Abstract
Objective
To compare incidences of neuroinflammatory events, including demyelinating disease (DML), inflammatory polyneuropathies (IPN) and multiple sclerosis (MS), in patients with rheumatoid arthritis (RA) or spondyloarthritis (SpA; including psoriatic arthritis) starting a tumour necrosis factor inhibitor (TNFi), investigating whether monoclonal TNFi antibodies (other TNFis (oTNFis)) confer higher risk than etanercept.
Methods
This is an observational cohort study including patients from the five Nordic countries starting a TNFi in 2001–2020. Time to first neuroinflammatory event was identified through register linkages. We calculated crude incidence rates (cIR) per 1000 person-years and used multivariable-adjusted Cox regression to compare incidences of neuroinflammatory events overall and for DML, IPN and MS with oTNFi versus etanercept. We further examined individual TNFis and indications.
Results
33 883 patients with RA and 28 772 patients with SpA were included, initiating 52 704 and 46 572 treatment courses, respectively. In RA, we observed 135 neuroinflammatory events (65% DML) with cIR of 0.38 with oTNFi and 0.34 with etanercept. The HR of oTNFi versus etanercept was 1.07 (95% CI 0.74 to 1.54) for any neuroinflammatory event, 0.79 (95% CI 0.51 to 1.22) for DML, 2.20 (95% CI 1.05 to 4.63) for IPN and 0.73 (95% CI 0.34 to 1.56) for MS. In SpA, we observed 179 events (78% DML) with cIR of 0.68 with oTNFi and 0.65 with etanercept. The HR for any neuroinflammatory event, DML, IPN and MS was 1.06 (95% CI 0.75 to 1.50), 1.01 (95% CI 0.68 to 1.50), 1.28 (95% CI 0.61 to 2.69) and 0.94 (95% CI0.53 to 1.69), respectively.
Conclusion
The cIRs of neuroinflammatory events are higher in SpA than in RA, but the choice of specific TNFi does not seem to play an important role in the risk of neuroinflammatory events.
Keywords: Tumor Necrosis Factor Inhibitors; Spondylitis, Ankylosing; Arthritis, Rheumatoid; Arthritis, Psoriatic
WHAT IS ALREADY KNOWN ON THIS TOPIC.
Neuroinflammatory events, such as multiple sclerosis, have been reported in patients with rheumatoid arthritis, but particularly with psoriatic arthritis or spondyloarthropathies and during treatment with tumour necrosis factor inhibitors (TNFis), although the absolute risks seem low.
Due to the different mechanisms of actions of etanercept and other TNFis, the risk of demyelinating events may differ by the TNFi’s mode of action.
WHAT THIS STUDY ADDS
We compared the risk of neuroinflammatory disorders in patients with rheumatoid arthritis, psoriatic arthritis or spondyloarthropathies treated with etanercept versus treated with TNFi with other modes of action and demonstrate that the incidence rates were similar for etanercept and for TNFi with other modes of action, but dissimilar across indications.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
The rheumatological diagnosis (rheumatoid arthritis vs psoriatic arthritis and spondyloarthropathies) but not the choice of specific TNFi plays an important role in the risk of neuroinflammatory events.
Introduction
Treatment with tumour necrosis factor alpha inhibitors (TNFis) is the mainstay for several rheumatic diseases, including rheumatoid arthritis (RA) and spondyloarthritis (SpA), the latter comprising psoriatic arthritis (PsA) and axial and peripheral spondyloarthritis (AS/SpA).1–3 Although rare, events of neuroinflammatory disorders, such as demyelinating disease (DML; including multiple sclerosis (MS)) and inflammatory polyneuropathies (IPN), have been reported in association with treatment with TNFis.4–9
Whether these neuroinflammatory events are causally linked to TNFi remains uncertain, although links between the specific mechanism of action of different TNFis and central nervous system demyelination have been described.10–13 TNFis inhibit TNF-driven signalling by blocking the interactions between TNF molecules and their receptors. The two types of TNF, the transmembrane molecule TNF (tmTNF) and the soluble TNF (sTNF), are blocked by all TNFis, but etanercept is less effective than other TNFis in blocking tmTNF, while all are similarly effective with regard to inhibition of sTNF.14–17 With regard to demyelination, tmTNF promotes mostly protective features such as cell survival and remyelination, while sTNF promotes inflammation.10 12 13 Mice models have indicated that selective inhibition of sTNF may be therapeutic in autoimmune encephalomyelitis.10 If the same would apply to humans, the association between TNFis and risk of neuroinflammatory events may therefore differ between etanercept, (which would be hypothesised to have no increased risk or even a protective effect), and TNFis with other modes of action (other TNFis (oTNFis)), (which would increase the risk).14
Since neuroinflammatory events are rare, most evidence on the safety of TNFi with respect to demyelinating events comes from case reports and smaller case series.5 6 18–22 Comparative studies are sparse. In a study based on data from Sweden and Denmark, we showed that the incidence rates (IRs) of neuroinflammatory events in patients with RA were lower than the IRs in patients with SpA, and demonstrated that, in patients with SpA, being treated with TNF inhibitor was associated with an increased risk of neuroinflammatory events compared with not being treated with a biologic disease-modifying antirheumatic drug (bDMARD).23 A study from Kunchok et al24 suggested that this increased risk also applied to patients with RA.
To further investigate the (differential) association between the two types of TNFi drugs and neuroinflammatory events in patients with RA and SpA, this study aimed to contrast the risks with etanercept to those with four other TNFis.
Methods
We performed an observational cohort study on the association between treatment with specific TNFi drugs (exposure) and risk of neuroinflammatory events (outcome). We used prospectively collected individual patient-level data from registers in Denmark, Finland, Iceland, Norway and Sweden during the study period from 1 January 2001 (1 January 2009 for Norway) through 1 October 2021 (1 January 2019 for Denmark, 31 May 2020 for Norway, 31 December 2020 for Sweden and Finland).
Design and setting
In the Nordic countries, healthcare systems are tax-funded; individual-level information on healthcare use is recorded in clinical and administrative registers. For this study, we identified patients with RA and those with SpA (here defined as PsA or AS/SpA) from the following clinical rheumatology registers (CRRs): DANBIO (Denmark), ROB-FIN (Finland), ICEBIO (Iceland), NOR-DMARD (Norway) and SRQ (the Swedish Rheumatology Quality Register, Sweden).25–30 Using personal identification numbers assigned to all residents, data from these CRRs were linked to other health and population registers within each country. In brief, we used the National Patient Register in each country to identify past and incident neuroinflammatory events and comorbidities, and the population registers for emigration and vital status of the patients.31
Exposure definition
In the CRRs, we identified all registered TNFi treatment initiations. We made no distinction between a biosimilar and its originator product, and we disregarded any treatment interruption of the same TNFi shorter than 3 months. At each treatment start, the number of biologic or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) the patient had been previously exposed to was retrieved. Treatment initiations preceded by more than four b/tsDMARD exposures were excluded. We defined two exposure cohorts: initiators of etanercept and initiators of any other TNFi, respectively. One patient could contribute to more than one cohort (eg, a patient starting etanercept, later switching to adalimumab, before switching to infliximab, contributed with one observation to the etanercept cohort and two observations to the oTNFi cohort). Patients were excluded if at treatment start they had a history of any neuroinflammatory event. Only treatments started during the study period were analysed.
Outcome
We defined three groups of neuroinflammatory events using the 10th version of the International Classification of Diseases (ICD-10), together with a fourth definition combining the following three (ie, having at least one of them): (1) demyelinating events (DML), including DML of the central nervous system and optic neuritis (ICD-10 G35, G36.0, G36.8, G36.9, G37.1, G37.3, G37.5, G37.8, G37.9, G04.8, G04.9, H46 and H48.1); (2) IPN, including inflammatory and drug-induced polyneuropathies (ICD-10 G61.0, G61.8 and G61.9); and (3) MS (ICD-10 G35; also included in DML). For each treatment cohort, the first registration with any of the neuroinflammatory outcome diagnosis codes was retrieved from the National Patient Register, recorded as main or secondary diagnosis in outpatient care or hospitalisation.
