Abstract
INTRODUCTION: Spinal meningiomas (SMs) are relatively rare central nervous system tumors that usually trigger neurological symptoms. The prevalence of SMs is increasing with the aging of the global population. This study aimed to perform a systematic epidemiologic and survival prognostic analysis of SMs to evaluate their public health impact and to develop a novel method to estimate the overall survival at 3-year, 5-year, and 10-year in patients with SMs. METHODS: Five thousand one hundred fifty eight patients with SMs were recruited from the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2019. Firstly, descriptive analysis was performed on the epidemiology of SMs. Secondly, these individuals were randomly allocated to the training and validation sets in a ratio of 7:3. Kaplan-Meier method and Cox regression analysis were utilized in the training set to identify independent prognostic factors and to construct a nomogram for survival prognosis. Subsequently, the discriminative power, predictive performance, and clinical utility of the nomogram were evaluated by receiver operating characteristic curve and decision curve analysis. Finally, a mortality risk stratification system and a web-based dynamic nomogram were constructed to quantify the risk of mortality in patients with SMs. RESULTS: The annual age-adjusted incidence rates of SMs increased steadily since 2004, reaching a rate of 0.40 cases per 100 000 population in 2019, with a female-to-male ratio of ~4:1. The age groups of 50-59, 60-69, and 70-79 years old were the most prevalent ages for SMs, accounting for 19.08, 24.93, and 23.32%, respectively. In addition, seven independent prognostic factors were identified to establish a prognostic nomogram for patients with SMs. The decision curve analysis and receiver operating characteristic curve indicated that the nomogram had high clinical utility and favorable accuracy. Moreover, the mortality risk stratification system effectively divided patients into low-risk, middle-risk, and high-risk subgroups. CONCLUSIONS: SMs are relatively rare benign spinal tumors prevalent in the white elderly female population. Clinicians could use the nomogram to personalize the prediction of the overall survival probability of patients with SMs, categorize these patients into different mortality risk subgroups, and develop personalized decision-making plans. Moreover, the web-based dynamic nomogram could help to further promote clinical application and assist clinicians in providing personalized counseling, timely monitoring, and clinical assessment for patients.