Document Type : Original Article
- Abolfazl Hosseinnataj 1
- Roya Nikbakht 2
- Seyed Nouraddin Mousavinasab 1
- Sharareh Eskandarieh 3
- Mohammad Ali Sahraian 3
- Seyed Mohammad Baghbanian 4
1 Department of Biostatistics and Epidemiology, School of Health, Mazandaran University of Medical Sciences, Sari, Iran
2 Department of Biostatistics and Epidemiology, School of Health, Golestan University of Medical Sciences, Gorgan, Iran
3 Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
4 Department of Neurology, School of Medicine, Mazandaran University of Medical Sciences, Sari, Iran
Background: It may take a long time to diagnose multiple sclerosis (MS) since the emergence of primary symptoms. This study aimed to use count regression models to compare their fit and to identify factors affecting delay in the diagnosis of MS.
Methods: Data were collected from the Nationwide MS Registry of Iran (NMSRI) for Mazandaran Province, Iran, using census sampling until April 2022. The four models of Poisson regression, negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression, and zero-inflated negative binomial (ZINB) regression were used in this study.
Results: In this study on 2894 patients, 74.0% were women, and 8.5% had a family history of MS. The mean ± standard deviation (SD) of the patients’ age was 34.96 ± 9.41 years, and the mean delay in diagnosis was 12.32 ± 33.26 months, with a median of 0 (Q1-Q3: 0-9). The NB regression model showed the best performance, and factors, including a history of hospitalization and the year of symptom onset, had significant effects on a delayed diagnosis. Besides, the Expanded Disability Status Scale (EDSS) score was significantly different before and after 2017; it was also associated with sex, type of MS, and history of hospitalization.
Conclusion: The mean diagnostic delay and the mean age of MS diagnosis are critical in Mazandaran Province. Patients with MS develop the disease at an early age and are diagnosed with a long delay. The time of symptom onset is a significant factor in the diagnosis of MS, and in recent years, there have been improvements in the diagnostic process.
- Compston A, Coles A. Multiple sclerosis. Lancet 2008; 372(9648): 1502-17.
- Frohman EM, Havrdova E, Lublin F, Barkhof F, Achiron A, Sharief MK, et al. Most patients with multiple sclerosis or a clinically isolated demyelinating syndrome should be treated at the time of diagnosis. Arch Neurol 2006; 63(4): 614-9.
- Gelfand JM. Multiple sclerosis: Diagnosis, differential diagnosis, and clinical presentation. Handb Clin Neurol 2014; 122: 269-90.
- Miller D, Barkhof F, Montalban X, Thompson A, Filippi M. Clinically isolated syndromes suggestive of multiple sclerosis, part I: Natural history, pathogenesis, diagnosis, and prognosis. Lancet Neurol 2005; 4(5): 281-8.
- Ghasemi N, Razavi S, Nikzad E. Multiple sclerosis: Pathogenesis, symptoms, diagnoses and cell-based therapy. Cell J 2017; 19(1): 1-10.
- McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 2001; 50(1): 121-7.
- Poser CM, Paty DW, Scheinberg L, McDonald WI, Davis FA, Ebers GC, et al. New diagnostic criteria for multiple sclerosis: Guidelines for research protocols. Ann Neurol 1983; 13(3): 227-31.
- Steenhof M, Stenager E, Nielsen NM, Kyvik K, Moller S, Hertz JM. Familial multiple sclerosis patients have a shorter delay in diagnosis than sporadic cases. Mult Scler Relat Disord 2019; 32: 97-102.
- Eskandarieh S, Heydarpour P, Elhami SR, Sahraian MA. Prevalence and Incidence of Multiple Sclerosis in Tehran, Iran. Iran J Public Health 2017; 46(5): 699-704.
- Pugliatti M, Riise T, Sotgiu MA, Sotgiu S, Satta WM, Mannu L, et al. Increasing incidence of multiple sclerosis in the province of Sassari, northern Sardinia. Neuroepidemiology 2005; 25(3): 129-34.
- Sloka JS, Pryse-Phillips WE, Stefanelli M. Incidence and prevalence of multiple sclerosis in Newfoundland and Labrador. Can J Neurol Sci 2005; 32(1): 37-42.
