1. Dell'Avvento, S, Sotgiu, MA, Manca, S, et al. Epidemiology of multiple sclerosis in the pediatric population of Sardinia, Italy. Eur J Pediatr 2016; 175: 19–29.
Google Scholar |
Crossref |
Medline2. Ghezzi, A, Baroncini, D, Zaffaroni, M, et al. Pediatric versus adult MS: similar or different? Mult Scler Demyelinat Dis 2017; 2: 5.
Google Scholar |
Crossref3. Marrie, RA, O'Mahony, J, Maxwell, C, et al. Canadian Pediatric demyelinating disease network. Incidence and prevalence of MS in children: a population-based study in Ontario, Canada. Neurology 2018; 91: e1579–e1590.
Google Scholar |
Crossref |
Medline4. Banwell, B, Kennedy, J, Sadovnick, D, et al. Incidence of acquired demyelination of the CNS in Canadian children. Neurology 2009; 72: 232–239.
Google Scholar |
Crossref |
Medline |
ISI5. Jeong, A, Oleske, DM, Holman, J. Epidemiology of pediatric-onset multiple sclerosis: a systematic review of the literature. J Child Neurol 2019; 34: 705–712.
Google Scholar |
SAGE Journals |
ISI6. Alroughani, R, Boyko, A. Pediatric multiple sclerosis: a review. BMC Neurol 2018; 18: 27.
Google Scholar |
Crossref |
Medline7. Disanto, G, Magalhaes, S, Handel, AE, et al. HLA-DRB1 confers increased risk of pediatric-onset MS in children with acquired demyelination. Neurology 2011; 76: 781–786.
Google Scholar |
Crossref |
Medline |
ISI8. Gontika, M, Skarlis, C, Artemiadis, A, et al. HLA-DRB1 allele impact on pediatric multiple sclerosis in a hellenic cohort. Mult Scler J Exp Transl Clin 2020; 6: 2055217320908046
Google Scholar |
Medline9. Waubant, E, Mowry, EM, Krupp, L, et al. Common viruses associated with lower pediatric multiple sclerosis risk. Neurology 2011; 76: 1989–1995.
Google Scholar |
Crossref |
Medline |
ISI10. Mikaeloff, Y, Caridade, G, Tardieu, M, et al. Parental smoking at home and the risk of childhood-onset multiple sclerosis in children. Brain 2007; 130: 2589–2595.
Google Scholar |
Crossref |
Medline |
ISI11. Langer-Gould, A, Brara, SM, Beaber, BE, et al. Childhood obesity and risk of pediatric multiple sclerosis and clinically isolated syndrome. Neurology 2013; 80: 548–552.
Google Scholar |
Crossref |
Medline |
ISI12. Gianfrancesco, MA, Stridh, P, Rhead, B, et al. Evidence for a causal relationship between low vitamin D, high BMI, and pediatric-onset MS. Neurology 2017; 88: 1623–1629.
Google Scholar |
Crossref |
Medline |
ISI13. Graves, JS, Chitnis, T, Weinstock-Guttman, B, et al.
Network of pediatric multiple sclerosis centers. Maternal and perinatal exposures Are associated With risk for pediatric-onset multiple sclerosis. Pediatrics 2017; 139: e20162838.
Google Scholar |
Crossref |
Medline14. Brenton, JN, Engel, CE, Sohn, MW, et al. Breastfeeding during infancy Is associated With a lower future risk of pediatric multiple sclerosis. Pediatr Neurol 2017; 77: 67–72.
Google Scholar |
Crossref |
Medline15. Bjørnevik, K, Riise, T, Casetta, I, et al. Sun exposure and multiple sclerosis risk in Norway and Italy: the EnvIMS study. Mult Scler 2014; 20: 1042–1049.
Google Scholar |
SAGE Journals |
ISI16. Islam, T, Gauderman, WJ, Cozen, W, et al. Childhood sun exposure influences risk of multiple sclerosis in monozygotic twins. Neurology 2007; 69: 381–388.
Google Scholar |
Crossref |
Medline |
ISI17. Tremlett, H, Waubant, E. The Gut Microbiota and pediatric multiple sclerosis: recent findings. Neurotherapeutics 2018; 15: 102–108.
Google Scholar |
Crossref |
Medline18. Mar, S, Liang, S, Waltz, M, et al. Several household chemical exposures are associated with pediatric-onset multiple sclerosis. Ann Clin Transl Neurol 2018; 5: 1513–1521.
Google Scholar |
Crossref |
Medline19. Beaton, D, Bombardier, C, Guillemin, F, et al. Recommendations for the cross-cultural adaptation of the DASH & QuickDASH outcome measures. Institute for Work & Health 2002, 2007.
Google Scholar20. Pugliatti, M, Casetta, I, Drulovic, J, et al. A questionnaire for multinational case-control studies of environmental risk factors in multiple sclerosis (EnvIMS-Q). Acta Neurol Scand Suppl 2012; 195: 43–50.
Google Scholar |
Crossref21. Fitzpatrick, R, Davey, C, Buxton, MJ, et al. Evaluating patient based outcome measures for use in clinical trials. Health Technol Assess 1998; 2: i-iv.
Google Scholar22. Bradette-Laplante, M, Carbonneau, É, Provencher, V, et al. Development and validation of a nutrition knowledge questionnaire for a Canadian population. Public Health Nutr 2017; 20: 1184–1192.
Google Scholar |
Crossref |
Medline23. Streiner, DL, Norman, GR. Health measurement scales: a practical guide to their development and use. Oxford: Oxford University Press, 1995.
Google Scholar24. Manns, S, Cramp, F, Lewis, R, et al. A qualitative evaluation of the appropriateness, validity, acceptability, feasibility and interpretability of the Bristol impact of hypermobility (BIoH) questionnaire. Musculoskelet Sci Pract 2018; 38: 69–76.
Google Scholar |
Crossref |
Medline25. Cohen, J . A coefficient of agreement for nominal scales. Educ Psychol Measur 1960; 20: 37–46.
Google Scholar |
SAGE Journals |
ISI26. Landis, JR, Koch, GG. The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159–173.
Google Scholar |
Crossref |
Medline |
ISI27. Magalhaes, S, Wolfson, C. Harmonization: a methodology for advancing research in multiple sclerosis. Acta Neurol Scand 2012; 126: 31–35.
Google Scholar |
Crossref28. Magalhaes, S, Banwell, B, Bar-Or, A, et al. A framework for measurement and harmonization of pediatric multiple sclerosis etiologic research studies: the pediatric MS tool-kit. Mult Scler 2019; 25: 1170–1177.
Google Scholar |
SAGE Journals |
ISI29. Lucas, R, Ponsonby, AL, McMichael, A, et al. Observational analytic studies in multiple sclerosis: controlling bias through study design and conduct. The Australian multicentre study of environment and immune function. Mult Scler 2007; 13: 827–839.
Google Scholar |
SAGE Journals |
ISI30. Magalhaes, S, Pugliatti, M, Casetta, I, et al. The EnvIMS study: design and methodology of an international case-control study of environmental risk factors in multiple sclerosis. Neuroepidemiology 2015; 44: 173–181.
Google Scholar |
Crossref |
Medline |
ISI31. Schilling, LM, Kozak, K, Lundhal, K, et al. Inaccessible novel questionnaires in published medical research: hidden methods, hidden costs. Am J Epidemiol 2006; 164: 1141–1144.
Google Scholar |
Crossref |
Medline |
ISI
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