Supplementing Single‐Arm Trials with External Control Arms—Evaluation of German Real‐World Data

As single-arm trials (SATs) are increasingly used in pharmaceutical research, the validity of such study designs needs to be critically assessed. We characterize the feasibility of supplementing SATs with real-world data (RWD)-derived external control arms by determining the proportion of SATs on breast cancer and amyotrophic lateral sclerosis (ALS) for which an external control arm based on RWD can be constructed. The main outcome measure is the number and percentage of trials for which all important eligibility criteria and at least one primary endpoint could be identified in one of five German RWD sources. We surveyed all SATs concerning breast cancer or ALS treatment registered in the European Union's clinical trial registers between 2004 and 2023. Ten out of 379 breast cancer SATs and 2 of 11 ALS SATs could feasibly be supplemented with RWD-derived external control arms, if all important eligibility criteria and a primary endpoint have to be identifiable in the RWD source. Ninety-three breast cancer trials had at least one outcome ascertainable in a RWD source, and 35 trials had all important eligibility criteria recorded in a RWD source. Nine ALS trials had at least one primary endpoint ascertainable in RWD sources, and 2 had all important eligibility criteria recorded in a RWD source. Our study shows that SATs with RWD-derived external control arms will rarely be suitable to establish treatment effects of medicines in the current setting for the investigated phenotypes and that SATs should be designed with limitations of the source of external controls in mind.

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Publication Details

Journal
Clinical Pharmacology & Therapeutics
Published
2025-04-16
DOI
https://doi.org/10.1002/cpt.3684
Citations
1
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
2.63
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article

Supplementing Single‐Arm Trials with External Control Arms—Evaluation of German Real‐World Data

Britta Haenisch, Martin Russek, Jonas Peltner
1 citations
Clinical Pharmacology & Therapeutics
Advanced Causal Inference Techniques
2.63
article

Supplementing Single‐Arm Trials with External Control Arms—Evaluation of German Real‐World Data

Britta Haenisch, Martin Russek, Jonas Peltner
article en
1 citations

Abstract

As single-arm trials (SATs) are increasingly used in pharmaceutical research, the validity of such study designs needs to be critically assessed. We characterize the feasibility of supplementing SATs with real-world data (RWD)-derived external control arms by determining the proportion of SATs on breast cancer and amyotrophic lateral sclerosis (ALS) for which an external control arm based on RWD can be constructed. The main outcome measure is the number and percentage of trials for which all important eligibility criteria and at least one primary endpoint could be identified in one of five German RWD sources. We surveyed all SATs concerning breast cancer or ALS treatment registered in the European Union's clinical trial registers between 2004 and 2023. Ten out of 379 breast cancer SATs and 2 of 11 ALS SATs could feasibly be supplemented with RWD-derived external control arms, if all important eligibility criteria and a primary endpoint have to be identifiable in the RWD source. Ninety-three breast cancer trials had at least one outcome ascertainable in a RWD source, and 35 trials had all important eligibility criteria recorded in a RWD source. Nine ALS trials had at least one primary endpoint ascertainable in RWD sources, and 2 had all important eligibility criteria recorded in a RWD source. Our study shows that SATs with RWD-derived external control arms will rarely be suitable to establish treatment effects of medicines in the current setting for the investigated phenotypes and that SATs should be designed with limitations of the source of external controls in mind.

Clinical Pharmacology & TherapeuticsVol. 118(6)
Federal Institute for Drugs and Medical Devices (DE), University of Bonn (DE), German Center for Neurodegenerative Diseases (DE)
Good health and well-being
Openalex Percentile: Top 13%
Advanced Causal Inference Techniques
2.63
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