Pharmacogenetic study in gastric cancer patients treated with adjuvant fluorouracil/leucovorin or epirubicin/cisplatin/fluorouracil before and after chemoradiation on CALGB 80101 (Alliance)
Bibliographic record
Abstract
There is a lack of pharmacogenetic predictors of outcome in gastric cancer patients. The aim of this study was to assess previously identified candidate genes associated with 5-fluorouracil (5-FU), cisplatin, or epirubicin toxicity or response in a cohort of resected gastric cancer patients treated on CALGB (Alliance) 80101. Gastric or gastroesophageal cancer patients randomized to adjuvant 5-FU/leucovorin or epirubicin/cisplatin/5-FU before and after 5-FU chemoradiation were genotyped for single nucleotide polymorphisms (SNPs) in GSTP1 (rs1695), ERCC1 (rs11615 and rs3212986), XRCC1 (rs25487), UGT2B7 (rs7439366) and the 28 base-pair tandem repeats in TYMS (rs34743033). Logistic regression and log rank tests were used to assess the association between each SNP and incidence of grade 3/4 neutropenia and leukopenia, overall (OS) and progression-free survival (PFS), respectively. Toxicity endpoint analyses were adjusted for the treatment arm, while OS and PFS were also adjusted for performance status, sex, age, lymph node involvement, and primary tumor site and size. Of 281 subjects with successful genotyping results and available clinical (toxicity and efficacy) data, 166 self-reported non-Hispanic White patients were included in the final analysis. There was a lack of evidence of an association among any SNPs tested with grade 3/4 neutropenia and leukopenia or OS and PFS. Age, lymph node involvement, and primary tumor size were significantly associated with OS and PFS. This study failed to confirm results of previous gastric cancer pharmacogenetic studies.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".