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Abstract 4369281: Demographic Disparities in Tafamidis Treatment and Clinical Outcomes Across the United States

2025· article· en· W4415791746 on OpenAlexaff
Nicole Cyrille-Superville, Hanna K. Gaggin, Andrew Rosen, Margarita Udall, Liana Hennum, Xingyu Gao, Elizabeth Nagelhout, Allison Keshishian, Margot K. Davis

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsCumulative incidenceIncidence (geometry)CohortRetrospective cohort studyEpidemiologyCumulative riskHealth equityHealth care

Abstract

fetched live from OpenAlex

Introduction: Transthyretin amyloid cardiomyopathy (ATTR-CM) is a progressive, often fatal disease. A better understanding of demographic disparities in diagnosis and treatment is crucial to optimize care and improve outcomes across diverse patient (pt) populations. Objectives: To evaluate potential differences in initiation of tafamidis, the only approved ATTR-CM therapy at the time of the study, and subsequent clinical outcomes by gender and race. We hypothesized that significant demographic differences exist in treatment patterns and clinical outcomes. Methods: We conducted a retrospective cohort analysis using the US Komodo Healthcare Map ® (01/2016-06/2024). Pts with amyloidosis ICD-10-CM diagnosis codes were identified and followed from diagnosis to tafamidis initiation and cardiovascular-related hospitalization (CVH) or death. Cumulative incidence of treatment initiation and survival probabilities were stratified by gender and race. Results: We identified 11,311 pts with ATTR-CM (63.9% men [mean age, 73.5 y] and 36.1% women [mean age, 72.4 y]). After diagnosis, women had a significantly lower cumulative incidence of tafamidis initiation compared to men at all time points ( P <0.001). At 3 mo after diagnosis, the cumulative incidence was 9.9% among women versus 19.9% among men; by 12 mo, this gap persisted (14.5% vs 28.5%). Race further compounded these disparities ( P <0.001; Figure 1 ). At 12 mo, White men had the highest cumulative incidence of initiation (31.0%), followed by Black men (26.7%), Black women (22.0%), and White women (11.4%). CVH or death occurred in 57.7% of women versus 53.6% of men. Event-free survival at 12 mo was lowest in Black women (42.9%) versus Black men (46.8%), White women (48.6%), and White men (54.4%) ( P <0.001; Figure 2 ). Black women experienced the shortest median (95% CI) time to CVH or death (8.0 mo [6.8-10.0]), followed by Black men (9.9 mo [8.8-12.0]), White women (11.0 mo [9.6-13.0]), and White men (15.0 mo [14.0-16.0]; Table ). Conclusion: This large-scale analysis of a US cohort suggests existing gender and racial disparities in tafamidis treatment initiation and outcomes in ATTR-CM. White women had the lowest rates of tafamidis initiation, while Black women had the worst clinical outcomes, highlighting a compounded disparity in treatment and survival by gender and race. These findings underscore the urgent need to address demographic-based disparities and ensure equitable care for all pts with ATTR-CM.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.343
Teacher spread0.320 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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