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[Methods for controlling time-varying confounding in pharmaco-epidemiological studies: a systematic reveiw].
Zhao, H Y; Zeng, X Y; Liu, F Q; Chen, S Y; Zhan, S Y.
Afiliação
  • Zhao HY; Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China.
  • Zeng XY; Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China.
  • Liu FQ; Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China.
  • Chen SY; Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China.
  • Zhan SY; Department of Epidemiology and Biostatistics/China Center for Health Development Studies, School of Public Health Peking University, Beijing 100191, China Center for Intelligent Public Health, Institute for Artificial Intelligence, Peking University, Beijing 100871, China;Coressponding author: Zhan
Zhonghua Liu Xing Bing Xue Za Zhi ; 42(12): 2179-2187, 2021 Dec 10.
Article em Zh | MEDLINE | ID: mdl-34954984
Objective: To systematically review the application of methods for controlling time-varying confounding in pharmaco-epidemiological studies. Methods: PubMed, Embase, CNKI, and Wanfang were searched for pharmaco-epidemiological studies involving time-varying confounding on June 15th, 2020. The basic characteristics, drug exposure and outcome, time-varying confounders and the application of methods to control these confounders were analyzed. Results: A total of 298 articles were included. An increasing trend was observed in numbers of studies dealing with time-varying confounding in pharmaco-epidemiological studies in recent years. A total of 106 (35.6%) studies involved the safety or effectiveness of medication use in HIV/AIDS patients and 92 of them involved antiretroviral drugs. The most common outcome was mortality, while the most commonly concerned time-dependent confounders were laboratory examination results (179, 60.1%), comorbidities (136, 45.6%), and co-used medications (108, 36.2%). Marginal structure model (MSM) and inverse probability of treatment weighting (IPTW) were the most commonly used methods to control time-varying confounding factors (244, 81.9%). Compared with the results after properly controlling time-varying confounding, traditional methods adjusting only baseline confounders resulted in substantial bias (median 18.2%, interquartile range, 7.4%-40.8%). As for basic assumptions needed for causal methods controlling time-varying confounding, 28.9% and 64.8% of the included studies examined or discussed the assumptions of positivity and no unmeasured confounders, respectively. Conclusions: At present, most of the fields of drug therapy for chronic diseases still pay insufficient attention to time-varying confoundings. Information collected in routine medical practice, such as laboratory tests, comorbidities, and co-used drugs, was the most commonly concerned time-varying confounder. MSM and IPTW were the most commonly applied methods for dealing with time-varying confounding.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Confusão Epidemiológicos Tipo de estudo: Observational_studies / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: Zh Revista: Zhonghua Liu Xing Bing Xue Za Zhi Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fatores de Confusão Epidemiológicos Tipo de estudo: Observational_studies / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: Zh Revista: Zhonghua Liu Xing Bing Xue Za Zhi Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China