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Exploring Global Geographic Variation in Exacerbation Rates in Randomized Controlled Trials of Biologics in Patients With Severe Asthma: A Systematic Literature Review

2025· article· en· W4410268806 on OpenAlexaff
Daniel J. Jackson, Piotr Kuna, Loretta Jacques, R. Alfonso Cristancho, Tricia Finney‐Hayward, Neelesh Kumar Mehra, Terence E. Taylor, Jessie Z. Yu, Lydia Vinals, Jeremiah Hwee

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsGlaxoSmithKline (Canada)
Fundersnot available
KeywordsMedicineAsthmaExacerbationRandomized controlled trialAsthma exacerbationsGeographic variationIntensive care medicineMEDLINESystematic reviewInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Rationale: Depemokimab is the first ultra-long-acting biologic with enhanced interleukin-5 binding affinity, high potency and extended half-life, enabling twice-yearly dosing for patients with asthma. In the Phase III SWIFT-1/2 studies, depemokimab significantly reduced exacerbations rates versus placebo; however, a high placebo response was seen in patients from Central East Europe. Previous reports have highlighted treatment effect differences across countries. This systematic literature review (SLR) summarized geographic variations in exacerbation rates and biologic treatment responses in randomized controlled trials (RCTs) enrolling patients with severe asthma. Methods: Following a predefined protocol, MEDLINE, Embase, and Evidence-based Medicine Reviews Databases were searched from inception to May 7, 2024, for RCTs of respiratory biologics for adult patients with severe asthma reporting exacerbation rates by geographic region. Key respiratory conferences (2019-2024) were also searched. Records were screened by one reviewer in two phases (abstract then full text), with 10% of screened publications validated by a second reviewer. Results were synthesized qualitatively. Results: Six publications reporting five unique trials reported on exacerbations by geographic region. Data from the SWIFT-1/2 studies were also included for reference. Subgroup and post hoc analyses by geographic region of RCTs for tezepelumab (NAVIGATOR), benralizumab (CALIMA/SIROCCO), reslizumab (NCT02452190), dupilumab (TRAVERSE open-label extension), and depemokimab (SWIFT-1/2) consistently reported the smallest treatment effects on exacerbation rates in Central East European countries (Table). Across four trials reporting arm-level exacerbation rates for tezepelumab, benralizumab, depemokimab, and dupilumab, patients from Central East Europe had the lowest exacerbation rates while on placebo. Only CALIMA and SIROCCO (benralizumab) reported patient baseline characteristics by geographic region, with patients from Central East Europe reporting the lowest exacerbation rate (suggesting less severe disease) of all regions in the year preceding study entry. While subgroup analyses of exacerbation rates by region were prespecified in most trials, some population sizes were small, limiting the ability to draw strong conclusions. Conclusions: Geographical variation in exacerbation rate was consistently observed across biologic RCTs in patients with severe asthma. Lower biologic treatment effects were observed in Central East Europe versus other regions due to lower exacerbation rates in the placebo arm. This could lead to misinterpretation of efficacy results if not considered in future studies. Further studies are needed to better understand how patient characteristics, background treatment adherence, clinical practice, and biologic access may affect the observed geographic differences in exacerbation rates, and how these may impact trial participation, and interpretation of trial results.

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)0.052
metaresearch head score (Gemma)0.175
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.175
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0170.015
Bibliometrics0.0200.018
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.317
Teacher spread0.296 · 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 designSystematic review
DomainMethods
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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