Biostatistics and Epidemiology最新文献_第8页

Epidemiological characteristics of severe cases of hand, foot, and mouth disease in Guangdong, China 广东省严重手足口病病例流行病学特征分析

Biostatistics and Epidemiology Pub Date : 2018-01-01 DOI: 10.1080/24709360.2018.1469809

Zhicheng Du, Wangjian Zhang, Dingmei Zhang, Shicheng Yu, Y. Hao

{"title":"Epidemiological characteristics of severe cases of hand, foot, and mouth disease in Guangdong, China","authors":"Zhicheng Du, Wangjian Zhang, Dingmei Zhang, Shicheng Yu, Y. Hao","doi":"10.1080/24709360.2018.1469809","DOIUrl":"https://doi.org/10.1080/24709360.2018.1469809","url":null,"abstract":"ABSTRACT Hand, foot, and mouth disease (HFMD) has become a major public health issue in China, especially in Guangdong. The burden of severe cases deserves further attention. We hereby explored the epidemiological features of severe HFMD in Guangdong. Patients who were from rural areas (OR = 2.03, 95% CI: 1.86–2.21), males (OR = 1.17, 1.07–1.28), aged ≤3 years old (2.48, 1.68–3.68, and 1.63, 1.10–2.41, for ≤1 and 2–3 years, respectively), and/or infected with EV71 (6.69, 5.98–7.49) tended to progress to severe status. Cases from rural areas tended to have a longer interval from onset to diagnosis (p < .001; i.e. the proportions of each interval (≤1, ∼2, ∼3, ∼4, and >4 days) for rural and urban areas in 2009 were 14%, 13%, 14%, 8%, 51%, and 21%, 21%, 15%, 11%, 31%, respectively). The spatial pattern of the epidemics clarified by the flexible scan statistic showed that the clusters of severe cases were observed to be expanding from the Pearl River Delta Region to the Eastern Region and the Mountainous Region. Overall, the relative risk of the most likely clusters ranged from 5.548 to 15.558 (all p < .001). Our results were particularly practical and important for developing severe HFMD-targeted control programs in the context of disease surveillance. Abbreviations: CA16: Coxsackievirus A16; EV71: enterovirus 71; GDP: gross domestic product; HFMD: hand; foot and mouth disease.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"2 1","pages":"114 - 99"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2018.1469809","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43540542","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: 7

On two-step residual inclusion estimator for instrument variable additive hazards model 仪器变量加性危害模型的两步残差包含估计

Biostatistics and Epidemiology Pub Date : 2018-01-01 DOI: 10.1080/24709360.2017.1406567

Binyan Jiang, Jialiang Li, J. Fine

引用次数: 7

Goodness-of-fit test for the parametric proportional hazard regression model with interval-censored data 区间截尾数据的参数比例风险回归模型的拟合优度检验

Biostatistics and Epidemiology Pub Date : 2018-01-01 DOI: 10.1080/24709360.2018.1529347

R. Sakurai, S. Hattori

{"title":"Goodness-of-fit test for the parametric proportional hazard regression model with interval-censored data","authors":"R. Sakurai, S. Hattori","doi":"10.1080/24709360.2018.1529347","DOIUrl":"https://doi.org/10.1080/24709360.2018.1529347","url":null,"abstract":"ABSTRACT Interval-censored data are common in medical research. Fully parametric models provide simple and efficient inference for the estimation of survival functions using interval-censored observations. Inference based on a parametric regression model requires the complete specification of the probability density function, and therefore, correctly specifying the model is crucial, while the regression diagnostic is a very important step. However, regression diagnostic methods for use with the interval-censored data have not been completely developed. Here, we developed a model-checking procedure based on the cumulative martingale residuals for the interval-censored observations. We employed the conditional expectation of residuals for the diagnostics, because the data showing the exact failure time cannot be obtained for the interval-censoring analyses, and developed the formal resampling-based supremum-type test and graphical model-checking techniques. A simulation study demonstrated an excellent performance of the proposed method during the detection of a misspecified functional form of covariates in the finite sample. Furthermore, we used this method for the analysis of the medical checkup data obtained in Japan.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"2 1","pages":"115 - 131"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2018.1529347","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48434276","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: 0

