Abstract
OBJECTIVE: Impairments of speech are common in patients with glioma and negatively impact health-related quality of life (HRQoL). The benchmark for clinical assessments is task-based measures, which are not always feasible to administer and may miss essential components of HRQoL. In this study, the authors tested the hypothesis that variations in natural language (NL) correlate with HRQoL in a pattern distinct from task-based measures of language performance. METHODS: NL use was assessed using audio samples collected unobtrusively from 18 patients with newly diagnosed low- and high-grade glioma. NL measures were calculated using manual segmentation and correlated with Quality of Life in Neurological Disorders (Neuro-QoL) outcomes. Spearman's rank-order correlation was used to determine relationships between Neuro-QoL scores and NL measures. RESULTS: The distribution of NL measures across the entire patient cohort included a mean ± SD total time speaking of 11.5 ± 2.20 seconds, total number of words of 27.2 ± 4.44, number of function words of 10.9 ± 1.68, number of content words of 16.3 ± 2.91, and speech rate of 2.61 ± 0.20 words/second. Speech rate was negatively correlated with functional domains (rho = -0.62 and p = 0.007 for satisfaction with social roles; rho = -0.74 and p < 0.001 for participation in social roles) but positively correlated with impairment domains (rho = 0.58 and p = 0.009 for fatigue) of Neuro-QoL. CONCLUSIONS: Assessment of NL at the time of diagnosis may be a useful measure in the context of treatment planning and monitoring outcomes for adult patients with glioma.