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Enregistrement W4417004613 · doi:10.1182/blood-2025-2611

The first characterization of disease burden and healthcare resource utilization for the recent definition of severe von Willebrand disease using a large United States real-world dataset

2025· article· en· W4417004613 sur OpenAlexaff
Angela C. Weyand, Michelle Sholzberg, Laura de Azevedo Guido, Jacob Lai, Nicole Engel-Nitz, Qiana Amos, Robert F. Sidonio

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiquePlatelet Disorders and Treatments
Établissements canadiensSt. Michael's Hospital
Organismes subventionnairesnon disponible
Mots-clésVon Willebrand diseaseDiseaseRetrospective cohort studyHealth careDisease burdenSeverity of illnessVon Willebrand factor

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: von Willebrand Disease (VWD) is a heterogenous condition with variable manifestations of symptoms ranging from mild to frequent, prolonged, and excessive bleeding. Consequently, the impact of symptoms is often underappreciated, leading to delayed and under-diagnosis, and under-treatment. While a universally aligned definition for VWD severity is lacking, a panel of experts recently developed a working consensus to better define Severe VWD using VWF:Ag laboratory values and/or bleeding symptoms (Wynn et al., ASH 2024). In addition, 2021 ASH ISTH NHF WFH guidelines suggest long-term prophylaxis for people with VWD who have a history of severe and frequent bleeds. With this new consensus definition of Severe VWD, there may be many patients who are not receiving prophylaxis who could be eligible to benefit from it (Connell, et al., Blood 2021). Objectives: To describe the real-world disease impact, including bleeding manifestations, treatment burden, and healthcare resource utilization (HCRU) in severe VWD defined by laboratory values. Methods: This retrospective population-based study included data from Commercial and Medicare Advantage members with claims of VWD during the study period (January 2007 to October 2023) in the Optum Research Database, including linked available laboratory data. Patients were characterized as having VWD if they had 1) ≥2 claims with an ICD-9 or ICD-10 code for a VWD diagnosis at least 30 days apart (286.4, D68.0x), or 2) any VWD-specific treatment or 3) ≥1 laboratory result with a von Willebrand factor antigen (VWF:Ag) or ristocetin cofactor (VWF:RCo) <50 IU/dL. Index date was the earliest of these criteria. Patients were included if they had ≥6 months of health insurance coverage before and at least 30 days after the index date, unless they died. Data reported are from the 12-month period consisting of the 6-months prior to and 6-months after the index date. A subgroup of patients with laboratory findings were classified as Severe VWD (defined as VWF:Ag < 20 IU/dL) and evaluated. An age-, gender-, and region-matched non-VWD population was analyzed for comparison.Disease burden (including bleeding manifestations, bleeding frequency, and anemia), treatment burden (including VWD-related treatments, supportive care, and blood transfusions), and HCRU (including ambulatory visits, emergency room visits, and inpatient hospital stays) were evaluated. Results:9,882 patients met inclusion criteria for the diagnosis of VWD. In a subset of 800 VWD patients with laboratory data, 22% were categorized as Severe VWD. 42% of Severe VWD patients had anemia in the study timeframe. In the Severe VWD patients with recorded bleeding, clinically meaningful bleeding manifestations were: gastrointestinal bleeding (27%), hematoma (49%), hematuria (16%), and joint bleeds (4%). Treatment burden and HCRU were multi-fold higher in the Severe VWD group when comparing to the non-VWD cohort (n=98,920): iron replacement therapy (53x), blood transfusions (33x), days of hospitalization (9x), emergency room visits (5x), and ambulatory visits (4x) over the 12-month period. Additional analyses on bleeding manifestations, treatment burden, and HCRU across VWD Types will be presented at the ASH Conference. Conclusions: Applying the VWF:Ag laboratory definition of Severe VWD identified a group of patients representing > 1/5 of all diagnosed VWD. These patients were characterized with high disease burden, and multi-fold higher treatment burden and HCRU when compared to a non-VWD population. While other bleeding, such as heavy menstrual bleeds, nose bleeds, and bruising are also highly prevalent in this population, they are frequently under-reported in claims data. Based on a prior claims dataset identifying ~140,000 diagnosed VWD patients in the US (Weyand et al., ASH 2024), there exists a substantial number of Severe VWD patients that could benefit from long-term prophylaxis treatment. Currently available long-term prophylactic treatment options can be burdensome, requiring frequent intravenous infusions. Due to the limitations of current prophylactic treatment options and underappreciation of the impact of the disease, many VWD patients who could be eligible to benefit from long-term prophylaxis may be untreated. Novel prophylactic therapy options are needed to reduce treatment burden, increase bleed control, decrease HCRU, and improve outcomes for patients with VWD.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,019
Score d'incertitude au seuil0,038

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,004
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,034
Tête enseignante GPT0,301
Écart entre enseignants0,267 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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