Quality of life and caregiver burden in familial frontotemporal lobar degeneration: Analyses of symptomatic and asymptomatic individuals within the LEFFTDS cohort.

OBJECTIVE: The Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects evaluates familial frontotemporal lobar degeneration (FTLD) kindreds with MAPT, GRN, or C9orf72 mutations. Objectives were to examine whether health-related quality of life (HRQoL) correlates with clinical symptoms and caregiver burden, and whether self-rated and informant-rated HRQoL would correlate with each other. METHODS: Individuals were classified using the Clinical Dementia Rating (CDR® ) Scale plus National Alzheimer's Coordinating Center (NACC) FTLD. HRQoL was measured with DEMQOL and DEMQOL-proxy; caregiver burden with the Zarit Burden Interview (ZBI). For analysis, Pearson correlations and weighted kappa statistics were calculated. RESULTS: The cohort of 312 individuals included symptomatic and asymptomatic individuals. CDR® plus NACC FTLD was negatively correlated with DEMQOL (r = -0.20, P = .001), as were ZBI and DEMQOL (r = -0.22, P = .0009). There was fair agreement between subject and informant DEMQOL (κ = 0.36, P <.0001). CONCLUSION: Lower HRQoL was associated with higher cognitive/behavior impairment and higher caregiver burden. These findings demonstrate the negative impact of FTLD on individuals and caregivers.

Nonlinear Z-score modeling for improved detection of cognitive abnormality.

INTRODUCTION: Conventional Z-scores are generated by subtracting the mean and dividing by the standard deviation. More recent methods linearly correct for age, sex, and education, so that these "adjusted" Z-scores better represent whether an individual's cognitive performance is abnormal. Extreme negative Z-scores for individuals relative to this normative distribution are considered indicative of cognitive deficiency. METHODS: In this article, we consider nonlinear shape constrained additive models accounting for age, sex, and education (correcting for nonlinearity). Additional shape constrained additive models account for varying standard deviation of the cognitive scores with age (correcting for heterogeneity of variance). RESULTS: Corrected Z-scores based on nonlinear shape constrained additive models provide improved adjustment for age, sex, and education, as indicated by higher adjusted-R2. DISCUSSION: Nonlinearly corrected Z-scores with respect to age, sex, and education with age-varying residual standard deviation allow for improved detection of non-normative extreme cognitive scores.