William Reiss

Safety of biological therapies following rituximab treatment in rheumatoid arthritis patients

Objective: To assess the safety of biological disease-modifying antirheumatic drugs (DMARD) in rheumatoid arthritis (RA) patients following rituximab. Methods: RA patients who participated in an international rituximab clinical trial programme were included. Patients who had received one or more rituximab courses and entered safety follow-up (SFU) were permitted additional biological DMARD. Serious infection events (SIE) were collected. Results: Of 185 of 2578 patients who entered SFU and received another biological DMARD, 88.6% had peripheral B-cell depletion at the time of initiation of another biological agent. Thirteen SIE (6.99 events/100 patient-years) occurred following rituximab but before another biological DMARD and 10 SIE (5.49 events/100 patient-years) occurred following another biological DMARD. SIE were of typical type and severity for RA patients. 153 had received one or more tumour necrosis factor inhibitor(s). No fatal or opportunistic infections occurred. Conclusions: In this analysis, treatment with biological DMARD after rituximab was not associated with an increased serious infection rate. Sample size with limited follow-up restricts definitive conclusions.

Low immunogenicity of tocilizumab in patients with rheumatoid arthritis

Objective Subcutaneous (SC) and intravenous formulations of tocilizumab (TCZ) are available for the treatment of patients with rheumatoid arthritis (RA), based on the efficacy and safety observed in clinical trials. Anti-TCZ antibody development and its impact on safety and efficacy were evaluated in adult patients with RA treated with intravenous TCZ (TCZ-IV) or TCZ-SC as monotherapy or in combination with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). Methods Data from 5 TCZ-SC and 8 TCZ-IV phase III clinical trials and 1 TCZ-IV clinical pharmacology safety study (>50 000 samples) were pooled to assess the immunogenicity profile of TCZ-SC and TCZ-IV (8974 total patients). The analysis included antidrug antibody (ADA) measurement following TCZ-SC or TCZ-IV treatment as monotherapy or in combination with csDMARDs, after dosing interruptions or in TCZ-washout samples, and the correlation of ADAs with clinical response, adverse events or pharmacokinetics (PK). Results The proportion of patients who developed ADAs following TCZ-SC or TCZ-IV treatment was 1.5% and 1.2%, respectively. ADA development was also comparable between patients who received TCZ monotherapy and those who received concomitant csDMARDs (0.7–2.0%). ADA development did not correlate with PK or safety events, including anaphylaxis, hypersensitivity or injection-site reactions, and no patients who developed ADAs had loss of efficacy. Conclusions The immunogenicity risk of TCZ-SC and TCZ-IV treatment was low, either as monotherapy or in combination with csDMARDs. Anti-TCZ antibodies developed among the small proportion of patients had no evident impact on PK, efficacy or safety.

FRI0254 Comparative effectiveness of rituximab versus anti-tumor necrosis factor switching for rheumatoid arthritis patients

