Beyond EDSS: Memory-guided saccades as candidate digital biomarkers of processing speed and fatigue in MS-A proof-of-concept study.

BACKGROUND

Disability monitoring in multiple sclerosis (MS) relies on EDSS and MRI lesion metrics that are often insensitive to cognitive dysfunction and fatigue.

OBJECTIVE

To test whether memory-guided saccade (MGS) performance relates to processing speed and fatigue independent of mood symptoms, EDSS, and MRI inflammatory activity.

METHODS

Forty-four MS patients completed MGS eye tracking. Error types and Total Task Error Rate were related to the Symbol Digit Modalities Test (SDMT), fatigue impact, mood scales, EDSS, and MRI lesion measures (including 5-year new T2 lesions) using age- and sex-adjusted partial correlations with mood sensitivity analyses.

RESULTS

Mean Total Task Error Rate was 21.5% (SD 20.6); delay errors predominated. Lower SDMT scores correlated with more delay errors (r = -0.47, p = 0.002) and higher Total Task Error Rate (r = -0.40, p = 0.008). Greater fatigue correlated with more omissions (r = 0.36, p = 0.018) and higher Total Task Error Rate (r = 0.35, p = 0.022). Associations persisted after mood adjustment. No relationships were observed with EDSS or new T2 lesions (all p > 0.1).

CONCLUSIONS

Preliminary, exploratory associations were observed between MGS metrics and measures of processing speed and fatigue in MS, independent of EDSS and MRI lesion activity. These findings should be regarded as hypothesis-generating and support further investigation of MGS as a candidate functional digital biomarker in larger, prospective, controlled studies with longitudinal follow-up and test-retest reliability assessment.