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Adverse events in MS patients fulfilling or not inclusion criteria of the respective clinical trial – The problem of generalizability

Open AccessPublished:November 19, 2022DOI:https://doi.org/10.1016/j.msard.2022.104422

      Highlights

      • Across all analysed drugs, 27.2% of the patients would have been eligible for inclusion into a phase III clinical trial if all five predefined criteria were applied.
      • 61.5% of patiets would have been included into the respective clinical trial if the selection criterion “relapse” was dropped.
      • A low transferability of phase III clinical trial criteria, to patients in routine care with the exception of age, does not imply a higher risk with regard to adverse and serious adverse events.

      Abstract

      Background

      The aim of this study was to evaluate how many MS patients treated with an approved DMD in routine care would have fulfilled the inclusion and exclusion criteria of phase III clinical trial and would therefore be eligible for the respective drug trial. Further, adverse events and disease progression for these patients were compared.

      Methods

      A comparison of patients fulfilling phase III clinical trial inclusion and exclusion criteria and those who do not with regard to sociodemographic and clinical characteristics, adverse events and disease progression. Database was the REGIMS register, a national, prospective, observational, clinical multicentre registry. 1248 MS Patients were included.

      Results

      27.2% patients would have been eligible for inclusion into a phase III clinical trial of their indication. Patients who did not meet the criterion age are more likely to have a serious adverse event (SAE), whereas patients who did not fulfil the criterion relapse had a significant lower occurrence of an adverse event (AE). Non-fulfilment of other inclusion criteria (EDSS Score; medication history and MS type) did not show any significant differences in drug safety variables, AE and SAE.

      Conclusion

      Our results suggest that a low transferability of phase III clinical trial criteria, to patients in routine care with the exception of age, does not imply a higher risk with regard to adverse and serious adverse events.

      Keywords

      1. Introduction

      Multiple sclerosis is a chronic autoimmune disease of the central nervous system. The disease is characterised by inflammation, demyelination and axonal loss which occur in early stages. The clinical course is heterogeneous, but in most patients the initial stages are described by reversible episodes of neurological dysfunction followed by irreversible clinical and cognitive deficiencies (
      • Filippi M.
      • Bar-Or A.
      • Piehl F.
      • et al.
      Multiple sclerosis.
      ).
      MS patients are treated with disease modifying drugs (DMDs) in order to prevent relapses and progression of the disease. The MS drug market is rapidly growing with several new medications approved annually thus, rapidly increasing treatment options for patients with active MS. MS is therefore an example for a dynamic market facing known challenges in pharmacovigilance. Among the latter is the question of generalizability of results of the initial phase III clinical trials to all later treated patients with the disease, which is subject of controversial discussions between clinical trialists and authorities approving new drugs since a long time. Generalizability includes the question of effectiveness of a new drug in patients who did not fulfil inclusion criteria, e.g. because of age, comorbidities or specific disease characteristics, but get treated with this drug after its approval. It also relates to the long-term safety of a new drug, especially in dynamic markets where the treatment experience for many of the newly approved drugs is limited.
      Due to the high efficacy and known potential risks of biologicals in the MS therapy a long term evaluation of newly approved DMDs is of crucial importance in terms of drug safety. Phase III studies provide information on efficacy and safety for many common adverse events and thus are essential for drug approval. (
      • Friedman L.M.
      • Furberg C.D.
      • DeMets D.L
      Fundamentals of Clinical Trials.
      ) Nevertheless, phase III studies cannot reliably detect rare adverse events. Furthermore, drug safety analysed in phase III clinical trials with strict in- and exclusion criteria might not adequately represent the safety profile in the widespread clinical use after drug approval. Considering the setting of phase III clinical trials the transfer of results into clinical routine might be restricted causing a lack of generalizability. (
      • Fischer L.
      • Knaebel H.P.
      • Golcher H.
      • et al.
      To whom do the results of the multicenter, randomized, controlled INSECT trial (ISRCTN 24023541) apply? - assessment of external validity.
      ;
      • He Z.
      • Tang X.
      • Yang X.
      • et al.
      Clinical trial generalizability assessment in the big data era: a review.
      ) Therefore, post marketing studies such as phase IV studies, post admission surveillance studies and registries are essential for a holistic drug life cycle insuring additional information in terms of safety and efficacy.
      Natalizumab was the first monoclonal antibody that was approved in 2006 for MS therapy by the European Commission. (

      European Medicines Agency - Committee for Medicinal Products for Human. Tysabri - Authorisation details, https://www.ema.europa.eu/en/medicines/human/EPAR/tysabri (accessed 28. 06.).

      ) Another landmark in DMD development was, fingolimod (2011), the first oral MS medication. Alemtuzumab (2013) and ocrelizumab (2018) are further monoclonal antibodies which have been approved for MS, with ocrelizumab having an approval for the treatment of both PPMS and the more common RRMS phenotype. (
      • Tintore M.
      • Vidal-Jordana A.
      • Sastre-Garriga J.
      Treatment of multiple sclerosis - success from bench to bedside.
      ) Recently approved (2020) MS DMDs are ozanimod and siponimod. (
      • Jalkh G.
      • Abi Nahed R.
      • Macaron G.
      • et al.
      Safety of newer disease modifying therapies in multiple sclerosis.
      ) Considering the risk of severe adverse events (SAE) in patients using DMDs, drug monitoring is a central component of response and safety. (
      • Simbrich A.
      • Thibaut J.
      • Khil L.
      • et al.
      Drug-use patterns and severe adverse events with disease-modifying drugs in patients with multiple sclerosis: a cohort study based on German claims data.
      ) Daclizumab is a MS DMD that was withdrawn from the market in 2018, after reports of autoimmune encephalitis in Europe. (

      European medicines agency - CHMP. Zinbryta: daclizumab.

