Survival impact of surgical resection of primary tumor in patients with stage IV colorectal cancer: Results from a large population‐based cohort study
Bibliographic record
Abstract
BACKGROUND: Currently, there is very low-quality evidence available regarding benefit of surgical resection of the primary tumor (SRPT), in patients with stage IV colorectal cancer (CRC). In the absence of randomization, the reported benefit may reflect selection of younger and healthier patients with good performance status. A large population-based cohort study was undertaken to determine the survival benefit of SRPT in advanced CRC by eliminating various biases reported in the literature. METHODS: A retrospective cohort study involving patients with stage IV CRC, diagnosed between 1992 and 2005, in the province of Saskatchewan, Canada. Survival was estimated by using the Kaplan-Meier method. Survival distribution was compared by log-rank test. Cox proportional multivariate regression analysis was performed to determine survival benefit of SRPT by controlling other prognostic variables. RESULTS: A total of 1378 eligible patients were identified. Their median age was 70 years (range, 22-98 years) and male:female ratio was 1.3:1; 944 (68.5%) of them underwent SRPT. Among 1378 patients, 42.3% received chemotherapy and 19.1% received second-generation therapy. Patients who underwent SRPT and received chemotherapy had median overall survival of 18.3 months (95% confidence interval [CI] = 16.6-20 months) compared with 8.4 months (95% CI = 7.1-9.7 months) if they were treated with chemotherapy alone (P < .0001). Cox proportional analysis revealed that use of chemotherapy (hazard ratio [HR] = 0.47, 95% CI = 0.41-0.54), SRPT (HR = 0.49, 95% CI = 0.41-0.58), second-line chemotherapy (HR = 0.47, 95% CI = 0.45-0.64), and metastasectomy (HR = 0.54, 95% CI = 0.45-0.64) were correlated with superior survival. CONCLUSIONS: SRPT improves survival in patients with stage IV CRC, independent of other prognostic variables including age, performance status, comorbid illness and chemotherapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".