Improving dihydropyrimidine dehydrogenase genotyping (DPYD) prior to initiation of fluoropyrimidine-based chemotherapy at a community-based hospital: A quality improvement initiative.
Bibliographic record
Abstract
347 Background: Dihydropyrimidine dehydrogenase gene (DPYD) testing is crucial in preventing toxicities from fluoropyrimidine chemotherapy. Despite benefits and established guidelines, its adoption within healthcare organizations remains inconsistent and suboptimal. We implemented a quality improvement project to improve DPYD testing prior to fluoropyrimidine chemotherapy at a community-based hospital. We aimed to increase DPYD testing for patients receiving fluoropyrimidine-based chemotherapy from 65% to 95% between July 2023 to July 2024. Balancing measures included DPYD testing turnaround time. Methods: For baseline diagnostics, manual chart review was performed on 126 patients to identify frequency of DPYD testing, and turnaround time (TAT) between May 1, 2023 to August 4, 2023. Patients were excluded if they received fluoropyrimidine-based chemotherapy prior to May 1, 2023. A multidisciplinary team including medical oncology residents and staff, pharmacists, nurses, and clinical informatics specialists worked jointly to identify and address barriers to implementation. Barriers identified included lack of established workflows and awareness of the importance of testing. Diagnostic tools utilized included Ishikawa diagrams and process mapping. The team used Plan-Do-Study-Act (PDSA) cycles to address barriers. A p-chart was used to analyze the results. Results: The baseline DPYD testing rate was 65%. Barriers identified via multidisciplinary sessions included lack of established workflow, awareness and importance of testing. PDSA cycles included education sessions to breast medical oncologists and medical oncology nurses, and development of a best-practice advisory in the electronic medical record. The percentage of eligible patients receiving DPYD testing increased from 65% to 95.8% in the total population. For breast cancer patients, the rate increased from 16.7% to 100%. For gastrointestinal cancer patients, the rate increased from 56.1% to 94.2%. Sustainability was demonstrated two months post-intervention with TAT stable between 7-8 days. Conclusions: Through PDSA cycles, we improved the frequency of DPYD testing for patients receiving fluoropyrimidine chemotherapy from 65% to 95.8%. Future work will assess changes in chemotherapy prescribing behavior in the setting of variant DPYD results, and outcomes of patients with variant DPYD testing.
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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 | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".