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STOCKHOLM – , according to research presented at the annual congress of the European Committee for Treatment and Research in Multiple Sclerosis. The resulting measurement is stable, not highly sensitive to age, and appropriate for research applications. “It could give a clinician an earlier indication of the potential disease course of a patient,” said Ryan Ramanujam, PhD, assistant professor of translational neuroepidemiology at Karolinska Institutet in Stockholm.
Researchers who study MS use various scores to measure disease severity, including the Expanded Disability Status Scale (EDSS) and the MS Severity Scale (MSSS). These scores cannot predict a patient’s future status, however, and they do not remain stable throughout the course of a patient’s disease. Fitting a linear model over a series of scores over time can provide a misleading impression of a patient’s disease progression. “What we need is a metric to give a holistic overview of disease course, regardless of when it’s measured in a patient’s disease progression,” said Dr. Ramanujam. Such a measurement could aid the search for genes that affect MS severity, he added.
Examining disability by patient age
Dr. Ramanujam and colleagues constructed their measure using the ARMSS score, which ranks EDSS score by age instead of by disease duration. The ARMSS score ranges from 0 to 10, and the median value is 5 for all patients at a given age. Investigators can calculate the score using a previously published global matrix of values for ARMSS and MSSS available in the R package ms.sev.
The investigators found that the ARMSS score is slightly superior to the MSSS in detecting small increases in EDSS. One benefit of the ARMSS score, compared with the MSSS, is that it allows investigators to study patients for whom time of disease onset is unknown. The ARMSS score also removes potential systematic bias that might result from a neurologist’s retrospective assignment of date of disease onset, said Dr. Ramanujam.
He and his colleagues used ARMSS to compare patients’ disease course with what is expected for that patient (i.e., an ARMSS that remains stable at 5). They extracted data for 15,831 patients participating in the Swedish MS registry, including age and EDSS score at each neurological visit. Eligible patients had serial EDSS scores for 10 years. Dr. Ramanujam and colleagues included 4,514 patients in their analysis.
Measures at 2 years correlated with those at 10 years
The researchers created what they called the ARMSS integral by calculating the ARMSS score’s change from 5 at each examination (e.g., −0.5 or 1). “The ARMSS integral can be thought of as the cumulative disability that a patient accrues over his or her disease course, relative to the average patient, who had the disease for the same ages,” said Dr. Ramanujam. At 2 years of follow-up and at 10 years of follow-up, the distribution of ARMSS integrals for the study population followed a normal pattern.
Next, the investigators sought to compare patients by standardizing their follow-up time. To do this, they calculated what they called the ARMSS-rate by dividing each patient’s ARMSS integral by the number of years of follow-up. The ARMSS-rate offers a “snapshot of disease severity and progression,” said Dr. Ramanujam. When the researchers compared ARMSS-rates at 2 years and 10 years for each patient, they found that the measure was “extremely stable over time and strongly correlated with future disability.” The correlation improved slightly when the researchers compared ARMSS-rates at 4 years and 10 years.
The investigators then categorized patients based on their ARMSS-rate at 2 years (e.g., 0 to 1, 1 to 2, 2 to 3). When they compared the values in these categories with the median ARMSS-rates for the same individuals over the subsequent 8 years, they found strong group-level correlations.
To analyze correlations on an individual level, Dr. Ramanujam and colleagues examined the ability of different metrics at the time closest to 2 years of follow-up to predict those measured at 10 years. They assigned the value 1 to the most severe quartile of outcomes and the value 0 to all other quartiles. For predictors and outcomes, the investigators examined ARMSS-rate and the integral of progression index, which they calculated using the integral of EDSS. They also included EDSS at 10 years as an outcome for progression index.
For predicting the subsequent 8 years of ARMSS-rates, ARMSS-rate at 2 years had an area under the curve (AUC) of 0.921. When the investigators performed the same analysis using a cohort of patients with MS from British Columbia, Canada, they obtained an AUC of 0.887. Progression index at 2 years had an AUC of 0.61 for predicting the most severe quartile of the next 8 years. Compared with this result, ARMSS integral up to 2 years was slightly better at predicting EDSS at 10 years, said Dr. Ramanujam. The progression index poorly predicted the most severe quartile of EDSS at 10 years.
The main limitation of the ARMSS integral and ARMSS-rate is that they are based on EDSS, he added. The EDSS gives great weight to mobility and largely does not measure cognitive disability. “Future metrics could therefore include additional data such as MRI, Symbol Digit Modalities Test, or neurofilament light levels,” said Dr. Ramanujam. “Also, self-assessment could be one area to improve in the future.”
Dr. Ramanujam had no conflicts of interest to disclose. He receives funding from the MultipleMS Project, which is part of the EU Horizon 2020 Framework.
