Year: 2020
Type: conference-abstract
Abstract: Pediatric low-grade gliomas (pLGG) account for one third of all central nervous system (CNS) tumors. MRI is the preferred imaging modality for diagnosis and response evaluation. This study aims to evaluate if radiographic characteristics of pLGG at diagnosis are prognostic. Medical records of 700 pLGG patients were reviewed who were seen between 1998- 2019 at our institution. Summary statistics were provided to describe patient demographic and clinical characteristics. 603 patients were not eligible because incomplete records, 97 patients were identified and eligible for the review. There were 45 females and 52 males with the mean age of 6.5 years at diagnosis. Patients were categorized based on contrast enhancement to 2 groups; none/mild versus moderate/high with 65 and 32 patients respectively. 31 patients had infiltrative glioma (32.3%) with more than one lobe involved at diagnosis. Fifteen patients (15.46%) had hydrocephalous at initial diagnosis. 32 patients (32.9%) did not have any treatment and remained stable while 65(67.0%) had either surgery, chemotherapy or radiation or combination. 21 patients had neurofibromatosis type-1(NF-1) with better outcome comparing to non-NF1 as previously reported. No statistically significant difference in outcome was found based on the imaging characteristics at diagnosis including contrast enhancement, hydrocephalus, tumor size, presence of cyst or infiltrative tumors. The 5 years PFS rate for the entire cohort was 47%. Our study results are limited by low patient number, hence collaborative multi-institutional studies are warranted to delineate consensus and investigate prognostic factors to improve the outcome of pLGG.
Source: Neuro-Oncology
Authors: Muhammad Baig, Michael Chan, Jason Johnson, Sana Mohiuddin, Ruitao Lin, Michael Roth, Zsila Sadighi, John Slopis, Soumen Khatua, Wafik Zaky
Institution: The University of Texas MD Anderson Cancer Center
Language: English
Subfield: Genetics (clinical)
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $5,132
OpenAlex ID: W3111405332