Background In patients who have failed 1 or more TNF-α inhibitors (TNFi), there is little data to guide clinical decision making in terms of changing mechanism of action or prescribing another TNFi. Objectives To compare the effectiveness of rituximab (RTX) versus a subsequent TNFi among RA patients with prior TNFi exposure using data from a multi-center observational registry within the United States (the Consortium of Rheumatology Researchers of North America: CORRONA). Methods We identified RA patients from 3/1/06 to present who had discontinued at least 1 TNFi and initiated either RTX or a subsequent TNFi, had moderate or high disease activity based on the Clinical Disease Activity Index (CDAI) at the time of initiation and had follow-up at 12 months (3 month window). A propensity score (PS) for TNFi vs. RTX was estimated using patient demographic information, disease characteristics (severity, duration, activity), comorbidities, past medication history and concurrent medications. We trimmed the PS distributions, excluding patients who fell outside the region of common support (n=2). Our primary outcome was achievement of low disease activity (CDAI ≤10). Multivariable logistic regression models with adjustment for fixed and random effects (patient and provider) were performed. Covariates with a standardized difference of <0.1 as well as 4 factors chosen a priori (baseline CDAI, steroid use, background methotrexate use, and number of prior TNFi’s) were included in the models. As a sensitivity analysis, we reran the analyses using PS matched TNFi and RTX initiators. Results 266 RTX users and 744 TNFi users who met inclusion criteria were included in the analyses. Baseline characteristics are described in Table 1. As compared to the TNFi users, RTX users were older, had a greater duration of RA, had prior exposure to a greater number of prior biologics and were more likely to be receiving prednisone. Achievement of low disease activity occurred in 35% of the RTX users and 28% of the TNFi users. RTX was associated with a greater likelihood of achievement of low disease activity (1.74, 95% CI 1.22-2.47) after adjustment for age, race, insurance status, comorbidity, and RA characteristics (baseline disease activity, severity and medication use [current and prior]). Results from PS matched multivariable analyses were similar. Overall reported rates in RTX users were 0.02 events per person-year (PPY) (95% CI 0.01-0.04) for cardiovascular events, 0.02 PPY (95% CI 0.01-0.05) for serious infections and 0.02 PPY (95% CI 0.01-0.04) for malignancies. The rates in TNFi users were 0.02 PPY (95% CI 0.01-0.03), 0.03 PPY (95% 0.02-0.05) and 0.02 PPY (95% 0.01-0.03), respectively. Image/graph Conclusions In RA patients who failed 1 or more TNFi agents, use of RTX was associated with a higher likelihood of achieving CDAI low disease activity than use of a subsequent TNFi. Disclosure of Interest: L. Harrold Grant/research support from: National Institute of Health - K23AR053856, Consultant for: CORRONA, G. Reed Consultant for: University of Massachusetts Medical School, Employee of: CORRONA, R. Magner Employee of: University of Massachusetts Medical School, A. Shewade Employee of: Genentech, Inc., A. John Employee of: Genentech, Inc., W. Reiss Employee of: Genentech, Inc., J. Greenberg Shareholder of: CORRONA, Consultant for: AstraZeneca, CORRONA, Novartis and Pfizer, J. Kremer Shareholder of: CORRONA, Employee of: CORRONA

Sustained Response Following Discontinuation of Methotrexate in Patients With Rheumatoid Arthritis Treated With Subcutaneous Tocilizumab: Results From a Randomized, Controlled Trial

To evaluate whether tocilizumab (TCZ) monotherapy is noninferior to treatment with TCZ plus methotrexate (MTX) for maintaining clinical responses in patients with rheumatoid arthritis (RA) in whom low disease activity is achieved with TCZ plus MTX.

RAPID3 and ACR/EULAR Provisional Remission Definitions as Predictors of Radiographic Outcome in a Rheumatoid Arthritis Clinical Trial With Tocilizumab

The American College of Rheumatology/European League Against Rheumatism established definitions of remission for rheumatoid arthritis (RA) based on composite scores, including tender (TJC) and swollen joint counts (SJC), patient global visual analog scale (VAS) score, laboratory tests, and, in the Simplified Disease Activity Index (SDAI), the physician global score. Time constraints on a physicians schedule demand an easy yet accurate tool to measure disease activity. We assessed the predictive ability of the Routine Assessment of Patient Index Data 3 (RAPID3) with and without a single swollen joint versus the SDAI and/or Boolean remission criteria for functional and radiographic outcomes.

