Predictors of Gastrostomy Tube Placement in Head and Neck Cancer Patients Undergoing Radiation or Chemoradiotherapy: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Malnutrition is a major problem in head and neck cancer (HNC) with up to half of patients requiring gastrostomy tube (G-tube) placement. Predicting this need remains complex given mixed evidence surrounding its usage. METHODS: A comprehensive search was performed to identify studies examining risk factors associated with G-tube placement following radiotherapy (RT) or concurrent chemoradiotherapy (CCRT) in HNC patients. RESULTS: Sixteen retrospective studies were included (n = 11 015). The overall prevalence of G-tube placement was 44% with 76% of patients receiving reactive G-tube placement. Pretreatment dysphagia, pretreatment BMI < 18.5, and tumors in the hypopharynx were significant predictive factors for prophylactic G-tube placement. Type of chemotherapy regimen, tumors in the nasopharynx, and cytokine changes were significant predictive factors for reactive G-tube placement. CONCLUSION: Several factors were identified that contribute to increased risk of G-tube placement and may guide current decision-making algorithms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".