Predicting overall survival (OS) in patients (pts) with metastatic colorectal cancer (mCRC) treated with chemotherapy (CT): The British Columbia Cancer Agency (BCCA) mCRC score.
Bibliographic record
Abstract
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]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".