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ObjectiveTo further elucidate the relationship between low socioeconomic status (SES) and larger, more complex stones requiring staged surgical interventions. Specifically, we aimed to determine if underinsurance (Medicaid, Medicare, and self-pay insurance types) is associated with multiple surgeries within 1 year.MethodsWe performed a retrospective longitudinal analysis of prospectively collected data from the California statewide Department of Health Care Access and Information (HCAI) dataset. We included adult patients who had their first recorded kidney stone encounter between 2009 and 2018 and underwent at least 1 urologic stone procedure. We followed these patients within the dataset for one year after their initial surgery to assess for factors predicting multiple surgical treatments for stones.ResultsA total of 156,319 adults were included in the study. The proportions of individuals in private insurance, Medicaid, Medicare and self-pay/indigent groups differed by the presence or absence of additional surgeries (64.0%, 13.5%, 19.4%, and 0.1%, vs 70.3%, 10.1%, 16.6%, and 0.1%, respectively). Compared to private insurance, Medicaid (1.46 [1.40-1.53] P < .001) and Medicare (1.15 [1.10-1.20] P < .001) insurance types were associated with significantly greater odds of multiple surgeries, whereas no significant association was seen in the self-pay/indigent insurance type (1.35 [0.83-2.19], P = 1.0).ConclusionIn a statewide, California database from 2009 to 2018, underinsured adults had higher odds of undergoing a second procedure for kidney stones within 1 year of initial surgical treatment. This study adds to the expanding body of literature linking suboptimal healthcare access and disparate outcomes for kidney stone patients.

The medical and surgical management of kidney stones is one of the most common functions of the urologist. Management choices are often nuanced, involving the decision to embark on one surgical plan among several options. As the wider medical community critically evaluates the care we provide to an increasingly diverse population, it will be important to examine patient outcomes with a particular focus on ensuring equitable care. This review examines the influence of social parameters on the care of kidney stone patients. The dearth of literature in this area warrants rigorous studies on the relationship between race as well as socioeconomic status and the management of kidney stone disease.

ObjectiveTo determine if limited food access census tracts and food swamp census tracts are associated with increased risk for repeat kidney stone surgery. And to elucidate the relationship between community-level food retail environment relative to community-level income on repeat stone surgery over time.MethodsData were abstracted from the University of California, San Francisco Information Commons. Adult patients were included if they underwent at least one urologic stone procedure. Census tracts from available geographical data were mapped using Food Access Research Atlas data from the United States Department of Agriculture Economic Research Service. Kaplan-Meier curves were employed to illustrate time to a second surgical procedure over 5 years, and log-rank tests were used to test for statistically significant differences. A multivariate Cox regression model was used to generate hazard ratios for undergoing second surgery by group.ResultsA total of 1496 patients were included in this analysis. Repeat stone surgery occurred in 324 patients. Kaplan-Meier curves demonstrated a statistically significant difference in curves depicting patients living in low income census tracts (LICTs) vs those not living in LICTs (P

Background: The 2018 Leibovich prognostic model for nonmetastatic renal cell carcinoma (RCC) combines clinical, surgical, and pathologic factors to predict progression‐free survival (PFS) and cancer‐specific survival (CSS) for patients with clear cell (ccRCC), papillary (pRCC), and chromophobe (chRCC) histology. Despite high accuracy, <1% of the original cohort was Black. Here, the authors examined this model in a large population with greater Black patient representation. Methods: By using a prospectively maintained RCC institutional database, patients were assigned Leibovich model risk scores. Survival outcomes included 5‐year and 10‐year PFS and CSS. Prognostic accuracy was determined using area under the curve (AUC) analysis and calibration plots. Black patient subanalyses were conducted. Results: In total, 657 (29%) of 2295 patients analyzed identified as Black. Declines in PFS and CSS were observed as scores increased. Discrimination for ccRCC was strong for PFS (AUC: 5‐year PFS, 0.81; 10‐year PFS, 0.78) and for CSS (AUC: 5‐year CSS, 0.82; 10‐year CSS, 0.74). The pRCC AUC for PFS was 0.74 at 5 years and 0.71 at 10 years; and the AUC for CSS was 0.74 at 5 years and 0.70 at 10 years. In chRCC, better performance was observed for CSS (AUC at 5 years, 0.75) than for PFS (AUC: 0.66 at 5 years; 0.55 at 10 years). Black patient subanalysis revealed similar‐to‐improved performance for ccRCC at 5 years (AUC: PFS, 0.79; CSS, 0.87). For pRCC, performance was lower for PFS (AUC at 5 years, 0.63) and was similar for CSS (AUC at 5 years, 0.77). Sample size limited Black patient 10‐year and chRCC analyses. Conclusions: The authors externally validated the 2018 Leibovich RCC prognostic model and found optimal performance for ccRCC, followed by pRCC, and then chRCC. Importantly, the results were consistent in this large representation of Black patients. Plain Language Summary: In 2018, a model to predict survival in patients with renal cell carcinoma (kidney cancer) was introduced by Leibovich et al.This model has performed well; however, Black patients have been under‐represented in examination of its performance.In this study, 657 Black patients (29%) were included, and the results were consistent.This work is important for making sure the model can be applied to all patient populations. The authors examined and externally validated the 2018 Leibovich prognostic model for nonmetastatic renal cell carcinoma in a large population with greater Black patient representation. The results indicated optimal performance of the model across all histologies and were consistent among Black patients. [ABSTRACT FROM AUTHOR]