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AB0374 Flare incidence and predictive factors in a population of patients with rheumatoid arthritis under optimised treatment with adalimumab and infliximab
  1. A Pieren1,
  2. C Plasencia1,
  3. D Pascual-Salcedo2,
  4. MB Paredes1,
  5. A Balsa1
  1. 1Rheumatology
  2. 2Immunology, Hospital la Paz, Madrid, Spain

Abstract

Background Anti-TNF are nowadays widely used for the treatment of Rheumatoid Arthritis (RA),which has drastically changed the prognostic of the disease,carrying an important healthcare expense.This is why,optimisation seems a successful strategy that should not be linked to a worse become of our patients' clinical evolution.

Objectives Describe a population of patients with RA under optimised treatment with Adalimumab (Ada) and Infliximab (Ifx).Study the incidence of flares and establish predictive factors of flares at baseline and pre-optimization.

Methods Observational study of the prospective cohort RA-Paz. All the patients diagnosed of RA under treatment with Ifx and Ada between Jan.2000 and Dec.2016 of the day-care unit of La Paz Hospital,were included.Demographic data,clinical activity and blood sample results were collected at baseline, pre-optimization (pre-op)and at 3,6,9,12,18 and 24 months.Drug serum trough levels were measured under ELISA in each visit.Optimal range for Ifx was described as drug concentration between 1000- 4000 ng/ml and 1500- 5000 ng/ml for Ada.Optimisation was defined as drug use below standard dose.Flares were collected from the pre-op visit.Flare was described as clinical worsening which led to a therapeutic change or a DAS28>3.2 and DeltaDAS28>0,6.Predictive factors of flare at baseline and pre-op were evaluated with a uni and multivariate analysis. Statistical study was performed with the statistical program SPSS.

Results Of the 271 patients diagnosed of RA, 74 patients were optimised (44 under Ada and 30 under Ifx). Baseline demographic caracteristics are shown in the table below.During the 24 months after the pre-op visit, 55,4% (41)of the patients presented at least one flare,with an average of 1,38 flares [1–5]. Most of the patients (53.7%,22/41),were controlled with the adjustment of non biological treatment.Only 39,0% (16) of the patients,had to go back to the previous optimised dose and 7,3% (3)to the standard dose.88% (39/41)were controlled after the dose modification.104 flares were collected,33% (34) happened at the 3rd month and 20% (21) at 24th. In the population who presented flares, we observed a persistent higher DAS Vs the patients who never presented flares (DAS pre-op 3,20±1,16 Vs 2,26±0,59;DAS 24month 3,61±1,13Vs2,10±0,65;p=0,007). A least proportion of patients with flares were in supra-optimal range (13,3% with flares vs 26% without, p=0,007). At baseline, no clinical factors were predictive of flare. Nor were blood sample results. In contrast, a higher disease activity, measured by DAS pre-op (p=0,004),a worst EULAR answer (p=0,027) and not being in supra-optimal range (p=0,032),were statistically correlated with flares development at the univariate analysis. Time to the optimisation tended to the significance (OR=1,152; p=0.08). In the multivariate analysis, only a higher DAS pre-op (OR:2,00,[1,08–3,73])and being in optimal (OR:5,90, [1,38–25,2])and sub-optimal range (OR=6,05 [1,28–28,7]), were independently correlated.

Conclusions In our cohort of optimised patients, we noted a high proportion of flares. However, flares were controlled with dosage readjustment without needing a treatment change. Independently correlated predictive factors for flares were a higher disease activity measured by DAS and not being in therapeutic range in the pre-optimisation visit.

Disclosure of Interest None declared

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