Rituximab is a monoclonal antibody that targets CD20+ B cells. After rituximab infusion, B-cell depletion usually ensues, mainly of B memory cells, with a subsequent reduction of IgG production and of B effector cells, resulting in a lower production of IgM. Furthermore, a secondary effect on T helper cell response has also been described.1 Rituximab is widely used for treating rheumatic diseases (RMDs) such as systemic sclerosis, systemic lupus erythematosus, Sjögren syndrome, and idiopathic inflammatory myopathies, although it has only been approved for treating rheumatoid arthritis (RA), microscopic polyangiitis, and granulomatosis with polyangiitis.
The effect of rituximab on B-cell response has been studied, focusing on the possible associated higher rates of infection and the lower seroconversion rates after vaccination in treated patients. A lower IgG response has been previously described after influenza and pneumococcal vaccination in patients with RA.2 Retrospective studies have reported a higher infection rate in RA patients treated with rituximab compared with other biologics such as abatacept or tocilizumab.3
Whether patients with RMD have a higher risk for severe COVID-19, especially those receiving rituximab treatment, has been a matter of debate since the start of the pandemic. Initial case reports and small cohorts reported a possible increase in the risk of severe SARS-CoV-2 infection in patients treated with rituximab.4 This finding has not been consistently observed in larger cohorts.5 Only the COVID-19 Global Rheumatology Alliance registry, which evaluated factors associated with COVID-19–related deaths, found rituximab exposure to be an independent risk factor.6
A recent case report highlighted the lack of seroconversion and possibility of reinfection in patients treated with rituximab.7 After the first COVID-19 wave (polymerase chain reaction [PCR] detection was not widely available initially), Madrid was a registered high impact area with official data showing more than 390,242 infected people and 19,291 infection-related deaths until December 22, 2020.8
Seroconversion after possible SARS-CoV-2 infection, in a cohort of unvaccinated RMD patients treated with rituximab in a high impact area, has not previously been described.
METHODS
Study Design
Medical records review study of a cohort of patients with an RMD followed up at the Rheumatology Department of the Ramón y Cajal University Hospital (Madrid, Spain), who had undergone a serological test for anti–SARS-CoV-2 IgG between April 15, 2020 and December 22, 2020. Positivity rate for anti–SARS-CoV-2 IgG and predictors of a positive serological result were analyzed in rituximab-treated patients and compared with those not treated with rituximab.
The current study was a subanalysis of a larger study of SARS-CoV-2 infection in RMD patients (study number 136/20), approved by the local ethics committee (Comité de Ética de Investigación con Medicamentos del Hospital Universitario Ramón y Cajal) on May 5, 2020. All patients provided informed consent to participate and for publication of data before their inclusion. The research was conducted in compliance with the Helsinki Declaration.
Patients
Patients aged >16 years, regardless of previous COVID-19 history, were included. Patients with an RMD treated with targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs) or biological tsDMARDS (bDMARDs), rather than rituximab or TNF inhibitor were excluded (Figure). Patients were classified into 2 groups according to rituximab treatment in the previous year (RTX group and n-RTX group). History of confirmed/suspected COVID-19 and serological test result for anti–SARS-CoV-2 were recorded. Patients treated with corticosteroids, conventional DMARDs (cDMARDs), and/or TNF inhibitor constituted the control group (n-RTX group).
FIGURE.
Patient selection. RTX group, patients treated with rituximab; n-RTX group, patients treated with TNF inhibitors, cDMARDs, and/or corticosteroids; *Other bDMARDs rather than rituximab or TNF inhibitor.
Rheumatic disease diagnosis, age at diagnosis, age at time of serological test for SARS-CoV-2, comorbidities, interstitial lung involvement, previous suspected/confirmed COVID-19, and previous PCR determination were documented at inclusion.
Rheumatic disease diagnosis was divided into 2 subgroups for the purpose of data analysis: arthropathies and connective tissue diseases. Arthropathies included RA (and secondary Sjögren syndrome), psoriatic arthritis, juvenile idiopathic arthritis, spondyloarthropathies, gout, and polymyalgia rheumatica. Connective tissue diseases included systemic sclerosis, inflammatory myopathies, systemic lupus erythematosus, vasculitis, and primary Sjögren syndrome.