Statistical analyses
Main analysis
We performed separate analyses for patients with RA and patients with SpA. In each indication, the two TNFi exposure cohorts (etanercept vs oTNFi) were followed from treatment start until the end of follow-up. We applied an ‘ever since treatment start’ approach in which follow-up ended at the first registered neuroinflammatory event (the one under investigation), emigration, death or end of the study period, whichever came first, hence disregarding treatment discontinuation or switch to another drug. For example, an event occurring during treatment with the second TNFi treatment initiated during follow-up would be attributed to both TNFi treatment courses during the study period. For each exposure and indication, we calculated the number of neuroinflammatory events, the follow-up time at risk and the crude IRs. Separately for each indication, we compared the incidences with oTNFi and etanercept, using the latter as reference, and obtained the HR and the 95% CI using Cox regressions, with time since treatment start as the time scale, and a robust sandwich estimator to account for the correlated data structure. All analyses were stratified by the number of b/tsDMARDs the patients had been exposed to prior to the TNFi start. In addition to an unadjusted model (model 1), we performed analyses adjusted for age, sex and calendar period of TNFi start (model 2), and further adjusted for disease duration, C reactive protein (CRP) and concomitant use of methotrexate (model 3). All included covariates were chosen a priori and intended to capture important potential confounders such as demographics (age, sex), time trends (calendar year), level and duration of inflammation (CRP and disease duration), and comedication (methotrexate). CRP at treatment start was categorised into quartiles with a ‘missing’ category added to these. No imputation was performed for other variables. Each variable was measured at treatment start and retrieved from the CRR. The Danish data were analysed in Denmark, as individual-level data from the Danish national health registers can only be analysed in Denmark due to data security policy. The data from the four other countries were pooled and analysed in Sweden where the Cox regressions were also stratified by country. Cox regression results for the five countries together were estimated from a random-effects meta-analysis of the latter and the Danish results. In all tabulations, cells with less than five neuroinflammatory events are displayed as ‘n/a’ and no HRs were assessed. Data analyses were performed in SAS V.9.4, and figures were obtained in R V.4.2.0 (ggplot2 package).
Secondary analyses
We performed the analyses splitting the four drugs (adalimumab, certolizumab pegol, infliximab and golimumab) that had been previously grouped together as oTNFi. We also performed the analyses separately for PsA and AS/SpA.
Sensitivity analyses
For testing the robustness of our results, we performed several sensitivity analyses by (1) applying an ‘on-drug’ approach in which, in addition to the censoring events described above, we ended follow-up 3 months after each treatment discontinuation; (2) performing the analyses in patients where the TNFi was their first ever b/tsDMARD therapy; (3) starting the follow-up 3 months after treatment start in order to avoid attributing an event to the starting treatment should the first symptoms appeared just around the treatment start; and (4) stratifying the follow-up time (less than 1 year, 1–5 years, more than 5 years) for investigating any time structure in the occurrence of events.
Data protection and data sharing
Data from Finland, Iceland, Norway and Sweden are available on reasonable request, but access is regulated by the legal framework of the register linkages performed; Danish data are not available.
Patient involvement
This study was performed within the context of a Nordic rheumatology registers collaboration, which employed a patient representative panel which was not directly involved in the design and conduct of this study.
Results
Rheumatoid arthritis
The study included 33 883 patients with RA initiating 52 704 treatment courses with a TNFi (76% women, mean age 55 (SD 13) years). Denmark contributed 14 005 treatment courses, Finland 5149, Iceland 1182, Norway 1766 and Sweden 30 602. Of these, 61% represented a first ever b/tsDMARD start. Etanercept represented 41% of all treatment courses (table 1). In each country, the characteristics of the patients in the two treatment groups were overall similar for all measured variables.
Table 1.
Baseline characteristics of each treatment cohort (etanercept vs other TNFi) by country: patients with RA
| Denmark | Finland | Iceland | Norway | Sweden | ||||||
| Treatment cohorts | Etanercept | oTNFi | Etanercept | oTNFi | Etanercept | oTNFi | Etanercept | oTNFi | Etanercept | oTNFi |
| Episodes, n | 4968 | 9037 | 1923 | 3226 | 409 | 773 | 598 | 1168 | 13 067 | 17 535 |
| Patients*, n | 4486 | 6674 | 1411 | 2330 | 241 | 482 | 456 | 907 | 8274 | 11 523 |
| TNFi | ||||||||||
| Adalimumab | 0 | 3411 | 0 | 1640 | 0 | 265 | 0 | 200 | 0 | 6913 |
| Certolizumab pegol | 0 | 1485 | 0 | 342 | 0 | <5 | 0 | 519 | 0 | 2019 |
| Infliximab | 0 | 3715 | 0 | 789 | 0 | 414 | 0 | 287 | 0 | 6805 |
| Golimumab | 0 | 426 | 0 | 455 | 0 | 92 | 0 | 162 | 0 | 1798 |
| Female (%) | 3777 (76) | 6806 (75) | 1459 (76) | 2404 (75) | 309 (76) | 573 (74) | 454 (76) | 877 (75) | 10 163 (78) | 13 418 (77) |
| Age at TNFi start | 57 (48–66) | 57 (47–65) | 54 (43–62) | 54 (44–61) | 52 (41–62) | 52 (42–61) | 55 (42–63) | 55 (44–64) | 58 (46–66) | 58 (47–66) |
| Disease duration (years) | ||||||||||
| <1 | 138 (3) | 346 (4) | 69 (4) | 119 (4) | 58 (17) | 97 (15) | 67 (14) | 114 (12) | 703 (5) | 1044 (6) |
| 1–5 | 1561 (33) | 2902 (33) | 487 (26) | 780 (25) | 145 (42) | 267 (40) | 158 (32) | 266 (29) | 3710 (29) | 4758 (28) |
| >5 | 3097 (65) | 5468 (63) | 1343 (71) | 2254 (71) | 146 (42) | 299 (45) | 269 (54) | 537 (59) | 8472 (66) | 11 421 (66) |
| Number previous b/tsDMARDs | ||||||||||
| 0 | 2436 (49) | 6094 (67) | 1280 (67) | 2149 (67) | 233 (57) | 476 (62) | 336 (56) | 629 (54) | 7717 (59) | 10 848 (62) |
| 1 | 1827 (37) | 1913 (21) | 539 (28) | 686 (21) | 138 (34) | 169 (22) | 185 (31) | 324 (28) | 3592 (27) | 4159 (24) |
| 2 | 498 (10) | 683 (8) | 89 (5) | 292 (9) | 29 (7) | 88 (11) | 59 (10) | 130 (11) | 1162 (9) | 1604 (9) |
| 3 | 144 (3) | 241 (3) | 14 (1) | 69 (2) | 6 (1) | 27 (3) | 15 (3) | 61 (5) | 419 (3) | 626 (4) |
