Elaine Cristina Miglorini1,2, Victor Henrique Ignácio de Souza2,3, Camila Maria de Oliveira1,2, Gabriela Bolzan2,4, Maria Luiza Saraiva-Pereira2,4,5,6, Vanessa Bielefeldt Leotti7,8, Laura Bannach Jardim9,10,11,12,13,14. 1. Programa de Pós-Graduação em Ciências Médicas, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2400, Porto Alegre, 90035-003, Brazil. 2. Centros de Pesquisa Clínica e Experimental, Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos, 2350, Porto Alegre, 90035-003, Brazil. 3. Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2400, Porto Alegre, 90035-003, Brazil. 4. Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, Building 43312, Porto Alegre, 91501-970, Brazil. 5. Departamento de Bioquímica, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2600-Prédio Anexo, 90.035-003, Porto Alegre, Brazil. 6. Serviço de Genética Médica, Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos, 2350, Porto Alegre, 90035-003, Brazil. 7. Departamento de Estatística, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, Building 43-111, Porto Alegre, 91501-900, Brazil. 8. Grupo de Pesquisa e Pós-Graduação, Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos, 2350, Porto Alegre, 90035-003, Brazil. 9. Programa de Pós-Graduação em Ciências Médicas, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2400, Porto Alegre, 90035-003, Brazil. ljardim@hcpa.edu.br. 10. Centros de Pesquisa Clínica e Experimental, Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos, 2350, Porto Alegre, 90035-003, Brazil. ljardim@hcpa.edu.br. 11. Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos, 2400, Porto Alegre, 90035-003, Brazil. ljardim@hcpa.edu.br. 12. Programa de Pós-Graduação em Genética e Biologia Molecular, Universidade Federal do Rio Grande do Sul, Av. Bento Gonçalves, 9500, Building 43312, Porto Alegre, 91501-970, Brazil. ljardim@hcpa.edu.br. 13. Serviço de Genética Médica, Hospital de Clínicas de Porto Alegre, Rua Ramiro Barcelos, 2350, Porto Alegre, 90035-003, Brazil. ljardim@hcpa.edu.br. 14. Departamento de Medicina Interna, Universidade Federal do Rio Grande do Sul, Rua Ramiro Barcelos 2350, Porto Alegre, 90035-003, Brazil. ljardim@hcpa.edu.br.
The COVID-19
pandemic disrupted countless human activities since 2020. In most places, face-to-face visits for research projects were interrupted for months; some studies were adapted to use remote methods. One challenge was to find an instrument prone to remote application that could detect a reduction in functional status among carriers of spinocerebellar ataxias. The most used criterion is the cutoff of 3 points in the Scale for Assessment and Rating of Ataxia (SARA) [1]. The remote SARAhome version was recently proposed [2], but the technology needed was not available in research centers like ours yet.As an alternative, we studied the Friedreich Ataxia Rating Scale/activities of daily living (FARS-ADL) [3], a patient-reported outcome designed to evaluate limitations in functional status of ataxic subjects.We aimed to test if FARS-ADL could distinguish subjects with SARA score > = 3 (ataxics) among persons belonging to families with spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD). Confirmed carriers and their relatives at 50% risk were evaluated during July and August 2021. FARS-ADL was administered as a structured interview by telephone; SARA and DNA samples were collected simultaneously in our institution within 15 days after FARS-ADL. Participants at 50% risk and examiners were kept blinded to their genetic results.Nineteen ataxic (with SARA > = 3) and 13 pre-ataxic (with SARA < 3) SCA3/MJD carriers, and 13 related controls were included, with median (IQR) ages of 44.01 (19.00), 29.00 (8.00), and 40.00 (13.75) years. Ataxic and pre-ataxic subjects carried 75 (4) and 75 (4) CAG repeats in their expanded alleles; age at onset of gait ataxia was 43 (19) in ataxics. Two alternatives were used to define FARS-ADL cutoffs between ataxic and pre-ataxic. According to a maximum-accuracy cut-point, FARS-ADL values less than 4 detected persons with SARA < 3, while values greater than 8 detected persons with SARA > = 3 (Fig. 1A). According to the ROC curve and Youden’s index, a FARS-ADL score larger than 4 points detected presence of SARA > = 3 (Fig. 1B), with 7.7% and 5.6% of false-positives and false-negatives, and with sensitivity and specificity of 0.94 and 0.92.
Fig. 1
A Correlation between the Scale for Assessment and Rating of Ataxia (SARA) and Friedreich Ataxia Rating Scale-activities of daily living (FARS-ADL) scores. Circles and crosses represent carriers of ATXN3 expansions and non-carriers (controls). The grey zone represents the limits outside the accuracy maximization model, while the hatched line represents the cutoff according to the ROC curve. B The receiver operating characteristic (ROC) curve of FARS-ADL as predictor of SARA scores equal or larger than 3 points
A Correlation between the Scale for Assessment and Rating of Ataxia (SARA) and Friedreich Ataxia Rating Scale-activities of daily living (FARS-ADL) scores. Circles and crosses represent carriers of ATXN3 expansions and non-carriers (controls). The grey zone represents the limits outside the accuracy maximization model, while the hatched line represents the cutoff according to the ROC curve. B The receiver operating characteristic (ROC) curve of FARS-ADL as predictor of SARA scores equal or larger than 3 pointsFormer reports on simultaneous FARS-ADL and SARA data were obtained in Friedreich's Ataxia (FRDA) subjects with SARA larger than 3 [4, 5], where 57 out of 594 subjects showed FARS-ADL scores of 4 or less (Reetz, personal communication). This would be equivalent to 9.6% false-negatives if FARS-ADL larger than 4 was used to classify FRDA subjects as ataxic.Remote evaluations of persons at risk for ataxia might continue to be a demand for the near future. FARS-ADL is an easy to perform questionnaire through online interfaces or telephone calls. FARS-ADL does not detect ataxia, but in this population at risk for ataxia, it might help investigators to assume which subjects are already ataxic in the temporary impossibility of using the gold-standard method SARA. The specificity was high in SCA3/MJD, but not sufficient for FRDA. Therefore, it will be important to study more pre-ataxic and ataxic carriers to confirm the usefulness of FARS-ADL as a remote predictor of the symptomatic/ataxic status in SCA3/MJD and in other forms of ataxia.
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Authors: Kathrin Reetz; Imis Dogan; Ralf-Dieter Hilgers; Paola Giunti; Michael H Parkinson; Caterina Mariotti; Lorenzo Nanetti; Alexandra Durr; Claire Ewenczyk; Sylvia Boesch; Wolfgang Nachbauer; Thomas Klopstock; Claudia Stendel; Francisco Javier Rodríguez de Rivera Garrido; Christian Rummey; Ludger Schöls; Stefanie N Hayer; Thomas Klockgether; Ilaria Giordano; Claire Didszun; Myriam Rai; Massimo Pandolfo; Jörg B Schulz Journal: Lancet Neurol Date: 2021-03-23 Impact factor: 44.182