Variables and Operative Definitions
Rate of anti–SARS-CoV-2 IgG positivity was considered the primary end point of the study, defined as the percentage of patients having a positive serological result in each group (also calculated according to previous history of confirmed or suspected COVID-19). Confirmed COVID-19 was considered in patients with at least 2 symptoms: a positive PCR for SARS-CoV-2 and/or a compatible chest x-ray. Suspected COVID-19 was diagnosed in patients presenting with at least 2 symptoms suggestive of SARS-CoV-2 infection.
Serological Test
One SARS-CoV-2 antibody assay was available in the hospital’s routine laboratory and was used during the study. A chemiluminescent microparticle immunoassay for SARS-CoV-2 IgG was used (SARS-CoV-2 IgG for use with ARCHITECT; Abbott Laboratories, Abbott Park, IL; reference 06R8620). This is a qualitative assay for the detection of IgG antibodies against the SARS-CoV-2 nucleocapsid protein (N-IgG) in human serum and plasma. Positivity of anti N-IgG is defined by an index >1.40.
Statistical Analysis
Categorical variables were reported as proportions and/or percentages, whereas continuous variables were expressed as the mean and standard deviation (SD) or median values and interquartile ranges (IQRs), for normally or nonnormally distributed variables, respectively. The Mann-Whitney U test, Student t test, and χ2 test were used to compare data (RTX and n-RTX groups), when appropriate. A multivariate logistic regression model was plotted to identify the association of rituximab treatment and a positive anti–SARS-CoV-2 IgG result. Odds ratios (ORs) were calculated with 95% confidence interval and adjusting for potential confounding factors. Variables were selected if they modified the crude OR by more than 10%. Statistical significance was assumed at a p value <0.05. Independent variables were selected for the multivariate model based on clinical judgment or if the p value was <0.20 in the bivariate analysis. Multicollinearity among independent variables was also explored, using Pearson and Spearman correlations to build the model. All the analyses were performed using the SPSS 25.0 statistical program.
RESULTS
One-hundred fifty-two patients were included, 48 of whom were on rituximab treatment. The demographic and clinical characteristics of patients included in the study and the bivariate analysis comparing the RTX and n-RTX groups are summarized in Table 1.
TABLE 1.
Demographic and Clinical Characteristics
| Rituximab (RTX = 48) | No Rituximab (n-RTX = 104) | Total Cohort (n = 152) | p value | |
|---|---|---|---|---|
| Patients, n (%) | 48/152 (31.6) | 104/152 (68.4) | 152/152 (100) | — |
| Age at inclusion, mean (SD), y | 62.3 (14.9) | 58.4 (17.5) | 59.6 (16.8) | p = 0.190 |
| Female, n (%) | 38 (79.2) | 74 (71.2) | 112/152 (73.7) | p = 0.297 |
| Diagnosis, n (%) | ||||
| Arthropathies | 25 (52.1) | 58 (55.8) | 83/152 (54.6) | p = 0.727 |
| Connective tissue diseases | 23 (47.9) | 46 (44.2) | 69/152 (45.4) | |
| Comorbidities, n (%) | ||||
| Hypertension | 18 (37.5) | 34 (32.7) | 52/152 (34.2) | p = 0.561 |
| Diabetes | 5 (10.4) | 10 (9.6) | 15/152 (9.9) | p = 0.878 |
| Dyslipidemia | 18 (37.5) | 30 (28.8) | 48/152 (31.6) | p = 0.286 |
| COPD/asthma | 6 (12.5) | 4 (3.8) | 10/152 (6.6) | p = 0.045* |
| CVD | 11 (22.9) | 25 (24) | 36/152 (23.7) | p = 0.831 |
| ILD, n (%) | 17 (35.4) | 8 (7.7) | 25/152 (16.4) | p < 0.0001* |
| CCs, n (%) | 26 (54.2) | 33 (31.7) | 59/152 (38.8) | p = 0.008* |
| CCs, median (IQR), mg/d | 5 (5–10) | 5 (3.8–8.8) | 5 (5–10) | p = 0.217 |
| cDMARDs, n (%) | 27 (56.3) | 73 (70.2) | 100/152 (65.8) | p = 0.092 |
| bDMARDs, n (%) | ||||
| None | 0 (0) | 82 (78.8) | 82/152 (53.9) | p < 0.0001* |
| TNF inhibitor | 0 (0) | 22 (21.2) | 22/152 (14.5) | |
| Rituximab | 48 (100) | 0 (0) | 48/152 (31.6) | |
| Previous PCR, n (%) | ||||
| No previous PCR | 29 (60.4) | 72 (69.2) | 101/152 (66.4) | p = 0.191 |
| Negative | 11 (22.9) | 12 (11.5) | 23/152 (15.1) | |
| Positive | 8 (16.7) | 20 (19.2) | 28/152 (18.4) | |
| Time from positive PCR to serological test, median (IQR), d | 43.5 (10.5–89.3) | 62.5 (18.3–88-3) | 63 (19–90.5) | p = 0.574 |
| Previous symptoms, n (%) | 13 (27.1) | 36 (34.6) | 49/152 (32.2) | p = 0.356 |
| Time from symptoms to serological test, mean (SD), d | 107 (44–238-5) | 80.5 (32.8–124.3) | 92 (35.5–155) | p = 0.181 |
| COVID-19, n (%) | ||||
| No suspected | 35 (72.9) | 66 (63.5) | 101/152 (66.4) | p = 0.183 |
| Suspected | 3 (6.3) | 18 (17.3) | 21/152 (13.8) | |
| Confirmed | 10 (20.8)a | 20 (19.2) | 30/152 (19.7) |
aTwo patients had a negative PCR but compatible chest x-ray and symptoms requiring hospitalization.
