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Single-arm Trials with Historical Controls: Study Designs to Avoid Time-related Biases
1From the Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital, and Departments of Epidemiology, Biostatistics, and Medicine, McGill University, Montreal, Canada.
Single-arm trials with external controls can be biased by time. Careful consideration of calendar time and cohort entry is crucial for accurate treatment comparisons in oncology drug development.
Area of Science:
- Clinical Trials
- Oncology
- Biostatistics
Background:
- Single-arm trials with external historical controls are increasingly used by regulatory agencies for drug approval, especially for rare diseases or specific indications.
- This trial design is common in oncology for assessing novel therapeutics.
- However, time-related biases can arise when comparing outcomes over time with external controls.
Purpose of the Study:
- To identify and illustrate potential time-related biases in single-arm trials using external historical controls.
- To demonstrate how these biases can affect treatment effectiveness estimates.
- To emphasize the importance of understanding these biases for valid drug approval.
Main Methods:
- Described two potential biases: calendar time differences and choice of time zero (cohort entry).
- Utilized simulated data emulating a blinatumomab trial for relapsed/refractory acute lymphoblastic leukemia (ALL) mortality.
- Compared blinatumomab arm (2010-2014) with historical controls (1990-2013).
Main Results:
- Non-concurrent calendar times led to apparent survival differences, with median survival of 6.1 months (blinatumomab) vs. 3.3 months (controls), which varied significantly over time.
- Selection bias due to defining control cohort entry by the latest salvage treatment altered the hazard ratio from 0.56 to 0.98.
- Adjusting cohort entry to matched salvage treatment improved the comparison accuracy.
Conclusions:
- Single-arm trials with external controls require careful management of time-related biases.
- Understanding and mitigating biases from calendar time and cohort selection is essential for generating valid evidence for regulatory drug approval.
- Accurate assessment of promising treatments in oncology relies on robust trial designs that account for temporal effects.
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