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Record W2903790709 · doi:10.1164/rccm.201810-1944ci

Role of Biologics in Asthma

2018· review· en· W2903790709 on OpenAlexaff
M.C. McGregor, James G. Krings, Parameswaran Nair, Mario Castro

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
FundersNational Heart, Lung, and Blood Institute
KeywordsMedicineAsthmaIntensive care medicineMEDLINEImmunology

Abstract

fetched live from OpenAlex

Patients with severe uncontrolled asthma have disproportionally high morbidity and healthcare utilization as compared with their peers with well-controlled disease. Although treatment options for these patients were previously limited, with unacceptable side effects, the emergence of biologic therapies for the treatment of asthma has provided promising targeted therapy for these patients. Biologic therapies target specific inflammatory pathways involved in the pathogenesis of asthma, particularly in patients with an endotype driven by type 2 (T2) inflammation. In addition to anti-IgE therapy that has improved outcomes in allergic asthma for more than a decade, three anti-IL-5 biologics and one anti-IL-4R biologic have recently emerged as promising treatments for T2 asthma. These targeted therapies have been shown to reduce asthma exacerbations, improve lung function, reduce oral corticosteroid use, and improve quality of life in appropriately selected patients. In addition to the currently approved biologic agents, several biologics targeting upstream inflammatory mediators are in clinical trials, with possible approval on the horizon. This article reviews the mechanism of action, indications, expected benefits, and side effects of each of the currently approved biologics for severe uncontrolled asthma and discusses promising therapeutic targets for the future.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.371
Teacher spread0.339 · 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.

Study designOther design
Domainnot available
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

Citations429
Published2018
Admission routes1
Has abstractyes

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