Multi-Criterial Model for Weighting Biological Risk Factors in Multiple Sclerosis: Clinical and Health Insurance...

Area of Science:

• Neurology
• Epidemiology
• Biostatistics

Background:

• The exact causes of Multiple Sclerosis (MS) are unknown, with individual risk factors playing a minor role until interacting.
• Quantifying the combined effect of these factors for MS risk prediction is challenging, limiting clinical and insurance use.

Purpose of the Study:

• To create a population-based model for weighting biological risk factors in MS.
• To calculate individual MS risk for health insurance purposes.

Main Methods:

• Retrospective analysis of 596 MS patients at diagnosis.
• Identified risk factors: low vitamin D (<10 nm/L), extreme BMI (<15 or >30 Kg/m²), female sex, family kinship, and age at onset (20-45 years).
• Applied the Choquet integral to model the interplay of these uncertain biological risk factors.

Main Results:

• In a representative 30-year-old patient with BMI 15 and second-degree kinship, low vitamin D (<10 nm/L) was the primary MS risk contributor.
• Calculated MS risks were 0.110 for females and 0.106 for males.
• Family kinship emerged as a major contributor, especially when combined with other factors.

Conclusions:

• A novel multi-criterial model enables risk stratification for Multiple Sclerosis.
• This model facilitates health insurance applications by providing individual MS risk values.
• The study highlights the significant role of interacting biological factors, particularly vitamin D and family history, in MS etiology.