Machine Learning and External Validation of the IDENTIFY Risk Calculator for Patients with Haematuria Referred to Secondary Care for Suspected Urinary Tract Cancer.

Background: The IDENTIFY study developed a model to predict urinary tract cancer using patient characteristics from a large multicentre, international cohort of patients referred with haematuria. In addition to calculating an individual's cancer risk, it proposes thresholds to stratify them into very-low-risk (<1%), low-risk (1-<5%), intermediate-risk (5-<20%), and high-risk (≥20%) groups.

Objective: To externally validate the IDENTIFY haematuria risk calculator and compare traditional regression with machine learning algorithms.

Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review.

Background And Objective: The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients' response to treatment.

Androgen deprivation therapy in localized prostate cancer. Current status and future trends.

Introduction: Prostate cancer (PCa) has been recognized as an androgen-sensitive disease since the investigations from Huggins and Hodges in 1941. Thanks to these findings, they received the Nobel Prize in 1966. This was the beginning of the development of androgen deprivation therapy (ADT) as treatment for patients with PCa.

Metastatic testicular cancer presenting with hematuria and flank pain.

Testicular cancer (TC) represents 1% of male neoplasms and 5% of urological tumors. Most of seminoma patients and about 55% of patients with nonseminoma TC have stage I disease at diagnosis. TC usually presents with a palpable testicular mass incidentally found by the patient himself or its partner by palpation.

Observational study over 8-year period evaluating microbiological characteristics and risk factor for isolation of multidrug-resistant organisms (MDRO) in patients with healthcare-associated infections (HAIs) hospitalized in a urology ward.

To analyze, in a urology ward, the prevalence and characteristics of healthcare-associated infections (HAIs) due to multidrug-resistant organisms (MDRO). We carried out an observational study from 2012 to 2019, evaluating MDRO among patients with HAIs, who were hospitalized in the urology ward. MDRO include spp.