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CompletedNCT06199388Updated Jan 10, 2024

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

An observational study in Glioma, sponsored by Tang-Du Hospital. Completed at 1 site in China. Open to participants aged Up to 21 Years. Per ClinicalTrials.gov, last updated 2024-01-10.

Sponsored by Tang-Du Hospital · Observational

Study type
Observational
Model
Cohort
Time perspective
Retrospective
Enrollment
9,532
Ages
Up to 21 Years
Sex
All
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Study summary

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.

Read the detailed description

This retrospective study focuses on survival prediction in pediatric glioma patients using a population-based approach. The model was trained using the Surveillance, Epidemiology, and End Results (SEER) Registry database. 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 between 2000 and 2018, among patients under 21 years old, and meeting the third edition of the ICD-O-3 classification. Only patients with available survival time were included, and those with unknown or missing clinical features were excluded. This cohort consisted of 258 pediatric glioma patients diagnosed at Tangdu Hospital in Xi\'an, China, between January 2010 and December 2018. These patients had complete clinical data and comprehensive follow-up records.

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Conditions studied

  • Glioma

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03

In context

Glioma

1,397 studies on the registry are indexed under Glioma; 351 are open to participants now.

This study's enrollment of 9,532 is above the median of 88 across 238 observational studies indexed under Glioma.

Browse Glioma studies →

Lead sponsor

Tang-Du Hospital is the lead sponsor of 164 studies on the registry; 77 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
Up to 21 Years
Sexes eligible
All
Sampling method
Probability sample

Study population

the US Surveillance, Epidemiology, and End Results (SEER) between January 2000 and December 2018 and a Chinese registry (The Tangdu Hospital of the Fourth Military Medical Universitye) between January 2010 and December 2018

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

Exclusion Criteria:

  • Only patients with available survival time were included, and those with unknown or missing clinical features were excluded.
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Study design

Observational model
Cohort
Time perspective
Retrospective
Enrollment
9,532 participants (actual)
Patient registry
No

Groups and cohorts

  • SEER database

    The model was trained using the Surveillance, Epidemiology, and End Results (SEER) Registry database. 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 between 2000 and 2018, among patients under 21 years old, and meeting the third edition of the ICD-O-3 classification. Only patients with available survival time were included, and those with unknown or missing clinical features were excluded.

    Other: Survival state

  • Chinese cohort

    To assess the generalizability of the final model, an external validation cohort from China was used. This cohort consisted of 258 pediatric glioma patients diagnosed at Tangdu Hospital in Xi\'an, China, between January 2010 and December 2018. These patients had complete clinical data and comprehensive follow-up records.

    Other: Survival state

Interventions

  • OtherSurvival state

    We recorded clinically relevant information and survival status of pediatric glioma patients

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What researchers measure

Primary outcomes

  1. 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

    Time frame: 2000.01-2018.12

  2. 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

    Time frame: 2010.01-2018.12

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Study locations

1 site
  • Tangdu Hospital
    Xi'an, Shannxi 710000, China
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References and documents

Publications

  • 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. PubMed 31922529 ↗
  • 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. PubMed 29617544 ↗

Individual participant data

Plan to share: No — The data involves the relevant personal privacy information of the patient

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jan 10, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT06199388
Lead sponsor
Tang-Du Hospital
Responsible party
Sponsor
First posted
Jan 10, 2024
Start date
Sep 20, 2022
Primary completion
Aug 16, 2023
Completion
Dec 20, 2023
Last update
Jan 10, 2024

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Dec 2023. You cannot join it, but the record below documents what was studied.

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