Dosimetry and Gastrointestinal Toxicity Relationships in a Phase II Trial of Pelvic Lymph Node Radiotherapy in Advanced Localised Prostate Cancer
Bibliographic record
Abstract
AIMS: Pelvic lymph node (PLN) radiotherapy for high-risk prostate cancer is limited by late gastrointestinal toxicity. Application of rectal and bowel constraints may reduce risks of side-effects. We evaluated associations between intensity-modulated radiotherapy (IMRT) dose-volume data and long-term gastrointestinal toxicity. MATERIALS AND METHODS: Data from a single-centre dose-escalation trial of PLN-IMRT were analysed, including conventionally fractionated (CFRT) and hypofractionated (HFRT) radiotherapy schedules. Associations between volumes of rectum and bowel receiving specified doses and clinician- and patient-reported toxicity outcomes were investigated independently. A metric, δ median (δM), was defined as the difference in the medians of a volume between groups with and without toxicity at a specified dose and was used to test for statistically significant differences. RESULTS: Constraints were respected in most patients and, when exceeded, led to higher rates of gastrointestinal toxicity. Biologically relevant associations between rectum dose-points and toxicity were more numerous with both mild and moderate toxicity thresholds, but statistical significance was limited after correction for false discovery rate. Rectal V50Gy (CFRT) associated with grade 2+ bleeding; bowel V43Gy and V47 (HFRT/4 days/week schedule) associated with patient-reported loose stools and diarrhoea, respectively. Further investigation showed that CFRT patients with rectal bleeding had a mean rectal V50Gy above the treatment planning constraint. CONCLUSIONS: When dose-volume parameters are kept below tight constraints, toxicity is low. Residual dosimetry loses much of its predictive power for gastrointestinal toxicity in the setting of PLN-IMRT for prostate cancer. We have benchmarked dose-volume constraints for safely delivering PLN-IMRT using CFRT or HFRT.
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 | 0.001 | 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".