Related Experiment Video
Updated: Aug 27, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Augmenting randomized clinical trial data with historical control data: Precision medicine applications
Boris Freidlin1, Edward L Korn1
1Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD, USA.
Abstract:
As precision medicine becomes more precise, the sizes of the molecularly targeted subpopulations become increasingly smaller. This can make it challenging to conduct randomized clinical trials of the targeted therapies in a timely manner. To help with this problem of a small patient subpopulation, a study design that is frequently proposed is to conduct a small randomized clinical trial (RCT) with the intent of augmenting the RCT control arm data with historical data from a set of patients who have received the control treatment outside the RCT (historical control data). In particular, strategies have been developed that compare the treatment outcomes across the cohorts of patients treated with the standard (control) treatment to guide the use of the historical data in the analysis; this can lessen the potential well-known biases of using historical controls without any randomization. Using some simple examples and completed studies, we demonstrate in this commentary that these strategies are unlikely to be useful in precision medicine applications.
Insights
Augmenting small clinical trials with historical data is challenging in precision medicine. Strategies for using historical controls are unlikely to be effective for small, targeted patient groups.
Area of Science:
- Clinical Trials
- Precision Medicine
- Biostatistics
Background:
- Precision medicine yields smaller patient subpopulations, complicating randomized clinical trials (RCTs).
- Augmenting small RCTs with historical control data is a proposed solution for timely trials.
- Existing strategies aim to mitigate bias when incorporating external control data.
Purpose of the Study:
- To evaluate the utility of proposed strategies for using historical control data in precision medicine.
- To demonstrate the limitations of these strategies with simple examples and case studies.
Main Methods:
- Analysis of strategies for augmenting RCT control arms with historical data.
- Illustrative examples and review of completed studies.
Main Results:
- The evaluated strategies are unlikely to be effective for precision medicine applications.
- Challenges remain in leveraging historical data for small, targeted patient populations.
Conclusions:
- Current methods for incorporating historical controls are not well-suited for the unique challenges of precision medicine.
- Further research is needed to develop robust methods for small-sample clinical trials in targeted therapies.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Clinical Trials
There are four phases in a clinical trial. A phase one...
Analysis of Population Pharmacokinetic Data
Clinical Trials: Overview
Blinding
Hazard Ratio
For example, in a clinical trial...

