Patient data meta‐analysis of Post‐Authorization Safety Surveillance (PASS) studies of haemophilia A patients treated with <scp>rAHF</scp>‐PFM
Bibliographic record
Abstract
UNLABELLED: A Post-Authorization Safety Study (PASS) global program was designed to assess safety and effectiveness of rAHF-PFM (ADVATE) use in haemophilia patients in routine clinical settings. The main aim of this project was to estimate the rate of inhibitors and other adverse events across ADVATE-PASS studies by meta-analysing individual patient data (IPD). Eligible Studies: PASS studies conducted in different countries, between 2003 and 2013, for which IPD were provided. Eligible patients: haemophilia A patients with baseline FVIII:C < 5%, with a known number of prior exposure days (EDs). PRIMARY OUTCOME: de novo inhibitors in severe, previously treated patients (PTPs) with > 150 EDs. SECONDARY OUTCOMES: de novo inhibitors according to prior exposure and disease severity; other adverse events; annualized bleeding rate (ABR). ANALYSIS: random-effects logistic regression. Five of seven registered ADVATE-PASS (Australia, Europe, Japan, Italy and USA) and 1188 patients were included (median follow-up 384 days). Among severe PTPs with > 150 EDs, 1/669 developed de novo inhibitors (1.5 per 1000; 95% confidence interval [CI] 0.2, 10.6 per 1000). Among all patients included in the PASS studies, 21 developed any type of inhibitors (2.0%, 95% CI: 0.8%, 4.7%). Less than 1% of patients presented with other serious adverse events possibly related to ADVATE. The overall median ABR was 3.83 bleeds/year (first, third quartiles: 0.60, 12.90); 1.66 (0, 4.78) in the 557 patients continuously on prophylaxis ≥ twice/week. Meta-analysing PASS data from different countries confirmed the overall favourable safety and effectiveness profile of ADVATE in routine clinical settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".