Using Bayesian networks to identify musculoskeletal symptoms influencing the risk of developing psoriatic arthritis in people with psoriasis.

ABSTRACT:

Objectives

The aim of this study was to explore the use of Bayesian networks (BNs) to understand the relationships between musculoskeletal symptoms and the development of PsA in people with psoriasis.

Methods

Incident cases of psoriasis were identified for 1998 to 2015 from the UK Clinical Research Practice Datalink. Musculoskeletal symptoms (identified by Medcodes) were concatenated into primary groups, each made up of several subgroups. Baseline demographics for gender, age, BMI, psoriasis severity, alcohol use and smoking status were also extracted. Several BN structures were composed using a combination of expert knowledge and data-oriented modelling based on: (i) primary musculoskeletal symptom groups; (ii) musculoskeletal symptom subgroups and (iii) demographic variabl

SUBMITTER: Green A 

PROVIDER: S-EPMC8824425 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature