Transperineal Prostate Biopsies Using Local Anesthesia: Experience with 1,287 Patients. Prostate Cancer Detection Rate, Complications and Patient Tolerability
Bibliographic record
Abstract
PURPOSE: We report our experience with transperineal prostate biopsy as well as the cancer diagnosis rate, complications and patient tolerability in 1,287 consecutive patients at risk for prostate cancer. MATERIALS AND METHODS: Beginning in October 2016 transperineal prostate biopsy was performed using local anesthesia in all patients undergoing prostate biopsy. Data on prebiopsy characteristics and results, including the cancer detection rate, complications and patient tolerability scores, were collected retrospectively from patient records. RESULTS: The cancer detection rate of transperineal prostate biopsy was 49.8% (641 of 1,287 patients). Clinically significant prostate cancer was detected in 385 patients and 62 (9.7%) had exclusively anterior zone pathology findings. Urinary retention developed in 20 patients (1.6%) following transperineal prostate biopsy, requiring temporary catheterization. In 4 patients (0.3%) lower urinary tract symptoms were suggestive of infection but only 1 had a positive urine culture. The only hospital admission was for a patient with persistent hypotension after biopsy. Patients tolerated transperineal prostate biopsy reasonably well and generally reported only mild levels of discomfort on a pain visual analogue scale. Infiltration of the anesthesia was rated more painful than the biopsy. CONCLUSIONS: Transperineal prostate biopsy with the patient under local anesthesia is a feasible alternative to transrectal biopsy in the detection of prostate cancer. Transperineal prostate biopsy has an acceptable cancer detection rate with additional detection of anterior zone cancers. It is a safer alternative in patients due to the low risk of complications, in particular urosepsis, and it is well tolerated. Transperineal prostate biopsy using local anesthesia could be considered a standard modality for the initial diagnosis of prostate cancer.
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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 | 0.003 |
| 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 | 0.001 |
| 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".