Iron Surveillance and Management in Gastro-Intestinal Oncology Patients: A National Physician Survey
Bibliographic record
Abstract
PURPOSE: Iron deficiency (ID) is a complication of gastrointestinal (GI) cancers that may manifest as iron deficiency anemia (IDA). Serum ferritin monitoring and oral iron supplementation have the limitations of being falsely elevated and poorly absorbed, respectively. This study aims to assess the discordance in surveillance, treatment practices, and awareness of ID/IDA in GI cancer patients by Canadian physicians treating these patients. METHODS: From February 2020 to September 2021, a 22-question electronic survey was sent to medical oncologists (MOs), surgical oncologists (SOs), and gastroenterologists (GEs). The survey collected information about four domains: physician demographics, surveillance practices, treatment practices, and awareness of ID/IDA in GI cancer patients and ASCO/ASH guidelines. RESULTS: A total of 108 (34 MOs, 19 SOs, and 55 GEs) of the 872 (12.4%) invited physicians completed the survey. Of these, 26.5% of MOs, 36.8% of SOs, and 70.9% of GEs measured baseline iron parameters, with few continuing surveillance throughout treatment. Ferritin was widely measured by MOs (88.9%), SOs (100%), and GEs (91.4%). Iron was supplemented if ID/IDA was identified pre-treatment by 66.7% of MOs, 85.7% of SOs, and 94.2% of GEs. Parenteral iron was prescribed by SOs (100%), while oral iron was prescribed by MOs (83.3%) and GEs (87.9%). Only 18.6% of physicians were aware of the ASCO/ASH guidelines regarding erythropoiesis-stimulating agents with parenteral iron for treating chemotherapy-induced anemia. CONCLUSION: Results illustrate variations in practice patterns for IDA management across the different physician specialties. Moreover, there appeared to be gaps in the knowledge and care surrounding evidence-based IDA management principles which may contribute to poor clinical outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".