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Background: The optimal timing for discontinuing screening of prostate cancer (PCa) in elderly men is currently not known and remains debated. Objective: To assess prostate cancer–specific mortality (PCSM) in elderly men who previously underwent prostate-specific antigen (PSA)-based screening and to identify those who may benefit from continued screening. Design, setting, and participants: A total of 7052 men, who participated in the screening arm of the Rotterdam section of the European Randomized Study of Screening for Prostate Cancer and were aged 70–74 yr at their last screening visit after undergoing a maximum of three screening rounds without being diagnosed with PCa, were included. Outcome measurements and statistical analysis: The cumulative incidence of PCSM by the age of 85 yr was assessed. Additionally, a competing risk regression was performed to assess the potential predictors of PCSM. Results and limitations: The median follow-up was 16 yr. The cumulative incidence of PCSM by the age of 85 yr was 0.54% (95% confidence interval [CI]: 0.40–0.70) in all men, 0.11% (95% CI: 0.05–0.27) in men with PSA <2 ng/ml, 0.85% (95% CI: 0.47–1.5) in men with PSA 2–3 ng/ml, and 6.8% (95% CI: 3.1–15) in men with PSA ≥6.5 ng/ml and no previous benign biopsy. PSA (subdistribution hazard ratio [sHR]: 2.0; 95% CI: 1.7–2.3), previous benign prostate biopsy (sHR: 0.41; 95% CI: 0.23–0.72), and hypertension (sHR: 0.48; 95% CI: 0.25–0.91) were significantly associated with PCSM. Conclusions: Men aged 70–74 yr who have previously undergone PSA-based screening without receiving a PCa diagnosis have a very low risk of dying from PCa by the age of 85 yr. These data suggest that screening may be discontinued in men with PSA <3.0 ng/ml or previous benign prostate biopsies. Those with higher PSA levels and no prior biopsies may consider continued screening if

BACKGROUND AND OBJECTIVE: The possible negative impact of radical surgery on patients' health-related quality of life (HRQoL) plays an important role in preoperative counseling. Here, we analyzed the HRQoL of patients treated for upper urinary tract urothelial carcinoma (UTUC) in the context of a single-arm phase 2 multicenter study, in which the safety and efficacy of a single preoperative intravesical instillation with mitomycin C were investigated. Our objective was to investigate early changes in HRQoL in patients undergoing radical surgery for UTUC and identify factors associated with these outcomes.METHODS: Patients with pTanyN0-1M0 UTUC were prospectively included. HRQoL was assessed using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ-C30) questionnaire at baseline, and at 1 and 3 mo after surgery. A linear mixed model was used to evaluate the changes in HRQoL over time and identify the variables associated with these outcomes. The clinical effect size was used to assess the clinical impact and level of perceptibility of HRQoL changes for clinicians and/or patients based on given thresholds.KEY FINDINGS AND LIMITATIONS: Between 2017 and 2020, 186 patients were included. At baseline, 1 mo after surgery, and 3 mo after surgery, response rates were 91%, 84%, and 78%, respectively. One month after surgery, a statistically significant and clinically relevant deterioration was observed in physical, role, and social functioning, and for the included symptom scales: constipation, fatigue, and pain. An improvement in emotional functioning was observed. At 3 mo, HRQoL returned to baseline levels, except emotional functioning, which improved at 1 mo and persisted to be better than that before surgery. Age >70 yr was associated with worse physical functioning, but better social and emotional functioning. Male patients reported better emotional functioning than fe

Cancer survivorship was recently identified as a prostate cancer (PCa) research priority by PIONEER, a European network of excellence for big data in PCa. Despite being a research priority, cancer survivorship lacks a clear and agreed definition, and there is a distinct paucity of patient-reported outcome (PRO) data available on the subject. Data collection on cancer survivorship depends on the availability and implementation of (validated) routinely collected patient-reported outcome measures (PROMs). There have been recent advances in the availability of such PROMs. For instance, the European Organisation for Research and Treatment of Cancer Quality of Life Group (EORTC QLG) is developing survivorship questionnaires. This provides an excellent first step in improving the data available on cancer survivorship. However, we propose that an agreed, standardised definition of (prostate) cancer survivorship must first be established. Only then can real-world data on survivorship be collected to strengthen our knowledge base. With more men than ever surviving PCa, this type of research is imperative to ensure that the quality of life of these men is considered as much as their quantity of life. Patient summary: As there are more prostate cancer survivors than ever before, research into cancer survivorship is crucial. We highlight the importance of such research and provide recommendations on how to carry it out. The first step should be establishing agreement on a standardised definition of survivorship. From this, patient-reported outcome measures can then be used to collect important survivorship data.

