共查询到20条相似文献，搜索用时 78 毫秒
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M.‐A. Bind T. J. VanderWeele J. D. Schwartz B. A. Coull 《Statistics in medicine》2017,36(26):4182-4195
Mediation analysis has mostly been conducted with mean regression models. With this approach modeling means, formulae for direct and indirect effects are based on changes in means, which may not capture effects that occur in units at the tails of mediator and outcome distributions. Individuals with extreme values of medical endpoints are often more susceptible to disease and can be missed if one investigates mean changes only. We derive the controlled direct and indirect effects of an exposure along percentiles of the mediator and outcome using quantile regression models and a causal framework. The quantile regression models can accommodate an exposure‐mediator interaction and random intercepts to allow for longitudinal mediator and outcome. Because DNA methylation acts as a complex “switch” to control gene expression and fibrinogen is a cardiovascular factor, individuals with extreme levels of these markers may be more susceptible to air pollution. We therefore apply this methodology to environmental data to estimate the effect of air pollution, as measured by particle number, on fibrinogen levels through a change in interferon‐gamma (IFN‐γ) methylation. We estimate the controlled direct effect of air pollution on the qth percentile of fibrinogen and its indirect effect through a change in the pth percentile of IFN‐γ methylation. We found evidence of a direct effect of particle number on the upper tail of the fibrinogen distribution. We observed a suggestive indirect effect of particle number on the upper tail of the fibrinogen distribution through a change in the lower percentiles of the IFN‐γ methylation distribution. 相似文献
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Dylan S. Small Marshall M. Joffe Kevin G. Lynch Jason A. Roy A. Russell Localio 《Statistics in medicine》2014,33(20):3421-3433
Tom Ten Have made many contributions to causal inference and biostatistics before his untimely death. This paper reviews Tom's contributions and discusses potential related future research directions. We focus on Tom's contributions to longitudinal/repeated measures categorical data analysis and particularly his contributions to causal inference. Tom's work on causal inference was primarily in the areas of estimating the effect of receiving treatment in randomized trials with nonadherence and mediation analysis. A related area to mediation analysis he was working on at the time of his death was posttreatment effect modification with applications to designing adaptive treatment strategies. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Michele Santacatterina Celia García-Pareja Rino Bellocco Anders Sönnerborg Anna Mia Ekström Matteo Bottai 《Statistics in medicine》2019,38(10):1891-1902
Marginal structural Cox models have been used to estimate the causal effect of a time-varying treatment on a survival outcome in the presence of time-dependent confounders. These methods rely on the positivity assumption, which states that the propensity scores are bounded away from zero and one. Practical violations of this assumption are common in longitudinal studies, resulting in extreme weights that may yield erroneous inferences. Truncation, which consists of replacing outlying weights with less extreme ones, is the most common approach to control for extreme weights to date. While truncation reduces the variability in the weights and the consequent sampling variability of the estimator, it can also introduce bias. Instead of truncated weights, we propose using optimal probability weights, defined as those that have a specified variance and the smallest Euclidean distance from the original, untruncated weights. The set of optimal weights is obtained by solving a constrained quadratic optimization problem. The proposed weights are evaluated in a simulation study and applied to the assessment of the effect of treatment on time to death among people in Sweden who live with human immunodeficiency virus and inject drugs. 相似文献
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Xu Shi Robert Wellman Patrick J. Heagerty Jennifer C. Nelson Andrea J. Cook 《Statistics in medicine》2020,39(4):369-386
