Wen Wang, Qiao He, Jiayue Xu, Mei Liu, Mingqi Wang, Qianrui Li, Xia Zhang, Yunxiang Huang, Yuanjin Zhang, Ling Li, Kang Zou, Guowei Li, Kevin Lu, Pei Gao, Feng Chen, Jeff Jianfei Guo, Min Yang, Xin Sun
{"title":"利用日常收集的医疗保健数据，在观察性研究中报告、处理和解释随时间变化的药物治疗方法","authors":"Wen Wang, Qiao He, Jiayue Xu, Mei Liu, Mingqi Wang, Qianrui Li, Xia Zhang, Yunxiang Huang, Yuanjin Zhang, Ling Li, Kang Zou, Guowei Li, Kevin Lu, Pei Gao, Feng Chen, Jeff Jianfei Guo, Min Yang, Xin Sun","doi":"10.1111/jebm.12577","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Time-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.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>A 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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Two 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.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Among 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.</p>\n </section>\n </div>","PeriodicalId":16090,"journal":{"name":"Journal of Evidence‐Based Medicine","volume":"16 4","pages":"495-504"},"PeriodicalIF":3.6000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reporting, handling, and interpretation of time-varying drug treatments in observational studies using routinely collected healthcare data\",\"authors\":\"Wen Wang, Qiao He, Jiayue Xu, Mei Liu, Mingqi Wang, Qianrui Li, Xia Zhang, Yunxiang Huang, Yuanjin Zhang, Ling Li, Kang Zou, Guowei Li, Kevin Lu, Pei Gao, Feng Chen, Jeff Jianfei Guo, Min Yang, Xin Sun\",\"doi\":\"10.1111/jebm.12577\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Time-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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>A 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Two 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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>Among 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.</p>\\n </section>\\n </div>\",\"PeriodicalId\":16090,\"journal\":{\"name\":\"Journal of Evidence‐Based Medicine\",\"volume\":\"16 4\",\"pages\":\"495-504\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2023-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Evidence‐Based Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jebm.12577\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Evidence‐Based Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jebm.12577","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Reporting, handling, and interpretation of time-varying drug treatments in observational studies using routinely collected healthcare data
Background
Time-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.
Methods
A 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.
Results
Two 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.
Conclusions
Among 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.
期刊介绍：
The Journal of Evidence-Based Medicine (EMB) is an esteemed international healthcare and medical decision-making journal, dedicated to publishing groundbreaking research outcomes in evidence-based decision-making, research, practice, and education. Serving as the official English-language journal of the Cochrane China Centre and West China Hospital of Sichuan University, we eagerly welcome editorials, commentaries, and systematic reviews encompassing various topics such as clinical trials, policy, drug and patient safety, education, and knowledge translation.
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