Evaluation of biases present in the cohort multiple randomised controlled trial design: a simulation study

Abstract

BackgroundThe cohort multiple randomised controlled trial (cmRCT) design provides an opportunity to incorporate the benefits of randomisation within clinical practice; thus reducing costs, integrating electronic healthcare records, and improving external validity. This study aims to address a key concern of the cmRCT design: refusal to treatment is only present in the intervention arm, and this may lead to bias and reduce statistical power.MethodsWe used simulation studies to assess the effect of this refusal, both random and related to event risk, on bias of the effect estimator and statistical power. A series of simulations were undertaken that represent a cmRCT trial with time-to-event endpoint. Intention-to-treat (ITT), per protocol (PP), and instrumental variable (IV) analysis methods, two stage predictor substitution and two stage residual inclusion, were compared for various refusal scenarios.ResultsWe found the IV methods provide a less biased estimator for the causal effect when refusal is present in the intervention arm, with the two stage residual inclusion method performing best with regards to minimum bias and sufficient power. We demonstrate that sample sizes should be adapted based on expected and actual refusal rates in order to be sufficiently powered for IV analysis.ConclusionWe recommend running both an IV and ITT analyses in an individually randomised cmRCT as it is expected that the effect size of interest, or the effect we would observe in clinical practice, would lie somewhere between that estimated with ITT and IV analyses. The optimum (in terms of bias and power) instrumental variable method was the two stage residual inclusion method. We recommend using adaptive power calculations, updating them as refusal rates are collected in the trial recruitment phase in order to be sufficiently powered for IV analysis.

The Trials within Cohorts design faced methodological advantages and disadvantages in the exercise oncology setting

“…Before the start of the study, a required sample size of 166 patients was estimated based on an expected acceptance rate of 70% in the intervention group, a clinically relevant 10-point difference in quality of life, a power of 80%, and an alpha of 0.05 [12]. After the recruitment of 152 patients, the actual acceptance rate was lower than expected (i.e., 55% instead of 70%) and the sample size was updated, as recommended by Candlish et al [15], to 260 patients. Noticeably, this sample size modification was not based on interim analysis of the trial outcome.…”

“…It took 18 months to identify and randomize these 166 patients. As recommended by Candlish et al [15], we updated the sample size after the recruitment of 152 patients because the actual acceptance rate (55%) of the intervention deviated from the expected rate (70%). Twelve additional months were needed to reach the updated sample size (n 5 260).…”

Erratum to: Evaluation of biases present in the cohort multiple randomised controlled trial design: a simulation study

“…After publication of the original article [1], it came to the authors’ attention that there was an error affecting the References. The published Reference 14 [2] is incorrect, and should have cited a different article by Pate et al [3].…”

Factors associated with patient-reported likelihood of using online self-care interventions: a Scleroderma Patient-centered Intervention Network (SPIN) cohort study

“…A potential problem with this approach is that a substantial number of patients offered an intervention that is undergoing testing may not accept it, since they did not enrol in the cohort with any expectation that it would be offered to them. This would dilute intervention effects estimated on an intention-to-treat basis, potentially substantially if the rate of accepted offers is low, as the intervention arm then includes a large proportion of patients receiving care as usual 23. A possible solution that has been suggested to reduce non-acceptance of intervention offers is to present cohort patients with a list of possible interventions as part of regular cohort data collection and ask if they would agree to use them if offered 4.…”