Objective To construct and validate a nomogram for patients with endometrial carcinoma to predict the 3‐ and 5‐year overall survival (OS) based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods Demographic and clinical pathologic characteristics of patients with endometrial carcinoma diagnosed between 1973 and 2015 were extracted from the SEER database. Univariate and multivariate Cox analyses were carried out to identify the independent characteristics and further included into the construction of a nomogram. Finally, concordance index and calibration curves were used to validate the nomogram. Results A total of 49 844 patients were enrolled into our analysis. The results of univariate Cox analysis showed that age, race, marital status, FIGO Stage, grade, and metastatic status to bone, brain, lung, or liver were significant factors. Multivariate Cox analysis was performed and it confirmed all factors as independent variables. Next, a nomogram was constructed using these independent variables in prediction of the 3‐ and 5‐year OS. Furthermore, results with concordance indices (0.852 in training set and 0.861 in validation set) and calibration curves closer to ideal curves indicated the accurate predictive ability of this nomogram. Conclusions The individualized nomogram demonstrated a good ability in prognostic prediction for patients with endometrial carcinoma.

Background: Corpus Carcinoma is the most commonly diagnosed female cancer worldwide. However, the well-known biomarkers are not enough to meet the needs of precision medicine. Novel targets are desirable and highly valuable for improved patient survival. In this regard, we identified complement component C7 as one of the candidates based on data from the TCGA database.Method: C7 expression was examined by mRNA expression profile in 425 cases of corpus carcinoma, including grade 3 data (such as mRNA-seq, miRNA-seq, and clinical data) from 406 primary corpus carcinoma tissues and 19 normal controls from the dataset. The availability of data is demonstrated by heat maps, and the distribution of genes is demonstrated by volcanic maps. Then the value of C7 was demonstrated on the basis of genomics and clinical epidemiology respectively, confirmed by grade 3 data from TCGA. The relationship between the C7 expression and five-year survival of corpus carcinoma patients was analyzed in order to investigate the function of C7 in corpus carcinoma. Result: In our present study, we reported for the first time that C7 was an independent prognostic factor of corpus carcinoma and the 5-year survival rate of patients with high C7 expression is lower than that of patients with low C7 expressions. (p=0.02265) Conclusion: In summary, high expression of C7 may promote corpus carcinoma development. Our present study laid a foundation to help clinicians improve the identification of patients for C7 in the era of precision medicine.