      ;
      • Biogen M.E.D.I.A.
      • Abbvie M.E.D.I.A
      Biogen and AbbVie Announce the Voluntary Worldwide Withdrawal of Marketing Authorizations For ZINBRYTA® (daclizumab) For Relapsing Multiple Sclerosis.
      ) Cladribine has been associated with thrombocytopenia, leukopenia, and anaemia possibly as a result of higher doses administration. (
      • Beutler E.
      • Koziol J.A.
      • McMillan R.
      • et al.
      Marrow suppression produced by repeated doses of cladribine.
      ) Fingolimod and natalizumab have been associated with progressive multifocal leukoencephalopathy (PML). (
      • Berger J.R.
      • Cree B.A.
      • Greenberg B.
      • et al.
      Progressive multifocal leukoencephalopathy after fingolimod treatment.
      ;
      • Bloomgren G.
      • Richman S.
      • Hotermans C.
      • et al.
      Risk of natalizumab-associated progressive multifocal leukoencephalopathy.
      ) MS registries that have been implemented in several countries play an important role in drug monitoring and the implementation of drug safety through long-term assessment of the frequency of potential rare side effects. (
      • Flachenecker P.
      • Stuke K.
      National MS registries.
      ;
      • Willis C.D.
      • McNeil J.J.
      • Cameron P.A.
      • et al.
      Monitoring drug safety with registries: useful components of postmarketing pharmacovigilance systems.
      )
      The aim of our study was to evaluate how many MS patients treated with an approved DMD in routine clinical care would have fulfilled inclusion and exclusion criteria of phase III clinical trial and would therefore been eligible for the respective drug trial. A further goal was to compare patients fulfilling inclusion and exclusion criteria and those who do not with regard to sociodemographic and clinical characteristics, adverse events and disease progression.

      2. Methods

      2.1 Ethics

      The study was approved by the local Ethics Committee of the Medical Chamber Westphalia-Lippe and the School of Medicine University of Muenster, Germany (Approval number: 2013–308-b-S). Further, the study was approved by the Ethics Commission of the School of Medicine University of Bochum (Approval number: 4588–13). All patients gave written informed consent.

      2.2 Data source and study population

      REGIMS is a German immunotherapy registry and part of the disease-orientated Competence Network Multiple Sclerosis (Krankheitsbezogenes Kompetenznetz Multiple Sklerose [KKNMS]). REGIMS primary goal is to record the frequency, type, characteristics and effects of adverse events in current and new immunotherapeutic DMDs used in routine clinical care of MS patients. REGIMS is a national, prospective, observational (i.e., non-interventional), clinical multicentre registry. Further REGIMS details have been described elsewhere. (
      • Simbrich A.
      • Thibaut J.
      • Khil L.
      • et al.
      chances and challenges of registry-based pharmacovigilance in multiple sclerosis: lessons learnt from the implementation of the multicenter REGIMS Registry.
      )
      Included in this analysis were patients enroled in REGIMS between Oct. 2013 and Sept. 2020 who started treatment with one of the following DMDs: ocrelizumab, cladribine, daclizumab, dimethyl fumarate, teriflunomide, alemtuzumab, fingolimod, natalizumab, mitoxantrone, glatiramer acetate, peginterferon β−1a, interferon β−1a and interferon β−1b. 1748 REGIMS patients receiving a DMD were initially included, but analysis was restricted to the 1660 patients who had a relapsing MS type, due to the small number of patients with PPMS. Patients with incomplete data on DMD start, EDSS (Expanded Disability Status Scale) score, clinical course, relapse data and implausible medication history data were additionally excluded, leaving 1493 baseline patients. 1248 patients with a baseline and follow up visits were used for the analysis (Supplement Table S1).

      2.3 Data analysis

      Post approval compliance with selected phase III clinical trial criteria was based on the ‘Summary of Product Characteristics’ for each DMD, published by the European Medicines Agency and the respective phase III clinical trial providing information on efficacy and safety. A complete summary of inclusion and exclusion criteria applied in this study were published elsewhere. (
      • Jalusic K.O.
      • Ellenberger D.
      • Rommer P.
      • et al.
      Effect of applying inclusion and exclusion criteria of phase III clinical trials to multiple sclerosis patients in routine clinical care.
      ) Mostly, patients were included if they were between 18 and 55 years old; had a RRMS clinical course with at least 2 relapses within the last 2 years prior to randomization or 1 relapse in the year before and/or a MRI scan of the brain showing abnormalities consistent with multiple sclerosis (e. g. at least one gadolinium-enhancing lesion 0 to 6 weeks to randomization). Given that the exact number of T2 lesions is not collected in REGIMS, magnetic resonance imaging (MRI) was not taken into consideration. A further selection criterion was an EDSS Score between 0.0 und 5.0 (Supplement Table S2). Medication history was a common exclusion criterion in clinical trials (Supplement Table S3). The assessment of in- and exclusion criteria was done for patients with complete baseline data and follow up visits. In the first step the proportion of patients eligible to clinical trials across different DMDs was analysed. In the next step the percentage of patients fulfilling each criterion of the phase III clinical trial was described for every DMD separately. Finally, patients who did not meet all in- and exclusion criteria for a certain drug were compared with those who did in term of clinical and sociodemographic characteristics.
      Outcome assessment was based on patient's last follow up visit. Analysed was a follow-up period of up to 30 months after baseline. For the outcome analysis the following items were used: adverse event (AE), serious adverse event (SAE), relapse /disease progression, DMD change, EDSS. Documentation was done in an Electronic Data Capture (EADC) system by physicians in the study centres. Safety data (AE) in REGIMS are reported irrespective of causality. SAEs are instantly delivered to the registry and reported to the holder of marketing authorisation. Relapses are not documented as AEs. Change in EDSS score was defined as a difference between the baseline and follow up EDSS score of at least 0.5 points.
      For categorical, between group comparisons of eligible and ineligible patients the chi-square tests were used and for continuous variables Students t-test. In order to investigate the difference in drug safety data (AE and SAE) between patient's who did not and those who fulfilled all five predefined in- and exclusion criteria, logistic regression models were applied. A p-value of <0.05 was considered statistically significant. Analyses were performed using STATA/SE 13.0.

