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Record W2519276961 · doi:10.1080/1744666x.2016.1237288

300 IR HDM tablet: a sublingual immunotherapy tablet for the treatment of house dust mite-associated allergic rhinitis

2016· review· en· W2519276961 on OpenAlexaff
Pascal Demoly, Yoshitaka Okamoto, William H. Yang, Philippe Devillier, Karl‐Christian Bergmann

Bibliographic record

VenueExpert Review of Clinical Immunology · 2016
Typereview
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsOttawa Allergy Research CorporationUniversity of Ottawa
FundersStallergenes Greer France
KeywordsMedicineSublingual immunotherapyHouse dust miteTolerabilityAsthmaAllergyAllergic asthmaDermatologyAllergen immunotherapyPyroglyphidaeAdverse effectImmunologyInternal medicineAllergen

Abstract

fetched live from OpenAlex

INTRODUCTION: The once-daily 300 index of reactivity (IR) house dust mite (HDM) tablet (Actair®; Stallergenes Greer, Antony, France/Shionogi & Co. Ltd., Osaka, Japan) is the first sublingual immunotherapy (SLIT) tablet to be approved for the treatment of HDM-induced allergic rhinitis. Areas covered: This drug profile reviews the current body of evidence on the efficacy, safety and tolerability of the 300 IR HDM tablet, its pharmacodynamics, and its role in clinical practice. Expert commentary: Data from its clinical development program demonstrate favorable efficacy and safety in adults and adolescents with HDM-induced allergic rhinitis, irrespective of mono- or polysensitization status, or the presence of comorbid mild asthma. The 300 IR HDM tablet is effective from as early as 2 months after treatment initiation, providing allergic symptom control and a reduction in the need for symptomatic medication, while improving health-related quality of life. Clinical efficacy is maintained for 1 year after treatment is stopped.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.104
GPT teacher head0.442
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations16
Published2016
Admission routes1
Has abstractyes

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