Objectives: To compare the performance of currently available biopsy decision support tools incorporating magnetic resonance imaging (MRI) findings in predicting clinically significant prostate cancer (csPCa). Patients and Methods: We retrospectively included men who underwent prostate MRI and subsequent targeted and/or systematic prostate biopsies in two large European centres. Available decision support tools were identified by a PubMed search. Performance was assessed by calibration, discrimination, decision curve analysis (DCA) and numbers of biopsies avoided vs csPCa cases missed, before and after recalibration, at risk thresholds of 5%–20%. Results: A total of 940 men were included, 507 (54%) had csPCa. The median (interquartile range) age, prostate-specific antigen (PSA) level, and PSA density (PSAD) were 68 (63–72) years, 9 (7–15) ng/mL, and 0.20 (0.13–0.32) ng/mL2, respectively. In all, 18 multivariable risk calculators (MRI-RCs) and dichotomous biopsy decision strategies based on MRI findings and PSAD thresholds were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (area under the receiver operating characteristic curve 0.86) of the MRI-RCs that could be assessed in the whole cohort. DCA showed the highest clinical utility for the Van Leeuwen model, followed by the RPCRC. At the 10% threshold the Van Leeuwen model would avoid 22% of biopsies, missing 1.8% of csPCa, whilst the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCas. These multivariable models outperformed all dichotomous decision strategies based only on MRI-findings and PSAD. Conclusions: Even in this high-risk cohort, biopsy decision support tools would avoid many prostate biopsies, whilst missing very few csPCa cases. The Van Leeuwen model had the highest clinical utility, followed by the RPCRC. These multivariable MRI-R

BACKGROUND: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics.OBJECTIVE: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data.DESIGN, SETTING, AND PARTICIPANTS: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146).OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data.RESULTS AND LIMITATIONS: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent.CONCLUSIONS: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and

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. Methods: We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria. Key findings and limitations: The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance. Conclusions and clinical implications: Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa. Patient summary: In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.

Importance: Magnetic resonance imaging (MRI)-based risk calculators can replace or augment traditional prostate cancer (PCa) risk prediction tools. However, few data are available comparing performance of different MRI-based risk calculators in external cohorts across different countries or screening paradigms. Objective: To externally validate and compare MRI-based PCa risk calculators (Prospective Loyola University Multiparametric MRI [PLUM], UCLA [University of California, Los Angeles]-Cornell, Van Leeuwen, and Rotterdam Prostate Cancer Risk Calculator-MRI [RPCRC-MRI]) in cohorts from Europe and North America. Design, Setting, and Participants: This multi-institutional, external validation diagnostic study of 3 unique cohorts was performed from January 1, 2015, to December 31, 2022. Two cohorts from Europe and North America used MRI before biopsy, while a third cohort used an advanced serum biomarker, the Prostate Health Index (PHI), before MRI or biopsy. Participants included adult men without a PCa diagnosis receiving MRI before prostate biopsy. Interventions: Prostate MRI followed by prostate biopsy. Main Outcomes and Measures: The primary outcome was diagnosis of clinically significant PCa (grade group ≥2). Receiver operating characteristics for area under the curve (AUC) estimates, calibration plots, and decision curve analysis were evaluated. Results: A total of 2181 patients across the 3 cohorts were included, with a median age of 65 (IQR, 58-70) years and a median prostate-specific antigen level of 5.92 (IQR, 4.32-8.94) ng/mL. All models had good diagnostic discrimination in the European cohort, with AUCs of 0.90 for the PLUM (95% CI, 0.86-0.93), UCLA-Cornell (95% CI, 0.86-0.93), Van Leeuwen (95% CI, 0.87-0.93), and RPCRC-MRI (95% CI, 0.86-0.93) models. All models had good discrimination in the North American cohort, with an AUC of 0.85 (95% CI, 0.80-0.89) for PLUM and AUCs of 0.83 for the UCLA-Cornell (95% CI, 0.80-0.88), Van Leeuwen (95% CI, 0.79-0.8