failure Time Data

PubMed Central

Zhao, Shanshan

2014-01-01

Summary Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This paper focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error and error associated with temporal variation. The underlying model with the ‘true’ mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling design. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. PMID:25139469

Covariate measurement error correction methods in mediation analysis with failure time data.

PubMed

Zhao, Shanshan; Prentice, Ross L

2014-12-01

Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This article focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error, and error associated with temporal variation. The underlying model with the "true" mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling designs. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. © 2014, The International Biometric Society.

Bone sialoprotein is predictive of bone metastases in resectable non-small-cell lung cancer: a retrospective case-control study.

PubMed

Papotti, Mauro; Kalebic, Thea; Volante, Marco; Chiusa, Luigi; Bacillo, Elisa; Cappia, Susanna; Lausi, Paolo; Novello, Silvia; Borasio, Piero; Scagliotti, Giorgio V

2006-10-20

Bone metastases (BM) in non-small-cell lung cancer (NSCLC) may be detected at diagnosis or during the course of the disease, and are associated with a worse prognosis. Currently, there are no predictive or diagnostic markers to identify high-risk patients for metastatic bone dissemination. Thirty patients with resected NSCLC who subsequently developed BM were matched for clinicopathologic parameters to 30 control patients with resected NSCLC without any metastases and 26 patients with resected NSCLC and non-BM lesions. Primary tumors were investigated by immunohistochemistry for 10 markers involved in bone resorption or development of metastases. Differences among groups were estimated by chi2 test, whereas the prognostic impact of clinicopathologic parameters and marker expression was evaluated by univariate (Wilcoxon and Mantel-Cox tests) and multivariate (Cox proportional hazards regression model) analyses. The presence of bone sialoprotein (BSP) was strongly associated with bone dissemination (P < .001) and, independently, with worse outcome (P = .02, Mantel-Cox test), as defined by overall survival. To evaluate BSP protein expression in nonselected NSCLC, a series of 120 consecutive resected lung carcinomas was added to the study, and BSP prevalence reached 40%. No other markers showed a statistically significant difference among the three groups or demonstrated a prognostic impact, in terms of both overall survival and time interval to metastases. BSP protein expression in the primary resected NSCLC is strongly associated with BM progression and could be useful in identifying high-risk patients who could benefit from novel modalities of surveillance and preventive treatment.

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

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.

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.

Locoregional Control of Non-Small Cell Lung Cancer in Relation to Automated Early Assessment of Tumor Regression on Cone Beam Computed Tomography

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

Brink, Carsten, E-mail: carsten.brink@rsyd.dk; Laboratory of Radiation Physics, Odense University Hospital; Bernchou, Uffe

2014-07-15

Purpose: Large interindividual variations in volume regression of non-small cell lung cancer (NSCLC) are observable on standard cone beam computed tomography (CBCT) during fractionated radiation therapy. Here, a method for automated assessment of tumor volume regression is presented and its potential use in response adapted personalized radiation therapy is evaluated empirically. Methods and Materials: Automated deformable registration with calculation of the Jacobian determinant was applied to serial CBCT scans in a series of 99 patients with NSCLC. Tumor volume at the end of treatment was estimated on the basis of the first one third and two thirds of the scans.more » The concordance between estimated and actual relative volume at the end of radiation therapy was quantified by Pearson's correlation coefficient. On the basis of the estimated relative volume, the patients were stratified into 2 groups having volume regressions below or above the population median value. Kaplan-Meier plots of locoregional disease-free rate and overall survival in the 2 groups were used to evaluate the predictive value of tumor regression during treatment. Cox proportional hazards model was used to adjust for other clinical characteristics. Results: Automatic measurement of the tumor regression from standard CBCT images was feasible. Pearson's correlation coefficient between manual and automatic measurement was 0.86 in a sample of 9 patients. Most patients experienced tumor volume regression, and this could be quantified early into the treatment course. Interestingly, patients with pronounced volume regression had worse locoregional tumor control and overall survival. This was significant on patient with non-adenocarcinoma histology. Conclusions: Evaluation of routinely acquired CBCT images during radiation therapy provides biological information on the specific tumor. This could potentially form the basis for personalized response adaptive therapy.« less

Chemoprevention with special reference to inherited colorectal cancer.

PubMed

Lynch, Patrick M

2008-01-01

Familial Adenomatous Polyposis (FAP) is a model for the adenoma-carcinoma sequence in several respects. One important area in which FAP serves as a model is chemoprevention. Early prevention trials mainly utilized micronutrients and were largely unsuccessful in preventing or causing regression of adenomas. A new era was ushered in by the recognition that antiarthritic doses of a nonsteroidal anti-inflammatory agent (NSAID), sulindac, could actually induce regression of colorectal adenomas in patients with FAP. Follow-up studies showed positive but variable long-term efficacy for colorectal adenomas, but sulindac appears to lack significant benefit in regressing duodenal adenomas or preventing initial occurrence of adenomas in APC mutation carriers. Due to the well-known side effects of traditional NSAIDs, selective COX-2 inhibitors have been studied rather extensively. Celecoxib has shown benefit in regressing colorectal adenomas and appears to have some duodenal activity as well. Rofecoxib, in smaller trials, showed efficacy as well. However, the entire field of NSAID research in chemoprevention is undergoing reexamination in light of recent demonstration of cardiovascular toxicity in nonfamilial or sporadic adenoma prevention trials. Whether NSAIDs will have a significant future in FAP chemoprevention will depend on a sober assessment of risks and benefits. These same issues will likely foster a more intensive search for new agents. FAP will undoubtedly continue to have a lead role in the testing of new agents, both in the interest of FAP management as such, and in anticipation of trials in nonfamilial adenomas, a problem with even greater societal impact. The historical development of chemoprevention in FAP will be presented, with an emphasis on issues of trial design.

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.

Bayesian multivariate hierarchical transformation models for ROC analysis.

PubMed

O'Malley, A James; Zou, Kelly H

2006-02-15

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayesian multivariate hierarchical transformation models for ROC analysis

PubMed Central

O'Malley, A. James; Zou, Kelly H.

2006-01-01

SUMMARY A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box–Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial. PMID:16217836

Testing goodness of fit in regression: a general approach for specified alternatives.

PubMed

Solari, Aldo; le Cessie, Saskia; Goeman, Jelle J

2012-12-10

When fitting generalized linear models or the Cox proportional hazards model, it is important to have tools to test for lack of fit. Because lack of fit comes in all shapes and sizes, distinguishing among different types of lack of fit is of practical importance. We argue that an adequate diagnosis of lack of fit requires a specified alternative model. Such specification identifies the type of lack of fit the test is directed against so that if we reject the null hypothesis, we know the direction of the departure from the model. The goodness-of-fit approach of this paper allows to treat different types of lack of fit within a unified general framework and to consider many existing tests as special cases. Connections with penalized likelihood and random effects are discussed, and the application of the proposed approach is illustrated with medical examples. Tailored functions for goodness-of-fit testing have been implemented in the R package global test. Copyright © 2012 John Wiley & Sons, Ltd.

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.

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.

Cancer Survival Estimates Due to Non-Uniform Loss to Follow-Up and Non-Proportional Hazards

PubMed

K M, Jagathnath Krishna; Mathew, Aleyamma; Sara George, Preethi

2017-06-25

Background: Cancer survival depends on loss to follow-up (LFU) and non-proportional hazards (non-PH). If LFU is high, survival will be over-estimated. If hazard is non-PH, rank tests will provide biased inference and Cox-model will provide biased hazard-ratio. We assessed the bias due to LFU and non-PH factor in cancer survival and provided alternate methods for unbiased inference and hazard-ratio. Materials and Methods: Kaplan-Meier survival were plotted using a realistic breast cancer (BC) data-set, with >40%, 5-year LFU and compared it using another BC data-set with <15%, 5-year LFU to assess the bias in survival due to high LFU. Age at diagnosis of the latter data set was used to illustrate the bias due to a non-PH factor. Log-rank test was employed to assess the bias in p-value and Cox-model was used to assess the bias in hazard-ratio for the non-PH factor. Schoenfeld statistic was used to test the non-PH of age. For the non-PH factor, we employed Renyi statistic for inference and time dependent Cox-model for hazard-ratio. Results: Five-year BC survival was 69% (SE: 1.1%) vs. 90% (SE: 0.7%) for data with low vs. high LFU respectively. Age (<45, 46-54 & >54 years) was a non-PH factor (p-value: 0.036). However, survival by age was significant (log-rank p-value: 0.026), but not significant using Renyi statistic (p=0.067). Hazard ratio (HR) for age using Cox-model was 1.012 (95%CI: 1.004 -1.019) and the same using time-dependent Cox-model was in the other direction (HR: 0.997; 95% CI: 0.997- 0.998). Conclusion: Over-estimated survival was observed for cancer with high LFU. Log-rank statistic and Cox-model provided biased results for non-PH factor. For data with non-PH factors, Renyi statistic and time dependent Cox-model can be used as alternate methods to obtain unbiased inference and estimates. Creative Commons Attribution License

Cell-type-specific roles for COX-2 in UVB-induced skin cancer

PubMed Central

Herschman, Harvey

2014-01-01

In human tumors, and in mouse models, cyclooxygenase-2 (COX-2) levels are frequently correlated with tumor development/burden. In addition to intrinsic tumor cell expression, COX-2 is often present in fibroblasts, myofibroblasts and endothelial cells of the tumor microenvironment, and in infiltrating immune cells. Intrinsic cancer cell COX-2 expression is postulated as only one of many sources for prostanoids required for tumor promotion/progression. Although both COX-2 inhibition and global Cox-2 gene deletion ameliorate ultraviolet B (UVB)-induced SKH-1 mouse skin tumorigenesis, neither manipulation can elucidate the cell type(s) in which COX-2 expression is required for tumorigenesis; both eliminate COX-2 activity in all cells. To address this question, we created Cox-2 flox/flox mice, in which the Cox-2 gene can be eliminated in a cell-type-specific fashion by targeted Cre recombinase expression. Cox-2 deletion in skin epithelial cells of SKH-1 Cox-2 flox/flox;K14Cre + mice resulted, following UVB irradiation, in reduced skin hyperplasia and increased apoptosis. Targeted epithelial cell Cox-2 deletion also resulted in reduced tumor incidence, frequency, size and proliferation rate, altered tumor cell differentiation and reduced tumor vascularization. Moreover, Cox-2 flox/flox;K14Cre + papillomas did not progress to squamous cell carcinomas. In contrast, Cox-2 deletion in SKH-1 Cox-2 flox/flox; LysMCre + myeloid cells had no effect on UVB tumor induction. We conclude that (i) intrinsic epithelial COX-2 activity plays a major role in UVB-induced skin cancer, (ii) macrophage/myeloid COX-2 plays no role in UVB-induced skin cancer and (iii) either there may be another COX-2-dependent prostanoid source(s) that drives UVB skin tumor induction or there may exist a COX-2-independent pathway(s) to UVB-induced skin cancer. PMID:24469308

Cell-type-specific roles for COX-2 in UVB-induced skin cancer.

