Search

Patients presenting with microhematuria represent a heterogeneous population with a broad spectrum of risk for genitourinary malignancy. Recognizing that patient-specific characteristics modify the risk of underlying malignant etiologies, this guideline sought to provide a personalized diagnostic testing strategy.The systematic review incorporated evidence published from January 2010 through February 2019, with an updated literature search to include studies published up to December 2019. Evidence-based statements were developed by the expert Panel, with statement type linked to evidence strength, level of certainty, and the Panel's judgment regarding the balance between benefits and risks/burdens.Microhematuria should be defined as ≥ 3 red blood cells per high power field on microscopic evaluation of a single specimen. In patients diagnosed with gynecologic or non-malignant genitourinary sources of microhematuria, clinicians should repeat urinalysis following resolution of the gynecologic or non-malignant genitourinary cause. The Panel created a risk classification system for patients with microhematuria, stratified as low-, intermediate-, or high-risk for genitourinary malignancy. Risk groups were based on factors including age, sex, smoking and other urothelial cancer risk factors, degree and persistence of microhematuria, as well as prior gross hematuria. Diagnostic evaluation with cystoscopy and upper tract imaging was recommended according to patient risk and involving shared decision-making. Statements also inform follow-up after a negative microhematuria evaluation.Patients with microhematuria should be classified based on their risk of genitourinary malignancy and evaluated with a risk-based strategy. Future high-quality studies are required to improve the care of these patients.

INTRODUCTION AND OBJECTIVE:In April 2017 the United States Preventive Services Task Force (USPSTF) published a draft guideline that reversed 2012 guidance against routine screening for prostate can...

INTRODUCTION AND OBJECTIVE:Prostate MRI and tissue-based gene expression (genomic) testing may facilitate the use of observational management for prostate cancer, however their independent role is ...

INTRODUCTION AND OBJECTIVES:Young adults are historically the least likely to have health insurance in the United States. We aimed to investigate whether implementation of key provisions of the Aff...

Surgical treatment for prostate cancer represents a large national health care expenditure. We determined whether state level variation in the cost of radical prostatectomy exists and whether we could explain this variation by adjusting for covariates associated with cost.Using the 2004 Healthcare Cost and Utilization Project National Inpatient Sample of 7,978,041 patients we identified 9,917 who were 40 years old or older with a diagnosis of prostate cancer who underwent radical prostatectomy without cystectomy. We used linear regression to examine state level regional variation in radical prostatectomy costs, controlling for the local area wage index, patient demographics, case mix and hospital characteristics.The mean +/- SD unadjusted cost was $9,112 +/- $4,434 (range $2,001 to $49,922). The unadjusted mean cost ranged from $12,490 in California to $4,650 in Utah, each significantly different from the mean of $8,903 in the median state, Washington (p0.0001). After adjusting for all potential confounders total cost was highest in Colorado and lowest in New Jersey, which were significantly different from the median, Washington ($10,750 and $5,899, respectively, vs $8,641, p0.0001). The model explained 85.9% of the variance with regional variation accounting for the greatest incremental proportion of variance (35.1%) and case mix variables accounting for an incremental 32.3%.The total cost of radical prostatectomy varies significantly across states. Controlling for known total cost determinants did not completely explain these differences but altered ordinal cost relationships among states. Cost variation suggests inefficiencies in the health care market. Additional studies are needed to determine whether these variations in total cost translate into differences in quality or outcome and how they may be translated into useful policy measures.

INTRODUCTION AND OBJECTIVES: The rapid diffusion of the surgical robot has been fraught with controversy because of the technology’s high costs and disputed marginal benefit. Some have suggested that adoption of the surgical robot has facilitated partial nephrectomy (PN), an underutilized procedure considered more challenging yet less morbid than radical nephrectomy. We sought to determine whether institutional acquisition of the robot was associated with a higher rate of PN. METHODS: We used the 2001, 2005 and 2008 Health-care Cost and Utilization Project State In-patient Databases from 7 states to identify 21,569 surgical procedures for renal tumors. These patient-level records were aggregated to the hospital-level then merged with the American Hospital Association Survey and with publicly available data on timing of robot acquisition. We used a difference-in-difference model to assess whether robot acquisition was associated with an increase in the PN rate, adjusting for total nephrectomy rate, year of surgery, year of robot acquisition and several hospital-level factors. We performed two sensitivity analyses to determine whether there was a time lag between robot acquisition and changes in PN utilization (because of a presumed necessity to develop requisite surgical skill) and to ensure no association existed between robot acquisition and performance of an unrelated procedure (the presence of which might suggest an unmeasured confounding characteristic was the actual cause for increased surgical volume). RESULTS: In the multivariable adjusted differences-in-differences model (Figure 1), hospitals acquiring a robot between 2001-2005 performed more PN in both 2005 (30% increase) and 2008 (35% total increase) (p

