Can Transurethral Resection of the Prostate (TURP) Be Another Gateway to the Focal Therapy of Localized Prostate Cancer?
Bibliographic record
Abstract
Background and Objectives Minimally invasive methods are expected to avoid the risk of overtreatment and overtreatment of radical therapy to manage the increased number of patients with low-volume, low-grade localized prostate cancer. Based on our experience of radical transurethral resection of prostate cancer (TURPCa) as a radical treatment, we studied the efficacy and safety of focal TURPCa as a focal therapy for patients with localized prostate cancer. Materials and Methods We performed focal TURPCa in 49 patients during the period from July 2007 to August 2016 and followed them with prostate-specific antigen (PSA) testing for the mean period of 68.0 months. We selected the patient as a candidate for the study if the biopsy revealed that cancer foci were limited in one lobe, or the foci were several or less even found in both lobes. Standard TURP was followed by further resection and fulguration of the peripheral zone where cancer was considered to exist. We selected one of our three methods of focal TURPCa as follows: one lobe radical TURPCa, radical resection of the affected lobe with unaffected lobe being resected less vigorously; nerve-sparing radical TURPCa, radical resection of both lobes except for the posterolateral part of the prostate; target radical TURPCa, radical resection of the cancer focus and the surrounding prostate when the target is suggested single. Results Twelve patients were in the low-risk group (D’Amico), 29 in the intermediate-risk group, and 8 in the high-risk group. Pathological stages were as follows: pT0, three cases; pT2a-b, 17 cases; pT2c, 29 cases. The preoperative PSA of 6.15±2.73 ng/mL (mean±SD) dropped to 0.172±0.283 ng/mL postoperatively. PSA failure occurred in only two patients (4.1%). Incontinence did not develop and erectile function was preserved in eight (44.4%) of the 18 potent patients. The most frequent complication was bladder neck contracture (20.4%). Other complications included acute epididymitis (8.1%), bladder tamponade (2.0%). No patients died of prostate cancer. Conclusions Though the final assessment of efficacy will require long-term follow-up results with more cases, we may think focal TURPCa can be another treatment option as a focal therapy for localized 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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".