BMJ€¦ · OBJECTIVE: Three non-tumor-necrosis factor-alpha (TNF) inhibitors — rituximab,...

Confidential: For Review Only

Emulated trial of non-TNF inhibitors- rituximab, abatacept,

and tocilizumab- in patients with rheumatoid arthritis and

inadequate response to TNF inhibitors

Journal: BMJ

Manuscript ID BMJ.2018.044168

Article Type: Research

BMJ Journal: BMJ

Date Submitted by the Author: 05-Apr-2018

Complete List of Authors: Gottenberg, Jacques-Eric; Hopital de Hautepierre, Morel, Jacques; Department of Rheumatology, Montpellier University Hospital, Montpellier, France Perrodeau, Elodie; CHU Hôtel Dieu, Centre d’épidémiologie clinique Bardin, Thomas; Department of Rheumatology, Lariboisière Hospital, Paris, France Combe, Bernard; Montpelier University Hospital, Departement de rhumatologie Dougados, Maxime; Dept of Rheumatology; Flipo, René-Marc; CHU Roger Salengro Hospital, Rheumatology Saraux, Alain; Department of Rheumatology, University Hospital, Brest, France Schaeverbeke, Thierry; Pellegrin Hospital, Rheumatology Sibilia, Jean; Hôpitaux Universitaires de Strasbourg, Service de Rhumatologie Soubrier, Martin; CHU, Rheumatology Vittecoq, Olivier ; Department of Rheumatology, University Hospital, Rouen, France Baron, Gabriel; INSERM APHP University Paris Descartes Constantin, Arnaud; Department of Rheumatology, University Hospital, Toulouse, France Ravaud, Philippe ; Department of Epidemiology and Public Health, Hotel Dieu, Assistance Publique des Hôpitaux de Paris (APHP), Paris, France Mariette, Xavier; Université Paris-Sud,

Keywords: rheumatoid arthritis, registry, comparative effectiveness

https://mc.manuscriptcentral.com/bmj

BMJ


Emulated trial of non-TNF inhibitors- rituximab, abatacept, and tocilizumab- in patients with rheumatoid arthritis and inadequate response to TNF

inhibitors

Jacques-Eric Gottenberg1, Jacques Morel2, Elodie Perrodeau3, Thomas Bardin4, Bernard Combe2, Maxime Dougados5, Rene-Marc Flipo6, Alain Saraux7,

Thierry Schaeverbeke8, Jean Sibilia1, Martin Soubrier9, Olivier Vittecoq10, Gabriel Baron3, Arnaud Constantin11, Philippe Ravaud3,*, Xavier Mariette12*, on behalf

of the French Society of Rheumatology and of all the investigators participating to the AIR, ORA and REGATE registries

1 Department of Rheumatology, National Center For Rare Systemic Autoimmune Diseases, Strasbourg University Hospital, IBMC, CNRS, Strasbourg University, Strasbourg, France

2 Department of Rheumatology, Montpellier University Hospital, Montpellier, France

3 Department of Epidemiology and Public Health, Hotel Dieu, Assistance Publique des Hôpitaux de Paris (APHP), Paris, France

4 Department of Rheumatology, Lariboisière Hospital, Paris, France

5 Department of Rheumatology, Cochin Hospital, Paris, France

6Department of Rheumatology, University Hospital, Lille, France

7Department of Rheumatology, University Hospital, Brest, France

8Department of Rheumatology, University Hospital, Bordeaux, France

9Department of Rheumatology, University Hospital, Clermont Ferrand, France

10Department of Rheumatology, University Hospital, Rouen, France

11Department of Rheumatology, University Hospital, Toulouse, France

12Department of Rheumatology, Université Paris Sud, AP-HP, HôpitauxUniversitaires Paris-Sud, Center for Immunology of viral infections and autoimmune diseases (IMVA), INSERM U1184, Le Kremlin Bicêtre, France

* Contributed equally to the study

Running title : Emulated trial of non-TNF inhibitors in rheumatoid arthritis

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Corresponding authors:

Jacques-Eric Gottenberg, Department of Rheumatology, National Center For Rare Systemic Autoimmune Diseases, Strasbourg University Hospital, IBMC,

CNRS, Strasbourg University, 1 avenue Molière, 67000 Strasbourg, France; phone: +33 3 88 12 79 53; email: [email protected]

Xavier Mariette, Department of Rheumatology, Bicetre Hospital, 78 Av du Général Leclerc 94275 Le Kremlin Bicêtre, France; phone: +33 1 45 21 37 51;

email: [email protected]

Word count: 3574 words

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ABSTRACT OBJECTIVE: Three non-tumor-necrosis factor-alpha (TNF) inhibitors — rituximab, abatacept and tocilizumab — are widely used in patients with rheumatoid

arthritis (RA) and inadequate response to TNF inhibitors. No randomized, controlled trials comparing the effectiveness and safety of these 3 biologics have

been completed. To compare the effectiveness and safety of non-TNF inhibitors in patients with RA.

DESIGN: Large-scale, population-based, prospective study, with propensity score adjustment, and sensitivity analysis. The observational data were used to

emulate a target trial with 3 groups: rituximab, abatacept and tocilizumab.

SETTING: France.

PARTICIPANTS: 3162 patients with RA according to 1987 ACR criteria, age > 18 years, who had no severe cardiovascular disease, no active or severe

infections, no severe immunodeficiency with complete follow-up data at month 24.

INTERVENTION : Initiation of intravenous rituximab, abatacept or tocilizumab for rheumatoid arthritis.

MAIN OUTCOME MEASURE: Drug treatment retention without failure at month 24. Failure was defined as all-cause death; rituximab, abatacept, or

tocilizumab discontinuation; initiation of a new biologic or a combination of conventional disease-modifying anti-rheumatic drugs; or increase in corticosteroid

dose > 10 mg/d as compared with baseline at 2 successive visits.

RESULTS: At month 24, drug retention without failure was significantly greater with rituximab and tocilizumab than abatacept (hazard ratio 2.41 [95%

confidence interval: 1.96; 2.97]; p< 0.001, and 2.01 [1.41; 2.86], p< 0�001, respectively), with no significant difference between tocilizumab and rituximab.

Death or presence of cancer or serious infections did not significantly differ among the 3 drug treatments.

CONCLUSION: Among patients with refractory RA followed up in common practice, the effectiveness of rituximab or tocilizumab at 2 years was better than

that of abatacept.

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Funding source The French Society of Rheumatology had an unrestricted educational grant from Bristol-Myers Squibb (BMS), Roche and Chugai. BMS, Roche and Chugai

had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the

manuscript for publication.

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INTRODUCTION

Tumor-necrosis factor (TNF)-alpha inhibitors have greatly improved the daily life of patients with rheumatoid arthritis (RA) [1]. However, as much as one third

of patients fail to respond to anti-TNF agents. [2] Alternative and more recently approved non-TNF targeted biologic agents include rituximab (a B-cell–

depleting agent), abatacept (targeting T-cell costimulation), and tocilizumab (an interleukin-6 receptor inhibitor). These 3 drugs have demonstrated their

efficacy as compared with placebo but have not been compared against each other in randomized controlled trials (RCTs) [3-5]. Network meta-analyses of

randomized placebo-controlled trials were conducted, but they concern by definition highly selected patients [6-8].

Disease activity is usually higher and comorbidities are less frequent in RCTs than in real life. Co-treatment with methotrexate, known to improve the

effectiveness of biologics, is less frequent in real life than in RCTs. In addition, the primary outcomes of RCTs are evaluated in the short term (usually between

6 and 12 months). Therefore, the long-term drug retention rate and corticosteroid-sparing effect, 2 relevant markers of efficacy, cannot be analysed in RCTs.

Finally, the short-term follow-up in RCTs limits the analysis of serious adverse events, notably serious infections and cancers.

For all these reasons, registry data for drugs are useful to complement data from RCTs and investigate their external validity in terms of common practice.

Comparing the effectiveness and safety of biologics represents a further step that was performed in only a few studies mainly focusing on different anti-TNF

agents [9]. Most likely, randomized controlled head-to-head comparisons of rituximab, abatacept and tocilizumab will not be performed. Prospective academic

registries and comparative effectiveness research now allows for focusing on the so-far poorly addressed comparison of non-TNF targeted biologics.

The present study aimed to compare the efficacy of 3 non-TNF targeted therapies — rituximab, abatacept, and tocilizumab—in patients with long-standing

and refractory RA.

METHODS

Study data

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Prospective registries sponsored by the French Society of Rheumatology are Autoimmunity and Rituximab (AIR), Orencia and Rheumatoid Arthritis (ORA),

and REGistry–RoAcTEmra(REGATE). The 3 registries are strictly observational and non-interventional studies. The objectives of these registries are to

determine and compare the effectiveness and safety of intravenous rituximab, abatacept, and tocilizumab in common practice, aiming to enroll most patients

initiating these drugs in France as soon as the drugs were marketed.

The methodology of these registries was previously reported[10]. Their methodology was similar on purpose because we wanted to compare the 3 drugs.