      3. Results

      3.1 Demographic and clinical characteristics

      In total 1248 patents with at least one follow-up visit were analysed in this study. Mean time to follow up was 6.7 months (standard deviation [SD] = 3.1). Supplement Table S1 describes the flowchart of inclusions into the analysis. Demographic and clinical characteristics are summarised in Table 1. The majority of the patients were females (70.1%), mean age was 37.6 (SD = 11.1) with a range from 16 to 75 years. The mean number of relapses 24 months within baseline was 1.5 (SD: 1.6). 5.2% of the REGIMS patients had a relapse at baseline. Mean EDSS Score at baseline was 2.7 (SD: 1.7). 94.6% of patients suffered from RRMS, 4.3% from SPMS and 1.0% had a CIS. In total 1356 (S)AE were recorded. Cold (6.13%), influenza like illness (2.95%), lymphopenia (2.80%) and urinary infection (2.07) were the most often observed (S)AEs (Supplement Table S4).
      Table 1Demographic and clinical characteristics of the Regims patients.
      CharacteristicsBaseline and follow up (Outcome analysis)
      TotalFulfilling all criteriaNot fulfilling all criteria
      Patients (N).1248340908
      Female,%70.168.870.6
      Age, years, mean (SD)37.6 (11.1)34.0 (8.9)38.9 (11.6)
      Age 1st symptom's, mean (SD)29.5 (10.1)27.8 (8.5)30.1 (10.6)
      Age diagnosis, years, mean (SD)31.5 (10.5)29.5 (8.9)32.2 (10.9)
      Disease duration, mean (SD)9.7 (7.8)7.1 (6.6)10.7 (8.0)
      EDSS-Score, mean (SD)2.7 (1.7)2.3 (1.2)2.8 (1.8)
      Relapses
      Nummber of relapses 24 months within randomization
      , mean (SD)
      1.5 (1.6)2.8 (1.7)1.0 (1.3)
      Relapse baseline
      Relapse at baseline.
      ,% (patients)
      5.28.63.9
      RRMS,%94.699.492.8
      DMT: disease-modifying therapy; EDSS: expanded disability status scale; RRMS: relapsing-remitting multiple sclerosis
      a Nummber of relapses 24 months within randomization
      b Relapse at baseline.

      3.1.1 Post approval compliance with selected phase III clinical trial criteria

      Across all analysed drugs, 27.2% of the patients would have been eligible for inclusion into a phase III clinical trial if all five predefined criteria were applied. 61.5% would have been included into the respective clinical trial if the selection criterion “relapse” was dropped.
      Hence, the highest exclusion proportion (58.5%) was due to non-fulfilment of the selection criterion “relapse”, followed by ”medication history” (26.4%). 9.8% of the patients did not fulfil the criterion “EDSS score”, while 8.9% did not comply with the criterion “age”. Finally, “clinical course” led to the lowest exclusion percentage (3.5%).
      Table 2 shows the percentages of REGIMS patients who would have been included in a phase III clinical trial of the respective drug. Patients treated with alemtuzumab (53.0%) and interferons (53.9%) showed the highest concordance with clinical trial criteria, fulfilling all five selection criteria. Patients treated with mitoxantrone (10.0%) and teriflunomide (12.1%) showed the lowest concordance. 35.1% of fingolimod and 25.4% of glatiramer acetate patients would have been selected for the respective phase III clinical trial fulfilling all four admission criteria (age, EDSS score, relapse, clinical course).
      Table 2Percentage of Regims patients fulfilling phase III clinical trial selection criteria. N = 1248.
      DMTPatients (N)% of patients fulfilling each criterion% patients fulfilling all criteria% patients fulfilling 4 criteria
      Percentage of patients fulfilling all criteria when selection criterion relapse was excluded.
      AgeEDSS ScoreRelapseClinical courseMedication history
      All drugs124891.190.241.596.673.627.261.5
      Ocrelizumab8989.978.734.888.868.522.553.9
      Cladribine14100.085.735.7100.071.421.464.3
      Daclizumab10100.090.070.0100.050.040.050.0
      Dimethyl fumarate10890.792.630.699.157.416.749.1
      Teriflunomide5881.089.720.7100.065.512.148.3
      Alemtuzumab16898.892.364.398.289.953.081.6
      Fingolimod21493.593.040.296.3n/a35.186.9
      Natalizumab42289.189.334.699.156.914.946.0
      Mitoxantrone2060.075.095.0100.025.010.010.0
      Glatiramer acetate6786.692.528.485.1n/a25.473.1
      Interferons7897.496.266.791.084.653.973.1
      a Percentage of patients fulfilling all criteria when selection criterion relapse was excluded.
      The highest concordance with all admission criteria, when dropping the criterion “relapse”, was attained in patients treated with fingolimod (86.9%) and alemtuzumab (81.6%). In contrast, the lowest was observed in those treated with mitoxantrone (10.0%), natalizumab (46.0%), teriflunomide (48.3%), and dimethyl fumarate (49.1%).

