Partial gland ablation with high intensity focal ultrasound impact on genito-urinary function and quality of life: our initial experience.
Bibliographic record
Abstract
INTRODUCTION: Partial gland ablation (PGA) using high intensity focal ultrasound (HIFU) is an alternative to active surveillance for low to intermediate risk localized prostate cancer. This pilot study assessed quality of life (QoL) outcomes during the implementation of PGA-HIFU at our institution. MATERIALS AND METHODS: We prospectively enrolled 25 men with a diagnosis of localized low/intermediate risk prostate cancer who elected to undergo PGA-HIFU in a pilot study at our institution between 2013 and 2016. Patients underwent pre-treatment mpMRI and transrectal ultrasound-guided biopsies. The primary endpoints were impact on patient-reported functional outcomes (erectile, urinary function, QoL) assessed at 1, 3, 6- and 12-months. RESULTS: The median age was 64 years old (IQR 59.5-67). Baseline median International Index of Erectile Function-15 score was 50, which decreased to 18 at 1 month (p < 0.0005), returned to baseline by 3 months and thereafter. International Prostate Symptom Score median at baseline was 8, which worsened to 12 at 1 month (p = 0.0088), and subsequently improved to baseline thereafter. On the UCLA-Expanded Prostate Cancer Index Composite urinary function, there was a decrease in median score from 92.7 at baseline to 76.0 at 1 month (p < 0.0001), which improved to or above baseline afterwards. QoL remained similar to baseline at each follow up period as assessed by EQ-5D and the Functional Cancer Therapy-Prostate score. CONCLUSIONS: In this initial cohort of PGA-HIFU men at our institution, patients demonstrated a slight, but transient, deterioration in urinary and erectile function at 1 month prior to normalization. All QoL metrics showed no impact upon 1 year of follow up post-treatment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".