Inhibitor incidence in an unselected cohort of previously untreated patients with severe haemophilia B: a PedNet study
Bibliographic record
Abstract
The incidence of FIX inhibitors in severe hemophilia B (SHB) is not well defined. Frequencies of 3-5% have been reported but most studies to date were small, including patients with different severities, and without prospective follow-up for inhibitor incidence. Study objective was to investigate inhibitor incidence in patients with SHB followed up to 500 exposure days (ED), the frequency of allergic reactions, and the relationship with genotypes. Consecutive previously untreated patients (PUPs) with SHB enrolled into the PedNet cohort were included. Detailed data was collected for the first 50 ED, followed by annual collection of inhibitor status and allergic reactions. Presence of inhibitors was defined by at least two consecutive positive samples. Additionally, data on factor IX gene mutation was collected. 154 PUPs with SHB were included; 75% were followed until 75 ED, and 43% until 500 ED. Inhibitors developed in 14 patients (7 high-titre). Median number of ED at inhibitor manifestation was 11 (IQR 6.5-36.5). Cumulative inhibitor incidence was 9.3% (95%CI 4.4-14.1) at 75 ED, and 10.2% (5.1-15.3) at 500 ED. Allergic reactions occurred in 4 (28.6%) inhibitor patients. Missense mutations were most frequent (46.8%) overall but not associated with inhibitors. Nonsense mutations and deletions with large structural changes comprised all mutations among inhibitor patients and were associated with an inhibitor risk of 26.9% and 33.3%, respectively. In an unselected, well-defined cohort of PUPs with SHB, cumulative inhibitor incidence was 10.2% at 500 ED. Nonsense mutations and large deletions were strongly associated with the risk of inhibitor development. The PedNet Registry is registered at clinicaltrials.gov; identifier: NCT02979119.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".