Predicting disease progression in high-grade glioma with neuropsychological parameters: the value of personalized longitudinal assessment

E. Butterbrod, J. Bruijn, M.M. Braaksma, G.-J.M. Rutten, C.C. Tijssen, M.C.J. Hanse, M.M. Sitskoorn, K. Gehring

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

© 2019, The Author(s).Purpose: Progressive disease in patients with high-grade glioma may be reflected in cognitive decline. However, the cognitive functions most sensitive to progression may differ between patients. We investigated whether decline on a personalized selection of tests predicted progressive disease according to RANO criteria in high-grade glioma patients. Methods: Starting one day before surgery, patients underwent neuropsychological assessment every three months during standard treatment and clinical follow-up. We first made a personalized selection of three tests that showed the highest Reliable Change Index (RCI) values, i.e., most positive change, at the first post-surgical assessment for each patient. In subsequent follow up, a decline of RCI ≤ − 1 on at least two of the three tests in the selection was considered cognitive decline. We performed a discrete Cox proportional hazards model including a time-dependent coefficient cognitive decline (vs. stability) and covariate age to predict progressive disease. Results: Twenty five patients were included. Cognitive decline on the personalized test selection preceded or had occurred by the time progression was established in 9/15 patients with RANO confirmed progressive disease (60%). Decline was absent in 8/10 patients (80%) with stable disease during participation. The independent hazard ratio for progression in case of cognitive decline was 5.05 (p ' 0.01) compared to stable performance. Conclusions: Using only three patient-specific neuropsychological tests, we found a fivefold increased chance of disease progression in case of cognitive decline as compared to stable performance. Brief, patient-tailored cognitive assessment may be a noninvasive addition to disease monitoring without overburdening patients and clinical care.
Original languageEnglish
Pages (from-to)511-518
JournalJournal of Neuro-Oncology
Volume144
Issue number3
DOIs
Publication statusPublished - 1 Sep 2019
Externally publishedYes

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