Survival of metastatic colorectal cancer patients treated with chemotherapy in Alberta (1995–2004)
Bibliographic record
Abstract
GOALS OF WORK: Clinical trials have suggested that advances in chemotherapy significantly improve the survival of patients with metastatic colorectal cancer. Comparable evidence from clinical practice is scarce. This study aims to investigate the survival of patients with metastatic colorectal cancer treated with chemotherapy in Alberta, Canada. PATIENTS AND METHODS: Trends of relative survival of patients diagnosed in 1994-2003 were assessed using Alberta Cancer Registry (ACR) data. The median overall survival (OS) of patients diagnosed in 2004 was determined by linking Cancer Registry data with Electronic Medical Records (EMR). Cox regression models were fitted to calculate the hazard ratio for patients treated with chemotherapy. RESULTS: The 2-year relative survival for patients with metastatic colorectal cancer who received chemotherapy increased significantly from 29% to 41% over the 10 years (1994-2003, p < 0.015). A 69% reduction in the risk of mortality was observed in the 168 patients who received chemotherapy compared to the 87 patients who did not, after adjusting for age, gender, and number of metastases. The median OS of patients who received chemotherapy was 17.5 months. This is comparable to the 18-20 months seen in recently published clinical trials, considering the patients in this study were from the real clinical practice, nearly half of them were older than 70, and many of them might have important co-morbidities. CONCLUSIONS: The survival of patients diagnosed with metastatic colorectal cancer in Alberta has improved in recent years; this is most likely attributable in large part to the use of 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".