Partial prostatectomy in prostate cancer: a systematic review of current evidence
Bibliographic record
Abstract
• Partial prostatectomy shows promise but lacks evidence for routine clinical use. • Partial prostatectomy has emerged as a novel surgical option aiming to preserve urinary and sexual function while maintaining oncologic control in carefully selected patients with localized prostate cancer. • Early series suggest feasibility and safety, but long-term oncological outcomes remain uncertain compared with radical prostatectomy and focal therapies. To evaluate the current evidence in the literature about partial prostatectomy as a treatment for localized prostate cancer. A systematic search of nine databases was conducted up to December 2024 to identify studies involving patients with localized prostate cancer who underwent partial prostatectomy reporting clinical epidemiological characteristics, diagnostic strategies, histopathological findings, tumor staging, functional and oncological outcomes. The primary outcome was biochemical recurrence rate. Secondary outcomes were overall survival, disease-free survival, erectile dysfunction, urinary incontinence, and perioperative complications. The extracted data were systematically synthesized. The authors analyzed five studies with a total of 48 patients (three prospective and two retrospective), all with low- or intermediate-risk disease. The mean surgical duration ranged from 129.2 to 208 min, with a single Clavien-Dindo Grade III complication reported. Only one study defined and reported biochemical recurrence, with a rate of 28 %. Urinary continence was preserved in 92 %–100 % of cases, while erectile function in 40 %–100 % ‒ which may represent a point of concern for this procedure. Overall survival and disease-free survival were consistently reported at 100 %. The lack of standardized reporting and the absence of randomized clinical trials prevented the performance of a meta-analysis and hindered the applicability of the findings to clinical practice. Randomized clinical trials are still needed to provide stronger evidence regarding partial prostatectomy, as current data remain insufficient to support its routine use. With further research, partial prostatectomy may become an option for patients with favorable and intermediate-risk disease with unilateral lesions and concordance between magnetic resonance imaging and biopsy findings. Until then, radical prostatectomy remains the cornerstone of treatment for this patient profile.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".