Biostatistics and Epidemiology最新文献_第9页

Validity and power of minimization algorithm in longitudinal analysis of clinical trials. 最小化算法在临床试验纵向分析中的有效性和有效性。

Biostatistics and Epidemiology Pub Date : 2017-01-01 Epub Date: 2017-06-13 DOI: 10.1080/24709360.2017.1331822

Hua Weng, Randall Bateman, John C Morris, Chengjie Xiong

{"title":"Validity and power of minimization algorithm in longitudinal analysis of clinical trials.","authors":"Hua Weng, Randall Bateman, John C Morris, Chengjie Xiong","doi":"10.1080/24709360.2017.1331822","DOIUrl":"https://doi.org/10.1080/24709360.2017.1331822","url":null,"abstract":"We studied the validity of longitudinal statistical inferences of clinical trials using minimization, a dynamic randomization algorithm designed to minimize treatment imbalance for prognostic factors. Repeated measures analysis of covariance and the random intercept and slope models, were used to simulate longitudinal clinical trials randomized by minimization or simple randomization. The simulations represented a wide range of analyses in real-world trials, including missing data caused by dropouts, unequal allocation of treatment arms, and efficacy analyses on either the original outcome or its change from baseline. We also analyzed the database from the Dominantly Inherited Alzheimer Network (DIAN), and used the estimated parameters to simulate the ongoing DIAN trial. Our analyses demonstrated minimization had conservative type I errors when the prognostic factor used in the minimization algorithm had a relatively strong correlation with the outcome and was not adjusted for in analyses. In contrast, adjusted tests for the prognostic factor as a covariate resulted in type I errors close to the nominal significance level. In many simulation scenarios, the adjusted tests using minimization had slightly greater statistical power than those using simple randomization, whereas in the other scenarios, the power of adjusted tests using these two randomization methods are almost indistinguishable.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"1 1","pages":"59-77"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2017.1331822","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35665221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Joint modeling of longitudinal cholesterol measurements and time to onset of dementia in an elderly African American Cohort 纵向胆固醇测量和老年非裔美国人痴呆发病时间的联合建模

Biostatistics and Epidemiology Pub Date : 2017-01-01 DOI: 10.1080/24709360.2017.1381300

Shanshan Li, Mengjie Zheng, Sujuan Gao

{"title":"Joint modeling of longitudinal cholesterol measurements and time to onset of dementia in an elderly African American Cohort","authors":"Shanshan Li, Mengjie Zheng, Sujuan Gao","doi":"10.1080/24709360.2017.1381300","DOIUrl":"https://doi.org/10.1080/24709360.2017.1381300","url":null,"abstract":"ABSTRACT This paper presents a statistical method for analyzing the association between longitudinal cholesterol measurements and the timing of onset of dementia. The proposed approach jointly models the longitudinal and survival processes for each individual on the basis of a shared random effect, where a linear mixed effects model is assumed for the longitudinal component and an extended Cox regression model is employed for the survival component. A dynamic prediction model is built based on the joint model, which provides prediction of the conditional survival probabilities at different time points using available longitudinal measurements as well as baseline characteristics. We apply our method to the Indianapolis-Ibadan Dementia project, a 20-year study of dementia in elderly African Americans living in Indianapolis, Indiana. We find that with baseline covariates and comorbidities adjusted, the risk of dementia decreases by 1% per one mg/dl increase in total cholesterol. Therefore we conclude that, in a healthy cohort of African Americans aged 65 years or more, high late-life cholesterol level is associated with lower incidence of dementia.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"1 1","pages":"148 - 160"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2017.1381300","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45026971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Using time-varying quantile regression approaches to model the influence of prenatal and infant exposures on childhood growth 使用时变分位数回归方法模拟产前和婴儿暴露对儿童生长的影响

Biostatistics and Epidemiology Pub Date : 2017-01-01 DOI: 10.1080/24709360.2017.1358137

