An Innovative Approach to Modelling the Optimal Treatment Sequence for Patients with Relapsing-Remitting Multiple Sclerosis: Implementation, Validation, and Impact of the Decision-Making Approach.

ABSTRACT:

Introduction

An innovative computational model was developed to address challenges regarding the evaluation of treatment sequences in patients with relapsing-remitting multiple sclerosis (RRMS) through the concept of a 'virtual' physician who observes and assesses patients over time. We describe the implementation and validation of the model, then apply this framework as a case study to determine the impact of different decision-making approaches on the optimal sequence of disease-modifying therapies (DMTs) and associated outcomes.

Methods

A patient-level discrete event simulation (DES) was used to model heterogeneity in disease trajectories and outcomes. The evaluation of DMT options was implemented through a Markov model representing the patient's disease; outcomes include

SUBMITTER: Piena MA 

PROVIDER: S-EPMC8866358 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature