Association of factor expression levels with health-related quality of life and direct medical costs for people with haemophilia B
Bibliographic record
Abstract
Aims Gene therapy trials aim to provide a functional cure for patients with haemophilia B (HB), and treatment impact is analyzed by factor IX expression levels (FELs). We investigated the relationship of FELs with health-related quality of life (HRQoL) and costs.Materials and methods This was a retrospective cross-sectional analysis of the European (CHESS I-II) and US (CHESS-US) CHESS population studies. Physicians recruited consecutive patients and extracted information from the medical records; patients completed questionnaires between 2014 and 2015 (CHESS-I), 2018–2019 (CHESS-II) and 2019 (CHESS US). Patients with inhibitors were excluded. HRQoL was assessed using the EQ-5D-5L. Twelve-month haemophilia-related direct medical costs included office visits and hospitalizations based on country-level unit costs. A Tobit model was used to analyze FELs and HRQoL and generalized linear models for direct medical costs.Results A total of 191 men with HB completed the EQ-5D questionnaire; the mean age was 36.8 years, with a mean FEL of 10.1 IU/dL (median, 4.0). Mean EQ-5D was 0.77 (SD, 0.23). The Tobit model adjusting for age, body mass index and blood-borne viruses showed every 1% increase in FEL was associated with +0.006 points in the mean EQ-5D score (p = .003). Mean haemophilia-related direct medical costs excluding factor replacement therapy were €2,028/year (median, €919) in CHESS I-II (EU, n = 226), and $7,171/year (median, $586) in CHESS US (n = 181). Adjusted EU and US models showed every 1% increase in FEL was associated with a decrease in haemophilia-related direct medical costs of €108/year and $529/year, respectively.Limitations Direct medical costs were based on physician extraction of encounters from medical records, potentially underestimating costs of care. The voluntary nature of participation may have introduced selection biases.Conclusions We observed a significant association of increases in FEL with increased HRQoL and decreased costs in Europe and the United States among men with HB and no inhibitors.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".