World neurosurgery · 2024
Epidemiological Characteristics and Prognosis Model of Pineal Region Tumors: A Retrospective Analysis Based on the SEER Database.
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Li Ao, Bai Xue, Chen Mengfei, Li Zhuoqi, Sun Tao
Аннотация
BACKGROUND: A pineal region tumor is a rare intracranial tumor, and its specific location leads to its own characteristics. This study aimed to provide some insight for medical practice in the care of pineal region tumors. We investigated the key epidemiological characteristics and survival prognosis of pineal tumors based on the epidemiological data from the Surveillance, Epidemiology, and End Results database.
METHODS: Data of pineal region tumor patients from 1975 to 2019 were extracted from the Surveillance, Epidemiology, and End Results database. The data were divided into 3 pathologic groups: germ cell tumors, pineal parenchymal tumors, and other. The patients' overall survival (OS) was analyzed using the Kaplan-Meier method. The prognostic effects of the patient characteristics on OS were explored using the Cox proportional hazard model. The analysis results are presented as tabular data, Kaplan-Meier plots, forest plots, and nomograms. A calibration curve was used to verify the nomograms. All analyses were performed for all patients overall and stratified by pathological group using SPSS and R language.
RESULTS: Based on the predefined inclusion and exclusion criteria, 628 patients were included in this study, of whom 440 (70.1%) were male and 188 (29.9%) were female. Most patients were aged 0-19 years. The pathological type was germinoma for 225 patients (35.8%). Age, surgery, behavioral code, and pathology were significant factors for OS. A calibration curve was used to verify that the nomograms had a good prediction effect.
CONCLUSIONS: An intuitive nomogram was developed and verified and can predict the prognosis of patients with pineal tumors.
METHODS: Data of pineal region tumor patients from 1975 to 2019 were extracted from the Surveillance, Epidemiology, and End Results database. The data were divided into 3 pathologic groups: germ cell tumors, pineal parenchymal tumors, and other. The patients' overall survival (OS) was analyzed using the Kaplan-Meier method. The prognostic effects of the patient characteristics on OS were explored using the Cox proportional hazard model. The analysis results are presented as tabular data, Kaplan-Meier plots, forest plots, and nomograms. A calibration curve was used to verify the nomograms. All analyses were performed for all patients overall and stratified by pathological group using SPSS and R language.
RESULTS: Based on the predefined inclusion and exclusion criteria, 628 patients were included in this study, of whom 440 (70.1%) were male and 188 (29.9%) were female. Most patients were aged 0-19 years. The pathological type was germinoma for 225 patients (35.8%). Age, surgery, behavioral code, and pathology were significant factors for OS. A calibration curve was used to verify that the nomograms had a good prediction effect.
CONCLUSIONS: An intuitive nomogram was developed and verified and can predict the prognosis of patients with pineal tumors.