Disparities in Real-World Treatment Patterns Among Patients with Von Willebrand Disease in a Large US Population-Based Dataset
Bibliographic record
Abstract
Introduction: Von Willebrand disease (VWD) is the most common inherited bleeding disorder, affecting up to 1% of the population. Due to heterogeneity in bleeding manifestations among patients with VWD and lack of clear consensus, there is variation in treatments provided. We used a largest-to-date US administrative database to evaluate national trends in bleeding and treatments provided to patients with VWD. Objectives: To describe real-world patient characteristics, bleeding events, and treatment patterns of individuals with VWD using a large national US claims database. Methods: This retrospective study included data from patients with VWD from 2015 to 2024 in the Komodo Healthcare database of patient claims data, representing 49,797 unique diagnosed and treated VWD patients. Patients were defined as having VWD if they had ≥2 claims with an ICD-10 code for a VWD diagnosis (D68.0x) and an associated VWD national drug code (NDC) for VWD treatment. Patient demographics and types of bleeding events, treatments used, and treatment frequencies were collected. Treatments used by bleeding event were analyzed. Prophylactic or on-demand use was categorized based on the dosing frequency of treatments. Results Patient demographics: By age cohort, 20% were 0-17 years, 46% were 18-39 years, 22% were 40-64 years, and 12% were ≥65 years. Females represented 73% of patients diagnosed and treated for VWD. Bleeding phenotype: The most common bleeds across all treated patients with at least one bleeding event claim were heavy menstrual bleeding (77% of female patients with VWD) and nosebleeds (31%). Other bleeds and bleeding comorbidities included hematomas (18%), gastrointestinal (GI) bleeds (16%), internal bleeds (12%), anemia (10%), gum bleeds (3%), and joint bleeds (2%). Patients aged 0-11 years and 12-17 tended to have more nosebleeds, heavy menstrual bleeding was the most frequent bleed among females 12-17, 18-39 and 40-64 years of age cohorts, and GI bleeding was the most frequent type of bleed in the ≥65 years of age cohort. Treatments: Based on dosing frequencies, the reason for VWD treatment use was primarily categorized as on-demand for 90% of patients and prophylaxis for the remaining 10%. On-demand medications included antifibrinolytics and desmopressin, which were used 46% and 31% of the time, respectively, while 23% used VWF replacement therapies. Among prophylaxis users, 49% of patients were treated with VWF replacement therapies, most commonly Humate-P (77%), followed by wilate (16%), Vonvendi (11%), and Alphanate (8%). Patients could have received multiple VWF therapies. Hemlibra was used in 2% of patients, mainly to treat those with joint bleeds. The most common uses of VWF replacement were for joint bleeds (57%), GI bleeds (40%), gum bleeds (37%), internal bleeds (35%), hematomas (34%), and nosebleeds (27%). Heavy menstrual bleeding was treated with VWF replacement therapies in only 17% of patients. 47% of patients with anemia were treated with VWF replacement. Deeper analysis on treatment frequencies by bleed type will be presented at the ASH conference. Conclusions: Use of NDCs within a large, national US claims database has enabled granular examination of the treatment patterns and disease burden across the VWD population over time. The bleeding phenotypes and hemostatic medications used to treat VWD patients are variable. Even in recent years, prophylactic treatment has been used in a minority of VWD patients who have bleeding comorbidities, despite some experiencing severe and frequent bleeds. Treatment burden may be a factor as VWF replacements are often infused 2 to 3 times per week as prophylaxis. While heavy menstrual bleeding and nosebleeds were the most common bleeding phenotypes among VWD patients with bleeding comorbidities (and likely underrepresented in claims data), only a minority of patients received VWF replacement therapies. These findings suggest a high unmet need for better treatment options for VWD patients who may benefit from prophylactic therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".