Purpose

The adequacy of the urologist work force in absolute numbers and relative distribution is unclear. To develop effective policies addressing the needs of an aging population we must better understand the urologist work force. We assessed the geographic distribution of urologists throughout the United States at the county level and determined the county characteristics associated with increased urologist density.

Materials and methods

County level data from the Department of Health and Human Services Area Resource File and the United States Census were analyzed in this ecological study. Logistic regression and ordinal logistic regression models were built to identify predictors of urologist density, defined as the number of urologists per 100,000 individuals. National patterns of urologist density were mapped graphically at the county level.

Results

Overall 63% of the counties in the United States lack a urologist. Based on multivariate models urologists were less likely to be found in nonmetropolitan counties (OR 0.57, 95% CI 0.46-0.72) and rural counties (OR 0.03, 95% CI 0.02-0.06) than in metropolitan counties, which confirmed visually mapped models. Patterns of urologist density also appeared to be influenced by climate and county education levels rather than by traditional socioeconomic measures. Urologists younger than 45 years old were 3 times less likely to be located in nonmetropolitan and rural counties than their older counterparts.

Conclusions

The uneven distribution of urologists throughout the United States is likely to worsen as younger physicians continue to cluster in urban areas. Governing bodies must consider this distribution in their calls for increasing the number of training positions.

Purpose

The surgical work force distribution at the county level varies widely across the United States, and the impact of differential access on cancer outcomes is unclear. We used urologists as a test case because they are the first care providers for urologic cancers, can easily be identified from available data sources, and are unevenly distributed throughout the country. The goal of this study was to determine the effect of increasing urologist density on local prostate, bladder, and kidney cancer mortality.

Patients and methods

Using county-level data from the Area Resource File, US Census, National Cancer Institute, and Centers for Disease Control, regression models were built for prostate, bladder, and kidney cancer mortality, controlling for categorized urologist density, county demographics, socioeconomic factors, and preexisting health care infrastructure.

Results

For each of the three cancers, there was a statistically significant cancer-specific mortality reduction associated with counties that had more than zero urologists (16% to 22% reduction for prostate cancer, 17% to 20% reduction for bladder cancer, and 8% to 14% reduction for kidney cancer with increasing urologist density) relative to zero urologists. However, increasing density greater than two urologists per 100,000 people had no statistically significant impact on mortality for any of the tumors studied.

Conclusion

The presence of a urologist is associated with lower mortality for urologic cancers in that county, but increasing urologist density does not yield further improvements. Therefore, a nuanced and geographically aware policy toward the size and distribution of the future work force is most likely to provide the greatest population-level improvement in cancer mortality outcomes.

Background

ImmunoCyt/uCyt (Scimedx, Denville, NJ, USA) is a well-established urinary marker assay with high sensitivity for the diagnosis of urothelial carcinoma (UC) and can function as a second-level test to arbitrate atypical reads of urine cytology.

Objective

To determine the utility of uCyt as a reflex test for atypical cytology in patients undergoing a hematuria evaluation or surveillance with a history of UC.

Design, setting, and participants

The uCyt assay was performed as a second-level reflex test on all voided urine cytology tests read as atypical between January 2007 and June 2010 in an academic medical center. Records were retrospectively reviewed. Three hundred twenty-four patients underwent a total of 506 uCyt assays.

Intervention

Reflex uCyt assay on atypical urine cytology.

Outcome measurements and statistical analysis

The uCyt test characteristics include sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV).

Results and limitations

Reflex uCyt was performed on 506 atypical voided urine samples that were followed by cystoscopy within 90 d. Reflex uCyt with a history of UC showed a sensitivity of 73%, a specificity of 49%, and an NPV of 80%. In those with a history of low-grade UC, reflex uCyt had a sensitivity of 75%, a specificity of 50%, and an NPV of 82%, while in those with a history of high-grade UC, it had a sensitivity of 74%, a specificity of 44%, and an NPV of 79%. Without prior history of UC, reflex uCyt had a sensitivity of 85%, a specificity of 59%, and an NPV of 94%. This study's limitations include its retrospective design and interobserver variability inherent to cystoscopy, which was used as the reference test.

Conclusions

When used as a reflex test on atypical urine cytology, negative uCyt may predict a negative cystoscopy in select patients and modulate the urgency and further work-up in those with no prior history or low-grade disease.

Introduction

Digital rectal examination (DRE) is part of the clinical evaluation of men on active surveillance (AS). The purpose of the present study is to analyze the value of DRE as a predictor of upgrading in a population of men with prostate cancer (PCa) treated with AS.

