An exploratory analysis of a multiplatform adaptive randomized controlled trial (RCT) demonstrates heterogeneity of responses to therapeutic-dose heparin in patients hospitalized for COVID-19. In all 3 analyses of trial results, “heparin was more likely to be beneficial in those who were less severely ill at presentation or had lower BMI and more likely to be harmful in sicker patients and those with higher BMI,” the authors conclude. “The findings illustrate the importance of considering [heterogeneity of treatment effect] in the design and analysis of RCTs.”
The trial compared therapeutic-dose heparin with usual-care pharmacologic thromboprophylaxis in 3,320 patients hospitalized for COVID-19 on 5 continents. The heterogeneity of treatment responses was assessed in 3 ways: (1) conventional subgroup analyses of baseline characteristics, (2) a multivariable outcome prediction model (risk-based approach), and (3) a multivariable causal forest model (effect-based approach).
Based on the main outcomes of organ support–free days (assigning a value of −1 to those who died in the hospital and the number of days free of cardiovascular or respiratory organ support up to day 21 for those who survived to hospital discharge) and hospital survival, the study showed the following: “Baseline demographic characteristics were similar between patients randomized to therapeutic-dose heparin or usual care (median age, 60 years; 38% female; 32% known non-White race; 45% Hispanic). In the overall multiplatform RCT population, therapeutic-dose heparin was not associated with an increase in organ support–free days (median value for the posterior distribution of the OR, 1.05; 95% credible interval, 0.91-1.22). In conventional subgroup analyses, the effect of therapeutic-dose heparin on organ support–free days differed between patients requiring organ support at baseline or not (median OR, 0.85 vs 1.30; posterior probability of difference in OR, 99.8%), between females and males (median OR, 0.87 vs 1.16; posterior probability of difference in OR, 96.4%), and between patients with lower body mass index (BMI <30) vs higher BMI groups (BMI ≥30; posterior probability of difference in ORs >90% for all comparisons). In risk-based analysis, patients at lowest risk of poor outcome had the highest propensity for benefit from heparin (lowest risk decile: posterior probability of OR >1, 92%) while those at highest risk were most likely to be harmed (highest risk decile: posterior probability of OR <1, 87%). In effect-based analysis, a subset of patients identified at high risk of harm (P = .05 for difference in treatment effect) tended to have high BMI and were more likely to require organ support at baseline.”
Editorial: “While conventional one-variable-at-a-time subgroup analyses and risk score approaches will continue to have a role in estimating and reporting variation in treatment effects across clinically relevant patient subgroups, randomized trials should increasingly report effect score analyses for detecting heterogeneity of treatment effect on an absolute scale to better inform personalized care decisions in real-world populations,” editorialists conclude, pointing to 4 implications of the trial: “First, it is important to recognize that one-variable-at-a-time subgroup analyses, risk score analyses, and effect score analyses answer different questions.… Second, heterogeneity assessments often require larger sample sizes than those needed for estimation of average effects; thus, the most informative analyses will use data from large trials and pooled harmonized data from multiple similar trials.… Third, the internal development of scores should adopt modern approaches to control overfitting (ie, by sample splitting) and quantify uncertainty.… Fourth, shared decision-making between clinicians and patients requires information regarding heterogeneity on the absolute scale.…”