Low‐dose immune tolerance induction for children with hemophilia A with poor‐risk high‐titer inhibitors: A pilot study in China
Bibliographic record
Abstract
BACKGROUND: Immune tolerance induction (ITI) therapy is currently unaffordable in China. Management of hemophilia A children with high-titer inhibitor is therefore a challenge. AIM: To describe the ITI strategy using plasma-derived factor VIII/von Willebrand factor concentrate (pdFVIII/VWF) +/- immunosuppression and to report its efficacy in children with hemophilia A having poor-risk status for ITI success. METHODS: A prospective pilot study on children with hemophilia A having poor-risk status (all with at least inhibitor titer > 10 BU pre-ITI initiation). Patients received ~50 IU/kg FVIII every other day using domestic intermediate purity pdFVIII/VWF products, either alone or in combination with rituximab +/- prednisone. RESULTS: Sixteen patients with median age 2.9 (range, 2.2-13.2) years and median pre-ITI inhibitor titer 30.7 (range, 10.4-128) BU were enrolled. Analysis at median 14.7 (range, 12.4-22.6) months' follow-up showed a total response rate of 87.5%. This included success (achieving inhibitor < 0.6 BU) in 13 patients (81.3%) in a median of 8.8 (range, 3.2-11.8) months, and partial success (achieving inhibitor < 5 BU but > 0.6BU) in 1 (6.3%). Compared to the pre-ITI period, the mean bleeds/month during ITI was 0.51 (64.0% reduction), and joint bleeds/month was 0.34 (64.3% reduction). This low-dose ITI strategy cost less by 70% to 87% than that for the high-dose FVIII regimen. No severe adverse events were observed. CONCLUSION: This low-dose ITI strategy of pdFVIII/VWF +/- immunosuppression achieved relatively satisfactory outcomes in children with hemophilia A inhibitor having poor-risk status. This low-dose regimen showed economic advantages and is therefore suitable for using in China. However, further study in a larger cohort with a longer follow-up time is needed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".