Gillespie, David ORCID: https://orcid.org/0000-0002-6934-2928, Farewell, Daniel ORCID: https://orcid.org/0000-0002-8871-1653, Barrett-Lee, Peter, Casbard, Angela ORCID: https://orcid.org/0000-0001-6241-3052, Hawthorne, Anthony Barney, Hurt, Christopher ORCID: https://orcid.org/0000-0003-1206-8355, Murray, Nick, Probert, Chris, Stenson, Rachel and Hood, Kerenza ORCID: https://orcid.org/0000-0002-5268-8631 2017. The use of randomisation-based efficacy estimators in non-inferiority trials. Trials 18 (1) , 117. 10.1186/s13063-017-1837-3 |
Preview |
PDF
- Published Version
Available under License Creative Commons Attribution. Download (909kB) | Preview |
Abstract
Background In a non-inferiority (NI) trial, analysis based on the intention-to-treat (ITT) principle is anti-conservative, so current guidelines recommend analysing on a per-protocol (PP) population in addition. However, PP analysis relies on the often implausible assumption of no confounders. Randomisation-based efficacy estimators (RBEEs) allow for treatment non-adherence while maintaining a comparison of randomised groups. Fischer et al. have developed an approach for estimating RBEEs in randomised trials with two active treatments, a common feature of NI trials. The aim of this paper was to demonstrate the use of RBEEs in NI trials using this approach, and to appraise the feasibility of these estimators as the primary analysis in NI trials. Methods Two NI trials were used. One comparing two different dosing regimens for the maintenance of remission in people with ulcerative colitis (CODA), and the other comparing an orally administered treatment to an intravenously administered treatment in preventing skeletal-related events in patients with bone metastases from breast cancer (ZICE). Variables that predicted adherence in each of the trial arms, and were also independent of outcome, were sought in each of the studies. Structural mean models (SMMs) were fitted that conditioned on these variables, and the point estimates and confidence intervals compared to that found in the corresponding ITT and PP analyses. Results In the CODA study, no variables were found that differentially predicted treatment adherence while remaining independent of outcome. The SMM, using standard methodology, moved the point estimate closer to 0 (no difference between arms) compared to the ITT and PP analyses, but the confidence interval was still within the NI margin, indicating that the conclusions drawn would remain the same. In the ZICE study, cognitive functioning as measured by the corresponding domain of the QLQ-C30, and use of chemotherapy at baseline were both differentially associated with adherence while remaining independent of outcome. However, while the SMM again moved the point estimate closer to 0, the confidence interval was wide, overlapping with any NI margin that could be justified. Conclusion Deriving RBEEs in NI trials with two active treatments can provide a randomisation-respecting estimate of treatment efficacy that accounts for treatment adherence, is straightforward to implement, but requires thorough planning during the design stage of the study to ensure that strong baseline predictors of treatment are captured. Extension of the approach to handle nonlinear outcome variables is also required. Trial registration The CODA study: ClinicalTrials.gov, identifier: NCT00708656. Registered on 8 April 2008. The ZICE study trial: ClinicalTrials.gov, identifier: NCT00326820. Registered on 16 May 2006.
Item Type: | Article |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Medicine |
Uncontrolled Keywords: | Treatment non-adherence; Non-inferiority; Efficacy; Intention-to-treat; Per-protocol; Structural; mean models |
Publisher: | BioMed Central |
ISSN: | 1745-6215 |
Date of First Compliant Deposit: | 29 June 2017 |
Date of Acceptance: | 13 February 2017 |
Last Modified: | 20 Jan 2024 14:49 |
URI: | https://orca.cardiff.ac.uk/id/eprint/101838 |
Citation Data
Cited 4 times in Scopus. View in Scopus. Powered By Scopus® Data
Actions (repository staff only)
Edit Item |