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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).
Better together?
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).
Relapse predictor?
In the second study, Dr. Bose and colleagues evaluated the role of the two serum measures in predicting relapse after disease-modifying therapy (DMT) discontinuation. That study included 42 patients who discontinued DMT treatment after having been disease-activity free for 2 years while on the drugs. They were compared with 36 patients who had similar characteristics and had continued DMT treatment.
All patients (mean age, 44.5 years) had a mean of 7.4 years since prior disease activity.
Increases in sNfL following DMT discontinuation, but not before, were associated with a significantly greater risk for clinical disease worsening at a mean follow-up of 7.5 years (HR, 9.4; P = .007). Change in sGFAP was associated with new MRI lesions (HR, 8.3; P = .039), compared with no changes.
“The crux of this study” was that patients with increased biomarker levels after stopping DMTs “were at a significantly higher risk for disease activity in the future compared to those whose biomarker levels remained stable,” Dr. Bose noted.
“We think this finding, if replicated in another cohort, has the potential to be included in guidelines regarding stopping DMT in patients with MS,” he added.
Clinically useful?
Jeffrey Cohen, MD, current president of ACTRIMS, said the first study supports mounting evidence on how sNfL and sGFAP at onset can predict future disease and have the potential to improve current predictive models.
“Combining clinical, MRI, and serum biomarkers into a single model works better than any of the three factors individually,” said Dr. Cohen, who is director of the Mellen Center for MS Treatment and Research and professor of neurology at the Cleveland Clinic.
“For the clinician, this information may help with treatment selection,” he added.
Dr. Cohen noted that the suggestion that the biomarkers could also be helpful in predicting relapse after discontinuation is of importance.
“Increasingly, we are considering this issue in the clinical setting,” he said. However, he also noted some caveats.
“Interpretation of the results of the study is not straightforward, illustrating the complexity of the issue,” Dr. Cohen said. “One issue is that the patients in the study were relatively young, with an average age of 45, which is not a group in which we typically would consider stopping therapy.”
Dr. Bose has received a postdoctoral fellowship grant from the Multiple Sclerosis Society of Canada. Dr. Cohen reports having received personal compensation for consulting for Biogen, Bristol-Myers Squibb, Convelo, Genentech, Janssen, NervGen, Novartis, and PSI; speaking for H3 Communications; and serving as an editor of the Multiple Sclerosis Journal.
A version of this article first appeared on Medscape.com.
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).
Better together?
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).
Relapse predictor?
In the second study, Dr. Bose and colleagues evaluated the role of the two serum measures in predicting relapse after disease-modifying therapy (DMT) discontinuation. That study included 42 patients who discontinued DMT treatment after having been disease-activity free for 2 years while on the drugs. They were compared with 36 patients who had similar characteristics and had continued DMT treatment.
All patients (mean age, 44.5 years) had a mean of 7.4 years since prior disease activity.
Increases in sNfL following DMT discontinuation, but not before, were associated with a significantly greater risk for clinical disease worsening at a mean follow-up of 7.5 years (HR, 9.4; P = .007). Change in sGFAP was associated with new MRI lesions (HR, 8.3; P = .039), compared with no changes.
“The crux of this study” was that patients with increased biomarker levels after stopping DMTs “were at a significantly higher risk for disease activity in the future compared to those whose biomarker levels remained stable,” Dr. Bose noted.
“We think this finding, if replicated in another cohort, has the potential to be included in guidelines regarding stopping DMT in patients with MS,” he added.
Clinically useful?
Jeffrey Cohen, MD, current president of ACTRIMS, said the first study supports mounting evidence on how sNfL and sGFAP at onset can predict future disease and have the potential to improve current predictive models.
“Combining clinical, MRI, and serum biomarkers into a single model works better than any of the three factors individually,” said Dr. Cohen, who is director of the Mellen Center for MS Treatment and Research and professor of neurology at the Cleveland Clinic.
“For the clinician, this information may help with treatment selection,” he added.
Dr. Cohen noted that the suggestion that the biomarkers could also be helpful in predicting relapse after discontinuation is of importance.
“Increasingly, we are considering this issue in the clinical setting,” he said. However, he also noted some caveats.
“Interpretation of the results of the study is not straightforward, illustrating the complexity of the issue,” Dr. Cohen said. “One issue is that the patients in the study were relatively young, with an average age of 45, which is not a group in which we typically would consider stopping therapy.”
Dr. Bose has received a postdoctoral fellowship grant from the Multiple Sclerosis Society of Canada. Dr. Cohen reports having received personal compensation for consulting for Biogen, Bristol-Myers Squibb, Convelo, Genentech, Janssen, NervGen, Novartis, and PSI; speaking for H3 Communications; and serving as an editor of the Multiple Sclerosis Journal.
A version of this article first appeared on Medscape.com.
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).
Better together?
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).
Relapse predictor?
In the second study, Dr. Bose and colleagues evaluated the role of the two serum measures in predicting relapse after disease-modifying therapy (DMT) discontinuation. That study included 42 patients who discontinued DMT treatment after having been disease-activity free for 2 years while on the drugs. They were compared with 36 patients who had similar characteristics and had continued DMT treatment.
All patients (mean age, 44.5 years) had a mean of 7.4 years since prior disease activity.
Increases in sNfL following DMT discontinuation, but not before, were associated with a significantly greater risk for clinical disease worsening at a mean follow-up of 7.5 years (HR, 9.4; P = .007). Change in sGFAP was associated with new MRI lesions (HR, 8.3; P = .039), compared with no changes.
“The crux of this study” was that patients with increased biomarker levels after stopping DMTs “were at a significantly higher risk for disease activity in the future compared to those whose biomarker levels remained stable,” Dr. Bose noted.
“We think this finding, if replicated in another cohort, has the potential to be included in guidelines regarding stopping DMT in patients with MS,” he added.
Clinically useful?
Jeffrey Cohen, MD, current president of ACTRIMS, said the first study supports mounting evidence on how sNfL and sGFAP at onset can predict future disease and have the potential to improve current predictive models.
“Combining clinical, MRI, and serum biomarkers into a single model works better than any of the three factors individually,” said Dr. Cohen, who is director of the Mellen Center for MS Treatment and Research and professor of neurology at the Cleveland Clinic.
“For the clinician, this information may help with treatment selection,” he added.
Dr. Cohen noted that the suggestion that the biomarkers could also be helpful in predicting relapse after discontinuation is of importance.
“Increasingly, we are considering this issue in the clinical setting,” he said. However, he also noted some caveats.
“Interpretation of the results of the study is not straightforward, illustrating the complexity of the issue,” Dr. Cohen said. “One issue is that the patients in the study were relatively young, with an average age of 45, which is not a group in which we typically would consider stopping therapy.”
Dr. Bose has received a postdoctoral fellowship grant from the Multiple Sclerosis Society of Canada. Dr. Cohen reports having received personal compensation for consulting for Biogen, Bristol-Myers Squibb, Convelo, Genentech, Janssen, NervGen, Novartis, and PSI; speaking for H3 Communications; and serving as an editor of the Multiple Sclerosis Journal.
A version of this article first appeared on Medscape.com.
Reporting from ACTRIMS Forumn 2022