Glioma Clinical Trial
Official title:
Development and Validation of a Deep Learning-Based Survival Prediction Model for Pediatric Glioma Patients: A Retrospective Study Using the SEER Database and Chinese Data
Verified date | December 2023 |
Source | Tang-Du Hospital |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational |
Accurately predicting the survival of pediatric glioma patients is crucial for informed clinical decision-making and selecting appropriate treatment strategies. However, there is a lack of prognostic models specifically tailored for pediatric glioma patients. This study aimed to address this gap by developing a time-dependent deep learning model to aid physicians in making more accurate prognostic assessments and treatment decisions.
Status | Completed |
Enrollment | 9532 |
Est. completion date | December 20, 2023 |
Est. primary completion date | August 16, 2023 |
Accepts healthy volunteers | |
Gender | All |
Age group | N/A to 21 Years |
Eligibility | Inclusion Criteria: - To identify specific tumor types, the International Classification of Diseases for Oncology, 3rd Edition codes (ICD-O-3) were used, including codes 9450, 9394, 9421, 9384, 9383, 9424, 9400, 9420, 9410, 9411, 9380, 9382, 9391, 9393, 9390, 9401, 9381, 9451, 9440, 9441, 9442, 9430, and 9380, covering astrocytic tumors, oligodendroglia tumors, oligoastrocytic tumors, ependymal tumors, and other gliomas. Inclusion criteria comprised all primary brain tumors (C71.0-C71.9, C72.3, C72.8, C75.3) diagnosed, among patients under 21 years old, and meeting the third edition of the ICD-O-3 classification. Exclusion Criteria: - Only patients with available survival time were included, and those with unknown or missing clinical features were excluded. |
Country | Name | City | State |
---|---|---|---|
China | Tangdu Hospital | Xi'an | Shannxi |
Lead Sponsor | Collaborator |
---|---|
Tang-Du Hospital |
China,
Doll KM, Rademaker A, Sosa JA. Practical Guide to Surgical Data Sets: Surveillance, Epidemiology, and End Results (SEER) Database. JAMA Surg. 2018 Jun 1;153(6):588-589. doi: 10.1001/jamasurg.2018.0501. No abstract available. — View Citation
Thomas L, Li F, Pencina M. Using Propensity Score Methods to Create Target Populations in Observational Clinical Research. JAMA. 2020 Feb 4;323(5):466-467. doi: 10.1001/jama.2019.21558. No abstract available. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | overall survival | The primary outcome was overall survival (OS), which was defined as the time interval from the pediatric glioma diagnosis until death or the end of follow-up in SEER registry | 2000.01-2018.12 | |
Primary | overall survival | The primary outcome was overall survival (OS), which was defined as the time interval from the pediatric glioma diagnosis until death or the end of follow-up in Chinese registry | 2010.01-2018.12 |
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