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Record W4392139117 · doi:10.1038/s41416-024-02604-y

Fluoropyrimidine type, patient age, tumour sidedness and mutation status as determinants of benefit in patients with metastatic colorectal cancer treated with EGFR monoclonal antibodies: individual patient data pooled analysis of randomised trials from the ARCAD database

2024· article· en· W4392139117 on OpenAlexaff
Christos S. Karapetis, Hao Liu, Michael J. Sorich, Levi Pederson, Eric Van Cutsem, Tim Maughan, J.-Y. Douillard, Chris J. O’Callaghan, D. Jonker, Carsten Bokemeyer, Alberto Sobrero, Chiara Cremolini, Benoist Chibaudel, John Zalcberg, Richard Adams, Marc Buyse, Marc Peeters, Takayuki Yoshino, Aimery de Gramont

Bibliographic record

VenueBritish Journal of Cancer · 2024
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsOttawa Hospital
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsKRASMedicineOncologyInternal medicineCetuximabHazard ratioColorectal cancerPanitumumabCapecitabineConfidence intervalProgression-free survivalChemotherapyCancer

Abstract

fetched live from OpenAlex

Abstract Background KRAS mutations in metastatic colorectal cancer (mCRC) are used as predictive biomarkers to select therapy with EGFR monoclonal antibodies (mAbs). Other factors may be significant determinants of benefit. Methods Individual patient data from randomised trials with a head-to-head comparison between EGFR mAb versus no EGFR mAb (chemotherapy alone or best supportive care) in mCRC, across all lines of therapy, were pooled. Overall survival (OS) and progression-free survival (PFS) were compared between groups. Treatment effects within the predefined KRAS biomarker subsets were estimated by adjusted hazard ratio (HRadj) and 95% confidence interval (CI). EGFR mAb efficacy was measured within the KRAS wild-type subgroup according to BRAF and NRAS mutation status. In both KRAS wild-type and mutant subgroups, additional factors that could impact EGFR mAb efficacy were explored including the type of chemotherapy, line of therapy, age, sex, tumour sidedness and site of metastasis. Results 5675 patients from 8 studies were included, all with known mCRC KRAS mutation status. OS (HRadj 0.90, 95% CI 0.84–0.98, p = 0.01) and PFS benefit (HRadj 0.73, 95% CI 0.68–0.79, p < 0.001) from EGFR mAbs was observed in the KRAS wild-type group. PFS benefit was seen in patients treated with fluorouracil (HRadj 0.75, 95% CI 0.68–0.82) but not with capecitabine-containing regimens (HRadj 1.04, 95% CI 0.86–1.26) (pinteraction = 0.002). Sidedness also interacted with EGFR mAb efficacy, with survival benefit restricted to left-sided disease (pinteraction = 0.038). PFS benefits differed according to age, with benefits greater in those under 70 (pinteraction = 0.001). The survival benefit was not demonstrated in those patients with mutations found in the KRAS, NRAS or BRAF genes. The presence of liver metastases interacted with EGFR mAb efficacy in patients with KRAS mutant mCRC (pinteraction = 0.004). Conclusion The benefit provided by EGFR mAbs in KRAS WT mCRC is associated with left-sided primary tumour location, younger patient age and absence of NRAS or BRAF mutations. Survival benefit is observed with fluorouracil but not capecitabine. Exploratory results support further research in KRAS mutant mCRC without liver metastases.

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)0.016
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.017
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.331
Teacher spread0.296 · 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 designMeta-analysis
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

Citations3
Published2024
Admission routes1
Has abstractyes

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