AB025. 155. Sarcopenia is highly prevalent and associated with poorer outcomes in pancreatic and oesophagogastric cancer: systematic review and meta-analysis
Bibliographic record
Abstract
Background: Sarcopenia is a depletion of skeletal muscle mass associated with increased morbidity and mortality in gastrointestinal malignancy. It has been increasingly reported with the recent advent of software to measure sarcopenia using standard staging CT. Patients with pancreatic, oesophageal and gastric cancer are potentially at increased risk due to nutritional complications. The aim of this review was to determine the prevalence and impact of sarcopenia in these malignancies. Methods: Systematic literature search of Medline and Embase databases was developed with a medical librarian and performed by two investigators following the PRISMA guidelines (search period 1990–August 2017). Studies were included if prevalence and method of sarcopenia measurement were reported. Other outcome measures included effect on morbidity and survival. Studies were grouped into pancreatic and oesophagogastric for analysis. Pooled estimation (ES) for prevalence was computed using random effects model and presented with 95% CI. Results: After screening 473 titles, 17 observational studies (4,206 patients) in pancreatic and 30 studies (5,561 patients) in oesophagogastric were analyzed. Prevalence of sarcopenia was higher in pancreatic cancer (49.6%) compared to oesophagogastric (34%) ES 0.49 (0.39–0.59) vs. 0.34 (0.27–0.4) There was significant heterogeneity regarding definition of sarcopenia and reporting of outcome measures. In studies with sufficient data, sarcopenia was independent of BMI and independently associated with poorer survival and higher post-operative complications. Conclusions: Sarcopenia detected during staging CT was present in half and one third of patients with pancreatic and oesophagogastric cancers respectively and is a poor prognostic indicator. This justifies further research into the mechanism and potential treatment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".