Assessing the treatment effect in a randomized controlled trial with extensive non-adherence: the EVOLVE trial

Abstract

Intention-to-treat (ITT) analysis is widely used to establish efficacy in randomized clinical trials. However, in a long-term outcomes study where non-adherence to study drug is substantial, the on-treatment effect of the study drug may be underestimated using the ITT analysis. The analyses presented herein are from the EVOLVE trial, a double-blind, placebo-controlled, event-driven cardiovascular outcomes study conducted to assess whether a treatment regimen including cinacalcet compared with placebo in addition to other conventional therapies reduces the risk of mortality and major cardiovascular events in patients receiving hemodialysis with secondary hyperparathyroidism. Pre-specified sensitivity analyses were performed to assess the impact of non-adherence on the estimated effect of cinacalcet. These analyses included lag-censoring, inverse probability of censoring weights (IPCW), rank preserving structural failure time model (RPSFTM) and iterative parameter estimation (IPE). The relative hazard (cinacalcet versus placebo) of mortality and major cardiovascular events was 0.93 (95% confidence interval 0.85, 1.02) using the ITT analysis; 0.85 (0.76, 0.95) using lag-censoring analysis; 0.81 (0.70, 0.92) using IPCW; 0.85 (0.66, 1.04) using RPSFTM and 0.85 (0.75, 0.96) using IPE. These analyses, while not providing definitive evidence, suggest that the intervention may have an effect while subjects are receiving treatment. The ITT method remains the established method to evaluate efficacy of a new treatment; however, additional analyses should be considered to assess the on-treatment effect when substantial non-adherence to study drug is expected or observed.

Trial registration: ClinicalTrials.gov NCT00345839.

Keywords: intention-to-treat; inverse probability of censoring weights; iterative parameter estimation; lag-censoring; non-adherence; rank preserving structural failure time model.