Pharmacogenetic‐guided dosing for fluoropyrimidine (<i>DPYD</i>) and irinotecan (<i>UGT1A1*28</i>) chemotherapies for patients with cancer (<scp>PACIFIC</scp>‐<scp>PGx</scp>): A multicenter clinical trial
Bibliographic record
Abstract
PACIFIC-PGx evaluated the feasibility of implementing pharmacogenetics (PGx) screening in Australia and the impact of DPYD/UGT1A1 genotype-guided dosing on severe fluoropyrimidine (FP) and irinotecan-related toxicities and hospitalizations, compared to historical controls. This prospective single arm trial enrolled patients starting FP/irinotecan for any cancer between 7 January 2021 and 25 February 2022 from four Australian hospitals (one metropolitan, three regional). During the accrual period, 462/487 (95%) consecutive patients screened for eligibility for DPYD and 50/109 (46%) for UGT1A1 were enrolled and genotyped (feasibility analysis), with 276/462 (60%) for DPYD and 30/50 (60%) for UGT1A1 received FP/irinotecan (safety analysis). DPYD genotyping identified 96% (n = 443/462) Wild-Type, 4% (n = 19/462) Intermediate Metabolizers (50% dose reduction), and 0% Poor Metabolizers. UGT1A1 genotyping identified 52% (n = 26/50) Wild-Type, 40% (n = 20/50) heterozygous, and 8% (n = 4/50) homozygous (30% dose reduction). Key demographics for the FP/irinotecan safety cohorts included: age range 23-89/34-74 years, male 56%/73%, Caucasian 83%/73%, lower gastrointestinal cancer 50%/57%. Genotype results were reported prior to cycle-1 (96%), average 5-7 days from sample collection. PGx-dosing for DPYD variant allele carriers reduced high-grade toxicities compared to historic controls (7% vs. 39%; OR = 0.11, 95% CI 0.01-0.97, p = 0.024). High-grade toxicities among Wild-Type were similar (14% vs. 14%; OR = 0.99, 95% CI 0.64-1.54, p = 0.490). PGx-dosing reduced FP-related hospitalizations (-22%) and deaths (-3.7%) compared to controls. There were no high-grade toxicities or hospitalizations for UGT1A1*28 homozygotes. PGx screening and prescribing were feasible in routine oncology care and improved patient outcomes. Findings may inform expanded PGx programs within cancer and other disease settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".