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Record W4297184211 · doi:10.1186/s13223-022-00721-y

Effectiveness and safety of lanadelumab in ethnic and racial minority subgroups of patients with hereditary angioedema: results from phase 3 studies

2022· article· en· W4297184211 on OpenAlexvenueaboutno aff
Timothy Craig, Rafael Zaragoza-Urdaz, H. Henry Li, Ming Yu, Hong Ren, Salomé Juethner, John Anderson

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2022
Typearticle
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupMedicineHereditary angioedemaAdverse effectHealth equityPopulationDemographyClinical trialPandemicHealth careMinority groupFamily medicineGerontologyPublic healthCoronavirus disease 2019 (COVID-19)DiseaseInternal medicineEnvironmental healthPolitical scienceImmunologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic has highlighted disparities in healthcare, particularly in the United States, even though disparities have existed since the organization of the modern healthcare system. Recruitment of patients from racial and ethnic minority groups is often minimal in phase 3 clinical trials, and is further exacerbated in the case of trials for rare diseases such as hereditary angioedema (HAE). This can lead to a gap in the understanding of minority patients' experiences with these diseases and their response to potential treatment options. METHODS: We reviewed data from phase 3 double-blind (HELP) and open-label extension (HELP OLE) trials of lanadelumab, a monoclonal antibody developed for long-term prophylaxis against attacks of HAE. Efficacy (attack rate reduction) and safety (adverse events) results from White patients were compared descriptively to those from Hispanic/Latino patients, Black/African Americans, and other minority Americans. RESULTS: Not surprisingly, few minorities were recruited across both studies: 9.5% Black, 2.4% Asian, and 7.1% Hispanic/Latino versus 88.1% White and 91.7% non-Hispanic/non-Latino received lanadelumab in HELP, and 4.7% Black, 0.9% Asian, 0.9% other, and 6.1% Hispanic/Latino versus 93.4% White and 93.4% non-Hispanic/non-Latino were enrolled in HELP OLE. Although these studies were conducted in the United States, Canada, Europe, and Jordan, all minorities were from the United States. Despite the number of minority patients being far less than expected for the population, there was no evidence that either efficacy or adverse event profiles differed between ethnic or racial groups. CONCLUSIONS: The HELP and HELP OLE studies described herein recruited far fewer minorities than would be ideal to represent these populations. However, evidence suggests that the effectiveness and tolerance of lanadelumab are similar between the groups. Nonetheless, the disparity in recruitment into research for minorities has significant room for improvement. Trial registration NCT02586805, registered 26 October 2015, https://clinicaltrials.gov/ct2/show/record/NCT02586805 . NCT02741596, registered 18 April 2016, https://clinicaltrials.gov/ct2/show/NCT02741596 .

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)0.008
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.328
Teacher spread0.303 · 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 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".

Quick stats

Citations4
Published2022
Admission routes2
Has abstractyes

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