19: Real Data-Driven, Robust Survival Analysis on Patients with Parkinson's Disease

Dilmi Abeywardana Co-Author
 
Chris Tsokos Co-Author
Distinguished University Professor-USF
 
Malinda Iluppangama First Author
 
Malinda Iluppangama Presenting Author
 
Monday, Aug 4: 10:30 AM - 12:20 PM
2786 
Contributed Posters 
Music City Center 
Parkinson's Disease (PD) is a devastating neurodegenerative disorder that affects millions of people around the globe. Many researchers are continuously working to understand PD and develop treatments to improve the condition of PD patients that affects their day-to-day lives. In the last decades, the treatment of Deep Brain Stimulation (DBS) has given promising results for motor symptoms by improving the quality of daily living of PD patients. In the methodology of the present study, we have utilized sophisticated statistical approaches such as Nonparametric, Semiparametric, and robust Parametric survival analysis to extract useful and important information about the long-term survival outcomes of the patients who underwent DBS for PD. Finally, we were able to conclude that the probabilistic behavior of the survival time of female patients is statistically different from that of male patients. Furthermore, we have identified that the probabilistic behavior of the survival times of Female patients is characterized by the 3-parameter Lognormal distribution while that of Male patients is characterized by the 3-parameter Weibull distribution.

Keywords

Survival Analysis

COX-PH

Deep Brain Stimulation

Movement Disorder

Parkinson’s Disease

Parametric, Non-Parametric and Semi-Parametric Survival Analysis 

Abstracts


Main Sponsor

Biometrics Section