Sarcopenia Determined by Skeletal Muscle Index Predicts Overall Survival, Disease-free Survival, and Postoperative Complications in Resectable Esophageal Cancer
Bibliographic record
Abstract
BACKGROUND: Sarcopenia has been identified as a prognostic factor among certain types of cancer. In esophageal cancer, patients are at increased risk of malnutrition and sarcopenia, ultimately contributing to poor outcomes. A systematic review was conducted to determine whether sarcopenia, defined by the skeletal muscle index, is predictive of overall survival, disease-free survival, and postoperative complications in resectable esophageal cancer. MATERIALS AND METHODS: A systematic search of MEDLINE, EMBASE, Scopus, Web of Science, and Cochrane Library was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines up until January 2021. The primary outcome was overall survival; secondary outcomes included disease-free survival, pulmonary complications, and anastomotic leak. RESULTS: Twenty-one studies (4 prospective; 17 retrospective; 3966 patients) were included. Sarcopenia was present in 1940 (48.1%) patients and was associated with lower overall survival [hazard ratio (HR): 1.56; 95% confidence interval (CI): 1.25-1.95; P <0.00001; I2 =71%] and disease-free survival (HR: 1.73; 95% CI: 1.04-2.87; P =0.03; I2 =51%). A decrease in skeletal muscle index, independent of sarcopenia status, was associated with lower overall survival (HR: 1.81; 95% CI: 1.20-2.73; P =0.005; I2 =92%). Sarcopenia was associated with increased odds of pulmonary complications (odds ratio: 1.86; 95% CI: 1.29-2.66; P =0.0008; I2 =41%) and increased odds of anastomotic leak (odds ratio: 1.46; 95% CI: 1.11-1.93; P =0.008; I2 =0%). CONCLUSIONS: Sarcopenia is a predictor of overall survival, disease-free survival, and postoperative complications in patients with resectable esophageal cancer. Studies on the modifiability of sarcopenia in the preoperative period will help determine the utility of nutritional interventions.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| 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 teacher head, 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".