We consider the critical problem of pharmacosurveillance for adverse events once a drug or medical product is incorporated into routine clinical care. When making inference on comparative safety using large-scale electronic health records, we often encounter an extremely rare binary adverse outcome with a large number of potential confounders. In this context, it is challenging to offer flexible methods to adjust for high-dimensional confounders, whereas use of the propensity score (PS) can help address this challenge by providing both confounding control and dimension reduction. Among PS methods, regression adjustment using the PS as a covariate in an outcome model has been incompletely studied and potentially misused. Previous studies have suggested that simple linear adjustment may not provide sufficient control of confounding. Moreover, no formal representation of the statistical procedure and associated inference has been detailed. In this paper, we characterize a three-step procedure, which performs flexible regression adjustment of the estimated PS followed by standardization to estimate the causal effect in a select population. We also propose a simple variance estimation method for performing inference. Through a realistic simulation mimicking data from the Food and Drugs Administration's Sentinel Initiative comparing the effect of angiotensin-converting enzyme inhibitors and beta blockers on incidence of angioedema, we show that flexible regression on the PS resulted in less bias without loss of efficiency, and can outperform other methods when the PS model is correctly specified. In addition, the direct variance estimation method is a computationally fast and reliable approach for inference. 相似文献
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Patient noncompliance complicates the analysis of many randomized trials seeking to evaluate the effect of surgical intervention as compared with a nonsurgical treatment. If selection for treatment depends on intermediate patient characteristics or outcomes, then 'as-treated' analyses may be biased for the estimation of causal effects. Therefore, the selection mechanism for treatment and/or compliance should be carefully considered when conducting analysis of surgical trials. We compare the performance of alternative methods when endogenous processes lead to patient crossover. We adopt an underlying longitudinal structural mixed model that is a natural example of a structural nested model. Likelihood-based methods are not typically used in this context; however, we show that standard linear mixed models will be valid under selection mechanisms that depend only on past covariate and outcome history. If there are underlying patient characteristics that influence selection, then likelihood methods can be extended via maximization of the joint likelihood of exposure and outcomes. Semi-parametric causal estimation methods such as marginal structural models, g-estimation, and instrumental variable approaches can also be valid, and we both review and evaluate their implementation in this setting. The assumptions required for valid estimation vary across approaches; thus, the choice of methods for analysis should be driven by which outcome and selection assumptions are plausible. 相似文献
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Jessica G. Young Mats J. Stensrud Eric J. Tchetgen Tchetgen Miguel A. Hernán 《Statistics in medicine》2020,39(8):1199-1236
In failure-time settings, a competing event is any event that makes it impossible for the event of interest to occur. For example, cardiovascular disease death is a competing event for prostate cancer death because an individual cannot die of prostate cancer once he has died of cardiovascular disease. Various statistical estimands have been defined as possible targets of inference in the classical competing risks literature. Many reviews have described these statistical estimands and their estimating procedures with recommendations about their use. However, this previous work has not used a formal framework for characterizing causal effects and their identifying conditions, which makes it difficult to interpret effect estimates and assess recommendations regarding analytic choices. Here we use a counterfactual framework to explicitly define each of these classical estimands. We clarify that, depending on whether competing events are defined as censoring events, contrasts of risks can define a total effect of the treatment on the event of interest or a direct effect of the treatment on the event of interest not mediated by the competing event. In contrast, regardless of whether competing events are defined as censoring events, counterfactual hazard contrasts cannot generally be interpreted as causal effects. We illustrate how identifying assumptions for all of these counterfactual estimands can be represented in causal diagrams, in which competing events are depicted as time-varying covariates. We present an application of these ideas to data from a randomized trial designed to estimate the effect of estrogen therapy on prostate cancer mortality. 相似文献
