Chieh-I Chen

Treatment effectiveness and treatment patterns among rheumatoid arthritis patients after switching from a tumor necrosis factor inhibitor to another medication

Objectives After treatment failure with a tumor necrosis factor inhibitor (TNFi), patients with rheumatoid arthritis (RA) can switch to another TNFi (TNFi cyclers) or to a targeted disease-modifying antirheumatic drug (DMARD) with a non-TNFi mechanism of action (non-TNFi switchers). This study compared treatment patterns and treatment effectiveness between TNFi cyclers and non-TNFi switchers in patients with RA. Methods The analysis included a cohort of patients from the Truven Health Analytics MarketScan Commercial database with RA who switched from a TNFi (adalimumab, certolizumab pegol, etanercept, golimumab, or infliximab) either to another TNFi or to a non-TNFi targeted DMARD (abatacept, tocilizumab, or tofacitinib) between January 1, 2010 and September 30, 2014. A claims-based algorithm was used to estimate treatment effectiveness based on six criteria (adherence, no dose increase, no new conventional therapy, no switch to another targeted DMARD, no new/increased oral glucocorticoid, and intra-articular injections on <2 days). Results The cohort included 5,020 TNFi cyclers and 1,925 non-TNFi switchers. Non-TNFi switchers were significantly less likely than TNFi cyclers to switch therapy again within 6 months (13.2% vs 19.5%; P<0.001) or within 12 months (29.7% vs 34.6%; P<0.001) and significantly more likely to be persistent on therapy at 12 months (61.8% vs 58.2%; P<0.001). Non-TNFi switchers were significantly more likely than TNFi cyclers to achieve all six of the claims-based effectiveness algorithm criteria for the 12 months after the initial switch (27% vs 24%; P=0.011). Conclusion Although the absolute differences were small, these results support switching to a non-TNFi targeted DMARD instead of TNFi cycling when patients with RA require another therapy after TNFi failure.

Outcomes of tumor necrosis factor inhibitor cycling versus switching to a disease-modifying anti-rheumatic drug with a new mechanism of action among patients with rheumatoid arthritis

Abstract Objectives: To examine treatment patterns, treatment effectiveness, and treatment costs for 1 year after patients with rheumatoid arthritis switched from a tumor necrosis factor inhibitor (TNFi) (adalimumab, certolizumab pegol, etanercept, golimumab, or infliximab), either cycling to another TNFi (“TNFi cyclers”) or switching to a new mechanism of action (abatacept, tocilizumab, or tofacitinib) (“new MOA switchers”). Methods: This retrospective cohort study used administrative claims data for a national insurer. Treatment persistence (without switching again, restarting, or discontinuing), treatment effectiveness (defined below), and costs were assessed for the 12-month post-switch period. Patients were “effectively treated” if they satisfied all six criteria for a treatment effectiveness algorithm (high adherence, no dose increase, no new conventional synthetic disease-modifying anti-rheumatic drug, no subsequent switch in therapy, no new/increased oral glucocorticoids, and <2 glucocorticoid injections). Multivariable logistic models were used to adjust for baseline factors. Results: The database included 581 new MOA switchers and 935 TNFi cyclers. New MOA switchers were 39% more likely than TNFi cyclers to persist after the switch (odds ratio [OR] = 1.39; 95% confidence interval [CI] = 1.12–1.74; p = .003) and 36% less likely to switch therapy again (OR = 0.64; 95% CI = 0.51–0.81; p < .001). New MOA switchers were 43% more likely than TNFi cyclers to be effectively treated (OR = 1.43; 95% CI = 1.11–1.85; p = .006). New MOA switchers had 16% lower drug costs than TNFi cyclers (cost ratio = 0.84; 95% CI = 0.79–0.88; p < .001) and 11% lower total costs of rheumatoid arthritis-related medical care (cost ratio = 0.89; 95% CI = 0.84–0.94; p < .001). Limitations: Claims payments may not reflect rebates or other cost offsets. Medical and pharmacy claims do not include clinical end-points or reasons that lead to new MOA switching vs TNFi cycling. Conclusions: These results support switching to a new MOA after a patient fails treatment with a TNFi, which is consistent with recent guidelines for the pharmacologic management of established rheumatoid arthritis.