PubMed

Jiao, Jing; Mikulec, Carol; Ishikawa, Tomo-o; Magyar, Clara; Dumlao, Darren S; Dennis, Edward A; Fischer, Susan M; Herschman, Harvey

2014-06-01

In human tumors, and in mouse models, cyclooxygenase-2 (COX-2) levels are frequently correlated with tumor development/burden. In addition to intrinsic tumor cell expression, COX-2 is often present in fibroblasts, myofibroblasts and endothelial cells of the tumor microenvironment, and in infiltrating immune cells. Intrinsic cancer cell COX-2 expression is postulated as only one of many sources for prostanoids required for tumor promotion/progression. Although both COX-2 inhibition and global Cox-2 gene deletion ameliorate ultraviolet B (UVB)-induced SKH-1 mouse skin tumorigenesis, neither manipulation can elucidate the cell type(s) in which COX-2 expression is required for tumorigenesis; both eliminate COX-2 activity in all cells. To address this question, we created Cox-2(flox/flox) mice, in which the Cox-2 gene can be eliminated in a cell-type-specific fashion by targeted Cre recombinase expression. Cox-2 deletion in skin epithelial cells of SKH-1 Cox-2(flox/flox);K14Cre(+) mice resulted, following UVB irradiation, in reduced skin hyperplasia and increased apoptosis. Targeted epithelial cell Cox-2 deletion also resulted in reduced tumor incidence, frequency, size and proliferation rate, altered tumor cell differentiation and reduced tumor vascularization. Moreover, Cox-2(flox/flox);K14Cre(+) papillomas did not progress to squamous cell carcinomas. In contrast, Cox-2 deletion in SKH-1 Cox-2(flox/flox); LysMCre(+) myeloid cells had no effect on UVB tumor induction. We conclude that (i) intrinsic epithelial COX-2 activity plays a major role in UVB-induced skin cancer, (ii) macrophage/myeloid COX-2 plays no role in UVB-induced skin cancer and (iii) either there may be another COX-2-dependent prostanoid source(s) that drives UVB skin tumor induction or there may exist a COX-2-independent pathway(s) to UVB-induced skin cancer. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Rofecoxib modulates multiple gene expression pathways in a clinical model of acute inflammatory pain

PubMed Central

Wang, Xiao-Min; Wu, Tian-Xia; Hamza, May; Ramsay, Edward S.; Wahl, Sharon M.; Dionne, Raymond A.

2007-01-01

New insights into the biological properties of cyclooxygenase-2 (COX-2) and its response pathway challenge the hypothesis that COX-2 is simply pro-inflammatory and inhibition of COX-2 solely prevents the development of inflammation and ameliorates inflammatory pain. The present study performed a comprehensive analysis of gene/protein expression induced by a selective inhibitor of COX-2, rofecoxib, compared with a non-selective COX inhibitor, ibuprofen, and placebo in a clinical model of acute inflammatory pain (the surgical extraction of impacted third molars) using microarray analysis followed by quantitative RT-PCR verification and Western blotting. Inhibition of COX-2 modulated gene expression related to inflammation and pain, the arachidonic acid pathway, apoptosis/angiogenesis, cell adhesion and signal transduction. Compared to placebo, rofecoxib treatment increased the gene expression of ANXA3 (annexin 3), SOD2 (superoxide dismutase 2), SOCS3 (suppressor of cytokine signaling 3) and IL1RN (IL1 receptor antagonist) which are associated with inhibition of phospholipase A2 and suppression of cytokine signaling cascades, respectively. Both rofecoxib and ibuprofen treatment increased the gene expression of the pro-inflammatory mediators, IL6 and CCL2 (chemokine C-C motif ligand 2), following tissue injury compared to the placebo treatment. These results indicate a complex role for COX-2 in the inflammatory cascade in addition to the well-characterized COX-dependent pathway, as multiple pathways are also involved in rofecoxib-induced anti-inflammatory and analgesic effects at the gene expression level. These findings may also suggest an alternative hypothesis for the adverse effects attributed to selective inhibition of COX-2. PMID:17070997

Prevention of posterior capsular opacification through cyclooxygenase-2 inhibition

PubMed Central

Barden, Curtis A; Lu, Ping; Kusewitt, Donna F.; Colitz, Carmen M. H.

2007-01-01

Purpose To determine if cyclooxygenase-2 (COX-2) is upregulated when lens epithelial cells (LEC) in clinical samples of cataracts and posterior capsule opacification (PCO) undergo epithelial-mesenchymal transition (EMT)-like changes. We also wanted to learn if inhibition of the enzymatic activity of COX-2 could prevent PCO formation. Methods To ensure that EMT-like changes were occurring in LEC, real-time RT-PCR was used to examine expression of EMT markers. Clinical samples of canine cataracts and PCO were examined for COX-2 expression using immunohistochemistry, western blot analysis, and real-time RT-PCR. The COX-2 inhibitors, rofecoxib and celecoxib, were used in an ex vivo model of PCO formation, and the effects on cellular migration, proliferation, and apoptosis were analyzed using immunohistochemistry and western blots. Prostaglandin E2 (PGE2) expression was examined with ELISA. Results Markers of EMT, such as lumican, Snail, Slug, and COX-2 were expressed in LEC. In clinical samples of cataracts and PCO, there was overexpression of COX-2 protein and mRNA. Both rofecoxib and celecoxib were effective at inhibiting PCO formation in our ex vivo model. Prevention of PCO with the COX-2 inhibitors appeared to work through decreased migration and proliferation, and increased apoptosis. Neither of the drugs had a toxic effect on confluent LEC and appeared to inhibit PCO through their pharmacologic action. Synthesis of PGE2 was inhibiting in the capsules treated with the COX-2 inhibiting drugs. Conclusions Extracapsular phacoemulsification cataract surgery is the most common surgical procedure performed in human and veterinary ophthalmology. The most frequent postoperative complication is PCO. The LEC that remain adhered to the lens capsule undergo EMT-like changes, proliferate, and migrate across the posterior lens capsule causing opacities. We have shown that COX-2, a protein associated with EMT, is upregulated in canine cataracts and PCO. Inhibiting the enzymatic activity effectively prevented EMT of LEC in our ex vivo model of PCO through pharmacologic action, and not acute toxicity. These findings indicate that using COX-2 inhibitors in vivo may be an effective technique in preventing PCO. PMID:17563718

On comparison of net survival curves.

