Predictors of motor outcome with pallidal stimulation for Parkinson's disease from the CSP468 cohort

Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is an effective treatment for medication‑refractory Parkinson's disease (PD), though outcomes vary widely. The influence of lead location relative to the GPi therapeutic sweetspot has not previously been examined within a multivariable regression framework. This study evaluated the predictive utility of volume-of-tissue-activated (VTA)-sweetspot overlap on postoperative UPDRS‑III outcomes in the CSP #468 cohort receiving bilateral GPi‑DBS, alongside demographic/clinical predictors, using two independently derived sweetspot models. CSP #468 was a multicenter randomized clinical trial with blinded 6‑month outcomes and robust collection of associated features of PD. A prior publication generated a cross validated 6‑month GPi-sweetspot from this dataset. An independent single‑surgeon cohort was used to construct a separate sweetspot uninfluenced by CSP outcomes. Multivariable modeling was completed using backward‑selection linear regression with Bonferroni correction. Models were checked for assumptions, data leakage, and overfitting. Each sweetspot-multivariable model's ability to predict outcomes in the opposite cohort was assessed. Both sweetspots localized to the primary motor GPi. The independent sweetspot multivariable model included VTA‑sweetspot overlap and levodopa response (R²_Adj = 0.19) and remained robust under leave-one-out cross validation. The CSP sweetspot multivariable model also predicted outcomes in the independent cohort (p = 0.004), demonstrating meaningful external validity.