Psychometric properties of the Friedreich Ataxia Rating Scale

Christian Rummey; Louise A Corben; Martin B Delatycki; S H Subramony; Khalaf Bushara; Christopher M Gomez; Joseph Chad Hoyle; Grace Yoon; Bernard Ravina; Katherine D Mathews; George Wilmot; Theresa Zesiewicz; Susan Perlman; Jennifer M Farmer; David R Lynch

doi:10.1212/NXG.0000000000000371

Psychometric properties of the Friedreich Ataxia Rating Scale

Neurol Genet. 2019 Oct 29;5(6):371. doi: 10.1212/NXG.0000000000000371. eCollection 2019 Dec.

Authors

Affiliation

¹ Clinical Data Science GmbH (C.R.), Basel, Switzerland; Bruce Lefroy Centre for Genetic Health Research (L.A.C., M.B.D.), Murdoch Children's Research Institute, Parkville, Victoria, Australia; Department of Paediatrics (L.A.C., M.B.D.), University of Melbourne, Parkville, Victoria, Australia; Department of Neurology (S.H.S.), McKnight Brain Institute, Room, Gainesville, FL; University of Minnesota (K.B.); University of Chicago (C.M.G.); Ohio State University (J.C.H.); Divisions of Neurology and Clinical and Metabolic Genetics (G.Y.), Department of Paediatrics, the Hospital for Sick Children, University of Toronto, Ontario, Canada Hospital; University of Rochester (B.R.); University of Iowa (K.D.M.); Emory University (G.W.); University of South Florida (T.Z.); Friedreich's Ataxia Research Alliance (S.P.), Downingtown, PA; and Division of Neurology (D.R.L.), Children's Hospital of Philadelphia.

Abstract

Objective: To investigate the psychometric properties of the Friedreich Ataxia Rating Scale neurologic examination (FARSn) and its subscores, as well as the influence of the modifications resulting in the now widely used modified FARS (mFARS) examination.

Methods: Based on cross-sectional FARS data from the FA-Clinical Outcome Measures cohort, we conducted correlation-based psychometric analyses to investigate the interplay of items and subscores within the FARSn/mFARS constructs.

Results: The results provide support for both the FARSn and the mFARS constructs, as well as individually for their upper limb and lower limb coordination components. The omission of the peripheral nervous system subscore (D) and 2 items of the bulbar subscore (A) in the mFARS strengthens the overall construct compared with the complete FARS.

Conclusions: A correlation-based psychometric analysis of the neurologic FARSn score justifies the overall validity of the scale. In addition, omission of items of limited functional significance as created in the mFARS improves the features of the measures. Such information is crucial to the ongoing application of the mFARS in natural history studies and clinical trials. Additional analyses of longitudinal changes will be necessary to fully ascertain its utility, especially in nonambulant patients.