Briefly, regular mail and “push” emails were sent by the French Society of Rheumatology to all French rheumatology departments and physicians prescribing

biologics in RA when each of these three biologics was approved; the emails asked for the physician’s agreement to participate in each registry. Such consent

involved agreement to 1) frequent visits by a trained clinical nurse to the hospital pharmacy to obtain the list of all patients receiving an intravenous infusion of

rituximab, abatacept, or tocilizumab in the physician’s department; 2)subsequent frequent access by clinical nurses to patient charts; 3) limiting missing data in

patient charts on key pre-specified items (treatment, disease activity score, etc.) and limiting the risk of lost to follow-up; and 4) allowing the French Society of

Rheumatology to directly contact the patient’s general practitioner, rheumatologist, or patients themselves to obtain missing follow-up data. In each registry,

26 trained clinical-study nurses visited each center to collect efficacy and safety data from patient charts at the same pre-specified intervals, independently

from disease severity or drug mode of administration: at drug initiation and at 3 months and every 6 months thereafter or at drug discontinuation andafter drug

discontinuation for 7 years. Even after drug discontinuation, a systematic follow-up for safety was performed. All information was drawn from the clinical

charts. Data were collected in an electronic case report form (www.air-cri.org; www.ora-cri.org; http://www.regate-sfr.org/index.htm). Two clinical research

assistants performed random on-site monitoring to control for the quality of collected data and to obtain data considered missing by study nurses. In addition,

a summary of collected data for key items for each enrolled patient was sent once a year to each center after the initiation of the registries. In case of serious

adverse events (death, cancers, serious infections defined as those requiring intravenous antibiotics and/or hospitalization and/or resulting in death, major

cardiovascular events [ie, death of cardiovascular origin, stroke, myocardial infarction]), study nurses were asked to send a copy of the chart to each registry

coordinator. All serious adverse events were adjudicated by the registry coordinators (JEG, JM and XM).

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The 3 registries were approved by an Institutional Review Board and regulatory authorities before data collection. Bristol-Myers Squibb for ORA and Roche for

AIR and Roche and Chugai for REGATE gave an unrestricted grant to the French Society of Rheumatology but had no role in the collection, analysis, or

interpretation of data. The study was conducted according to the current regulations of the International Conference on Harmonization guidelines and the

principles of the Declaration of Helsinki. Written informed consent was obtained from patients.

Treatment groups and follow-up

Using observational data, we emulated a trial to compare 3 groups of patients with RA (those initiating intravenous rituximab, abatacept or tocilizumab) at 24-

month follow-up[11].

Eligibility criteria

From September 2005 to August 2013, patients > 18 years old were recruited from 107 clinical centers in France. The inclusion criteria were diagnosis of RA

according to the 1987 American College of Rheumatology criteria, age >18 years and initiation of intravenous treatment with rituximab, abatacept, or

tocilizumab before March 2013 (to ensure a minimal theoretical follow up of 2 years for all patients). The exclusion criteria were contraindications to any the 3

biologics (rituximab, abatacept or tocilizumab): severe cardiovascular disease, active or severe infections, severe immunodeficiency, or prior use of any of

these 3 biologics. The list of all patients receiving intravenous rituximab, abatacept, or tocilizumab in each center was obtained from the pharmacist of each

hospital, so all consecutive patients receiving one of the 3 drugs at the time of the study were included in each center, which limited inclusion bias.

Endpoints

The primary endpoint was drug retention without failure at month 24. We added the notion of lack of failure ofdrug retention because for patients receiving

rituximab, a drug with intermittent administration, realizing retention in the absence of this complementary information on failure was difficult. Failure was

defined as all-cause death, discontinuation of the drug studied in the registry, and initiation of a combination of conventional disease-modifying anti-rheumatic

drugs (DMARDs)and/or a new biologic and/or increase of oral corticosteroids dose >10 mg/d at 2 consecutive visits as compared to the baseline dose.

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Secondary endpoints included European League Against Rheumatism (EULAR) response at months 6, 12 and 24. Good EULAR response was defined as a

decrease in Disease Activity Score in 28 joints–erythrocyte sedimentation rate (DAS28-ESR) > 1�2 points and resulting DAS28 ≤ 3�2. A moderate EULAR

response was defined as a decrease in DAS28-ESR > 0�6 points and resulting DAS28 ≤ 5�1. Because the data were not systematically recorded at exact

fixed times, we used a 2-month window (the closest information to the time within 2 months before or after this time).

Safety endpoints included time to first serious adverse events (among serious infection, major adverse cardiovascular events [MACEs], cancer, and death).

Each component of this composite endpoint was considered separately. A serious infection was defined as an infection requiring hospitalization and/or

intravenous antibiotics and/or resulting in death. MACEs were defined as death of cardiovascular origin, stroke, or myocardial infarction. Serious infections,

MACEs, cancer and death were considered in the analysis regardless of their time of occurrence, even after registry drug discontinuation.

Statistical analysis

We used a propensity-score approach to adjust for differences in observed factors that might affect both treatment assignment and outcome and to emulate

randomization. The propensity score was defined as the probability of receiving rituximab, abatacept, or tocilizumab based on patient covariates. Propensity

was estimated by using a multinomial model with the drug received as the dependent variable and the following baseline variables as independent variables:

age, disease duration, sex, history of: serious or recurrent infection, cancer, MACE, cardiac insufficiency, renal insufficiency, hepatic disease, respiratory

disease, extra-articular involvement, smoking, diabetes, arterial hypertension, dyslipidemia, gammaglobulin level, immunoglobulin G (IgG) and IgM levels,

neutropenia, positive rheumatoid factor or antibodies against cyclic citrullinated peptides (anti-CCPs), number of previous conventional synthetic DMARDs,

number of previous anti-TNF drugs received, disease activity at registry drug initiation (number of tender joints, number of swollen joints, ESR, C-reactive

protein [CRP] level, patient global assessment of disease activity, DAS28-ESR), co-treatment at registry drug initiation including concomitant conventional

synthetic DMARDs received and daily dose of corticosteroids, and number of patients receiving each treatment in the patient’s center. Covariate balance was

checked after adjustment.

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The primary analysis was based on inverse probability weighting [12]; each patient was weighted by the inverse propensity of their group. To increase

statistical efficiency and for better coverage of confidence intervals, we used stabilized weights [13]. We used multiple imputation by chained equation by

using all baseline variables of the propensity-score model as well as the drug received. Ten independent imputed datasets were generated. For each dataset,

a propensity score was estimated and the resulting scores were pooled according to Rubin’s rules.

Marginal models with robust estimation of variance were used to account for center clustering. Survival without drug failure was estimated by weighted

Kaplan-Meier product-limit estimator and compared by a marginal Cox model, with the drug (rituximab, abatacept, or tocilizumab) as the only covariate.

Hazard ratios (HRs) and their 95% confidence intervals (CIs) were calculated to quantify the between-group differences. Patients were analyzed in the groups

to which they were initially treated. Five sensitivity analyses were performed for the primary outcome. In the first analysis, we used an unweighted analysis.

The models for the weighted and unweighted analyses were identical except that each patient was weighted by the inverse of the propensity score in the

adjusted marginal Cox model. Second, we repeated the propensity-weighted comparisons by using patient as a unit of clustering instead of center. Third, to

evaluate the consistency of our analyses regarding the definition of failure, we used our marginal Cox model with 3 alternative definitions of failure; 1)death or

discontinuation of the registry drug; 2)death or initiation of a combination of conventional DMARDs or a biologic DMARD; 3)death or discontinuation of the

registry drug or initiation of a combination of conventional DMARDs or a biologic DMARD.

To compare EULAR response, we used logistic regression with weighted generalized estimating equations (GEEs), with drug as the only covariate. Non-

responder patients (because of discontinuation of the drug studied in the registry and/or initiation of a combination of conventional DMARDs and/or a new

biologic and/or increased dosage of oral corticosteroids > 10 mg/d at 2 consecutive visits) were considered EULAR non-responders.

Survival without serious adverse events was estimated globally and for each type of event (serious infection, MACE, cancer, death). Survival rates were also

compared by using a marginal Cox model.

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All tests were 2-sided and were considered statistically significant at alpha = 0�05. Statistical analyses involved use of SAS 9.4 (SAS Institute Inc., Cary, NC).

Graphs were computed by usingR 3�2�2 (R Core Team, 2015, R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/).

Role of the funding source The French Society of Rheumatology had an unrestricted educational grant from Bristol-Myers Squibb (BMS), Roche and Chugai. BMS,Roche and Chugai

had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the

manuscript for publication.

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RESULTS

Baseline characteristics of patients and follow-up

From September 2005 to June 2013, the AIR, ORA, and REGATE registries included 4134 patients (rituximab, 1947 patients from September 2005 to

January 2010; abatacept, 823 from January 2007 to October 2010; and tocilizumab, 1364 from April 2010 to June 2013) from 107 centers (53 university and

54 non-university centers) (AIR: 86 centers, ORA: 82 centers, REGATE: 77 centers, 53 centers participated to the 3 registries) (Figure 1). Among the 4134

enrolled patients, 3183 fulfilled the eligibility criteria for this emulated trial and data for 3162 could be analyzed at 24 months. The database was frozen in

March 2015 for the present analysis. Baseline characteristics for the 3 drug groups differed in the unweighted cohort (Table 1 and eTable 1), notably in

median [interquartile range (IQR)] disease duration (rituximab: 11 years [6; 18]; abatacept: 11years [5; 19]; tocilizumab: 8 years [3;16]);history of cancer

(14.4%, 5.3% and 4.2% of patients, respectively); rheumatoid factor positivity (80.5%, 75.0%, and 79.8% of patients, respectively); disease activity (mean [SD]

DAS28-ESR 5�5[1.2], 5.2[1.3], and 5.0[1.4] respectively);and concomitant treatment with a conventional DMARD (64.9%, 66.5%, and 59.5% of patients,

respectively) and with corticosteroids (prednisone: 77.7%, 74.4%, and 66.5% of patients, respectively).

Propensity-weighted analysis

Propensity scores were calculated for 3162 patients.. Weights ranged from 0.2 to 31.2. The weighted groups were well balanced for recorded baseline

variables, with standardized differences ranging from 0% to 25% and exceeding 10% for only 16 of the 99 comparisons (Table 1, eTable 1, eTable 2 and

eFigure 1). A standardized difference of 10% or more is generally considered meaningful[14].

