Sabrina L. Noyes

Impact of Reduced Glomerular Filtration Rate and Proteinuria on Overall Survival of Patients with Renal Cancer.

PURPOSE Although it is commonly staged according to glomerular filtration rate, an international work group recommended classifying chronic kidney disease by cause, glomerular filtration rate and albuminuria. Data on nonsurgical patients with chronic kidney disease indicate proteinuria to be an independent predictor of renal function decrease and mortality. We evaluated whether preoperative proteinuria impacted survival in patients undergoing nephrectomy. MATERIALS AND METHODS An institutional registry was queried for information regarding preoperative creatinine/glomerular filtration rate and urinalysis in 900 patients, including 362 and 538 treated with partial and radical nephrectomy, respectively. Patients were grouped according to glomerular filtration rate level (G1 to G5), proteinuria level (A1 to A3) and chronic kidney disease risk classification (low to very high). Kaplan-Meier and Cox proportional hazards analyses of overall survival were performed. RESULTS The preoperative glomerular filtration rate was less than 60 ml/minute/1.73 m(2) in 30% of patients (median 73, IQR 56-91) and 20% of patients had baseline proteinuria. According to the KDIGO (Kidney Disease Improving Global Outcomes) classification 23% of patients were at moderately increased, 11% were at high and 8% were at very high risk for chronic kidney disease progression. Kaplan-Meier analysis revealed that the preoperative glomerular filtration rate, proteinuria and chronic kidney disease risk group were associated with poor overall survival. In Cox proportional hazard models accounting for age, gender, race, tumor size, clinical stage and surgery type the glomerular filtration rate, proteinuria and chronic kidney disease risk group were highly significant predictors of overall survival (p <0.0001). CONCLUSIONS Preoperative proteinuria is a significant predictor of overall survival in patients who undergo nephrectomy. Classification according to preoperative glomerular filtration rate and proteinuria more accurately predicts survival than using the glomerular filtration rate alone after accounting for cancer stage. This information supports routine evaluation of proteinuria in patients with kidney cancer.

Prevalence of Proteinuria and Other Abnormalities in Urinalysis Performed in the Urology Clinic

OBJECTIVE To compare the prevalence of proteinuria in the urology clinic with other outpatient settings. Chronic kidney disease is classified according to cause, glomerular filtration rate, and proteinuria. Proteinuria may be more prevalent in patients with known chronic kidney disease, renal disorders (benign or malignant), or after urologic surgery. METHODS A cross-sectional study of 3 populations undergoing urinalysis (UA) testing was carried out: general outpatients (n = 20,334), urology outpatients (n = 5023), and kidney cancer patients (n = 1016). Proteinuria was classified under Kidney Disease: Improving Global Outcomes guidelines: A1 (<30 mg), A2 (30-300 mg), and A3 (>300 mg). RESULTS Proteinuria was detected throughout a community-based health system in 8.6% of UA (8.2%: A2; 0.4%: A3). In comparison, 18.6% of urology office-performed UA had proteinuria (16.0%: A2, 2.5%: A3) (P < .0001 vs non-urology). Kidney cancer patients were more likely to have proteinuria (17.9%: A2, 3.8%: A3). The proportion with A3 was significantly higher in urology and kidney cancer patients when compared with other outpatients (each P < .0001), and in the kidney cancer subgroup compared with all urology patients (P < .0001). Additional abnormalities were frequently present on microscopic analysis of UA in the urology clinic, including hematuria (20.9%), pyuria (21.8%), and bacteriuria (3.1%). CONCLUSION The value of UA in the urology clinic as a screening test for proteinuria and other conditions appears high, with >56% having at least 1 abnormality. The population risk of proteinuria in the urology clinic is 18.5%, which is higher than that observed in non-urology clinics. Patients with kidney cancer appear more likely to have proteinuria than the average urology patient. We recommend evaluation of urology patients with UA to identify proteinuria.

