Prognostic significance of nutritional markers in metastatic gastric and esophageal adenocarcinoma.
Bibliographic record
Abstract
4557 Background: Malnutrition and sarcopenia (defined as low skeletal muscle mass) are recognized as poor prognostic factors in many cancers. Studies to date in gastroesophageal cancer have largely focused on patients (pts) undergoing curative intent surgery. This study aims to evaluate the prognostic utility of nutritional markers and sarcopenia in pts with de novo metastatic gastric and esophageal adenocarcinoma (GEA). Methods: Pts with de novo metastatic GEA seen at the Princess Margaret Cancer Centre from 2010-2016 with available pre-treatment abdominal computed tomography imaging were identified from an institutional database. Nutritional index (NRI) was calculated using weight and albumin, with moderate/severe malnutrition defined as NRI < 97.5. Skeletal muscle index (SMI) normalized by height was calculated at the L3 level using Slice-O-Matic software. Sarcopenia was defined as SMI < 34.4cm2/m2 in women and < 45.4cm2/m2 in men based on previously established consensus. Results: Of 175 consecutive pts, median age was 61, 69% were male, 79% had ECOG performance status 0-1, and 71% received chemotherapy. Median BMI was 24.2 (range 15.7-39.8), 70% of pts had > 5% weight loss in the preceding 3 months, and 29% had moderate/severe malnutrition. 68 pts (39%) were sarcopenic, of whom 46% were malnourished. Median overall survival (OS) was 9.3 months (95% CI 7.3-11.4) for all pts. OS was significantly worse in malnourished pts (5.5 vs 10.9 months, p = 0.000475) and displayed a non-significant trend in sarcopenic pts (7.8 vs 10.6 months, p = 0.186). On univariable Cox proportional hazards (PH) analysis, ECOG (p < 0.001), number of metastatic sites (p = 0.029) and NRI (p < 0.001) were significant prognostic factors, while BMI (p = 0.57) and sarcopenia (p = 0.19) were not. On multivariable Cox PH analysis, ECOG (p < 0.001) and NRI (p = 0.025) remained significant as poor prognostic factors for OS. Conclusions: This study demonstrates in a large cohort of de novo metastatic GEA pts that ECOG and NRI were significantly associated with poor OS. NRI was superior to BMI alone. Early identification of malnourished pts using NRI may allow for supportive interventions to optimize nutritional status. Further study is needed to determine whether these factors can be modified to improve prognosis in these pts.
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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".