Efficacy results

Table 2 describes the causes of failure (all-cause death, discontinuation of the registry drug, initiation of a combination of conventional DMARDs or a new

biologic, increase of oral corticosteroids dose> 10 mg/d at 2 consecutive visits compared to baseline). At month 24 (weighted cohort), 68.6% of patients [95%

CI: 65.3; 71.5] were still receiving rituximab without failure, 39.3% [34.1; 44.5] abatacept, and 63.4% [56.1; 69.8] tocilizumab. Drug retention without failure

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was significantly greater with rituximab and tocilizumab than abatacept (HR 2.41 [95% CI: 1.96; 2.97]; p< 0.001, and 2.01 [1.41; 2.86], p< 0�001, respectively),

with no difference between tocilizumab and rituximab (1.20 [0.88; 1.64], p= 0.251) (Table 3, Figure 2). At month 24, good or moderate EULAR response was

significantly more frequent in patients treated with rituximab or tocilizumab than in patients treated with abatacept (Table 4, eTable 3).

Safety

At month 24 (weighted cohort), 436 patients had experienced at least one adverse event including serious infection, MACE, cancer, or death: 224(14.5%) in

the rituximab group,101(16.2%) in the abatacept group, and 111(11.6%) in the tocilizumab group (Table 5). Survival without a serious adverse event did not

differ among the 3drug treatments at month 24 (Table 6 and Figure 3). The risk was not increased with abatacept (HR 1.13 [95% CI: 0.78; 1.63], p= 0.530) or

tocilizumab (0.89 [0.55; 1.42], p= 0.619) versus rituximab nor abatacept versus tociluzimab (1.27 [0.77; 2.09], p= 0.350).

Additional analyses

Sensitivity analysis findings in the overall cohort (unweighted, no center effect, 3 definitions of failure) were consistent with primary analysis findings based on

propensity adjustment (Figures 4, 5, 6).

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DISCUSSION

The present study revealed that drug retention without failure at month 24 for treating RA was better with rituximab or tocilizumab than abatacept. Drug

retention seems a good surrogate marker of the balance between effectiveness and adverse events and appears particularly adequate in registry studies and

relevant in common practice. We chose month 24 for the primary endpoint evaluation to have a long-term consideration of drug retention and because it

corresponded to the median follow-up in the most recent registry (the tocilizumab registry, which therefore had a higher rate of lost-to follow-up given its more

recent onset).

Only a few comparative effectiveness studies have examined rituximab, abatacept, and tocilizumab. They used limited population samples, compared disease

activity in the short term, and had discrepant results[15-19]. Very limited registry data are available regarding the retention rate of non-TNF targeted biologics,

notably for rituximab and tocilizumab. In a recent collaboration between nine European registries, including the French registry, the median crude retention

rate for abatacept varied from 1�4 and 2�1 years depending on autoantibody status[20], in agreement with the median abatacept retention rate in the present

study.

Randomized clinical trials are the standard strategy to compare drugs. However, although non-TNF biologics were compared to anti-TNF agents in a few

trials[21 22], no randomized clinical trial has ever compared rituximab, abatacept, and tocilizumab, and probably no direct head to head randomized clinical

trial will compare these 3 drugs in the future.

As in all observational studies, the main limitations of our study are lack of randomization and the channeling bias inherent in this type of study. Thus, using

observational data, we emulated a trial comparing 3 groups of patients with RA (those initiating intravenous rituximab, abatacept or tocilizumab) at 24-month

follow-up. Drug retention after adjustment of baseline factors is the most robust outcome for comparing patients from registries treated with different drugs. We

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used a propensity-score approach to adjust for differences in observed factors that might affect both treatment assignment and outcome and to emulate

randomization.

We included in the propensity score all collected baseline characteristics of patients in terms of comorbidities, previous treatments, disease activity, and co-

treatments to minimize the likelihood of observing incorrect associations. To test the robustness of our results, we used multiple sample populations

(unweighted and weighted cohorts) and outcome criteria. Results were consistent among these different approaches. Analysis of EULAR response yielded

similar results as for the primary endpoint. However, missing data and the differential effect of tocilizumab on acute-phase reactants included in the definition

of EULAR response as compared with abatacept and rituximab should be noted (the Clinical Disease Activity Index, which excludes acute-phase reactants, is

not collected in AIR and ORA).

Because we included patients treated with rituximab in the study, a drug for which it can be difficult to assess retention since given intermittently, we added the

concept of drug retention without failure where failure is defined by death or initiation of a new biologic or combination of conventional DMARDs, or marked

increase in oral corticosteroid dose. Differences in drug administration should also be considered, since evaluating monthly before their infusion might result in

an earlier decision to discontinue abatacept or tocilizumab compared to patients treated intermittently with rituximab. To limit the risk of favoring rituximab over

abatacept or tocilizumab, we chose a primary endpoint evaluation at month 24. Of interest, the possible bias of a different schedule of infusion concerns the

comparison of only abatacept and rituximab retention and not abatacept and tocilizumab retention (both drugs are given monthly).

Patients enrolled in the study were mostly refractory to previous treatment with anti-TNF agents. Therefore, the results of our study should not be extrapolated

to biologic (anti-TNF)-naïve patients (for whom abatacept and tocilizumab have marketing authorizations). In addition, all patients received intravenous

abatacept and tocilizumab. Therefore, the characteristics and comorbidities of outpatients who receive subcutaneous abatacept or tocilizumab might differ

from those of enrolled patients.

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The strengths of our registry data include its real-life setting (as reflected by the burden of comorbidities; in the ORA registry, only about 20% of patients would

have fulfilled all the inclusion criteria for at least one of the pivotal controlled trials[23]); the large number of unselected patients enrolled corresponding to most

non-TNF biologic initiators (eg,>85% of prescriptions of rituximab in non-hematology and non-oncology departments between 2005 and 2009[24]); enrollment

in university and non-university centers; the systematic collection at pre-specified time intervals of efficacy and safety data from patient charts independent of

any physician’s intervention; the inclusion of consecutive patients in each center without any bias because the list of patients was obtained from pharmacists;

the intravenous in-hospital administration of drugs, which ensures adherence to treatment and accurate information on baseline characteristics, drug retention,

and co-treatments; the long-term prospective follow-up; and centralized validation of serious adverse events.

The originality of this study is its evaluation of the effectiveness of non-TNF biologics in real life (most of the literature describes only the effect of methotrexate

and anti-TNF agents in this setting) and in providing some new insights into the benefit–risk ratio of non-TNF biologics. The 3 non-TNF biologics did not

significantly differ in serious adverse events. Serious adverse events were numerically more common for tocilizumab than for rituximab and abatacept.

Therefore, the observed higher drug retention rate of rituximab and tocilizumab than abatacept is related to greater effectiveness rather than a better safety

profile. About 30% (for rituximab and tocilizumab) to 60% (for abatacept) of patients discontinued their non-TNF target biologic at month 24, which

emphasizes the need to continue to enlarge the armamentarium of new biologic and targeted DMARDs in RA.

In this national registry-based cohort of patients with RA, drug retention without failure was greater with rituximab or tocilizumab than abatacept. These results

mostly concern patients with long-standing and refractory RA who previously received one or more biologics and not biologic agent-naïve patients with shorter

disease duration.

Author contributions: JEG, JM, PR, XM designed the study; EP, GB and PR made the statistical analyses; JEG, JM, TB, BC, MD, RMF, AS, TS, JS, MS, OV,

AC, PR, XM interpreted the data; JEG drafted the manuscript; all coauthors edited the manuscript.

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Conflict of interest statement for first and last authors and statisticians: JEG received research grants and honoraria (<10 000 USD) from Abbvie, BMS,

Janssen, MSD, UCB, Pfizer, Lilly and from Roche, XM received honoraria (<10 000 USD) from BMS, Pfizer and UCB. GB, EP and PR have no disclosures.

Role of the funding source: Bristol-Myers Squibb for ORA, Roche for AIR and REGATE and Chugai for REGATE gave an unrestricted grant to the French

Society of Rheumatology but had no role in the collection, analysis, or interpretation of data.

The study received approval from an Institutional Review Board and regulatory authorities before data collection.

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REFERENCES

1. Scott DL, Wolfe F, Huizinga TW. Rheumatoid arthritis. Lancet 2010;376(9746):1094-108 doi: 10.1016/S0140-

6736(10)60826-4[published Online First: Epub Date]|.

2. Hyrich KL, Lunt M, Watson KD, et al. Outcomes after switching from one anti-tumor necrosis factor alpha agent to

a second anti-tumor necrosis factor alpha agent in patients with rheumatoid arthritis: results from a large UK

national cohort study. Arthritis and rheumatism 2007;56(1):13-20 doi: 10.1002/art.22331[published Online

First: Epub Date]|.

3. Cohen SB, Emery P, Greenwald MW, et al. Rituximab for rheumatoid arthritis refractory to anti-tumor necrosis

factor therapy: Results of a multicenter, randomized, double-blind, placebo-controlled, phase III trial

evaluating primary efficacy and safety at twenty-four weeks. Arthritis and rheumatism 2006;54(9):2793-806

doi: 10.1002/art.22025[published Online First: Epub Date]|.

4. Emery P, Keystone E, Tony HP, et al. IL-6 receptor inhibition with tocilizumab improves treatment outcomes in

patients with rheumatoid arthritis refractory to anti-tumour necrosis factor biologicals: results from a 24-

week multicentre randomised placebo-controlled trial. Annals of the rheumatic diseases 2008;67(11):1516-

23 doi: 10.1136/ard.2008.092932[published Online First: Epub Date]|.

5. Genovese MC, Becker JC, Schiff M, et al. Abatacept for rheumatoid arthritis refractory to tumor necrosis factor

alpha inhibition. The New England journal of medicine 2005;353(11):1114-23 doi:

10.1056/NEJMoa050524[published Online First: Epub Date]|.

