Comorbidity and overall survival (OS) in cetuximab-treated patients with advanced colorectal cancer (ACRC)—Results from NCIC CTG CO.17: A phase III trial of cetuximab versus best supportive care (BSC)
Bibliographic record
Abstract
4074 Background: The interplay between comorbidity, age and performance status (PS) as predictors of outcome in ACRC is not well described. We examined these factors as predictors of treatment toxicity and outcome in cetuximab-treated patients with ACRC. Methods: Comorbidity was independently evaluated by 2 physicians using the Charlson Comorbidity Index (CCI), a previously validated measure of comorbidity based on the presence or absence of index medical conditions weighted according to their affect on mortality. CCI score was correlated with demographic data (age, gender), PS, site of primary, time from diagnosis to randomization, body mass index, hemoglobin, alkaline phosphatase (ALP), lactate dehydrogenase (LDH), creatinine clearance, K-ras status and OS. Results: 572 patients were included. 41% were ≥65 years and 25% had comorbidities at randomization. CCI score was 1 in 21% and ≥ 2 in 4%. In multivariate analysis (MVA) of all covariates, only older age (≥65 years) was associated with greater comorbidity (p=0.005). OS was different among 3 comorbidity groups (CCI score 0, 1, ≥ 2) in univariate analysis (median OS 4.9 vs 5.9 vs 4.8 months;, logrank p=0.04) but not in MVA. Conversely, lower PS remained associated with better OS in MVA (HR 1.96 for PS=2 vs. PS=0, p<0.0001). Age was not associated with OS (p=0.11). Other factors significantly associated with OS in MVA included time from diagnosis to randomization, LDH, ALP, hemoglobin, Kras status and cetuximab treatment. In the BSC arm, comorbidity was not associated with OS in MVA (HR 0.83 CCI 1 vs. CCI0, p=0.26 and HR 0.90 for CCI2 vs. CCI0, p=0.78) suggesting comorbidity is not prognostic in this setting. Patients with higher CCI score had a nonsignificant trend toward greater treatment effects. Patients ≥65 years had less gr≥3 vomiting (1.8 vs 7.9%, p=0.034) but more dyspnea (24.5 vs 11.2%, p=0.005). Patients with higher CCI scores had less vomiting (p=0.008) but more non-neutropenic infection (p=0.012). Conclusions: In this clinical trial, comorbidity and age were not independent predictors of survival, highlighting the difference between comorbidity and PS. [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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".