Recent developments in statistical methods for GWAS and high-throughput sequencing association studies of complex traits GWAS统计方法和复杂性状高通量测序关联研究的最新进展

Biostatistics and Epidemiology Pub Date : 2018-01-01 DOI: 10.1080/24709360.2018.1529346

Duo Jiang, Miaoyan Wang

引用次数: 5

The Kaplan-Meier Method for Estimating and Comparing Proportions in a Randomized Controlled Trial with Dropouts. Kaplan-Meier法估计和比较随机对照试验中有退出的比例。

Biostatistics and Epidemiology Pub Date : 2018-01-01 Epub Date: 2017-11-30 DOI: 10.1080/24709360.2017.1407866

Jarcy Zee, Sharon X Xie

{"title":"The Kaplan-Meier Method for Estimating and Comparing Proportions in a Randomized Controlled Trial with Dropouts.","authors":"Jarcy Zee, Sharon X Xie","doi":"10.1080/24709360.2017.1407866","DOIUrl":"https://doi.org/10.1080/24709360.2017.1407866","url":null,"abstract":"<p><p>We propose a method for estimating and comparing proportions of study participants who reached an event of interest during a randomized controlled trial. Standard methods for estimating this proportion include the intent-to-treat method, which counts the number who reached the event of interest divided by the total number of participants, and the completers-only method, which counts the number who reached the event only among those who completed the entire study. When participants drop out of the study early, however, these methods will either be biased or inefficient. We propose to use the Kaplan-Meier method from survival analysis to estimate the proportion of interest in this non-survival setting. We show through extensive simulation studies that the Kaplan-Meier method has less bias and is more efficient than the standard methods. We demonstrate the performance of all methods for estimating proportions in one sample and for comparing proportions across two samples. Finally, we apply the proposed method to a data set for estimating and comparing proportions of patients who achieved treatment response during a Parkinson's disease trial for the treatment of impulse control disorders.</p>","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"2 1","pages":"23-33"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2017.1407866","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36507405","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

Exact inference on meta-analysis with generalized fixed-effects and random-effects models 广义固定效应和随机效应模型meta分析的精确推断

Biostatistics and Epidemiology Pub Date : 2018-01-01 DOI: 10.1080/24709360.2017.1400714

Sifan Liu, L. Tian, Steve Lee, Min‐ge Xie

{"title":"Exact inference on meta-analysis with generalized fixed-effects and random-effects models","authors":"Sifan Liu, L. Tian, Steve Lee, Min‐ge Xie","doi":"10.1080/24709360.2017.1400714","DOIUrl":"https://doi.org/10.1080/24709360.2017.1400714","url":null,"abstract":"ABSTRACT Meta-analysis with fixed-effects and random-effects models provides a general framework for quantitatively summarizing multiple comparative studies. However, a majority of the conventional methods rely on large-sample approximations to justify their inference, which may be invalid and lead to erroneous conclusions, especially when the number of studies is not large, or sample sizes of the individual studies are small. In this article, we propose a set of ‘exact’ confidence intervals for the overall effect, where the coverage probabilities of the intervals can always be achieved. We start with conventional parametric fixed-effects and random-effects models, and then extend the exact methods beyond the commonly postulated Gaussian assumptions. Efficient numerical algorithms for implementing the proposed methods are developed. We also conduct simulation studies to compare the performance of our proposal to existing methods, indicating our proposed procedures are better in terms of coverage level and robustness. The new proposals are then illustrated with the data from meta-analyses for estimating the efficacy of statins and BCG vaccination.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"2 1","pages":"1 - 22"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2017.1400714","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46269654","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: 10

Identifying associated risk factors for severity of diabetic retinopathy from ordinal logistic regression models 从有序logistic回归模型中识别糖尿病视网膜病变严重程度的相关危险因素

