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The importance of considering competing treatment affecting prognosis in the evaluation of therapy in trials: the example of renal transplantation in hemodialysis trials

Abstract : Background. During the follow-up in a randomized controlled trial (RCT), participants may receive additional (non-randomly allocated) treatment that affects the outcome. Typically such additional treatment is not taken into account in evaluation of the results. Two pivotal trials of the effects of hemodiafiltration (HDF) versus hemodialysis (HD) on mortality in patients with end-stage renal disease reported differing results. We set out to evaluate to what extent methods to take other treatments (i.e. renal transplantation) into account may explain the difference in findings between RCTs. This is illustrated using a clinical example of two RCTs estimating the effect of HDF versus HD on mortality. Methods. Using individual patient data from the Estudio de Supervivencia de Hemodiafiltración On-Line (ESHOL; n =  902) and The Dutch CONvective TRAnsport STudy (CONTRAST; n = 714) trials, five methods for estimating the effect of HDF versus HD on all-cause mortality were compared: intention-to-treat (ITT) analysis (i.e. not taking renal transplantation into account), per protocol exclusion (PPexcl; exclusion of patients who receive transplantation), PPcens (censoring patients at the time of transplantation), transplantation-adjusted (TA) analysis and an extension of the TA analysis (TAext) with additional adjustment for variables related to both the risk of receiving a transplant and the risk of an outcome (transplantation–outcome confounders). Cox proportional hazards models were applied. Results. Unadjusted ITT analysis of all-cause mortality led to differing results between CONTRAST and ESHOL: hazard ratio (HR) 0.95 (95% CI 0.75–1.20) and HR 0.76 (95% CI 0.59–0.97), respectively; difference between 5 and 24% risk reductions. Similar differences between the two trials were observed for the other unadjusted analytical methods (PPcens, PPexcl, TA) The HRs of HDF versus HD treatment became more similar after adding transplantation as a time-varying covariate and including transplantation–outcome confounders: HR 0.89 (95% CI 0.69–1.13) in CONTRAST and HR 0.80 (95% CI 0.62–1.02) in ESHOL. Conclusions. The apparent differences in estimated treatment effects between two dialysis trials were to a large extent attributable to differences in applied methodology for taking renal transplantation into account in their final analyses. Our results exemplify the necessity of careful consideration of the treatment effect of interest when estimating the therapeutic effect in RCTs in which participants may receive additional treatments.
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Soumis le : mercredi 8 avril 2020 - 16:16:30
Dernière modification le : vendredi 15 mai 2020 - 12:22:09

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C. Marijn Hazelbag, Peter Peters, Peter Blankestijn, Michiel Bots, Bernard Canaud, et al.. The importance of considering competing treatment affecting prognosis in the evaluation of therapy in trials: the example of renal transplantation in hemodialysis trials. Nephrology Dialysis Transplantation, Oxford University Press (OUP), 2017, 32 (Suppl 2), pp.ii31-ii39. ⟨10.1093/ndt/gfw458⟩. ⟨hal-01832341⟩

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