Regional radiation dose susceptibility within the parotid gland: Effects on salivary loss and recovery
Bibliographic record
Abstract
PURPOSE: Xerostomia is one of the most likely late toxic effects of radiotherapy treatment in patients with head-and-neck cancers. Modern treatment techniques can incorporate knowledge of complication risk into treatment plans. To this end, the authors attempt to quantify the regional radiotherapy dose-dependence of salivary output loss and recovery in a prospective study. METHODS: Salivary output was collected from patients undergoing radiotherapy treatment for head-and-neck cancers at the BC Cancer Agency between February 2008 and May 2013. Regional dose-dependence (i.e., dose susceptibility) of loss and recovery is quantified using nonparametric (Spearman's rank correlation coefficients, local linear regression) and parametric (least-sum of squares, least-median of squares) techniques. RESULTS: Salivary flow recovery was seen in 79 of 102 patients considered (p < 0.0001, Wilcoxon sign rank test). Output loss was strongly correlated with left- and right parotid combined dose φ = min (DL, 45 Gy) + min (DR, 45 Gy), and can be accurately predicted. Median early loss (three months) was 72% of baseline, while median overall loss (1 yr) was 56% of baseline. Fitting an exponential model to whole parotid yields dose sensitivities A3m = 0.0604 Gy(-1) and A1y = 0.0379 Gy(-1). Recovery was not significantly associated with dose. Hints of lateral organ sub-segment dose-response dimorphism were observed. CONCLUSIONS: Sub-segmentation appears to predict neither loss nor recovery with any greater precision than whole parotid mean dose, though it is not any worse. Sparing the parotid to a combined dose φ of <50 Gy is recommended for a patient to keep ≈40% of baseline function and thus avoid severe xerostomia at 12 months post-treatment. It seems unlikely that a population's mean recovery will exceed 20%-30% of baseline output at 1 yr after radiotherapy treatment using current (whole-organ based) clinical guidelines.
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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 | 0.001 |
| 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".