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Exploration of a Potential Desirability of Outcome Ranking Endpoint for Complicated Intra-Abdominal Infections Using
Tori Kinamon1,2,3, Ramya Gopinath1, Ursula Waack1
1Center for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, MD, USA.
Insights
Desirability of outcome ranking (DOOR) was adapted for complicated intra-abdominal infection (cIAI) trials. This novel endpoint, based on patient outcomes, showed similar treatment arm results, aiding clinical trial design.
Area of Science:
- Clinical trial design
- Infectious disease research
- Medical statistics
Background:
- Desirability of Outcome Ranking (DOOR) offers a novel approach to clinical trial design by integrating safety and efficacy into an ordinal ranking system.
- This study focused on developing and applying a disease-specific DOOR endpoint for registrational trials in complicated intra-abdominal infection (cIAI).
Purpose of the Study:
- To derive and evaluate a cIAI-specific DOOR endpoint for assessing overall participant outcomes in clinical trials.
- To characterize the clinical experiences of participants in cIAI trials using a data-driven approach.
Main Methods:
- An a priori DOOR prototype was applied to patient-level data from 9 phase 3 cIAI trials submitted to the FDA (2005-2019).
- A cIAI-specific DOOR endpoint was derived based on clinically meaningful events, and then applied to estimate treatment arm outcome probabilities.
- Component analyses were used to assess the risk-benefit profiles of study treatments versus comparators.
Main Results:
- Key findings included the proportion of participants requiring additional surgeries, the diversity of infectious complications, and the association between worse outcomes and increased complications/procedures.
- DOOR distributions between treatment arms were similar across all trials, with DOOR probability estimates ranging from 47.4% to 50.3% and no significant differences.
- Component analyses provided insights into the risk-benefit assessments for study treatments compared to their respective comparators.
Conclusions:
- A DOOR endpoint for cIAI trials was designed and evaluated to better define the overall clinical experience of participants.
- The study suggests that similar data-driven methodologies can be employed to develop DOOR endpoints for other infectious diseases.
Background:
Desirability of outcome ranking (DOOR) is a novel approach to clinical trial design that incorporates safety and efficacy assessments into an ordinal ranking system to evaluate overall outcomes of clinical trial participants. Here, we derived and applied a disease-specific DOOR endpoint to registrational trials for complicated intra-abdominal infection (cIAI).
Methods:
Initially, we applied an a priori DOOR prototype to electronic patient-level data from 9 phase 3 noninferiority trials for cIAI submitted to the US Food and Drug Administration between 2005 and 2019. We derived a cIAI-specific DOOR endpoint based on clinically meaningful events that trial participants experienced. Next, we applied the cIAI-specific DOOR endpoint to the same datasets and, for each trial, estimated the probability that a participant assigned to the study treatment would have a more desirable DOOR or component outcome than if assigned to the comparator.
Results:
Three key findings informed the cIAI-specific DOOR endpoint: (1) a significant proportion of participants underwent additional surgical procedures related to their baseline infection; (2) infectious complications of cIAI were diverse; and (3) participants with worse outcomes experienced more infectious complications, more serious adverse events, and underwent more procedures. DOOR distributions between treatment arms were similar in all trials. DOOR probability estimates ranged from 47.4% to 50.3% and were not significantly different. Component analyses depicted risk-benefit assessments of study treatment versus comparator.
Conclusions:
We designed and evaluated a potential DOOR endpoint for cIAI trials to further characterize overall clinical experiences of participants. Similar data-driven approaches can be utilized to create other infectious disease-specific DOOR endpoints.
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