Prognostic significance of malnutrition in metastatic esophageal squamous cell carcinoma.
Bibliographic record
Abstract
171 Background: Disease related symptoms including anorexia, nausea and dysphagia lead patients with esophageal cancer to become malnourished. Malnourishment can result in systemic inflammation, reduced treatment tolerance, poorer quality of life and decreased overall survival. Currently weight loss is the main clinical measure of malnutrition, and thus we set out to evaluate the prognostic utility of alternative screening tools of malnutrition. Methods: Patients with metastatic esophageal squamous cell cancer (MESCC) attending the Princess Margaret Cancer Centre, between January 2011 and December 2016, were identified from the institutional gastroesophageal database. Nutritional Risk Score (NRS), Nutritional Risk Index (NRI) and Neutrophil Lymphocyte Ratio (NLR) were calculated and correlated with clinical-pathological variables and survival. Malnutrition was defined as NRS ≥ 3, NRI < 97.5 and NLR ≥ 3. Results: Of the 64 consecutive patients, 30 (47%) presented with de novo metastatic disease and 34 (53%) with recurrence. The median age was 62 years (range 40-85), 47 patients were ECOG PS ≤ 2 and 29 (45%) received systemic chemotherapy. 90% of patients experienced weight loss > 5% prior to diagnosis and median BMI was 20.1 (range 14.3-34.9). NRI identified 37 (58%) and NRS 45 (70%) patients as malnourished. Both were associated with poorer ECOG PS (p = 0.012 and p = 0.027 respectively). No difference was identified with sex, smoking status or albumin with univariate analysis. NRI did not associate significantly with age. Median overall survival was 5months; 8.1-9 months with normal nutrition and 2.8-3.2 months in malnourished patients. Kaplan Meier analysis revealed significant difference in overall survival (malnutrition vs. normal nutrition) using NRS (p = 0.029) and NRI (p = 0.001) but not weight (p = 0.509) or NLR (p = 0.69). Conclusions: Patients with MESCC identified as malnourished at the time of diagnosis have inferior survival outcomes. Malnutrition tools are superior to weight alone with respect to discriminating outcomes in this patient population. Further investigation is needed in larger patient cohorts; to identify those at risk, initiate early supportive interventions and improve patient outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.002 | 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".