PubMed

Pavlič, Klemen; Perme, Maja Pohar

2017-05-02

Relative survival analysis is a subfield of survival analysis where competing risks data are observed, but the causes of death are unknown. A first step in the analysis of such data is usually the estimation of a net survival curve, possibly followed by regression modelling. Recently, a log-rank type test for comparison of net survival curves has been introduced and the goal of this paper is to explore its properties and put this methodological advance into the context of the field. We build on the association between the log-rank test and the univariate or stratified Cox model and show the analogy in the relative survival setting. We study the properties of the methods using both the theoretical arguments as well as simulations. We provide an R function to enable practical usage of the log-rank type test. Both the log-rank type test and its model alternatives perform satisfactory under the null, even if the correlation between their p-values is rather low, implying that both approaches cannot be used simultaneously. The stratified version has a higher power in case of non-homogeneous hazards, but also carries a different interpretation. The log-rank type test and its stratified version can be interpreted in the same way as the results of an analogous semi-parametric additive regression model despite the fact that no direct theoretical link can be established between the test statistics.

A Box-Cox normal model for response times.

PubMed

Klein Entink, R H; van der Linden, W J; Fox, J-P

2009-11-01

The log-transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test where the lognormal model violated the normality assumption, the possibilities of the broader class of Box-Cox transformations for response time modelling are investigated. After an introduction and an outline of a broader framework for analysing responses and response times simultaneously, the performance of a Box-Cox normal model for describing response times is investigated using simulation studies and a real data example. A transformation-invariant implementation of the deviance information criterium (DIC) is developed that allows for comparing model fit between models with different transformation parameters. Showing an enhanced description of the shape of the response time distributions, its application in an educational measurement context is discussed at length.

Percentage of Positive Biopsy Cores: A Better Risk Stratification Model for Prostate Cancer?

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

Huang Jiayi; Vicini, Frank A.; Williams, Scott G.

2012-07-15

Purpose: To assess the prognostic value of the percentage of positive biopsy cores (PPC) and perineural invasion in predicting the clinical outcomes after radiotherapy (RT) for prostate cancer and to explore the possibilities to improve on existing risk-stratification models. Methods and Materials: Between 1993 and 2004, 1,056 patients with clinical Stage T1c-T3N0M0 prostate cancer, who had four or more biopsy cores sampled and complete biopsy core data available, were treated with external beam RT, with or without a high-dose-rate brachytherapy boost at William Beaumont Hospital. The median follow-up was 7.6 years. Multivariate Cox regression analysis was performed with PPC, Gleasonmore » score, pretreatment prostate-specific antigen, T stage, PNI, radiation dose, androgen deprivation, age, prostate-specific antigen frequency, and follow-up duration. A new risk stratification (PPC classification) was empirically devised to incorporate PPC and replace the T stage. Results: On multivariate Cox regression analysis, the PPC was an independent predictor of distant metastasis, cause-specific survival, and overall survival (all p < .05). A PPC >50% was associated with significantly greater distant metastasis (hazard ratio, 4.01; 95% confidence interval, 1.86-8.61), and its independent predictive value remained significant with or without androgen deprivation therapy (all p < .05). In contrast, PNI and T stage were only predictive for locoregional recurrence. Combining the PPC ({<=}50% vs. >50%) with National Comprehensive Cancer Network risk stratification demonstrated added prognostic value of distant metastasis for the intermediate-risk (hazard ratio, 5.44; 95% confidence interval, 1.78-16.6) and high-risk (hazard ratio, 4.39; 95% confidence interval, 1.70-11.3) groups, regardless of the use of androgen deprivation and high-dose RT (all p < .05). The proposed PPC classification appears to provide improved stratification of the clinical outcomes relative to the National Comprehensive Cancer Network classification. Conclusions: The PPC is an independent and powerful predictor of clinical outcomes of prostate cancer after RT. A risk model replacing T stage with the PPC to reduce subjectivity demonstrated potentially improved stratification.« less

Cyclooxygenase 2 Promotes Parathyroid Hyperplasia in ESRD

PubMed Central

Zhang, Qian; Qiu, Junsi; Li, Haiming; Lu, Yanwen; Wang, Xiaoyun; Yang, Junwei; Wang, Shaoqing; Zhang, Liyin; Gu, Yong; Hao, Chuan-Ming

2011-01-01

Hyperplasia of the PTG underlies the secondary hyperparathyroidism (SHPT) observed in CKD, but the mechanism underlying this hyperplasia is incompletely understood. Because aberrant cyclooxygenase 2 (COX2) expression promotes epithelial cell proliferation, we examined the effects of COX2 on the parathyroid gland in uremia. In patients with ESRD who underwent parathyroidectomy, clusters of cells within the parathyroid glands had increased COX2 expression. Some COX2-positive cells exhibited two nuclei, consistent with proliferation. Furthermore, nearly 78% of COX2-positive cells expressed proliferating cell nuclear antigen (PCNA). In the 5/6-nephrectomy rat model, rats fed a high-phosphate diet had significantly higher serum PTH levels and larger parathyroid glands than sham-operated rats. Compared with controls, the parathyroid glands of uremic rats exhibited more PCNA-positive cells and greater COX2 expression in the chief cells. Treatment with COX2 inhibitor celecoxib significantly reduced PCNA expression, attenuated serum PTH levels, and reduced the size of the glands. In conclusion, COX2 promotes the pathogenesis of hyperparathyroidism in ESRD, suggesting that inhibiting the COX2 pathway could be a potential therapeutic target. PMID:21335517

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

Confounder summary scores when comparing the effects of multiple drug exposures.