      3.1.2 Comparison of patients treated with DMDs post approval

      Table 3 shows the comparison of MS patients fulfilling all predefined phase III trial inclusion criteria and those who did not. The latter group was older at therapy start, as well as at the time of diagnosis and at age of first symptoms with the exception of those treated with alemtuzumab, cladribine and interferons. Patient who did not fulfil all criteria had a higher EDSS Score and less relapses in the two years before treatment start.
      Table 3Mean difference (Δ) between patients fulfilling all inclusion criteria for phase III clinical trials (
      • Jalusic K.O.
      • Ellenberger D.
      • Rommer P.
      • et al.
      Effect of applying inclusion and exclusion criteria of phase III clinical trials to multiple sclerosis patients in routine clinical care.
      ) compared to patients who would not.
      Mean ΔOcrelizumabCladribineDaclizumabDimethyl- fumarateTeriflunomideAlemtuzu-mabFingolimodNatalizumabMitoxantroneGlatiramer acetateInterferons
      Patients
      Number of patients missed at least one selection criterion; DMT: disease-modifying therapy; EDSS: expanded disability status scale; No: number., *p<.05; **p<.01; ***p<.001.
      69116905179139359185036
      Age (years)+9.6 ***−4.1+4.3+4.8+8.1*+2.7+4.9**+4.9***+9.6+5.3+4.2
      Age diagnosis (years)+3.9−13.1+3.7+2.6+4.9+0.5+3.2*+3.5**+8.7+5.1−0.1
      Age symptoms (years)+3.0−15.7*+2.6+1.5+0.80.03+3.7*+3.0*+20.6*+4.0−0.3
      EDSS-Score+1.3*1.02.1−0.3+0.9+0.4+0.3+0.5*+0.6+0.6+0.7 *
      Relapses 24 months, No−1.7***−1.6*−1.4 *−1.8***−1.4***−2.1***−2.1***−1.6***+0.1−1.5***−0.8*
      a Number of patients missed at least one selection criterion; DMT: disease-modifying therapy; EDSS: expanded disability status scale; No: number., *p<.05; **p<.01; ***p<.001.