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Cong Liu Junghwan Lee Casey Ta Ali Soroush James R Rogers Jae Hyun Kim Karthik Natarajan Jason Zucker Yehoshua Perl Chunhua Weng 《JMIR Public Health and Surveillance》2022,8(5)
BackgroundCOVID-19 messenger RNA (mRNA) vaccines have demonstrated efficacy and effectiveness in preventing symptomatic COVID-19, while being relatively safe in trial studies. However, vaccine breakthrough infections have been reported.ObjectiveThis study aims to identify risk factors associated with COVID-19 breakthrough infections among fully mRNA-vaccinated individuals.MethodsWe conducted a series of observational retrospective analyses using the electronic health records (EHRs) of the Columbia University Irving Medical Center/New York Presbyterian (CUIMC/NYP) up to September 21, 2021. New York City (NYC) adult residences with at least 1 polymerase chain reaction (PCR) record were included in this analysis. Poisson regression was performed to assess the association between the breakthrough infection rate in vaccinated individuals and multiple risk factors—including vaccine brand, demographics, and underlying conditions—while adjusting for calendar month, prior number of visits, and observational days in the EHR.ResultsThe overall estimated breakthrough infection rate was 0.16 (95% CI 0.14-0.18). Individuals who were vaccinated with Pfizer/BNT162b2 (incidence rate ratio [IRR] against Moderna/mRNA-1273=1.66, 95% CI 1.17-2.35) were male (IRR against female=1.47, 95% CI 1.11-1.94) and had compromised immune systems (IRR=1.48, 95% CI 1.09-2.00) were at the highest risk for breakthrough infections. Among all underlying conditions, those with primary immunodeficiency, a history of organ transplant, an active tumor, use of immunosuppressant medications, or Alzheimer disease were at the highest risk.ConclusionsAlthough we found both mRNA vaccines were effective, Moderna/mRNA-1273 had a lower incidence rate of breakthrough infections. Immunocompromised and male individuals were among the highest risk groups experiencing breakthrough infections. Given the rapidly changing nature of the SARS-CoV-2 pandemic, continued monitoring and a generalizable analysis pipeline are warranted to inform quick updates on vaccine effectiveness in real time. 相似文献
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电子病历的核心是临床数据存储库,本文以中山市人民医院电子病历项目为案例,介绍了在新医疗体制改革和医院电子信息化快速发展的背景下,探讨建立临床数据存储厍、实现电子病历电子化存储及其信息资源开发利用的方案,重点阐述了建立临床数据存储库需要重点帑竿决的关键技术问题,以及项目实施后的应用体会,为后继电子病历研究提供依据。 相似文献
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After over half a century of computer application development in medicine, the US health system has gone digital with an enthusiastic confidence for rapid improvements in care outcomes, especially those of quality of care, safety, and productivity. The bad news is that evidence for the justification of the hype around health information technology (HIT) is conflicting, and the expected benefits of a digital health system have not yet materialized. We propose a national system for monitoring HIT impact based on the paradigm of the learning health system (LHS): learning from practical experience through high‐quality, ongoing monitoring of care outcomes. Our proposal aims at leveraging current de facto standard research data repositories used to support large‐scale clinical studies by incorporating data needed for more robust HIT assessments and application of rigorous research designs that are now feasible on a large scale. 相似文献
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Catherine A. Welch Irene Petersen Jonathan W. Bartlett Ian R. White Louise Marston Richard W. Morris Irwin Nazareth Kate Walters James Carpenter 《Statistics in medicine》2014,33(21):3725-3737
