BMC Medical Research Methodology (Oct 2024)

Application of the estimand framework for an emulated trial using reference based multiple imputation to investigate informative censoring

  • A. Atkinson,
  • M. Zwahlen,
  • S. De Wit,
  • H. Furrer,
  • J. R. Carpenter

DOI
https://doi.org/10.1186/s12874-024-02364-6
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 6

Abstract

Read online

Abstract Background The ICH E9 (R1) addendum on Estimands and Sensitivity analysis in Clinical trials proposes a framework for the design and analysis of clinical trials aimed at improving clarity around the definition of the targeted treatment effect (the estimand) of a study. Methods We adopt the estimand framework in the context of a study using “trial emulation” to estimate the risk of pneumocystis pneumonia, an opportunistic disease contracted by people living with HIV and AIDS having a weakened immune system, when considering two antibiotic treatment regimes for stopping antibiotic prophylaxis treatment against this disease. A “while on treatment” strategy has been implemented for post-randomisation (intercurrent) events. We then perform a sensitivity analysis using reference based multiple imputation to model a scenario in which patients lost to follow-up stop taking prophylaxis. Results The primary analysis indicated a protective effect for the new regime which used viral suppression as prophylaxis stopping criteria (hazard ratio (HR) 0.78, 95% confidence interval [0.69, 0.89], p < 0.001). For the sensitivity analysis, when we apply the “jump to off prophylaxis” approach, the hazard ratio is almost the same compared to that from the primary analysis (HR 0.80 [0.69, 0.95], p = 0.009). The sensitivity analysis confirmed that the new regime exhibits a clear improvement over the existing guidelines for PcP prophylaxis when those lost to follow-up “jump to off prophylaxis”. Conclusions Our application using reference based multiple imputation demonstrates the method’s flexibility and simplicity for sensitivity analyses in the context of the estimand framework for (emulated) trials.

Keywords