Contributions
Abstract: EP1577
Type: ePoster
Abstract Category: Pathology and pathogenesis of MS - 24 Neuropsychology
Background: Detecting cognitive impairment among patients with multiple sclerosis (MS) is relevant, given the profound impact of cognitive impairment on quality of life. A potential screening tool for cognitive impairment is the Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNQ). However, the interpretability of its patient-reported version (MSNQ-P) is unclear.
Objectives: This study aimed to increase the interpretability of the MSNQ-P by (1) determining the optimal cut-off score to predict cognitive impairment among MS patients, and by (2) investigating which factors predict patient-reported cognitive problems.
Methods: A cohort of 335 MS patients completed the Dutch version of the MSNQ-P and a neuropsychological examination. Patients were classified into cognitively impaired (CI; n = 87), mildly cognitively impaired (MCI; n = 107) and cognitively preserved (CP; n = 141), based on the scores of 88 healthy controls. The optimal cut-off score to detect CI and MCI was considered the value for which [sensitivity + specificity] was highest. Furthermore, backward prediction models were used to determine which factors (cognition, depression, anxiety, fatigue, age, disease duration, education and physical disability) predict the MSNQ-P scores. Patients with scores on each factor were included in these analyses (N = 244).
Results: Preliminary results demonstrated a value of 20 as the optimal cut-off score to detect MS patients with CI (sensitivity = .60, specificity = .57, accuracy = .58), and 12 to detect MS patients with MCI (sensitivity = .82, specificity = .41, accuracy = .59). The MSNQ-P was predicted by the following factors: cognition, depression, anxiety, fatigue, education and physical disability, of which fatigue was the strongest predictor. The model explained 49 percent of the variance on the MSNQ-P.
Conclusion: Due to low psychometric properties, the MSNQ-P cannot solely be used as a screening tool to detect cognitive impairment among MS patients, which is in line with previous studies. Multiple factors influenced patient-reported cognitive problems, including fatigue, depression, anxiety, cognition, education and physical disability.
Disclosure:
I.M. Nauta has received a grant from the Dutch MS Foundation.
L.J. Balk reports no conflict of interests.
J.M. Sonder has received a grant from the Dutch MS Foundation.
B.M.J. Uitdehaag has received personal compensation for consulting from Biogen Idec, Genzyme, Merck Serono, Novartis, Roche en TEVA.
B.A. de Jong has received speaker and consulting fees from Merck-Serono, Biogen, TEVA, Genzyme and Novartis.
Abstract: EP1577
Type: ePoster
Abstract Category: Pathology and pathogenesis of MS - 24 Neuropsychology
Background: Detecting cognitive impairment among patients with multiple sclerosis (MS) is relevant, given the profound impact of cognitive impairment on quality of life. A potential screening tool for cognitive impairment is the Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNQ). However, the interpretability of its patient-reported version (MSNQ-P) is unclear.
Objectives: This study aimed to increase the interpretability of the MSNQ-P by (1) determining the optimal cut-off score to predict cognitive impairment among MS patients, and by (2) investigating which factors predict patient-reported cognitive problems.
Methods: A cohort of 335 MS patients completed the Dutch version of the MSNQ-P and a neuropsychological examination. Patients were classified into cognitively impaired (CI; n = 87), mildly cognitively impaired (MCI; n = 107) and cognitively preserved (CP; n = 141), based on the scores of 88 healthy controls. The optimal cut-off score to detect CI and MCI was considered the value for which [sensitivity + specificity] was highest. Furthermore, backward prediction models were used to determine which factors (cognition, depression, anxiety, fatigue, age, disease duration, education and physical disability) predict the MSNQ-P scores. Patients with scores on each factor were included in these analyses (N = 244).
Results: Preliminary results demonstrated a value of 20 as the optimal cut-off score to detect MS patients with CI (sensitivity = .60, specificity = .57, accuracy = .58), and 12 to detect MS patients with MCI (sensitivity = .82, specificity = .41, accuracy = .59). The MSNQ-P was predicted by the following factors: cognition, depression, anxiety, fatigue, education and physical disability, of which fatigue was the strongest predictor. The model explained 49 percent of the variance on the MSNQ-P.
Conclusion: Due to low psychometric properties, the MSNQ-P cannot solely be used as a screening tool to detect cognitive impairment among MS patients, which is in line with previous studies. Multiple factors influenced patient-reported cognitive problems, including fatigue, depression, anxiety, cognition, education and physical disability.
Disclosure:
I.M. Nauta has received a grant from the Dutch MS Foundation.
L.J. Balk reports no conflict of interests.
J.M. Sonder has received a grant from the Dutch MS Foundation.
B.M.J. Uitdehaag has received personal compensation for consulting from Biogen Idec, Genzyme, Merck Serono, Novartis, Roche en TEVA.
B.A. de Jong has received speaker and consulting fees from Merck-Serono, Biogen, TEVA, Genzyme and Novartis.