Incorporating Baseline Outcome Data in Individual Participant Data Meta-Analysis of Non-randomized Studies.

ABSTRACT:

Background

In non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC).

Methods

SUBMITTER: Syrogiannouli L 

PROVIDER: S-EPMC8902696 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature