Summary What is known and objective The application of biologics to treat inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is well established. Our aim was to characterize the most recent five years of data on rates of adherence, persistence, switching and dose escalations with biologics used to treat IBD in the United States. Methods We systematically reviewed electronic databases MEDLINE, MEDLINE In‐Process, EMBASE and Cochrane Library for 2012‐2017 as well as conference proceedings for 2016‐2017 published in English. Results and discussion Of 449 records identified, 41 met all screening criteria. Published studies varied greatly in methodology, data sources, population studied, follow‐up time and endpoint definitions, preventing meaningful comparisons across studies. Based on studies using a medication possession rate threshold of <80% or <86%, 38%‐77% of patients were found non‐adherent to biologics. Discontinuation within the first 3 months occurred in 0%‐25% of patients in six studies; 7%‐65% discontinued by 12 months in 13 studies. Among all patients who initiated an index biologic, the switch rate to another biologic ranged from 4.5% to 20% in 6 studies. Dose escalations were reported in only four studies; 8%‐35% of patients had their dose escalated within the first year of therapy. What is new and conclusion This study demonstrates variability in study design and methodology to assess adherence, persistence, switching and dose escalation with biologics among adults with IBD in the United States. Our findings suggest that real‐world biologic use may be suboptimal and indicate new therapies and/or additional patient support may be needed.

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This paper introduces a method which conditions on the number of events that occur in the control group to determine rejection regions and power for comparative Poisson trials with multiple experimental treatment arms that are each compared to one control arm. This leads to the negative multinomial as the statistical distribution used for testing. For one experimental treatment and one control with curtailed sampling, this is equivalent to Gail's (1974) approach. We provide formulas to calculate exact one‐sided overall Type I error and pointwise power for tests of treatment superiority and inferiority (vs the control). Tables of trial design parameters for combinations of one‐sided overall Type I error = 0.05, 0.01 and pointwise power = 0.90, 0.80 are provided. Curtailment approaches are presented to stop follow‐up of experimental treatment arms or to stop the study entirely once the final outcomes for each arm are known.

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e18302 Background: Findings from few studies examining preferences for MM treatment are limited in application, as they are largely missing the voices of patients (PTs). The present qualitative study elucidates PT preferences, the perceived trade-offs they are willing to make, and how these may differ by line of therapy (LOT). Methods: Semi-structured phone interviews were conducted with MM PTs (front-line [FL] = 11, early relapse 1- 2 prior-lines [1/2PL] = 10) recruited via purposive sampling from targeted panels and PT groups, April-May 2018. A discussion guide was developed and a trained interviewer conducted 1-hour interviews on the diversity and valence of factors influencing how PTs evaluate potential regimens and how preferences vary by experience (i.e., LOT). Interviews were audio recorded and transcribed, responses coded, and content analysis performed to identify key themes emerging from textual data. Results: The sample was 42% male, mean age 64 years, with mean 58 months since diagnosis. Three key themes were identified. Firstly, treatment decision-making, revealed that trust in one’s health care provider (HCP) was a potent influence on treatment choice. Whereas FL PTs reported often only one option is offered and rely on HCP to make decisions, 1/2PL PTs consider other sources of information and engage in more shared decision-making. Secondly, expectations about treatment, illustrated that HCPs discuss important factors, e.g., efficacy and tolerability, in general terms with FL PTs and provide more details to 1/2PL PTs. Lastly, “ top of mind” factors that influenced treatment decisions, effectiveness, followed by side effects, emerged as the greatest influences on preference, although 1/2PL PTs reported less concern with side effects than FL PTs. Relatedly, quality of life was described as salient; the lived experience of treatment was often mentioned within the context of side effects. Conclusions: The way PTs construct, prioritize, and communicate about treatment when assessing “benefit-risk” is a dynamic process, based on where PTs are in their treatment journey. By examining treatment preferences grounded in PTs’ lived and changing experiences with MM, the findings may contribute to better PT-HCP engagement through treatment decision-making and improve clinical care.