PubMed

Cadarette, Suzanne M; Gagne, Joshua J; Solomon, Daniel H; Katz, Jeffrey N; Stürmer, Til

2010-01-01

Little information is available comparing methods to adjust for confounding when considering multiple drug exposures. We compared three analytic strategies to control for confounding based on measured variables: conventional multivariable, exposure propensity score (EPS), and disease risk score (DRS). Each method was applied to a dataset (2000-2006) recently used to examine the comparative effectiveness of four drugs. The relative effectiveness of risedronate, nasal calcitonin, and raloxifene in preventing non-vertebral fracture, were each compared to alendronate. EPSs were derived both by using multinomial logistic regression (single model EPS) and by three separate logistic regression models (separate model EPS). DRSs were derived and event rates compared using Cox proportional hazard models. DRSs derived among the entire cohort (full cohort DRS) was compared to DRSs derived only among the referent alendronate (unexposed cohort DRS). Less than 8% deviation from the base estimate (conventional multivariable) was observed applying single model EPS, separate model EPS or full cohort DRS. Applying the unexposed cohort DRS when background risk for fracture differed between comparison drug exposure cohorts resulted in -7 to + 13% deviation from our base estimate. With sufficient numbers of exposed and outcomes, either conventional multivariable, EPS or full cohort DRS may be used to adjust for confounding to compare the effects of multiple drug exposures. However, our data also suggest that unexposed cohort DRS may be problematic when background risks differ between referent and exposed groups. Further empirical and simulation studies will help to clarify the generalizability of our findings.

Progress of statistical analysis in biomedical research through the historical review of the development of the Framingham score.

PubMed

Ignjatović, Aleksandra; Stojanović, Miodrag; Milošević, Zoran; Anđelković Apostolović, Marija

2017-12-02

The interest in developing risk models in medicine not only is appealing, but also associated with many obstacles in different aspects of predictive model development. Initially, the association of biomarkers or the association of more markers with the specific outcome was proven by statistical significance, but novel and demanding questions required the development of new and more complex statistical techniques. Progress of statistical analysis in biomedical research can be observed the best through the history of the Framingham study and development of the Framingham score. Evaluation of predictive models comes from a combination of the facts which are results of several metrics. Using logistic regression and Cox proportional hazards regression analysis, the calibration test, and the ROC curve analysis should be mandatory and eliminatory, and the central place should be taken by some new statistical techniques. In order to obtain complete information related to the new marker in the model, recently, there is a recommendation to use the reclassification tables by calculating the net reclassification index and the integrated discrimination improvement. Decision curve analysis is a novel method for evaluating the clinical usefulness of a predictive model. It may be noted that customizing and fine-tuning of the Framingham risk score initiated the development of statistical analysis. Clinically applicable predictive model should be a trade-off between all abovementioned statistical metrics, a trade-off between calibration and discrimination, accuracy and decision-making, costs and benefits, and quality and quantity of patient's life.

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.

Differential effects of smoking on lung cancer mortality before and after household stove improvement in Xuanwei, China.

PubMed

Lee, K-M; Chapman, R S; Shen, M; Lubin, J H; Silverman, D T; He, X; Hosgood, H D; Chen, B E; Rajaraman, P; Caporaso, N E; Fraumeni, J F; Blair, A; Lan, Q

2010-08-24

In Xuanwei County, Yunnan Province, China, lung cancer mortality rates in both males and females are among the highest in China. We evaluated differential effects of smoking on lung cancer mortality before and after household stove improvement with chimney to reduce exposure to smoky coal emissions in the unique cohort in Xuanwei, China. Effects of independent variables on lung cancer mortality were measured as hazard ratios and 95% confidence intervals using a multivariable Cox regression model that included separate time-dependent variables for smoking duration (years) before and after stove improvement. We found that the effect of smoking on lung cancer risk becomes considerably stronger after chimney installation and consequent reduction of indoor coal smoke exposure.

Improved parameter inference in catchment models: 1. Evaluating parameter uncertainty

NASA Astrophysics Data System (ADS)

Kuczera, George

1983-10-01

A Bayesian methodology is developed to evaluate parameter uncertainty in catchment models fitted to a hydrologic response such as runoff, the goal being to improve the chance of successful regionalization. The catchment model is posed as a nonlinear regression model with stochastic errors possibly being both autocorrelated and heteroscedastic. The end result of this methodology, which may use Box-Cox power transformations and ARMA error models, is the posterior distribution, which summarizes what is known about the catchment model parameters. This can be simplified to a multivariate normal provided a linearization in parameter space is acceptable; means of checking and improving this assumption are discussed. The posterior standard deviations give a direct measure of parameter uncertainty, and study of the posterior correlation matrix can indicate what kinds of data are required to improve the precision of poorly determined parameters. Finally, a case study involving a nine-parameter catchment model fitted to monthly runoff and soil moisture data is presented. It is shown that use of ordinary least squares when its underlying error assumptions are violated gives an erroneous description of parameter uncertainty.

Statins use and risk of new-onset diabetes in hypertensive patients: a population-based retrospective cohort study in Yinzhou district, Ningbo city, People's Republic of China.

PubMed

Li, Hailong; Lin, Hongbo; Zhao, Houyu; Xu, Yang; Cheng, Yinchu; Shen, Peng; Zhan, Siyan

2018-01-01

Reports have suggested that statin use is associated with an increased incidence of type 2 diabetes mellitus (T2DM). Guidelines suggested that statins should be prescribed in hypertensive patients for primary prevention. However, there were very few studies on the risk of T2DM associated with statin use among patients with hypertension in mainland People's Republic of China. To determine the association between statin use and new-onset diabetes mellitus among patients with hypertension in mainland People's Republic of China. We performed a retrospective cohort study of hypertensive patients using the Yinzhou regional health care database from January 1, 2010, to August 31, 2016. Patients aged 30-90 years old without T2DM were eligible for inclusion. We identified new statin initiators and nonusers by using prescription records of inpatients and outpatients. Multivariate Cox model and propensity score methods were used to adjust potential confounders, including age, sex, body mass index, comorbidities, lifestyle characteristics, and baseline antihypertensive drug use. The risk of incident T2DM among statin initiators compared to nonusers was estimated by the Cox proportional hazards model. Propensity scores for statin use were then developed using logistic regression, statin initiators were matched 1:1 with nonusers according to propensity scores with the nearest neighbor matching method within 0.2 caliper width, and Cox regression was again conducted. Among 67,993 patients (21,551 statin initiators; 46,442 nonusers), the unadjusted incidence rate of incident T2DM was higher in statin initiators than nonusers (25.68 versus 14.19 events/1,000 person-years; adjusted hazard ratio: 1.55; 95% confidence interval: 1.44-1.66). After propensity score 1:1 matching (19,818 statin initiators; 19,818 nonusers), baseline characteristics between 2 groups were balanced except that the nonusers group was 0.53 years older on average ( P <0.001). Then statin use was still associated with a significant increased risk for T2DM in the matched cohort (adjusted hazard ratio: 1.54; 95% confidence interval: 1.41-1.67). Subgroup analyses also demonstrated similar findings. Our study indicated an association between statin use and an increased risk of new-onset diabetes mellitus. It provides better understanding of statin and new-onset diabetes mellitus association among hypertensive patients in real-word setting. As an observational study, our findings were prone to unmeasured confounding and bias.