INTRODUCTION AND OBJECTIVES: The surgical robot has been widely adopted in the United States in spite of its high cost and controversy surrounding its benefit. We identified hospital and regional factors were associated with early adoption of this new technology by hospitals. METHODS: To ascertain robot acquisition by hospitals, we combined publicly available data from the website of the robot’s sole manufacturer (Intuitive Surgical, Sunnyvale, CA) with data collected from the websites and personnel of the hospitals themselves. These data were subsequently linked with data on numbers of radical prostatectomy aggregated to the hospital level from the 2001 and 2005 Healthcare Cost and Utilization Project State Inpatient Databases from AZ, FL, MD, NC, NY, NJ, and WA as well as data from the 2005 American Hospital Association Annual Survey. We performed a survival time analysis with the primary dependent variable of interest being time to acquisition of the surgical robot. Our primary independent variable of interest was hospital teaching status. We identified 554 total hospitals performing radical prostatectomy; 67 of these hospitals had acquired a surgical robot by the end of 2005. RESULTS: Hospitals acquiring robots during the study period performed more radical prostatectomies on average in 2001 (90 vs.18, p 0.01), had more average hospital beds (562 vs. 267, p 0.01), and were more likely to be teaching hospitals (67% vs. 33%, p 0.01) than their counterparts who did not acquire surgical robots. A multivariable Cox proportional hazards model demonstrated that these 3 variables were independently associated with time to robot acquisition: baseline radical prostatectomy volume in 2001 (HR for High vs. Low 8.44, HR for Medium vs. Low 3.13, p 0.01), teaching status (HR 3.44, p 0.01), and hospital bed number (HR 1.01 per every 10 beds, p 0.02). The model fit the data well with a concordance index of 0.83. Neither hospital ownership nor quantification of regional level competition was significantly associated with robot acquisition. CONCLUSIONS: The surgical robot was adopted first by larger, busier, teaching institutions. It remains unclear what impact the early acquisition of new technology at teaching hospitals might have on trainees and future patterns of care.

INTRODUCTION AND OBJECTIVE: The Partin Tables are a widely used nomogram predicting the pathologic stage of prostate cancer (CaP) given common preoperative clinical characteristics. The model is based on patients undergoing radical prostatectomy (RP) at the Johns Hopkins Medical Institutions, a tertiary care center. We sought to validate the Partin tables using a large national cohort to see whether the model could be applied to all patients undergoing RP for CaP in the United States. METHODS: The published 2007 Partin Tables were used to estimate the risk of positive lymph nodes (LN+), seminal vesicle invasion (SV+), and extraprostatic extension (EPE+) in men with prostate cancer from the NCI-SEER Database using clinical stage, preoperative PSA, and Gleason score. The discriminative and predictive ability of the tables were explored by constructing receiver operating characteristic (ROC) and calibration curves. An overall Brier score was calculated for each endpoint. The utility of the nomogram was determined based on clinically relevant endpoints. RESULTS: We identified 11,185 men who underwent RP for CaP in the years 2004-2005. The Partin tables discriminated between patient groups at risk for lymph node involvement and seminal vesicle involvement well, with an AUC of 0.77 and 0.74, and Brier score 0.026 and 0.042, respectively. Extraprostatic extension discrimination and prediction was more limited (AUC 0.62, Brier score 0.171). CONCLUSIONS: The Partin tables showed excellent discrimination for seminal vesicle and lymph node involvement. Prediction of lymph node involvement was reasonable even within lower risk groups. Prediction of extraprostatic extension and seminal vesicle involvement was somewhat more limited.