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Type-2 Inflammation and Lung Function Changes in the Placebo Arms of Asthma Clinical Trials: Findings from the ORACLE2 Meta-analysis

2025· article· en· W4410273601 on OpenAlexaff
Jacques St-Pierre, Samuel Mailhot-Larouche, Fleur L. Meulmeester, C.A. Celis-Preciado, Samuel Lemaire‐Paquette, Sanjay Ramakrishnan, M.E. Wechsler, G.G. Brusselle, J. Corren, Mark Holliday, Sarah Diver, Christopher E. Brightling, Mario Castro, N.A. Hanania, David J. Jackson, Michael J. Neil, A. Laugerud, Emilio Santoro, Christopher Compton, Megan Hardin, Cécile Holweg, A. Subhashini, Timothy Hinks, Richard Beasley, Jacob K. Sont, Ewout W. Steyerberg, Ian Pavord, Simon Couillard

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsSt. Thomas HospitalUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineMeta-analysisPlaceboAsthmaLung functionClinical trialInflammationInternal medicineLungIntensive care medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION: In randomized controlled trials (RCTs), many patients receiving placebo show improvement in clinical outcomes including lung function. Regression to the mean and increased adherence to medication are potential explanatory mechanisms. Given that type-2 inflammation is a treatment-responsive characteristic, we hypothesized that baseline type-2 biomarker levels (blood eosinophil count (BEC) and exhaled nitric oxide (FeNO)) are associated with the magnitude of lung function improvement over time in the placebo groups in RCTs. METHODS: The OxfoRd Asthma attaCk risk scaLE (ORACLE2) patient-level meta-analysis dataset was used to identify prognostic variables associated to lung function changes. The dataset includes control arms of 22 RCTs assessing fixed treatment regimens on asthma exacerbation rates over at least 24 weeks. We excluded open-label RCTs, and we excluded trials missing Forced Expiratory Volume in 1 second (FEV1) at the 52-week follow-up. Multiple imputation by chained equations was used for others missing values in 10 iterations. Lung function change was defined as the change in FEV1 (mL) over one year. Adjusted regression coefficients (aRC)[95% confidence intervals (CI)] were computed using linear regression. Interactions terms between in FeNO and BEC was assessed in this model and restricted cubic spline curves were plotted to visualize the potential interaction. RESULTS: Patients with moderate-to-severe asthma (n=2,675), from 9 RCTs with a placebo arm were included. An improvement in lung function was observed in the placebo group across trials. Factors associated with lung function change (ΔFEV1 (mL)) included (aRC [95%CI]) (Figure A): FeNO (per 10-fold increase: 67 ml [28-107]), age (per 10-year increase: -42 ml [-53--31]), baseline FEV1 (per 10% decrease: 54 ml [44-64]), FEV1 reversibility (per 10% increase: 128 ml [114-142]), and presence of nasal polyposis (40 ml [0-80]). FeNO and BEC have a significant positive interaction (interaction term [95%CI]: 133[24-242]) (Figure B). CONCLUSION: Type 2 inflammatory biomarkers, particularly FeNO, emerged as a factor associated with lung function improvement on placebo in asthma trials. Low adherence in pre-trial among patients with high FeNO may partially explain the observed lung function improvements in this group within the placebo arm of RCTs. Further research is needed to understand the mechanisms underlying this observation and its impact on the outcomes of RCTs. REGISTRATION: PROSPERO-CRD42021245337 JSP&SML= co-primary authors

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.063
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.039
Bibliometrics0.0030.005
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.091
GPT teacher head0.426
Teacher spread0.334 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
DomainMethods
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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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