Serious infections in patients with relapsing and progressive forms of multiple sclerosis: A German claims data study

Open AccessPublished:October 15, 2022DOI:


      • The risk of serious infections in MS patients varies according to MS phenotype.
      • Higher rates of infection were observed in older, male, and progressive individuals.
      • Progressive MS patients had 4-times as many serious infections as those with RRMS.
      • Most SIs were of bacterial origin or impacted respiratory and genitourinary tracts.



      People with multiple sclerosis (pwMS) have a higher risk of serious infection (i.e., infection-related hospitalizations) than people without MS. Few studies have explored the risk of serious infections by MS phenotype in a real-world setting. This retrospective study compared the incidence of serious infections among people with relapse remitting MS (RRMS), primary progressive MS (PPMS), and secondary progressive MS (SPMS).


      Adult pwMS were selected from a German claims database, based on one inpatient or two outpatient diagnoses of MS (ICD-10 G35) by a neurologist from 01/01/2016 to 12/31/2018. Three cohorts (RRMS, PPMS, SPMS) were identified based on codes for MS subtypes included in the German Modification of the ICD-10 system. A fourth cohort of unspecified MS patients combined those with conflicting MS subtype diagnoses and multiple unspecified codes for MS. Serious infections were defined as hospitalizations for which infections were selected as the primary inpatient diagnosis. Infections were identified from a basket of ICD-10 codes distributed across 11 main categories, according to possible pathogen (e.g., other bacterial diseases [A30-A49]) or anatomical location (e.g., urinary tract infection [N39.0]). Multiple infections were counted if an interval of at least 60 days was recorded between episodes. Serious infections were counted from index (i.e., first recorded MS code) until the end of the study period or death. Incidence rates (IRs) were reported per 100 patient years (PY).


      A total of 4,250 pwMS (RRMS: 2,307, PPMS: 282, SPMS: 558, unspecified MS: 1,135) were included; 32 patients progressed from RRMS to SPMS during the follow-up period. Mean (SD) age at baseline was 46.6 (13.6), 61.9 (12.4), and 62.5 (11.8) years in patients with RRMS, PPMS, and SPMS, respectively. Most pwMS were female (RRMS 74.8%, PPMS 62.1%, SPMS 67.4%). Progressive pwMS were more likely to have at least 1 comorbidity (PPMS 87.2%, SPMS 87.5%) compared to those with relapsing MS (61.9%). Most RRMS patients received disease-modifying therapy during follow-up (82.1%), while less than half of progressive MS patients did (PPMS 23.8%, SPMS 31.4%). Over a mean (SD) follow-up period of 3.5 (0.8) years, the IR of serious infections per 100 PY was higher in progressive MS cohorts (PPMS 13.5 [11.3–16.1], SPMS 13.6 [12.0–15.3]) than in the RRMS group (3.4 [3.0–3.7]). Yearly IRs remained stable over time in each cohort. Where anatomical location was specified, respiratory (2.0 per 100 PY) and genitourinary (1.9 per 100 PY) infections were most common. Across all subtypes, higher rates of serious infections were observed in men and older patients.


      Progressive MS, older age and male sex are associated with an increased risk of serious infections. Overall, respiratory and genitourinary infections were the most commonly reported serious infections.