| 4 | 63 (1) | 106 (1) | 1 (0) | 30 (1) | 3 (1) | 13 (2) | 3 (1) | 24 (2) | 177 (1) | 298 (2) |
| Clinical measurements | ||||||||||
| CRP | 10.0 (4.0–25.0) |
10.0 (4.0–25.0) |
10.0 (5.0–26.0) |
10.0 (5.0–29.0) |
5.0 (3.0–17.0) |
7.0 (3.0–17.0) |
5.0 (2.0–13.0) |
5.0 (2.0–13.0) |
9.0 (4.0–24.0) |
10.0 (4.0–27.0) |
| SJC | 4 (1–7) | 4 (2–8) | 3 (1–7) | 3 (1–7) | 5 (2–8) | 5 (2–10) | 3 (1–6) | 3 (1–6) | 5 (2–9) | 6 (3–10) |
| TJC | 6 (3–12) | 7 (3–12) | 4 (1–7) | 3 (1–7) | 6 (2–10) | 6 (3–11) | 4 (1–8) | 4 (1–9) | 6 (2–10) | 6 (3–10) |
| PGH | 33 (20–50) | 35 (20–51) | 50 (26–69) | 52 (29–70) | 70 (50–84) | 69 (50–82) | 49 (26–70) | 50 (28–70) | 59 (39–75) | 60 (40–75) |
| HAQ† | 1.3 (0.8–1.8) | 1.3 (0.8–1.8) | 1.0 (0.5–1.5) | 1.0 (0.5–1.5) | 1.1 (0.8–1.5) | 1.1 (0.8–1.6) | 0.6 (0.3–1.0) | 0.6 (0.3–1.0) | 1.1 (0.6–1.5) | 1.1 (0.8–1.6) |
| Pain VAS | 62 (40–77) | 60 (39–75) | 50 (27–70) | 53 (29–72) | 65 (42–80) | 67 (45–80) | 47 (21–70) | 42 (22–65) | 60 (38–75) | 60 (39–75) |
| DAS28 | 4.7 (3.7–5.6) | 4.7 (3.7–5.6) | 4.4 (3.4–5.4) | 4.3 (3.2–5.3) | 4.5 (3.6–5.2) | 4.7 (3.8–5.6) | 3.9 (3.0–4.8) | 4.0 (3.0–4.8) | 4.6 (3.7–5.4) | 4.7 (3.8–5.5) |
| Concomitant methotrexate | 2978 (60) | 6339 (70) | 708 (53) | 1368 (61) | 180 (44) | 350 (45) | 370 (62) | 753 (64) | 8198 (63) | 12 373 (71) |
| Comorbidities | ||||||||||
| IBD | 68 (1) | 200 (2) | 9 (0) | 67 (2) | 1 (0) | 3 (0) | 2 (0) | 22 (2) | 108 (1) | 313 (2) |
| Diabetes | 152 (3) | 212 (2) | 27 (1) | 40 (1) | 4 (1) | 8 (1) | 18 (3) | 28 (2) | 397 (3) | 492 (3) |
| Thyroidea | 279 (6) | 447 (5) | 47 (2) | 73 (2) | 6 (1) | 4 (1) | 24 (4) | 39 (3) | 622 (5) | 742 (4) |
| Smoking | ||||||||||
| Current | 390 (8) | 600 (7) | 38 (2) | 69 (2) | 47 (11) | 95 (12) | 99 (17) | 184 (16) | 747 (6) | 964 (5) |
| Former | 420 (9) | 603 (7) | 9 (0) | 14 (0) | 102 (25) | 180 (23) | 206 (34) | 352 (30) | 2537 (19) | 3039 (17) |
| Never | 754 (15) | 981 (11) | 193 (10) | 270 (8) | 163 (40) | 267 (35) | 180 (30) | 344 (29) | 2294 (18) | 2833 (16) |
| Missing | 3404 (69) | 6853 (76) | 1683 (88) | 2873 (89) | 97 (24) | 231 (30) | 113 (19) | 288 (25) | 7489 (57) | 10 699 (61) |
Median (quartiles) for continuous variables and number (percentages) for binary variables are displayed. If not otherwise specified, the statistics pertain to treatment episodes. All variables are measured at treatment start.
*Patients were allowed starting a treatment with the same molecule several times.
†mHAQ in Norway.
b/tsDMARD, biologic or targeted synthetic disease-modifying antirheumatic drug; CRP, C reactive protein (mg/L); DAS28, Disease Activity Score based on 28 joint count and CRP; HAQ, Health Assessment Questionnaire; IBD, inflammatory bowel disease; mHAQ, modified Health Assessment Questionnaire; oTNFi, other tumour necrosis factor inhibitors (adalimumab, certolizumab pegol, infliximab, golimumab); PGH, patient’s global health assessment; RA, rheumatoid arthritis; SJC, 28 swollen joint count; TJC, 28 tender joint count; TNFi, tumour necrosis factor inhibitor; VAS, 0–100 Visual Analogue Scale.
During 369 505 person-years, we observed a total of 135 incident neuroinflammatory events corresponding to a crude IR of 0.37 per 1000 person-years, 0.34 for etanercept and 0.38 for oTNFi. The number of DML, IPN and MS events was 88, 47 and 29, respectively; thus, DML represented 65% of the total number of events, of which 33% were MS (figure 1).
Figure 1.
Number of events, person-years and crude incidence rates of neuroinflammatory events in patients with RA. The values of HR (95% CI) from the comparison of oTNFi with etanercept with Cox regression analyses are displayed. The analyses were adjusted for age, sex, calendar period of TNFi start, disease duration, CRP and concomitant use of methotrexate, and stratified by the number of b/tsDMARDs the patients had been exposed to prior to the TNFi start. Displayed HRs resulted from a random-effects meta-analysis of the analyses performed in Denmark (Danish data) and in Sweden (pooled data from Finland, Iceland, Norway and Sweden, with Cox regressions also stratified by country). ‘Any’ refers to any neuroinflammatory event (DML, IPN or MS). b/tsDMARD, biologic or targeted synthetic disease-modifying antirheumatic drug; CRP, C reactive protein; DML, demyelinating disease; ETN, etanercept; IPN, inflammatory polyneuropathy; MS, multiple sclerosis; oTNFi: other tumour necrosis factor inhibitors (adalimumab, certolizumab pegol, infliximab, golimumab); pyrs, person-years; RA, rheumatoid arthritis; TNFi, tumour necrosis factor inhibitor.
Table 2 displays the crude and successively adjusted HRs resulting from the comparison of oTNFi with etanercept by outcome. The meta-analysis of the results obtained in Denmark and in Sweden (for the Finnish, Icelandic, Norwegian and Swedish pooled data) provided an HR of 1.07 (95% CI 0.74 to 1.54) for the combined outcome of all neuroinflammatory events with oTNFi versus etanercept. For the specific outcomes, the corresponding HRs were 0.79 (95% CI 0.51 to 1.22) for DML, 2.2 (95% CI 1.05 to 4.63) for IPN and 0.73 (95% CI 0.34 to 1.56) for MS.
Table 2.
HR and 95% CI obtained from Cox regression comparing oTNFi with etanercept in patients with RA
| Etanercept n/1000 pyr |
oTNFi n/1000 pyr |
Country* | Model 1† HR (95% CI) |
Model 2 ‡HR (95% CI) |
Model 3§ HR (95% CI) |
Meta-analysis HR (95% CI) |
|
| Outcome | |||||||
| Any | 47/137 | 88/232 | Denmark | 1.09 (0.51 to 2.31) | 1.09 (0.52 to 2.32) | 1.14 (0.54 to 2.42) | 1.07 (0.74 to 1.54) |
| FI, ICE, NO, SE, pooled | 1.10 (0.73 to 1.66) | 1.10 (0.73 to 1.66) | 1.04 (0.68 to 1.59) | ||||
| DML | 38/137 | 50/229 | Denmark | 0.80 (0.31 to 2.04) | 0.78 (0.30 to 2.01) | 0.82 (0.32 to 2.11) | 0.79 (0.51 to 1.22) |
| FI, ICE, NO, SE, pooled | 0.78 (0.48 to 1.26) | 0.79 (0.49 to 1.28) | 0.78 (0.47 to 1.28) | ||||
| IPN | 9/137 | 38/233 | Denmark | 1.79 (0.49 to 6.52) | 1.78 (0.49 to 6.48) | 1.83 (0.50 to 6.67) | 2.20 (1.05 to 4.63) |
| FI, ICE, NO, SE, pooled | 2.77 (1.13 to 6.80) | 2.73 (1.11 to 6.69) | 2.41 (0.97 to 5.97) | ||||
| MS | 13/137 | 16/233 | Denmark | 0.66 (0.20 to 2.18) | 0.69 (0.21 to 2.27) | 0.78 (0.24 to 2.54) | 0.73 (0.34 to 1.56) |
| FI, ICE, NO, SE, pooled | 0.73 (0.28 to 1.90) | 0.80 (0.31 to 2.08) | 0.70 (0.26 to 1.88) |
The follow-up started at TNFi start and ended at first registered event date, emigration, death or end of the study period, whichever came first. Patients could be on any line of biological therapy.
