ObjectiveTo investigate whether antidrug antibodies and/or drug non‐trough levels predict the long‐term treatment response in a large cohort of patients with rheumatoid arthritis (RA) treated with adalimumab or etanercept and to identify factors influencing antidrug antibody and drug levels to optimize future treatment decisions.MethodsA total of 331 patients from an observational prospective cohort were selected (160 patients treated with adalimumab and 171 treated with etanercept). Antidrug antibody levels were measured by radioimmunoassay, and drug levels were measured by enzyme‐linked immunosorbent assay in 835 serial serum samples obtained 3, 6, and 12 months after initiation of therapy. The association between antidrug antibodies and drug non‐trough levels and the treatment response (change in the Disease Activity Score in 28 joints) was evaluated.ResultsAmong patients who completed 12 months of followup, antidrug antibodies were detected in 24.8% of those receiving adalimumab (31 of 125) and in none of those receiving etanercept. At 3 months, antidrug antibody formation and low adalimumab levels were significant predictors of no response according to the European League Against Rheumatism (EULAR) criteria at 12 months (area under the receiver operating characteristic curve 0.71 [95% confidence interval (95% CI) 0.57, 0.85]). Antidrug antibody–positive patients received lower median dosages of methotrexate compared with antidrug antibody–negative patients (15 mg/week versus 20 mg/week; P = 0.01) and had a longer disease duration (14.0 versus 7.7 years; P = 0.03). The adalimumab level was the best predictor of change in the DAS28 at 12 months, after adjustment for confounders (regression coefficient 0.060 [95% CI 0.015, 0.10], P = 0.009). Etanercept levels were associated with the EULAR response at 12 months (regression coefficient 0.088 [95% CI 0.019, 0.16], P = 0.012); however, this difference was not significant after adjustment. A body mass index of ≥30 kg/m2 and poor adherence were associated with lower drug levels.ConclusionPharmacologic testing in anti–tumor necrosis factor–treated patients is clinically useful even in the absence of trough levels. At 3 months, antidrug antibodies and low adalimumab levels are significant predictors of no response according to the EULAR criteria at 12 months.

Knee osteoarthritis (OA) is a heterogeneous disease, and identification of its subgroups/phenotypes can improve patient treatment and drug development. We aimed to identify homogeneous OA subgroups/phenotypes using pain development over time; to understand the interplay between pain and functional limitation in time course, and to investigate subgroups' responses to available pharmacological and surgical treatments. We used group-based trajectory modelling to identify pain trajectories in the phase-three VIDEO trial (n=474, three-year follow-up) and also in the Osteoarthritis Initiative cohort study (n=4796, nine-year follow-up). We extended trajectory models by (1) fitting dual trajectories to investigate the interplay between pain and functional limitation over time, and (2) including analgesic use as a time-varying covariate. Also, we investigated the relationship between trajectory-groups and knee replacement in regression models. We identified four pain trajectory-groups in the trial and six in the cohort. These overlapped and led us to define four OA phenotypes: low-fluctuating, mild-increasing, moderate-treatment-sensitive and severe-treatment-insensitive pain. Over time, functional knee limitation followed the same 8 8 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. trajectory as pain with almost complete concordance (94.3%) between pain and functional limitation trajectory-groups. Notably, we identified a phenotype with severe pain that did not benefit from available treatments, and another one most likely to benefit from knee replacement. Thus, knee OA subgroups/phenotypes can be identified based on patients' pain experiences in studies with long and regular follow-up. We provided a robust approach, reproducible between different study designs that informs clinicians about symptom development and delivery of treatment options and opens a new avenue toward personalized medicine in OA.

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