OP0133 Differences in Physician-Reported and DAS28-Based Assessment of Disease Remission Among Patients with Rheumatoid Arthritis (RA) in Clinical Practices

Background The ultimate goal of RA treatment is to achieve disease remission. Studies have shown that objective, measure-based treatment decision-making leads to improved patient outcomes. In addition, the National Quality Forum (NQF) recently endorsed three measures for RA, including assessment of disease activity using a standardized tool. However, in clinical practice physicians may still rely on subjective assessment of disease activity. Objectives To compare physician-reported and DAS28-based clinical assessments of RA disease remission. Methods Data were drawn from the Adelphi RA-DSP, a cross-sectional survey of United States rheumatologists and their RA patients between January and March 2014. Clinical remission status (DAS28 ESR <2.6) was compared with physician-reported remission and categorized as “match”, “physician over-reported” (physician-reported remission, but no-remission by DAS28 criteria) and “physician under-reported” (physician-reported no-remission, but remission by DAS28 criteria). Multinomial logistic regressions were conducted to evaluate patient and physician characteristics associated with differences between DAS28-based and physician-reported remission. Results Included in the analysis were 531 RA patients (75% female, mean age 56.4 years, 7.7 years since RA diagnosis, 53% treated with biologic) in the care of 78 rheumatologists (31% female, 37% practice only in office). 56% of physicians reported using only subjective criteria to assess remission; 30% of patients were evaluated using a standardized disease activity measure during last visit. While physicians reported 50% of patients were in remission, 32% were in remission by DAS28 criteria. Remission status was over-reported by physicians in 25% and underreported in 7% of patients. Regression analyses indicated that physician over-reporting was significantly higher among patients treated with biologics (Relative Risk Ratio (RRR)=2.01, P=0.003), those in the care of physicians with high RA workload (RRR=2.51, P=0.011), and patients considered by their physicians to have “satisfactory” RA control (RRR=6.09, P<0.001) or with average general health level (RRR=1.87, P=0.049); but significantly lower for patients with medium to high current pain level (RRR=0.23, P=0.004) or considered by their physicians to be highly involved in treatment (RRR=0.60, P=0.035). Physician under-reporting was significantly higher among obese patients (RRR=2.95, P=0.002), patients with average general health level (RRR=2.03, P=0.029), and those with more than 5 tender or swollen joints (RRR=2.72, P=0.019), but significantly lower among patients with medium to high current pain level (RRR=0.18, P=0.004) or those who saw physicians with high RA workload (RRR=0.43, P=0.029). Conclusions This study points out the need to increase the use of standardized measures of RA disease activity, and ensure consistency of use across clinical care. Addressing these gaps in care may help optimize treatment decisions, reduce variability in delivery of patient care and ultimately improve RA patient outcomes. Disclosure of Interest W. Wei Shareholder of: Sanofi, Employee of: Sanofi, C. Chen: None declared, E. Sullivan: None declared, S. Blackburn: None declared, J. Curtis Grant/research support from: Roche/Genentech, UCB, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, AbbVie, Consultant for: Roche/Genentech, UCB, Janssen, CORRONA, Amgen, Pfizer, BMS, Crescendo, AbbVie

Burden of rheumatoid arthritis among US Medicare population: co-morbidities, health-care resource utilization and costs

Abstract Objectives The study aimed to assess the burden of RA among the US Medicare population (aged ≥65 years) by comparing co-morbidities, health-care resource utilization (HCRU) and costs against matched non-RA Medicare patients. Methods Data were obtained from the Medicare fee-for-service claims database from 2010 to 2013. RA Medicare patients were identically matched with Medicare patients without RA (controls) based on demographics. Bivariate analyses were conducted to examine differences between cohorts for co-morbidities, HCRU and costs. A generalized linear model was used to test relationships between patient-level characteristics, HCRU and costs. Results The study population included 115 867 RA patients and 115 867 age-, sex-, race- and region-matched non-RA controls. Mean age was 75.2 years; 79.4% were female. Co-morbidities were greater in RA vs non-RA patients [Charlson Co-morbidity Index (excluding RA): 1.86 vs 1.00; P < 0.0001]. All-cause annual HCRU was greater in RA vs non-RA patients. Total annual health-care costs were ∼3-fold higher in RA vs non-RA patients (

OP0102 Patient reported benefits of sarilumab monotherapy versus adalimumab monotherapy in adult patients with active rheumatoid arthritis

20 919 vs

AB0359 Treatment Effectiveness for Rheumatoid Arthritis after Switching from A Tumor Necrosis Factor Inhibitor to Another Agent

7197, respectively; P < 0.0001) with the major driver of costs in the RA cohort being outpatient costs. Approximately half of the overall costs in the RA cohort were RA related (

FRI0550 Real-World Treatment Patterns among Rheumatoid Arthritis Patients Who Switch from A Tumor Necrosis Factor Inhibitor To Another Medication

11 587). After controlling for differences in patient characteristics and co-morbidities between cohorts, the adjusted total mean annual costs for RA patients were still more than twice those of non-RA patients (

FRI0233 Real-World Treatment Persistence and Clinical Outcomes of TNFI Cycling vs Switching To New Mechanism-of-Action Dmards among Patients with Rheumatoid Arthritis in The United States

16 374 vs

AB0321 Predicting the Need for Rescue Medication Using Baseline Variables: Evidence from Rheumatoid Arthritis (RA) Patients in the Sarilumab Mobility Phase 3 Trial

6712; P < 0.0001). Conclusions Among US Medicare patients, those with an RA diagnosis had a significantly greater burden of co-morbidities, HCRU and costs compared with a matched cohort without RA.

