Late Gastrointestinal Tolerance After Prostate Radiotherapy: Is the Anal Canal the Culprit? A Narrative Critical Review
Bibliographic record
Abstract
INTRODUCTION: Late gastro-intestinal toxicities (LGIT) secondary to pelvic radiotherapy (RT) are well described in the literature. LGIT are mainly related to rectal or ano-rectal irradiation; however, involvement of the anal canal (AC) in the occurrence of LGIT remains poorly described and understood. MATERIALS AND METHODS: The aim of this work was to explore the potential role of the AC in the development of LGIT after prostate irradiation and identify predictive factors that could be optimized in order to limit these toxicities. This narrative literature review was realized using the Pubmed database. We identified original articles published between June 1997 and July 2019, relating to LGIT after RT for localized prostate cancer and for which AC was identified independently. Articles defining the AC as part of an anorectal or rectal volume only were excluded. RESULTS: A history of abdominal surgery or cardio-vascular risk, anticoagulant or tobacco use, and the occurrence of acute GIT during RT increases the risk of LGIT. A dose-effect relationship was identified between dose to the AC and development of LGIT. Identification and contouring of the AC and adjacent anatomical structures (muscles or nerves) are justified to apply specific dose constraints. As a limitation, our review mainly considered on 3DCRT which is no longer the standard of care nowadays; we did not identify any reports in the literature using moderately hypofractionated RT for the prostate and AC specific dosimetry. CONCLUSION: These results suggest that the AC may have an important role in the development of LGIT after pelvic RT for prostate cancer. The individualization of the AC during planning should be recommended in prospective studies.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".