All analyses were stratified by the number of previous biologic or targeted synthetic disease-modifying antirheumatic drugs (stratified Cox).
‘Any’ refers to any neuroinflammatory event (DML, IPN or MS).
*'FI, ICE, NO, SE, pooled’ includes Finland, Iceland, Norway and Sweden: pooled data, analysis stratified by country (stratified Cox).
†Model 1: crude estimate.
‡Model 2: analyses were adjusted for age, sex and calendar year.
§Model 3: analyses were further adjusted for CRP, disease duration and concomitant methotrexate.
CRP, C reactive protein (mg/L); DML, demyelinating disease; IPN, inflammatory polyneuropathy; MS, multiple sclerosis; oTNFi, other tumour necrosis factor inhibitors (adalimumab, certolizumab pegol, infliximab, golimumab); pyr, person-years; RA, rheumatoid arthritis; TNFi, tumour necrosis factor inhibitor.
Secondary analysis: individual TNFis
When analysing individual TNFis, we did not observe strong variations between crude IRs of the combined outcome, with the lowest for etanercept (0.34 (0.26–0.46) per 1000 person-years) and the highest for certolizumab pegol (0.47 (0.25–0.88); table 3). For the specific outcomes, modelling individual TNFis (with etanercept as reference) was only possible for the comparison of adalimumab and infliximab with etanercept and was performed without Danish data (which included too few events). Regarding IPN, we obtained an HR of 1.88 (0.65–5.47) for adalimumab and 3.04 (1.05–8.79) for infliximab (vs etanercept). For DML and MS, all HRs were close to 1 (data not shown).
Table 3.
Number of events, person-years, crude incidence rates (95% CL) and HR (95% CI) obtained from Cox regression comparing each TNFi with etanercept for the combined outcome (any neuroinflammatory event) and in patients with RA
| Events, n | Person-years | Crude incidence rates per 1000 person-years (95% CL) | Meta-analysis HR (95% CI) |
|
| TNFi | ||||
| Etanercept | 47 | 137 135 | 0.34 (0.26–0.46) | Reference |
| Adalimumab | 36 | 97 840 | 0.37 (0.27–0.51) | 1.03 (0.65 to 1.62) |
| Certolizumab pegol | 10 | 21 123 | 0.47 (0.25–0.88) | 1.40 (0.68 to 2.90) |
| Golimumab | 5 | 14 289 | 0.35 (0.15–0.84) | 1.08 (0.37 to 3.16) |
| Infliximab | 36 | 98 468 | 0.37 (0.26–0.51) | 1.06 (0.67 to 1.70) |
CL, confidence limits; RA, rheumatoid arthritis; TNFi, tumour necrosis factor inhibitor.
Spondyloarthritis
The study included 28 772 patients with SpA initiating 46 572 treatment courses with a TNFi (49% women, mean age 45 (SD 13) years). Denmark contributed 12 383 treatment courses, 3983 from Finland, 1597 from Iceland, 3749 from Norway and 24 860 from Sweden. Sixty per cent represented a first ever b/tsDMARD start. Etanercept represented 33% of all treatment courses. For the characteristics, see table 4.
Table 4.
Baseline characteristics of each treatment cohort (etanercept vs other TNFi) by country: patients with SpA
| Denmark | Finland | Iceland | Norway | Sweden | ||||||
| Treatment cohorts | Etanercept | oTNFi | Etanercept | oTNFi | Etanercept | oTNFi | Etanercept | oTNFi | Etanercept | oTNFi |
| Episodes, n | 3175 | 9208 | 1244 | 2739 | 366 | 1231 | 1018 | 2731 | 8581 | 16 279 |
| Patients*, n | 2896 | 6140 | 946 | 1928 | 144 | 818 | 713 | 1980 | 5440 | 9803 |
| TNFi | ||||||||||
| Adalimumab | 0 | 3552 | 0 | 1341 | 0 | 367 | 0 | 617 | 0 | 7114 |
| Certolizumab pegol | 0 | 924 | 0 | 175 | 0 | <5 | 0 | 870 | 0 | 1291 |
| Infliximab | 0 | 3280 | 0 | 661 | 0 | 717 | 0 | 576 | 0 | 5261 |
| Golimumab | 0 | 1452 | 0 | 562 | 0 | 145 | 0 | 668 | 0 | 2613 |
| Female (%) | 1632 (51) | 4303 (47) | 559 (45) | 1143 (42) | 216 (59) | 616 (50) | 506 (50) | 1387 (51) | 4431 (52) | 7844 (48) |
| Age at TNFi start | 45 (35–54) | 43 (34–53) | 44 (34–54) | 45 (35–53) | 47 (37–55) | 45 (35–55) | 43 (34–53) | 44 (36–54) | 47 (36–57) | 45 (35–55) |
| Disease duration (years) | ||||||||||
| <1 | 349 (12) | 1384 (16) | 52 (5) | 153 (6) | 69 (21) | 345 (33) | 197 (26) | 397 (21) | 496 (6) | 867 (5) |
| 1–5 | 1293 (44) | 3407 (40) | 371 (33) | 810 (32) | 115 (35) | 296 (28) | 214 (29) | 520 (27) | 2069 (24) | 3745 (23) |
| >5 | 1306 (44) | 3725 (44) | 700 (62) | 1531 (61) | 140 (43) | 410 (39) | 334 (45) | 979 (52) | 5937 (70) | 11 507 (71) |
| Number of previous b/tsDMARDs | ||||||||||
| 0 | 1467 (46) | 5978 (65) | 885 (71) | 1820 (66) | 143 (39) | 817 (66) | 579 (57) | 1447 (53) | 5312 (62) | 9650 (59) |
| 1 | 1240 (39) | 1809 (20) | 311 (25) | 565 (21) | 175 (48) | 252 (20) | 301 (30) | 742 (27) | 2259 (26) | 3829 (24) |
| 2 | 351 (11) | 869 (9) | 36 (3) | 262 (10) | 35 (10) | 114 (9) | 101 (10) | 345 (13) | 655 (8) | 1765 (11) |
| 3 | 97 (3) | 394 (4) | 9 (1) | 74 (3) | 11 (3) | 38 (3) | 26 (3) | 137 (5) | 253 (3) | 743 (5) |
| 4 | 20 (1) | 158 (2) | 3 (0) | 18 (1) | 2 (1) | 10 (1) | 11 (1) | 60 (2) | 102 (1) | 292 (2) |
| Clinical measurements | ||||||||||
| CRP | 5.0 (2.0–14.3) |
6.0 (2.0–16.0) |
8.0 (3.0–20.0) |
7.0 (3.0–19.0) |
4.0 (2.0–10.0) |
6.0 (3.0–14.0) |
5.0 (2.0–11.0) |
5.0 (2.0–10.0) |
5.0 (2.0–14.0) |
6.0 (2.0–17.0) |
| SJC | 0 (0–2) | 0 (0–2) | 1 (0–2) | 1 (0–2) | 2 (0–5) | 1 (0–4) | 0 (0–1) | 0 (0–1) | 1 (0–3) | 0 (0–3) |
| TJC | 2 (0–7) | 2 (0–6) | 1 (0–3) | 1 (0–3) | 3 (0–6) | 2 (0–5) | 0 (0–3) | 1 (0–3) | 2 (0–6) | 2 (0–6) |
| PGH | 28 (15–45) | 29 (15–45) | 51 (25–70) | 50 (25–70) | 70 (48–82) | 70 (50–83) | 57 (37–74) | 54 (35–72) | 62 (44–76) | 62 (43–77) |
| HAQ† | 1.0 (0.6–1.5) | 1.0 (0.6–1.5) | 0.8 (0.3–1.4) | 0.8 (0.4–1.3) | 1.0 (0.6–1.5) | 0.9 (0.5–1.4) | 0.6 (0.3–0.9) | 0.6 (0.3–0.9) | 0.9 (0.5–1.3) | 0.9 (0.5–1.3) |
| Pain VAS | 66 (46–81) | 66 (47–80) | 55 (30–71) | 55 (30–72) | 66 (44–80) | 67 (47–79) | 53 (32–71) | 51 (31–70) | 63 (44–76) | 63 (43–77) |
