Abstract
Cocaine use disorder (CUD) is a worldwide health problem with limited effective treatment options. The therapeutic potential of repetitive transcranial magnetic stimulation (rTMS) is gaining more attention following evidence of its role on craving reduction in CUD. However, the heterogeneity of results underscores a pressing need for biomarkers of treatment outcome. We asked whether brain connectomics together with clinical assessments can predict response to add-on rTMS therapy for CUD better than solely conventional clinical assessments.
A total of 36 patients with CUD underwent an open-label acute phase of receiving two daily sessions of 5-Hz rTMS on the left dorsolateral prefrontal cortex (LDLPFC). Subsequently, 19 and 14 patients continued to an open-label maintenance phase of two weekly rTMS sessions for 3 and 6 months, respectively. Pre and post treatment resting-state brain functional connectivity as well as two clinical scores related to craving were measured to predict the subsequent response to rTMS therapy. Two conventional clinical scores, namely Cocaine craving questionnaires (CCQ) and visual analogue scale (VAS) were used as craving level assessments. We used a priori seed-driven connectivity of DLPFC and anterior cingulate cortex (ACC) together with the connectivity from a whole-brain multi-voxel pattern analysis at each time point to predict the reduction in craving after rTMS.
The combination of connectivity changes and baseline craving severity measures improved the prediction of individual craving compared to the prediction with only initial craving severity. The predictive model from the combination of neuromarkers could explain 45 to 97 percent of variance in craving changes assessed by two different clinical scores. We used leave-one-subject-out cross-validation to support the generalizability of our findings. Our results indicate that employing neuromarkers from resting-state functional connectivity of pre and post condition of CUD patients receiving add-on rTMS therapy increases the power of predicting craving changes and support the idea that neuromarkers may offer improvements in precision medicine approaches.