The long-term outcomes of cirrhotic patients with pleural effusion.

PubMed

Hung, Tsung-Hsing; Tseng, Chih-Wei; Tsai, Chih-Chun; Tsai, Chen-Chi; Tseng, Kuo-Chih; Hsieh, Yu-Hsi

2018-01-01

A pleural effusion is an abnormal collection of fluid in the pleural space and may cause related morbidity or mortality in cirrhotic patients. Currently, there are insufficient data to support the long-term prognosis for cirrhotic patients with pleural effusion. In this study, we investigated the short- and long-term effects of pleural effusion on mortality in cirrhotic patients and evaluated the benefit of liver transplantation in these patients. The National Health Insurance Database, derived from the Taiwan National Health Insurance Program, was used to identify 3,487 cirrhotic patients with pleural effusion requiring drainage between January 1, 2007 and December 31, 2010. The proportional hazards Cox regression model was used to control for possible confounding factors. The 30-day, 90-day, 1-year, and 3-year mortalities were 20.1%, 40.2%, 59.1%, and 75.9%, respectively, in the cirrhotic patients with pleural effusion. After Cox proportional hazard regression analysis adjusted by patient gender, age, complications of cirrhosis and comorbid disorders, old age, esophageal variceal bleeding, hepatocellular carcinoma, hepatic encephalopathy, pneumonia, renal function impairment, and without liver transplantation conferred higher risks for 3-year mortality in the cirrhotic patients with pleura effusion. Liver transplantation is the most important factor to determine the 3-year mortalities (HR: 0.17, 95% CI 0.11- 0.26, P < 0.001). The 30-day, 30 to 90-day, 90-day to 1-year, and 1 to 3-year mortalities were 5.7%, 13.4%, 20.4%, and 21.7% respectively, in the liver transplantation group, and 20.5%, 41.0%, 61.2%, and 77.5%, respectively, in the non-liver transplantation group. In cirrhotic patients, the presence of pleural effusion predicts poor long-term outcomes. Liver transplantation could dramatically improve the survival and should be suggested as soon as possible.

Myocardial Injury in Patients With Sepsis and Its Association With Long-Term Outcome.

PubMed

Frencken, Jos F; Donker, Dirk W; Spitoni, Cristian; Koster-Brouwer, Marlies E; Soliman, Ivo W; Ong, David S Y; Horn, Janneke; van der Poll, Tom; van Klei, Wilton A; Bonten, Marc J M; Cremer, Olaf L

2018-02-01

Sepsis is frequently complicated by the release of cardiac troponin, but the clinical significance of this myocardial injury remains unclear. We studied the associations between troponin release during sepsis and 1-year outcomes. We enrolled consecutive patients with sepsis in 2 Dutch intensive care units between 2011 and 2013. Subjects with a clinically apparent cause of troponin release were excluded. High-sensitivity cardiac troponin I (hs-cTnI) concentration in plasma was measured daily during the first 4 intensive care unit days, and multivariable Cox regression analysis was used to model its association with 1-year mortality while adjusting for confounding. In addition, we studied cardiovascular morbidity occurring during the first year after hospital discharge. Among 1258 patients presenting with sepsis, 1124 (89%) were eligible for study inclusion. Hs-cTnI concentrations were elevated in 673 (60%) subjects on day 1, and 755 (67%) ever had elevated levels in the first 4 days. Cox regression analysis revealed that high hs-cTnI concentrations were associated with increased death rates during the first 14 days (adjusted hazard ratio, 1.72; 95% confidence interval, 1.14-2.59 and hazard ratio, 1.70; 95% confidence interval, 1.10-2.62 for hs-cTnI concentrations of 100-500 and >500 ng/L, respectively) but not thereafter. Furthermore, elevated hs-cTnI levels were associated with the development of cardiovascular disease among 200 hospital survivors who were analyzed for this end point (adjusted subdistribution hazard ratio, 1.25; 95% confidence interval, 1.04-1.50). Myocardial injury occurs in the majority of patients with sepsis and is independently associated with early-but not late-mortality, as well as postdischarge cardiovascular morbidity. © 2018 American Heart Association, Inc.

Drug-Eluting Stents versus Bare-Metal Stents in Taiwanese Patients with Acute Coronary Syndrome: An Outcome Report of a Multicenter Registry

PubMed Central

Lai, Chi-Cheng; Yip, Hon-Kan; Lin, Tsung-Hsien; Wu, Chiung-Jen; Lai, Wen-Ter; Liu, Chun-Peng; Chang, Shu-Chen; Mar, Guang-Yuan

2014-01-01

Background The study aims to compare cardiovascular outcomes of using bare-metal stents (BMS) and drug-eluting stents (DES) in patients with acute coronary syndrome (ACS) through analysis of the database from the Taiwan ACS registry. Large domestic studies comparing outcomes of interventional strategies using DES and BMS in a Taiwanese population with ACS are limited. Methods and Results Collected data regarding characteristics and cardiovascular outcomes from the registry database were compared between the BMS and DES groups. A Cox regression model was used in an unadjusted or adjusted manner for analysis. Baseline characteristics apparently varied between DES group (n = 650) and BMS group (n = 1672) such as ACS types, Killip’s classifications, or coronary blood flows. Compared with the BMS group, the DES group was associated with significantly lower cumulative incidence of all-cause mortality (3.4% vs. 5.8%, p = 0.008), target vessel revascularization (TVR) (5.2% vs. 7.4%, p = 0.035), or major adverse cardiac events (MACE) (10.2% vs. 15.6%, p < 0.001) at 1 year in a real-world setting. Cox regression analysis showed the BMS group referenced as the DES group had significantly higher risk-adjusted total mortality [hazard ratio (HR) = 1.85, p = 0.026], target vessel revascularization (TVR) (HR = 1.59, p = 0.035), and MACE (HR = 1.68, p = 0.001). Conclusions The data show use of DES over BMS provided advantages to patients with ACS in terms of lower 1-year mortality, TVR, and MACE. The study suggests implantation of DES compared with BMS in Taiwanese patients with ACS is safe and beneficial in the real-world setting. PMID:27122834

Adolescent meat intake and breast cancer risk.