| BASDAI | 6.4 (4.8–7.7) | 6.3 (4.8–7.7) | 4.1 (1.8–6.2) | 4.2 (2.0–5.9) | 6.5 (5.8–8.1) | 6.1 (4.5–7.6) | 5.3 (3.4–6.8) | 5.0 (3.2–6.6) | 5.8 (4.1–7.1) | 5.8 (4.1–7.2) |
| ASDAS | 3.5 (2.8–4.1) | 3.4 (2.7–4.1) | 2.9 (2.1–3.7) | 2.8 (1.9–3.5) | 3.3 (2.7–4.2) | 3.5 (2.9–4.0) | 2.9 (2.3–3.7) | 2.9 (2.2–3.6) | 3.1 (2.4–3.8) | 3.2 (2.4–3.8) |
| Concomitant methotrexate | 979 (31) | 3042 (30) | 369 (44) | 949 (52) | 92 (25) | 292 (24) | 228 (22) | 734 (27) | 3266 (38) | 6805 (42) |
| Comorbidities | ||||||||||
| IBD | 102 (3) | 487 (5) | 21 (2) | 164 (6) | 4 (1) | 35 (3) | 15 (1) | 164 (6) | 235 (3) | 1420 (9) |
| Diabetes | 53 (2) | 128 (1) | 9 (1) | 15 (1) | 2 (1) | 9 (1) | 13 (1) | 37 (1) | 124 (1) | 225 (1) |
| Thyroidea | 113 (4) | 243 (3) | 17 (1) | 30 (1) | 1 (0) | 6 (0) | 12 (1) | 49 (2) | 238 (3) | 365 (2) |
| Smoking | ||||||||||
| Current | 349 (11) | 906 (10) | 25 (2) | 100 (4) | 57 (16) | 184 (15) | 196 (19) | 501 (18) | 571 (7) | 1164 (7) |
| Former | 240 (8) | 495 (5) | 8 (1) | 33 (1) | 86 (23) | 198 (16) | 286 (28) | 774 (28) | 1719 (20) | 3241 (20) |
| Never | 492 (16) | 1249 (14) | 105 (8) | 348 (13) | 129 (35) | 426 (35) | 361 (35) | 931 (34) | 2096 (24) | 3957 (24) |
| Missing | 2094 (66) | 6558 (71) | 1106 (89) | 2258 (82) | 94 (26) | 423 (34) | 175 (17) | 525 (19) | 4195 (49) | 7917 (49) |
Median (quartiles, IQR) for continuous variables and number (percentages) for binary variables are displayed. If not otherwise specified, the statistics pertain to treatment episodes. All variables are measured at treatment start.
*Patients were allowed starting a treatment with the same molecule several times.
†mHAQ in Norway.
ASDAS, Ankylosing Spondylitis Disease Activity Score; BASDAI, Bath Ankylosing Spondylitis Disease Activity Index; b/tsDMARD, biologic or targeted synthetic disease-modifying antirheumatic drug; CRP, C reactive protein (mg/L); HAQ, Health Assessment Questionnaire; IBD, inflammatory bowel disease; mHAQ, modified Health Assessment Questionnaire; oTNFi, other tumour necrosis factor inhibitors (adalimumab, certolizumab pegol, infliximab, golimumab); PGH, patient’s global health assessment; SJC, 28 swollen joint count; SpA, spondyloarthritis (including psoriatic arthritis and ankylosing spondylitis); TJC, 28 tender joint count; TNFi, tumour necrosis factor inhibitor; VAS, 0–100 Visual Analogue Scale.
During 267 314 person-years, we observed a total of 179 incident neuroinflammatory events, corresponding to a crude IR of 0.67 per 1000 person-years, 0.65 for etanercept vs 0.68 for oTNFi. The number of DML, IPN and MS events was 140, 39 and 63, respectively, with DML representing 78% of the total number of events, with 45% of these being MS (figure 2).
Figure 2.
Number of events, person-years and crude incidence rates of neuroinflammatory events in patients with SpA. The values of the HR (95% CI) from the comparison of oTNFi with etanercept with Cox regression analyses are displayed. The analyses were adjusted for age, sex, calendar period of TNFi start, disease duration, CRP and concomitant use of methotrexate, and stratified by the number of b/tsDMARDs the patients had been exposed to prior to the TNFi start. Displayed HRs resulted from a random-effects meta-analysis of the analyses performed in Denmark (Danish data) and in Sweden (pooled data from Finland, Iceland, Norway and Sweden, with Cox regressions also stratified by country). ‘Any’ refers to any neuroinflammatory event (DML, IPN or MS). b/tsDMARD, biologic or targeted synthetic disease-modifying antirheumatic drug; CRP, C reactive protein; DML, demyelinating event; ETN, etanercept; IPN, inflammatory polyneuropathy; MS, multiple sclerosis; oTNFi, other tumour necrosis factor inhibitors (adalimumab, certolizumab pegol, infliximab, golimumab); pyrs, person-years; SpA, spondyloarthritis (including psoriatic arthritis and ankylosing spondylitis); TNFi, tumour necrosis factor inhibitor.
The HR for the comparison of oTNFi with etanercept, by outcome, through the meta-analysis of the results obtained from analyses performed in Denmark and in Sweden, was 1.06 (95% CI 0.75 to 1.50) for oTNFi versus etanercept for the combined outcome of all neuroinflammatory events. For the specific outcomes, the corresponding HRs were 1.01 (95% CI 0.68 to 1.50) for DML, 1.28 (95% CI 0.61 to 2.69) for IPN and 0.94 (95% CI 0.53 to 1.69) for MS (table 5).
Table 5.
HR and 95% CI obtained from Cox regression comparing oTNFi with etanercept in patients with SpA
| Etanercept n/1000 pyr |
oTNFi n/1000 pyr |
Country* | Model 1† HR (95% CI) |
Model 2‡ HR (95% CI) |
Model 3§ HR (95% CI) |
Meta-analysis HR (95% CI) |
|
| Outcome | |||||||
| Any | 51/78 | 128/189 | Denmark | 0.74 (0.38 to 1.45) | 0.75 (0.38 to 1.46) | 0.95 (0.47 to 1.94) | 1.06 (0.75 to 1.50) |
| FI, ICE, NO, SE, pooled | 1.08 (0.74 to 1.57) | 1.09 (0.74 to 1.59) | 1.09 (0.73 to 1.63) | ||||
| DML | 41/79 | 99/189 | Denmark | 0.65 (0.28 to 1.53) | 0.65 (0.28 to 1.54) | 0.98 (0.37 to 2.55) | 1.01 (0.68 to 1.50) |
| FI, ICE, NO, SE, pooled | 1.01 (0.67 to 1.53) | 1.03 (0.68 to 1.55) | 1.01 (0.65 to 1.57) | ||||
| IPN | 10/79 | 29/189 | Denmark | 0.91 (0.31 to 2.65) | 0.91 (0.31 to 2.67) | 0.97 (0.33 to 2.89) | 1.28 (0.61 to 2.69) |
| FI, ICE, NO, SE, pooled | 0.87 (0.48 to 1.59) | 0.91 (0.50 to 1.65) | 1.00 (0.53 to 1.91) | ||||
| MS | 21/79 | 42/189 | Denmark | 0.38 (0.12 to 1.17) | 0.37 (0.12 to 1.14) | 0.71 (0.18 to 2.81) | 0.94 (0.53 to 1.69) |
| FI, ICE, NO, SE, pooled | 1.49 (0.55 to 4.09) | 1.52 (0.55 to 4.17) | 1.63 (0.59 to 4.49) |
The follow-up started at TNFi start and ended at first registered event date, emigration, death or end of the study period, whichever came first. Patients could be on any line of biological therapy.
