Abstract: Objective To construct a nomogram predictive model for postoperative cervical cancer patients, and establish a risk strat-ification system based on the individual scores of the nomogram. Methods The data of 6, 835 postoperative cervical cancer patients in the US SEER (Surveillance, Epidemiology, and End Results) database from 1973 to 2015 was collected to construct a predictive model, and 120 patients who underwent cervical cancer surgery at the Second Affiliated Hospital of Soochow University were selected as an external validation cohort. Through univariable and multivarible Cox regression analysis, prognostic factors were screened out to draw a nomogram, and a risk stratification system was established based on the prognostic risk score of the nomogram. Results The Cox regression analysis showed that the age at diagnosis, race, histological grade, T stage, N stage, lymph node dissection status, tumor size and depth of tumor invasion were independent of prognostic factors for patients with cervical cancer after surgery. The C-index of nomogram constructed in the training cohort, internal verification cohort and external cohort were 0.824, 0.814, and 0.730, respectively. The calibration curve showed that the model prediction was basically consistent with the actual survival situation, and the risk stratification system could clearly distinguish the survivals of patients with different FIGO stages (all P<0.05). Conclusions The nomogram can effectively predict the postoperative prognosis of patients with cervical cancer after surgery. The risk stratification system based on the nomogram prediction model has clinical value in distinguishing high-risk patients.

Key words: Cervical carcinoma, Prognosis；SEER database, Nomogram