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Reflexive paired somatic and germline testing at time of medical oncology referral in mCSPC: Impact on timely treatment.

2025· article· en· W4407701628 on OpenAlexaff
Richard Gagnon, Andrew Attwell, Adam Fundytus, Joanna Vergidis, Sunil Parimi, Eric Sonke, Nimira Alimohamed, Steven Yip, Corinne Maurice Dror, Kim N., Madison Hinkley, Jean‐Michel Lavoie

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryBC Cancer Agency
Fundersnot available
KeywordsMedicineGermlineReferralSomatic cellGermline mutationOncologyInternal medicineFamily medicineMutationGenetics

Abstract

fetched live from OpenAlex

62 Background: Use of PARP inhibitors (PARPi) improves outcomes in patients with metastatic castrate-resistant prostate cancer (mCRPC) harboring germline or somatic homologous recombination repair (HRR) mutations. To ensure timely PARPi initiation, genetic results should be available at castrate resistance, with testing initiated in the metastatic castration-sensitive (mCSPC) setting. Relying on ad hoc, provider-initiated testing risks biomarker unavailability when treatment decisions are made, leading to suboptimal therapies. This study evaluates a program of reflexive paired germline and tumor testing for mCSPC patients at medical oncology referral (typically following initial management and androgen deprivation therapy [ADT] by urology or radiation oncology) as a potentially effective time point for genetic testing. Methods: This was a single cancer centre, retrospective review of mCSPC patients offered simultaneous germline and tumor tissue next-generation sequencing at medical oncology referral. We examined test completion rates, timing of results relative to key disease timepoints (ADT initiation, first-line mCRPC treatment), and the frequency of detected pathogenic mutations. Timing of results was analyzed separately for all patients, those with HRR mutations, and those with timely referrals to medical oncology, defined as <90 days from ADT start. Results: Of 218 mCSPC patients, 212 (97.2%) completed germline or tumor tissue sequencing with interpretable results from at least one assay. Germline results were obtained in 171 patients (78.4%) and tumor tissue results in 194 (88.9%). HRR mutations were detected in 29 patients (13.3%): 15 germline, 10 somatic, and 4 of unknown origin. Median time from ADT initiation to germline and tumor tissue genetic results was 165 and 120 days, respectively. Germline results were available for 144 patients (84.2%) and tumor tissue results for 176 (90.7%) before initiation of first-line mCRPC treatment. Among the 29 patients with identified HRR mutations, 19 (76%) had germline results and 17 (81%) had tumor tissue results before first-line mCRPC treatment. In the subgroup of 175 patients referred to medical oncology within 90 days of ADT initiation, 136 patients (98.6%) had germline results and 148 (99.3%) had tumor tissue results before first-line mCRPC treatment. Conclusions: Reflexive paired genetic testing at medical oncology referral is effective in identifying HRR mutations and optimizing PARPi use based on current mCRPC indications. Ensuring timely patient identification through clear and accessible genetic testing pathways will help maximize therapeutic options for patients with advanced prostate cancer. If PARPi or other targeted agents demonstrate benefit in earlier disease states, this process may need to be shifted further upstream, requiring close multidisciplinary collaboration.

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)0.003
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.114
GPT teacher head0.494
Teacher spread0.380 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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