Technology review: high-intensity focused ultrasound for prostate cancer.
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: High-Intensity Focused Ultrasound (HIFU) is a technology that has moved from being used for benign prostate disease to the treatment of prostate cancer. A technology review was undertaken to guide patients and physicians as to its suitability. METHOD: An evidence-based review of published papers in the English language, with additional material from internet and other sources. RESULTS AND CONCLUSIONS: Only case series have been published; there are no randomized studies. The quality of evidence is poor, with no reports having longer follow-up than a mean of 2 years, with median follow-ups substantially shorter. Efficacy outcomes are thus premature and preclude assessment. Toxicity varies substantially with impotence rates 44%-61%, grade 2-3 incontinence 0%-14%, and rectal fistulae 0.7%-3.2%. There is limited data on the use of HIFU for the salvage therapy after radiation failure. There are no data on the toxicity of subsequent standard curative therapies after HIFU. In view of the lack of efficacy outcomes, and in the presence of significant toxicity, HIFU should only be offered within a research setting.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".