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Quantitative Bias Analysis for Single-Arm Trials With External Control Arms.

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Quantitative bias analysis (QBA) helps assess unmeasured confounding in external control arms (ECAs) for single-arm trials. QBA improved the accuracy of hazard ratio estimates in advanced non-small cell lung cancer analyses.

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Area of Science:

  • Oncology
  • Biostatistics
  • Health Services Research

Background:

  • External control arms (ECAs) from observational data are increasingly used in single-arm trials.
  • Unmeasured confounding poses a significant challenge to the validity of ECA-based analyses.
  • Quantitative bias analysis (QBA) offers a method to assess the potential impact of unmeasured confounding.

Purpose of the Study:

  • To evaluate the utility of QBA in exploring sensitivity to unmeasured confounding in non-randomized analyses using ECAs.
  • To compare hazard ratios from randomized trials with those derived from emulated ECA analyses.

Main Methods:

  • Emulated 15 treatment comparisons using randomized trial data and ECAs in advanced non-small cell lung cancer (aNSCLC).
  • Conducted a prespecified QBA after adjusting for measured confounders, synthesizing external evidence.
  • Compared hazard ratios for all-cause death between original trial control arms and ECA-derived analyses.

Main Results:

  • The difference in log hazard ratio estimates decreased with QBA adjustment (0.098) compared to unadjusted (0.247) and measured confounder-adjusted (0.139) analyses.
  • The ratio of hazard ratios was 1.17 after QBA, indicating a reduced bias compared to unadjusted (1.36) and measured confounder-adjusted (1.22) analyses.
  • QBA was feasible and informative, particularly when residual confounding was a major concern.

Conclusions:

  • QBA is a valuable tool for assessing bias in ECA analyses, especially in settings with expected residual confounding.
  • The findings support further investigation into QBA's application across diverse data sources and analytical scenarios.
  • Utilizing QBA can enhance the reliability of evidence generated from external control arms in clinical trials.