Evaluation of safety and effectiveness of factor VIII treatment in haemophilia A patients with low titre inhibitors or a personal history of inhibitor
Bibliographic record
Abstract
There is no prospective evidence on inhibitor recurrence among haemophilia A patients with low titre inhibitors or history of inhibitors, and whether or how therapeutic choices affect the risk of recurrence. The aims of this study were to synthesise safety data in patients with moderate-severe haemophilia A and with low titre inhibitors or inhibitor history enrolled in the rAHF PFM (ADVATE) - Post-Authorization Safety Studies (ADVATE-PASS) international programme. The study was conducted in clinics participating to the ADVATE PASS programme. The patient population consisted of patients entering the studies with low titre (≤ 5 BU) inhibitors or a positive personal history of inhibitors. Patients on Immune Tolerance Induction at study entry were excluded. Primary outcome was new or recurrent inhibitor titre > 5 BU. Secondary outcomes were any increase of inhibitor titre not reaching 5 BU; any unexplained change in treatment regimen. Primary analysis was done by two-stage random effects meta-analysis. Secondary analysis was done by a hierarchical Bayesian random effects logistic model. A total of 219 patients from seven studies were included. Of these 214 (97.7 %) patients had been previously treated for more than 50 exposure days. Two hundred ten patients had positive history for inhibitors, nine a baseline measurable titre. No patient presented a primary outcome event (95 % confidence interval [CI] 0-1.6 %). Six patients with previous history developed a low titre recurrence (overall rate 2.2, 95 %CI 0-4.8 %). When any increase of inhibitor titre or any treatment change was accounted for, overall 3.7 % (95 % CI 0 %-8.0 %) of patients experienced the outcome. In conclusion, the observed rate of events does not support the definition of this population as at high risk for inhibitor development.
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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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".