Laparoscopic and robotic simple prostatectomy (SP) have been introduced with the aim of reducing the morbidity of the standard open technique. To report a large multi-institutional series of minimally invasive SP (MISP). Consecutive cases of MISP done for the treatment of bladder outlet obstruction (BOO) due to benign prostatic enlargement (BPE) between 2000 and 2014 at 23 participating institutions in the Americas and Europe were included in this retrospective analysis. Laparoscopic or robotic SP. Demographic data and main perioperative outcomes were gathered and analyzed. A multivariable analysis was conducted to identify factors associated with a favorable trifecta outcome, arbitrarily defined as a combination of the following postoperative events: International Prostate Symptom Score 15ml/s, and no perioperative complications. Overall, 1330 consecutive cases were analyzed, including 487 robotic (36.6%) and 843 laparoscopic (63.4%) SP cases. Median overall prostate volume was 100ml (range: 89-128). Median estimated blood loss was 200ml (range: 150-300). An intraoperative transfusion was required in 3.5% of cases, an intraoperative complication was recorded in 2.2% of cases, and the conversion rate was 3%. Median length of stay was 4 d (range: 3-5). On pathology, prostate cancer was found in 4% of cases. Overall postoperative complication rate was 10.6%, mostly of low grade. At a median follow-up of 12 mo, a significant improvement was observed for subjective and objective indicators of BOO. Trifecta outcome was not significantly influenced by the type of procedure (robotic vs laparoscopic; p=0.136; odds ratio [OR]: 1.6; 95% confidence interval [CI], 0.8-2.9), whereas operative time (p=0.01; OR: 0.9; 95% CI, 0.9-1.0) and estimated blood loss (p=0.03; OR: 0.9; 95% CI, 0.9-1.0) were the only two significant factors. Retrospective study design, lack of a control arm, and limited follow-up represent major limitations of the present analysis. This study provides the largest outcome analysis reported for MISP for BOO/BPE. These findings confirm that SP can be safely and effectively performed in a minimally invasive fashion in a variety of healthcare settings in which specific surgical expertise and technology is available. MISP can be considered a viable surgical treatment in cases of large prostatic adenomas. The use of robotic technology for this indication can be considered in centers that have a robotic program in place for other urologic indications. Analysis of a large data set from multiple institutions shows that surgical removal of symptomatic large prostatic adenomas can be carried out with good outcomes by using robot-assisted laparoscopy.

Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention.

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2–10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), % fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p<0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2–10 ng/ml at initial biopsy, outperforming currently used %fPSA.