Confounder adjustment in observational comparative effectiveness researches: (2) statistical adjustment approaches for unmeasured confounders
10.3760/cma.j.issn.0254-6450.2019.11.020
- VernacularTitle: 如何控制观察性疗效比较研究中的混杂因素：（二）未知或未测量混杂因素的统计学分析方法
- Author:
Lihong HUANG
1
;
Yongyue WEI
2
;
Feng CHEN
2
Author Information
1. Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai 200032, China
2. Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Publication Type:Journal Article
- Keywords:
Observational study of therapy efficacy comparison;
Real world study;
Unmeasured confounder;
Adjustment;
Statistical method
- From:
Chinese Journal of Epidemiology
2019;40(11):1450-1455
- CountryChina
- Language:Chinese
-
Abstract:
Observational study of therapy efficacy comparison has been widely conducted to provide the additional efficacy evidence to support randomized control study. Statistical adjustment for unmeasured confounders is a major challenge in observational study of therapy efficacy comparison. This paper summarizes and evaluates the relative statistical methods. Currently, the most commonly used methods include instrumental variable, difference-in-differences (DiD) model and prior event rate ratio (PERR) adjustment. The instrumental variable method skill fully escapes unmeasured confounders through model structure, but it is not easy to obtain satisfied instrumental variables. Both PERR and DiD require the data prior to exposure which are not always collected in observational studies. Unmeasured confounders could result in new requirements and pose new challenges for statistical methods, which needs further study and improvement.
