Sarcopenia as a Predictor of Feeding Tube Placement in Individuals with Oropharyngeal Cancer
Bibliographic record
Abstract
Purpose: In oropharyngeal squamous cell carcinoma (OPSCC), systemic loss of skeletal muscle mass (SMM), or sarcopenia, is a strong prognostic predictor of survival outcomes. However, the relationship between sarcopenia and nutrition-related outcomes is not well understood. This investigation evaluated the prognostic significance of sarcopenia for feeding tube (FT) placement in a cohort of OPSCC patients. Methods and Materials: A retrospective cohort study was conducted with data collected from 194 OPSCC patients treated with definitive radiation therapy (RT) or chemoradiation therapy (CRT). Sarcopenia was assessed from computed tomography imaging at the level of the third cervical (C3) and fourth thoracic (T4) vertebrae. The prognostic nature of pretreatment sarcopenia and its relationship with FT placement was explored using logistic regression. Results: The median age of patients included was 61.0 years, and the majority were male (83%). In this patient cohort, 87.6% underwent concurrent CRT, and 30.9% received a FT over the course of treatment. Sarcopenia was identified at baseline in 72.7% of patients based on C3 SMM measurements and in 41.7% based on measures at the level of T4. Based on measures at both C3 and T4, those with sarcopenia were significantly more likely to receive a FT and had significantly worse freedom from FT placement compared with patients without sarcopenia. Sarcopenia assessed at T4 was a significant predictor of FT placement. Conclusions: SMM measured at T4 may represent a novel and practical biomarker for sarcopenia detection that is associated with the need for FT placement. These findings suggest that the detection of baseline sarcopenia could guide decision-making related to the need for nutritional support in OPSCC patients undergoing RT/CRT.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".