Development and validation of a scoring system for predicting disease activity in treatment-naïve patients with...

Relapsing-remitting MS (RRMS) exhibits significant heterogeneity and different treatment responses. Up to date, there is no international consensus on defining disease activity which foretells potential prognosis. This study aims to develop and validate a "Scoring System for Disease Activity Prognosis in Treatment-Naïve RRMS Patients" (DAPS-RRMS) to help guiding treatment decisions.

A set of clinical and radiological factors predicting RRMS disease activity based on an extensive literature review were identified. Real-world data from 520 treatment-naïve RRMS patients were extracted from the Egyptian MS registry dataset by independent neurologists and were disseminated among a group of MS experts for evaluation of each case separately. To convert this clinical impression into a validated score, ordinal logistic regression was used to develop the scoring system and nomogram; validation was conducted using Receiver Operating Characteristic (ROC); interrater reliability was assessed using Kendall's coefficient of concordance and the Intraclass Correlation Coefficient (ICC).

According to cut off values based on the sum of scores of involved parameters, patients were classified into four categories predicting disease activity, "Active" (0-9), "Highly Active" (9.5-14), "Very Highly Active" (14.5-19), and "Aggressive" (>19). The scoring tool demonstrated excellent performance metrics with high inter-rater agreement (Kendall's W 0.764), and reliability including a high area under the curve (AUC) for discriminating between categories.

This validated scoring system provides a practical and reliable tool for predicting RRMS disease activity and guiding treatment decisions in treatment-naïve patients, particularly in resource-limited countries. The model is combined with a user-friendly nomogram.