Deferiprone versus deferoxamine for transfusional iron overload in sickle cell disease and other anemias: Pediatric subgroup analysis of the randomized, open‐label FIRST study
Bibliographic record
Abstract
BACKGROUND: Children with sickle cell disease (SCD) who are chronically transfused often, require iron chelation therapy. There are limited data that allow for comparison of the efficacy and safety of the iron chelator deferiprone versus deferoxamine in children with SCD. METHODS: This post hoc analysis of the phase 3b/4, randomized, open-label FIRST (Ferriprox in Patients with IRon Overload in Sickle Cell Disease Trial) study (NCT02041299) included patients 17 years and younger with SCD or other anemias receiving deferiprone or deferoxamine. RESULTS: Overall, 142 patients were evaluated; mean ages were 10.5 and 11.7 years in the deferiprone and deferoxamine groups, respectively. At 12 months: mean change from baseline in liver iron concentration was -3.3 mg/g dry weight (dw) with deferiprone and -3.4 mg/g dw with deferoxamine (p = .8216); relative mean change (coefficient of variation %) in log cardiac T2* magnetic resonance imaging was 1.02 (21.8%) with deferiprone and 0.95 (19.5%) with deferoxamine (p = .0717); and the mean (standard error) change in serum ferritin levels was -133.0 (200.3) μg/L with deferiprone and -467.1 (244.1) μg/L with deferoxamine (p = .2924). The most common deferiprone-related adverse events (AEs) were upper abdominal pain (20.2%), vomiting (13.8%), pyrexia (9.6%), decreased neutrophil count (9.6%), increased alanine aminotransferase (ALT; 9.6%), and increased aspartate aminotransferase (AST; 9.6%). All cases of increased ALT, increased AST, and neutropenia resolved, most without intervention. CONCLUSIONS: This post hoc analysis of pediatric patients from FIRST corroborated previous findings in adults that deferiprone is comparable to deferoxamine in reducing iron overload. No new safety concerns were observed. Deferiprone is an oral chelation option that could improve adherence and outcomes in children.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".