Faculty Bibliography

To examine the prevalence and content of robotic surgery information presented on websites of U.S. hospitals. We completed a systematic analysis of 400 randomly selected U.S. hospital websites in June of 2010. Data were collected on the presence and location of robotic surgery information on a hospital's website; use of images or text provided by the manufacturer; use of direct link to manufacturer website; statements of clinical superiority; statements of improved cancer outcome; mention of a comparison group for a statement; citation of supporting data and mention of specific risks. Forty-one percent of hospital websites described robotic surgery. Among these, 37% percent presented robotic surgery on their homepage, 73% used manufacturer-provided stock images or text, and 33% linked to a manufacturer website. Statements of clinical superiority were made on 86% of websites, with 32% describing improved cancer control, and 2% described a reference group. No hospital website mentioned risks. Materials provided by hospitals regarding the surgical robot overestimate benefits, largely ignore risks and are strongly influenced by the manufacturer.

INTRODUCTION: The successful treatment of prostate cancer depends on the accurate estimation of the risk of regional lymph node (LN) involvement. The Roach formula (RF) has been criticized as overestimating LN risk. A modification of the RF has been attempted by other investigators using simplified adjustment ratios: the Nguyen formula (NF). METHODS AND MATERIALS: The National Cancer Institute Surveillance, Epidemiology, and End Results database was investigated for patients treated in 2004 through 2006 for whom at least 10 LN were examined at radical prostatectomy, cT1c or cT2 disease, and prostate-specific antigen (PSA) <26 ng/ml (N = 2,930). The Yale formula (YF) was derived from half of the sample (n = 1,460), and validated in the other half (n = 1,470). RESULTS: We identified 2,930 patients. Only 4.6% of patients had LN+, and 72.6% had cT1c disease. Gleason (GS) 8-10 histology was found in 14.4% of patients. The YF for prediction of %LN+ risk is [

OBJECTIVES: * To develop a '2010 Partin Nomogram' with total prostate-specific antigen (tPSA) as a continuous biomarker, in light of the fact that the current 2007 Partin Tables restrict the application of tPSA as a non-continuous biomarker by creating 'groups' for risk stratification with tPSA levels (ng/mL) of 0-2.5, 2.6-4.0, 4.1-6.0, 6.1-10.0 and >10.0. * To use a 'predictiveness curve' to calculate the percentile risk of a patient among the cohort. PATIENTS AND METHODS: * In all, 5730 and 1646 patients were treated with radical prostatectomy (without neoadjuvant therapy) between 2000 and 2005 at the Johns Hopkins Hospital (JHH) and University Clinic Hamburg-Eppendorf (UCHE), respectively. * Multinomial logistic regression analysis was performed to create a model for predicting the risk of the four non-ordered pathological stages, i.e. organ-confined disease (OC), extraprostatic extension (EPE), and seminal vesicle (SV+) and lymph node (LN+) involvement. * Patient-specific risk was modelled as a function of the B-spline basis of tPSA (with knots at the first, second and third quartiles), clinical stage (T1c, T2a, and T2b/T2c) and biopsy Gleason score (5-6, 3 + 4 = 7, 4 + 3 = 7, 8-10). RESULTS: * The '2010 Partin Nomogram' calculates patient-specific absolute risk for all four pathological outcomes (OC, EPE, SV+, LN+) given a patient's preoperative clinical stage, tPSA and biopsy Gleason score. * While having similar performance in terms of calibration and discriminatory power, this new model provides a more accurate prediction of patients' pathological stage than the 2007 Partin Tables model. * The use of 'predictiveness curves' has also made it possible to obtain the percentile risk of a patient among the cohort and to gauge the impact of risk thresholds for making decisions regarding radical prostatectomy. CONCLUSION: * The '2010 Partin Nomogram' using tPSA as a continuous biomarker together with the corresponding 'predictiveness curve' will help clinicians and patients to make improved treatment decisions

