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Brief international cognitive assessment for multiple sclerosis (BICAMS) cut-off scores for detecting cognitive impairment in multiple sclerosis.
Multiple Sclerosis and related Disorders 2021 January 13
BACKGROUND: Cognitive impairment (CI) affects 35-65% of multiple sclerosis (MS) patients. The Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) has been proposed as a highly feasible and cost-effective tool for cognitive impairment (CI) screening in MS. The tool yields scores that should, ideally, readily convey patients' cognitive status to the clinicians.
METHODS: To this aim, this study sought for cut-off scores of the three BICAMS test in a sample of 960 MS patients. We used three definitions for CI: 1.5, 1,65 and 2 standard deviations below the mean. Receiver operating characteristic (ROC) statistics helped us determine the capacity of BICAMS to diagnose CI. Optimal cut-offs were determined by the delta distance. Positive and negative predictive values, along with overall accuracy were also calculated.
RESULTS: Symbol Digit Modalities Test (SDMT) and California Verbal Learning Test-II (CVLT-II) showed a diagnostic accuracy ranging from 74.6 to 77.4%, across the three CI definitions. The accuracy of Brief Visuospatial Memory Test-Revised (BVMT-R) was over 88%. SDMT had a balanced sensitivity, while CVLT-II and BVMT-R had higher specificities than sensitivities at detecting CI. More specifically, BVMT-R showed 100% specificity for all CI definitions. Raw cut-off scores for BICAMS tests are also provided within the manuscript, along with the diagnostic calculations.
CONCLUSIONS: In this study, we confirmed that BICAMS is a good screening tool for CI and that simple cut-offs can be used in the everyday neurological practice.
METHODS: To this aim, this study sought for cut-off scores of the three BICAMS test in a sample of 960 MS patients. We used three definitions for CI: 1.5, 1,65 and 2 standard deviations below the mean. Receiver operating characteristic (ROC) statistics helped us determine the capacity of BICAMS to diagnose CI. Optimal cut-offs were determined by the delta distance. Positive and negative predictive values, along with overall accuracy were also calculated.
RESULTS: Symbol Digit Modalities Test (SDMT) and California Verbal Learning Test-II (CVLT-II) showed a diagnostic accuracy ranging from 74.6 to 77.4%, across the three CI definitions. The accuracy of Brief Visuospatial Memory Test-Revised (BVMT-R) was over 88%. SDMT had a balanced sensitivity, while CVLT-II and BVMT-R had higher specificities than sensitivities at detecting CI. More specifically, BVMT-R showed 100% specificity for all CI definitions. Raw cut-off scores for BICAMS tests are also provided within the manuscript, along with the diagnostic calculations.
CONCLUSIONS: In this study, we confirmed that BICAMS is a good screening tool for CI and that simple cut-offs can be used in the everyday neurological practice.
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