The deterioration of muscle mass and radiodensity is prognostic of poor survival in stage I–III colorectal cancer: a population‐based cohort study (<scp>C‐SCANS</scp>)
Bibliographic record
Abstract
BACKGROUND: Muscle abnormalities such as low muscle mass and low muscle radiodensity are well known risk factors for unfavourable cancer prognosis. However, little is known in regard to the degree and impact of longitudinal changes in muscle mass and radiodensity within the context of cancer. Here, we explore the relationship between muscle wasting and mortality in a large population-based study of patients with non-metastatic colorectal cancer (CRC). METHODS: A total of 1924 patients with stage I-III CRC who underwent surgical resection in the Kaiser Permanente Northern California Health System were included. Muscle mass and radiodensity were quantified using computed tomography images obtained at diagnosis and after approximately 14 months. Cox proportional-hazards models were used to estimate hazard ratios for all-cause mortality. RESULTS: The hazard ratio for all-cause mortality among patients with the largest deterioration in muscle mass (≥2 SD; ≥11.4% loss from baseline), as compared with those who remained stable (±1 SD; 0.0 ± 5.7%) was 2.15 [95% confidence interval (CI): 1.59-2.92; P < 0.001]. The hazard ratio for all-cause mortality among patients who experienced the largest deterioration in muscle radiodensity (≥2 SD; ≥20.2% loss from baseline), as compared with those who remained stable (±1 SD; 0.0 ± 10.1%) was 1.61 (95% CI: 1.20-2.15; P = 0.002). CONCLUSIONS: In patients with stage I-III CRC, muscle wasting is a risk factor for mortality, independent of change in body mass and other body composition parameters.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".