All analyses were stratified by the number of previous biologic or targeted synthetic disease-modifying antirheumatic drugs (stratified Cox).
‘Any’ refers to any neuroinflammatory event (DML, IPN or MS).
*‘FI, ICE, NO, SE, pooled’ includes Finland, Iceland, Norway and Sweden: pooled data, analysis stratified by country (stratified Cox).
†Model 1: crude estimate.
‡Model 2: analyses were adjusted for age, sex and calendar year.
§Model 3: analyses were further adjusted for CRP, disease duration and concomitant methotrexate.
CRP, C reactive protein (mg/L); DML, demyelinating disease; IPN, inflammatory polyneuropathy; MS, multiple sclerosis; oTNFi, other tumour necrosis factor inhibitors (adalimumab, certolizumab pegol, infliximab, golimumab); pyr, person-years; SpA, spondyloarthritis (including psoriatic arthritis and ankylosing spondylitis); TNFi, tumour necrosis factor inhibitor.
Secondary analyses
Separate analyses in subgroups of patients defined by indication (PsA vs AS/SpA) for all neuroinflammatory events revealed that crude IRs were higher in AS/SpA than in PsA, respectively, 0.79 and 0.52 per 1000 person-years, but for both indications the rates with etanercept did not differ significantly from those of oTNFi (online supplemental table 1).
rmdopen-2022-002924supp001.pdf (94.5KB, pdf)
When analysing individual TNFis, the crude IRs of all neuroinflammatory events ranged from 0.60 (0.44–0.82) per 1000 person-years for infliximab to 0.82 (0.46–1.49) for certolizumab pegol (table 6). Analyses of specific neuroinflammatory outcomes were performed without Danish data, which included too few events, and provided HRs that were either close to 1 or uninterpretable due to large CIs (data not shown).
Table 6.
Number of events, person-years, crude incidence rates (95% CL) and HR (95% CI) obtained from Cox regression comparing each TNFi with etanercept for the combined outcome (any neuroinflammatory event) and in patients with SpA
| Events, n | Person-years | Crude incidence rates per 1000 person-years (95% CL) | Meta-analysis HR (95% CI) |
|
| TNFi | ||||
| Etanercept | 51 | 78 390 | 0.65 (0.49–0.86) | Reference |
| Adalimumab | 58 | 81 436 | 0.71 (0.55–0.92) | 1.07 (0.71 to 1.60) |
| Certolizumab pegol | 11 | 13 363 | 0.82 (0.46–1.49) | 1.36 (0.64 to 2.91) |
| Golimumab | 19 | 26 930 | 0.71 (0.45–1.11) | 1.16 (0.64 to 2.09) |
| Infliximab | 40 | 66 629 | 0.60 (0.44–0.82) | 0.98 (0.62 to 1.55) |
CL, confidence limits; SpA, spondyloarthritis (including psoriatic arthritis and ankylosing spondylitis); TNFi, tumour necrosis factor inhibitor.
Sensitivity analyses
The three sensitivity analyses (applying an ‘on-drug’ approach, selecting patients on their first ever TNFi and starting the follow-up with a 3-month delay) had minor impact on the HRs (online supplemental table 2). Stratifying the follow-up time (less than 1 year, 1–5 years, more than 5 years) did not reveal any clear heterogeneity in the crude IRs over time, the comparison of the IRs should take the low number of events into account. (online supplemental table 3).
Discussion
In this study, including more than 60 000 patients with RA or SpA from the five Nordic countries and almost 100 000 treatment episodes of TNFis, we did not observe any statistical difference in the rates of neuroinflammatory events by type of TNFi drug, although among the eight combinations of outcome types and treatment indications under study a higher rate of IPN with oTNFi versus etanercept was observed in patients with RA (but not in SpA).
We hypothesised that etanercept could differ from the other TNFis in the association with neuroinflammatory disorders since its inhibitory effect on TNF molecules differs from that of other TNFis. Etanercept has been shown to be less effective than the other TNFis in blocking tmTNF, involved in remyelination, while all TNFis are similarly effective in blocking sTNF, which promotes inflammation.14–16 However, our results did not highlight any clear evidence of any clinically meaningful difference in risk with oTNFi than with etanercept. Comparative studies in this field have used TNFi treatment as one group.23 24 Case and small series reports have presented individual TNFis separately but have been solely descriptive and without any comparator.32 Thus, and to our knowledge, this is the first study to address the comparison of rates of demyelinating events by type of TNFi.
Aside from comparing etanercept with oTNFi, we also compared each individual TNFi, without observing any signal for a particular drug for all neuroinflammatory events, although for IPN and in RA only infliximab was associated with a threefold increased rate compared with etanercept, although with a large CI. Indeed, the finding of an increased risk for IPN in RA, but not in SpA, was unexpected and to our knowledge has not been previously reported. Our IPN definition included the ICD-10 code G61.9, that is, unspecified IPN, which may have inflated the number of events, which could be reported more often in patients treated for more severe RA, and for this reason preferably treated with infliximab compared with etanercept, and thus by nature not necessarily confined to drug-induced events.33 Either way, this finding, based on few events, calls for replication.
Consistent with our previous findings and that of others, the crude rates of demyelinating events were higher in patients with SpA compared with patients with RA.23 34 35 Interestingly, however, the relative risks for etanercept versus oTNFi did not differ substantially by indication. Previous studies have shown an inverse association between RA and MS,36 while patients with psoriasis disease have been shown to be at higher risk for MS.37 Also, the age distributions in patients with RA versus SpA differ substantially (the latter around a decade younger than the former), and MS generally occurs sooner in the course of life than RA (also around a decade). In our data, the mean age of onset of MS was around 45 years of age for both patients with RA and patients with SpA. The differences in both age distributions and the genetics between patients with RA and patients with SpA might explain the lower incidence of neuroinflammatory (at least MS) events in RA compared with SpA.38
Neuroinflammatory outcomes are relatively rare events, around 100 times less common than, for example, hospitalisation due to infection,39 or around 8–10 times rarer than cardiovascular diseases.40 41 This represents a challenge to studying factors involved in the occurrence of such outcomes. Nevertheless, among the analyses that we could perform on individual drugs, none provided HRs that would suggest any of the TNFi drugs to be more (or less) associated to DML or MS than etanercept.
Our study has limitations. One single recorded visit with an outcome-defining ICD code was used to define each outcome. This may leave room for misclassification, also between each individual type of neuroinflammatory events.42 However, this would impact the IRs rather than the HRs as we have little reason to believe that such misclassification would differ between etanercept and oTNFi. We adjusted for a series of potential confounders, including age, sex, calendar year, disease duration, CRP and concomitant methotrexate, which did not substantially alter the estimates; however, we could not adjust for smoking status, which was characterised by a high percentage of missing values. In the event that smoking status differs between individual TNFi drugs, residual confounding may remain. We used data from a long calendar period, with a study period starting in 2001 when all drugs were not yet available. However, adjusting for calendar year in the analysis did not substantially change the results. All patients were free of neuroinflammatory disease at treatment start, but we did not have access to family history of such diseases. This study investigated a hypothesis regarding interdrug differences between individual TNF inhibitors. For this reason, we did not include data on non-TNFi bDMARD or tsDMARD treatment episodes. We also lack a comparator group from the general population, which would help to anchor our results. Data for MS in Sweden show that, at the mean age of our patients and taking the sex distribution into account, the IR of MS never exceeds 0.20 per 1000 person-years, which is less than the rate we observed in patients with SpA but higher than the rate in patients with RA.43 We combined data from several countries and verified that there was no significant heterogeneity between these, yet care should be taken in generalising our results to all patients with RA or SpA.