6. Salliot C, Finckh A, Katchamart W, et al. Indirect comparisons of the efficacy of biological antirheumatic agents in

rheumatoid arthritis in patients with an inadequate response to conventional disease-modifying

antirheumatic drugs or to an anti-tumour necrosis factor agent: a meta-analysis. Annals of the rheumatic

diseases 2011;70(2):266-71 doi: 10.1136/ard.2010.132134[published Online First: Epub Date]|.

7. Schoels M, Aletaha D, Smolen JS, et al. Comparative effectiveness and safety of biological treatment options after

tumour necrosis factor alpha inhibitor failure in rheumatoid arthritis: systematic review and indirect pairwise

meta-analysis. Annals of the rheumatic diseases 2012;71(8):1303-8 doi: 10.1136/annrheumdis-2011-

200490[published Online First: Epub Date]|.

8. Bergman GJ, Hochberg MC, Boers M, et al. Indirect comparison of tocilizumab and other biologic agents in

patients with rheumatoid arthritis and inadequate response to disease-modifying antirheumatic drugs.

Seminars in arthritis and rheumatism 2010;39(6):425-41 doi: 10.1016/j.semarthrit.2009.12.002[published

Online First: Epub Date]|.

9. Hetland ML, Christensen IJ, Tarp U, et al. Direct comparison of treatment responses, remission rates, and drug

adherence in patients with rheumatoid arthritis treated with adalimumab, etanercept, or infliximab: results

from eight years of surveillance of clinical practice in the nationwide Danish DANBIO registry. Arthritis and

rheumatism 2010;62(1):22-32 doi: 10.1002/art.27227[published Online First: Epub Date]|.

10. Mariette X, Gottenberg JE, Ravaud P, et al. Registries in rheumatoid arthritis and autoimmune diseases: data

from the French registries. Rheumatology 2011;50(1):222-9 doi: 10.1093/rheumatology/keq368[published


11. Hernan MA, Robins JM. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available.

American journal of epidemiology 2016;183(8):758-64 doi: 10.1093/aje/kwv254[published Online First: Epub

Date]|.

12. PR R. Model-based direct adjustment. Journal of the American Statistical Association 1987;82:387-94

13. Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology.

Epidemiology 2000;11(5):550-60

14. Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW)

using the propensity score to estimate causal treatment effects in observational studies. Statistics in

medicine 2015;34(28):3661-79 doi: 10.1002/sim.6607[published Online First: Epub Date]|.

15. Pascart T, Philippe P, Drumez E, et al. Comparative efficacy of tocilizumab, abatacept and rituximab after non-

TNF inhibitor failure: results from a multicentre study. International journal of rheumatic diseases

2016;19(11):1093-102 doi: 10.1111/1756-185X.12845[published Online First: Epub Date]|.

16. Leffers HC, Ostergaard M, Glintborg B, et al. Efficacy of abatacept and tocilizumab in patients with rheumatoid

arthritis treated in clinical practice: results from the nationwide Danish DANBIO registry. Annals of the

rheumatic diseases 2011;70(7):1216-22 doi: 10.1136/ard.2010.140129[published Online First: Epub Date]|.

Page 17 of 53


BMJ

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960


17. Das S, Vital EM, Horton S, et al. Abatacept or tocilizumab after rituximab in rheumatoid arthritis? An exploratory

study suggests non-response to rituximab is associated with persistently high IL-6 and better clinical

response to IL-6 blocking therapy. Annals of the rheumatic diseases 2014;73(5):909-12 doi:

10.1136/annrheumdis-2013-204417[published Online First: Epub Date]|.

18. Walker UA, Jaeger VK, Chatzidionysiou K, et al. Rituximab done: what's next in rheumatoid arthritis? A European

observational longitudinal study assessing the effectiveness of biologics after rituximab treatment in

rheumatoid arthritis. Rheumatology 2016;55(2):230-6 doi: 10.1093/rheumatology/kev297[published Online

First: Epub Date]|.

19. Harrold LR, Reed GW, Solomon DH, et al. Comparative effectiveness of abatacept versus tocilizumab in

rheumatoid arthritis patients with prior TNFi exposure in the US Corrona registry. Arthritis research &

therapy 2016;18(1):280 doi: 10.1186/s13075-016-1179-7[published Online First: Epub Date]|.

20. Gottenberg JE, Courvoisier DS, Hernandez MV, et al. Brief Report: Association of Rheumatoid Factor and Anti-

Citrullinated Protein Antibody Positivity With Better Effectiveness of Abatacept: Results From the Pan-

European Registry Analysis. Arthritis & rheumatology 2016;68(6):1346-52 doi: 10.1002/art.39595[published


21. Gabay C, Emery P, van Vollenhoven R, et al. Tocilizumab monotherapy versus adalimumab monotherapy for

treatment of rheumatoid arthritis (ADACTA): a randomised, double-blind, controlled phase 4 trial. Lancet

2013;381(9877):1541-50 doi: 10.1016/S0140-6736(13)60250-0[published Online First: Epub Date]|.

22. Schiff M, Weinblatt ME, Valente R, et al. Head-to-head comparison of subcutaneous abatacept versus

adalimumab for rheumatoid arthritis: two-year efficacy and safety findings from AMPLE trial. Annals of the

rheumatic diseases 2014;73(1):86-94 doi: 10.1136/annrheumdis-2013-203843[published Online First: Epub

Date]|.

23. Gottenberg JE, Ravaud P, Cantagrel A, et al. Positivity for anti-cyclic citrullinated peptide is associated with a

better response to abatacept: data from the 'Orencia and Rheumatoid Arthritis' registry. Annals of the

rheumatic diseases 2012;71(11):1815-9 doi: 10.1136/annrheumdis-2011-201109[published Online First:

Epub Date]|.

24. Gottenberg JE, Ravaud P, Bardin T, et al. Risk factors for severe infections in patients with rheumatoid arthritis

treated with rituximab in the autoimmunity and rituximab registry. Arthritis and rheumatism

2010;62(9):2625-32 doi: 10.1002/art.27555[published Online First: Epub Date]|.

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FIGURE LEGENDS

Figure 1. Follow-up of enrolled patients

*Not meeting one of the criteria inclusion (n=781) or missing value for at least one inclusion criteria

(n=170)

**Severe cardiovascular disease, active or severe infections, severe immune deficiency

***Inclusion period: patients who initiated treatment before March 2013 (ie, 2 years before

database was locked,in March 2015, to have at least 2 years of theoretical follow-up)

****Patients with treatment failure before 2 years of follow-up or with at least 2 years of follow-up

ACR, American College of Rheumatology

Figure 2. Kaplan-Meier analysis of drug retention without failure at 24 months: (a)

unweighted and (b) weighted results. Vertical bars represent censored patients.

Figure 3.Kaplan-Meier analysis of survival without serious adverse events at 24 months: (a)

unweightedand (b) weighted results. Vertical bars represent censored patients.

Figure 4. Sensitivity analyses of drug retention without failure at month 24 for abatacept

and rituximab.

Definitions of failure: 1) death or discontinuation of the registry drug; 2) death or initiation of a

combination of conventional disease-modifying antirheumatic drugs (DMARDs) or a biologic

DMARD; 3) death or discontinuation of the registry drug or initiation of a combination of

conventional DMARDs or a biologic DMARD. The position of each square represents the point

estimate of the hazard ratio (HR). Error bars are 95% confidence intervals (CIs). N are weighted

number of patients included in each analysis.

Figure 5. Sensitivity analyses of drug retention without failure at month 24 for abatacept

and tocilizumab.


combination of conventional DMARDs or a biologic DMARD; 3) death or discontinuation of the

registry drug or initiation of a combination of conventional DMARDs or a biologic DMARD. The

position of each square represents the point estimate of the HR. Error bars indicate 95%

confidence intervals (CIs). N are weighted number of patients included in each analysis.

Figure 6. Sensitivity analyses of drug retention without failure at month 24 for rituximab

and tocilizumab.


combination of conventional DMARDs or a biologic DMARD; 3) death or discontinuation of the

registry drug or initiation of a combination of conventional DMARDs or a biologic DMARD. The

position of each square represents the point estimate of the HR. Error bars are 95% confidence

intervals (CIs). N are weighted number of patients included in each analysis.

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Table 1: Baseline characteristics of the 3183 enrolled patients.

UnweightedCohort Weighted Cohort

Rituximab

(n=1614)

Abatacept

(n=610)

Tocilizumab

(n=938)

Rituximab

(n=1548)

Abatacept

(n=620)

Tocilizumab

(n=964)

Age (years), mean (SD) 58.0 (12.7) 59.7 (13.8) 56.5 (13.9) 58.1 (12.9) 57.3 (14.1) 57.9 (14.1)

Disease duration (years),

median [IQR]

11.0 [6.0-

18.0]

11.0 [5.0-

19.0] 8.0 [3.0-16.0]

10.0 [5.0-

18.0]

11.0 [5.0-

18.0]

12.0 [5.0-

21.0]

Sex (female), n (%) 1287 (79.7) 478 (78.4) 741 (79.0) 1243

(80.3) 491 (79.2) 765 (79.4)

Previous infection

serious or recurrent, n

(%)

565 (35.0) 206 (33.8) 112 (11.9) 446 (28.8) 171 (27.6) 305 (31.6)

History of cancer, n (%) 232 (14.4) 32 (5.3) 39 (4.2) 158 (10.2) 55 (8.9) 69 (7.1)

Rheumatoid factor-

positive, n (%) 1237 (80.5) 412 (75.0) 627 (79.8)

1154

(79.0) 448 (80.0) 665 (77.5)

Anti-CCP antibody

positive, n (%) 1074 (77.0) 382 (74.3) 631 (82.8)

1023

(76.4) 1023 (76.4) 1023 (76.4)

No. of previous anti-TNF

agents, median [IQR]