FRI0058 Improvements in Health Related Quality of Life (HRQOL) Reported by Rheumatoid Arthritis (RA) Patients in a Randomized Controlled Trial [RCT] of Sarilumab [Mobility] that Met or Exceeded the Patient Acceptable Symptom State [Pass] And Normative Values

Background The phase 3 MONARCH superiority study (NCT02332590) compared efficacy and safety of sarilumab (a human anti-IL-6Rα monoclonal antibody [mAb]) 200 mg administered subcutaneously every 2 weeks (q2w), with adalimumab (an anti-TNF-α mAb) 40 mg administered q2w, in patients with active rheumatoid arthritis (RA) who were either intolerant of, or inadequate responders to methotrexate treatment. Sarilumab monotherapy demonstrated superiority to adalimumab monotherapy in reduction of disease activity and improvements in physical function and signs and symptoms of RA, with safety and tolerability consistent with IL-6R or TNF blockade. Objectives To compare patient-reported outcomes (PROs) with sarilumab vs adalimumab from MONARCH. Methods PROs assessed at baseline, weeks 12 and 24 included ACR components (Patient Global Assessment of Disease Activity [PtGA], Pain visual analog scale [VAS], Health Assessment Questionnaire Disability Index [HAQ-DI]), Medical Outcomes Study Short Form-36 (SF-36), Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F), Morning Stiffness VAS, RA Impact of Disease (RAID) and RA-specific Work Productivity Survey (WPS-RA). Least-squares mean (LSM) between-group differences were determined by mixed-model for repeated measures with treatment, visit, treatment-by-visit interaction and region as fixed effects, and the corresponding baseline PRO scores as continuous covariates. A P-value <0.05 was considered statistically significant for PROs in a predefined hierarchy (ACR components, SF-36 physical component summary [PCS], FACIT-F and SF-36 mental component summary [MCS] scores). For PROs not in the hierarchy, significance is not claimed. Changes from baseline were compared with published values for minimum clinically important differences (MCIDs). Results Baseline demographics, disease characteristics and PROs were generally balanced between treatment groups (n=184 sarilumab; n=185 adalimumab). Improvements from baseline to week 24 were greater with sarilumab vs adalimumab across PtGA, Pain VAS, HAQ-DI, SF-36 PCS, Morning Stiffness VAS, RAID and WPS-RA global scores (all P<0.05, statistical significance is claimed only for PROs in the hierarchy; see table). Between-group differences in FACIT-F and SF-36 MCS scores were not significant. Improvements ≥MCID were reported by a greater percentage of patients with sarilumab than adalimumab for HAQ-DI (≥0.22 units), RAID (≥3 units), SF-36 PCS (≥2.5), and Morning Stiffness VAS (≥10) (all nominal P<0.05). Conclusions Sarilumab monotherapy compared with adalimumab monotherapy resulted in greater and clinically meaningful improvements in many PROs, including patient-reported disease activity, pain, physical function, morning stiffness, productivity, health related quality of life and health status. Acknowledgements This study was sponsored by Sanofi and Regeneron Pharmaceuticals, Inc. Disclosure of Interest V. Strand Consultant for: AbbVie, Amgen, AstraZeneca, Biogen, BMS, Celltrion, CORRONA, Crescendo, Genentech/Roche, GSK, Janssen, Eli Lilly, Novartis, Pfizer, Regeneron Pharmaceuticals, Sandoz, Sanofi, and UCB, L. Gossec Grant/research support from: Member of institution that received research funding for the current study, C. Proudfoot Shareholder of: Sanofi, Employee of: Sanofi, C. Chen Shareholder of: Regeneron Pharmaceuticals, Inc., Employee of: Regeneron Pharmaceuticals, Inc., M. Reaney Shareholder of: Sanofi, Employee of: Sanofi, S. Guillonneau Shareholder of: Sanofi, Employee of: Sanofi, T. Kimura Shareholder of: Regeneron Pharmaceuticals, Inc., Employee of: Regeneron Pharmaceuticals, Inc., J. van Adelsberg Shareholder of: Regeneron Pharmaceuticals, Inc., Employee of: Regeneron Pharmaceuticals, Inc., Y. Lin Shareholder of: Sanofi, Employee of: Sanofi, E. Mangan Shareholder of: Pfizer Inc. and Regeneron Pharmaceuticals, Inc., Employee of: Regeneron Pharmaceuticals, Inc., H. van Hoogstraten Shareholder of: Sanofi, Employee of: Sanofi, G. R. Burmester Grant/research support from: Member of institution that received research funding for the current study