Our study has several strengths. We were able to collect a large number of patients with RA and SpA, and a large number of treatment courses, making this study among the largest on this topic. This allowed us to assess the risk of neuroinflammatory disorders by type of outcome, by type of treated condition and by type of TNFi drug. In addition, patients were followed for a long time; the median follow-up was between 5 and 6 years, which ensures sufficient time for observing rare events. The use of register data also ensured low risk of (differential) misclassification of exposure, outcomes and covariates. Further, we could investigate the robustness of our results through sensitivity and secondary analyses, which did not show any signal that contradicted our main results.
In conclusion, the IRs of neuroinflammatory events were higher in SpA as compared with RA, all between 1/10 000 and 1/1000 person-years. However, the choice of specific TNFi drug does not seem to play an important role in the risk of neuroinflammatory events.
Acknowledgments
We would like to thank all patients and clinical departments contributing to DANBIO, ICEBIO, ROB-FIN, NOR-DMARD and SRQ-ARTIS.
Footnotes
Twitter: @elizabetharkema
Presented at: The study was presented as an oral presentation at the EULAR conference in June 2022 (OP0060).
Contributors: Substantial contribution to conception and design: all coauthors. Analysis and data management: BD, JL, TIK. Interpretation of data: all coauthors. Drafting the article: BD, TIK, EVA, KH, JA. Revising it critically: all coauthors. Reading and approval of the final version: all coauthors.
Funding: This work was supported by NordForsk and the Foundation for Research in Rheumatology (Foreum) and Vinnova. The research infrastructure was supported by funds from the Swedish Research Council, the Swedish Heart Lung Foundation and the Swedish Cancer Society, and funds from Region Stockholm-Karolinska Institutet (ALF). The Center for Treatment of Rheumatic and Musculoskeletal Diseases (REMEDY) (Norway) is funded as a Centre for Clinical Treatment Research by the Research Council of Norway (project 328657).
Competing interests: BD: partly employed by the ARTIS national safety monitoring system (AbbVie, AstraZeneca, BMS, Eli Lilly, Galapagos, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi and UCB). TIK: has received congress participation support from Biogen and advisory board fee for Novartis. KH: clinical assessor at the Swedish Product Agency. SAP: grants and support for attending meeting from Boehringer Ingelheim. HR: consultant and lecture fees for AbbVie, Pfizer, UCB and Viatris. BG: consultant and lecturer fee for Novartis and Nordic Pharma. LD: grant from BMS outside the present work; support for attending meetings from Galderma, AbbVie, Eli Lilly and Janssen. JA: grants from AbbVie, AstraZeneca, BMS, Eli Lilly, Galapagos, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi and UCB; AbbVie, AstraZeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi and UCB have entered into agreements with Karolinska Institutet with JA as the principal investigator, mainly in the context of safety monitoring of biologics via the ARTIS national safety monitoring system.
Provenance and peer review: Not commissioned; externally peer reviewed.
Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
Data availability statement
Data are available upon reasonable request. Data from Finland, Iceland, Norway and Sweden are available upon reasonable request but access is regulated by the legal framework of the register linkages performed; Danish data are not available.
Ethics statements
Patient consent for publication
Not required.
Ethics approval
Approval from the data protection agencies and registry holders and/or ethics approvals were provided by the relevant authorities in each country.
References
- 1.Gossec L, Baraliakos X, Kerschbaumer A, et al. EULAR recommendations for the management of psoriatic arthritis with pharmacological therapies: 2019 update. Ann Rheum Dis 2020;79:700–12. 10.1136/annrheumdis-2020-217159 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Smolen JS, Landewé RBM, Bijlsma JWJ, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Ann Rheum Dis 2020;79:685–99. 10.1136/annrheumdis-2019-216655 [DOI] [PubMed] [Google Scholar]
- 3.van der Heijde D, Ramiro S, Landewé R, et al. 2016 update of the ASAS-EULAR management recommendations for axial spondyloarthritis. Ann Rheum Dis 2017;76:978–91. 10.1136/annrheumdis-2016-210770 [DOI] [PubMed] [Google Scholar]
- 4.TNF neutralization in MS . TNF neutralization in ms: results of a randomized, placebo-controlled multicenter study. Neurology 1999;53:457. 10.1212/WNL.53.3.457 [DOI] [PubMed] [Google Scholar]
- 5.Chey SY, Kermode AG. Central nervous system demyelination related to tumour necrosis factor alpha inhibitor. Mult Scler J Exp Transl Clin 2022;8:20552173211070750. 10.1177/20552173211070750 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Gharib MH, AlKahlout MA, Garcia Canibano B, et al. Demyelinating neurological adverse events following the use of anti-TNF-α agents: a double-edged sword. Case Rep Neurol Med 2022;2022:3784938. 10.1155/2022/3784938 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Ożóg MK, Grabarek BO, Wierzbik-Strońska M, et al. Neurological complications of biological treatment of psoriasis. Life (Basel) 2022;12:118. 10.3390/life12010118 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Theibich A, Dreyer L, Magyari M, et al. Demyelinizing neurological disease after treatment with tumor necrosis factor alpha-inhibiting agents in a rheumatological outpatient clinic: description of six cases. Clin Rheumatol 2014;33:719–23. 10.1007/s10067-013-2419-8 [DOI] [PubMed] [Google Scholar]
- 9.van Oosten BW, Barkhof F, Truyen L, et al. Increased MRI activity and immune activation in two multiple sclerosis patients treated with the monoclonal anti-tumor necrosis factor antibody Ca2. Neurology 1996;47:1531–4. 10.1212/wnl.47.6.1531 [DOI] [PubMed] [Google Scholar]
- 10.Brambilla R, Ashbaugh JJ, Magliozzi R, et al. Inhibition of soluble tumour necrosis factor is therapeutic in experimental autoimmune encephalomyelitis and promotes axon preservation and remyelination. Brain 2011;134(Pt 9):2736–54. 10.1093/brain/awr199 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Dendrou CA, Bell JI, Fugger L. A clinical conundrum: the detrimental effect of TNF antagonists in multiple sclerosis. Pharmacogenomics 2013;14:1397–404. 10.2217/pgs.13.140 [DOI] [PubMed] [Google Scholar]
- 12.Kemanetzoglou E, Andreadou E. Cns demyelination with TNF-α blockers. Curr Neurol Neurosci Rep 2017;17:36. 10.1007/s11910-017-0742-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kristensen LB, Lambertsen KL, Nguyen N, et al. The role of non-selective TNF inhibitors in demyelinating events. Brain Sci 2021;11:38. 10.3390/brainsci11010038 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Horiuchi T, Mitoma H, Harashima S, et al. Transmembrane TNF-alpha: structure, function and interaction with anti-TNF agents. Rheumatology (Oxford) 2010;49:1215–28. 10.1093/rheumatology/keq031 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kaymakcalan Z, Sakorafas P, Bose S, et al. Comparisons of affinities, avidities, and complement activation of adalimumab, infliximab, and etanercept in binding to soluble and membrane tumor necrosis factor. Clin Immunol 2009;131:308–16. 10.1016/j.clim.2009.01.002 [DOI] [PubMed] [Google Scholar]
