Importance:The COVID-19 pandemic exploits existing inequalities in social determinants of health (SDOH) in disease burden and access to healthcare. Few studies have examined these emerging disparities using indicators of SDOH.Objective:To evaluate predictors of COVID-19 test positivity, morbidity, and mortality and their implications for inequalities in SDOH and for future policies and health care improvements.Design, Setting, and Participants:A cross sectional analysis was performed on all patients tested for COVID-19 on the basis of symptoms with either a history of travel to at risk regions or close contact with a confirmed case, across the Mount Sinai Health System (MSHS) up until April 26th 2020.Main Outcomes and Measures:Primary outcome was death from COVID-19 and secondary outcomes were test positivity, and morbidity (e.g., hospitalization and intubation caused by COVID-19).Results:Of 20,899 tested patients, 8,928 tested positive, 1,701 were hospitalized, 684 were intubated, and 1,179 died from COVID-19. Age, sex, race/ethnicity, New York City borough (derived from first 3 digits of zip-code), and English as preferred language were significant predictors of test positivity, hospitalization, intubation and COVID-19 mortality following multivariable logistic regression analyses.Conclusions and Relevance:People residing in poorer boroughs were more likely to be burdened by and die from COVID-19. Our results highlight the importance of integrating comprehensive SDOH data into healthcare efforts with at-risk patient populations.

Objective: To perform a systematic review and meta‐analysis of post‐radical cystectomy (RC) mortality and complications in older people to aid decision‐making pertinent to RC, as bladder cancer is typically a disease of older people, yet older people are less likely than their younger peers to undergo RC, predominantly due to concerns about morbidity and mortality of surgery. Materials and Methods: A systematic search of MEDLINE, Scopus and Ovid Emcare was performed in May 2023 for all studies in the past 20 years that reported mortality and/or complications in the 90‐days following RC. All studies reporting mortality or complication outcomes in patient groups aged >75 years were included. Exclusion criteria included partial, or organ‐sparing cystectomy, non‐English language articles, and 75 years. Results: A total of 76 studies were included, with data from 58 504 older patients across five continents and 19 countries. Post‐RC 90‐day mortality was 11% in studies reporting outcomes for patients aged ≥80 years, and 7% in studies of patients aged ≥75 years. The 90‐day mortality was higher in patients aged ≥80 years compared to patients aged <80 years (odds ratio [OR] 3.42, 95% confidence interval [CI] 1.62–7.22). Older people were more likely to experience a minor (Clavien–Dindo Grade I–II) postoperative complication than younger patients (OR 1.17, 95% CI 1.01–1.36), whereas there was no difference for major complications (Clavien–Dindo Garde III–IV; OR 1.00, 95% CI 0.63–1.60). A higher co‐morbid status was more strongly correlated with 90‐day mortality in older patients than in younger patients. Conclusions: Older patients face higher postoperative mortality following RC than younger patients. Postoperative outcomes should be weighed against the high risk of cancer‐specific death if no curative treatment is offered. Older people must be monitored closely postoperatively to try and prevent death as a result of escalation from minor and major complications.

Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) can detect multiparametric magnetic resonance imaging (mpMRI)-invisible prostate tumours and improve the sensitivity of detection of prostate cancer (PCa) in comparison to mpMRI alone. Numerous risk calculators have been validated as tools for stratification of men at risk of being diagnosed with clinically significant (cs)PCa. To develop a novel risk calculator using clinical parameters and imaging parameters from mpMRI and PSMA PET/CT in a cohort of patients undergoing mpMRI and PSMA PET/CT before biopsy. A total of 291 men from the PRIMARY prospective trial underwent mpMRI and PSMA PET/CT before transperineal prostate biopsy with sampling of systematic and targeted cores. Novel risk calculators were developed using multivariable logistic regression analysis to predict detection of overall PCa (International Society of Urological Pathology grade group [GG] ≥1) and csPCa (GG ≥2). The risk calculators were then compared with the European Randomised Study of Screening for Prostate Cancer risk calculator incorporating mpMRI (ERSPC-MRI). Resampling methods were used to evaluate the discrimination and calibration of the risk calculators and to perform decision curve analysis. Age, prostate-specific antigen, prostate volume, and mpMRI Prostate Imaging-Reporting and Data System scores were included in the MRI risk calculator, resulting in area under the receiver operating characteristic curve (AUC) values of 0.791 for overall PCa (GG ≥1) and 0.812 for csPCa (GG ≥2). Addition of the maximum standardised uptake value (SUVmax) on PSMA PET/CT for the prostate lesion, and of SUVmax for the mpMRI lesions for the MRI-PSMA risk calculator resulted in AUCs of 0.831 for overall PCa and 0.876 for csPCa (≥ISUP2).The ERSPC-MRI risk calculator had AUCs of 0.758 (p = 0.02) for overall PCa and 0.805 (p = 0.001) for csPCa. Both the MRI and MRI-PSMA risk calculators were superior to the ERSPC-MRI for both overall PCa and csPCa. These novel risk calculators incorporate clinical and radiological parameters for stratification of men at risk of csPCa. The risk calculator including PSMA PET/CT data is superior to a calculator incorporating mpMRI data alone. We evaluated a new risk calculator that uses clinical information and results from two types of scan to predict the risk of clinically significant prostate cancer on prostate biopsy. This risk model can guide patients and clinicians in shared decision-making and may help in avoiding unnecessary prostate biopsies.

