Background: To enhance the use of quality of life (QoL) measures in clinical practice, it is pertinent to help clinicians interpret QoL scores.
Objective: The aim of this study was to define clusters of QoL levels from a specific questionnaire (MusiQoL) for multiple sclerosis (MS) patients using a new method of interpretable clustering based on unsupervised binary trees and to test the validity regarding clinical and functional outcomes.
Methods: In this international, multicenter, cross-sectional study, patients with MS were classified using a hierarchical top-down method of Clustering using Unsupervised Binary Trees. The clustering tree was built using the 9 dimension scores of the MusiQoL in 2 stages, growing and tree reduction (pruning and joining). A 3-group structure was considered, as follows: “high,” “moderate,” and “low” QoL levels. Clinical and QoL data were compared between the 3 clusters.
Results: A total of 1361 patients were analyzed: 87 were classified with “low,” 1173 with “moderate,” and 101 with “high” QoL levels. The clustering showed satisfactory properties, including repeatability (using bootstrap) and discriminancy (using factor analysis). The 3 clusters consistently differentiated patients based on sociodemographic and clinical characteristics, and the QoL scores were assessed using a generic questionnaire, ensuring the clinical validity of the clustering.
Conclusions: The study suggests that Clustering using Unsupervised Binary Trees is an original, innovative, and relevant classification method to define clusters of QoL levels in MS patients.
*EA3279 Self-Perceived Health Assessment Research Unit and Department of Public Health, Nord University Hospital, APHM, Aix-Marseille University
†Department of Mathematics, Faculté des Sciences de Luminy, Aix-Marseille University, Marseille, France
‡Institute of Clinical Neurosciences, Hospital Regional Universitario Carlos Haya, Málaga, Spain
§Neurological Rehabilitation Center Quellenhof, Bad Wildbad, Germany
∥Departments of Neurology and CRMBM CNRS6612, Timone University Hospital, APHM, Marseille, France
Supported by Merck Serono SA—Geneva, Switzerland, a branch of Merck Serono SA, Coinsins, Switzerland, an affiliate of Merck KGaA, Darmstadt, Germany.
The authors declare no conflict of interest.
Reprints: Karine Baumstarck, MD, PhD, Aix-Marseille University, EA 3279—Public Health, Chronic Diseases and Quality of Life—Research Unit, Marseille 13284, France. E-mail: email@example.com.