Can Observational Analyses of Routinely Collected Data Emulate Randomized Trials? Design and Feasibility of the Observational Patient Evidence for Regulatory Approval Science and Understanding Disease Project.

OBJECTIVES

The Observational Patient Evidence for Regulatory Approval Science and Understanding Disease (OPERAND) project examines whether real-world data (RWD) can be used to inform regulatory decision making.

METHODS

OPERAND evaluates whether observational analyses using RWD to emulate index trials can produce effect estimates similar to those of the trials and examines the impact of relaxing the eligibility criteria of the observational analyses to obtain samples that more closely match the real-world populations receiving the treatments. In OPERAND, 2 research teams independently attempt to emulate the ROCKET Atrial Fibrillation and LEAD-2 trials using OptumLabs data. This article describes the design of the project, summarizes the approaches of the 2 research teams, and presents feasibility results for 2 emulations using new-user designs.

RESULTS

There were differences in the teams' conceptualizations of the emulation, design decisions for cohort identification, and resulting RWD cohorts. These differences occurred even though both teams were guided by the same index trials and had access to the same source of RWD.

CONCLUSIONS

Reasonable alternative design and analysis approaches may be taken to answer the same research question, even when attempting to emulate the same index trial. Researcher decision making is an understudied and potentially important source of variability across RWD analyses.