PubMed

Farvid, Maryam S; Cho, Eunyoung; Chen, Wendy Y; Eliassen, A Heather; Willett, Walter C

2015-04-15

The breast is particularly vulnerable to carcinogenic influences during adolescence due to rapid proliferation of mammary cells and lack of terminal differentiation. We investigated consumption of adolescent red meat and other protein sources in relation to breast cancer risk in the Nurses' Health Study II cohort. We followed prospectively 44,231 women aged 33-52 years who, in 1998, completed a detailed questionnaire about diet during adolescence. Relative risks (RR) and 95% confidence intervals (95%CI) were estimated using Cox proportional hazard regression. We documented 1132 breast cancer cases during 13-year follow-up. In multivariable Cox regression models with major breast cancer risk factors adjustment, greater consumption of total red meat in adolescence was significantly associated with higher premenopausal breast cancer risk (highest vs. lowest quintiles, RR, 1.43; 95%CI, 1.05-1.94; Ptrend  = 0.007), but not postmenopausal breast cancer. Adolescent intake of poultry was associated with lower risk of breast cancer overall (RR, 0.76; 95%CI, 0.60-0.97; for each serving/day). Adolescent intakes of iron, heme iron, fish, eggs, legumes and nuts were not associated with breast cancer. Replacement of one serving/day of total red meat with one serving of combination of poultry, fish, legumes, and nuts was associated with a 15% lower risk of breast cancer overall (RR, 0.85; 95%CI, 0.74-0.96) and a 23% lower risk of premenopausal breast cancer (RR, 0.77; 95%CI, 0.64-0.92). In conclusion, higher consumption of red meat during adolescence was associated with premenopausal breast cancer. Substituting other dietary protein sources for red meat in adolescent diet may decrease premenopausal breast cancer risk. © 2014 UICC.

Adolescent meat intake and breast cancer risk

PubMed Central

Farvid, Maryam S; Cho, Eunyoung; Chen, Wendy Y; Eliassen, A. Heather; Willett, Walter C

2015-01-01

The breast is particularly vulnerable to carcinogenic influences during adolescence due to rapid proliferation of mammary cells and lack of terminal differentiation. We investigated consumption of adolescent red meat and other protein sources in relation to breast cancer risk in the Nurses' Health Study II cohort. We followed prospectively 44,231 women aged 33-52 years who, in 1998, completed a detailed questionnaire about diet during adolescence. Relative risks (RR) and 95% confidence intervals (95%CI) were estimated using Cox proportional hazard regression. We documented 1132 breast cancer cases during 13-year follow-up. In multivariable Cox regression models with major breast cancer risk factors adjustment, greater consumption of adolescent total red meat was significantly associated with higher premenopausal breast cancer risk (highest vs lowest quintiles, RR, 1.42; 95%CI, 1.05-1.94; Ptrend=0.007), but not postmenopausal breast cancer. Adolescent poultry intake was associated with lower risk of breast cancer overall (RR, 0.75; 95%CI, 0.59-0.96; for each serving/day). Adolescent intakes of iron, heme iron, fish, eggs, legumes and nuts were not associated with breast cancer. Replacement of one serving/day of total red meat with one serving of combination of poultry, fish, legumes, and nuts was associated with a 16% lower risk of breast cancer overall (RR, 0.84; 95%CI, 0.74-0.96) and a 24% lower risk of premenopausal breast cancer (RR, 0.76; 95%CI, 0.64-0.92). Higher consumption of red meat during adolescence was associated with premenopausal breast cancer. Substituting other dietary protein sources for red meat in adolescent diet may decrease premenopausal breast cancer risk. PMID:25220168

Dynamic Contrast-Enhanced Magnetic Resonance Imaging as a Predictor of Outcome in Head-and-Neck Squamous Cell Carcinoma Patients With Nodal Metastases

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

Shukla-Dave, Amita, E-mail: davea@mskcc.org; Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY; Lee, Nancy Y.

2012-04-01

Purpose: Dynamic contrast-enhanced MRI (DCE-MRI) can provide information regarding tumor perfusion and permeability and has shown prognostic value in certain tumors types. The goal of this study was to assess the prognostic value of pretreatment DCE-MRI in head and neck squamous cell carcinoma (HNSCC) patients with nodal disease undergoing chemoradiation therapy or surgery. Methods and Materials: Seventy-four patients with histologically proven squamous cell carcinoma and neck nodal metastases were eligible for the study. Pretreatment DCE-MRI was performed on a 1.5T MRI. Clinical follow-up was a minimum of 12 months. DCE-MRI data were analyzed using the Tofts model. DCE-MRI parameters weremore » related to treatment outcome (progression-free survival [PFS] and overall survival [OS]). Patients were grouped as no evidence of disease (NED), alive with disease (AWD), dead with disease (DOD), or dead of other causes (DOC). Prognostic significance was assessed using the log-rank test for single variables and Cox proportional hazards regression for combinations of variables. Results: At last clinical follow-up, for Stage III, all 12 patients were NED. For Stage IV, 43 patients were NED, 4 were AWD, 11 were DOD, and 4 were DOC. K{sup trans} is volume transfer constant. In a stepwise Cox regression, skewness of K{sup trans} (volume transfer constant) was the strongest predictor for Stage IV patients (PFS and OS: p <0.001). Conclusion: Our study shows that skewness of K{sup trans} was the strongest predictor of PFS and OS in Stage IV HNSCC patients with nodal disease. This study suggests an important role for pretreatment DCE-MRI parameter K{sup trans} as a predictor of outcome in these patients.« less

Tumor-infiltrating lymphocytes predict response to chemotherapy in patients with advance non-small cell lung cancer.

PubMed

Liu, Hui; Zhang, Tiantuo; Ye, Jin; Li, Hongtao; Huang, Jing; Li, Xiaodong; Wu, Benquan; Huang, Xubing; Hou, Jinghui

2012-10-01

Accumulating preclinical evidence suggests that anticancer immune responses contribute to the success of chemotherapy. The predictive significance of tumor-infiltrating lymphocytes (TILs) for response to neoadjuvant chemotherapy in non-small cell lung cancer (NSCLC) remains unknown. The aim of this study was to investigate the prognostic and predictive value of TIL subtypes in patients with advanced NSCLC treated with platinum-based chemotherapy. In total, 159 patients with stage III and IV NSCLC were retrospectively enrolled. The prevalence of CD3(+), CD4(+), CD8(+) and Foxp3(+) TILs was assessed by immunohistochemistry in tumor tissue obtained before chemotherapy. The density of TILs subgroups was treated as dichotomous variables using the median values as cutoff. Survival curves were estimated by the Kaplan-Meier method, and differences in overall survival between groups were determined using the Log-rank test. Prognostic effects of TIL subsets density were evaluated by Cox regression analysis. The presence of CD3(+), CD4(+), CD8(+), and FOXP3(+) TILs was not correlated with any clinicopathological features. Neither the prevalence of TILs nor combined analysis displayed obvious prognostic performances for overall survival in Cox regression model. Instead, higher FOXP3(+)/CD8(+) ratio in tumor sites was an independent factor for poor response to platinum-based chemotherapy in overall cohort. These findings suggest that immunological CD8(+) and FOXP3(+)Tregs cell infiltrate within tumor environment is predictive of response to platinum-based neoadjuvant chemotherapy in advanced NSCLC patients. The understanding of the clinical relevance of the microenvironmental immunological milieu might provide an important clue for the design of novel strategies in cancer immunotherapy.

Flow-covariate prediction of stream pesticide concentrations.

PubMed

Mosquin, Paul L; Aldworth, Jeremy; Chen, Wenlin

2018-01-01

Potential peak functions (e.g., maximum rolling averages over a given duration) of annual pesticide concentrations in the aquatic environment are important exposure parameters (or target quantities) for ecological risk assessments. These target quantities require accurate concentration estimates on nonsampled days in a monitoring program. We examined stream flow as a covariate via universal kriging to improve predictions of maximum m-day (m = 1, 7, 14, 30, 60) rolling averages and the 95th percentiles of atrazine concentration in streams where data were collected every 7 or 14 d. The universal kriging predictions were evaluated against the target quantities calculated directly from the daily (or near daily) measured atrazine concentration at 32 sites (89 site-yr) as part of the Atrazine Ecological Monitoring Program in the US corn belt region (2008-2013) and 4 sites (62 site-yr) in Ohio by the National Center for Water Quality Research (1993-2008). Because stream flow data are strongly skewed to the right, 3 transformations of the flow covariate were considered: log transformation, short-term flow anomaly, and normalized Box-Cox transformation. The normalized Box-Cox transformation resulted in predictions of the target quantities that were comparable to those obtained from log-linear interpolation (i.e., linear interpolation on the log scale) for 7-d sampling. However, the predictions appeared to be negatively affected by variability in regression coefficient estimates across different sample realizations of the concentration time series. Therefore, revised models incorporating seasonal covariates and partially or fully constrained regression parameters were investigated, and they were found to provide much improved predictions in comparison with those from log-linear interpolation for all rolling average measures. Environ Toxicol Chem 2018;37:260-273. © 2017 SETAC. © 2017 SETAC.

SURVIVAL DISPARITIES BY MEDICAID STATUS: AN ANALYSIS OF EIGHT CANCERS

PubMed Central

Koroukian, Siran M.; Bakaki, Paul M.; Raghavan, Derek

2011-01-01

Study Objective To compare survival and 5-year mortality, by Medicaid status, in adults diagnosed with 8 select cancers. Methods Linking records from the Ohio Cancer Incidence Surveillance System (OCISS) with Ohio Medicaid enrollment data, we identified Medicaid and non-Medicaid patients aged 15–54 years and diagnosed with the following incident cancers in the years 1996–2002: cancer of the testis; Hodgkin’s and non-Hodgkin’s lymphoma; early-stage melanoma, colon, lung, and bladder cancer; or pediatric malignancies (n=12,703). Medicaid beneficiaries were identified in the pre-diagnosis group if they were enrolled in Medicaid at least 3 months before cancer diagnosis, and in the peri/post-diagnosis group if they enrolled in Medicaid upon or after being diagnosed with cancer. We also linked the OCISS with death certificates and data from the U.S. Census. Using Cox and logistic regression analysis, we examined the association between Medicaid status and each of survival and 5-year mortality, respectively, after adjusting for patient covariates. Results Nearly 11% of the study population were Medicaid beneficiaries. Of those, 45% were identified in the peri/post-diagnosis group. Consistent with higher mortality, findings from the Cox regression model indicated that compared to non-Medicaid, patients in the Medicaid pre-diagnosis and peri/post-diagnosis groups experienced unfavorable survival outcomes (adjusted hazard ratio (AHR): 1.52, 95% confidence interval (1.27, 1.82), and 2.01 (1.70, 2.38), respectively). Conclusions Medicaid status was associated with unfavorable survival, even after adjusting for confounders. Impact The findings reflect the vulnerability of Medicaid beneficiaries and possible inadequacies in the process of care. PMID:22213271