Objectives: To investigate the utility of Magnetic Resonance Imaging (MRI) for prostate cancer diagnosis in the Australian setting.Patients and methods: All consecutive men who underwent a prostate biopsy (transperineal or transrectal) at Royal Melbourne Hospital between July 2017 to June 2019 were included, totalling 332 patients. Data were retrospectively collected from patient records. For each individual patient, the risk of prostate cancer diagnosis at biopsy based on clinical findings was determined using the European Randomized study of Screening for Prostate Cancer (ERSPC) risk calculator, with and without incorporation of MRI findings.Results: MRI has good diagnostic accuracy for clinically significant prostate cancer. A PI‐RADS 2 or lower finding has a negative predictive value of 96% for clinically significant cancer, and a PI‐RADS 3, 4 or 5 MRI scan has a sensitivity of 93%. However, MRI has a false negative rate of 6.5% overall for clinically significant prostate cancers. Pre‐ biopsy MRI may reduce the number of unnecessary biopsies, as up to 50.0% of negative or ISUP1 biopsies have MRI PI‐RADS 2 or lower. Incorporation of MRI findings into the ERSPC calculator improved predictive performance for all prostate cancer diagnoses (AUC 0.77 vs 0.71, P = .04), but not for clinically significant cancer (AUC 0.89 vs 0.87, P = .37).Conclusion: MRI has good sensitivity and negative predictive value for clinically significant prostate cancers. It is useful as a pre‐biopsy tool and can be used to significantly reduce the number of unnecessary prostate biopsies. However, MRI does not significantly improve risk predictions for clinically significant cancers when incorporated into the ERSPC risk calculator.

Objective: To compare the accuracy of the European Randomized Study of Screening for Prostate Cancer (ERSPC) RC, MRI‐ERSPC‐RC, and Prostate Biopsy Collaborative Group (PBCG) RC in patients undergoing transperineal prostate biopsy.Patients and methods: We identified 392 patients who underwent mpMRI before transperineal prostate biopsy across multiple public and private institutions between January 2017 and August 2019. The estimated probabilities of detecting PCa and significant PCa were calculated using the MRI‐ERSPC‐RC, ERSPC‐RC, and PBCG‐RC. Receiver operating characteristic (ROC) curves for each calculator were generated and the area underneath the curve (AUC) was compared. Calibration and clinical utility were assessed with calibration plots and decision curve analysis, respectively.Results: PCa was detected in 285 patients (72.7%) with significant PCa found in 200 patients (51.1%). ROC curve analysis found the MRI‐ERSPC‐RC outperformed the ERSPC‐RC and PBCG‐RC. For the prediction of PCa, the AUC was 0.756, 0.696, and 0.675 for the MRI‐ERSPC‐RC, ERSPC‐RC, and PBCG‐RC, respectively. The AUC for the prediction of significant PCa was 0.803, 0.745, and 0.746 for the MRI‐ERSPC‐RC, ERSPC‐RC, and PBCG‐RC, respectively.Conclusions: Our study validated the ERSPC‐RC, MRI‐ERSPC‐RC, and PBCG‐RC in a cohort undergoing transperineal prostate biopsy with the MRI‐ERSPC‐RC performing the best. These RCs may enable improved shared decision making and help to guide patient selection for biopsy.