Presence and duration of feeding tube in a 5‐year cohort of patients with head and neck cancer treated with curative i<scp>ntensity‐modulated</scp> radiation therapy
Bibliographic record
Abstract
BACKGROUND: Our study assessed post-radiation therapy (RT) G-tube presence, duration, and clinical predictors in patients with head and neck cancer (HNC). METHODS: We identified those 1-5-years post-RT with stage III/IV nasopharyngeal, oropharyngeal, hypopharyngeal, laryngeal, or unknown primaries. Logistic regression identified predictors of post-RT G-tube presence, Kaplan-Meier analysis estimated G-tube days, and log-rank test compared by tumor site. RESULTS: The 977 patients had mean age 60.6 ± 11.6 years, 804 (82.3%) male, 764 (78.2%) stage IV, and 618 (63.3%) oropharyngeal primaries. All patients received intensity-modulated RT (IMRT), 571 (58.4%) received chemotherapy, and 698 (71.4%) prophylactic G-tube. G-tube prevalence 1- and 5-years post-IMRT was 7.1% and 4.8%, respectively. Median post-IMRT G-tube days were overall 63 (95%CI: 56-70), nasopharynx 119 (95%CI: 109-131), oropharynx 57 (95%CI: 51-68), hypopharynx 126 (95%CI: 77-256), larynx 53 (95%CI: 21-63), unknown 30 (95%CI: 17-55), of which hypopharynx was highest p < 0.001. CONCLUSIONS: At an institution offering prophylactic G-tube for patients with advanced HNC, no differences were found in yearly G-tube use 1-5 years post-IMRT. Across all patients, median post-IMRT days with G-tube was 63 day but those with hypopharyngeal tumors registered the most days.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".