Optimizing Outcomes in PLGG Survivorship Study

Award: $364,000 over 3 years (2019-2023)
Principle Investigators: Dr. Tobey Macdonald, Children’s Hospital of Atlanta; Dr. Krista Hardy, Children’s National Medical Center, Dr. Tricia King, Georgia State University Medical Center

Pediatric low grade gliomas (PLGG) are the most common childhood brain cancer. Although there are higher survival rates and less severe cognitive complications relative to other pediatric brain tumors, the cognitive outcomes among PLGG are variable and disruption in cognitive abilities and everyday functioning may be subtle in some PLGG survivors. Therefore, it is essential to identify changes in cognition as early as possible so that interventions can be initiated quickly in order to optimize long-term outcomes. Unfortunately, due to better outcomes on average in PLGG, fewer children are routinely referred for monitoring of neurocognitive outcomes over time. The technology for computer-based assessment of neuropsychological functioning has only recently become widely available. it is crucial to establish a reliable, valid, and efficient screening battery in PLGG that is sensitive to subtle neurocognitive changes and impairments in order to improve the quality of care available in standard practice of PLGG. Our first aim is to examine performance on computerized measures of processing speed, attention, and executive function using NIH Toolbox and Cogstate. We also will obtain concurrent reliability and sensitivity data with gold-standard measures of performance of these constructs, and parent report of attention, executive and adaptive abilities in everyday functioning, as well as important contextual information on sleep, fatigue, physical activity, and household material hardship. Second, it is critical to understand the genetic predisposition of individuals with PLGG that may impact cognitive outcomes after treatment for PLGG. Using whole genome sequencing of patient DNA, we plan to conduct host genome wide analyses, disease-associated genome variant profiles, as well as targeted SNP analyses in order to identify the SNPs associated with neurocognitive vulnerabilities (e.g. sustained attention difficulties), and SNPs associated with neuroinflammation following brain tumor treatment. In sum, integration of computerized measures with traditional measures of neurocognitive functioning fits within a problem-prevention model that emphasizes universal monitoring of children over time with minimal burden and cost. The model is designed to identify children with emerging problems before significant functional impairments develop, and to respond to the call for risk-based approaches to survivorship care. McCabe and colleagues recently commented that, “Although tailoring follow-up survivorship care based on risk for adverse outcomes is widely considered to be the way forward,” few studies evaluating this approach have been published, and “none considered other aspects of risk such as psychosocial adjustment and risk of long-term or late-effects of treatment” (p 809). Data provided by the proposed study also have the potential to permit development and implementation of treatment strategies for at-risk children that can be administered before the onset of functional cognitive impairments.

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