2.0 [1.0-

2.0] 2.0 [1.0-2.0] 1.0 [0.0-2.0]

2.0 [1.0-

2.0] 2.0 [1.0-2.0] 2.0 [1.0-2.0]

No. of conventional

DMARDs, median

[IQR]

3.0 [2.0-

4.0] 2.0 [1.0-4.0] 2.0 [1.0-3.0]

3.0 [2.0-

4.0] 3.0 [2.0-4.0] 2.0 [1.0-4.0]

No. of tender joints,

median [IQR]

9.0 [5.0-

15.0]

8.0 [3.0-

15.0] 7.0 [3.0-13.0]

8.0 [4.0-

15.0]

8.0 [3.0-

14.0] 8.0 [4.0-12.0]

No. of swollen joints,

median [IQR]

6.0 [3.0-

10.0] 5.0 [2.0-9.0] 5.0 [2.0-8.0]

6.0 [3.0-

10.0]

6.0 [2.0-

10.0] 5.0 [2.0-10.0]

ESR, median [IQR] 32.0 [17.0-

51.0]

28.0 [15.0-

50.0]

27.0 [13.0-

48.0]

31.0 [16.0-

50.0]

29.0 [16.0-

45.0]

28.0 [15.0-

47.0]

CRP level, median [IQR] 16.0 [5.6-

38.0]

13.0 [4.8-

28.5]

12.5 [4.0-

32.0]

13.0 [5.0-

36.0]

13.9 [5.0-

28.0]

15.0 [5.0-

37.0]

Patient global

assessment of disease

activity [range 0-100],

mean (SD)

61.5 (22.0) 59.7 (22.8) 57.8 (24.7) 60.4 (22.3) 62.9 (21.9) 57.0 (26.4)

DAS28-ESR, mean (SD) 5.5 (1.2) 5.2 (1.3) 5.0 (1.4) 5.4 (1.3) 5.3 (1.3) 5.3 (1.3)

Concomitant treatment

with aconventional

DMARD, n (%)

1043 (64.9) 401 (66.5) 556 (59.5) 984 (63.8) 387 (62.9) 585 (60.9)

Corticosteroids, n (%) 1242 (77.7) 456 (74.4) 623 (66.5) 1133

(74.3) 460 (74.9) 684 (71.2)

If corticosteroids, dose

(mg/d), mean (SD) 11.8 (8.8) 11.2 (8.3) 10.3 (7.2) 11.3 (8.3) 11.6 (8.5) 11.2 (7.2)

IQR, interquartile range; CCP, cyclic citrullinated peptide; TNF, tumor necrosis factor; DMARD, disease-modifying

anti-rheumatic drug; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; DAS28-ESR, Disease Activity

Score in 28 joints-erythrocyte sedimentation rate

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Table 2: Causes of drug failure at 24 months of follow-up.

UnweightedCohort Weighted Cohort

Rituximab

(n=515)

n (%)

Abatacept

(n=347)

n (%)

Tocilizumab

(n=263)

n (%)

Rituximab

(n=480)

n (%)

Abatacept

(n=373)

n (%)

Tocilizumab

(n=315)

n (%)

Death 26 (5.0%) 19 (5.5%) 4 (1.5%) 25 (5.3) 20 (5.3) 14 (4.3)

Introduction of a new

biologic DMARD or

combination of DMARDs

206 (40.0) 128 (36.9) 171 (65.0) 185 (38.6) 164 (44.1) 215 (68.3)

Discontinuation of biologic 454 (88.2) 322 (92.8) 241 (91.6) 424 (88.5) 347 (93.1) 288 (91.3)

If discontinuation, cause

Death 4 (0.9) 0 (0.0) 2 (0.9) 3 (0.7) 0 (0.0) 4 (1.4)

Adverse event 64 (14.1) 58 (18.0) 97 (41.6) 66 (15.7) 58 (16.6) 115 (42.5)

Inefficacy 332 (73.1) 205 (63.7) 107 (45.9) 306 (72.1) 224 (64.7) 121 (44.5)

Otherreason 54 (11.9) 59 (18.3) 27 (11.6) 49 (11.5) 65 (18.7) 31 (11.6)

Increase of corticosteroids

dose (>10 mg/baseline)

2 (0.4) 6 (1.7) 4 (1.5) 2 (0.5) 5 (1.5) 3 (1.0)

DMARD, disease-modifying anti-rheumatic drug

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Table 3: Unweighted and weighted survival without drug failure at 24 month s.

Rituximab Abatacept Tocilizumab

Number

of

failures

Survivalwithoutfailure

% [95% CI]

Number

of

failures


% [95% CI]

Number

of

failures


% [95% CI]

Unweighted 515 67.6 [65.2 ; 69.8] 347 42.5 [38.5 ; 46.4] 263 68.0 [64.6 ; 71.1]

Weighted 480 68.6 [65.3 ; 71.5] 373 39.3 [34.1 ; 44.5] 315 63.4 [56.1 ; 69.8]

Table 4: Comparison of moderate and good EULAR response (weighted analysis) at 6, 12 and 24 months

Rituximab

(n, %)

Abatacept

(n, %)

Tocilizumab

(n, %)

ABA vs RTX

OR [95% CI]

P

TOC vs RTX

OR [95% CI]

p

ABA vs TOC

OR [95% CI]

6 months 511 (54.5) 235 (48.0) 508 (72.9) 0.77 [0.55;1.07] 0.118 2.26 [1.51;3.37] <0.001 0.34 [0.21;0.54]

12 months 377 (43.3) 171 (34.0) 417 (59.9) 0.66 [0.52;0.84] <0.001 1.98 [1.30;3.03] 0.002 0.33 [0.22;0.51]

24 months 322 (34.6) 125 (22.7) 272 (44.2) 0.55 [0.39;0.78] 0.001 1.51 [0.95;2.41] 0.084 0.37 [0.21;0.63]

OR, odds ratio; CI, confidence interval; RTX, rituximab; ABA, abatacept; TOC, tocilizumab

EULAR non-response was considered death, discontinuation of the drug studied in the registry and/or initiation of a

combination of conventional DMARDs and/or a new biologic and/or increase in oral corticosteroids dose > 10 mg/day

at 2 consecutive visits.

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Table 5: Description of serious adverse events (SAEs) in the unweighted and weighted cohorts.

Unweighted Cohort Weighted Cohort

Rituximab

(n=1614)

n (%)

Abatacept

(n=610)

n (%)

Tocilizumab

(n=938)

n (%)

Rituximab

(n=1548)

n (%)

Abatacept

(n=620)

n (%)

Tocilizumab

(n=964)

n (%)

No.of patients with at least

one SAE

237 (14.7) 104 (17.0) 104 (11.1) 224 (14.5) 101 (16.2) 111 (11.6)

First SAE

Serious infection 172 (72.6) 69 (66.3) 83 (79.8) 157 (70.2) 69 (68.5) 88 (78.9)

Death 18 (7.6) 15 (14.4) 3 (2.9) 19 (8.4) 15 (14.3) 10 (9.1)

Cancer 34 (14.3) 16 (15.4) 12 (11.5) 37 (16.6) 13 (13.1) 10 (8.9)

MACE 13 (5.5) 4 (3.8) 6 (5.8) 11 (4.8) 4 (4.1) 3 (3.0)

No. of*

Serious infections 220 (13.6) 87 (14.3) 92 (9.8) 205 (13.2) 88 (14.2) 100 (10.4)

Death 39 (2.4) 26 (4.3) 4 (0.4) 34 (2.2) 26 (4.2) 14 (1.4)

MACEs 16 (1.0) 5 (0.8) 6 (0.6) 13 (0.8) 5 (0.8) 3 (0.3)

Cancers 42 (2.6) 19 (3.1) 17 (1.8) 43 (2.8) 14 (2.3) 17 (1.8)

SAE: serious adverse event (serious infection, major adverse cardiovascular event, cancer, or death); MACE: major

adverse cardiovascular event (death of cardiovascular origin, stroke, or myocardial infarction).

*Numbers in parenthesesare rates of each event

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Table 6: Survival without SAE for the weighted cohort.

Rituximab Abatacept Tocilizumab

No.events

Survivalwithoutevent

% [95% CI] No.events


% [95% CI] No.events


% [95% CI]

SAE 224 85.0 [82.5 ; 87.2] 101 83.4 [78.5 ; 87.2] 111 86.7 [80.6 ; 91.1]

Serious

infection

163 89.1 [86.8 ; 91.0] 71 88.2 [83.8 ; 91.4] 88 89.5 [83.8 ; 93.3]

Death 34 97.7 [96.4 ; 98.5] 26 95.7 [92.6 ; 97.5] 14 98.3 [94.7 ; 99.5]

MACE 12 99.2 [98.3 ; 99.6] 5 99.1 [96.9 ; 99.7] 3 99.6 [95.8 ; 99.9]

Cancer 42 97.1 [95.8 ; 98.1] 14 97.6 [94.9 ; 98.9] 12 98.5 [94.9 ; 99.6]

SAE: serious adverse event (serious infection, major adverse cardiovascular event, cancer, or death); MACE: major

adverse cardiovascular event (death of cardiovascular origin, stroke, or myocardial infarction).

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Figure 1.

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Figure 2.

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Figure 3.

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Figure

4.

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Figure 5.

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Figure

6.

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Appendix -Supplementary Material

eTable 1. Baseline characteristics in the unweighted and weighted cohort.

eTable 2. Standardized differences between groups before and after adjustment on the

propensity score. Standardized difference is the mean difference divided by the pooled

standard deviation, expressed as a percentage.

eTable 3. EULAR response in the unweighted and weighted cohort at 6, 12 and 24 months.

eFigure 1. Standardized differences between groups before and after adjustment on the

propensity score.

