Urinary incontinence and use of incontinence surgery after radical prostatectomy: a national study using patient‐reported outcomes
Bibliographic record
Abstract
OBJECTIVES: To investigate whether patient-reported urinary incontinence (UI) and bother scores after radical prostatectomy (RP) result in subsequent intervention with UI surgery. PATIENTS AND METHODS: Men diagnosed with prostate cancer in the English National Health Service between April 2014 and January 2016 were identified. Administrative data were used to identify men who had undergone a RP and those who subsequently underwent a UI procedure. The National Prostate Cancer Audit database was used to identify men who had also completed a post-treatment survey. These surveys included the Expanded Prostate Cancer Composite Index (EPIC-26). The frequency of subsequent UI procedures, within 6 months of the survey, was explored according to EPIC-26 UI scores. The relationship between 'good' (≥75) or 'bad' (≤25) EPIC-26 UI scores and perceptions of urinary bother was also explored (responses ranging from 'no problem' to 'big problem' with respect to their urinary function). RESULTS: We identified 11 290 men who had undergone a RP. The 3-year cumulative incidence of UI surgery was 2.5%. After exclusions, we identified 5165 men who had also completed a post-treatment survey after a median time of 19 months (response rate 74%). A total of 481 men (9.3%) reported a 'bad' UI score and 207 men (4.0%) also reported that they had a big problem with their urinary function. In all, 47 men went on to have UI surgery within 6 months of survey completion (0.9%), of whom 93.6% had a bad UI score. Of the 71 men with the worst UI score (zero), only 11 men (15.5%) subsequently had UI surgery. CONCLUSION: In England, there is a significant number of men living with severe, bothersome UI after RP, and an unmet clinical need for UI surgery. The systematic collection of patient-reported outcomes could be used to identify men who may benefit from UI surgery.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".