Artificial intelligence is highly regarded as the most promising future technology that will have a great impact on healthcare across all specialties. Its subsets, machine learning, deep learning, and artificial neural networks, are able to automatically learn from massive amounts of data and can improve the prediction algorithms to enhance their performance. This area is still under development, but the latest evidence shows great potential in the diagnosis, prognosis, and treatment of urological diseases, including bladder cancer, which are currently using old prediction tools and historical nomograms. This review focuses on highly significant and comprehensive literature evidence of artificial intelligence in the management of bladder cancer and investigates the near introduction in clinical practice.

Introduction To evaluate the efficacy and safety of ureteroscopic thulium laser treatment of upper urinary tract carcinoma (UTUC). Material and Methods Forty-two consecutive patients underwent conservative thulium laser treatment for UTUC at two referral institutions. All patients underwent preliminary biopsy and then laser vaporization. A 272 μm and a 365 μm laser fibers were used with a flexible and semirigid scope, respectively. Ablation was carried out with a 10-20 Watt power. Results Mean age at surgery was 68 years old (SD 10.7). Mean tumour size was 14.3 (range 2-30) mm. Preliminary biopsy revealed the presence of low-grade disease in 29 (69.1%) patients, high-grade in 4 (9.5%) and one carcinoma in situ 1 (2.4%), while it was not conclusive in 8 (19%) cases. Final stage was pTa and pTis in 41 (97.6%) and 1 (2.4%) patients, respectively. The 38% (16) experienced Clavien-Dindo grade I complication, 47.6% (20) a grade II and 2.4% (1) a grade III. Five (12%) patients underwent a second-look procedure due to residual disease. Eight (19%) patients experienced clinical recurrence. The median estimated recurrence-free survival was 44 months (SE 3.68). Four patients (9.5%) underwent a nephroureterectomy. Final pathological stage was pTis, pT3 high grade, pTa low grade and pT0. Median follow-up was 26.3 (range 2-54) months, and no progression or upstaging of disease occurred. Conclusions Thulium laser management of UTUC is a safe and efficacious conservative treatment. Our experience shows optimal vaporization and haemostatic control in the absence of major complications.

Background: Several biochemical and clinical markers have been proposed for selecting patients for active surveillance (AS). However, some of these are expensive and not easily accessible. Moreover, currently about 30% of patients on AS harbor aggressive disease. Hence, there is an urgent need for other tools to accurately identify patients with low-risk prostate cancer (PCa). Patients: We retrospectively reviewed the medical records of 260 patients who underwent radical prostatectomy and were eligible for AS according to the following criteria: clinical stage T2a or less, prostate-specific antigen level < 10 ng/mL, 2 or fewer cores involved with cancer, Gleason score (GS) ≤6 grade, and prostate-specific antigen density < 0.2 ng/mL/cc. Methods: Univariate and multivariate analyses were performed to evaluate the association of patient and tumor characteristics with reclassification, defined as upstaged (pathological stage >pT2) and upgraded (GS ≥7) disease. A base model (age, prostate-specific antigen, prostate volume, and clinical stage) was compared with models considering neutrophil to lymphocyte ratio (NLR) or platelets to lymphocyte ratio (PLR), monocyte to lymphocyte (MLR), and eosinophil to lymphocyte ratio (ELR). OR and 95% CI were calculated. Finally, a decision curve analysis was performed. Results: Univariate and multivariate analyses showed that NLR, PLR, and ELR upgrading were significantly associated with upgrading (ORs ranging from 2.13 to 4.13), but not with upstaging except for MLR in multivariate analysis, showing a protective effect. Conclusion: Our results showed that NLR, PLR, and ELR are predictors of Gleason upgrading. Therefore, these inexpensive and easily available tests might be useful in the assessment of low-risk PCa, when considering patients for AS.

Background: A systemic inflammatory marker, the modified Glasgow prognostic score (mGPS), could predict outcomes in non-muscle-invasive bladder cancer (NIMBC). We aimed to investigate the predictive power of mGPS in oncological outcomes in HG/G3 T1 NMIBC patients undergoing Bacillus Calmette–Guérin (BCG) therapy. Methods: We retrospectively reviewed patient’s medical data from multicenter institutions. A total of 1382 patients with HG/G3 T1 NMIBC have been administered adjuvant intravesical BCG therapy, every week for 3 weeks given at 3, 6, 12, 18, 24, 30 and 36 months. The analysis of mGPS for recurrence and progression was performed using multivariable and univariable Cox regression models. Results: During follow-up, 659 patients (47.68%) suffered recurrence, 441 (31.91%) suffered progression, 156 (11.28%) died of all causes, and 67 (4.84%) died of bladder cancer. At multivariable analysis, neutrophil to lymphocyte ratio [hazard ratio (HR): 7.471; p = 0.0001] and erythrocyte sedimentation rate (ESR) (HR: 0.706; p = 0.006 were significantly associated with recurrence. mGPS has no statistical significance for progression (p = 0.076). Kaplan–Meier survival analysis showed a significant difference in survival among patients from different mGPS subgroups. Five-year OS was 93% (CI 95% 92–94), in patients with mGPS 0, 82.2% (CI 95% 78.9–85.5) in patients with mGPS 1 and 78.1% (CI 95% 60.4–70) in mGPS 2 patients. Five-year CSS was 98% (CI 95% 97–99) in patients with mGPS 0, 90% (CI 95% 87–94) in patients with mGPS 1, and 100% in mGPS 2 patients. Limitations are applicable to a retrospective study. Conclusions: mGPS may have the potential to predict recurrence in HG/G3 T1 NMIBC patients, but more prospective, with large cohorts, studies are needed to study the influence of systemic inflammatory markers in prediction of outcomes in NMIBC for a definitive conclusion.