Transporting trial results to synthetic real-world populations in order to estimate real-world effectiveness of newly marketed medicines.

ABSTRACT:

Introduction

Real-world effectiveness of a new treatment is relevant information for patients, healthcare professionals and payers, especially when patients encountered in routine clinical care differ significantly from those recruited in the randomised controlled trials (RCTs) that led to approval. However, obtaining effect estimates can be challenging when a new drug has only recently been marketed and real-world data (RWD) are not yet available. For new breast cancer (BC) therapies, we illustrate how RCT inferences can be transported to a target population and how a synthetic population can be generated to mimic a target population for which no RWD is yet available.

Methods and analysis

In our framework, we defined the data-generating process for the RCT population and th

SUBMITTER: Leiva-Escobar I 

PROVIDER: S-EPMC12306361 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature