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 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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".