High rate of spontaneous inhibitor clearance during the long term observation study of a single cohort of 524 haemophilia A patients not undergoing immunotolerance
Bibliographic record
Abstract
BACKGROUND: The natural history of inhibitors in patients with haemophilia A not undergoing immune tolerance induction (ITI) is largely unknown. A recent randomized controlled trial suggests that the higher the FVIII dose used for ITI, the faster the clearance and the lower the rate of bleeding, without any difference in the rate of tolerance. We aimed at assessing the rate of spontaneous inhibitor clearance in a large cohort of patients not undergoing ITI. METHODS: A retrospective analysis of anti-FVIII inhibitors of long-term registry data in a single centre cohort of 524 haemophilia A patients considered for synovectomy was performed. Patients were tested for inhibitors before and 15 days after any and each surgical episode and thereafter did not undergo immune tolerance at any time. RESULTS: The cumulative incidence of inhibitors overall was 34% (180 out of 524) with the highest percentage of 39% (168 out of 434) in severe patients which represented 83% of the cohort. Among the 180 inhibitor patients: 63 had permanent inhibitors; 70 fulfilled current criteria for transient inhibitors but a third category of 47 additional patients cleared the alloantibody spontaneously in >6 months. At logistic regression, both the inhibitor titre and the gene mutation were shown to predict time to clearance. CONCLUSIONS: Spontaneous clearance of inhibitors over variable time in the absence of ITI treatment was found in up to 2/3 of the cases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".