- Baghbanian SM, Cheraghmakani H, HabibiSaravi R, Azar A, Ghasemihamedani F. Does the multiple sclerosis (MS) map need to change again? An update of MS prevalence in Mazandaran province of Iran in 2018. BMC Neurol 2020; 20(1): 52.
- Cheraghmakani H, Baghbanian SM, HabibiSaravi R, Azar A, Ghasemihamedani F. Age and sex-adjusted incidence and yearly prevalence of multiple sclerosis (MS) in Mazandaran province, Iran: An 11-years study. PLoS One 2020; 15(7): e0235562.
- Adamec I, Barun B, Gabelic T, Zadro I, Habek M. Delay in the diagnosis of multiple sclerosis in Croatia. Clin Neurol Neurosurg 2013; 115(Suppl 1): S70-S72.
- Noyes K, Weinstock-Guttman B. Impact of diagnosis and early treatment on the course of multiple sclerosis. Am J Manag Care 2013; 19(17 Suppl): s321-s331.
- Ghiasian M, Faryadras M, Mansour M, Khanlarzadeh E, Mazaheri S. Assessment of delayed diagnosis and treatment in multiple sclerosis patients during 1990-2016. Acta Neurol Belg 2021; 121(1): 199-204.
- Mobasheri F, Jaberi AR, Hasanzadeh J, Fararouei M. Multiple sclerosis diagnosis delay and its associated factors among Iranian patients. Clin Neurol Neurosurg 2020; 199: 106278.
- Fernandez O, Fernandez V, Arbizu T, Izquierdo G, Bosca I, Arroyo R, et al. Characteristics of multiple sclerosis at onset and delay of diagnosis and treatment in Spain (the Novo Study). J Neurol 2010; 257(9): 1500-7.
- Aires A, Barros A, Machado C, Fitas D, Cacao G, Pedrosa R, et al. Diagnostic delay of multiple sclerosis in a portuguese population. Acta Med Port 2019; 32(4): 289-94.
- Thormann A, Sorensen PS, Koch-Henriksen N, Laursen B, Magyari M. Comorbidity in multiple sclerosis is associated with diagnostic delays and increased mortality. Neurology 2017; 89(16): 1668-75.
- Shahin S, Eskandarieh S, Moghadasi AN, Razazian N, Baghbanian SM, Ashtari F, et al. Multiple sclerosis national registry system in Iran: Validity and reliability of a minimum data set. Mult Scler Relat Disord 2019; 33: 158-61.
- Chau AMH, Lo ECM, Wong MCM, Chu CH. Interpreting poisson regression models in dental caries studies. Caries Res 2018; 52(4): 339-45.
- Lord D, Park BJ. Negative binomial regression models and estimation methods: Probability density and likelihood functions. Texas A&M University, Korea Transport Institute; 2012.
- Workie MS, Azene AG. Bayesian zero-inflated regression model with application to under-five child mortality. J Big Data 2021; 8(1): 4.
- Cottrell DA, Kremenchutzky M, Rice GP, Hader W, Baskerville J, Ebers GC. The natural history of multiple sclerosis: A geographically based study. 6. Applications to planning and interpretation of clinical therapeutic trials in primary progressive multiple sclerosis. Brain 1999; 122 (Pt 4): 641-7.
- Dahl OP, Aarseth JH, Myhr KM, Nyland H, Midgard R. Multiple sclerosis in Nord-Trondelag County, Norway: A prevalence and incidence study. Acta Neurol Scand 2004; 109(6): 378-84.
- Esbjerg S, Keiding N, Koch-Henriksen N. Reporting delay and corrected incidence of multiple sclerosis. Stat Med 1999; 18(13): 1691-706.
- Kingwell E, Leung AL, Roger E, Duquette P, Rieckmann P, Tremlett H. Factors associated with delay to medical recognition in two Canadian multiple sclerosis cohorts. J Neurol Sci 2010; 292(1-2): 57-62.
- Marrie RA, Cutter G, Tyry T, Hadjimichael O, Campagnolo D, Vollmer T. Changes in the ascertainment of multiple sclerosis. Neurology 2005; 65(7): 1066-70.