High-intensity focused ultrasound with visually directed power adjustment for focal treatment of localized prostate cancer: systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: To characterize patient outcomes following visually directed high-intensity focused ultrasound (HIFU) for focal treatment of localized prostate cancer. METHODS: We performed a systematic review of cancer-control outcomes and complication rates among men with localized prostate cancer treated with visually directed focal HIFU. Study outcomes were calculated using a random-effects meta-analysis model. RESULTS: A total of 8 observational studies with 1,819 patients (median age 67 years; prostate-specific antigen 7.1 mg/ml; prostate volume 36 ml) followed over a median of 24 months were included. The mean prostate-specific antigen nadir following visually directed focal HIFU was 2.2 ng/ml (95% CI 0.9-3.5 ng/ml), achieved after a median of 6 months post-treatment. A clinically significant positive biopsy was identified in 19.8% (95% CI 12.4-28.3%) of cases. Salvage treatment rates were 16.2% (95% CI 9.7-23.8%) for focal- or whole-gland treatment, and 8.6% (95% CI 6.1-11.5%) for whole-gland treatment. Complication rates were 16.7% (95% CI 9.9-24.6%) for de novo erectile dysfunction, 6.2% (95% CI 0.0-19.0%) for urinary retention, 3.0% (95% CI 2.1-3.9%) for urinary tract infection, 1.9% (95% CI 0.1-5.3%) for urinary incontinence, and 0.1% (95% CI 0.0-1.4%) for bowel injury. CONCLUSION: Limited evidence from eight observational studies demonstrated that visually directed HIFU for focal treatment of localized prostate cancer was associated with a relatively low risk of complications and acceptable cancer control over medium-term follow-up. Comparative, long-term safety and effectiveness results with visually directed focal HIFU are lacking.
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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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.039 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".