A Prognostic Enrichment Strategy for Selection of Patients With Acute Respiratory Distress Syndrome in Clinical Trials

Objectives: Incomplete or ambiguous evidence for identifying high-risk patients with acute respiratory distress syndrome for enrollment into randomized controlled trials has come at the cost of an unreasonable number of negative trials. We examined a set of selected variables early in acute respiratory distress syndrome to determine accurate prognostic predictors for selecting high-risk patients for randomized controlled trials. Design: A training and testing study using a secondary analysis of data from four prospective, multicenter, observational studies. Setting: A network of multidisciplinary ICUs. Patients: We studied 1,200 patients with moderate-to-severe acute respiratory distress syndrome managed with lung-protective ventilation. Interventions: None. Measurements and Main Results: We evaluated different thresholds for patient's age, PaO2/FIO2, plateau pressure, and number of extrapulmonary organ failures to predict ICU outcome at 24 hours of acute respiratory distress syndrome diagnosis. We generated 1,000 random scenarios as training (n = 900, 75% of population) and testing (n = 300, 25% of population) datasets and averaged the logistic coefficients for each scenario. Thresholds for age ( 70 yr), PaO2/FIO2 (≤ 100, 101–150, > 150 mm Hg), plateau pressure ( 30 cm H2O), and number of extrapulmonary organ failure ( 2) stratified accurately acute respiratory distress syndrome patients into categories of risk. The model that included all four variables proved best to identify patients with the highest or lowest risk of death (area under the receiver operating characteristic curve, 0.86; 95% CI, 0.84–0.88). Decision tree analyses confirmed the accuracy and robustness of this enrichment model. Conclusions: Combined thresholds for patient's age, PaO2/FIO2, plateau pressure, and extrapulmonary organ failure provides prognostic enrichment accuracy for stratifying and selecting acute respiratory distress syndrome patients for randomized controlled trials.

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