A novel nomogram and risk classification system predicting the overall survival of patients with papillary renal cell carcinoma after nephrectomy: A population-based study.

Background: Papillary renal cell carcinoma (pRCC) is the largest histologic subtype of non-clear-cell RCC. To date, there is no reliable nomogram to predict the prognosis of patients with pRCC after nephrectomy. We aimed to first establish an effective nomogram to predict the overall survival (OS) of patients with pRCC after nephrectomy. Methods: A total of 3,528 eligible patients with pRCC after nephrectomy were identified from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The patients were randomized into the training cohort (n = 2,472) and the validation cohort (n = 1,056) at a 7:3 ratio. In total, 122 real-world samples from our institute (titled the AHMU-pRCC cohort) were used as the external validation cohort. Univariate and subsequent multivariate Cox regression analyses were conducted to identify OS-related prognostic factors, which were further used to establish a prognostic nomogram for predicting 1-, 3-, and 5-year OS probabilities. The performance of the nomogram was evaluated by using the concordance index (C-index), receiver operating characteristic curve (ROC), calibration plot, and decision curve analysis (DCA). Results: Multivariate Cox analysis showed that age, race, marital status, TNM stage, tumor size, and surgery were significant OS-related prognostic factors. A prognostic model consisting of these clinical parameters was developed and virtualized by a nomogram. High C-index and area under the ROC curve (AUC) values of the nomogram at 1, 3, and 5 years were found in the training, validation, and AHMU-pRCC cohorts. The calibration plot and DCA also showed that the nomogram had a satisfactory clinical application value. A risk classification system was established to risk-stratify patients with pRCC. Conclusion: Based on a large cohort from the public SEER database, a reliable nomogram predicting the OS of patients with pRCC after nephrectomy was constructed, which could optimize the survival assessment and clinical treatment.

p27-V109G Polymorphism Is Not Associated with the Risk of Prostate Cancer: A Case-Control Study of Han Chinese Men in Central China.

OBJECTIVE: We conducted an update meta-analysis aiming to verify the association between p27-V109G polymorphism and cancer risk, particular for prostate cancer (PCa). Then, we conducted a case-control study of Han Chinese in central China to verify the evidence-based results. METHODS: Relevant studies were collected from diverse databases up to March 2017. In addition, a hospital-based (H-B) case-control study enrolling 90 PCa patients and 140 healthy controls was included to verify these evidence-based findings. Genetic risk was calculated by odds ratio (OR) with its corresponding 95% confidence interval (CI). The p27-V109G polymorphism was determined by MassARRAY genotyping method. RESULTS: Finally, twenty-four published studies comprising 9627 cases and 12,102 controls were enrolled for the current meta-analysis. Overall analysis suggested that p27-V109G polymorphism decreased overall cancer risk in allelic contrast, heterozygote, and dominant models. When stratified analysis was conducted by ethnicity, data revealed that p27-V109G polymorphism was associated with a decreased cancer risk in Caucasians. Highlighted in the subgroup analysis by cancer type, we uncovered a significantly decreased risk of PCa in allelic contrast, dominant, homogeneous, and recessive models. However, in the validation case-control study, we failed to uncover a positive association between p27-V109G polymorphism and PCa risk. In addition, negative results were also identified when subgroup analyses were stratified by age, tumor grade, tumor stage, PSA levels, and other measurements. CONCLUSION: Although evidence-based results suggest that p27-V109G polymorphism plays a protective role in overall cancer risk, particularly for PCa, our case-control study failed to validate any association between this particular polymorphism and PCa risk.