Implementing Historical Controls in Oncology Trials

Olivier Collignon1,2, Anna Schritz1, Riccardo Spezia3

  • 1Luxembourg Institute of Health, Competence Center in Methodology and Statistics, Strassen, Luxembourg.

The Oncologist
|February 1, 2021
PubMed

Insights

Single-arm oncology trials using historical controls can speed drug development and reduce patient enrollment. Careful study selection, statistical analysis, and regulatory engagement are crucial for success in high unmet need cases.

Area of Science:

  • Oncology Drug Development
  • Clinical Trial Design

Background:

  • Oncology drug development is expanding beyond randomized trials to include single-arm trials for specific cancer subtypes.
  • These trials often utilize historical controls, presenting both opportunities and challenges.

Purpose of the Study:

  • To discuss the benefits and risks of using historical controls in single-arm oncology trials.
  • To outline regulatory and statistical considerations for this approach.

Main Methods:

  • Leveraging historical control data to potentially shorten development timelines and reduce patient enrollment.
  • Careful selection of past studies and prespecified statistical analyses accounting for heterogeneity.
  • Early engagement with regulatory bodies like the European Medicines Agency and U.S. Food and Drug Administration.

Main Results:

  • Historical controls can accelerate drug development and decrease patient numbers compared to randomized controlled trials.
  • This approach is most suitable for high unmet clinical need scenarios with well-characterized disease and objective endpoints.
  • Regulatory agencies have approved medicines based on non-randomized experiments, though evidentiary packages may be less comprehensive.

Conclusions:

  • Incorporating historical data in single-arm oncology trials offers potential benefits but requires meticulous planning.
  • Key elements for success include careful data selection, robust statistical methods addressing between-study variation, and proactive regulatory consultation.
  • This paradigm is best applied in situations of high unmet need or challenging experimental conditions where disease trajectory and endpoints are clearly defined.

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