High-Intensity Focused Ultrasound and Cryotherapy as Salvage Treatment in Local Radio-Recurrent Prostate Cancer
Bibliographic record
Abstract
BACKGROUND: Salvage high-intensity focused ultrasound (HIFU) and cryotherapy (CRYO) have emerged as interesting alternatives in the treatment of local radio-recurrent prostate cancer. Currently, recommendations concerning the use of CRYO and HIFU in the salvage setting are still evolving. AIM: The objective of this review was to analyze the results from studies on CRYO and HIFU as salvage treatment in local radio-recurrent prostate cancer. MATERIALS AND METHODS: A National Center for Biotechnology Information PubMed search (www.pubmed.gov) was conducted from 1993 to 2011 using medical subject headings 'High-Intensity Focused Ultrasound', 'Cryotherapy', 'Local Radio-Recurrent' and 'Prostate Cancer'. RESULTS: In the past years, there have been several published series demonstrating promising acceptable morbidity and oncological outcomes in the short term for HIFU and in the intermediate term for CRYO. The introduction of newer-generation devices and technical modifications has facilitated reduction of complications associated with the procedures. As with any salvage treatment, careful patient selection and subsequent follow-up are principal points. CONCLUSIONS: HIFU and CRYO are promising salvage treatments in patients with local radio-recurrent prostate cancer. The risk of significant complications in the salvage setting is higher compared with primary therapy; therefore, the patients must be informed about the risk of complications and the modality of treatment. However, only further evaluation in formal prospective clinical trials will hopefully confirm their role in clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".