      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Multiple Sclerosis and Related Disorders
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Filippi M.
        • Bar-Or A.
        • Piehl F.
        • et al.
        Multiple sclerosis.
        Nat. Rev. Dis. Primers. 2018; 4 (2018/11/08): 43
        • Marrie R.A.
        • Cohen J.
        • Stuve O.
        • et al.
        A systematic review of the incidence and prevalence of comorbidity in multiple sclerosis: overview.
        Mult. Scler. 2015; 21 (2015/03/01): 263-281
        • Smith K.A.
        • Burkill S.
        • Hiyoshi A.
        • et al.
        Comorbid disease burden among MS patients 1968–2012: a Swedish register–based cohort study.
        Mult. Scler. 2020; 27 (2021/02/01): 268-280
        • Binzer S.
        • McKay K.A.
        • Brenner P.
        • Hillert J.
        • Manouchehrinia A.
        Disability worsening among persons with multiple sclerosis and depression.
        Neurology. 2019; 93: e2216
        • Maric G.
        • Pekmezovic T.
        • Tamas O.
        • et al.
        Impact of comorbidities on the disability progression in multiple sclerosis.
        Acta Neurol. Scand. 2022; 145 (2022/01/01doi:): 24-29
        • Castelo-Branco A.
        • Chiesa F.
        • Conte S.
        • et al.
        Infections in patients with multiple sclerosis: a national cohort study in Sweden.
        Mult. Scler. Relat. Disord. 2020; 45 (07/01)102420
        • Montgomery S.
        • Hillert J.
        • Bahmanyar S.
        Hospital admission due to infections in multiple sclerosis patients.
        J. Neurol. 2013; 20 (2013/08/01doi:): 1153-1160
        • Nelson R.E.
        • Xie Y.
        • DuVall S.L.
        • et al.
        Multiple Sclerosis and Risk of Infection-Related Hospitalization and Death in US Veterans.
        Int. J. MS Care. 2015; 17 (Sep-Oct): 221-230
        • Persson R.
        • Lee S.
        • Ulcickas Yood M.
        • et al.
        Infections in patients diagnosed with multiple sclerosis: a multi-database study.
        Mult. Scler. Relat. Disord. 2020; 41
        • Wijnands J.M.
        • Kingwell E.
        • Zhu F.
        • et al.
        Infection-related health care utilization among people with and without multiple sclerosis.
        Mult. Scler. 2017; 23 (Oct): 1506-1516
        • Harding K.
        • Zhu F.
        • Alotaibi M.
        • Duggan T.
        • Tremlett H.
        • Kingwell E.
        Multiple cause of death analysis in multiple sclerosis.
        Neurology. 2020; 94: e820
        • Kingwell E.
        • Zhu F.
        • Evans C.
        • Duggan T.
        • Oger J.
        • Tremlett H.
        Causes that Contribute to the Excess Mortality Risk in Multiple Sclerosis: a Population-Based Study.
        Neuroepidemiology. 2020; 54: 131-139
        • Luna G.
        • Alping P.
        • Burman J.
        • et al.
        Infection Risks Among Patients With Multiple Sclerosis Treated With Fingolimod, Natalizumab, Rituximab, and Injectable Therapies.
        JAMA Neurol. 2020; 77: 184-191
        • Otero-Romero S.
        • Sánchez-Montalvá A.
        • Vidal-Jordana A.
        Assessing and mitigating risk of infection in patients with multiple sclerosis on disease modifying treatment.
        Expert Rev. Clin. Immunol. 2021; 17 (Mar): 285-300
        • Wijnands J.M.A.
        • Zhu F.
        • Kingwell E.
        • et al.
        Disease-modifying drugs for multiple sclerosis and infection risk: a cohort study.
        J. Neurol. Neurosurg. Psychiatry. 2018; 89: 1050
        • Charlson M.E.
        • Pompei P.
        • Ales K.L.
        • MacKenzie C.R.
        A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
        J. Chronic Dis. 1987; 40: 373-383
        • Brand J.S.
        • Smith K.A.
        • Piehl F.
        • Olsson T.
        • Montgomery S.
        Risk of serious infections in multiple sclerosis patients by disease course and disability status: results from a Swedish register-based study.
        Brain Behav. Immun. Health. 2022; 22 (Jul)100470
        • Maass C.
        • Kuske S.
        • Lessing C.
        • Schrappe M.
        Are administrative data valid when measuring patient safety in hospitals? A comparison of data collection methods using a chart review and administrative data.
        Int. J. Qual. Health Care. 2015; 27: 305-313
        • Jetté N.
        • Quan H.
        • Hemmelgarn B.
        • et al.
        The Development, Evolution, and Modifications of ICD-10: challenges to the International Comparability of Morbidity Data.
        Med. Care. 2010; 48
        • Quan H.
        • Li B.
        • Saunders L.D.
        • et al.
        Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database.
        Health Serv. Res. 2008; 43: 1424-1441
        • Niemann M.
        • Märdian S.
        • Niemann P.
        • et al.
        Transforming the German ICD-10 (ICD-10-GM) into Injury Severity Score (ISS)—Introducing a new method for automated re-coding.
        PLoS ONE. 2021; 16e0257183
        • Phé V.
        • Pakzad M.
        • Curtis C.
        • et al.
        Urinary tract infections in multiple sclerosis.
        Mult. Scler. 2016; 22 (Jun): 855-861
        • Mahadeva A.
        • Tanasescu R.
        • Gran B.
        Urinary tract infections in multiple sclerosis: under-diagnosed and under-treated? A clinical audit at a large University Hospital.
        Am. J. Clin. Exp. Immunol. 2014; 3: 57-67
        • Aiello M.
        • Rampello A.
        • Granella F.
        • et al.
        Cough Efficacy Is Related to the Disability Status in Patients with Multiple Sclerosis.
        Respiration. 2008; 76: 311-316
        • Ribbons K.A.
        • McElduff P.
        • Boz C.
        • et al.
        Male Sex Is Independently Associated with Faster Disability Accumulation in Relapse-Onset MS but Not in Primary Progressive MS.
        PLoS ONE. 2015; 10e0122686
        • Scalfari A.
        • Neuhaus A.
        • Daumer M.
        • Muraro P.A.
        • Ebers G.C.
        Onset of secondary progressive phase and long-term evolution of multiple sclerosis.
        J. Neurol. Neurosurg. Psychiatry. 2014; 85: 67
        • Vaughn C.B.
        • Jakimovski D.
        • Kavak K.S.
        • et al.
        Epidemiology and treatment of multiple sclerosis in elderly populations.
        Nat. Rev. Neurol. 2019; 15 (2019/06/01): 329-342
      1. Holstiege, J., Steffen, A., Goffrier, B., Bätzing, J., 2017. Epidemiology of multiple sclerosis – a population-based, Germany-wide study. Central Research Institute of Ambulatory Health Care in Germany (Zi). Versorgungsatlas Report No. 17/09. Berlin, 2017. DOI: 10.20364/VA-17.09. URL: