Normative data and validation of a regression based summary score for assessing meaningful neuropsychological change

Abstract

Reliable detection and quantification of longitudinal cognitive change are of considerable importance in many neurological disorders, particularly to monitor central nervous system effects of disease progression and treatment. In the current study, we developed normative data for repeated neuropsychological (NP) assessments (6 testings) using a modified standard regression-based (SRB) approach in a sample that includes both HIV-uninfected (HIV–, N = 172) and neuromedically stable HIV-infected (HIV+, N = 124) individuals. Prior analyses indicated no differences in NP change between the infected and uninfected participants. The norms for change included correction for factors found to significantly affect follow-up performance, using hierarchical regression. The most robust and consistent predictors of follow-up performance were the prior performance on the same test (which contributed in all models) and a measure of prior overall NP competence (predictor in 97% of all models). Demographic variables were predictors in 10–46% of all models and in small amounts; while test–retest interval contributed in only 6% of all models. Based on the regression equations, standardized change scores (z scores) were computed for each test measure at each interval; these z scores were then averaged to create a total battery change score. An independent sample of HIV– participants who had completed 8 of the 15 tests was used to validate an abridged summary change score. The normative data are available in an electronic format by e-mail request to the first author. Correction for practice effects based on normative data improved the consistency of NP impairment classification in a clinically stable longitudinal cohort after baseline.