Biostatistics and Epidemiology Pub Date : 2018-01-01 DOI: 10.1080/24709360.2017.1406040

V. Kulothungan, M. Subbiah, R. Ramakrishnan, R. Raman

引用次数: 2

Tree-based ensemble methods for individualized treatment rules 基于树的个性化治疗规则集成方法

Biostatistics and Epidemiology Pub Date : 2018-01-01 DOI: 10.1080/24709360.2018.1435608

Kehao Zhu, Ying Huang, Xiao‐Hua Zhou

{"title":"Tree-based ensemble methods for individualized treatment rules","authors":"Kehao Zhu, Ying Huang, Xiao‐Hua Zhou","doi":"10.1080/24709360.2018.1435608","DOIUrl":"https://doi.org/10.1080/24709360.2018.1435608","url":null,"abstract":"ABSTRACT There is a growing interest in the development of statistical methods for personalized medicine or precision medicine, especially for deriving optimal individualized treatment rules (ITRs). An ITR recommends a patient to a treatment based on the patient's characteristics. The common parametric methods for deriving an optimal ITR, which model the clinical endpoint as a function of the patient's characteristics, can have suboptimal performance when the conditional mean model is misspecified. Recent methodology development has cast the problem of deriving optimal ITR under a weighted classification framework. Under this weighted classification framework, we develop a weighted random forests (W-RF) algorithm that derives an optimal ITR nonparametrically. In addition, with the W-RF algorithm, we propose the variable importance measures for quantifying relative relevance of the patient's characteristics to treatment selection, and the out-of-bag estimator for the population average outcome under the estimated optimal ITR. Our proposed methods are evaluated through intensive simulation studies. We illustrate the application of our methods using data from Clinical Antipsychotic Trials of Intervention Effectiveness Alzheimer's Disease Study.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"2 1","pages":"61 - 83"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2018.1435608","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46111890","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

Nonparametric estimation of medical cost quantiles in the presence of competing terminal events 存在竞争性终端事件时医疗费用分位数的非参数估计

Biostatistics and Epidemiology Pub Date : 2017-01-01 DOI: 10.1080/24709360.2017.1342185

Mei-Cheng Wang, Yifei Sun

引用次数: 0

Statistical considerations for assessing cognition and neuropathology associations in preclinical Alzheimer's disease 评估临床前阿尔茨海默病的认知和神经病理学关联的统计学考虑

Biostatistics and Epidemiology Pub Date : 2017-01-01 DOI: 10.1080/24709360.2017.1342186

M. Malek-Ahmadi, E. Mufson, S. Perez, Kewei Chen

{"title":"Statistical considerations for assessing cognition and neuropathology associations in preclinical Alzheimer's disease","authors":"M. Malek-Ahmadi, E. Mufson, S. Perez, Kewei Chen","doi":"10.1080/24709360.2017.1342186","DOIUrl":"https://doi.org/10.1080/24709360.2017.1342186","url":null,"abstract":"ABSTRACT Analysis of the associations between the neuropathology of Alzheimer's disease (AD) and cognition has become a major area of investigation as both basic and clinical researchers have turned their attention toward identifying the factors underlying the onset of preclinical AD. Here we provide a conceptual overview of statistical approaches for analyzing associations between cognition and AD neuropathology in the context of the prodromal AD. The review will discuss a variety of statistical approaches, their application to various clinical pathological variables, and research questions, as well as the importance of accounting for and including interaction terms in statistical models. The overview presented here will introduce data analysts and statisticians to the nomenclature of AD neuropathology and provide relevant background information regarding the nature of cognitive and neuropathological data generated in the investigation of preclinical AD. In addition, we will introduce a number of statistical approaches that researchers who specialize in AD neuropathology may utilize in their studies. For both audiences, this review will provide an applied statistical framework to draw from for future research.","PeriodicalId":37240,"journal":{"name":"Biostatistics and Epidemiology","volume":"1 1","pages":"104 - 92"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/24709360.2017.1342186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45352245","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: 5