Ferritin Levels, Compliance and Adverse Events Related to Infused Iron Chelation Therapy in a Cohort of Patients from Usual Care Setting in the United States.
Bibliographic record
Abstract
Abstract Background: Deferoxamine (DFO) is an iron chelation therapy (ICT) agent administered to patients undergoing chronic blood transfusions to avoid toxic iron overload. Although efficacious, it is burdensome to patients due to the need for almost daily infusions lasting 8–10 hours each, and the occurrence of treatment-related adverse events (AEs). Purpose: To document ferritin levels, compliance and prevalence of AEs in a cohort of patients undergoing DFO ICT. Methods: A naturalistic cohort study of resource utilization and quality-of-life burden of infused ICT in the usual care setting (acute hospital and out-patient) was undertaken in four US treatment centers between September and December 2005. Patients aged ≥6 years with thalassemia or sickle cell disease (SCD) currently undergoing ICT were eligible to participate. This abstract refers only to patient compliance, ferritin levels and AEs related to infused ICT. Compliance (up to 7 days prior to the study) and AEs (up to 30 days prior to the study) were obtained from patient interviews. Ferritin data from these same patients during their initial and most recent year of ICT were collected from medical charts. Results: 49 patients on infused ICT (50% male; mean age: 28 ± 10 years) with thalassemia (n=40) or SCD (n=9) were recruited. Ferritin level test results obtained from charts indicate that, in general, average blood iron levels were high and remained stable or increased over time, despite ICT. During the initial year of ICT (n=35), mean ferritin level was 2687 ± 1535 ng/mL for thalassemia patients and 2088 ± 791 ng/mL for SCD patients (2519 ± 1382 overall). During the most recent year of ICT (n=45), thalassemia patients had a mean ferritin level value of 2496 ± 2556 ng/mL and SCD patients had a mean ferritin level value of 4108 ± 2030 ng/mL (2741 ± 2532 overall). For all patients in whom data from the most recent year and the initial year of ICT were available (n=29), mean ferritin level increased by 306 ± 2774 ng/mL over a mean period of 20 ± 9 years of therapy. In general, high mean ferritin level during the most recent year of ICT was associated with poor compliance reported over the previous 7-day period (Table). Seventy-seven percent of patients reported missing at least one DFO dose over the previous 4 weeks. Among these patients, 14% did so due to AEs. Over the previous 30 days, 55% suffered at least one AE; the most commonly reported were site soreness (85%), site irritation (74%), ringing in the ears (26%), temporary hearing loss (11%), blurred vision (11%) and abdominal pain (11%). Conclusions: Infused ICT may not provide adequate effectiveness in the real world. High ferritin levels seem to be associated with patient non-compliance to infused ICT, which may result from the occurrence of bothersome side effects and the burdensome mode of administration. In all patients, even those compliant, generally high ferritin levels highlight the risk for iron-overload complications. An ICT agent offering improved convenience and patient satisfaction could improve the clinical and economic outcomes of therapy. Compliance and ferritin levels associated with infused ICT Compliance (%) Patients, n (%) Mean ferritin level ± SD, ng/mL Thalassemia (n=39) 0–50 9 (23) 3615 ± 3522 51–80 14 (36) 2831 ± 2474 81+ 16 (41) 1573 ± 1694 SCD (n=6) 0–50 2 (33) 5637 ± 2850 51–80 1 (17) 3828 81+ 3 (50) 3840 ± 1965
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".