Authors :
Presenting Author: Wei Zhao, MD, MSc – McGovern Medical School, UTHealth Houston
Yi-Lee Ting, MS, CGC – Labcorp
Kaley Marcinski Nascimento, MD – Washington University School of Medicine
Sarah Poll, PhD – GeneDx
Daniel Pineda Alvarez, MD – Labcorp
M. Brandon Westover, MD, PhD – Beth Israel Deaconess Medical Center
Fábio Nascimento, MD – Washington University School of Medicine
Rationale:
Genetic testing in epilepsy has become increasingly available, and recommendations for its use have been set forth by several professional societies. Yet, studies on adults with epilepsy are limited. We believe the development of a user-friendly risk prediction model may aid adult providers in selecting patients who may be good candidates to undergo genetic testing.
Methods: Adults who underwent multigene panel testing for epilepsy from March 2016 to June 2024 were divided into a training set (n=1,449) and testing set (n=1,450). We developed prediction models based on clinical characteristics using logistic regression and FasterRisk scores for positive genetic tests and tested their performance.
Results:
The prediction models had poor discriminative power and failed to predict positive results, suggesting that conventional clinical characteristics (sex, intellectual disability, developmental delay, autism, medically refractory epilepsy, family history of epilepsy, and age at seizure onset) are insufficient for selecting patients for genetic testing (Table 1).
Table 1. Logistic regression and FasterRisk models
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Logistic regression model, without age of seizure onset
Accuracy=89.0%, Recall=0%
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Variables
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Male
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ID
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DD
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Autism
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MRE
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FH
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Intercept
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Effect estimate
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-0.20
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0.51
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0.40
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0.15
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0.19
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-0.17
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-2.05
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P-value
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0.23
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0.01
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0.16
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0.59
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0.28
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0.35
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< 2x10 |