Trial reportRespiratory research2023
Can we predict who will benefit most from biologics in severe asthma? A post-hoc analysis of two phase 3 trials.
Trial report in Respiratory research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
A Multicenter, Randomized, Double-blind, Placebo-controlled, Parallel Group, Dose Ranging Study to Determine the Effect of Mepolizumab on Exacerbation Rates in Subjects With Severe Uncontrolled Refractory Asthma
MEA115588 A Randomised, Double-blind, Double-dummy, Placebo-controlled, Parallel-group, Multi-centre Study of the Efficacy and Safety of Mepolizumab Adjunctive Therapy in Subjects With Severe Uncontrolled Refractory Asthma
Who cites it
8 citing papers in PubMed, 20 citations in OpenAlex.
- Primary care provider referral patterns and awareness of biologic therapy for uncontrolled asthma.The journal of allergy and clinical immunology. Global · 2026Article
- Green Light for Response: Clinical Stratification of Response to Biologic Therapy in Severe Asthma.Journal of asthma and allergy · 2026Article
- Real-world evidence on biologic use in paediatric asthma: there but not there yet?ERJ open research · 2025Article
- INSIGHTS Asthma Pragmatic Registry - A Pragmatic Approach to High-Validity Real-World Evidence for Asthma.Pragmatic and observational research · 2025Article
- An Updated Systematic Review on Asthma Exacerbation Risk Prediction Models Between 2017 and 2023: Risk of Bias and Applicability.Journal of asthma and allergy · 2025Review
- Anti-interleukin-5/anti-interleukin-5 receptor α treatment improves self-reported work productivity in patients with severe eosinophilic asthma: a prospective cohort trial.ERJ open research · 2024Article
- Epigenetic patient stratification via contrastive machine learning refines hallmark biomarkers in minoritized children with asthma.Research square · 2024Article
- Promising treatment biomarkers in asthma.Frontiers in drug safety and regulation · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 5 countries.
Funding
Abstract
backgroundIndividualized prediction of treatment response may improve the value proposition of advanced treatment options in severe asthma. This study aimed to investigate the combined capacity of patient characteristics in predicting treatment response to mepolizumab in patients with severe asthma.
methodsPatient-level data were pooled from two multinational phase 3 trials of mepolizumab in severe eosinophilic asthma. We fitted penalized regression models to quantify reductions in the rate of severe exacerbations and the 5-item Asthma Control Questionnaire (ACQ5) score. The capacity of 15 covariates towards predicting treatment response was quantified by the Gini index (measuring disparities in treatment benefit) as well as observed treatment benefit within the quintiles of predicted treatment benefit.
resultsThere was marked variability in the ability of patient characteristics to predict treatment response; covariates explained greater heterogeneity in predicting treatment response to asthma control than to exacerbation frequency (Gini index 0.35 v. 0.24). Key predictors for treatment benefit for severe exacerbations included exacerbation history, blood eosinophil count, baseline ACQ5 score and age, and those for symptom control included blood eosinophil count and presence of nasal polyps. Overall, the average reduction in exacerbations was 0.90/year (95%CI, 0.87‒0.92) and average reduction in ACQ5 score was 0.18 (95% CI, 0.02‒0.35). Among the top 20% of patients for predicted treatment benefit, exacerbations were reduced by 2.23/year (95% CI, 2.03‒2.43) and ACQ5 score were reduced by 0.59 (95% CI, 0.19‒0.98). Among the bottom 20% of patients for predicted treatment benefit, exacerbations were reduced by 0.25/year (95% CI, 0.16‒0.34) and ACQ5 by -0.20 (95% CI, -0.51 to 0.11).
conclusionA precision medicine approach based on multiple patient characteristics can guide biologic therapy in severe asthma, especially in identifying patients who will not benefit as much from therapy. Patient characteristics had a greater capacity to predict treatment response to asthma control than to exacerbation.
trial registrationClinicalTrials.gov number, NCT01691521 (registered September 24, 2012) and NCT01000506 (registered October 23, 2009).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.