Most implementations of multiple imputation (MI) of missing data are designed for simple rectangular data structures ignoring temporal ordering of data. Therefore, when applying MI to longitudinal data with intermittent patterns of missing data, some alternative strategies must be considered. One approach is to divide data into time blocks and implement MI independently at each block. An alternative approach is to include all time blocks in the same MI model. With increasing numbers of time blocks, this approach is likely to break down because of co‐linearity and over‐fitting. The new two‐fold fully conditional specification (FCS) MI algorithm addresses these issues, by only conditioning on measurements, which are local in time. We describe and report the results of a novel simulation study to critically evaluate the two‐fold FCS algorithm and its suitability for imputation of longitudinal electronic health records. After generating a full data set, approximately 70% of selected continuous and categorical variables were made missing completely at random in each of ten time blocks. Subsequently, we applied a simple time‐to‐event model. We compared efficiency of estimated coefficients from a complete records analysis, MI of data in the baseline time block and the two‐fold FCS algorithm. The results show that the two‐fold FCS algorithm maximises the use of data available, with the gain relative to baseline MI depending on the strength of correlations within and between variables. Using this approach also increases plausibility of the missing at random assumption by using repeated measures over time of variables whose baseline values may be missing. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. 相似文献
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目的：建立记录简单、操作方便、符合门诊业务特点的电子病历。方法通过分析门诊业务的特殊性和门诊电子病历的需求程度,比较门诊病历与住院电子病历之间的差异,提出采用数据抽取的方法建立门诊电子病历。结果基于数据抽取的电子病历符合门诊的业务要求,医疗信息丰富,具有可操作性和可行性。结论住院电子病历以及其建设思路不适合完全移植到门诊业务中,采用数据抽取的方法,自动生成电子病历能够快速完成门诊病历的收集储存,对患者、医师、医院都具有重要意义。 相似文献
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目的总结我院电子病历系统在应用中的关键问题与具体实施经验,为科学合理地搭建数字化医院提供设计方案。方法电子病历以病人为中心建立信息集成与相关服务,包括传统的门诊、住院病历、各类检查、检验报告以及各类影像等多媒体信息。结果最终实现电子病历标准的统一,在不同平台下的电子病历与医疗仪器设备的无缝连接和医学数据信息的无障碍交换,实现医院内部电子病历信息资源的集成和共享。结论电子病历系统在医院的应用提升了临床工作效率,为临床决策提供了辅助功能。 相似文献
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Rebecca A. Hubbard 《Statistics in medicine》2021,40(1):29-31
As availability of health care data for research opens up new frontiers in medical statistics, keeping a focus on the science behind the data is more important than ever to promote sound research and protect the validity of research results. Though the electronic databases currently amassed for research far exceed in scale and scope the observational research Professor Hill likely conceived of, his guidance to statisticians to ground our work in the biological and medical processes behind the data remains salient across the decades. 相似文献
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居益君 《江苏卫生事业管理》2010,21(5):64-65
随着医院信息化建设的不断推进,越来越多的医疗机构开始使用电子病历。利用电子病历规范、快捷、易保存、易修改、易检索、资源共享等优势,可充分提高医院工作效率,优化工作流程,促进医疗质量稳步提升,加强电子病历运维的事前控制、环节控制和终末控制则是提高医疗质量的有效保障。 相似文献
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Mireille E. Schnitzer Robert W. Platt Madeleine Durand 《Statistics in medicine》2020,39(29):4538-4550
In this tutorial, we focus on the problem of how to define and estimate treatment effects when some patients develop a contraindication and are thus ineligible to receive a treatment of interest during follow-up. We first describe the concept of positivity, which is the requirement that all subjects in an analysis be eligible for all treatments of interest conditional on their baseline covariates, and the extension of this concept in the longitudinal treatment setting. We demonstrate using simulated datasets and regression analysis that under violations of longitudinal positivity, typical associational estimates between treatment over time and the outcome of interest may be misleading depending on the data-generating structure. Finally, we explain how one may define “treatment strategies,” such as “treat with medication unless contraindicated,” to overcome the problems linked to time-varying eligibility. Finally, we show how contrasts between the expected potential outcomes under these strategies may be consistently estimated with inverse probability weighting methods. We provide R code for all the analyses described. 相似文献
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病历是指医务人员在医疗活动过程中形成的文字、符号、图表、影像、切片等资料的总和,是医疗损害诉讼、司法鉴定、医疗事故鉴定最重要的依据.随着电子信息技术的日新月异,电子病历应运而生.电子病历的出现及发展让医疗卫生系统信息化迈出重要一步,使医务工作者及患者体验到了信息高速公路带来的方便与快捷,然而,目前我国的电子病历的运用正处于初级起步阶段,对电子病历的法律认可度亟需进一步探讨. 相似文献
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Michael K. Rakotz Bernard G. Ewigman Menaka Sarav Ruth E. Ross Ari Robicsek Chad W. Konchak Thomas F. Gavagan David W. Baker David J. Hyman Kenneth P. Anderson Christopher M. Masi 《Annals of family medicine》2014,12(4):352-358