Reporting, handling, and interpretation of time‐varying drug treatments in observational studies using routinely collected healthcare data

Author:

Wang Wen123,He Qiao123,Xu Jiayue123ORCID,Liu Mei123,Wang Mingqi123,Li Qianrui123,Zhang Xia123,Huang Yunxiang123,Zhang Yuanjin123,Li Ling123,Zou Kang123,Li Guowei45,Lu Kevin6,Gao Pei7,Chen Feng8,Guo Jeff Jianfei9,Yang Min1011,Sun Xin123ORCID

Affiliation:

1. Institute of Integrated Traditional Chinese and Western Medicine Chinese Evidence‐based Medicine Center and Cochrane China Center West China Hospital Sichuan University Chengdu Sichuan China

2. National Medical Products Administration Key Laboratory for Real World Data Research and Evaluation in Hainan Chengdu Sichuan China

3. Sichuan Center of Technology Innovation for Real World Data Chengdu Sichuan China

4. Department of Health Research Methods Evidence and Impact McMaster University Hamilton Ontario Canada

5. Center for Clinical Epidemiology and Methodology Guangdong Second Provincial General Hospital Guangzhou Guangdong China

6. South Carolina College of Pharmacy University of South Carolina Columbia Columbia South Carolina USA

7. Department of Epidemiology and Biostatistics Peking University Health Science Center Beijing China

8. Department of Biostatistics Center for Global Health School of Public Health Nanjing Medical University Nanjing Jiangsu China

9. College of Pharmacy University of Cincinnati Cincinnati Ohio USA

10. Department of Epidemiology and Biostatistics West China School of Public Health Sichuan University Chengdu Sichuan China

11. Faculty of Health Design and Art Swinburne Technology University Victory Australia

Abstract

AbstractBackgroundTime‐varying drug treatments are common in studies using routinely collected health data (RCD) for assessing treatment effects. This study aimed to examine how these studies reported, handled, and interpreted time‐varying drug treatments.MethodsA systematic search was conducted on PubMed from 2018 to 2020. Eligible studies were those used RCD to explore drug treatment effects. We summarized the reporting characteristics and methods employed for handling time‐varying treatments. Logistic regressions were performed to investigate the association between study characteristics and the reporting of time‐varying treatments.ResultsTwo hundred and fifty‐six studies were included, and 225 (87.9%) studies involved time‐varying treatments. Of these, 24 (10.7%) reported the proportion of time‐varying treatments and 105 (46.7%) reported methods used to handle time‐varying treatments. Multivariable logistic regression showed that medical studies, prespecified protocol, and involvement of methodologists were associated with a higher likelihood of reporting the methods applied to handle time‐varying treatments. Among the 105 studies that reported methods, as‐treated analyses were the most commonly used analysis sets, which were employed in 73.9%, 75.3% and 88.2% of studies that reported approaches for treatment discontinuation, treatment switching and treatment add‐on. Among the 225 studies involved time‐varying treatments, 27 (12.0%) acknowledged the potential bias introduced by treatment change, of which 14 (51.9%) suggested that potential biases may impact acceptance or rejection of the null hypothesis.ConclusionsAmong observational studies using RCD, the underreporting about the presence and methods for handling time‐varying treatments was largely common. The potential biases due to time‐varying treatments have frequently been disregarded. Collaborative endeavors are strongly needed to enhance the prevailing practices.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Health Policy,General Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3