# Target trial emulation in oncology: current use and future directions

## TL;DR

This paper reviews how target trial emulation is currently used in oncology and identifies challenges and potential solutions for improving its reliability and application.

## Contribution

The study systematically reviews 90 TTE studies in oncology, highlighting biases and proposing solutions to enhance their use.

## Key findings

- Registry databases and overall survival are commonly used in TTE studies for cancer treatment.
- Immortal time bias and prevalent user bias are significant issues in over half of the TTE cases.
- Only 42.9% of TTE trials aligned with preexisting RCTs in both statistical and estimate agreement.

## Abstract

Target trial emulation (TTE) has demonstrated popularity because of its ability to improve the reliability of causal inference from observational data. Nevertheless, knowledge about the current use, potential challenges, and insights of target trials in oncology is scarce. A total of 90 TTE studies in cancer areas were identified through systematic reviews in PubMed and Embase. Among the 54 applications in cancer treatment, registry databases (44.4%) and overall survival (OS, 63.0%) were predominantly used as data sources and primary endpoints, respectively. Approximately 30 (55.6%) of the included TTE cases were associated with immortal time bias, and 21 (38.9%) were associated with prevalent user bias. Among the 21 trials from 13 studies that aimed to calibrate the results from preexisting randomized controlled trials (RCTs), only 42.9% met both statistical agreement and estimate agreement. The availability of fit-for-purpose data sources and uncertainty about result concordance were the main hurdles limiting the quantity and quality of TTE in oncology areas. Promoting regulatory acceptance by initiating special projects could be crucial for the expanded application of real-world data (RWD) using TTE. Potential solutions, such as the integration of electronic medical records at the regional or country level, linkage with insurance claims databases, the modernization of eligibility criteria, the use of OS as the primary endpoint, and other best practices, were recommended for improving the feasibility and quality of oncology TTE.

The online version contains supplementary material available at 10.1186/s40779-026-00685-9.