Methods

We used the prostate biopsy (PBx) database from an academic center, including PBx from 2006-2018, and identified 2029 confirmatory biopsies (CxPBx) of men treated with AS, of which 726 men had both diagnostic (initial) and CxPBx information available. We did a descriptive analysis and evaluated sensitivity, specificity, and predictive values of DRE for the detection of clinically significant PCa (csPCa). Multivariable regression analysis was done to identify predictors of csPCa. The primary outcome was to evaluate DRE as a predictor of the presence of csPCa at CxPBx.

Results

Among the 2029 patients with a CxPBx, 75% had PCa, and of these, 30.3% had upgrading to International Society of Urologic Pathologists (ISUP) grade ≥2. Thirteen percent of men had a suspicious DRE (done by their treating physician). Sensitivity, specificity, negative and positive predictive values of DRE to detect csPCa were best with a prostate-specific antigen (PSA) <4 ng/ml (27%, 88%, 31%, and 87%, respectively). A suspicious DRE at CxPBx, particularly if the DRE at diagnosis was negative, was a predictor of csPCa (odds ratio [OR] 2.34, p=0.038). The main limitation of our study is the retrospective design and the lack of magnetic resonance imaging.

Conclusions

We believe DRE should still be used as part of AS and can predict the presence of csPCa, even with low PSA values. A suspicious nodule on DRE represents a higher risk of upgrading and should prompt further assessment.

Introduction

This was a secondary analysis aiming to assess whether hydrophilic or hydrophobic statins have a differential effect on urinary retention (UR) and lower urinary tract symptoms (LUTS) in men following a prostate biopsy (PBx), who were at risk for prostate cancer development.

Methods

This was a population-based cohort study with data incorporated from the Institute for Clinical and Evaluative Sciences database to identify all Ontarian men aged 66 and above with a history of a single negative PBx between 1994 and 2016, with no drug prescription history of any of several putative chemo-preventative medications (statins, proton pump inhibitors, five-alpha-reductase inhibitors, and alpha-blockers). Multivariable Cox regression models with time-dependent covariates were used to assess the association of hydrophilic and hydrophobic statins with UR and LUTS within 30 days of a PBx. All models were adjusted for other known putative chemopreventive medications, age, rurality, pharmacologically treated diabetes, comorbidity score, and study inclusion year.

Results

Overall, 21 512 men were included, with a median followup time of 9.4 years (interquartile range [IQR] 5.4-13.4 years). Hydrophobic and hydrophilic statins were initiated by 30.7% and 19.6% of men, respectively, after the first negative PBx. UR and LUTS were experienced by 2.2% and 10% of men, respectively. Cox models demonstrated hydrophilic statins were associated with a lower risk of UR (hazard ratio [HR] 0.56, 95% confidence interval [CI] 0.38-0.83, p=0.0038) and LUTS (HR 0.86, 95% CI 0.76-0.98, p=0.022), while no such association was shown for hydrophobic statins.

Conclusions

Initiation of hydrophilic statins in men older than 66 appears to be inversely associated with the risk of UR and LUTS within 30 days of a PBx.

Introduction

Active surveillance (AS) is standard of care in low-risk prostate cancer (PCa). This study describes a novel total cancer location (TCLo) density metric and aims to determine its performance in predicting clinical progression (CP) and grade progression (GP).

Methods

This was a retrospective study of patients on AS after confirmatory biopsy (CBx). We excluded patients with Gleason ≥7 at CBx and <2 years followup. TCLo was the number of locations with positive cores at diagnosis (DBx) and CBx. TCLo density was TCLo/prostate volume (PV). CP was progression to any active treatment while GP occurred if Gleason ≥7 was identified on repeat biopsy or surgical pathology. Independent predictors of time to CP or GP were estimated with Cox regression. Kaplan-Meier analysis compared progression-free survival (PFS) curves between TCLo density groups. Test characteristics of TCLo density were explored with receiver operating characteristic (ROC) curves.

Results

We included 181 patients who had CBx from 2012-2015 and met inclusion criteria. The mean age of patients was 62.58 years (standard deviation [SD] 7.13) and median followup was 60.9 months (interquartile range [IQR] 23.4). A high TCLo density score (>0.05) was independently associated with time to CP (hazard ratio [HR] 4.70; 95% confidence interval [CI] 2.62-8.42; p<0.001) and GP (HR 3.85; 95% CI 1.91-7.73; p<0.001). ROC curves showed TCLo density has greater area under the curve than number of positive cores at CBx in predicting progression.

Conclusions

TCLo density is able to stratify patients on AS for risk of CP and GP. With further validation, it could be added to the decision-making algorithm in AS for low-risk localized PCa.