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eTable1: Baseline characteristics in the unweighted and weighted cohort.

UnweightedCohort WeightedCohort

Rituximab, Abatacept, Tocilizumab Rituximab, Abatacept, Tocilizumab,

Characteristics n = 1614 n = 610 n = 938 n = 1548 n = 620 n = 964

Age (years)

Missing data 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

Min/Max 20/89 19/87 19/90 20/89 19/87 19/90

Med [IQR] 59 [50 ; 67] 60 [51 ; 70] 57 [48 ; 66] 59 [50 ; 67] 58 [48 ; 68] 59 [49 ; 69]

Mean (sd) 58.02 (12.67) 59.68 (13.83) 56.48 (13.85) 58.11 (12.87) 57.33 (14.12) 57.91 (14.13)

Disease duration (years)

Missing data 68 (4.2) 10 (1.6) 48 (5.1) 64 (4.1) 12 (1.9) 28 (2.9)

Min/Max 0/68 0/48 0/65 0/68 0/48 0/65

Med [IQR] 11 [6 ; 18] 11 [5 ; 19] 8 [3 ; 16] 10 [5 ; 18] 11 [5 ; 18] 12 [5 ; 21]

Mean (SD) 13.23 (9.72) 13.41 (9.9) 10.85 (9.84) 12.75 (9.88) 12.71 (9.52) 14.03 (10.59)

Sex

Missing data 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

Female 1287 (79.7) 478 (78.4) 741 (79) 1243 (80.3) 491 (79.2) 765 (79.4)

Male 327 (20.3) 132 (21.6) 197 (21) 305 (19.7) 129 (20.8) 199 (20.6)

Previous infection serious or recurrent

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Missing data 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

No 1049 (65) 404 (66.2) 826 (88.1) 1102 (71.2) 449 (72.4) 659 (68.4)

Yes 565 (35) 206 (33.8) 112 (11.9) 446 (28.8) 171 (27.6) 305 (31.6)

History of cancer

Missing data 4 (0.2) 1 (0.2) 1 (0.1) 4 (0.2) 0 (0) 0 (0)

No 1378 (85.6) 577 (94.7) 898 (95.8) 1387 (89.8) 565 (91.1) 895 (92.9)

Yes 232 (14.4) 32 (5.3) 39 (4.2) 158 (10.2) 55 (8.9) 69 (7.1)

Extra-articularinvolvement

Missing data 20 (1.2) 9 (1.5) 4 (0.4) 20 (1.3) 6 (0.9) 5 (0.5)

No 1241 (77.9) 539 (89.7) 820 (87.8) 1252 (81.9) 521 (84.8) 776 (80.9)

Yes 353 (22.1) 62 (10.3) 114 (12.2) 277 (18.1) 93 (15.2) 183 (19.1)

History of smoking

Missing data 16 (1) 1 (0.2) 0 (0) 20 (1.3) 0 (0.1) 0 (0)

No 1237 (77.4) 496 (81.4) 739 (78.8) 1204 (78.8) 467 (75.4) 789 (81.8)

Yes 361 (22.6) 113 (18.6) 199 (21.2) 324 (21.2) 152 (24.6) 175 (18.2)

Diabetes

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Missing data 16 (1) 1 (0.2) 0 (0) 20 (1.3) 0 (0.1) 0 (0)

No 1430 (89.5) 561 (92.1) 841 (89.7) 1383 (90.4) 552 (89.1) 882 (91.5)

Yes 168 (10.5) 48 (7.9) 97 (10.3) 146 (9.6) 68 (10.9) 82 (8.5)

Arterial hypertension

Missing data 16 (1) 1 (0.2) 0 (0) 20 (1.3) 0 (0.1) 0 (0)

No 1079 (67.5) 414 (68) 662 (70.6) 1055 (69) 428 (69.1) 690 (71.5)

Yes 519 (32.5) 195 (32) 276 (29.4) 474 (31) 191 (30.9) 275 (28.5)

Dyslipidemia

Missing data 16 (1) 1 (0.2) 0 (0) 20 (1.3) 0 (0.1) 0 (0)

No 1391 (87) 507 (83.3) 770 (82.1) 1311 (85.8) 521 (84.1) 841 (87.3)

Yes 207 (13) 102 (16.7) 168 (17.9) 217 (14.2) 99 (15.9) 123 (12.7)

Cardiacinsufficiency

Missing data 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

No 1543 (95.6) 598 (98) 927 (98.8) 1502 (97) 598 (96.4) 935 (97)

Yes 71 (4.4) 12 (2) 11 (1.2) 47 (3) 22 (3.6) 29 (3)

History of MACE

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Missing data 16 (1) 0 (0) 1 (0.1) 20 (1.3) 0 (0) 0 (0)

No 1560 (97.6) 571 (93.6) 920 (98.2) 1493 (97.7) 600 (96.7) 921 (95.6)

Yes 38 (2.4) 39 (6.4) 17 (1.8) 36 (2.3) 20 (3.3) 43 (4.4)

History of renalinsufficiency

Missing data 0 (0) 1 (0.2) 1 (0.1) 0 (0) 2 (0.4) 1 (0.1)

No 1558 (96.5) 571 (93.8) 878 (93.7) 1471 (95) 581 (94.1) 922 (95.8)

Yes 56 (3.5) 38 (6.2) 59 (6.3) 77 (5) 37 (5.9) 41 (4.2)

History of hepaticdisease

Missing data 0 (0) 4 (0.7) 3 (0.3) 0 (0) 9 (1.5) 3 (0.3)

No 1604 (99.4) 571 (94.2) 881 (94.2) 1514 (97.8) 595 (97.4) 935 (97.3)

Yes 10 (0.6) 35 (5.8) 54 (5.8) 34 (2.2) 16 (2.6) 26 (2.7)

History of respiratorydisease

Missing data 0 (0) 3 (0.5) 1 (0.1) 0 (0) 2 (0.3) 1 (0.1)

No 1462 (90.6) 603 (99.3) 929 (99.1) 1464 (94.5) 602 (97.5) 938 (97.4)

Yes 152 (9.4) 4 (0.7) 8 (0.9) 84 (5.5) 16 (2.5) 25 (2.6)

Rheumatoid factor

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Missing data 78 (4.8) 61 (10) 152 (16.2) 88 (5.7) 63 (10.1) 106 (11)

Negative 299 (19.5) 137 (25) 159 (20.2) 306 (21) 109 (19.6) 193 (22.5)

Positive 1237 (80.5) 412 (75) 627 (79.8) 1154 (79) 448 (80.4) 665 (77.5)

Anti-CCPantibodies

Missing data 220 (13.6) 96 (15.7) 176 (18.8) 211 (13.6) 99 (16) 176 (18.3)

Negative 320 (23) 132 (25.7) 131 (17.2) 315 (23.6) 113 (21.6) 127 (16.2)

Positive 1074 (77) 382 (74.3) 631 (82.8) 1023 (76.4) 408 (78.4) 660 (83.8)

RF or anti-CCP antibody +

Missing data 93 (5.8) 67 (11) 128 (13.6) 102 (6.6) 66 (10.6) 96 (9.9)

No 169 (11.1) 84 (15.5) 84 (10.4) 175 (12.1) 68 (12.2) 99 (11.4)

Yes 1352 (88.9) 459 (84.5) 726 (89.6) 1271 (87.9) 487 (87.8) 769 (88.6)

Gammaglobulinlevel (g/L)

Missing data 570 (35.3) 279 (45.7) 584 (62.3) 539 (34.8) 287 (46.2) 633 (65.7)

Min/Max 0.93/182 1.5/26.1 3.2/49 0.93/182 1.5/26.1 3.2/49

Med [IQR] 10.9 [8.8 ; 13.8] 10.4 [8.5 ; 13.15] 11.2 [8.9 ; 13.67] 11 [8.8 ; 13.5] 10.5 [8.4 ; 13.1] 11.7 [8.9 ; 14.7]

Mean (SD) 11.87 (7.18) 11.17 (4.08) 11.69 (4.19) 11.69 (6.42) 11.25 (4.2) 12.18 (4.55)

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IgGlevel(g/L)

Missing data 733 (45.4) 423 (69.3) 769 (82) 691 (44.6) 413 (66.5) 716 (74.3)

Min/Max 0.09/34.2 2.06/26.7 5.2/32.5 0.09/34.2 2.06/26.7 5.2/32.5

Med [IQR] 11.2 [9 ; 13.83] 11.3 [8.19 ; 13.35] 11.3 [9 ; 13.52] 11.4 [9 ; 13.8] 12.2 [7.9 ; 13.8] 11.9 [9.3 ; 12.9]

Mean (sd) 11.85 (4.21) 11.25 (4.06) 11.65 (3.9) 11.81 (4.15) 11.63 (4.32) 11.52 (3.9)

IgMlevel(g/L)

Missing data 733 (45.4) 424 (69.5) 770 (82.1) 698 (45.1) 413 (66.6) 717 (74.4)

Min/Max 0.18/81 0.09/10.4 0.2/9.14 0.18/81 0.09/10.4 0.2/9.14

Med [IQR] 1.35 [0.93 ; 1.92] 1.16 [0.76 ; 1.73] 1.3 [0.85 ; 1.87] 1.3 [0.9 ; 1.8] 1.1 [0.8 ; 1.6] 1.5 [0.9 ; 1.9]

Mean (sd) 1.69 (2.95) 1.58 (1.62) 1.49 (1.05) 1.62 (2.84) 1.42 (1.43) 1.54 (0.89)

Low gammaglobulin level

Missing data 570 (35.3) 279 (45.7) 584 (62.3) 539 (34.8) 287 (46.2) 633 (65.7)

No 992 (95) 310 (93.7) 344 (97.2) 954 (94.5) 305 (91.4) 326 (98.3)

