Iron Chelation Efficiency of Deferasirox (Exjade®, ICL670) in Patients with Transfusional Hemosiderosis.
Bibliographic record
Abstract
Abstract Iron excretion can be calculated according to Angelucci et al (NEJM 2000). As applied to the novel oral iron chelator deferasirox (DSX), chelation efficiency can then be determined as the % iron excretion vs theoretical iron binding capacity of chelator dose: % efficiency = [iron excretion (mg/kg/day)/chelator dose (mg/kg/day)] x [374/56] x 2 x 100 (374 and 56 represent the molecular weights of DSX and iron; factor 2 accounts for the tridentate ligand). In a total of 325 patients with β-thalassemia (n=285) or rare anemias, such as MDS (n=13), DBA (n=14) or other anemias (n=13), included in the DSX Phase II and III Studies 0108 and 0107, liver iron concentration (LIC) was evaluated by liver biopsy at baseline and study end. All patients were treated with once-daily oral DSX 5, 10, 20 or 30 mg/kg according to baseline LIC (2–3, >3–7, >7–14 and >14 mg Fe/g dw, respectively). In these patients, the average dose during study was 22.8 ± 7.6 mg/kg. The average iron intake was 0.37 mg/kg/day and was similar between dose cohorts. Efficiency of daily DSX treatment (mean ± SD) Baseline LIC 2–3 >3–7 >7–14 >14 DSX, mg/kg 5 (n=9) 10 (n=49) 20 (n=81) 30 (n=186) Iron excretion (mg/kg/day) 0.14 ± 0.1 0.21 ± 0.1 0.39 ± 0.1 0.57 ± 0.2 Iron intake (mg/kg/day) 0.39 ± 0.1 0.37 ± 0.1 0.38 ± 0.1 0.36 ± 0.1 Ratio iron excretion/intake 0.33 ± 0.2 0.53 ± 0.4 1.09 ± 0.5 1.66 ± 0.8 Efficiency (%) 31.6 ± 26.4 27.5 ± 18.4 27.1 ± 10.3 27.3 ± 12.4 There were no differences in the chelation efficiency of DSX between the overall initial dose groups, and thus between different LIC categories at baseline, or between age and disease groups. Using the estimated efficiency of 27%, and the formula above, the approximate dose (mg) needed to achieve iron balance corresponds to an iron intake in mg Fe/kg/day divided by 0.02. For a patient receiving 0.2, 0.4 or 0.6 mg/kg Fe/day the doses of 10, 20 or 30 mg/kg, respectively, are estimated to achieve iron balance (eg for a 44 kg person receiving 4 units of blood/month a dose of 30 mg/kg would be required to achieve iron balance). Further analysis reveals that chelation efficiency does appear to increase somewhat with iron intake: in patients with <0.3 mg/kg/day Fe (average 0.23) the estimated efficiency is 22%, but becomes 34% in those with >0.5 mg/kg/day Fe (average 0.55). Applying different chelation efficiency estimates for low and high iron intake, 14 and 22 mg/kg/day DSX, respectively, would be required to chelate the transfused iron. In Study 0107, 230 patients were treated with deferoxamine (DFO) at an average daily dose of 45 mg/kg (5 days/week). Using the molecular weight of DFO (656) and a factor of 1 for a hexadentate ligand in the calculation, the overall chelation efficiency for DFO is 13% (10–17% in the lowest and highest iron intake categories, respectively). These calculations, based on the formula of Angelucci et al, correspond well to the overall observation in the DSX clinical studies, that iron balance or net negative iron balance is achieved by daily doses of 20–30 mg/kg in regularly transfused patients. The results also confirm that the estimated chelation efficiency of DSX is around twice that of DFO.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".