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THE DEVELOPMENT AND VALIDATION OF A DISABILITY AND OUTCOME PREDICTION ALGORITHM IN MULTIPLE SCLEROSIS PATIENTS

SIMONA OPREA 1, ANDREI VĂLEANU 2*, SIMONA NEGREȘ 2

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At the moment, multiple sclerosis (MS) is considered one of the major disability factors among the young population. Considering the high prevalence and severity of this chronic disease, the aim of this study was to develop a disability and outcome prediction algorithm in MS patients. The data from two MS patient groups was analysed – Group A (151 patients with the following drug therapies: interferon beta-1a, glatiramer acetate, teriflunomide, natalizumab) and Group B (58 patients treated with natalizumab). Considering certain demographical and clinical predictive variables, as well as different disability threshold values, several prediction models were developed and validated, which are able to estimate the disability (Expanded Disability Status Scale, EDSS) and outcome probabilities. The prediction model validation on estimating the disability and outcome probabilities yielded a maximum Area Under the Receiver Operating Characteristic Curve (ROC AUC) Score of 80 - 82%. The overall results indicate that for Group A disability prediction based on EDSS is appropriate, while for Group B the outcome might be a better measure for probability estimation. Hence, the results suggest that the outcome is a more appropriate measure for monitoring natalizumab treated MS patients, since it depends on other clinical characteristics as opposed to the sole disability estimation through the EDSS score. A disability and outcome prediction model in MS patients was developed and validated. Despite the fact that the obtained results were satisfactory given the small dataset, by embedding more predictive demographical and clinical variables in the algorithm, as well as including more patients, the model could be used through an online platform in MS patients’ monitoring and prioritization, in order to succeed in improving the quality of life and reducing disability progression.