Thompson, R. Houston

610 Background: Personalized treatment for clinical T1 renal cortical masses (RCMs) should account for competing risks related to tumor and patient characteristics. Using a contemporary multi-institutional cohort, we developed treatment-specific prediction models for cancer-specific mortality (CSM), other-cause mortality (OCM), and 90-day complication rates for patients managed with surgery, thermal ablation (TA), and active surveillance (AS). Methods: Preoperative clinical and radiological features were collected for eligible patients aged 18-91 years treated at four academic centers from 2000-2016. Prediction models used competing risks regressions for CSM and OCM and logistic regressions for 90-day Clavien >3 complications, adjusting for tumor size as well as patient age, sex, ECOG performance status (PS), and Charlson comorbidity index (CCI). Predictions accounted for missing data using multiple imputation. Results: After excluding 25 patients with no follow-up, the cohort included 4995 patients treated with radical nephrectomy (RN, n=1270), partial nephrectomy (PN, n=2842), thermal ablation (n=479), or active surveillance (n=404). Median follow-up was 5.1 years (IQR 2.5-8.5). Predictions from the fitted model are shown in an online calculator ( https://rgulati.shinyapps.io/rcc-risk-calculator ). To illustrate the use of this calculator for a specific patient, a 70-year-old female with a 5.5 cm RCM, PS of 2, and CCI of 3 has a predicted 5-year CSM of 4-7% across treatments, 5-year OCM of 34-49%, and 90-day risk of Clavien ≥3 complications of 4%, 10%, and 6% for RN, PN, and TA respectively. Conclusions: Personalized treatment selection for cT1 RCM is challenging. We present a competing risk calculator that incorporates pretreatment features to quantify competing causes of mortality and treatment-associated complications. Pending validation, this tool may be used in clinical practice to provide patients with estimated individualized treatment-specific probabilities of competing causes of death and complication risks to facilitate shared decision-making.

AbstractObjectivesPrevious studies noted discordance of programmed death‐1 (PD‐1) and one of its ligands (PD‐L1) across patient‐matched primary and metastatic clear cell renal cell carcinoma (ccRCC). There are inconsistencies if the primary or metastatic tumor has higher expression, and whether metastatic tumor expression is associated with patient outcome. Thus, we examined PD‐1 and PD‐L1 in patient‐matched tumors using a large number of ccRCC patients with long follow‐up.Materials and MethodsWe analyzed PD‐1 and PD‐L1 using immunohistochemistry in patient‐matched primary and metastatic tumors from 110 ccRCC patients. Concordance was assessed among longitudinal metastatic tumors, as well as across patient‐matched primary and metastatic tumors. Cox proportional hazards regression was used to evaluate the associations of metastatic tumor expression with cancer‐specific survival.ResultsWe observed inter‐metastatic tumor heterogeneity of PD‐1 in 25 (69%) of the 36 patients and of PD‐L1 in seven (19%) patients. Concordance between patient‐matched primary and metastatic tumors was 73% (Kappa = 0.16, 95% CI: −0.003‐0.32). Similarly, concordance of PD‐L1 between metastatic and patient‐matched primary tumors was 78% (Kappa = 0.27, 95% CI: 0.09‐0.46). Both markers demonstrated higher expression in primary vs metastatic tumors. Metastatic tumor expression of PD‐1 was significantly associated with metastatic location (P < .0001) and ccRCC‐specific survival (HR = 2.15, 95% CI: 1.06‐4.36, P = .035).ConclusionsThe expression of PD‐1 and PD‐L1 is discordant across patient‐matched ccRCC tumors, with higher expression in primary tumors. Higher PD‐1 expression was associated with metastatic location and lower cancer‐specific survival. If validated, these results highlight the importance of evaluating these biomarkers in metastatic tissue specifically.

Significance Statement Research investigating glomerular morphology in different cortical regions has been limited to animal models and a small number of human autopsy kidneys. In this study, the authors used tissue from living patients who underwent a radical nephrectomy (for a renal tumor) to characterize glomerular morphology and glomerulosclerosis by cortical depth. They found that glomerular volume and glomerulosclerosis differed by depth across three cortical regions (superficial, middle, and deep). Although most clinical associations with glomerulosclerosis and glomerulomegaly did not differ by cortical depth, there were important exceptions. Age-related glomerulosclerosis appeared to be an ischemic process and was more evident in the superficial (subcapsular) region. Diabetes-related glomerulosclerosis was more evident in the deep (juxtamedullary) region. Obesity more strongly associated with larger glomeruli in the superficial region. Background Age, CKD risk factors, and kidney function are associated with larger glomerular volume and a higher percentage of globally sclerotic glomeruli. Knowledge of how these associations may differ by cortical depth is limited. Methods To investigate glomerular volume and glomerulosclerosis across different depths of cortex, we studied wedge sections of the renal parenchyma from 812 patients who underwent a radical nephrectomy (for a tumor), separately characterizing glomeruli in the superficial (subcapsular), middle, and deep (juxtamedullary) regions. We compared the association of mean nonsclerotic glomerular volume and of glomerulosclerosis (measured as the percentage of globally sclerotic glomeruli) with age, obesity, diabetes, smoking, kidney function, and structural pathology in the superficial, middle, and deep regions. Results The superficial, middle, and deep regions showed significant differences in glomerular volume (0.0025, 0.0031, and 0.0028 µ m 3 , respectively) and in glomerulosclerosis (18%, 7%, and 11%, respectively). There was a marked increase in glomerulosclerosis with age in the superficial region, but larger glomerular volume was not associated with age at any cortical depth. Glomerulosclerosis associated more strongly with arteriosclerosis and ischemic-appearing glomeruli in the superficial region. Hypertension, lower eGFR, and interstitial fibrosis associated with glomerulosclerosis and glomerular volume to a similar extent at any depth. Diabetes and proteinuria more strongly associated with glomerulosclerosis in the deep and middle regions, respectively, but neither associated with glomerular volume differently by depth. Obesity associated more strongly with glomerular volume in the superficial cortex. Conclusions Most clinical characteristic show similar associations with glomerulosclerosis and glomerulomegaly at different cortical depths. Exceptions include age-related glomerulosclerosis, which appears to be an ischemic process and is more predominant in the superficial region.

Purpose The medical student performance evaluation (MSPE) summarizes a residency applicant’s academic performance. Despite attempts to improve standardized clerkship grading, concerns regarding grade inflation and variability at United States medical schools persist. This study’s aim was to describe current patterns of clerkship grading and applicant performance data provided in the MSPE. Method The authors evaluated Electronic Residency Application Service data submitted to a single institution for the 2016–2017 Match cycle. Clerkship grading characteristics regarding grading tiers, school rank, location, and size were obtained. Data regarding methods for summative comparisons such as key word utilization were also extracted. Descriptive statistics were generated, and generalized linear modeling was performed. Results Data were available for 137/140 (98%) MD-granting U.S. medical schools. Pass/fail grading was most commonly used during the preclinical years (47.4%). A 4-tier system was most common for clerkship grading (31%); however, 19 different grading schemes were identified. A median of 34% of students received the highest clerkship grade (range, 5%–97%). Students attending a top 20 medical school were more likely to receive the highest grade compared with those attending lower-rated schools (40% vs 32%, P < .001). Seventy-three percent of schools ranked students, most commonly using descriptive adjectives. Thirty-two different adjectives were used. Conclusions There is significant institutional variation in clinical grading practices and MSPE data. For core clerkships where most students received the highest grade, the ability to distinguish between applicants diminishes. A standardized approach to reporting clinical performance may allow for better comparison of residency applicants.