endpoints were clinically insignificant cancers, number of MRIs and biopsies.RESULTS: Of the 12,750 men who participated, 600 of the 5134 (11.7%) men had Stockholm3 !15% in the blood-based arm, and 929 of the 7609 (12.2%) men had PSA !3 ng/ml in the imaging-based arm. Significant prostate cancer was detected in 119 men (2.3%) using the blood-based strategy and in 192 men (2.5%) using the imagingbased strategy, for a relative difference of 1.08 [95% CI, 0.87-1.34]. More biopsies, 326 (6.3%) vs. 338 (4.4%), were taken (0.70 [95% CI, 0.61-0.79]), and more insignificant prostate cancers were detected 61 (1.2%) vs. 31 (0.5%) (0.45 [95% CI, 0.31-0.66]) using the bloodbased strategy compared to the imaging-based strategy.CONCLUSIONS: The Stockholm3 test combined with systematic biopsies can detect clinically significant prostate cancers at similar rates as PSA testing combined with MRI followed by systematic and targeted biopsies. However, with a higher number of detected clinically insignificant cancers and performed biopsies, the utility of the Stock-holm3 test combined with systematic biopsies would be in areas with limited access to MRIs.
4þ3, it increased from 68.1% to 70.8%. In general, there was an increment of 7-12% across the board.CONCLUSIONS: Our machine learning model has the potential to not only automate but also vastly enhance the utility to detect PCa early and aid in clinical decision making. Given the accuracy of our current model, we are hopeful of producing an automated software workflow that will aid in identifying tumor areas, determining their severity, and influencing treatment decisions.
While the prevalence of microscopic hematuria (MH) in the general population remains high, the malignancy detection rate is low. Extensive workup may create unnecessary radiation and instrumentation. Multiple guidelines and nomograms have been published to help reduce excessive evaluations. This study aimed to review our institution's malignancy detection rate, modelled using the revised 2021 AUA/SUFU Microhematuria guideline and Kaiser-Permanente Hematuria Risk Index (HRI).METHODS: Retrospective review of our microscopic hematuria database of 3,147 patients to analyze malignancy detection rate, stratified for the 2021 AUA guidelines and HRI risk categories. Patient inclusion was RBC ! 3/hpf with completed fields for demographics, risk factors, and full work-up. Categorization of malignancy was further broken down into grade, stage, and type. Solid parenchymal tumors (SPT) were included if pathologically confirmed or highly suspicious on imaging. Patients who presented with MH but had a history of gross hematuria were stratified per AUA or HRI grouping. Statistical analysis was performed by area under receiver operating characteristic curves.RESULTS: 2,001 patients met inclusion criteria. Overall, 36 neoplasms were diagnosed after workup: 21 non-muscle invasive bladder cancer, 1 muscle-invasive bladder cancer, 2 upper tract urothelial cancers, 12 SPTs. AUA risk categories had a total positive detection rate of 0% (Low), 0.67% (Medium), and 2.83% (High). HRI score (0-11) showed malignancy detection rates of 0.97% (Low; 0-4), 2.65% (Moderate; 5-8), and 9.68% (High;(9)(10)(11). Looking only at urothelial malignancies (excluding SPT), the breakdown (AUA versus HRI respectively) was Low: 0 vs 0.18%, Medium/Moderate: 0.13 vs 2.28%, and High: 2.10 vs 9.68%. The HRI classified 1,139 patients as low-risk with 2 urothelial malignancies detected (0.18%), while the AUA classification only included 163 patients (0%). The HRI score stratification urothelial detection area under the curve for ROC was 0.812 compared to 0.709 (AUA).CONCLUSIONS: After stratifying our database population based on the 2021 AUA/SUFU Guideline and Kaiser-Permanente HRI, we found that both groups had linear increases in malignancy detection rates with increasing risk group. However, the HRI, which uses a more granular categorization, would have avoided unnecessary workup in a significantly higher proportion of patients. Future directions should analyze further sub-stratification to create a more specific nomogram that avoids unnecessary workup.
INTRODUCTION AND OBJECTIVE: Gross Hematuria (GH) is associated with up to 20-25% incidence of genitourinary (GU) malignancy. Given that the emergency department (ED) is often the first point of care for patients presenting with GH, we assessed the demographics of GH patients presenting to the ED and subsequently diagnosed with new genitourinary (GU) malignancy within a safety net, tertiary care health system over a one-year period.METHODS: Patients presenting with GH to six EDs within the Henry Ford Health System (Southeast Michigan) between 1/1/2019 to 12/31/2019 and subsequently newly diagnosed GU malignancy were evaluated with respect to relevant socio-demographic and tumor variables.RESULTS: Of the 286,313 ED presentations in 2019, 1370 had a diagnosis of GH (0.48%), and 19 (1.4%) were subsequently diagnosed with of GU cancer.Median (IQR) age at diagnosis was 73 (68.5-84) years, 16% were Black, 26% female, 25% had family history of GU cancer and 58% were active smokers (average 42 pack year). Median household income was $54,168, 9% less than median state income. All patients were insured.Median time to diagnosis was 33 days, which was reduced to 20 days if Urology was consulted. Bladder (53%) and prostate (26%) comprised the majority of newly diagnosed GU cancers (Figure 1).CONCLUSIONS: Somewhat contrary to our hypothesis, GH represented w0.5% of all ED visits, with a small proportion (1.4%) being diagnosed with new GU cancer. This may be related to stage migration (earlier detection of cancers with imaging), better insurance (100% of our cohort was insured) or better access to care (HFHS is a tertiary care, safety net hospital). While timely urology evaluation decreased time for diagnosis (33 to 20 days) and majority (53%) were newly diagnosed with bladder cancer, nearly half harbored advanced prostate or kidney cancer when presenting with GH. Limitations of our study include a short analytic cohort (1 year), lack of survival outcomes and single center data.
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