Prognostic significance of sarcopenia in metastatic esophageal squamous cell carcinoma.
Bibliographic record
Abstract
4068 Background: Sarcopenia is defined as low skeletal muscle mass and represents a quantifiable marker of frailty. Disease related symptoms of anorexia, nausea and dysphagia, in addition to reduced physical activity contribute to muscle wasting in metastatic esophageal squamous cell cancer (MESCC) patients. This study set out to evaluate the prognostic utility of sarcopenia and its association with nutritional indices. Methods: MESCC patients (pts) with available abdominal CT imaging, attending Princess Margaret Cancer Centre between 2011 and 2016, were identified from the institutional database. Skeletal muscle index (SMI), normalized by height, was calculated at the third lumbar (L3) vertebra using SliceOMatic software. SMI cutoffs for sarcopenia were 34.4cm2/m2 in females and 45.4cm2/m2 in males based on previously established consensus. Nutritional risk index (NRI) was calculated using weight and albumin with malnutrition defined as < 97.5. Results: Of the 58 pts analyzed, 26 presented with de novo MESCC, median age was 64 (range 48-85), 30 pts were ECOG PS ≤1 and 45% received systemic therapy. 93% of pts experienced weight loss > 5% in the 3 months preceding diagnosis and median BMI was 20.4 (range 16.3-34.9). Twenty-four (41%) pts were sarcopenic (SP) with differences in BMI and NRI (p < 0.05) compared to non-sarcopenic (NSP) pts. Median BMI in SP pts was 18.9 (16.3-25.6), 46% had a BMI < 18.5 and none were obese (BMI ≥ 30). By NRI, 58% of SP pts were malnourished. Males comprised 71% of SP pts (p = 0.03) but no difference from NSP MESCC pts was identified with age, race, ECOG PS or smoking status with univariate analysis. Median overall survival (OS) was 6 months; 4.2 in SP pts and 6.2 in NSP pts. Significant difference was identified with NRI (p = .0.009) but not sarcopenia (p = 0.247) or BMI (p = 0.393). With a multi-variate Cox model for NRI and sarcopenia, including age, sex, race, and ECOG PS, only ECOG PS was a significant predictor of mortality, HR for 2-3 vs 0-1 of 5.4 (2.5-11.9) p < 0.001. Conclusions: Sarcopenia at diagnosis was not associated with OS. NRI was superior to BMI alone with respect to discriminating pt outcomes, however ECOG PS was the only measure significantly associated with survival.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".