Yes 52 (5) 21 (6.3) 10 (2.8) 55 (5.5) 29 (8.6) 6 (1.7)

LowIgGlevel

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Missing data 733 (45.4) 423 (69.3) 769 (82) 691 (44.6) 413 (66.5) 716 (74.3)

No 847 (96.1) 174 (93) 164 (97) 826 (96.3) 198 (95.4) 244 (98.4)

Yes 34 (3.9) 13 (7) 5 (3) 32 (3.7) 10 (4.6) 4 (1.6)

LowIgMlevel

Missing data 733 (45.4) 424 (69.5) 770 (82.1) 698 (45.1) 413 (66.6) 717 (74.4)

No 837 (95) 172 (92.5) 158 (94) 806 (94.8) 187 (90.4) 232 (93.9)

Yes 44 (5) 14 (7.5) 10 (6) 44 (5.2) 20 (9.6) 15 (6.1)

Neutropenia

Missing data 1 (0.1) 2 (0.3) 13 (1.4) 1 (0) 3 (0.5) 16 (1.6)

No 1515 (93.9) 522 (85.9) 761 (82.3) 1398 (90.3) 559 (90.6) 853 (89.9)

Yes 98 (6.1) 86 (14.1) 164 (17.7) 150 (9.7) 58 (9.4) 95 (10.1)

Previous treatment with any biologic

Missing data 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

No 357 (22.1) 65 (10.7) 235 (25.1) 353 (22.8) 83 (13.3) 135 (14)

Yes 1257 (77.9) 545 (89.3) 703 (74.9) 1195 (77.2) 537 (86.7) 830 (86)

No.of previous anti-TNF agents

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Missing data 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)

Min/Max 0/3 0/3 0/4 0/3 0/3 0/4

Med [IQR] 2 [1 ; 2] 2 [1 ; 2] 1 [0 ; 2] 2 [1 ; 2] 2 [1 ; 2] 2 [1 ; 2]

Mean (sd) 1.52 (1.04) 1.65 (0.93) 1.2 (0.92) 1.49 (1.04) 1.53 (0.95) 1.61 (0.97)

No.ofconventionalDMARDs

Missing data 1 (0.1) 0 (0) 0 (0) 1 (0) 0 (0) 0 (0)

Min/Max 0/6 0/10 0/7 0/6 0/10 0/7

Med [IQR] 3 [2 ; 4] 2 [1 ; 4] 2 [1 ; 3] 3 [2 ; 4] 3 [2 ; 4] 2 [1 ; 4]

Mean (SD) 3.06 (1.38) 2.59 (1.67) 2.09 (1.31) 2.77 (1.38) 2.88 (1.7) 2.84 (1.63)

No.of tender joints

Missing data 272 (16.9) 192 (31.5) 334 (35.6) 267 (17.2) 159 (25.7) 287 (29.8)

Min/Max 0/28 0/28 0/28 0/28 0/28 0/28

Med [IQR] 9 [5 ; 15] 8 [3 ; 15] 7 [3 ; 13] 8 [4 ; 15] 8 [3 ; 14] 8 [4 ; 12]

Mean (SD) 10.35 (7.25) 9.93 (7.83) 8.93 (7.22) 10.14 (7.41) 9.69 (7.67) 9.2 (6.93)

No.ofswollen joints

Missing data 266 (16.5) 194 (31.8) 334 (35.6) 261 (16.9) 161 (25.9) 289 (29.9)

Min/Max 0/28 0/24 0/28 0/28 0/24 0/28

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Med [IQR] 6 [3 ; 10] 5 [2 ; 9] 5 [2 ; 8] 6 [3 ; 10] 6 [2 ; 10] 5 [2 ; 10]

Mean (SD) 7.43 (5.61) 5.9 (5.19) 6.02 (5.19) 6.82 (5.41) 6.78 (5.33) 6.65 (5.38)

ESR

Missing data 252 (15.6) 201 (33) 86 (9.2) 247 (16) 169 (27.3) 66 (6.8)

Min/Max 1/165 1/175 1/140 1/165 1/175 1/140

Med [IQR] 32 [17 ; 51] 28 [15 ; 50] 27 [13 ; 48] 31 [16 ; 50] 29 [16 ; 45] 28 [15 ; 47]

Mean (sd) 37.69 (25.98) 35.86 (27.96) 34.6 (27.91) 36.43 (25.92) 36.02 (26.94) 35.37 (26.9)

CRP level

Missing data 177 (11) 160 (26.2) 108 (11.5) 171 (11.1) 144 (23.2) 114 (11.8)

Min/Max 0/500 0.1/310 0/255 0/500 0.1/310 0/255

Med [IQR] 16 [5.6 ; 38] 13 [4.85 ; 28.48] 12.5 [4 ; 32] 13 [5 ; 36] 13.9 [5 ; 28] 15 [5 ; 37]

Mean (SD) 28.42 (35.62) 24.11 (32.73) 25.25 (34.64) 26 (33.76) 26.08 (34.52) 28.68 (36.85)

Patient global assessment of disease activity [range 0-

100]

Missing data 343 (21.3) 217 (35.6) 381 (40.6) 337 (21.8) 181 (29.2) 334 (34.7)

Min/Max 0/100 0/100 0/100 0/100 0/100 0/100

Med [IQR] 65 [50 ; 80] 63 [50 ; 75] 60 [40 ; 79] 65 [50 ; 80] 70 [50 ; 80] 60 [40 ; 80]

Mean (SD) 61.51 (21.99) 59.7 (22.78) 57.8 (24.7) 60.36 (22.28) 62.85 (21.95) 57.01 (26.39)

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DAS28-ESR

Missing data 111 (6.9) 63 (10.3) 141 (15) 105 (6.8) 50 (8.1) 113 (11.7)

Min/Max 0.56/8.89 1.51/8.98 0.49/8.9 0.56/8.89 1.51/8.98 0.49/8.9

Med [IQR] 5.51 [4.75 ; 6.34] 5.33 [4.34 ; 6.13] 5.09 [4.16 ; 5.93] 5.4 [4.6 ; 6.2] 5.5 [4.5 ; 6.2] 5.5 [4.4 ; 6.3]

Mean (SD) 5.51 (1.24) 5.24 (1.32) 5.04 (1.38) 5.38 (1.28) 5.35 (1.3) 5.32 (1.3)

Treatment initiation

Missing data 0 (0) 5 (0.8) 117 (12.5) 0 (0) 6 (1) 94 (9.7)

1000mg 0 (0) 33 (5.5) 0 (0) 0 (0) 54 (8.8) 0 (0)

2*1g 1569 (97.2) 0 (0) 0 (0) 1507 (97.3) 0 (0) 0 (0)

4mg/kg 0 (0) 0 (0) 9 (1.1) 0 (0) 0 (0) 17 (1.9)

500mg 0 (0) 163 (26.9) 0 (0) 0 (0) 147 (24) 0 (0)

750mg 0 (0) 409 (67.6) 0 (0) 0 (0) 413 (67.3) 0 (0)

8mg/kg 0 (0) 0 (0) 714 (87) 0 (0) 0 (0) 764 (87.7)

Other 45 (2.8) 0 (0) 98 (11.9) 42 (2.7) 0 (0) 90 (10.4)

Other concomitant treatment with a conventional

DMARD

Missing data 6 (0.4) 7 (1.1) 4 (0.4) 6 (0.4) 4 (0.6) 3 (0.4)

Yes 1043 (64.9) 401 (66.5) 556 (59.5) 984 (63.8) 387 (62.8) 585 (60.9)

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No 565 (35.1) 202 (33.5) 378 (40.5) 558 (36.2) 229 (37.2) 376 (39.1)

Concomitant conventional DMARD

Missing data 1 (0.1) 0 (0) 0 (0) 1 (0.1) 0 (0) 0 (0)

Other 11 (1.1) 2 (0.5) 0 (0) 9 (1) 2 (0.4) 0 (0)

Azathiopine 25 (2.4) 6 (1.5) 1 (0.2) 18 (1.8) 9 (2.3) 1 (0.2)

Cyclophosphamide 2 (0.2) 0 (0) 0 (0) 2 (0.2) 0 (0) 0 (0)

Cyclosporine 2 (0.2) 0 (0) 0 (0) 1 (0.1) 0 (0) 0 (0)

Hydroxycloroquine 23 (2.2) 6 (1.5) 6 (1.1) 17 (1.7) 6 (1.6) 8 (1.4)

Leflunomide 153 (14.7) 64 (16) 71 (12.8) 125 (12.7) 70 (18.2) 73 (12.4)

Methotrexate 803 (77.1) 312 (77.8) 467 (84) 789 (80.2) 284 (73.5) 486 (83)

Methotrexate + Leflunomide 8 (0.8) 0 (0) 0 (0) 5 (0.5) 0 (0) 0 (0)

Sulfasalazine 15 (1.4) 11 (2.7) 11 (2) 18 (1.9) 16 (4) 17 (2.9)

Corticoids

Missing data 20 (1.2) 10 (1.6) 4 (0.4) 22 (1.4) 5 (0.9) 4 (0.4)

No 356 (22.3) 153 (25.5) 314 (33.6) 393 (25.7) 154 (25.1) 276 (28.8)

Yes 1238 (77.7) 447 (74.5) 620 (66.4) 1134 (74.3) 460 (74.9) 684 (71.2)

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If corticoids, dose (mg/d)

Missing data 16 (1.3) 13 (2.9) 14 (2.3) 13 (1.1) 10 (2.2) 26 (3.9)

Min/Max 1/80 1/60 1/60 1/80 1/60 1/60

Med [IQR] 10 [7 ; 15] 10 [7 ; 13] 10 [5 ; 10] 10 [7 ; 12.5] 10 [7 ; 13] 10 [7 ; 12.5]

Mean (SD) 11.84 (8.78) 11.24 (8.27) 10.3 (7.25) 11.32 (8.29) 11.61 (8.52) 11.16 (7.25)

CCP, cyclic citrullinatedpeptide; CRP, C-reactive protein; DAS28-ESR, Disease Activity Score in 28 joints-erythrocyte sedimentation rate; DMARD, disease-

modifying anti-rheumatic drug; ESR, erythrocyte sedimentation rate; IgG, immunoglobulin G; IgM, immunoglobulin M; IQR, interquartile range; MACE,major

adverse cardiovascular events; RF, rheumatoid factor; TNF, tumor necrosis factor

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eTable2: Standardized differences between groups before and after adjustment on the propensity score. Standardized difference is the mean difference divided by the

pooled standard deviation, expressed as a percentage.

