Statistical Approaches to Assess the Effects of Disease on Neurocognitive Function Over Time.
BACKGROUND
Assessment of the effects of disease on neurocognitive outcomes in children over time presents several challenges. These challenges are particularly pronounced when conducting studies in low-income countries, where standardization and validation is required for tests developed originally in high-income countries. We present a statistical methodology to assess multiple neurocognitive outcomes over time. We address the standardization and adjustment for age in neurocognitive testing, present a statistical methodology for development of a global neurocognitive score, and assess changes in individual and global neurocognitive scores over time in a cohort of children with cerebral malaria.


METHODS
Ugandan children with cerebral malaria (CM, N = 44), uncomplicated malaria (UM, N = 54) and community controls (N = 89) were assessed by cognitive tests of working memory, executive attention and tactile learning at 0, 3, 6 and 24 months after recruitment. Tests were previously developed and validated for the local area. Test scores were adjusted for age, and a global score was developed based on the controls that combined the assessments of impairment in each neurocognitive domain. Global normalized Z-scores were computed for each of the three study groups. Model-based tests compare the Z-scores between groups.


RESULTS
We found that continuous Z-scores gave more powerful conclusions than previous analyses of the dataset. For example, at all four time points, children with CM had significantly lower global Z-scores than controls and children with UM. Our methods also provide more detailed descriptions of longitudinal trends. For example, the Z-scores of children with CM improved from initial testing to 3 months, but remained at approximately the same level below those of controls or children with UM from 3 to 24 months. Our methods for combining scores are more powerful than tests of individual cognitive domains, as testing of the individual domains revealed differences at only some but not all time points.
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA ; Cardiac Rhythm Disease Management, Medtronic, Mounds View, Minnesota, USA.
Tracy L
TL
Bergemann
Department of Psychiatry, Makerere University School of Medicine, Kampala, Uganda ; Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.
Paul
P
Bangirana
International Neurologic and Psychiatric Epidemiology Program, College of Osteopathic Medicine, Michigan State University, East Lansing, Michigan, USA ; Neuropsychology Section, Department of Psychiatry, University of Michigan, Ann Arbor, Michigan.
Michael J
MJ
Boivin
Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA.
John E
JE
Connett
Neuropsychology Section, Department of Psychiatry, University of Michigan, Ann Arbor, Michigan.
Bruno J
BJ
Giordani
Division of Global Pediatrics, Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota, USA.
Chandy C
CC
John
Cumulative; Development; Global score; Longitudinal data analysis; Malaria; Neurocognitive; Normalization