Postoperative prognostic model for patients with clear cell renal cell carcinoma in a Chinese population

Basic Characteristics and Survival Outcomes of Asian-American Patients with Clear Cell Renal Cell Carcinoma and Comparisons with White Patients: A Population-Based Analysis

Background

To explore the baseline characteristics, pathological and survival outcomes of Asian-American patients with clear cell renal cell carcinoma (ccRCC), and make comparisons with White patients.

Materials and Methods

In this study, patients diagnosed with ccRCC between 2010 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Basic characteristics of Asian-American patients were analysed and compared with White patients. Then, proportional mortality ratio (PMR) analyses were performed in Asian population to investigate the proportions of different cause of deaths (CODs), and make comparisons with White patients. Moreover, Kaplan-Meier (KM) analyses were developed to investigate the survival disparities of ccRCC patients between Asian-Americans and White patients. Finally, a competing risk regression model was constructed to identify potential prognostic factors for ccRCC patients in the whole population.

Results

A total of 1586 Asian-American patients were eventually identified, and the median age at diagnosis was 61 years old. In Asian patients, those from South Asian had the youngest age at diagnosis (P<0.001) and the earliest stage of diseases (localized: 76.83%, T1: 70.73%, all P<0.05) when compared with other ethnicities. No significant differences were detected in tumor characteristics between Asian-Americans and White patients. Older age (P<0.001), earlier stage (P<0.001) and the administration of surgery (P=0.050) were tightly associated with a lower risk of dying of RCC in Asian-American patients. Additionally, Asian-American patients had comparable survival outcomes when compared with White patients. Lastly, competing risk regression model revealed that age at diagnosis (P<0.001), tumor grade (P<0.001), histological stage (P<0.001), median household income (P<0.001) and the administration of surgery (P<0.001) were prognostic factors for cancer-specific survival (CSS) in ccRCC patients, while died of other causes was regarded as a competing event.

Conclusion

Asian-American patients had similar tumor characteristics and survival outcomes with White patients. In Asian patients, those from South Asian had the youngest age at diagnosis and the earliest stage of diseases. Age, grade, histological stage, household income and surgery were identified to be closely related to CSS in ccRCC patients. In the future, prospective and well-designed studies are needed to verify our findings.

Development and Validation of a Nomogram Predicting the Prognosis of Renal Cell Carcinoma After Nephrectomy

Objective

To develop and validate a nomogram for predicting the overall survival (OS) of renal cell carcinoma (RCC) patients after nephrectomy.

Materials and Methods

In total, 488 patients with RCC who underwent nephrectomy at the Urology Department of the First Hospital of Shanxi Medical University between January 2013 and December 2018 were randomly divided into a development cohort (n = 344) and a validation cohort (n = 144). The development cohort was used to build a prediction model, and the validation cohort was used for validation. Single-factor and multifactor analyses were carried out with R software, and the nomogram, calibration chart, ROC curve and C index were constructed.

Results

The median follow-up time of the development and validation cohorts was 34 months. The total 3-year and 5-year survival rates of the development cohort were 93.3% and 91.6%, respectively; those of the validation cohort were 92.4% and 91.0%, respectively. Cox univariate analysis of the development cohort showed that age, type 2 diabetes mellitus (T2DM), smoking history, type of surgery, T stage, N stage, M stage and Fuhrman nuclear grade were prognostic factors for OS in RCC patients undergoing nephrectomy. Cox multivariate analysis showed that T2DM, smoking history and T stage were independent prognostic factors for OS in RCC patients undergoing nephrectomy (P < 0.05). According to the univariate and multivariate analyses, a nomogram was constructed. In the development cohort, the C index of predicted OS was 0.875 (95% CI, 0.820-0.930). The calibration curve of the 3-year and 5-year survival rates showed that the predicted value of the nomogram was consistent with the actual observed value. The area under the 3-year and 5-year survival ROC curves was 0.861 and 0.901, respectively. In the validation cohort, the C index was 0.880 (95% CI, 0.778-0.982). The calibration curve of the 3-year and 5-year survival rates showed that the predicted value of the nomogram was consistent with the actual observed value. The area under the 3-year and 5-year survival ROC curves was 0.813 and 0.799, respectively.

Conclusion

We developed and verified a new and accurate nomogram with available clinicopathological data that can effectively predict the OS of RCC patients after nephrectomy.

Prognostic analysis of postoperative clinically nonmetastatic renal cell carcinoma

Objectives

To investigate the survival characteristics of postoperative nonmetastatic renal cell carcinoma (RCC) patients, and the predictive value of a prognostic model.

Materials and Methods

We retrospectively evaluated data from 1202 postoperative nonmetastatic RCC patients who were treated between 1999 and 2012 at West China Hospital, Sichuan University (Chengdu, China). In addition, we also evaluated data relating to 53 205 cases acquired from the Surveillance, Epidemiology, and End Results (SEER) program. Survival analysis was performed on the cases, and subgroups, using the Kaplan‐Meier and Cox regression methods. The concordance index of the Stage Size Grade Necrosis (SSIGN), Leibovich, and the UCLA integrated staging system, scores was determined to evaluate the accuracy of these outcome prediction models.

Results

The 5‐year overall survival rate for RCC cases in West China Hospital was 87.6%; this was higher than that observed for SEER cases. Survival analysis identified several factors that exerted significant influence over prognosis, including the time of surgery, Eastern Cooperative Oncology Group performance status, tumor stage, size, nuclear differentiation, pathological subtypes, along with necrotic and sarcomatoid differentiation. Moreover tumor stage, size, and nuclear grade were all identified as independent predictors for both our cases and those from the SEER program. Patient groups with advanced RCC, and poorly differentiated RCC subgroups, were both determined to have a poor prognosis. The SSIGN model yielded the best predictive value as a prognostic model, followed by the Leibovich, and UCLA integrated staging system; this was the case for our patients, and for sub‐groups with a poor prognosis.

Conclusion

The prognosis of RCC was mostly influenced by tumor stage, size, and nuclear differentiation. SSIGN may represent the most suitable prognostic model for the Chinese population.