Composite Indices Using 3 or 4 Components of the Core Data Set Have Similar Predictive Ability to Measure Disease Activity in RA: Evidence from the DANCER and REFLEX Studies

Background. Understanding how disease-assessment indices perform in rheumatoid arthritis (RA) clinical trials can inform their use in routine practice. The study objective was to assess the capacity of combinations of RA Core Data Set measures to distinguish rituximab from control treatment. Methods. Post hoc analysis of two randomised clinical trials was used. Composite Efficacy Indices were derived by combining three or four RA Core Data Set measures from three possible sources: physician, patient, and laboratory. Results. All 105 Composite Efficacy Indices evaluated significantly distinguished rituximab from control treatment (P < 10−7). Generally, indices containing measures from three different sources had a greater capacity to distinguish rituximab from control treatment than indices containing three measures from one source. Composite Efficacy Indices performed as well as validated indices such as DAS28, RAPID3, and CDAI. Conclusions. All indices composed of three or four RA Core Data Set measures have a similar capacity to detect treatment differences. These results suggest that the precise measurement used is less important than whether any measurement is performed, although selection should be consistent for each patient. Therefore, the choice of assessment tool should not be limited to a prescribed list and should instead be left to the clinicians discretion.

AB0448 Patient-reported outcomes following discontinuation of methotrexate in patients with rheumatoid arthritis treated with subcutaneous tocilizumab: results from a randomised controlled trial

Background Patients with rheumatoid arthritis (RA) often receive methotrexate (MTX) in combination with biologics; however, MTX may be discontinued due to intolerance or to reduce the medication burden once disease control is achieved. Whereas previous studies have established the efficacy of tocilizumab (TCZ) initiated as monotherapy (MONO) for the treatment of RA,1,2 patient-reported outcomes (PROs) after MTX withdrawal in patients achieving good clinical response to TCZ +MTX have not been evaluated. PROs are important measures when determining response to therapy in patients with RA with respect to health-related quality of life (HRQOL).3,4 Objectives This study evaluated PROs between patients with RA who achieved low disease activity with TCZ +MTX and then continued or discontinued MTX in the COMP-ACT trial (NCT01855789). Methods US patients with RA who were inadequate responders to MTX were enrolled; initial combination therapy included MTX (≥15 mg/week orally) plus TCZ 162 mg subcutaneous either weekly (qw) or every 2 weeks (q2w). Patients who achieved DAS28-ESR≤3.2 at Week 24 were randomised 1:1 to receive TCZ-MONO or continue TCZ +MTX until week 52 (double-blind). Changes in PRO scores were measured between Week 24 and Weeks 40 and 52, and included patient global assessment of disease activity (PtGA; visual analogue score [VAS], 0–100 mm), pain (VAS), Health Assessment Questionnaire Disability Index (HAQ-DI, 0–3) and Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue. Results Of the 296 randomised patients (TCZ +MTX, n=148; TCZ-MONO, n=148), 74.8% were women, mean age was 55.5 years, mean RA duration was 6.8 years and mean DAS28-ESR was 6.3 at baseline. At Week 24 (randomization), PRO scores were similar between the randomised treatment groups. The mean changes in PtGA, pain, HAQ-DI and FACIT-fatigue scores from Week 24 to Weeks 40 were similar between the TCZ +MTX and TCZ-MONO groups (table 1). The proportion of patients with HAQ-DI <0.5 was similar between the groups at Week 24 (randomization), and remained similar at Weeks 40 and 52.Abstract AB0448 – Table 1 Changes in Patient-Reported Outcomes from Week 24 (Randomization) to Week 40 and Week 52 FACIT, Functional Assessment of Chronic Illness Therapy; HAQ-DI, Health Assessment Questionnaire Disability Index; MONO, monotherapy; MTX, methotrexate; PtGA, patient global assessment; SEM, standard error of the mean; TCZ, tocilizumab. * A negative change in score represents an improvement in the respective PRO except for Fatigue. † Estimated means from ANCOVA model includes Week 24 value as a covariate, treatment group, and the randomization stratification factors: DAS28 remission status at Week 24 (<2.6,≥2.6 to≤3.2), baseline weight-by-dosing group (<80 kg every 2 weeks [q2w],<80 kg weekly [qw], 80 to <100 kg q2w, 80 to <100 kg qw,≥100 kg qw), patient anti-TNF exposure (Yes or No). Conclusions Patients receiving TCZ who discontinue MTX appear to have similar PROs across multiple measures compared with patients continuing TCZ +MTX. Differences observed in clinical parameters between TCZ-MONO and TCZ +MTX did not appear to achieve a threshold that would be considered clinically meaningful. Similarities in PROs on both treatments were consistent with the clinical efficacy measures previously reported from COMP-ACT. References [1] Jones G, et al. J Rheumatol2017;44(2):142–6. [2] Dougados M, et al. Ann Rheum Dis. 2013;72(1):43–50. [3] Deshpande PR, et al. Perspect Clin Res. 2011;2(4):137–44. [4] Her M, Kavanaugh A. Curr Opin Rheumatol. 2012;24(3):327–34. Acknowledgements This study was funded by Genentech, Inc. Disclosure of Interest J. Kremer Shareholder of: Corrona, LLC, Consultant for: Abbvie, Amgen, Bristol-Myers Squibb, Eli Lilly and Company, Genentech, GlaxoSmithKline, Pfizer, Regeneron and Sanofi, W. Rigby Consultant for: Roche/Genentech, N. Singer Grant/research support from: Merck/EMD Serono (in kind lab resources) and unrestricted educational grants from several companies to MetroHealth for 2016 Cleveland Society of Rheumatology, C. Birchwood Employee of: Genentech, Inc., D. Gill Employee of: Genentech, Inc., W. Reiss Employee of: Genentech, Inc., J. Best Employee of: Genentech, Inc., J. Pei Employee of: Genentech, Inc., M. Michalska Employee of: Genentech, Inc.