- 16.Mitoma H, Horiuchi T, Tsukamoto H, et al. Molecular mechanisms of action of anti-TNF-α agents-comparison among therapeutic TNF-α antagonists. Cytokine 2018;101:56–63. 10.1016/j.cyto.2016.08.014 [DOI] [PubMed] [Google Scholar]
- 17.Scallon B, Cai A, Solowski N, et al. Binding and functional comparisons of two types of tumor necrosis factor antagonists. J Pharmacol Exp Ther 2002;301:418–26. 10.1124/jpet.301.2.418 [DOI] [PubMed] [Google Scholar]
- 18.Boussaid S, Rahmouni S, Rekik S, et al. Acute transverse myelitis revealing ankylosing spondylitis: a case report and literature review. Clin Case Rep 2021;9:e04878. 10.1002/ccr3.4878 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Figueroa Rodriguez F, Minkyung K, Jinna S, et al. Rheumatoid meningoencephalitis: a feared condition in the era of TNF blockers. Case Rep Rheumatol 2018;2018:4610260. 10.1155/2018/4610260 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Gherghel N, Stan A, Stan H. Pearls & Oy-sters: rheumatoid meningitis occurring during treatment with etanercept. Neurology 2018;91:806–8. 10.1212/WNL.0000000000006397 [DOI] [PubMed] [Google Scholar]
- 21.Matsuura-Otsuki Y, Hanafusa T, Yokozeki H, et al. Infliximab-induced aseptic meningitis during the treatment of psoriatic arthritis. Case Rep Dermatol 2017;9:26–9. 10.1159/000458405 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Tsuzaki K, Nakamura T, Okumura H, et al. Rheumatoid meningitis occurring during etanercept treatment. Case Rep Neurol Med 2017;2017:7638539. 10.1155/2017/7638539 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Kopp TI, Delcoigne B, Arkema EV, et al. Risk of neuroinflammatory events in arthritis patients treated with tumour necrosis factor alpha inhibitors: a collaborative population-based cohort study from Denmark and Sweden. Ann Rheum Dis 2020;79:566–72. 10.1136/annrheumdis-2019-216693 [DOI] [PubMed] [Google Scholar]
- 24.Kunchok A, Aksamit AJ Jr, Davis JM, et al. Association between tumor necrosis factor inhibitor exposure and inflammatory central nervous system events. JAMA Neurol 2020;77:937–46. 10.1001/jamaneurol.2020.1162 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Aaltonen KJ, Joensuu JT, Pirilä L, et al. Drug survival on tumour necrosis factor inhibitors in patients with rheumatoid arthritis in Finland. Scand J Rheumatol 2017;46:359–63. 10.1080/03009742.2016.1234641 [DOI] [PubMed] [Google Scholar]
- 26.Eriksson JK, Askling J, Arkema EV. The Swedish rheumatology quality register: optimisation of rheumatic disease assessments using register-enriched data. Clin Exp Rheumatol 2014;32(5 Suppl 85):S–147 [PubMed] [Google Scholar]
- 27.Ibfelt EH, Jensen DV, Hetland ML. The Danish nationwide clinical register for patients with rheumatoid arthritis: DANBIO. Clin Epidemiol 2016;8:737–42. 10.2147/CLEP.S99490 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Ibfelt EH, Sørensen J, Jensen DV, et al. Validity and completeness of rheumatoid arthritis diagnoses in the nationwide DANBIO clinical register and the Danish national patient registry. Clin Epidemiol 2017;9:627–32. 10.2147/CLEP.S141438 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Kvien TK, Lie E, Kaufmann C, et al. A norwegian DMARD register: prescriptions of dmards and biological agents to patients with inflammatory rheumatic diseases. Clin Exp Rheumatol 2005;23(5 Suppl 39):S188–94. [PubMed] [Google Scholar]
- 30.Thorsteinsson B, Geirsson AJ, Krogh NS, et al. Outcomes and safety of tumor necrosis factor inhibitors in reactive arthritis: a nationwide experience from Iceland. J Rheumatol 2020;47:1575–81. 10.3899/jrheum.191307 [DOI] [PubMed] [Google Scholar]
- 31.Chatzidionysiou K, Hetland ML, Frisell T, et al. Opportunities and challenges for real-world studies on chronic inflammatory joint diseases through data enrichment and collaboration between national registers: the Nordic example. RMD Open 2018;4:e000655. 10.1136/rmdopen-2018-000655 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Deepak P, Stobaugh DJ, Sherid M, et al. Neurological events with tumour necrosis factor alpha inhibitors reported to the food and drug administration adverse event reporting system. Aliment Pharmacol Ther 2013;38:388–96. 10.1111/apt.12385 [DOI] [PubMed] [Google Scholar]
- 33.Tsouni P, Bill O, Truffert A, et al. Anti-Tnf alpha medications and neuropathy. J Peripher Nerv Syst 2015;20:397–402. 10.1111/jns.12147 [DOI] [PubMed] [Google Scholar]
- 34.Kaltsonoudis E, Pelechas E, Voulgari PV, et al. Neuroinflammatory events after anti-tnfα therapy. Ann Rheum Dis 2022;81:e73. 10.1136/annrheumdis-2020-217723 [DOI] [PubMed] [Google Scholar]
- 35.Kaltsonoudis E, Zikou AK, Voulgari PV, et al. Neurological adverse events in patients receiving anti-TNF therapy: a prospective imaging and electrophysiological study. Arthritis Res Ther 2014;16:R125. 10.1186/ar4582 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Somers EC, Thomas SL, Smeeth L, et al. Are individuals with an autoimmune disease at higher risk of a second autoimmune disorder? Am J Epidemiol 2009;169:749–55. 10.1093/aje/kwn408 [DOI] [PubMed] [Google Scholar]
- 37.Islam MM, Poly TN, Yang HC, et al. Increase risk of multiple sclerosis in patients with psoriasis disease: an evidence of observational studies. Neuroepidemiology 2019;52:152–60. 10.1159/000495112 [DOI] [PubMed] [Google Scholar]
- 38.Olafsson S, Stridh P, Bos SD, et al. Fourteen sequence variants that associate with multiple sclerosis discovered by meta-analysis informed by genetic correlations. NPJ Genom Med 2017;2:24. 10.1038/s41525-017-0027-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Aaltonen KJ, Joensuu JT, Virkki L, et al. Rates of serious infections and malignancies among patients with rheumatoid arthritis receiving either tumor necrosis factor inhibitor or rituximab therapy. J Rheumatol 2015;42:372–8. 10.3899/jrheum.140853 [DOI] [PubMed] [Google Scholar]
- 40.Bengtsson K, Forsblad-d’Elia H, Lie E, et al. Are ankylosing spondylitis, psoriatic arthritis and undifferentiated spondyloarthritis associated with an increased risk of cardiovascular events? A prospective nationwide population-based cohort study. Arthritis Res Ther 2017;19:102. 10.1186/s13075-017-1315-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Delcoigne B, Ljung L, Provan SA, et al. Short-Term, intermediate-term and long-term risks of acute coronary syndrome in cohorts of patients with RA starting biologic dmards: results from four Nordic countries. Ann Rheum Dis 2022;81:789–97. 10.1136/annrheumdis-2021-221996 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Kalén E, Piehl F, Andersson M. Demyelinating events following anti-tumor necrosis factor alpha therapy: rare but challenging to treat. Eur J Neurol 2022;29:2047–55. 10.1111/ene.15318 [DOI] [PubMed] [Google Scholar]
- 43.Ahlgren C, Odén A, Lycke J. High nationwide incidence of multiple sclerosis in Sweden. PLoS One 2014;9:e108599. 10.1371/journal.pone.0108599 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
rmdopen-2022-002924supp001.pdf (94.5KB, pdf)
Data Availability Statement
Data are available upon reasonable request. Data from Finland, Iceland, Norway and Sweden are available upon reasonable request but access is regulated by the legal framework of the register linkages performed; Danish data are not available.