Prevalence of urinary tract cancer in the Spanish cohort of the IDENTIFY study.

INTRODUCTION: Malignant tumors of the urinary tract are associated with high morbidity and mortality, and their prevalence can vary worldwide. Recently, the IDENTIFY study has published results on the prevalence of urinary tract cancer at a global level. This study evaluates the prevalence of cancer within the Spanish cohort of the IDENTIFY study to determine whether the published results can be extrapolated to our population. PATIENTS AND METHODS: An analysis of the data from the Spanish cohort of patients in the IDENTIFY study was performed. This is a prospective cohort of patients referred to secondary care with suspected cancer, predominantly due to hematuria. Patients were recruited between December 2017 and December 2018. RESULTS: A total of 706 patients from 9 Spanish centers were analyzed. Of these, 277 (39.2%) were diagnosed with cancer: 259 (36.7%) bladder cancer, 10 (1.4%) upper tract urothelial carcinoma, 9 (1.2%) renal cancer and 5 (0.7%) prostate cancer. Increasing age (OR 1.05 (95% CI 1.03-1.06; P < 0.001)), visible hematuria (VH) OR 2.19 (95% CI 1.13-4.24; P = 0.02)) and smoking (ex-smokers: OR 2.11(95% CI 1.30-3.40; P = 0.002); smokers: OR 2.36 (95% CI 1.40-3.95; P = 0.001)) were associated with higher probability of bladder cancer. CONCLUSION: This study highlights the risk of bladder cancer in patients with VH and smoking habits. Bladder cancer presented the highest prevalence; higher than the prevalence reported in previous series and presented in the IDENTIFY study. Future work should evaluate other associated factors that allow us to create cancer prediction models to improve the detection of cancer in our patients.

A Preliminary Study of the Ability of the 4Kscore test, the Prostate Cancer Prevention Trial-Risk Calculator and the European Research Screening Prostate-Risk Calculator for Predicting High-Grade Prostate Cancer.

INTRODUCTION: To prevent the overdiagnosis and overtreatment of prostate cancer (PC), therapeutic strategies have been established such as active surveillance and focal therapy, as well as methods for clarifying the diagnosis of high-grade prostate cancer (HGPC) (defined as a Gleason score ≥7), such as multiparametric magnetic resonance imaging and new markers such as the 4Kscore test (4KsT). By means of a pilot study, we aim to test the ability of the 4KsT to identify HGPC in prostate biopsies (Bx) and compare the test with other multivariate prognostic models such as the Prostate Cancer Prevention Trial Risk Calculator 2.0 (PCPTRC 2.0) and the European Research Screening Prostate Cancer Risk Calculator 4 (ERSPC-RC 4). MATERIAL AND METHODS: Fifty-one patients underwent a prostate Bx according to standard clinical practice, with a minimum of 10 cores. The diagnosis of HGPC was agreed upon by 4 uropathologists. We compared the predictions from the various models by using the Mann-Whitney U test, area under the ROC curve (AUC) (DeLong test), probability density function (PDF), box plots and clinical utility curves. RESULTS: Forty-three percent of the patients had PC, and 23.5% had HGPC. The medians of probability for the 4KsT, PCPTRC 2.0 and ERSPC-RC 4 were significantly different between the patients with HGPC and those without HGPC (p≤.022) and were more differentiated in the case of 4KsT (51.5% for HGPC [25-75 percentile: 25-80.5%] vs. 16% [P 25-75: 8-26.5%] for non-HGPC; p=.002). All models presented AUCs above 0.7, with no significant differences between any of them and 4KsT (p≥.20). The PDF and box plots showed good discriminative ability, especially in the ERSPC-RC 4 and 4KsT models. The utility curves showed how a cutoff of 9% for 4KsT identified all cases of HGPC and provided a 22% savings in biopsies, which is similar to what occurs with the ERSPC-RC 4 models and a cutoff of 3%. CONCLUSIONS: The assessed predictive models offer good discriminative ability for HGPCs in Bx. The 4KsT is a good classification model as a whole, followed by ERSPC-RC 4 and PCPTRC 2.0. The clinical utility curves help suggest cutoff points for clinical decisions: 9% for 4KsT and 3% for ERSPC-RC 4. This preliminary study should be interpreted with caution due to its limited sample size.