Change in Skeletal Muscle Following Resection of Stage I–III Colorectal Cancer is Predictive of Poor Survival: A Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Sarcopenia at time of diagnosis predicts worse survival outcomes. It is currently unknown how changes in muscle mass over time interact with sarcopenia in colorectal patients treated with curative intent. Objectives of this study were to quantify sarcopenia and skeletal muscle loss from time of diagnosis to end of surveillance and determine its effect on survival outcomes after completion of 2 years of surveillance. METHODS: Retrospective cohort study of stage I-III colorectal cancer patients from 2007-2009, who underwent resection and had preoperative and 2-year surveillance computed tomography scans, without recurrence during that time. Body composition analysis was done at both time points to determine lumbar skeletal muscle index, radiodensity and adiposity. Change over time was standardized as a percentage per year. Cox proportional hazard regression modeling was used for survival analysis. RESULTS: Of 667 patients included, median survival from surgery was 7.96 years, with 75 recurrences occurring after 2 years. On average patients lost muscle mass (-0.415%/year; CI -0.789, -0.042) and radiodensity (-5.76 HU/year; CI -6.74, -4.80), but gained total adipose tissue (7.06%/year; CI 4.34, 9.79). Patients with sarcopenia at diagnosis (HR 1.80; CI 1.13, 2.85) or muscle loss over time (HR 1.55; CI 1.01, 2.37) had worse overall survival, with significantly worse joint effect (HR 2.73; CI 1.32, 5.65). CONCLUSIONS: Sarcopenia at diagnosis combined with ongoing skeletal muscle loss over time resulted in significantly worse survival. Patients with these features who are recurrence-free at 2 years are more likely to have a non-colorectal cancer cause of death.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it