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Predicting overall survival (OS) in patients (pts) with metastatic colorectal cancer (mCRC) treated with chemotherapy (CT): The British Columbia Cancer Agency (BCCA) mCRC score.

2013· article· en· W4232398903 on OpenAlexaffabout
Gillian Gresham, Winson Y. Cheung, Matthew Chan, Jason Kim, Daniel J. Renouf

Bibliographic record

VenueJournal of Clinical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsMcMaster UniversityBC Cancer AgencyUniversity of Ottawa
Fundersnot available
KeywordsMedicineColorectal cancerInternal medicineProportional hazards modelCohortUnivariate analysisClinical endpointCancerLymphovascular invasionPrimary tumorOncologyMultivariate analysisSurgeryRandomized controlled trialMetastasis

Abstract

fetched live from OpenAlex

419 Background: Median OS of mCRC is 2 years, but the prognosis of individual pts can be highly variable. Our study objective was to develop a scoring system to improve the prognostication of mCRC pts at baseline assessment. Methods: Pts diagnosed with mCRC from 2006 to 2008, referred to 1 of 5 regional cancer centers in British Columbia, and received CT were reviewed. Pts with ECOG >3 were excluded due to their uniform poor prognosis. Univariate analyses were performed on baseline variables and those significantly associated with prognosis were included in a multivariate stepwise selection. Each significant factor was given a weighted score (range 1-5) based on the regression coefficients. Patients were assigned a composite risk score (range 0-15) based on their baseline variables, and then separated into quartiles for OS using cut-point analysis and Kaplan-Meier methods. Validation was conducted with the bootstrap technique. C-index statistic was 0.75, which indicated good discrimination. Results: A total of 505 mCRC pts were included: median age 63 (range 22-86), 58% male, 75% ECOG 0-1, 58% colon primary, 34% >1 metastatic site, and 46% smokers. Median pre-treatment CEA was 16.8 ng/ml. In this cohort, 64% were metastatic at presentation, 81% underwent primary tumor resection, 23% received prior adjuvant CT, and 72% were treated with palliative CT. ECOG 2-3 (HR 3.1, 95%CI 2.4-4.2), no primary resection (HR 2.3, 95%CI 1.6-3.3), colon primary (HR 1.6, 95%CI 1.2-2.1), >1 metastatic site (HR 1.6, 95%CI 1.2-2.1), CEA level >4 ng/ml (HR 1.2, 0.8-1.6), male (HR 1.2, 95%CI 0.8-1.6), and smoker (HR 1.4, 95%CI 1.0-1.8) were significant in the multivariate model and assigned points corresponding to their effect size. Median OS varied significantly depending on the composite risk score (Table). Conclusions: In this population-based analysis, the BCCA mCRC score was a simple method that used baseline variables to improve the prognostication of mCRC pts. This model requires external validation. [Table: see text]

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)0.000
metaresearch head score (Gemma)0.001
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 score0.980
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.373
Teacher spread0.320 · 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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Citations1
Published2013
Admission routes2
Has abstractyes

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