Abstract:  Objective  To construct and validate a nomogram model for the prognosis of malignant meningioma based on SEER database. Methods The clinical data of patients with malignant meningioma from 1992 to 2019 were obtained from SEER database by SEER*Stat 8.4.0 software, and the screened cases were randomly divided into training set and validation set in a ratio of 8∶2. Using R 4.1.3 software, Lasso regression and multivariate Cox regression analysis were used to determine the independent prognostic factors of malignant meningioma, and the nomogram model of 1-year, 3-year and 5-year overall survival was constructed. The reliability of the nomogram was assessed by C-index, receiver operating characteristic curve (ROC), calibration curve and the risk stratification analysis. Results  A total of 717 patients were screened, including 576 in the training set and 141 in the validation set. After Lasso regression and multivariate Cox regression, age, gender, marital status and surgery were determined as independent prognostic factors for malignant meningioma（P＜0.05）. The C-index of the training set and validation set were 0.683 and 0.681, respectively. For the area under the curve (AUC) values of 1-year, 3-year and 5-year overall survival, the training set was 0.738, 0.717 and 0.747, the validation set was 0.704, 0.664 and 0.700. The calibration curve of the model showed that the predicted survival probability derived from the nomogram was in good agreement with the actual observed value. In addition, decision curve analysis (DCA) also showed that the nomogram had better benefit. After risk stratification of patients with malignant meningioma according to prognostic factors, there was a significant difference in the overall survival between the high and low risk groups (P<0.001). Conclusion  Age, gender, marital status and surgery are related to the prognosis of patients with malignant meningioma. The nomogram model constructed in this study can more accurately predict the prognosis of patients with malignant meningioma, but its wide application still needs external and prospective verify.

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