Designing an ARDS trial for 2020 and beyond: focus on enrichment strategies

Abstract

With the exception of a few successes in trials of supportive care, the majority of interventional clinical trials for acute respiratory distress syndrome (ARDS) have not led to new therapies. To improve the likelihood of benefit from clinical trial interventions in ARDS, clinical trial design must be improved. To optimize trial design, many factors need to be considered including the type of therapy to be tested, the type of trial (phase 2 or 3), how patients will be selected, primary and secondary end-points, and strategy for conduct of the trial, including potential newer trial designs such as platform or adaptive trials. Of these, optimization of patient selection is central to the likelihood of success and is particularly relevant in ARDS, which is a heterogeneous clinical syndrome, not a homogeneous disease. Recent advances including improved understanding of pathophysiologic mechanisms and better tools for outcome prediction in ARDS should facilitate both predictive and prognostic enrichment. This commentary focuses on new information and novel methods for prognostic and predictive enrichment that may be useful to optimize patient selection and increase the likelihood of positive clinical trials in ARDS.

Phenotypes and personalized medicine in the acute respiratory distress syndrome

“…The reader is also referred to a related article in this issue of Intensive Care Medicine that considers approaches to the design of ARDS trials based on prognostic and predictive enrichment strategies that identifies some approaches that are based on physiologic, systemic, radiographic or biologic criteria [4].…”

Pharmacologic Treatments for Acute Respiratory Distress Syndrome

“… 82 Identifying distinct subsets may increase the likelihood of either response or adverse outcome associated with specific interventions, and as such provide an opportunity for improving patient selection for clinical trials on therapeutics for ARDS. 83 , 84 As an example, subphenotypes of ARDS with variable levels of inflammation have been identified by using latent class analysis to examine clinical and biological data. 85 These subphenotypes have exhibited divergent clinical outcomes and differential response to specific supportive and pharmacologic therapies.…”

Toward Optimal Acute Respiratory Distress Syndrome Outcomes

“… 2 Second, the patients studied in mechanistic and clinical trials must be sufficiently defined and/or homogenous to allow for appropriate power calculations, enrollment, and subgroup analyses that can ultimately identify biomarkers and desperately needed therapies. 12 Third, some patients who have a syndrome that is consistent with or resembles ARDS may benefit from particular medications or interventions—such as the withdrawal of an injurious medication, the addition of antimicrobial agents, or immunosuppression. And finally, because mortality remains high for ARDS, defining the syndrome is important for clinical prognostication.…”