Classification and regression trees to identify COPD subgroups in clinical trial populations: insights from the IMPACT trial

Heterogeneity in chronic obstructive pulmonary disease (COPD) challenges the identification of optimal treatment populations. Subgroups derived from real-life cohorts using classification and regression trees (CARTs) have shown prognostic value for mortality, but their applicability to clinical trial populations to predict treatment response needs to be further investigated. We sought to evaluate whether previously identified CART-based subgroups are relevant for predicting outcomes and treatment response in the IMPACT trial, and to assess the stability of these subgroups using de novo clustering. Post-hoc analysis of the IMPACT trial, a randomized controlled trial comparing inhaled corticosteroid (ICS)-containing dual or triple therapy to dual long-acting bronchodilation in patients with COPD. CART-based classification from prior real-life cohorts was applied to trial participants. Additionally, de novo clustering was performed using factor analysis of mixed data to identify alternative subgroup structures. Outcomes included mortality, exacerbation rates, lung function, dyspnea, and health status. Subgroups were compared descriptively in terms of baseline characteristics and on-treatment outcomes, with particular attention to blood eosinophil count and treatment response. Among 10,355 patients, both CART-based (5 classes) and de novo (5 clusters) classifications identified subgroups with distinct baseline profiles and variable on-treatment outcomes. Exacerbation and mortality rates differed markedly across subgroups, with numerically greater differences between treatment arms in higher-risk groups. Most clusters showed heterogeneous patterns of outcomes, while one cluster, characterized by elevated blood eosinophils (median 930/mm³), showed a numerically lower exacerbation rate with triple versus dual bronchodilation. Improvements in lung function and symptom scores were also more pronounced in this group. Despite limited concordance between the two methods, both consistently identified subgroups with higher event rates and greater numerical separation between treatment arms, supporting their potential value for clinical trial enrichment and personalized treatment strategies. Application of a CART-based classification derived from real-life cohorts to a clinical trial population revealed subgroups with distinct baseline characteristics and differential treatment outcomes. These findings should be interpreted as exploratory and hypothesis-generating, and may inform future work on trial enrichment strategies and personalized approaches to COPD management. The IMPACT trial was registered on ClinicalTrials.gov under number NCT02164513, first submitted on 12 June 2014.