STOCKHOLM – , according to research presented at the annual congress of the European Committee for Treatment and Research in Multiple Sclerosis. The resulting measurement is stable, not highly sensitive to age, and appropriate for research applications. “It could give a clinician an earlier indication of the potential disease course of a patient,” said Ryan Ramanujam, PhD, assistant professor of translational neuroepidemiology at Karolinska Institutet in Stockholm.
Researchers who study MS use various scores to measure disease severity, including the Expanded Disability Status Scale (EDSS) and the MS Severity Scale (MSSS). These scores cannot predict a patient’s future status, however, and they do not remain stable throughout the course of a patient’s disease. Fitting a linear model over a series of scores over time can provide a misleading impression of a patient’s disease progression. “What we need is a metric to give a holistic overview of disease course, regardless of when it’s measured in a patient’s disease progression,” said Dr. Ramanujam. Such a measurement could aid the search for genes that affect MS severity, he added.
Examining disability by patient age
Dr. Ramanujam and colleagues constructed their measure using the ARMSS score, which ranks EDSS score by age instead of by disease duration. The ARMSS score ranges from 0 to 10, and the median value is 5 for all patients at a given age. Investigators can calculate the score using a previously published global matrix of values for ARMSS and MSSS available in the R package ms.sev.
The investigators found that the ARMSS score is slightly superior to the MSSS in detecting small increases in EDSS. One benefit of the ARMSS score, compared with the MSSS, is that it allows investigators to study patients for whom time of disease onset is unknown. The ARMSS score also removes potential systematic bias that might result from a neurologist’s retrospective assignment of date of disease onset, said Dr. Ramanujam.
He and his colleagues used ARMSS to compare patients’ disease course with what is expected for that patient (i.e., an ARMSS that remains stable at 5). They extracted data for 15,831 patients participating in the Swedish MS registry, including age and EDSS score at each neurological visit. Eligible patients had serial EDSS scores for 10 years. Dr. Ramanujam and colleagues included 4,514 patients in their analysis.
Measures at 2 years correlated with those at 10 years
The researchers created what they called the ARMSS integral by calculating the ARMSS score’s change from 5 at each examination (e.g., −0.5 or 1). “The ARMSS integral can be thought of as the cumulative disability that a patient accrues over his or her disease course, relative to the average patient, who had the disease for the same ages,” said Dr. Ramanujam. At 2 years of follow-up and at 10 years of follow-up, the distribution of ARMSS integrals for the study population followed a normal pattern.
Next, the investigators sought to compare patients by standardizing their follow-up time. To do this, they calculated what they called the ARMSS-rate by dividing each patient’s ARMSS integral by the number of years of follow-up. The ARMSS-rate offers a “snapshot of disease severity and progression,” said Dr. Ramanujam. When the researchers compared ARMSS-rates at 2 years and 10 years for each patient, they found that the measure was “extremely stable over time and strongly correlated with future disability.” The correlation improved slightly when the researchers compared ARMSS-rates at 4 years and 10 years.
The investigators then categorized patients based on their ARMSS-rate at 2 years (e.g., 0 to 1, 1 to 2, 2 to 3). When they compared the values in these categories with the median ARMSS-rates for the same individuals over the subsequent 8 years, they found strong group-level correlations.
To analyze correlations on an individual level, Dr. Ramanujam and colleagues examined the ability of different metrics at the time closest to 2 years of follow-up to predict those measured at 10 years. They assigned the value 1 to the most severe quartile of outcomes and the value 0 to all other quartiles. For predictors and outcomes, the investigators examined ARMSS-rate and the integral of progression index, which they calculated using the integral of EDSS. They also included EDSS at 10 years as an outcome for progression index.
For predicting the subsequent 8 years of ARMSS-rates, ARMSS-rate at 2 years had an area under the curve (AUC) of 0.921. When the investigators performed the same analysis using a cohort of patients with MS from British Columbia, Canada, they obtained an AUC of 0.887. Progression index at 2 years had an AUC of 0.61 for predicting the most severe quartile of the next 8 years. Compared with this result, ARMSS integral up to 2 years was slightly better at predicting EDSS at 10 years, said Dr. Ramanujam. The progression index poorly predicted the most severe quartile of EDSS at 10 years.
The main limitation of the ARMSS integral and ARMSS-rate is that they are based on EDSS, he added. The EDSS gives great weight to mobility and largely does not measure cognitive disability. “Future metrics could therefore include additional data such as MRI, Symbol Digit Modalities Test, or neurofilament light levels,” said Dr. Ramanujam. “Also, self-assessment could be one area to improve in the future.”
Dr. Ramanujam had no conflicts of interest to disclose. He receives funding from the MultipleMS Project, which is part of the EU Horizon 2020 Framework.