cDMARDs, conventional disease-modifying anti-rheumatic drugs; CCs, corticosteroids; CI, confidence interval; COPD, chronic obstructive pulmonary disease; CVD, cardiovascular disease;IQR, interquartile ranges; ILD, interstitial lung disease; PCR, Polymerase chain reaction; SD, stardard deviation.
Median age at inclusion was similar in the groups, 73.7% of patients were female. Regarding diagnosis, this was equally distributed, almost half of the patients were diagnosed with a connective tissue disease in both groups, but a higher rate of interstitial lung disease (ILD) was reported in the RTX group (RTX, 35.4%; n-RTX, 7.7%; p < 0.0001).
More than half of the patients in the RTX group were treated with corticosteroids, but median dose was not different between groups. Conventional DMARDs were more frequently prescribed to n-RTX patients, and 53.9% were neither treated with rituximab nor TNF inhibitor.
Only 33.5% of the cohort had a history of suspected and confirmed COVID-19. Rates of confirmed COVID-19 were similar between groups; however, a higher percentage of n-RTX patients had a history of suspected disease (n-RTX, 17.3%; RTX, 6.3%; p = 0.079).
Positivity Rate
Overall, seropositivity rate for anti–SARS-CoV-2 IgG was 25.7%. Among RTX and n-RTX groups, 8.3% (4/48) and 33.7% (35/104) (p = 0.01) had a positive anti–SARS-CoV-2 IgG, respectively. Four of 104 (3.8%) n-RTX patients tested positive without previous symptoms. No asymptomatic infections were diagnosed in the RTX group.
Univariable analysis showed a lower rate of positive anti–SARS-CoV-2 IgG in the RTX group with both confirmed (40%) and suspected (0%) infection compared with the n-RTX group, 80% and 83.3%, respectively (p = 0.045 and p = 0.015).
Multivariate Regression Model
A multivariate analysis was plotted to identify the effect of rituximab treatment on a negative anti–SARS-CoV-2 IgG result (Table 2). Rituximab treatment was the main factor associated with a negative IgG result, followed by older age at inclusion. Male sex and a previous positive SARS-CoV-2 PCR were identified as independent factors associated with a positive anti–SARS-CoV-2 IgG. The presence of ILD and cDMARDs use was retained in the model as confounding factors, whereas corticosteroids and previous chronic obstructive pulmonary disease were not included as they did not influence the main variable (RTX group).
TABLE 2.
Multivariate Analysis
| Total Cohort (n = 152) | ||
|---|---|---|
| OR (95% CI) | p value | |
| Sex (ref female) | 4.23 (1.55–11.50) | 0.005 |
| Age at inclusion, y | 0.97 (0.94–0.99) | 0.026 |
| ILD (ref no ILD) | 0.35 (0.08–1.47) | 0.151 |
| cDMARD (ref no cDMARD) | 1.61 (0.58–4.44) | 0.359 |
| Previous PCR (ref no previous PCR) | ||
| Negative | 1.98 (0.51–7.70) | 0.325 |
| Positive | 18.72 (5.20–67.43) | <0.0001 |
| RTX group (ref n-RTX) | 0.08 (0.02–0.37) | 0.001 |
cDMARDs, conventional disease-modifying anti-rheumatic drugs; CI, confidence interval; ILD, interstitial lung disease; OR, Odds Ratio; PCR, polymerase chain reaction; Ref, Reference; RTX, rituximab.
