Cognitive Performance Scores for the Pediatric Automated Neuropsychological Assessment Metrics in Childhood‐Onset Systemic Lupus Erythematosus. Issue 8 (August 2015)

• Record Type: Journal Article
• Authors: Vega‐Fernandez, Patricia; Vanderburgh White, Shana; Zelko, Frank; Ruth, Natasha M.; Levy, Deborah M.; Muscal, Eyal; Klein‐Gitelman, Marisa S.; Huber, Adam M.; Tucker, Lori B.; Roebuck‐Spencer, Tresa; Ying, Jun; Brunner, Hermine I.
• Is Part Of: Arthritis care & research. Volume 67:Issue 8(2015:Aug.)
• Page Start: 1119
• Page End: 1127
• Publication Date: 2015-08
• Subjects: Arthritis -- Periodicals; Rheumatism -- Periodicals; 616.72
• DOI: 10.1002/acr.22571
• Languages: English
• ISSNs: 2151-464X

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="acr22571-sec-0001" sec-type="section"> <title>Objective</title> <p>To develop and initially validate a global cognitive performance score (CPS) for the Pediatric Automated Neuropsychological Assessment Metrics (PedANAM) to serve as a screening tool of cognition in childhood lupus.</p> </sec> <sec id="acr22571-sec-0002" sec-type="section"> <title>Methods</title> <p>Patients (n = 166) completed the 9 subtests of the PedANAM battery, each of which provides 3 principal performance parameters (accuracy, mean reaction time for correct responses, and throughput). Cognitive ability was measured by formal neurocognitive testing or estimated by the Pediatric Perceived Cognitive Function Questionnaire‐43 to determine the presence or absence of neurocognitive dysfunction (NCD). A subset of the data was used to develop 4 candidate PedANAM‐CPS indices with supervised or unsupervised statistical approaches: PedANAM‐CPS<sub>UWA</sub>, i.e., unweighted averages of the accuracy scores of all PedANAM subtests; PedANAM‐CPS<sub>PCA</sub>, i.e., accuracy scores of all PedANAM subtests weighted through principal components analysis; PedANAM‐CPS<sub>logit</sub>, i.e., algorithm derived from logistic models to estimate NCD status based on the accuracy scores of all of the PedANAM subtests; and PedANAM‐CPS<sub>multiscore</sub>, i.e., algorithm derived from logistic models to estimate NCD status based on select PedANAM performance parameters. PedANAM‐CPS candidates were validated using the remaining data.</p> </sec> <sec id="acr22571-sec-0003" sec-type="section"> <title>Results</title> <p>PedANAM‐CPS indices were moderately correlated with each other (|r| > 0.65). All of the PedANAM‐CPS indices discriminated children by NCD status across data sets (<italic>P</italic> < 0.036). The PedANAM‐CPS<sub>multiscore</sub> had the highest area under the receiver operating characteristic curve (AUC) across all data sets for identifying NCD status (AUC >0.74), followed by the PedANAM‐CPS<sub>logit</sub>, the PedANAM‐CPS<sub>PCA</sub>, and the PedANAM‐CPS<sub>UWA</sub>, respectively.</p> </sec> <sec id="acr22571-sec-0004" sec-type="section"> <title>Conclusion</title> <p>Based on preliminary validation and considering ease of use, the PedANAM‐CPS<sub>multiscore</sub> and the PedANAM‐CPS<sub>PCA</sub> appear to be best suited as global measures of PedANAM performance.</p> </sec> </abstract>