Trial reportThorax2025
Identifying azithromycin responders with an individual treatment effect model in COPD.
Trial report in Thorax, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveLong-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease (COPD). However, patients would benefit from better identification of responders and non-responders to minimise unnecessary exposure. We aimed to assess treatment effect heterogeneity and estimate individual treatment effects (ITEs) to distinguish patients most likely to benefit from prophylactic treatment.
methodsWe used data from 1025 patients of the MACRO trial to assess the ITE of azithromycin on annual exacerbation rate. A Causal Forest was used as a causal machine learning model. We independently validated our findings using data from 83 patients of the COLUMBUS trial.
resultsThe tertile of patients with the best predicted ITE within MACRO and within the COLUMBUS independent validation cohort showed significant and substantially greater reductions in annual exacerbation rates (in MACRO -0.50, rate ratio 0.70, p=0.01, in COLUMBUS: -2.28, rate ratio 0.43, p<0.001) compared with the average treatment effect across the entire cohort (MACRO -0.35, rate ratio 0.83, p=0.01 and COLUMBUS -1.28, rate ratio 0.58, p=0.001). Conversely, no significant treatment effect was observed in the remaining two-thirds of patients. Primary determinants of ITE included respiratory symptoms, white blood cell count, haemoglobin, C-reactive protein and forced vital capacity. Smoking status did not emerge as a significant predictor.
conclusionBased on five easily obtainable parameters to predict ITE, we identified treatment effect heterogeneity in COPD subjects treated with azithromycin maintenance therapy and found a small subgroup of responders driving the average reduction in exacerbations reported in previous trials.
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