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Win Ratio Analysis of BOREAS and NOTUS: Faster Trials, Clearer Wins for Patients With Chronic Obstructive Pulmonary Disease With Type 2 Inflammation

2025· article· en· W4410270135 on OpenAlexaff
Sanjay Ramakrishnan, Simon Couillard, Nayia Petousi, Jessica Bon, Ian Pavord, S.P. Bhatt, Klaus F. Rabe, W. Deng, C. Xia, J. Heble, Mena Soliman

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMedicinePulmonary diseaseInflammationDiseaseInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Abstract RATIONALE: Evaluation of multiple endpoints in clinical trials is often limited by the occurrence of an endpoint of lower clinical importance. Win ratio analysis categorizes outcomes by importance, allowing comparisons of multiple endpoints between treatments. In this analysis, we used win ratio to compare the efficacy of add-on dupilumab 300 mg every 2 weeks (q2w) vs placebo using pooled data from the BOREAS and NOTUS phase 3 trials in patients with chronic obstructive pulmonary disease (COPD) and type 2 inflammation. METHODS: BOREAS (NCT03930732) and NOTUS (NCT04456673) were phase 3 randomized, double-blind, placebo-controlled trials that enrolled patients with COPD, moderate-to-severe airflow limitation and type 2 inflammation (blood eosinophil count ≥300 cells/µL at screening) on triple therapy. Patients were randomized 1:1 to receive add-on dupilumab 300 mg or placebo subcutaneously q2w for 52 weeks. Win ratio analysis compares each patient on dupilumab to each patient on placebo for occurrence of events in the pooled ITT populations. For each pair of comparison, multiple endpoints were ordered regarding clinical importance, with 3 outcomes possible for each endpoint for dupilumab vs placebo: dupilumab win, tie, placebo win. Endpoints were ranked by clinical importance; avoiding hospital was most important, followed by moderate exacerbations, lung function loss, and symptom deterioration. RESULTS: Evaluation of the pooled populations (dupilumab n = 938; placebo n = 934) across the composite endpoints for occurrence-of-event resulted in participants receiving dupilumab being 32% more likely to avoid hierarchically important clinical deterioration with dupilumab compared with placebo (1.32; 95% CI 1.17, 1.49). We also observed a higher win ratio for dupilumab for all 5 occurrence-of-event endpoints evaluated: death/hospital admission/emergency department (ED) visit ≥24 h (7.6% vs 5.6%), moderate exacerbation or ED visit <24 h (22.1% vs 17.9%), total number of moderate or severe (hospitalized) exacerbations during the study period (3.8% vs 2.8%), percent predicted post-bronchodilator forced expiratory volume in 1 second (FEV1) worsening from baseline by ≥ 10%, or post-bronchodilator FEV1 worsening for ≥ 100 mL at Week 52 (12.1% vs 8.2%) and improvement in St. George's Respiratory Questionnaire or Respiratory Symptom Tool for COPD scores (2.0% vs 1.5%). CONCLUSIONS: In patients with COPD and type 2 inflammation, receiving dupilumab increased the likelihood of avoiding the composite of death, hospitalization, exacerbations, worsening symptoms, and worsening lung function by 32% over 12 months of treatment. The win ratio provides a powerful clinically meaningful endpoint that could change how phase 3 trials are conducted in COPD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.402
Teacher spread0.366 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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