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Real-world analysis of the impact of timing of biomarker testing on first-line treatment choice in patients with metastatic colorectal cancer in British Columbia.

2025· article· en· W4406869988 on OpenAlexaboutno aff
Tae Hoon Lee, Tharani Krishnan, Sharlene Gill

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColorectal cancerOncologyBiomarkerCancerInternal medicine

Abstract

fetched live from OpenAlex

253 Background: The treatment landscape for metastatic colorectal cancer (mCRC) has evolved significantly, shifting from chemotherapy alone to more personalized approaches that include immune checkpoint inhibitors and targeted therapies. Treatment decisions in mCRC are driven by molecular characteristics, and current guidelines recommend a minimum standard of biomarker testing, such as mismatch repair (MMR) status, and RAS and BRAF mutations, at the time of metastatic disease diagnosis to guide treatment selection. This study aimed to assess the real-world implementation of biomarker testing in a contemporary cohort of mCRC patients in British Columbia (BC) and its impact on treatment decisions by medical oncologists. Methods: We conducted a retrospective chart review of patients who received first-line systemic therapy for mCRC in BC between January 2022 and December 2023. Patient demographics, tumour characteristics, and treatment details were obtained from the BC Cancer provincial pharmacy database. Medical oncology documentation and pathology reports were reviewed to determine the availability of biomarkers, including MMR status, and RAS and BRAF mutations (OncoPanel), at the time of initial medical oncology consultation, and to assess how these results influenced treatment plan. Results: To date, 71 eligible patients have been identified, with data collection ongoing. Of these, 82% had proficient MMR status, 17% had deficient MMR status, and 1% had incomplete data. RAS mutations were present in 55% of cases, while BRAF mutations were found in 21% (Table). At the time of the initial medical oncology consultation, MMR status was unavailable in 14 patients (20%), two of whom were later found to have deficient MMR status. OncoPanel results were unavailable for 63 patients (88%) at the time of the initial consultation, and in 16 of these cases (25%), the systemic therapy plan was modified once the results were received. Conclusions: Even in contemporary practice with publicly funded biomarker testing, the results for RAS and BRAF mutations were not available at the time of initial medical oncology consultation for most patients. Biomarker testing is an essential tool for guiding therapeutic decisions in mCRC. This subsequently led to treatment plan changes in one-quarter of cases after results were received. These findings highlight the importance of timely biomarker testing to ensure optimal and efficient treatment decision-making for all mCRC patients. Metastatic colorectal cancer biomarker testing. Proficient/WT Deficient/Mutated Incomplete MMR 58 12 1 RAS 29 39 3 BRAF 53 15 3

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)0.001
metaresearch head score (Gemma)0.009
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 score0.233
Threshold uncertainty score0.469

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.464
GPT teacher head0.555
Teacher spread0.091 · 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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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