Contributions
Abstract: 275
Type: Scientific Session
Abstract Category: Clinical aspects of MS - Clinical assessment tools
Background: The 9-Hole Peg Test (9HPT) is an established neuroperformance measure of upper extremity function in multiple sclerosis (MS). A technology-enabled adaptation of the 9HPT (Manual Dexterity Test, MDT) obtained via iPad® application is part of routine clinical care at our center. Relationship of 9HPT to other disease measures in a real-world setting is incompletely studied.
Objectives: To determine the association between MDT, patient-reported outcomes (PROs), and quantitative MRI metrics in a large clinical cohort.
Methods: iPad®-based neuroperformance tests, PROs, and quantitative MRI data were collected from an MS population at a single site. Brain MRIs obtained within 3 months of a clinical encounter during which MDT and PROs were collected were quantitatively analyzed via a semi-automated method to calculate T2 lesion volume (T2LV), normalized whole brain volume (BV), thalamic volume (TV), and cervical spinal cord area (CA). Spearman correlation coefficients (rho) and linear regression models were used to correlate MDT results with PROs and MRI metrics. Statistical significance was set at p< 0.001 to account for multiple comparisons. For linear regression modeling, MDT was inversely transformed due to non-normality.
Results: The study population comprised 955 patients (mean age 47.6±11.3 years, 71.9% female) who underwent evaluation between December 2015 and December 2017. There were significant correlations between dominant hand MDT and all PROs (p< 0.001), the strongest of which had rho values of Patient Determined Disease Steps (PDDS) (0.52), Neuro-QoL upper (-0.53) and lower (-0.56) extremity function. For MRI metrics, rho values were T2LV (0.36), BV (-0.32), TV (-0.36), and CA (-0.27). After accounting for age, gender, and PDDS score, separate linear regression models indicated that T2LV, BV, TV, and CA were significant predictors of 1/MDT (adjusted R-squared 0.23-0.28, p< 0.001). A model including all 4 MRI metrics showed T2LV and BV to be the strongest MRI predictors (adjusted R-squared 0.28, p< 0.05).
Conclusions: PROs and MRI metrics indicating increased disease severity had moderate correlation with longer times on MDT. Among MRI metrics, T2LV and BV most strongly predicted impaired MDT performance. These results support the use of MDT as an outcome measure in clinical practice and trials.
Disclosure: Laura Baldassari has received personal fees for serving on a scientific advisory board for Teva, and receives funding via a Sylvia Lawry Physician Fellowship Grant through the National Multiple Sclerosis Society (#FP-1606-24540).
Kunio Nakamura has received personal fees for consulting from NeuroRx Research, speaking from Sanofi Genzyme, and license from Biogen. He has received research support from NIH NINDS, NMSS, DOD, Biogen, Sanofi Genzyme, and Novartis.
Marisa McGinley has served on scientific advisory boards for Genzyme and Genentech, and receives funding via a Sylvia Lawry Physician Fellowship Grant through the National Multiple Sclerosis Society (#FP-1506-04742).
Gabrielle Macaron receives fellowship funding from Biogen Idec (#6873-P-FEL).
Brandon Moss is supported by National Multiple Sclerosis Society Institutional Clinician Training Award ICT 0002.
Ebtesam Alshehri: Nothing to disclose
Hong Li: Nothing to disclose
Malory Weber: Nothing to disclose
Robert Bermel has served as a consultant for Biogen, Genzyme, Genentech, and Novartis. He receives research support from Biogen and Genentech.
Daniel Ontaneda has received research support from National Multiple Sclerosis Society, National Institutes of Health, Patient Centered Research Institute, Race to Erase MS Foundation, Genentech, and Genzyme. He has also received consulting fees from Biogen Idec, Genentech/Roche, Genzyme, and Merck.
Jeffrey Cohen has received personal fees for consulting from Adamas, Celgene, Convelo, EMD Serono, Novartis, and PendoPharm; speaking for Mylan; and serving as Co-Editor of Multiple Sclerosis Journal - Experimental, Translational and Clinical.
