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OP0070 Inequity: Level of Education is Associated with Access to Biologic DMARDS Even in A Country with Highly Developed Social Welfare (NORWAY)
  1. P. Putrik1,2,
  2. S. Ramiro3,4,
  3. E. Lie5,
  4. A.P. Keszei6,
  5. T. Uhlig5,
  6. T.K. Kvien5,
  7. D. van der Heijde7,
  8. R. Landewé3,8,
  9. A. Boonen2
  1. 1Health Promotion and Education, Maastricht University
  2. 2Rheumatology, Maastricht University, CAPHRI, MUMC, Maastricht
  3. 3Clinical Immunology & Rheumatology, ARC, Amsterdam, Netherlands
  4. 4Rheumatology, Hospital Garcia de Orta, Almada, Portugal
  5. 5Rheumatology, Diakonhjemmet Hospital, Oslo, Norway
  6. 6Epidemiology, Maastricht University, Maastricht
  7. 7Rheumatology, Leiden University Medical Center, Leiden
  8. 8Rheumatology, Atrium Medical Center, Heerlen, Netherlands

Abstract

Background Biologic DMARDs (bDMARDs) have greatly improved the outcome of rheumatoid arthritis (RA). Investigating possible inequities in access to bDMARDs across socio-economic factors is important, and such analyses could provide clinicians and healthcare decision makers with useful information.

Objectives To explore whether there are differences in initiation rates for a first bDMARD across age, gender and educational status among RA patients.

Methods Data from the Norwegian NOR-DMARD study (2000-2012) was used. Only patients who were DMARD naïve at entrance into the study were included in the analyses. The first prescription of any bDMARD was the event of interest. In order to assess impact of education, age and gender on time to first bDMARD, two Cox regression models were built using forward step-wise modelling strategy. The first model included baseline predictors; the second was a time-varying model accounting for clinical information of all other visits between study inclusion and either start of bDMARD or censoring. Interactions between education and either year of baseline visit or age were tested.

Results In total, 1861 patients were included (mean age at baseline 56 yrs, 68% females), and 368 patients received a bDMARD in the time of the period of observation (mean time to bDMARD 2.60 yrs). In both models, the socio-economic factors age and education were significant predictors of time-till-prescription (prescription of a first bDMARD), with lower hazard ratios (HR) for lower education and older age (Table). Education and age consistently and significantly contributed to the model. Effect of lower education was more pronounced in later years (HRlow vs. high education =0.17 and 0.34 in patients who entered the cohort in 2008-2011, in time-varying and baseline models, respectively).

Conclusions Well-educated and younger patients apparently have potentially decisive advantages with regard to access to expensive treatments, even a country with highly developed welfare like Norway. A stronger effect of education in later years might be explained by changes in prescription practice and social trends towards longer education. Findings are relevant as the impact of age and education on access might result in avoidable adverse impact on health.

Disclosure of Interest None declared

DOI 10.1136/annrheumdis-2014-eular.2036

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