Chronic Kidney Disease Is More Common in Locally Advanced Renal Cell Carcinoma

OBJECTIVE To retrospectively evaluate clinical predictors of chronic kidney disease (CKD) in renal cell carcinoma (RCC) patients to identify associations between patient- and tumor-specific factors with poorer renal function. CKD and RCC are interrelated, with 26%-44% of RCC patients having concomitant CKD at diagnosis. PATIENTS AND METHODS Institutional registries from Spectrum Health and University of California, San Diego, were queried for preoperative glomerular filtration rate and proteinuria status before radical or partial nephrectomy. Preoperative clinical and tumor factors were recorded; proteinuria was classified as A1 (<30 mg), A2 (30-300 mg), and A3 (>300 mg). CKD was grouped by Kidney Disease Improving Global Outcomes classification (low, moderately increased, high, very high). RESULTS We evaluated 1569 patients undergoing surgery for renal cortical tumors. CKD status was low risk in 860 (55%), moderately increased in 381 (24%), high in 194 (12%), and very high in 134 (9%) patients. Increased radius, exophytic or endophytic properties, nearness of tumor to the collecting system or sinus in millimeters, anterior or posterior, location relative to polar lines score, tumor size, and clinical tumor stage were strongly associated with increased CKD risk at baseline. Clinical stage T3/T4 disease had more at-risk patients than stages T2 and T1 disease (39.5% vs 22% and 19%, P = .0001). Clinical tumor stage and gender were the only predictors of proteinuria, lower glomerular filtration rate, and higher CKD risk group in both univariate and multivariate analyses. CONCLUSION Forty-five percent of patients with RCC had moderate or higher CKD before treatment. A positive correlation between pretreatment CKD and locally advanced RCC (cT3/T4) was present. This likely relates to increased loss of functional parenchyma with increasing tumor size or stage, with important implications in patient management.

Long-Term Renal Function Recovery following Radical Nephrectomy for Kidney Cancer: Results from a Multicenter Confirmatory Study

Purpose: We sought to confirm the findings from a previous single institution study of 572 patients from Memorial Sloan Kettering Cancer Center in which we found that 49% of patients recovered to the preoperative estimated glomerular filtration rate within 2 years following radical nephrectomy for renal cell carcinoma. Materials and Methods: A multicenter retrospective study was performed in 1,928 patients using data contributed from 3 independent centers. The outcome of interest was postoperative recovery to the preoperative estimated glomerular filtration rate. Data were analyzed using cumulative incidence and competing risks regression with death from any cause treated as a competing event. Results: This study demonstrated that 45% of patients had recovered to the preoperative estimated glomerular filtration rate by 2 years following radical nephrectomy. Furthermore, this study confirmed that recovery of renal function differed according to preoperative renal function such that patients with a lower preoperative estimated glomerular filtration rate had an increased chance of recovery. This study also suggested that larger tumor size and female gender were significantly associated with an increased chance of renal function recovery. Conclusions: In this multicenter retrospective study we confirmed that in the long term a large proportion of patients recover to preoperative renal function following radical nephrectomy for kidney tumors. Recovery is more likely among those with a lower preoperative estimated glomerular filtration rate.

Renal Functional Outcome of Partial Nephrectomy for Complex R.E.N.A.L. Score Tumors With or Without Neoadjuvant Sunitinib: A Multicenter Analysis

Background Sunitinib might optimize the feasibility of partial nephrectomy (PN) for complex renal tumors with imperative indications. We compared the renal functional outcomes of patients with complex renal masses who had undergone sunitinib before PN with those of patients who had not required neoadjuvant sunitinib before PN. Patients and Methods We performed a multicenter retrospective analysis of patients with renal cell carcinoma who had undergone PN for a complex renal mass (R.E.N.A.L. nephrometry score, 10‐12) and imperative indications from January 2012 to July 2014. Neoadjuvant sunitinib was used in cases for which PN was not considered feasible. The cohort was divided into those patients who had undergone PN without neoadjuvant sunitinib and those who had undergone PN after sunitinib (no‐neoadjuvant vs. neoadjuvant). The change in tumor size and R.E.N.A.L. score were assessed. The primary outcome was the change in the estimated glomerular filtration rate (&Dgr;eGFR) from preoperatively to the last postoperative follow‐up visit. Results The data from 125 consecutive patients were analyzed (47 neoadjuvant and 78 no‐neoadjuvant; median follow‐up, 21 months). The neoadjuvant plus PN patients had had a greater median tumor size preoperatively (7.2 vs. 6 cm; P = .045). Sunitinib caused a significant decrease in the median tumor size (from 7.2 to 5.8 cm [19.4%]; P = .012) and R.E.N.A.L. score (from 11 to 9; P = .001). No significant differences were found between the neoadjuvant and no‐neoadjuvant groups in the ischemia time (P = .413) or incidence of complications (P = .728). The median &Dgr;eGFR was similar (neoadjuvant, 6.4; no‐neoadjuvant, 6.1; P = .534). Linear regression analysis for factors associated with an increasing &Dgr;eGFR demonstrated increasing age (estimate, −0.074; P = .009) increasing body mass index (estimate, −0.087; P = .043), and decreasing baseline eGFR (estimate, −0.104; P = .02) as significant factors. Conclusion The use of neoadjuvant sunitinib might facilitate complex PN and result in renal functional outcomes similar to those of patients with a complex renal mass who had not required neoadjuvant sunitinib. Micro‐Abstract Neoadjuvant sunitinib might facilitate partial nephrectomy (PN) in imperative indications. We performed a retrospective comparison of functional outcomes in patients who had and had not received neoadjuvant sunitinib before PN for imperative indications. We noted similar renal functional outcomes between the 2 groups. To the best of our knowledge, these findings represent the first such reported comparison.

Randomized trial finds that prostate cancer genetic risk score feedback targets prostate-specific antigen screening among at-risk men.

Prostate‐specific antigen (PSA) screening may reduce death due to prostate cancer but leads to the overdiagnosis of many cases of indolent cancer. Targeted use of PSA screening may reduce overdiagnosis. Multimarker genomic testing shows promise for risk assessment and could be used to target PSA screening.

Integration and Diagnostic Accuracy of 3T Nonendorectal coil Prostate Magnetic Resonance Imaging in the Context of Active Surveillance

OBJECTIVE To evaluate the integration of 3T nonendorectal coil multiparametric prostate magnetic resonance imaging (mpMRI) at 2 high-volume practices that routinely use mpMRI in the setting of active surveillance. MATERIALS AND METHODS This was an institutional review board-approved, Health Insurance Portability and Accountability Act-compliant, and dual-institution retrospective cohort study. Subjects undergoing 3T mpMRI without endorectal coil at either study institution over a 13-month period (August 1, 2015-August 31, 2016) were selected based on predefined criteria: clinical T1/T2 Gleason 6 prostate cancer, prostate-specific antigen <15 ng/mL, ≥40 years old, mpMRI within 2 years of prostate biopsy, and Prostate Imaging Reporting and Data System (PI-RADS) v2 score assigned. Subjects surveilled for Gleason ≥3 + 4 prostate cancer were excluded. The primary outcome was detection of Gleason ≥3 + 4 prostate cancer on magnetic resonance-ultrasound fusion biopsy, standard biopsy, or prostatectomy within 6 months following mpMRI. Positive predictive values (PPVs) were calculated. RESULTS A total of 286 subjects (N = 193 from institution 1, N = 93 from institution 2) met the criteria. Most (87% [90 of 104]) with maximum PI-RADS v2 scores of 1-2 did not receive immediate biopsy or treatment and remained on active surveillance. Incidence and PPVs for PI-RADS v2 scores of ≥3 were the following: PI-RADS 3 (n = 57 [20%], PPV 21% [6 of 29]), PI-RADS 4 (n = 96 [34%], PPV 51% [39 of 77]), and PI-RADS 5 (n = 29 [13%], PPV 71% [20 of 28]). No Gleason ≥4 + 3 prostate cancer was identified for PI-RADS v2 scores of 1-3 (0 of 43 with histology). Following mpMRI and subsequent biopsy, 21% (61 of 286) of subjects were removed from active surveillance and underwent definitive therapy. CONCLUSION The 3T nonendorectal coil mpMRI has been integrated into the care of patients on active surveillance and effectively stratifies risk of Gleason ≥3 + 4 prostate cancer in this population.

Comparison of RENAL, PADUA, CSA, and PAVP Nephrometry Scores in Predicting Functional Outcomes after Partial Nephrectomy

OBJECTIVE To evaluate the accuracy of radius, exophytic/endophytic, nearness to collecting system/sinus, anterior/posterior, and location relative to polar lines (RENAL), preoperative aspects and dimensions used for anatomical classification (PADUA), contact surface area (CSA), and preoperative assessment of volume preservation (PAVP) nephrometry scores in predicting postoperative renal functional outcomes after partial nephrectomy (PN). Few studies have compared the accuracy of tumor complexity systems directly in the same set of PN patients. MATERIALS AND METHODS Patients treated with robotic, laparoscopic, or open PN having available imaging (n = 344) were examined. The ability of 4 systems to predict nadir estimated glomerular filtration rate (eGFR [median postoperative day 1]) and new baseline eGFR (median: 0.95 year) was analyzed using univariable and multivariable models. RESULTS Median preoperative, nadir, and new baseline eGFR were 79 (interquartile range [IQR]: 63-97), 65 (IQR: 47-85), and 80 (IQR: 63-99) mL/min/1.73 m2. Multivariable models incorporating RENAL, PADUA, CSA, or PAVP were similarly predictive of postoperative renal function (nadir eGFR: R2 = 0.683-0.688, new baseline eGFR: R2 = 0.775). In univariable analysis, all 4 complexity systems were predictors of nadir GFR (each P < .05), with RENAL (P = .045), CSA (P = .027), and PAVP (P = .012) also significantly predicting nadir eGFR in multivariable models. No complexity system was significantly associated with new baseline eGFR in multivariable analysis, with only RENAL (P = .023) and PAVP (P = .049) having a statistically significant association in univariable analysis. CONCLUSION RENAL, PADUA, CSA, and PAVP are all predictors of early postoperative renal function. RENAL and PAVP provided the greatest predictive ability for later renal functional outcomes.

