Leonardo A Frizon1,2, Olivia Hogue3, Rebecca Achey4, Darlene P Floden1, Sean Nagel1, Andre G Machado1, Darlene A Lobel1. 1. Center for Neurological Restoration, Neurological Institute, Cleveland Clinic. Cleveland, Ohio. 2. Post-graduate Program in Medicine: Surgical Sciences, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil. 3. Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic. Cleveland, Ohio. 4. Cleveland Clinic Lerner College of Medicine. Cleveland, Ohio.
Abstract
BACKGROUND: There is a growing attention to determine the factors that predict quality of life (QoL) improvement after deep brain stimulation (DBS) for Parkinson's disease. Prior literature has largely focused on examining predictors one at a time, sometimes controlling for covariates. OBJECTIVE: To develop a model that could be used as a nomogram to predict improvement in QoL following DBS surgery in patients with Parkinson's disease. METHODS: All patients with complete pre- and postoperative movement disorder and neuropsychological testing who underwent DBS at a single institution between 2007-2012 were analyzed. The Parkinson's Disease Questionnaire-39 (PDQ-39) was used to measure QoL. Potential predictive factors, including patient demographics, clinical presentation characteristics, radiographic imaging, and motor and psychological testing were analyzed for impact on QoL. RESULTS: Sixty-seven patients were identified, 36 (53.73%) of whom had meaningfully improved QoL following surgery. Five baseline variables showed significant relationships with the outcome: years since symptom onset, percent change in on/off motor evaluation, levodopa equivalent daily dose, bilateral vs unilateral DBS implantation, and PDQ-39 score. The final model includes PDQ-39, percent change in UPRS-III, and years since symptom onset and is able to predict improvement in QoL with 81% accuracy. CONCLUSION: Our model accurately predicted whether QoL would improve in patients undergoing subthalamic nucleus DBS 81% of the time. Our data may serve as the foundation to further refine a clinically relevant prognostic tool that would assist the decision-making process for clinicians and DBS multidisciplinary teams assessing patient candidacy for surgery.
BACKGROUND: There is a growing attention to determine the factors that predict quality of life (QoL) improvement after deep brain stimulation (DBS) for Parkinson's disease. Prior literature has largely focused on examining predictors one at a time, sometimes controlling for covariates. OBJECTIVE: To develop a model that could be used as a nomogram to predict improvement in QoL following DBS surgery in patients with Parkinson's disease. METHODS: All patients with complete pre- and postoperative movement disorder and neuropsychological testing who underwent DBS at a single institution between 2007-2012 were analyzed. The Parkinson's Disease Questionnaire-39 (PDQ-39) was used to measure QoL. Potential predictive factors, including patient demographics, clinical presentation characteristics, radiographic imaging, and motor and psychological testing were analyzed for impact on QoL. RESULTS: Sixty-seven patients were identified, 36 (53.73%) of whom had meaningfully improved QoL following surgery. Five baseline variables showed significant relationships with the outcome: years since symptom onset, percent change in on/off motor evaluation, levodopa equivalent daily dose, bilateral vs unilateral DBS implantation, and PDQ-39 score. The final model includes PDQ-39, percent change in UPRS-III, and years since symptom onset and is able to predict improvement in QoL with 81% accuracy. CONCLUSION: Our model accurately predicted whether QoL would improve in patients undergoing subthalamic nucleus DBS 81% of the time. Our data may serve as the foundation to further refine a clinically relevant prognostic tool that would assist the decision-making process for clinicians and DBS multidisciplinary teams assessing patient candidacy for surgery.
Authors: Jeroen G V Habets; Marcus L F Janssen; Annelien A Duits; Laura C J Sijben; Anne E P Mulders; Bianca De Greef; Yasin Temel; Mark L Kuijf; Pieter L Kubben; Christian Herff Journal: PeerJ Date: 2020-11-18 Impact factor: 2.984