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Record W7133200569 · doi:10.51731/cjht.2025.1360

Dihydropyrimidine Dehydrogenase Deficiency Testing for Patients Treated With 5-Fluorouracil and Capecitabine

2025· article· W7133200569 on OpenAlexaboutno aff
CDA-AMC

Bibliographic record

VenueCanadian Journal of Health Technologies · 2025
Typearticle
Language
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDPYDDihydropyrimidine dehydrogenaseCapecitabineGenotypingAdverse effectGenetic testingGlucose-6-phosphate dehydrogenase deficiency

Abstract

fetched live from OpenAlex

What Is the Issue? Fluoropyrimidines, such as 5-fluorouracil and capecitabine, are drugs used for the treatment of solid tumour cancers. Deficiency in the enzyme dihydropyrimidine dehydrogenase (DPD), which breaks down these drugs, can significantly increase the risk of severe toxicity and death. Pretreatment DPD deficiency testing, via genotyping, or phenotyping, followed by dose adjustments is recommended in several countries to reduce adverse drug reactions. However, most evidence is based on genetic variants identified in individuals from European countries such as the Czech Republic, Denmark, France, Ireland, Italy, the Netherlands, Spain, and the UK. This raises uncertainties about the transferability of the safety and effectiveness of these approaches to patients from diverse ethnic origins. In Canada, access to DPD deficiency testing is inconsistent and varies widely across provinces and territories. What Did We Do? We conducted a national survey on the current state of DPD deficiency testing and a rapid review to identify and summarize evidence comparing the clinical and cost-effectiveness of DPD deficiency testing and test-guided dose adjustments versus usual care. We searched key resources, including journal citation databases, and conducted a focused internet search for relevant evidence published since 2015. One reviewer screened articles for inclusion based on predefined criteria, critically appraised the included studies, and narratively summarized the findings. What Did We Find? The survey results suggest that DPYD genotyping is conducted in 5 Canadian provinces, and 2 more are set to start testing later this year. One province indicated that they conduct both DPYD genotyping and DPD phenotyping, as required. The cost of testing ranged from CA$50 to CA$500 and was dependent on the testing platform and required turnaround time. The evidence suggests that DPYD variant carriers are at a higher risk of severe toxicities, hospitalization, and death compared to patients with the wild-type gene and that genotype-guided dose adjustments may improve these clinical outcomes in variant carriers. The data for the clinical utility of genotype-guided dosing is based largely on study populations from European countries, decreasing the utility of genotype testing in Canada, where the target population includes numerous ethnic origins. Further research and guideline development to support the validity and utility of variants more common in these groups. Phenotype testing provides an appealing complementary or alternative test that is independent of ethnic origin; however, evidence supporting its clinical validity and utility is minimal. Evidence suggests that DPYD testing with subsequent genotype-guide dose adjustments is cost-effective compared to usual care. No evidence was found on the cost-effectiveness of an extended DPYD genetic panel or of DPD phenotyping. What Does This Mean? Based on the evidence identified in this report, DPYD genotyping may be clinically valid and cost-effective to improve the safety of fluoropyrimidine use in Canada for patients of European descent. Clinicians and decision-makers can use the evidence summarized in this review to inform decisions regarding the implementation of DPD deficiency testing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.131
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.131
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.024
GPT teacher head0.279
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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