ABSTRACT
【Objective】 To construct a nomogram survival prediction model for patients with locally advanced renal cell carcinoma based on SEER database (n=7893), so as to provide reference for future prognosis study. 【Methods】 Case data were downloaded from the SEER database, and divided into the experimental group and validation group with a ratio of 7∶3 by simple randomization.The clinical information was analyzed, independent risk factors influencing prognosis were screened, and the overall survival (OS) and tumor-specific survival (CSS) were mapped.Model performance was evaluated using consistency index, area under the receiver operating characteristic curve (AUC), internal and external validation, and calibration curves. 【Results】 Patients’ age, tumor size, disease progression tpye, TNM stage, number of positive lymph nodes, marital status and pathological type were significantly correlated with OS and CSS (P<0.01).Based on the above predictors, the internal verification AUC of the 1-, 3- and 5- year OS nomogram model was 0.809, 0.721 and 0.715, respectively.The internal validation AUC of the nomogram model for 1-, 3- and 5- year CSS was 0.802, 0.745 and 0.735, respectively.The external validation AUC of the OS nomogram model was 0.792, 0.628 and 0.620 at 1, 3 and 5 years, respectively, and the external validation AUC of CSS was 0.943, 0.803 and 0.737 at 1.3 and 5 years, respectively, showing good model differentiation and accuracy. 【Conclusion】 The prediction performance of the nomogram model is good, and it can provide reference for individualized treatment.
ABSTRACT
【Objective】 A two-sample Mendelian randomization method was used to explore whether there is a causal relationship between the intake of alcohol, coffee, green tea and dairy products and the incidence of prostate cancer (PCa), in order to clarify the risk factors for the incidence of PCa and find a prevention pathway for PCa. 【Methods】 Data of alcohol, coffee, green tea, dairy products and prostate cancer were collected with genome-wide association study (GWAS).The causal relationship between their intake and the risk of PCa was analyzed with two-sample Mendelian randomization (2SMR).MR analysis was conducted with inverse-variance weighting (IVW).Sensitivity analysis was performed with weighted median, MR-Egger regression, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) tests. 【Results】 Coffee intake (OR: 0.994, 95%CI: 0.990-0.999, P=0.014) and green tea intake (OR: 0.999, 95%CI: 0.998-0.999, P=0.036) were negatively correlated with the risk of PCa.Alcohol intake (OR: 0.997, 95%CI: 0.990-1.004, P=0.392) and dairy intake (OR: 1.025, 95%CI: 0.983-1.069, P=0.256) were not associated with the risk of PCa.In weighted median, MR-Egger regression, and retention one method analyses, the results were robust without heterogeneity or pleiotropy. 【Conclusion】 There was a causal association between coffee intake and green tea intake and the onset of PCa, but no causal association between alcohol intake and dairy intake and PCa onset.