      3.1.3 Outcome comparison within regims patients

      amongst all REGIMS patients, 40.9% had at least one AE and 8.4% at least one SAE. 32.7% had a disease progression or relapse during the mean follow up time of 6.7 months. Table 4 shows the outcome comparison between patients fulfilling all five predefined inclusion criteria and patients missing at least one criterion (a), as well as the comparison when the criterion “relapse” is omitted (b).
      Table 4Outcome comparison between patient groups.
      a) all five predefined inclusion criteria and patients missing at least one criterion
      Disease modifying drug (DMD)All DMDsOcrelizumabDimethyl fumarateAlemtuzumabFingolimodNatalizumab
      Fullfilment of all 5 inclusion criteriaYesNoYesNoYesNoYesNoYesNoYesNo
      Adverse event (AE) [%]47.838.315.020.623.532.662.156.659.549.343.635.2
      Serious adverse event (SAE) [%]8.78.302.908.112.613.214.911.88.17.5
      Relapse /disease progression [%]34.432.135.036.233.331.137.134.241.328.827.033.4
      Change in DMD [%]2.73.207.304.501.32.72.93.22.0
      EDSS [%]No change31.538.647.460.025.053.421.635.033.834.430.034.2
      Increase33.033.415.821.531.322.731.832.533.832.831.737.7
      Decrease35.528.136.818.543.823.946.632.532.432.838.328.1
      b) four predefined inclusion criteria (without relapse) and patients missing at least one of those
      Disease modifying drug (DMD)All DMDsOcrelizumabDimethyl fumarateAlemtuzumabFingolimodNatalizumab
      Fullfilment of 4 inclusion criteriaYesNoYesNoYesNoYesNoYesNoYesNo
      Adverse event (AE) [%]43.037.512.527.530.631.541.865.554.144.434.438.2
      Serious adverse event (SAE) [%]7.99.30.05.02.011.111.917.21218.56.88.3
      Relapse /disease progression [%]33.331.735.436.634.029.136.532.333.332.132.032.9
      Change in DMD [%]2.73.64.27.33.93.60.70.02.27.41.62.6
      EDSSNo change [%]36.037.653.361.544.053.727.430.033.538.535.731.8
      Increase [%]32.035.422.218.024.024.131.136.734.126.931.940.9
      Decrease [%]32.027.024.420.532.022.241.533.332.434.632.427.3
      Across all DMDs, the percentage of patients having at least one adverse event was higher in the group who fulfilled, compared to the one who did not fulfil all inclusion criteria (47.8 % vs. 38.3%). When comparing the groups for single drugs, this result was also observed in patients treated with alemtuzumab, fingolimod and natalizumab. In contrast, for patients treatedwith ocrelizumab and dimethyl fumarate those not fulfilling all inclusion criteria had slightly more AEs.
      For SAE across all DMDs 8.7% of patients who fulfilled all five inclusion criteria experienced at least one SAE, compared to 8.3% of those who did not. Patients treated with alemtuzumab had also no difference in SAEs based on the fulfilment of admission criteria. In contrast to that, the proportion of patients who had at last one serious event and received ocrelizumab or dimethyl fumarate was higher in the non-fulfilment group. After dropping the criterion “relapse”, in the group of patients not fulfilling predefined four criteria 9.3% experienced at least one serious event, while in the other group it was 7.9%.
      In order to investigate a relationship between drug safety variables (AE; SAE) and the fulfilment (yes-no) of predefined inclusion criteria (criterion age, criterion EDSS Score, criterion medication history, criterion relapses, criterion MS Type) a logistic regression analysis was conducted. Table 5a shows the results of the logistic regression analysis where the dependant variable is AE. Yes equals 1 if a patient had at least one AE and 0 otherwise. The results of the multiple binary logistic regression indicate that, patients fulfilling the criterion relapses have higher odds of having AEs than patients not fulfilling this criterion (OR: 1.39; 95% CI: 1.10 – 1.75; p  = 0.005). Table 5b shows the results of the logistic regression analysis where the dependant variable is SAE. Patients fulfilling the criterion age have lower odds of having a SAE then patients not fulfilling this criterion (OR: 0.50; 95% CI: 0.28 – 0.91; p = 0.02).
      Table 5aOdds ratios for the risk of adverse events according to fulfilment of clinical trial inclusion criteria.
      AEUnivariateMultivariate
      Inclusion criteriaOR95% CIP- ValueOR95% CIP- Value
      Age0.9820.659 – 1.4640.9290.9390.623 – 1.4160.766
      EDSS Score0.9650.658 – 1.4140.8540.8600.576 – 1.2850.463
      Medication history1.2760.982 – 1.6570.0681.2870.987 – 1.6780.0.63
      Relapses1.4021.113 – 1.7670.0041.3911.103 – 1.7540.005
      ms type1.6990.859 – 3.3630.1281.8480.918 – 3.7210.085
      dependant variable is adverse event [AE] (1= at least one serious AE; 0 = no AE). Univariate adjusted to the inclusion of a single criterion as independent variable. Multivariate adjusted to the inclusion of all other listed criteria simultaneously.
      Table 5bOdds ratios for the risk of serious adverse events according to fulfilment of clinical trial inclusion criteria.
      SAEUnivariateMultivariate
      Inclusion criteriaOR95% CIP- ValueOR95% CIP- Value
      Age0.4920.277 – 0.8740.0160.5030.278 – 0.9100.023
      EDSS Score0.6070.339 – 1.0880.0930.5990.324 – 1.1070.102
      Medication history1.2840.793 – 2.0800.3091.4040.859 – 2.2960.175
      Relapses1.1010.733 – 1.6540.6431.1010.731 – 1.6580.646
      ms type1.8210.434 – 7.6560.4132.5800.595 – 11.1770.205
      dependant variable is adverse event [SAE] (1= at least one serious SAE; 0 = no SAE). Univariate adjusted to the inclusion of a single criterion as independent variable. Multivariate adjusted to the inclusion of all other listed criteria simultaneously.
      A further logistic regression analysis (Table S5a and S5b) evaluated the relationship between AE/SAE and individual patient's characteristics (age, EDSS Score, number of relapses, MS type, number of previous DMDs, disease duration). This analysis shows that patients with more relapses have higher odds of having AEs (OR: 1.15; 95% CI: 1.06 - 1.25; p = 0.01).
      When comparing the item relapse/disease progression, the percentage of patients who had a relapse or disease progression was slightly higher in the group of patients fulfilling all inclusion criteria (34.4% vs 32.1%). Alemtuzumab, dimethyl fumarate and fingolimod patients showed the same pattern in both groups, while for patients treated with ocrelizumab and natalizumab the progression was higher in the not concordant group.
      The proportion with treatment change of a DMD was slightly higher in the group of patients who did not fulfil all predefined criteria (3.2 % vs 2.7%). An exception from this pattern were patients receiving natalizumab with 3.2% of them changing the DMD while fulfilling all criteria compared to 2.0% in those who did not.
      Across all DMDs patients fulfilling all predefined inclusion criteria (35.5%) had a stronger EDSS decrease during the follow up than patients not fulfilling all criteria (28.1%).

      4. Discussion

      In this study we analysed the effects of transferring phase III clinical trials inclusion and exclusion criteria to MS patients treated with DMDs in clinical routine by investigating differences in drug safety (AE; SAE) and clinical characteristics between the two groups. We found that the majority of patients treated with an approved MS DMD in routine clinical care would not have met all predefined inclusion criteria of the respective phase III clinical trial. Main reason for this result was the criterion “relapse”. When this criterion is dropped, the proportion of patients fulfilling the other criteria increased to 61.5% on average. This result is in concordance with our previous published study based on the German MS Register (GMSR) (
      • Jalusic K.O.
      • Ellenberger D.
      • Rommer P.
      • et al.
      Effect of applying inclusion and exclusion criteria of phase III clinical trials to multiple sclerosis patients in routine clinical care.
      ) and with similar studies addressing generalizability of clinical trials in other diseases. (
      • He Z.
      • Tang X.
      • Yang X.
      • et al.
      Clinical trial generalizability assessment in the big data era: a review.
      ) Despite the large proportion of patients who would not have been recruited into the respective clinical trial, the criteria “age” and “relapse” were the only predictor variables with a statistical significant relation to drug safety outcomes. Since no generalizability studies of clinical trials for DMDs analysing safety data in MS patients have been published yet, this result cannot be compared to other studies.
      We also found that the probability of an AE in patients fulfilling the criterion relapse is higher than in patients not fulfilling this criterion. The reduction of the annualized relapse rate is a frequent endpoint in clinical trials and serves as a proxy for disease activity. Phase III clinical trials include patients with at least one relapse during one year or at least two relapses in two years prior to randomisation. The criterion “relapse” was the criterion with the highest percentage of non-fulfilment. In this study, we analysed treatment-naive patients and patients with a treatment history of MS DMDs. Receiving a high-efficacy DMD in the period preceding baseline might account for some patients having a lower relapse rate. Since a low rate of relapses indicates low disease activity, the non-fulfilment of this criterion may just show a successful treatment and is not considered as a potential safety risk in the drug therapy.
      Next to the criterion “relapse” patients showed the lowest concordance with the criterion “medication history”. Washout periods as required in most phase III clinical trials are hardly achievable in routine clinical care. In case patients do not respond to current treatment or have at least one relapse, guidelines recommend to switch to a second line therapy. (
      • Montalban X.
      • Gold R.
      • Thompson A.J.
      • et al.
      ECTRIMS/EAN Guideline on the pharmacological treatment of people with multiple sclerosis.
      ) Additionally, Sepulveda et al. showed that discontinuing a treatment with fingolimod without a suitable DMD switch resulted in rebound relapses. (
      • Sepúlveda M.
      • Montejo C.
      • Llufriu S.
      • et al.
      Rebound of multiple sclerosis activity after fingolimod withdrawal due to planning pregnancy: analysis of predisposing factors.
      ) This risk was also observed if natalizumab treatment is stopped without an appropriate DMD switch. (
      • Mustonen T.
      • Rauma I.
      • Hartikainen P.
      • et al.
      Risk factors for reactivation of clinical disease activity in multiple sclerosis after natalizumab cessation.
      ) Subsequently a medication history without DMD is nowadays rare and most patients are treated with multiple DMDs over their disease course. Our analysis showed that missing the criterion medication history does not imply a higher risk in terms of drug safety.
      DMDs for MS Patients in Germany are prescribed by physicians of various specialization. The German Society of Neurology published a Guideline for Diagnosis and therapy of MS, neuromyelitis optica spectrum diseases and MOG-IgG-associated diseases with recommendations for DMD prescriptions in MS patients. (
      • Hemmer B.
      • et al.
      Diagnose und Therapie der Multiplen Sklerose, Neuromyelitis-optica-Spektrum-Erkrankungen und MOG-IgG-assoziierten Erkrankungen.
      ) Supplement Figure S1 shows the therapy algorithm for initial setting/escalation according to the current guideline. However, it is unknown how many physicians follow this guideline.
      Elderly patients are often excluded from phase III clinical trials and additional information on safety of DMDs in ageing population is required. We showed that across all drugs 91.1% of the patients fulfilled the criterion age. The results of the logistic regression indicate that patients not fulfilling the predefined criterion age have a higher risk of having a SAE. The probability of different comorbidities and therefore the interaction of comorbidities and DMDs in elderly MS patients is higher than in younger patients. (
      • Capkun G.
      • Dahlke F.
      • Lahoz R.
      • et al.
      Mortality and comorbidities in patients with multiple sclerosis compared with a population without multiple sclerosis: an observational study using the US Department of Defense administrative claims database.
      ) This presents a potential risk in the drug therapy of older MS patients.
      Our study has several limitations. For some DMDs the number of patients was small, because of exclusion of patients with incomplete documentation or because of a low drug market share in general. Due to incomplete MRI data this criterion was not applied to the REGIMS patients, although some of the phase III clinical trials applied magnetic resonance imaging (MRI) of the brain indicating MS comparable abnormalities as an inclusion criterion. Since the exact dates on relapse timing are unknown, no statement can be made whether a AE is relapse related or not.
      The results of our study suggest that a low transferability of single phase III clinical trial criteria (EDSS, medication history, relapse) to patients in routine clinical care does not imply a higher risk in terms of drug safety. Elder patients, who are frequently excluded from clinical trials, however have a higher risk of having a serious adverse event. Generalizability of clinical trial results refers to the question if the tested drug would have the same effect and the same adverse event profile in patients who were excluded from the trial. But the answer to this question usually does not differentiate between patient's characteristics that are important in this context (e.g. pregnancy, specific comorbidies or disease cause) or less important (e.g. age) in the judgement of generalizability of results. Thus, assuming an adverse event risk as in the trial for a patient who is 5 years older than the inclusion criterion is probably more valid than assuming the same effect for a pregnant woman in the second trimester of pregnancy. However, the performance of a drug should also be verified, when used outside clinical trials, e.g. in registry based results or other study designs. Thus clinical routine data from prospective cohort studies and registers, such as REGIMS are needed to identify the risks and benefits of DMDs in different groups of patients.

      Credit author statement

      K.O.J., D.E., A.S. and K.B. conceptualized the study. K.O.J. and K.B. designed the study, analysed and interpreted the data. K.O.J. wrote the original draft. D.E. and A.S. reviewed the manuscript for intellectual content. All authors critically reviewed and approved the final version of the manuscript.

      Disclosure/conflict of interest statement and funding

      Jalusic K. O. has nothing to disclose.
      Ellenberger D. has nothing to disclose.
      Stahmann A. has no personal pecuniary interests to disclose, other than being the lead of the German MS Registry, which receives funding from a range of public and corporate sponsors, recently including The German Innovation Fund (G-BA), The German MS Trust, Biogen, German MS Society, Celgene (BMS), Merck and Novartis.
      Berger K. received funding from the German Ministry of Education and Research, for a project within the Competence Net Multiple Sclerosis and from the German Innovation Fund (GBA) for the coordination of the VersiMs project (both to the University of Münster).

