Transfusion-Related Iron Overload: A Covert Risk Of Supportive Cancer Care
Bibliographic record
Abstract
Abstract Background Chronic transfusion support plays a key role in survival and quality of life for patients with hematological disorders. However, transfusion-related iron overload (TRIO) is a significant cause of morbidity and mortality in these patients.Adequate iron overload (IO) screening and use of iron chelators, if necessary, is now standard practice in chronically transfused individuals such as hemoglobinopathy patients. Screening practices for IO for patients receiving multiple red blood cell (RBC) transfusions for other reasons (e.g. cancer) are unknown. Objective This two part study aimed to detect pediatric (Jaffer et al., 2012) and adult populations at risk for TRIO and to evaluate and compare current screening practices. Methods Children (≤ 18 years) and adults (> 18 years) receiving at least 1 RBC transfusion from January 1, 2008 to December 31, 2011 at a tertiary care academic institution were identified using a transfusion registry database. Only those receiving chronic RBC transfusions were included in the study. Chronic transfusion was defined as ≥20 units of RBC or ≥ 20 RBC transfusions dosed at 15ml/kg within 12 consecutive months where transfusions were not given in the setting of an operating room, trauma or surgical procedures, not given 7 days prior/post-surgical procedures and not all given in one day. An adjudicator resolved study inclusion ambiguity. The analysis excluded hemoglobinopathy patients. Medical records were reviewed to collect patient demographics, diagnosis, and to evaluate IO screening practices and frequency of iron chelation therapy. Results A total of 343 patients met the eligibility criteria: 27 pediatric and 316 adult patients, with mean ages of 8.1 years (SD 5.7) and 62 years (SD 12.6), respectively. Table 1 summarizes demographics, number of transfusions, and IO screening and results. Ferritin levels were checked for 12 (44%) pediatric and 227 (72%) adult patients: 2 (17%) pediatric and 30 (13%) adult patients had values<500 μg indicating no further TRIO screening was required. In the pediatric population, 81% had a cancer diagnosis, and just under a third were tested for ferritin, whereas 64% of the adults had cancer, with nearly two-thirds tested for ferritin. A statistically significant difference was observed in the percentage of pediatric and adult cancer patients screened for IO. Of those cancer patients screened, ferritin level > 500 occurred in 71% of pediatric and 85% of adult patients, with an iron chelator reported in 1 adult. Total RBC transfusions ranged from 20 to 44 with a median of 26.5 for pediatrics and 20 to 176 with a median of 31 for adults. Conclusion Despite high rates of RBC transfusion, screening for TRIO was inconsistent. Although information regarding reasons for not screening for TRIO or not treating with chelation therapy was not collected, the possibilities include a lack of awareness of the risk of TRIO and lack of access to ferriscan and/or to oral iron chelator in Canada for conditions other than hemoglobinopathy and a select subset of MDS cases. Considering TRIO presents an additional, yet unidentified, co-morbidity of cancer therapy and that the therapy (e.g. anthracyclines) may potentiate the end organ effect of TRIO, it is vital to develop strategies to evaluate cancer patients at risk for TRIO and ensure they have access to appropriate iron chelation therapy. Research is needed to explore the comorbidities associated with failure to treat TRIO and to identify barriers to treatment so cancer patients can receive optimal care. Disclosures: Leber: Novartis Canada: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau. Heddle:Canadian Blood Services and Health Canada: Research Funding.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".