Iron deficiency anemia in gastric cancer: a Canadian retrospective review
Bibliographic record
Abstract
BACKGROUND: Gastric cancer is highly prevalent amongst men and women. Previous studies have described the high prevalence of iron deficiency anemia (IDA) in gastrointestinal cancer patients, but few have focused on the gastric cancer population. We aimed to determine the point prevalence of patients with gastric cancer who developed IDA and chemotherapy-induced anemia, and to identify types and frequencies of IDA therapies. PATIENTS AND METHODS: A retrospective review was carried out for 126 gastric cancer patients from 2006 to 2016 at St Michael's Hospital, Toronto, Canada. Patient demographics, laboratory (ferritin, iron parameters) and clinical data regarding IDA were reviewed. IDA was defined as transferrin saturation less than 20%, ferritin less than 100 μg/l, and hemoglobin less than 130 g/l in men and less than 120 g/l in women. RESULTS: Of the 126 patients with gastric cancer identified (median age 70, interquartile range: 59-77), 64.3% were men. Only 18.3% of patients had a self-reported history of IDA, 40% had IDA at the time of gastric cancer diagnosis, and 58.7% were anemic. A total of 77 patients received chemotherapy, and of these, 54.2% developed chemotherapy-induced anemia. At the final follow-up, 21.4% of patients were diagnosed with IDA along their treatment course, and 79.4% were anemic. Red blood cell transfusions were most frequently prescribed (48.4%; median: 4 U; interquartile range: 2-6), compared with oral (31.8%) or intravenous iron (16.7%) therapy. CONCLUSION: The point prevalence of IDA was high in our gastric cancer patients despite inconsistent screening for IDA. Our findings indicate the need for a consistent diagnostic and therapeutic approach to IDA in this vulnerable patient population.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".