      Acknowledgement

      *The following REGIMS Investigators, contributed to the study through acquisition of data and critical review of the manuscript.
      Prof. Dr. med. Luisa Klotz, Universitätsklinikum Münster, Klinik für Allgemeine Neurologie, Münster; Prof. Dr. med Florian Stögbauer, Klinikum Osnabrück GmbH, Neurologische Klinik, Osnabrück.
      Prof. Dr.med. Orhan Aktas, Heinrich-Heine-Universität Düsseldorf, Klinik für Neurologie, Düsseldorf.
      Prof. Dr. med. Tjalf Ziemssen, Klinikum Carl Gustav Carus, Neurologische Universitätsklinik, Dresden.
      Prof. Dr. med. Frauke Zipp, Universitätsmedizin Mainz, Klinik und Poliklinik für Neurologie, Mainz.
      Priv.-Doz. Dr. med. Antonios Bayas, Universitätsklinikum Augsburg, Klinik für Neurologie und klinische Neurophysiologie, Augsburg.
      Prof. Dr. med. Thomas Müller, St. Joseph- Krankenhaus Berlin Weißensee, Klinik für Neurologie, Berlin.
      Prof. Dr. med. Friedemann Paul, Charité – Universitätsmedizin, Exzellenzcluster NeuroCure, Berlin.
      Dr. med. Maria Seipelt, Philipps-Universität Marburg, Klinik und Poliklinik für Neurologie, MarburgPD PD Dr. med. Klemens Angstwurm, Universität Regensburg, Klinik und Poliklinik für Neurologie, Regensburg.
      Prof. Dr. med. Martin Weber, Universitätsmedizin Göttingen Institut für Neuropathologie, Klinik für Neurologie Göttingen.
      Prof. Dr. med. Brigitte Wildemann, Universitätsklinikum Heidelberg, Neurologische Klinik, Heidelberg.
      Prof. Dr. med. Tania Kümpfel, Klinikum der Universität München, Institut für Klinische Neuroimmunologie, München.
      PD Dr. med. Markus Kowarik, Universität Tübingen, Zentrum für Neurologie, Abteilung Neurologie mit Schwerpunkt neurovaskuläre Erkrankungen, Tübingen.
      Dr. med. Matthias Grothe, Universitätsmedizin Greifswald, Klinik und Poliklinik für Neurologie, Greifswald
      Dr. med. Iris Steck, Medizinisches Versorgungszentrum für Neurologie und Psychiatrie Bremen Nord, Bremen.
      Prof. Dr. med. Christoph Heesen, Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurologie, Hamburg.
      Prof. Dr. med. Uwe K. Zettl, Universitätsmedizin Rostock, Zentrum für Nervenheilkunde, Klinik und Poliklinik für Neurologie, Rostock.
      Dr. med. Refik Pul, Universitätsklinikum Essen, Klinik für Neurologie, Essen.
      Prof. Dr. med. Hayrettin Tumani, Universität Ulm, Klinik und Poliklinik für Neurologie, Ulm.
      Dr. med. Matthias Kaste, Nordwestkrankenhaus Sanderbusch, Neurologische Klinik, Sande.
      Dr. med. Frank A. Hoffmann, Krankenhaus Martha-Maria Halle-Dölau gGmbH, Klinik für Neurologie.
      Prof. Dr. med. Wolfgang Freund, Krankenhaus Martha-Maria Halle-Dölau gGmbH, Klinik für Neurologie.
      Prof. Dr. med. Peter Schwenkreis, BG-Universitätsklinikum Bergmannsheil Bochum, Neurologische Universitätsklinik und Poliklinik, Bochum.
      Dr. med. Annette Walter, Klinikum Herford, Klinik für Neurologie, Herford
      Dr. med. Frank Halbgewachs, Neurologische Praxis Heidenheim - Dr. Halbgewachs - Dr. Breitinger, Heidenheim
      Dr. med. Florian Bethke, Klinikum Ibbenbüren, Klinik für Neurologie.
      Dr. med. Michael Hotz, Christliches Krankenhaus Quakenbrück, Neurologische Klinik, Quakenbrück.
      Dr. med. Stefan Harscher, Sophien- und Hufeland-Klinikum gGmbH Weimar, Klinik für Neurologie, Weimar.
      Dr. med. Ralf-Jochen Kuhlmann, Evangelisches Krankenhaus Castrop-Rauxel, Klinik für Neurologie, Castrop-Rauxel.
      Dr. med. Cordula Haltenhof, Ammerland Klinik GmbH, Klinik für Neurologie, Westersted.
      Dr. med. Muhterem Erinola, Katholisches Klinikum Lünen/Werne GmbH, Neurologische Klinik, Lünen.
      Prof. Dr. med. Jörg Berrouschot, Klinikum Altenburger Land GmbH, Klinik für Neurologie, Altenburg.
      Dr. med. Isabell Greeve, Evangelisches Klinikum Bethel Universitätsklinikum OWL der Universität Bielefeld Campus Bielefeld-Bethel.
      Dr. med. Felicitas Heidler, Ökumenisches Hainich Klinikum gGmbH, Klinik für Neurologie, Mühlhausen.
      Dr. med. Wolfgang Kusch, Herz-Jesu-Krankenhaus Hiltrup GmbH, Klinik für Neurologie, Münster.
      Dr. med. Alexander Niklas, Sana Klinikum Borna, Klinik für Neurologie, Borna.
      PD Dr. med. Hela-Felicitas Petereit, Praxis rechts vom Rhein, Köln.
      Dr. med. Jonas Repenthin, AMEOS Klinikum Oldenburg, Klinik für Neurologie und Neurophysiologie, MS-Ambulanz, Oldenburg/Holstein.
      Dr. med. Martin Brand, St. Augustinus Krankenhaus gGmbH, MVZ Medizinisches Versorgungszentrum GmbH.
      Dr. med. Heike Stephanik, Praxis Dr. Hinkfoth Ribnitz-Damgarten.
      Dr. med. Roland Bauer, Gemeinschaftspraxis für Neurologoie Dr. Roland Bauer und Dr. Anndrej Schleyer, Memmimgen.
      Dr. med. Katrin Hinkfoth, Praxis Dr. Hinroth Ribnitz-Damgarten.
      Dr. med. Christoph Lassek, Neurologische Gemeinschaftspraxis Kassel und Vellmar.

