WEST PALM BEACH, FL –, new research suggests.
The research shows that once standard clinical models can be incorporated into practice, the early measurement of these biomarkers will provide useful information in predicting who may be at risk of poorer outcomes, researcher Gauruv Bose, MD, Brigham Multiple Sclerosis Center, Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, told this news organization.
The findings were presented at annual meeting held by the Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS).
Although higher baseline sNfL levels in MS have previously been linked to greater brain atrophy and other long-term outcomes, and sGFAP changes are also associated with inflammation and damage through the disease course, less is known about longer-term effects of the two biomarker measures combined, Dr. Bose said.
“The value of using both sNfL and sGFAP in predictive models is of interest, since one correlates with neuroaxonal damage, while the other has correlated with astrocytic glial damage/cell turnover – potentially, though differently, reflecting inflammatory damage and neurodegeneration,” he added.
To investigate the relationship, the researchers evaluated patients with MS enrolled at the Brigham Multiple Sclerosis Center. All underwent neurologic examinations every 6 months, and MRI scans and blood samples were collected every year. Some had more than 20 years of follow-up.
The first study involved 144 patients (mean age, 37.4 years) from whom two samples of sNfL and sGFAP were collected within 3 years of MS onset.
The median baseline sNfL level was 10.7 pg/mL, and 50 patients (34.7%) already showed increases in sNfL at the 1-year follow-up. Their median sGFAP level at onset was 96 pg/mL, and 59 patients (41%) showed increases in sGFAP at the 1-year follow-up.
Results showed that higher baseline sNfL levels were significantly associated with increased risk for MS relapse at 10 years (hazard ratio, 1.34; P = .04), as well as with the development of new MRI lesions (HR, 1.35; P = .022).
Of the study group, 25 (17.4%) developed secondary progressive MS (SPMS) by the 10-year follow-up. For those prognostic assessments, the investigators compared utilization of a model using well-established clinical predictors of SPMS with and without the inclusion of sNfL and sGFAP.
The clinical model included key factors such as age, sex, body mass index, Extended Disability Status Scale (EDSS), timed 25-foot walk, and other measures.
The researchers found the clinical model alone predicted 10-year outcomes with an area under the receiver operating characteristic curve (AUC) of 0.75. However, with the addition of baseline sNfL and sGFAP measures, the AUC was improved to 0.79 (P = .0008).
Furthermore, the inclusion of additional follow-up sNfL and sGFAP measurements taken after baseline further improved the model’s AUC (0.82; P = .046).
The addition of the sNfL and sGFAP measures to the clinical models also improved the prediction of disability in MS at 10 years on EDSS (P = .068), as well as prediction of 10-year brain T2 lesion volume (P = .009) and brain parenchymal fraction (P = .04).