Systematic review and network <scp>meta‐analysis</scp> of re‐intervention rates of new surgical interventions for benign prostatic hyperplasia
Bibliographic record
Abstract
OBJECTIVE: To assess the re-intervention rates of new surgical benign prostatic hyperplasia (BPH) interventions, as the clinical durability of new surgical interventions for BPH is not widely known. METHODS: A critical review of new surgical BPH therapies namely 'UroLift®', 'Aquablation', 'Rezum', 'prostatic artery embolisation (PAE)' and 'temporary implantable nitinol device (iTIND)' was performed on PubMed, the Cochrane Library, and Embase databases between May 2010 and December 2022 according to the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) statement. All relevant articles were reviewed, and the risk of bias was evaluated using the Cochrane risk assessment tool and Newcastle-Ottawa Scale. RESULTS: Of the 32 studies included, there were 10 randomised controlled trials and 22 prospective observational cohorts. A total of 2400 participants were studied with a median patient age of 66 years, a median prostate volume of 51.9 mL, and a median International Prostate Symptom Score of 22. The lowest re-intervention rate at 12 months was for Aquablation at 0.01%, followed by Rezum at 0.02%, iTIND at 0.03%, and PAE at 0.05%. Network meta-analysis (NMA) showed that the best-ranked treatment at 12 months was transurethral resection of the prostate (TURP), followed by Aquablation, iTIND, Rezum, and UroLift. Re-intervention rates with these new BPH interventions are comparable, although some interventions reported better outcomes than TURP in the shorter term. CONCLUSIONS: While this systematic review and NMA showed that the re-intervention rate with these new surgical BPH interventions appears to be comparable to TURP in the short term, further studies are required to directly compare these various BPH procedures.
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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 | 0.023 | 0.062 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.048 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".