BACKGROUND: Despite its expense and controversy surrounding its benefit, the surgical robot has been widely adopted for the treatment of prostate cancer. OBJECTIVES: To determine the relationship between surgical robot acquisition and changes in volume of radical prostatectomy (RP) at the regional and hospital levels. RESEARCH DESIGN: Retrospective cohort study. SUBJECTS: Men undergoing RP for prostate cancer at nonfederal, community hospitals located in the states of Arizona, Florida, Maryland, North Carolina, New York, New Jersey, and Washington. MEASURES: Change in number of RPs at the regional and hospital levels before (2001) and after (2005) dissemination of the surgical robot. RESULTS: Combining data from the Healthcare Cost and Utilization Project State Inpatient Databases 2001 and 2005 with the 2005 American Hospital Association Survey and publicly available data on robot acquisition, we identified 554 hospitals in 71 hospital referral regions (HRR). The total RPs decreased from 14,801 to 14,420 during the study period. Thirty six (51%) HRRs had at least 1 hospital with a surgical robot by 2005; 67 (12%) hospitals acquired at least 1 surgical robot. Adjusted, clustered generalized estimating equations analysis demonstrated that HRRs with greater numbers of hospitals acquiring robots had higher increases in RPs than HRRs acquiring none (mean changes in RPs for HRRs with 9, 4, 3, 2, 1, and 0 are 414.9, 189.6, 106.6, 14.7, -11.3, and -41.2; P<0.0001). Hospitals acquiring surgical robots increased RPs by a mean of 29.1 per year, while those without robots experienced a mean change of -4.8, P<0.0001. CONCLUSIONS: Surgical robot acquisition is associated with increased numbers of RPs at the regional and hospital levels. Policy makers must recognize the intimate association between technology diffusion and procedure utilization when approving costly new medical devices with unproven benefit

OBJECTIVES: To assess a novel application of the Prostate Health Index (phi) and biopsy tissue DNA content in benign-adjacent and cancer areas to predict which patients would eventually require treatment of prostate cancer in the Proactive Surveillance cohort. METHODS: We identified 71 men who had had serum and biopsy tissue from their diagnosis banked and available for the present study. Of the 71 patients, 39 had developed unfavorable biopsy findings and 32 had maintained favorable biopsy status during surveillance. The serum total prostate-specific antigen (tPSA), free PSA (fPSA) and [-2]proPSA were measured using the Beckman Coulter immunoassay. The DNA content measurements of Feulgen-stained biopsy sections were performed using the AutoCyte imaging system. RESULTS: The ratio of phi was significantly greater (37.23 +/- 15.76 vs 30.60 +/- 12.28; P = .03) in men who ultimately had unfavorable biopsy findings. The serum phi ratio (P = .003), [-2]proPSA/%fPSA (P = .004), biopsy tissue DNA content (ie, benign-adjacent excess of optical density, P = .019; and cancer area standard deviation of optical density, P = .002) were significant predictors of unfavorable biopsy conversion on Cox regression analysis. However, phi and [-2]proPSA/%fPSA showed a highly significant correlation (rho = 0.927, P < .0001) and no difference in accuracy (c-index, 0.6247 vs 0.6158; P = .704) for unfavorable biopsy conversion prediction. Furthermore, phi and [-2]proPSA/%fPSA remained significant (P = .047 and P = .036, respectively) in the multivariate models and, combined with the biopsy tissue DNA content, showed improvement in the predictive accuracy (c-index, 0.6908 and 0.6884, respectively) for unfavorable biopsy conversion. CONCLUSIONS: The Prostate Health Index to proPSA/%fPSA, combined with biopsy tissue DNA content, improved the accuracy to about 70% to predict unfavorable biopsy conversion at the annual surveillance biopsy examination among men enrolled in an Active Surveillance program

OBJECTIVES: A PSA velocity (PSAV) >0.35 ng/ml/year approximately 10-15 years prior to diagnosis is associated with a greater risk of lethal prostate cancer. Some have recommended that a PSAV >0.35 ng/ml/year should prompt a prostate biopsy in men with a low serum PSA (<4 ng/ml) and benign DRE. However, less is known about the utility of this PSAV cutpoint for the prediction of treatment outcomes among men undergoing radical prostatectomy (RP). METHODS: Between 1992 and 2007, 339 men underwent RP at our institution with a preoperative PSA <4 ng/ml, benign DRE, and multiple preoperative PSA measurements. PSAV was calculated by linear regression analysis using all PSA values within 18 months prior to diagnosis. Kaplan-Meier survival analysis was performed, and biochemical progression rates were compared between PSAV strata using the log-rank test. RESULTS: The preoperative PSAV was >0.35 ng/ml/year in 124 (36.6%) of 339 men. Although there were no significant differences in clinico-pathological characteristics based upon PSAV, men with a PSAV >0.35 ng/ml/year were significantly more likely to experience biochemical progression after RP at a median follow-up of 4 years (P = 0.022). CONCLUSIONS: In this low-risk population with a preoperative PSA <4 ng/ml and benign DRE, approximately 1/3 had a preoperative PSAV >0.35 ng/ml/year. Physicians should carefully monitor men with a preoperative PSA >0.35 ng/ml/year as they are at increased risk of biochemical progression following RP