Correlation Between Saliva Production and Quality of Life Measurements in Head and Neck Cancer Patients Treated With Intensity-Modulated Radiotherapy
Bibliographic record
Abstract
PURPOSE: To investigate the strength of correlation between measured saliva flow rates and various toxicity endpoints commonly used in head and neck cancer (HNC) treatment. MATERIALS AND METHODS: All patients enrolled in a phase II study using intensity modulated radiotherapy (IMRT) for HNC treatment underwent whole mouth saliva flow measurements (stimulated and unstimulated). They were also assessed for salivary gland toxicity using Radiation Therapy Oncology Group (RTOG) late toxicity grading and 9 items representing patient-graded toxicities from 2 questionnaires (Xerostomia questionnaire and University of Washington quality of life). For each patient, saliva flow rates and quality of life (QOL) data were collected preradiotherapy (RT) and at 3 intervals post-RT (3, 6, and 12 months). RESULTS: A total of 188 sets of coregistered data were obtained for 47 patients over a period of approximately 4 years. Saliva production and mean QOL dropped significantly immediately after RT, but there was a statistically significant recovery in both parameters between 3- and 12-month post-RT. By 12 months, post-RT the mean QOL scores had returned to pre-RT baseline, although mean stimulated saliva production remained 58% below baseline. CONCLUSION: Patients with HNC treated with IMRT experienced a small drop in QOL which recovered to baseline by 12 months post-RT. There was no statistically significant correlation seen between global health-related QOL scores and stimulated saliva production rates in the post-RT period.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".