Proposed cut scores for tests of the Brief International Cognitive Assessment of Multiple Sclerosis (BICAMS)

Meghan Beier, Elizabeth S. Gromisch, Abbey J. Hughes, Kevin N. Alschuler, Renee Madathil, Nancy Chiaravalloti, Frederick W. Foley

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Objective Cognitive impairment (CI) is common in multiple sclerosis (MS). An international consensus committee developed the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) to screen for CI commonly seen in MS. BICAMS cut scores would allow clinicians to, efficiently and effectively, identify patients with possible CI and could aid in clinical decision-making. The aim of this study was to establish cut scores for the neuropsychological tests of the BICAMS. Methods This study utilized data collected from MS Centers in the United States. ROC curve analysis identified cut scores yielding the best balance of sensitivity and specificity. We tested two definitions of impairment: 1.5 and 2 standard deviations (SD) below the normative mean. Results All cut scores yielded excellent or good sensitivity and specificity for identifying impaired cognitive performance. The following cut scores yielded the best balance between sensitivity and specificity: On the Symbol Digit Modalities Test, 44 for 1.5 SD below the mean and 38 for 2 SD below the mean; on the California Verbal Learning Test – II learning trials, 39 (1.5 SD) and 35 (2 SD); and on the Brief Visuospatial Memory Test-Revised learning trials, 17 (1.5 SD) and 16 (2 SD). Conclusions Cut scores can accurately identify cognitive impairment on all subtests of the BICAMS. Use of cut scores may improve the efficiency of screening for cognitive impairment by reducing administrative burden and simplifying interpretation.

Original languageEnglish (US)
Pages (from-to)110-116
Number of pages7
JournalJournal of the Neurological Sciences
StatePublished - Oct 15 2017


  • Assessment
  • Cognition
  • Multiple sclerosis

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology


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