Sarcopenia as a prognostic indicator in colorectal cancer: an updated meta-analysis
Bibliographic record
Abstract
Background: Sarcopenia, often observed in the elderly, is associated with declining skeletal muscle mass and impaired muscle function. This condition has been consistently linked to a less favorable prognosis in various malignancies. Computed tomography (CT) is a frequently employed modality for evaluating skeletal muscle mass, enabling the measurement of the skeletal muscle index (SMI) at the third lumbar vertebra (L3) level. This measurement serves as a defining criterion for sarcopenia. The meta-analysis dealt with evaluating the promise sarcopenia held as a prognostic indicator in individuals with colorectal cancer. Methods: Research relevant to the subject was determined by systematically searching PubMed, Embase, Web of Science, WANFANG, and CNKI (up to June 11, 2023, published studies). In this meta-analysis, the incidence of sarcopenia in individuals with colorectal cancer was combined to analyze the disease-free survival (DFS), overall survival (OS), and cancer-specific survival (CSS) of these individuals with and without sarcopenia. The included research was evaluated for quality per the Newcastle-Ottawa Scale (NOS) score. In the multivariate analysis of each study, the direct extraction of hazard ratio (HR) with a 95% confidence interval (CI) was executed. STATA 11.0 was applied to integrate and statistically analyze the data. Results: Overall 20 articles participated in this meta-analysis. A 34% incidence of sarcopenia was noted in colorectal cancer. The presence of sarcopenia denoted a decrease in OS (HR=1.72,95% CI=1.45-2.03), DFS (HR=1.42,95% CI=1.26-1.60) and CSS (HR=1.48,95% CI=1.26-1.75) in individuals with colorectal cancer. In addition, the subgroup analysis depicted a pattern consistent with the overall analysis results. Conclusion: CT-defined sarcopenia exhibits promise as an indicator of survival prognosis in individuals with colorectal cancer. Future studies need a more rigorous definition of sarcopenia to further verify these findings. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023431435.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.040 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".