Potential Regional Differences for the Tolerability Profiles of Fluoropyrimidines
Bibliographic record
Abstract
PURPOSE: We conducted a retrospective analysis of safety data from randomized, single-agent fluoropyrimidine clinical trials (bolus fluorouracil/leucovorin [FU/LV] and capecitabine) to test the hypothesis that there are regional differences in fluoropyrimidine tolerability. METHODS: Treatment-related safety data from three phase III clinical studies were analyzed by multivariate analysis: two comparing capecitabine with bolus FU/LV in metastatic colorectal cancer (MCRC) and one comparing capecitabine plus oxaliplatin (XELOX) with bolus FU/LV as adjuvant treatment for colon cancer. The United States (US) was compared with non-US countries (all three studies) and with the rest of the world and East Asia (adjuvant study). RESULTS: In the MCRC studies (n = 1,189), more grade 3/4 adverse events (AEs; relative risk [RR], 1.77), dose reductions (RR, 1.72), and discontinuations (RR, 1.83) were reported in US versus non-US patients. Likewise, in the adjuvant colon cancer study (n = 1,864), more grade 3/4 AEs (RR, 1.47) and discontinuations (RR, 2.09) were reported in US versus non-US patients. After further dividing non-US patients into those in East Asia and the rest of the world, differential RRs for related grade 3/4 AEs, grade 4 AEs, and serious AEs were again observed, with East Asian patients having the lowest and US patients the highest RR. CONCLUSION: Regional differences exist in the tolerability profiles of fluoropyrimidines. More treatment-related toxicity was reported in the US compared with the rest of the world for bolus FU/LV and capecitabine in first-line MCRC and adjuvant colon cancer. In the adjuvant setting, a range of fluoropyrimidine tolerability was observed, with East Asian patients having the lowest, and US patients the highest, RR.
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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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".