Patient and parent preferences for characteristics of prophylactic treatment in hemophilia
Bibliographic record
Abstract
INTRODUCTION: New longer-acting factor products will potentially allow for less frequent infusion in prophylactic treatment of hemophilia. However, the role of administration frequency relative to other treatment attributes in determining preferences for prophylactic hemophilia treatment regimens is not well understood. AIM: To identify the relative importance of frequency of administration, efficacy, and other treatment characteristics among candidates for prophylactic treatment for hemophilia A and B. METHOD: An Internet survey was conducted among hemophilia patients and the parents of pediatric hemophilia patients in Australia, Canada, and the US. A monadic conjoint task was included in the survey, which varied frequency of administration (three, two, or one time per week for hemophilia A; twice weekly, weekly, or biweekly for hemophilia B), efficacy (no bleeding or breakthrough bleeding once every 4 months, 6 months, or 12 months), diluent volume (3 mL vs 2.5 mL for hemophilia A; 5 mL vs 3 mL for hemophilia B), vials per infusion (2 vs 1), reconstitution device (assembly required vs not), and manufacturer (established in hemophilia vs not). Respondents were asked their likelihood to switch from their current regimen to the presented treatment. Respondents were told to assume that other aspects of treatment, such as risk of inhibitor development, cost, and method of distribution, would remain the same. RESULTS: A total of 89 patients and/or parents of children with hemophilia A participated; another 32 were included in the exercise for hemophilia B. Relative importance was 47%, 24%, and 18% for frequency of administration, efficacy, and manufacturer, respectively, in hemophilia A; analogous values were 48%, 26%, and 21% in hemophilia B. The remaining attributes had little impact on preferences. CONCLUSION: Patients who are candidates for prophylaxis and their caregivers indicate a preference for reduced frequency of administration and high efficacy, but preferences were more sensitive to administration frequency than small changes in annual bleeding rate.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".