Nomogram for Early Prediction of Parkinson's Disease Based on microRNA Profiles and Clinical Variables.

ABSTRACT:

Background

Few efficient and simple models for the early prediction of Parkinson's disease (PD) exists.

Objective

To develop and validate a novel nomogram for early identification of PD by incorporating microRNA (miRNA) expression profiles and clinical indicators.

Methods

Expression levels of blood-based miRNAs and clinical variables from 1,284 individuals were downloaded from the Parkinson's Progression Marker Initiative database on June 1, 2022. Initially, the generalized estimating equation was used to screen candidate biomarkers of PD progression in the discovery phase. Then, the elastic net model was utilized for variable selection and a logistics regression model was constructed to establish a nomogram. Additionally, the receiver operating characteristic (ROC) c

SUBMITTER: Hou X 

PROVIDER: S-EPMC10357140 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature