Abstract
Background
Understanding individual variability in response to interventions is essential for developing personalized treatment strategies. In rare and clinically heterogeneous conditions like primary progressive aphasia (PPA), predicting treatment response is particularly challenging due to varying clinical manifestations. In this study, we aimed to identify and analyze predictors of individual language response to transcranial direct current stimulation (tDCS) of the left inferior frontal gyrus (IFG), using a novel, robust analytic approach focused on treatment effect heterogeneity.
Methods
We compared the ability of predicting individual effect (active vs sham tDCS during 20-minute sessions on weekdays for 3 weeks; active: 2 mA current across electrodes; sham: current ramped down after 30 seconds), using demographic and clinical patient characteristics (eg, PPA variant and disease progression, baseline language performance) or volumetric fMRI data versus functional connectivity (from resting-state fMRI) in the cohort of 36 patients.
Results
Functional connectivity alone had the highest predictive value for outcomes, explaining 62% of the variance of the tDCS effect in generalization (semantic fluency) and 75% of the main outcome (written naming), contrasted with <15% (for semantic fluency) and <23% (for written naming) of variance predicted by demographic and clinical patient characteristics or volumetric data. Patients with higher baseline functional connectivity within the left IFG (between pars opercularis and pars triangularis) were most likely to benefit from tDCS both in generalization (semantic fluency) as well as in the main outcome (written naming). In addition, patients with higher baseline FC between the middle temporal pole and superior temporal gyrus, were most likely to show generalization effects of tDCS.
Conclusions
The present study showcases the importance of a baseline functional connectivity scan in predicting tDCS outcomes, and points toward a precision medicine approach in neuromodulation studies. The study has important implications for clinical trials and practice, providing a statistical method that addresses heterogeneity in patient populations and allowing accurate prediction and enrollment of those who will most likely benefit from specific interventions.
Keywords
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References
Supplementary Material
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