Ying Wei, Xinran Ma, Xinhua Liu, M. Terry

{"title":"Using time-varying quantile regression approaches to model the influence of prenatal and infant exposures on childhood growth","authors":"Ying Wei, Xinran Ma, Xinhua Liu, M. Terry","doi":"10.1080/24709360.2017.1358137","DOIUrl":"https://doi.org/10.1080/24709360.2017.1358137","url":null,"abstract":"ABSTRACT For many applications, it is valuable to assess whether the effects of exposures over time vary by quantiles of the outcome. We have previously shown that quantile methods complement the traditional mean-based analyses, and are useful for studies of body size. Here, we extended previous work to time-varying quantile associations. Using data from over 18,000 children in the U.S. Collaborative Perinatal Project, we investigated the impact of maternal pre-pregnancy body mass index (BMI), maternal pregnancy weight gain, placental weight, and birth weight on childhood body size measured 4 times between 3 months and 7 years, using both parametric and non-parametric time-varying quantile regressions. Using our proposed model assessment tool, we found that non-parametric models fit the childhood growth data better than the parametric approaches. We also observed that quantile analysis resulted in difference inferences than the conditional mean models in three of the four constructs (maternal per-pregancy BMI, maternal weight gain, and placental weight). Overall, these results suggest the utility of applying time-varying quantile models for longitudinal outcome data. They also suggest that in the studies of body size, merely modelling the conditional mean may lead to incomplete summary of the data.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"1 1","pages":"133 - 147"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2017.1358137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48816696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Application of Concordance Probability Estimate to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease. 一致性概率估计在预测轻度认知障碍向阿尔茨海默病转化中的应用。

Biostatistics and Epidemiology Pub Date : 2017-01-01 Epub Date: 2017-07-31 DOI: 10.1080/24709360.2017.1342187

Xiaoxia Han, Yilong Zhang, Yongzhao Shao

引用次数: 8

Editorial 社论

Biostatistics and Epidemiology Pub Date : 2017-01-01 DOI: 10.1080/24709360.2016.1198464

Xiaohong Zhou

引用次数: 0

A tutorial on kernel density estimation and recent advances 一个关于核密度估计和最新进展的教程

Biostatistics and Epidemiology Pub Date : 2017-01-01 DOI: 10.1080/24709360.2017.1396742

Yen-Chi Chen

引用次数: 281

Analysis of progressive multi-state models with misclassified states: likelihood and pairwise likelihood methods 状态分类错误的渐进式多状态模型分析:似然与两两似然方法

Biostatistics and Epidemiology Pub Date : 2017-01-01 DOI: 10.1080/24709360.2017.1359356

G. Yi, Wenqing He, Feng He

引用次数: 0

Multi-state models and missing covariate data: Expectation-Maximization algorithm for likelihood estimation. 多状态模型和缺失协变量数据:似然估计的期望最大化算法。

Biostatistics and Epidemiology Pub Date : 2017-01-01 Epub Date: 2017-04-04 DOI: 10.1080/24709360.2017.1306156

Wenjie Lou, Lijie Wan, Erin L Abner, David W Fardo, Hiroko H Dodge, Richard J Kryscio

引用次数: 10

Linear Combinations of Multiple Outcome Measures to Improve the Power of Efficacy Analysis ---Application to Clinical Trials on Early Stage Alzheimer Disease. 多结局指标线性组合提高疗效分析的有效性——在早期阿尔茨海默病临床试验中的应用

Biostatistics and Epidemiology Pub Date : 2017-01-01 Epub Date: 2017-06-02 DOI: 10.1080/24709360.2017.1331821

Chengjie Xiong, Jingqin Luo, John C Morris, Randall Bateman

{"title":"Linear Combinations of Multiple Outcome Measures to Improve the Power of Efficacy Analysis ---Application to Clinical Trials on Early Stage Alzheimer Disease.","authors":"Chengjie Xiong, Jingqin Luo, John C Morris, Randall Bateman","doi":"10.1080/24709360.2017.1331821","DOIUrl":"https://doi.org/10.1080/24709360.2017.1331821","url":null,"abstract":"Modern clinical trials on Alzheimer disease (AD) focus on the early symptomatic stage or even the preclinical stage. Subtle disease progression at the early stages, however, poses a major challenge in designing such clinical trials. We propose a multivariate mixed model on repeated measures to model the disease progression over time on multiple efficacy outcomes, and derive the optimum weights to combine multiple outcome measures by minimizing the sample sizes to adequately power the clinical trials. A cross-validation simulation study is conducted to assess the accuracy for the estimated weights as well as the improvement in reducing the sample sizes for such trials. The proposed methodology is applied to the multiple cognitive tests from the ongoing observational study of the Dominantly Inherited Alzheimer Network (DIAN) to power future clinical trials in the DIAN with a cognitive endpoint. Our results show that the optimum weights to combine multiple outcome measures can be accurately estimated, and that compared to the individual outcomes, the combined efficacy outcome with these weights significantly reduces the sample size required to adequately power clinical trials. When applied to the clinical trial in the DIAN, the estimated linear combination of six cognitive tests can adequately power the clinical trial.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"1 1","pages":"36-58"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2017.1331821","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35919411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6