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OP0110 Association of pharmacological biomarkers with treatment response and long-term disability in patients with psoriatic arthritis: results from outpass
  1. M Jani1,2,
  2. H Chinoy1,2,
  3. A Barton1,2,
  4. on behalf of Outcomes of Psoriatic Arthritis Study Syndicate (OUTPASS)
  1. 1NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester Academic Health Science Centre, Central Manchester Foundation Trust and University of Manchester
  2. 2Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom


Background Up to 40% of patients with inflammatory arthritis on TNF-α inhibitor (TNFi) treatment fail to respond either due to primary inefficacy or loss of response. One explanation is immunogenicity leading to the development of anti-drug antibodies (ADAb) and subsequent low drug levels. Few data exist on whether such pharmacological tests correlate with treatment response in psoriatic arthritis (PsA). The clinical utility of whether such tests should be incorporated into practice is in question.

Objectives To identify (i) whether the presence of ADAbs/drug levels predict treatment response and disability in TNFi-treated PsA patients (ii) the factors associated with drug levels (iii) a drug level threshold for optimal therapeutic response.

Methods 75 patients were available from the Outcomes of Treatment in PsA Study Syndicate (OUTPASS) [n=49 adalimumab; n=26 etanercept], a national UK prospective observational cohort. Serum samples were collected at 3, 6 and 12 months following initiation of TNFi therapy. ADAbs were measured using radioimmunoassay (RIA) and random (non-trough) drug levels using ELISA assays at 3, 6 and 12 months. Disease activity (DAS28) scores were measured at each visit. Patient self-reported adherence to TNFi was measured at each time-point. Generalised estimating equation (GEE) was used to test the association between ADAbs and drug levels, both biomarkers and treatment response [as assessed by change in DAS28 score between pre-treatment and 12 months post-treatment (ΔDAS28)], Health assessment Questionnaire (HAQ) and the association between longitudinal/baseline factors with drug levels.

Results 264 serial samples were suitable for pharmacological testing (n=174 adalimumab; n=90 etanercept). Mean age was 51±12 years; 61% were female; median BMI 28.9 (IQR 26.0–34.9). 20% (n=10/49) of adalimumab-treated patients were positive for ADAbs, but none were detected in etanercept-treated patients. There was no significant association between etanercept drug levels and ΔDAS over 12 months [β= -0.039 (95% CI -0.31, 0.23), p=0.77]. Using GEE, adalimumab drug levels were significantly associated with ΔDAS28 over 12 months [β=0.055 (95% CI: 0.011, 0.099) p=0.014] and inversely with HAQ scores over 12 months [β= -0.022 (95% CI: -0.043, -0.00063]. ΔDAS28 was not independently associated with ADAb level [β=-0.0015 (95% CI: -0.0031, 0.000047), p=0.057]. Adalimumab concentrations between 4.5–8.5 mg/L were associated with an optimal treatment response at 6 months using concentration-effect curves. Factors that were significantly associated with adalimumab drug levels were ADAb level [β=-0.0073 (95% CI: -0.0014, 0.18), p<0.0001] and BMI [β=-0.15 (-0.29, -0.00450, p=0.043] in the final GEE model (adjusting for age, gender, adherence, BMI).

Conclusions TNFi drug-level testing in adalimumab-initiated PsA patients may be useful in determining treatment response and disability over 12 months; interestingly, both the presence of ADAbs and BMI were inversely associated with drug levels. Identification of a drug level threshold for optimal response may help tailor adalimumab therapy for PsA patients in the future.

Acknowledgements This work was funded from a grant awarded by the National Institute of Health and Research, Manchester Musculoskeletal BRU to MJ, AB.

Disclosure of Interest M. Jani Grant/research support from: Abbvie, UCB, Pfizer, H. Chinoy Grant/research support from: Novartis, Abbvie, Consultant for: Eli-Lilly and Novartis, Speakers bureau: UCB, A. Barton Grant/research support from: Eli-Lilly, Speakers bureau: Roche Chugai and Pfizer

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