P0541 Placebo rates in randomised clinical trials of Ulcerative Colitis: An individual patient data meta-analysis

Abstract Background Information on placebo rates is important for designing clinical trials. We aimed to assess placebo rates and associated factors using individual patient data from multiple randomised clinical trials in ulcerative colitis. Methods We conducted a meta-analysis of individual participant-level data from nine randomised trials using Vivli and Yale University Open Data Access data-sharing platforms. Phase 2 and 3 placebo-controlled randomised clinical trials of advanced biologic therapies in adults with moderate-to-severe active ulcerative colitis published since 2010 were included. Pooled placebo rates and 95% CIs were estimated using one-stage and two-stage meta-analytical approach. Significant patient-level factors (P<0.05) associated with placebo rates were identified using regression analyses. The pre-specified primary outcomes were placebo clinical response and remission. Results Outcome data were available for 1,703 patients from nine studies (three induction-only, one maintenance-only, and five including both phases). For induction trials, overall placebo response and remission rates were 33% (95% CI 29-38%) and 9% (95% CI 7-11%), respectively (Figure). Overall placebo response and remission rates in maintenance trials were 28% (95% CI 17%-41%) and 14% (95% CI 9-20%), respectively (Figure). A lower body mass index reduced odds of placebo response and remission, while higher baseline albumin levels and left-sided UC (compared to extensive) increased the odds of these outcomes. A one-point increase in the Mayo Clinic Score and adapted Mayo Clinic Score was associated with a 26% and 27% reduction in the odds of clinical remission. For induction trials, prior exposure to biologics or tumour necrosis factor antagonist therapy was associated with lower odds of both response and remission. Multi-centre trials have lower placebo effect than single-centre trials. Conclusion These results will enable future trials that include placebo to incorporate design elements that enable reduction of placebo rates as well as a precise benchmark for expected rates in clinical trials that do not include placebo.