Determination of Prostate Volume: A Comparison of Contemporary Methods

RATIONALE AND OBJECTIVES Prostate volume (PV) determination provides important clinical information. We compared PVs determined by digital rectal examination (DRE), transrectal ultrasound (TRUS), magnetic resonance imaging (MRI) with or without three-dimensional (3D) segmentation software, and surgical prostatectomy weight (SPW) and volume (SPV). MATERIALS AND METHODS This retrospective review from 2010 to 2016 included patients who underwent radical prostatectomy ≤1 year after multiparametric prostate MRI. PVs from DRE and TRUS were obtained from urology clinic notes. MRI-based PVs were calculated using bullet and ellipsoid formulas, automated 3D segmentation software (MRI-A3D), manual segmentation by a radiologist (MRI-R3D), and a third-year medical student (MRI-S3D). SPW and SPV were derived from pathology reports. Intraclass correlation coefficients compared the relative accuracy of each volume measurement. RESULTS Ninety-nine patients were analyzed. Median PVs were DRE 35 mL, TRUS 35 mL, MRI-bullet 49 mL, MRI-ellipsoid 39 mL, MRI-A3D 37 mL, MRI-R3D 36 mL, MRI-S3D 36 mL, SPW 54 mL, SPV-bullet 47 mL, and SPV-ellipsoid 37 mL. SPW and bullet formulas had consistently large PV, and formula-based PV had a wider spread than PV based on segmentation. Compared to MRI-R3D, the intraclass correlation coefficient was 0.91 for MRI-S3D, 0.90 for MRI-ellipsoid, 0.73 for SPV-ellipsoid, 0.72 for MRI-bullet, 0.71 for TRUS, 0.70 for SPW, 0.66 for SPV-bullet, 0.38 for MRI-A3D, and 0.33 for DRE. CONCLUSIONS With MRI-R3D measurement as the reference, the most reliable methods for PV estimation were MRI-S3D and MRI-ellipsoid formula. Automated segmentations must be individually assessed for accuracy, as they are not always truly representative of the prostate anatomy. Manual segmentation of the prostate does not require expert training.

Prostate multi-parametric MRI program implementation and impact: Initial clinical experience in a community-based health system

Introduction: Magnetic resonance imaging of the prostate is increasingly being performed at academic centers but implementation in community based health systems has lagged and literature regarding clinical impact in this setting is limited. We describe our experience developing a community based prostate magnetic resonance imaging program, including the evolution of interpretation and reporting methods, and the resulting clinical impact during a period of more than 5 years (August 2010 to December 2015). Methods: Data collected for prostate magnetic resonance imaging included demographic, clinical, scanning, pathology and treatment/management information. Suspicion level on prostate magnetic resonance imaging was correlated with pathology results when available. Outcomes were compared across 3 reporting eras, ie early, mid and Prostate Imaging Reporting and Data System, version 2. Results: A total of 537 prostate magnetic resonance images were obtained for diagnosed prostate cancer (60%) or screening (37%). During the study period the number of scans and ordering physicians increased. The proportion of patients with suspected extraprostatic extension (17.5%), lymph node metastasis (6.9%) and bone/other metastasis (4.3%) on prostate magnetic resonance imaging remained relatively constant. When stratified by era, there was a significant increase in low suspicion studies (p = 0.0002) and a trend toward a significant increase in cancer detection at biopsy (p = 0.09), reflecting increased specificity in the Prostate Imaging Reporting and Data System, version 2 era. Conclusions: While staging information with prostate magnetic resonance imaging was accurate early in the implementation of the program, lesion characterization improved with use of Prostate Imaging Reporting and Data System, version 2 criteria and standardized reporting. Regular multidisciplinary participation in community based prostate magnetic resonance imaging programs may maximize clinical impact.