Patil, Dattatraya H

AbstractBackgroundThe 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.MethodsBy 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.ResultsIn 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.ConclusionsThe 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.

Objectives To determine the prognostic potential of a 24‐gene signature, Sig24, for identifying patients with prostate cancer who are at risk of developing metastases or of prostate cancer‐specific mortality (PCSM) after radical prostatectomy (RP). Patients and Methods Sig24 scores were calculated from previously collected gene expression microarray data from the Cleveland Clinic and Mayo Clinic (I and II). The performance of Sig24 was determined using time‐dependent c‐index analysis, Cox proportional hazards regression and Kaplan–Meier survival analysis. Results Higher Sig24 scores were significantly associated with higher pathological Gleason scores in all three cohorts. Analysis of the Mayo Clinic II cohort, which included time‐to‐event information, indicated that patients with high Sig24 scores also had a higher risk of developing metastasis (hazard ratio [HR] 3.78, 95% confidence interval [CI]: 1.96–7.29; P < 0.001) or of PCSM (HR 6.54, 95% CI: 2.16–19.83; P < 0.001). Conclusions The findings of the present study show the applicability of Sig24 for the prognosis of metastasis or PCSM after RP. Future studies investigating the combination of Sig24 with available prognostic tests may provide new approaches to improve risk stratification for patients with prostate cancer.