FRI0222 Prevalence of low immunoglobulin levels and associations with rheumatoid arthritis factors

Background Little is known about the prevalence and the clinically associated factors of low IgG and IgM levels in patients (pts) with RA. Objectives To estimate the prevalence of low IgG and IgM levels in pts with RA and to investigate factors associated with low Ig Methods This cross-sectional analysis evaluated Ig levels measured centrally at the time of enrollment in CERTAIN, a prospective comparative effectiveness study of biologics nested within CORRONA. Multivariate models (MV) evaluated factors associated with low Ig levels. Results Characteristics for the 1151 enrollments were analyzed: 76% women, 86% Caucasian, 67% seropositive. The mean (±SD) age was 56.1 (±13.5) years, RA duration was 8.5 (±9.1) years and CDAI was 29.1 (±13.0). At the time of evaluation 35.7% of pts were biologic-naïve and 39.6% received prednisone in the last 6 months (34.8% of them ≤10mg/day). Low IgG (<700mg/dl) was noted in 76 (6.6%) pts and low IgM (<40mg/dl) in 63 (5.5%) pts. MV (Table 1) showed that pts with high disease activity were more likely to have low IgG. Prior exposure to biologics was not associated with low IgG or IgM. Instead, an opposite trend was suggested for prior exposure to TNF-α inhibitors. MV suggested that higher doses of prednisone are likely to be associated with low IgG levels and that seropositive pts are more likely to have normal Ig levels. Image/graph Conclusions High disease activity was associated with increased odds of low IgG. Effect of biologic agents, steroids and other factors on Ig levels, and clinical outcomes will be evaluated in a longitudinal analysis when CORRONA-CERTAIN is completed. Disclosure of Interest: D. Pappas Employee of: Columbia University, Paid instructor for: Novartis, A. John Employee of: Genentech, Inc., J. Curtis Grant/research support from: Roche/Genentech, UCB, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, Abb Vie, Consultant for: Roche/Genentech, UCB, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, Abb Vie, J. Kremer Shareholder of: CORRONA, Employee of: CORRONA, W. Reiss Employee of: Genentech, Inc., A. Shewade Employee of: Genentech, Inc., G. Silverman Grant/research support from: NIH, ACR, RRF, Consultant for: Lilly, Genentech, Roche, Pfizer, Employee of: New York University, J. Greenberg Shareholder of: CORRONA, Consultant for: AstraZeneca, CORRONA, Novartis, Pfizer