The Benefits and Harms of Pharmacological Treatment for Postradiation Pelvic Pain: A Systematic Review by the European Association of Urology Chronic Pelvic Pain Panel with Recommendations for Clinical Practice
Bibliographic record
Abstract
Context: Radiotherapy of the pelvis is a widely used method for the treatment of malignancies, and local complications including pain following pelvic radiation therapy are acknowledged complications. Objective: The primary objective is to assess the clinical effectiveness and safety of pharmacological therapies on postradiation pelvic pain. Evidence acquisition: A systematic review of the use of different pharmacological treatments in the management of post-radiation pelvic pain was conducted (PROSPERO-ID: CRD42021249026). Comprehensive searches of EMBASE, Medline, and Cochrane library were performed for publications between January 1980 and April 2021. The primary outcomes were improvement in pain and adverse events following treatment. The secondary outcomes included quality of life, bowel function, and urinary function. Evidence synthesis: After screening 1514 abstracts, four randomised controlled trials were identified, enrolling 355 patients with bladder and anorectal subtypes of postradiotherapy chronic pelvic pain (CPP). A narrative synthesis was performed as heterogeneity of included studies precluded a meta-analysis. A single study reported a significant reduction in pain after 6 mo in patients with bladder pain syndrome treated with hyaluronic acid or hyperbaric oxygen. Anorectal pain was reported to be reduced by the application of 4% formalin, but the use of hyperbaric oxygen in postradiotherapy anorectal pain remains controversial. Adverse event reporting was generally poor. Studies looking at medications used routinely in guidelines for neuropathic pain, such as gabapentin, pregabalin, amitriptyline, and duloxetine, were absent or of poor quality when it came to postradiation pelvic pain. Conclusions: Beneficial effects of hyperbaric oxygen or formalin on pain, quality of life, and functional symptoms were seen in patients with certain CPP subtypes, but the current evidence level is too weak to allow recommendations about the use of any pharmacological treatment for postradiation pelvic pain. Patient summary: Different pharmacological treatments are used to treat pain after radiotherapy, but current studies are of insufficient quality to determine whether these should be recommended and many chronic pelvic pain subtypes are not covered. Further research is needed.
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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 | 0.077 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".