Enriching single-arm clinical trials with external controls: possibilities and pitfalls
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Updated: Aug 16, 2025

A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition
Published on: September 20, 2019
Jérôme Lambert1,2, Etienne Lengliné3, Raphaël Porcher4,5
1Biostatistical Department, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris, Paris, France.
Abstract:
For the past decade, it has become commonplace to provide rapid answers and early patient access to innovative treatments in the absence of randomized clinical trials (RCT), with benefits estimated from single-arm trials. This trend is important in oncology, notably when assessing new targeted therapies. Some of those uncontrolled trials further include an external/synthetic control group as an innovative way to provide an indirect comparison with a pertinent control group. We aimed to provide some guidelines as a comprehensive tool for (1) the critical appraisal of those comparisons or (2) for performing a single-arm trial. We used the example of ciltacabtagene autoleucel for the treatment of adult patients with relapsed or refractory multiple myeloma after 3 or more treatment lines as an illustrative example. We propose a 3-step guidance. The first step includes the definition of an estimand, which encompasses the treatment effect and the targeted population (whole population or restricted to single-arm trial or external controls), reflecting a clinical question. The second step relies on the adequate selection of external controls from previous RCTs or real-world data from patient cohorts, registries, or electronic patient files. The third step consists of choosing the statistical approach targeting the treatment effect defined above and depends on the available data (individual-level data or aggregated external data). The validity of the treatment effect derived from indirect comparisons heavily depends on careful methodological considerations included in the proposed 3-step procedure. Because the level of evidence of a well-conducted RCT cannot be guaranteed, the evaluation is more important than in standard settings.
Insights
Estimating treatment benefits from single-arm trials is common in oncology. This study offers a 3-step guideline for critically appraising indirect comparisons using external controls, enhancing the reliability of new targeted therapies.
Area of Science:
- Oncology
- Clinical Trials
- Biostatistics
Background:
- Single-arm trials are increasingly used to assess innovative oncology treatments without randomized clinical trials (RCTs).
- External or synthetic control groups are sometimes incorporated into uncontrolled trials for indirect comparisons.
- Estimating treatment benefits in the absence of RCTs requires careful methodological consideration.
Purpose of the Study:
- To provide guidelines for the critical appraisal and performance of single-arm trials with external controls.
- To offer a comprehensive tool for evaluating indirect treatment comparisons in oncology.
- To illustrate a proposed 3-step guidance using ciltacabtagene autoleucel for multiple myeloma.
Main Methods:
- A 3-step guidance procedure is proposed for performing and appraising single-arm trials with external controls.
- Step 1: Define an estimand, specifying the treatment effect and target population.
- Step 2: Select appropriate external controls from RCTs or real-world data.
- Step 3: Choose a statistical approach based on data availability (individual or aggregated).
Main Results:
- The proposed 3-step guidance facilitates the definition of estimands, selection of external controls, and choice of statistical methods.
- Validity of treatment effects from indirect comparisons hinges on methodological rigor.
- Careful evaluation is crucial, especially when the level of evidence from RCTs is uncertain.
Conclusions:
- The 3-step guidance provides a framework for robust indirect treatment comparisons in oncology.
- Adherence to methodological considerations ensures the validity of treatment effect estimations.
- This approach supports evidence-based decision-making for early access to innovative therapies.
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