Impact of pretreatment dihydropyrimidine dehydrogenase genotype‐guided fluoropyrimidine dosing on chemotherapy associated adverse events
Bibliographic record
Abstract
Consensus guidelines exist for genotype-guided fluoropyrimidine dosing based on variation in the gene dihydropyrimidine dehydrogenase (DPYD). However, these guidelines have not been widely implemented in North America and most studies of pretreatment DPYD screening have been conducted in Europe. Given regional differences in treatment practices and rates of adverse events (AEs), we investigated the impact of pretreatment DPYD genotyping on AEs in a Canadian context. Patients referred for DPYD genotyping prior to fluoropyrimidine treatment were enrolled from December 2013 through November 2019 and followed until completion of fluoropyrimidine treatment. Patients were genotyped for DPYD c.1905+1G>A, c.2846A>T, c.1679T>G, and c.1236G>A. Genotype-guided dosing recommendations were informed by Clinical Pharmacogenetics Implementation Consortium guidelines. The primary outcome was the proportion of patients who experienced a severe fluoropyrimidine-related AE (grade ≥3, Common Terminology Criteria for Adverse Events version 5.0). Secondary outcomes included early severe AEs, severe AEs by toxicity category, discontinuation of fluoropyrimidine treatment due to AEs, and fluoropyrimidine-related death. Among 1394 patients, mean (SD) age was 64 (12) years, 764 (54.8%) were men, and 47 (3.4%) were DPYD variant carriers treated with dose reduction. Eleven variant carriers (23%) and 418 (31.0%) noncarriers experienced a severe fluoropyrimidine-related AE (p = 0.265). Six carriers (15%) and 284 noncarriers (21.1%) experienced early severe fluoropyrimidine-related AEs (p = 0.167). DPYD variant carriers treated with genotype-guided dosing did not experience an increased risk for severe AEs. Our data support a role for DPYD genotyping in the use of fluoropyrimidines in North America.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".