DISCUSSION
The current study found a lower seroconversion rate in the RTX group, regardless of previous COVID-19 history. To the authors' knowledge, this is the first study studying the anti–SARS-CoV-2 IgG rate in unvaccinated patients with RMD.
Overall seroprevalence was 25.7%, higher than the prevalence reported by the Spanish ENE-COVID study. In this population-based study that included 61,075 participants up to the May 11, 2020, seroprevalence in Madrid was 11.5%.9 No data have been published after that date; however, RMD patients in the current study, in contact with hospital care, could be at higher risk of infection. In this study, 3.8% asymptomatic infections were reported in the n-RTX group. A higher proportion was reported in the ENE-COVID study, with up to 35.8% of asymptomatic individuals.9
n-RTX patients, when previous COVID-19 was suspected or confirmed, had high seroconversion rates (80%–83%), similar to those reported in other studies.10 However, time from previous symptoms or positive PCR to serological determination was shorter than in the study by Noh et al,10 and positive anti–SARS-COV2 IgG rate could decline overtime and be lower at 6 months for the current cohort.
Few studies address seroconversion after COVID-19. The prospective COVISEP registry evaluated postinfection immune response in patients with multiple sclerosis and neuromyelitis optica spectrum disorders with 3 different tests (anti–S IgG, anti–S IgA, and anti–N IgG).11 Overall seroconversion rate after COVID-19 was similar to the current study, and anti-CD20 treatment was associated with a decreased odds of positive serology.11 Of note, time from the last anti-CD20 infusion was the only different variable in patients with positive and negative anti–SARS-CoV-2 IgG. No differences were found in the seroconversion rate between the tests.11 Louapre et al11 findings support the validity of our results, despite the fact that only the anti–N IgG test was available.
In the current study, older age at inclusion was independently associated with a negative serological result. A prospective study found older age was associated with persistently positive serological results, but no concise information about previous treatments and comorbidities were described.10
Male sex was associated with a positive serological result. In previous studies, sex was not found to be associated with different rates of seroconversion.10,11 In the current cohort, the subgroup of patients treated with TNF inhibitors was mostly represented by young males (57.1% of males; median age, 53 years; IQR, 39.5–66) who could have a preserved serological response.
Seroconversion in patients with RMD after vaccination, which was not available when the study was performed, has been extensively investigated. An impaired humoral response has been reported in several cases and in a retrospective study of patients treated with rituximab.12,13 A prospective Dutch study of patients with RMD found a delayed rather than impaired humoral response in RMD patients overall, but lower seroconversion rates in patients treated with anti-CD20.14 Thus, it is still unclear if T-cell responses, which could be preserved in patients with B-cell depletion, are representative of vaccine efficacy.15
Although a large cohort of patients with RMD treated with rituximab was included in this study, there was a low prevalence of confirmed COVID-19, hindering the identification of possible risk factors for negative or positive serological results. Not all the available bDMARDs were included, limiting the possibility of identification of other bDMARDs associated with an impaired serological response. Also, due to the study design, no factors associated with the possible source of infection were assessed, limiting the accurate evaluation of the prevalence of the disease and the differences with the overall population. However, the uniqueness of these results should be highlighted, the study was carried out after the first COVID-19 wave, where there was an extreme overload of inpatients and outpatients, systematic PCR detection was not possible, and only a qualitative serological antibody assay was available. Because of the high vaccination rates in Spain, there is a limited possibility of conducting similar studies in future.
CONCLUSIONS
In this cohort, rituximab treatment was the main factor associated with a negative anti–SARS-CoV-2 IgG. A lower positivity rate of anti–SARS-CoV-2 IgG was found in the RTX group, regardless of previous COVID-19 history. No asymptomatic infections were diagnosed, and no suspected COVID-19 cases were confirmed in the RTX group. Therefore, seroconversion should be assessed after COVID-19, and vaccination strategies should be reviewed in patients treated with rituximab.
ACKNOWLEDGMENTS
All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by all authors. The first draft of the manuscript was written by A.G.-F. and P.M.-A., and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. The authors wish to thank M.A. Martín-Martínez for her outstanding help in conducting the statistical design and analysis.
Footnotes
ORCID ID: https://orcid.org/0000-0003-3670-6796
The authors declare no conflict of interest.
Contributor Information
Patricia Morán-Álvarez, Email: moranalvarez@hotmail.es.
Javier Bachiller-Corral, Email: javierbachiller@gmail.com.
Mónica Vázquez-Díaz, Email: monicavazquezdiaz@yahoo.es.
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