Cost-Effectiveness of UGT1A1*28 Genotyping in Preventing Severe Neutropenia Following FOLFIRI Therapy in Colorectal Cancer.
Bibliographic record
Abstract
PURPOSE: Functional polymorphisms of the UGT1A1 gene, particularly the UGT1A1*28 variant, are associated with the severity of the bone marrow suppression in patients with metastatic colorectal cancer receiving irinotecan. This study assesses the cost-effectiveness of screening for UGT1A1*28 polymorphism associated with primary prophylactic Granulocytes Colony Stimulating Factor in patients homozygous for the *28 allele. The effectiveness was estimated based on the number of neutropenia avoided. METHODS: We modelled a theoretical population treated with combined 5-fluorouracil, leucovorin and irinotecan (FOLFIRI) for metastatic colorectal cancer. A decision tree simulated the health outcomes, measured by the prevalence of neutropenic events for two strategies, with or without UGT1A1 genotype screening. The model incorporated direct hospital costs and was validated with a sensitivity analysis. We calculated the cost-effectiveness ratio: CE=∆C / ∆E = "genotyping" cost - "no genotyping" cost / number of febrile neutropenia avoided. RESULTS: In the "genotyping strategy", the cost to avoid one febrile neutropenia event per 1000 patients treated was € 942.8 to € 1090.1. The sensitivity analysis showed a better CE ratio of € 733.4 to € 726.6 per febrile neutropenic event avoided. CONCLUSIONS: UGT1A1 genotype screening before irinotecan treatment is a cost-efficient strategy for the hospital. Systematic genotyping prior to chemotherapy, and administration of CSF in patients homozygotes for the *28 allele allow to avoid 91 febrile neutropenias at an acceptable cost.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 teacher head, 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".