STOCKHOLM – , according to research presented at the annual congress of the European Committee for Treatment and Research in Multiple Sclerosis. The resulting measurement is stable, not highly sensitive to age, and appropriate for research applications. “It could give a clinician an earlier indication of the potential disease course of a patient,” said Ryan Ramanujam, PhD, assistant professor of translational neuroepidemiology at Karolinska Institutet in Stockholm.
Researchers who study MS use various scores to measure disease severity, including the Expanded Disability Status Scale (EDSS) and the MS Severity Scale (MSSS). These scores cannot predict a patient’s future status, however, and they do not remain stable throughout the course of a patient’s disease. Fitting a linear model over a series of scores over time can provide a misleading impression of a patient’s disease progression. “What we need is a metric to give a holistic overview of disease course, regardless of when it’s measured in a patient’s disease progression,” said Dr. Ramanujam. Such a measurement could aid the search for genes that affect MS severity, he added.
Examining disability by patient age
Dr. Ramanujam and colleagues constructed their measure using the ARMSS score, which ranks EDSS score by age instead of by disease duration. The ARMSS score ranges from 0 to 10, and the median value is 5 for all patients at a given age. Investigators can calculate the score using a previously published global matrix of values for ARMSS and MSSS available in the R package ms.sev.
The investigators found that the ARMSS score is slightly superior to the MSSS in detecting small increases in EDSS. One benefit of the ARMSS score, compared with the MSSS, is that it allows investigators to study patients for whom time of disease onset is unknown. The ARMSS score also removes potential systematic bias that might result from a neurologist’s retrospective assignment of date of disease onset, said Dr. Ramanujam.
He and his colleagues used ARMSS to compare patients’ disease course with what is expected for that patient (i.e., an ARMSS that remains stable at 5). They extracted data for 15,831 patients participating in the Swedish MS registry, including age and EDSS score at each neurological visit. Eligible patients had serial EDSS scores for 10 years. Dr. Ramanujam and colleagues included 4,514 patients in their analysis.
Measures at 2 years correlated with those at 10 years
The researchers created what they called the ARMSS integral by calculating the ARMSS score’s change from 5 at each examination (e.g., −0.5 or 1). “The ARMSS integral can be thought of as the cumulative disability that a patient accrues over his or her disease course, relative to the average patient, who had the disease for the same ages,” said Dr. Ramanujam. At 2 years of follow-up and at 10 years of follow-up, the distribution of ARMSS integrals for the study population followed a normal pattern.
Next, the investigators sought to compare patients by standardizing their follow-up time. To do this, they calculated what they called the ARMSS-rate by dividing each patient’s ARMSS integral by the number of years of follow-up. The ARMSS-rate offers a “snapshot of disease severity and progression,” said Dr. Ramanujam. When the researchers compared ARMSS-rates at 2 years and 10 years for each patient, they found that the measure was “extremely stable over time and strongly correlated with future disability.” The correlation improved slightly when the researchers compared ARMSS-rates at 4 years and 10 years.
The investigators then categorized patients based on their ARMSS-rate at 2 years (e.g., 0 to 1, 1 to 2, 2 to 3). When they compared the values in these categories with the median ARMSS-rates for the same individuals over the subsequent 8 years, they found strong group-level correlations.
To analyze correlations on an individual level, Dr. Ramanujam and colleagues examined the ability of different metrics at the time closest to 2 years of follow-up to predict those measured at 10 years. They assigned the value 1 to the most severe quartile of outcomes and the value 0 to all other quartiles. For predictors and outcomes, the investigators examined ARMSS-rate and the integral of progression index, which they calculated using the integral of EDSS. They also included EDSS at 10 years as an outcome for progression index.
For predicting the subsequent 8 years of ARMSS-rates, ARMSS-rate at 2 years had an area under the curve (AUC) of 0.921. When the investigators performed the same analysis using a cohort of patients with MS from British Columbia, Canada, they obtained an AUC of 0.887. Progression index at 2 years had an AUC of 0.61 for predicting the most severe quartile of the next 8 years. Compared with this result, ARMSS integral up to 2 years was slightly better at predicting EDSS at 10 years, said Dr. Ramanujam. The progression index poorly predicted the most severe quartile of EDSS at 10 years.
The main limitation of the ARMSS integral and ARMSS-rate is that they are based on EDSS, he added. The EDSS gives great weight to mobility and largely does not measure cognitive disability. “Future metrics could therefore include additional data such as MRI, Symbol Digit Modalities Test, or neurofilament light levels,” said Dr. Ramanujam. “Also, self-assessment could be one area to improve in the future.”
Dr. Ramanujam had no conflicts of interest to disclose. He receives funding from the MultipleMS Project, which is part of the EU Horizon 2020 Framework.
REPORTING FROM ECTRIMS 2019