Abstract: 275
Type: Scientific Session
Abstract Category: Clinical aspects of MS - Clinical assessment tools
Background: The 9-Hole Peg Test (9HPT) is an established neuroperformance measure of upper extremity function in multiple sclerosis (MS). A technology-enabled adaptation of the 9HPT (Manual Dexterity Test, MDT) obtained via iPad® application is part of routine clinical care at our center. Relationship of 9HPT to other disease measures in a real-world setting is incompletely studied.
Objectives: To determine the association between MDT, patient-reported outcomes (PROs), and quantitative MRI metrics in a large clinical cohort.
Methods: iPad®-based neuroperformance tests, PROs, and quantitative MRI data were collected from an MS population at a single site. Brain MRIs obtained within 3 months of a clinical encounter during which MDT and PROs were collected were quantitatively analyzed via a semi-automated method to calculate T2 lesion volume (T2LV), normalized whole brain volume (BV), thalamic volume (TV), and cervical spinal cord area (CA). Spearman correlation coefficients (rho) and linear regression models were used to correlate MDT results with PROs and MRI metrics. Statistical significance was set at p< 0.001 to account for multiple comparisons. For linear regression modeling, MDT was inversely transformed due to non-normality.
Results: The study population comprised 955 patients (mean age 47.6±11.3 years, 71.9% female) who underwent evaluation between December 2015 and December 2017. There were significant correlations between dominant hand MDT and all PROs (p< 0.001), the strongest of which had rho values of Patient Determined Disease Steps (PDDS) (0.52), Neuro-QoL upper (-0.53) and lower (-0.56) extremity function. For MRI metrics, rho values were T2LV (0.36), BV (-0.32), TV (-0.36), and CA (-0.27). After accounting for age, gender, and PDDS score, separate linear regression models indicated that T2LV, BV, TV, and CA were significant predictors of 1/MDT (adjusted R-squared 0.23-0.28, p< 0.001). A model including all 4 MRI metrics showed T2LV and BV to be the strongest MRI predictors (adjusted R-squared 0.28, p< 0.05).
Conclusions: PROs and MRI metrics indicating increased disease severity had moderate correlation with longer times on MDT. Among MRI metrics, T2LV and BV most strongly predicted impaired MDT performance. These results support the use of MDT as an outcome measure in clinical practice and trials.
Disclosure: Laura Baldassari has received personal fees for serving on a scientific advisory board for Teva, and receives funding via a Sylvia Lawry Physician Fellowship Grant through the National Multiple Sclerosis Society (#FP-1606-24540).
Kunio Nakamura has received personal fees for consulting from NeuroRx Research, speaking from Sanofi Genzyme, and license from Biogen. He has received research support from NIH NINDS, NMSS, DOD, Biogen, Sanofi Genzyme, and Novartis.
Marisa McGinley has served on scientific advisory boards for Genzyme and Genentech, and receives funding via a Sylvia Lawry Physician Fellowship Grant through the National Multiple Sclerosis Society (#FP-1506-04742).
Gabrielle Macaron receives fellowship funding from Biogen Idec (#6873-P-FEL).
Brandon Moss is supported by National Multiple Sclerosis Society Institutional Clinician Training Award ICT 0002.
Ebtesam Alshehri: Nothing to disclose
Hong Li: Nothing to disclose
Malory Weber: Nothing to disclose
Robert Bermel has served as a consultant for Biogen, Genzyme, Genentech, and Novartis. He receives research support from Biogen and Genentech.
Daniel Ontaneda has received research support from National Multiple Sclerosis Society, National Institutes of Health, Patient Centered Research Institute, Race to Erase MS Foundation, Genentech, and Genzyme. He has also received consulting fees from Biogen Idec, Genentech/Roche, Genzyme, and Merck.
Jeffrey Cohen has received personal fees for consulting from Adamas, Celgene, Convelo, EMD Serono, Novartis, and PendoPharm; speaking for Mylan; and serving as Co-Editor of Multiple Sclerosis Journal - Experimental, Translational and Clinical.