SIU-ICUD: Principles and Outcomes of Focal Therapy in Localized Prostate Cancer
Bibliographic record
Abstract
Background/Objectives: Focal therapy (FT) for prostate cancer (PCa) is an alternative to radical treatments that aims to balance cancer control and quality of life preservation in well-selected patients. Understanding its general principles and outcomes is key for its widespread adoption and proper implementation. Methods: The International Consultation on Urological Diseases nominated a committee to review the literature on FT for PCa. A comprehensive PubMed search was conducted to identify articles focused on the different aspects of FT, including patient selection, imaging techniques, treatment modalities, cancer control and safety outcomes, integration with other approaches and future perspectives. Results: FT for PCa was introduced in the 1990s with cryotherapy and high-intensity focused ultrasound (HIFU) as pioneering modalities. Though initially guided by transrectal ultrasound (TRUS) and large biopsy templates, FT implementation expanded significantly with the advent of multiparametric magnetic resonance imaging (MRI) and the validation of the index lesion concept. Appropriate patient selection is key for FT and relies on prostate-specific antigen (PSA) metrics, MRI findings and targeted biopsy information. Multiple energy sources are now available, each with specific technical characteristics. Cancer control rates vary by energy modality, tumor characteristics, and institutional experience, demonstrating comparable outcomes to radical treatments in well-selected patients. The safety profile is excellent, with high rates of urinary continence and sexual function preservation. Post-treatment surveillance integrates PSA measurements, imaging, and histological assessment. Future directions for further FT adoption include the availability of long-term data, protocol standardization and technological improvements to enhance patient selection and treatment planning and delivery. Conclusions: FT is a valuable therapeutic option for selected patients with localized PCa, demonstrating promising oncological outcomes and better functional preservation compared to radical treatments. Understanding its principles and technical aspects is essential for offering comprehensive PCa care.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".