Heterogeneous Treatment Effects of Therapeutic-Dose Heparin in Patients Hospitalized for COVID-19

Abstract

Importance: Randomized clinical trials (RCTs) of therapeutic-dose heparin in patients hospitalized with COVID-19 produced conflicting results, possibly due to heterogeneity of treatment effect (HTE) across individuals. Better understanding of HTE could facilitate individualized clinical decision-making.

Objective: To evaluate HTE of therapeutic-dose heparin for patients hospitalized for COVID-19 and to compare approaches to assessing HTE.

Design, setting, and participants: Exploratory analysis of a multiplatform adaptive RCT of therapeutic-dose heparin vs usual care pharmacologic thromboprophylaxis in 3320 patients hospitalized for COVID-19 enrolled in North America, South America, Europe, Asia, and Australia between April 2020 and January 2021. Heterogeneity of treatment effect was assessed 3 ways: using (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). Analyses primarily used bayesian statistics, consistent with the original trial.

Exposures: Participants were randomized to therapeutic-dose heparin or usual care pharmacologic thromboprophylaxis.

Main outcomes and measures: 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.

Results: 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.

Conclusions and relevance: Among patients hospitalized for COVID-19, the effect of therapeutic-dose heparin was heterogeneous. In all 3 approaches to assessing HTE, 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 findings illustrate the importance of considering HTE in the design and analysis of RCTs.

Trial registration: ClinicalTrials.gov Identifiers: NCT02735707, NCT04505774, NCT04359277, NCT04372589.

Figure 1.. Three Strategies to Evaluate HTE of Therapeutic-Dose Heparin for COVID-19

ACTIV-4a indicates Accelerating COVID-19 Therapeutic Interventions and Vaccines-4 Antithrombotics Inpatient trial; ARD, observed absolute rate difference in hospital survival; ATTACC, Antithrombotic Therapy to Ameliorate Complications of COVID-19 trial; cARD, conditional absolute rate difference in hospital survival; cATE, conditional average treatment effect (the treatment effect within a subgroup); HTE, heterogeneity of treatment effect; OR, odds ratio; OSFDs, organ support–free days; REMAP-CAP, Randomized, Embedded, Multifactorial Adaptive Platform Trial for Community-Acquired Pneumonia. Strategy 1 consists of conventional tests for HTE using subgroup analyses. Differences in treatment effect among subgroups are evaluated in a regression model with an independent variable representing any one of several potential effect modifiers (patient, disease, or management characteristics) that might influence treatment effect. A separate model is computed for each potential effect modifier. Strategy 2 is a risk-based approach to test for HTE according to risk of outcomes (OSFDs and hospital survival) estimated using a risk model derived and internally validated in the trial data. Patient and disease characteristics are handled as predictors of outcome (candidate risk predictors) and combined in a single risk model to compute a single candidate effect modifier, the predicted risk of outcome. See Methods section of text and the eAppendix in Supplement 1 for details. Strategy 3 is an effect-based approach to test for HTE according to predicted treatment effect computed from a model combining multiple variables potentially associated with treatment effect (trained on part of the data, the training data set) and comparing predicted vs observed treatment effect on the remaining data (test data set). Patient and disease characteristics are used to compute a model of the difference in outcome with and without treatment, which is used to compute a single candidate effect modifier, the predicted treatment effect.

Figure 2.. Heterogeneity of Treatment Effect Evaluation by Conventional Subgroup Analysis

CrI indicates credible interval; OR, odds ratio. ^aPosterior probability of an OR greater than 1. ^bBody mass index is calculated as weight in kilograms divided by height in meters squared.

Figure 3.. Heterogeneity of Treatment Effect Evaluation by Risk-Based Analysis

CrI indicates credible interval; OR, odds ratio. Risk-based heterogeneity of treatment effect for organ support–free days is shown by risk deciles (ranging from lowest, group 1, to highest, group 10). All patients in risk groups 8 through 10 required respiratory organ support at baseline vs 2 of 1992 (0.1%) patients in risk groups 1 through 6 (see eTable 2 in Supplement 1). Clinical benefit was deemed substantially more probable than not (posterior probability of an OR >1 above 80%) in risk groups 1 through 6. A similar pattern was observed for hospital survival, although the posterior probability of benefit from heparin was lower for hospital survival vs organ support–free days. ^aPosterior probability of an OR greater than 1.

Figure 4.. Heterogeneity of Treatment Effect Evaluation by Effect-Based Analysis

Effect-based heterogeneity of treatment effect for hospital survival shown by deciles of predicted conditional absolute rate difference (cARD) in hospital survival derived from repeated cross-validation using a causal machine-learning algorithm (n = 100 repetitions).