ABA vs RTX TCZ vs RTX ABA vs TCZ

Preadjustment

Post

adjustment Preadjustment

Post


Post

adjustment

Age 12% 6% 11% 1% 24% 4%

Disease duration 2% 0% 24% 13% 26% 13%

Sex 3% 3% 2% 2% 2% 0%

Previous infection serious or recurrent 3% 3% 54% 6% 51% 9%

History of cancer 34% 5% 38% 11% 4% 6%

Extra-articularinvolvement 34% 8% 28% 3% 5% 10%

History of smoking 10% 8% 3% 7% 7% 16%

Diabetes 9% 5% 1% 4% 8% 8%

Arterial hypertension 1% 0% 7% 5% 6% 5%

Dyslipidemia 10% 5% 14% 4% 3% 9%

Cardiacinsufficiency 16% 3% 21% 0% 5% 3%

History of MACE 22% 5% 3% 12% 25% 6%

History of renalinsufficiency 12% 4% 13% 3% 0% 8%

History of hepaticdisease 26% 3% 26% 3% 0% 0%

History of respiratorydisease 48% 16% 47% 16% 1% 0%

Gammaglobulinlevel 13% 9% 3% 10% 10% 18%

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ABA vs RTX TCZ vs RTX ABA vs TCZ

Preadjustment

Post


Post


Post

adjustment

IgGlevel 15% 5% 5% 7% 10% 3%

IgMlevel 6% 10% 10% 4% 4% 7%

Neutropenia 25% 1% 35% 1% 11% 2%

Rheumatoid factor or anti-CPP antibody + 13% 0% 2% 2% 16% 2%

No.of previous anti-TNF agents 13% 4% 33% 12% 46% 9%

No.ofconventionalDMARDs 32% 7% 66% 4% 34% 3%

No.of tender joints 6% 6% 19% 13% 13% 7%

No.ofswollen joints 29% 1% 26% 3% 2% 2%

ESR 7% 2% 11% 4% 5% 2%

CRPlevel 13% 0% 9% 8% 3% 7%

Patient global assessment of disease activity 8% 11% 16% 14% 8% 25%

DAS28-ESR 21% 3% 36% 4% 16% 2%

Other concomitant treatment with a conventional DMARD 3% 2% 11% 6% 15% 4%

Corticosteroids dose 10% 3% 28% 6% 18% 9%

Volume of patients treated with rituximab 36% 10% 51% 8% 15% 1%

Volume of patients treated with abatacept 7% 11% 27% 3% 34% 8%

Volume of patients treated with tocilizumab 3% 13% 30% 17% 27% 3%

ABA: Abatacept; RTX: Rituximab; TCZ: Tocilizumab

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eTable 3: EULAR response in the unweighted and weighted cohort at 6, 12 and 24 months.

Unweighted Cohort Weigthed Cohort

Rituximab, Abatacept, Tocilizumab, Rituximab, Abatacept, Tocilizumab,

n = 1614 n = 610 n = 938 n = 1548 n = 620 n = 964

EULAR response

6 months

Missing data 715 (44.3) 197 (32.3) 319 (34) 680 (43.9) 173 (27.8) 311 (32.3)

Good response 195 (21.7) 90 (21.8) 355 (57.4) 180 (20.7) 101 (22.7) 375 (57.5)

Moderate response 374 (41.6) 142 (34.4) 157 (25.4) 360 (41.5) 153 (34.3) 160 (24.5)

No response 330 (36.7) 181 (43.8) 107 (17.3) 329 (37.8) 193 (43.1) 117 (18)

12 months

Missing data 858 (53.2) 276 (45.2) 393 (41.9) 833 (53.8) 272 (43.9) 370 (38.4)

Good response 188 (24.9) 85 (25.4) 328 (60.2) 168 (23.6) 84 (24.1) 341 (57.4)

Moderate response 289 (38.2) 122 (36.5) 137 (25.1) 279 (39) 131 (37.5) 180 (30.2)

No response 279 (36.9) 127 (38) 80 (14.7) 268 (37.5) 133 (38.3) 73 (12.4)

24 months

Missing data 985 (61) 344 (56.4) 557 (59.4) 948 (61.2) 363 (58.6) 540 (56.1)

Good response 178 (28.3) 87 (32.7) 221 (58) 158 (26.3) 88 (34.2) 238 (56.2)


No response 204 (32.4) 85 (32) 63 (16.5) 193 (32.2) 82 (32) 68 (16)

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Rituximab, Abatacept, Tocilizumab, Rituximab, Abatacept, Tocilizumab,

n = 1614 n = 610 n = 938 n = 1548 n = 620 n = 964

EULAR response or failure

6 months

Missing data 639 (39.6) 153 (25.1) 270 (28.8) 610 (39.4) 131 (21.2) 268 (27.8)

Good response 184 (18.9) 84 (18.4) 348 (52.1) 169 (18.1) 91 (18.7) 371 (53.3)

Moderate response 350 (35.9) 132 (28.9) 140 (21) 342 (36.4) 143 (29.3) 137 (19.7)

Failure or No response 441 (45.2) 241 (52.7) 180 (26.9) 427 (45.5) 254 (52) 189 (27.1)

12 months

Missing data 684 (42.4) 137 (22.5) 287 (30.6) 678 (43.8) 118 (19) 268 (27.8)

Good response 166 (17.8) 74 (15.6) 311 (47.8) 147 (16.9) 70 (13.9) 321 (46.1)

Moderate response 236 (25.4) 97 (20.5) 101 (15.5) 230 (26.4) 101 (20) 96 (13.8)

Failure or No response 528 (56.8) 302 (63.8) 239 (36.7) 493 (56.7) 332 (66) 279 (40.1)

24 months

Missing data 634 (39.3) 89 (14.6) 380 (40.5) 617 (39.9) 68 (11) 347 (36)

Good response 143 (14.6) 62 (11.9) 204 (36.6) 126 (13.5) 67 (12.1) 226 (36.7)


Failure or No response 653 (66.6) 398 (76.4) 293 (52.5) 609 (65.4) 427 (77.3) 345 (55.9)

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eTable 4: Description of corticosteroids in the unweighted and weighted cohort at 6, 12 and 24 months.


Rituximab Abatacept Tocilizumab Rituximab Abatacept Tocilizumab

Decrease ≥ 5 mg

6 months

No 173 (65) 213 (62.5) 293 (56.8) 171 (68.4) 216 (58.4) 287 (51.6)

Yes 93 (35) 128 (37.5) 223 (43.2) 79 (31.6) 154 (41.6) 270 (48.4)

12 months

No 153 (57.1) 146 (52.9) 194 (42.6) 136 (56.9) 142 (48.1) 197 (37.8)

Yes 115 (42.9) 130 (47.1) 261 (57.4) 103 (43.1) 153 (51.9) 323 (62.2)

24 months

No 95 (43.8) 90 (40.2) 119 (34.6) 85 (41.7) 79 (38) 121 (29.1)

Yes 122 (56.2) 134 (59.8) 225 (65.4) 119 (58.3) 128 (62) 295 (70.9)

Dose ≤ 5 mg

6 months

No 191 (71.8) 208 (61) 231 (44.8) 184 (73.6) 230 (62.2) 262 (47.1)

Yes 75 (28.2) 133 (39) 285 (55.2) 66 (26.4) 140 (37.8) 294 (52.9)

12 months

No 151 (56.3) 134 (48.6) 132 (29) 133 (55.3) 137 (46.5) 144 (27.8)

Yes 117 (43.7) 142 (51.4) 323 (71) 107 (44.7) 158 (53.5) 375 (72.2)

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Rituximab Abatacept Tocilizumab Rituximab Abatacept Tocilizumab

24 months

No 84 (38.7) 71 (31.7) 85 (24.7) 70 (33.9) 68 (32.9) 101 (24.2)

Yes 133 (61.3) 153 (68.3) 259 (75.3) 135 (66.1) 139 (67.1) 315 (75.8)

Discontinuation

6 months

No 254 (92.4) 304 (85.9) 461 (83.7) 230 (90.3) 327 (86.3) 493 (84.5)

Yes 21 (7.6) 50 (14.1) 90 (16.3) 25 (9.7) 52 (13.7) 91 (15.5)

12 months

No 238 (85.9) 233 (80.6) 347 (71.3) 218 (88.5) 233 (76.6) 409 (75.1)

Yes 39 (14.1) 56 (19.4) 140 (28.7) 28 (11.5) 71 (23.4) 136 (24.9)

24 months

No 174 (76.3) 157 (67.4) 219 (58.4) 169 (79.5) 146 (68.5) 272 (62)

Yes 54 (23.7) 76 (32.6) 156 (41.6) 44 (20.5) 67 (31.5) 167 (38)

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eFigure 1: Propensity score distribution.

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eFigure 2: Standardized differences between groups before and after adjustment on the propensity score.

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eFigure 1: Standardized differences between groups before and after adjustment on the propensity score.

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BMJ€¦ · OBJECTIVE: Three non-tumor-necrosis factor-alpha (TNF) inhibitors — rituximab,...

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