Adaptive propensity score procedure improves matching in prospective observational trials

BMC Med Res Methodol. 2019 Jul 16;19(1):150. doi: 10.1186/s12874-019-0763-3.

Abstract

Background: Randomized controlled trials are the gold-standard for clinical trials. However, randomization is not always feasible. In this article we propose a prospective and adaptive matched case-control trial design assuming that a control group already exists.

Methods: We propose and discuss an interim analysis step to estimate the matching rate using a resampling step followed by a sample size recalculation. The sample size recalculation is based on the observed mean resampling matching rate. We applied our approach in a simulation study and to a real data set to evaluate the characteristics of the proposed design and to compare the results to a naive approach.

Results: The proposed design achieves at least 10% higher matching rate than the naive approach at final analysis, thus providing a better estimation of the true matching rate. A good choice for the interim analysis seems to be a fraction of around [Formula: see text] to [Formula: see text] of the control patients.

Conclusion: The proposed resampling step in a prospective matched case-control trial design leads to an improved estimate of the final matching rate and, thus, to a gain in power of the approach due to sensible sample size recalculation.

Keywords: Adaptive design; Clinical Trials; Matched cohort; Prospective matching; Sample size recalculation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain Ischemia / therapy
  • Case-Control Studies
  • Conscious Sedation
  • Humans
  • Models, Statistical*
  • Observational Studies as Topic / statistics & numerical data*
  • Propensity Score*
  • Prospective Studies
  • Research Design*
  • Sample Size
  • Stroke / therapy