      References

        • Filippi M.
        • Bar-Or A.
        • Piehl F.
        • et al.
        Multiple sclerosis.
        Nat. Rev. Dis. Prim. 2018; 4: 43
        • Friedman L.M.
        • Furberg C.D.
        • DeMets D.L
        Fundamentals of Clinical Trials.
        4. ed. Springer, New York, NY2010
        • Fischer L.
        • Knaebel H.P.
        • Golcher H.
        • et al.
        To whom do the results of the multicenter, randomized, controlled INSECT trial (ISRCTN 24023541) apply? - assessment of external validity.
        BMC Surg. 2012; 12: 2
        • He Z.
        • Tang X.
        • Yang X.
        • et al.
        Clinical trial generalizability assessment in the big data era: a review.
        Clin. Transl. Sci. 2020;
      1. European Medicines Agency - Committee for Medicinal Products for Human. Tysabri - Authorisation details, https://www.ema.europa.eu/en/medicines/human/EPAR/tysabri (accessed 28. 06.).

        • Tintore M.
        • Vidal-Jordana A.
        • Sastre-Garriga J.
        Treatment of multiple sclerosis - success from bench to bedside.
        Nat. Rev. Neurol. 2019; 15: 53-58
        • Jalkh G.
        • Abi Nahed R.
        • Macaron G.
        • et al.
        Safety of newer disease modifying therapies in multiple sclerosis.
        Vaccines. 2020; : 9
        • Simbrich A.
        • Thibaut J.
        • Khil L.
        • et al.
        Drug-use patterns and severe adverse events with disease-modifying drugs in patients with multiple sclerosis: a cohort study based on German claims data.
        Neuropsychiatr. Dis. Treat. 2019; 15: 1439-1457
      2. European medicines agency - CHMP. Zinbryta: daclizumab.

        • Biogen M.E.D.I.A.
        • Abbvie M.E.D.I.A
        Biogen and AbbVie Announce the Voluntary Worldwide Withdrawal of Marketing Authorizations For ZINBRYTA® (daclizumab) For Relapsing Multiple Sclerosis.
        CAMBRIDGE, Mass. & NORTH CHICAGO, III, 2018
        • Beutler E.
        • Koziol J.A.
        • McMillan R.
        • et al.
        Marrow suppression produced by repeated doses of cladribine.
        Acta Haematol. 1994; 91: 10-15
        • Berger J.R.
        • Cree B.A.
        • Greenberg B.
        • et al.
        Progressive multifocal leukoencephalopathy after fingolimod treatment.
        Neurology. 2018; 90: e1815-e1821
        • Bloomgren G.
        • Richman S.
        • Hotermans C.
        • et al.
        Risk of natalizumab-associated progressive multifocal leukoencephalopathy.
        N. Engl. J. Med. 2012; 366: 1870-1880
        • Flachenecker P.
        • Stuke K.
        National MS registries.
        J. Neurol. 2008; 255: 102-108
        • Willis C.D.
        • McNeil J.J.
        • Cameron P.A.
        • et al.
        Monitoring drug safety with registries: useful components of postmarketing pharmacovigilance systems.
        J. Clin. Epidemiol. 2012; 65: 121-125
        • Simbrich A.
        • Thibaut J.
        • Khil L.
        • et al.
        chances and challenges of registry-based pharmacovigilance in multiple sclerosis: lessons learnt from the implementation of the multicenter REGIMS Registry.
        Drug Saf. 2021; 44: 7-15
        • Jalusic K.O.
        • Ellenberger D.
        • Rommer P.
        • et al.
        Effect of applying inclusion and exclusion criteria of phase III clinical trials to multiple sclerosis patients in routine clinical care.
        Mult. Scler. 2021; 1352458520985118
        • Montalban X.
        • Gold R.
        • Thompson A.J.
        • et al.
        ECTRIMS/EAN Guideline on the pharmacological treatment of people with multiple sclerosis.
        Mult. Scler. 2018; 24: 96-120
        • Sepúlveda M.
        • Montejo C.
        • Llufriu S.
        • et al.
        Rebound of multiple sclerosis activity after fingolimod withdrawal due to planning pregnancy: analysis of predisposing factors.
        Mult. Scler. Relat. Disord. 2020; 38101483
        • Mustonen T.
        • Rauma I.
        • Hartikainen P.
        • et al.
        Risk factors for reactivation of clinical disease activity in multiple sclerosis after natalizumab cessation.
        Mult. Scler. Relat. Disord. 2020; 38101498
        • Hemmer B.
        • et al.
        Diagnose und Therapie der Multiplen Sklerose, Neuromyelitis-optica-Spektrum-Erkrankungen und MOG-IgG-assoziierten Erkrankungen.
        S2k-Leitlinie, 2021 (2022, accessed 27 March 2022)
        • Capkun G.
        • Dahlke F.
        • Lahoz R.
        • et al.
        Mortality and comorbidities in patients with multiple sclerosis compared with a population without multiple sclerosis: an observational study using the US Department of Defense administrative claims database.
        Mult. Scler. Relat. Disord. 2015; 4: 546-554