Oral Presentation ARA-NSW 2019 - 41st Annual NSW Branch Meeting

Lower socioeconomic status is a predictor of opioid use in patients with inflammatory arthritis: a 16 year prospective longitudinal cohort. (#10)

Marissa N Lassere 1 2 , Ashley Fletcher 3 , Rachel Black 4 5 , Claire Barrett 6 , Graeme Carroll 7 , Susan Lester 5 8 , Bethan Richards 9 , Lyn March 10 11 , Rachelle Buchbinder 3 12 , Catherine Hill 4 5
  1. Department of Rheumatology, St George Hospital, Kogarah, NSW, Australia
  2. School of Public Health and Community Medicine, UNSW, Sydney, NSW, Australia
  3. Monash Department of Clinical Epidemiology, Cabrini Institute, Melbourne, Vic, Australia
  4. Rheumatology Unit, Royal Adelaide Hospital, Adelaide, SA, Australia
  5. Discipline of Medicine, The University of Adelaide, Adelaide, SA, Australia
  6. Department of Rheumatology, Redcliffe Hospital, Redcliffe, QLD, Australia
  7. Department of Rheumatology, Fiona Stanley Hospital, Perth, WA, Australia
  8. Rheumatology Unit, The Queen Elizabeth Hospital, Woodville, SA, Australia
  9. Department of Rheumatology, Institute of Rheumatology and Orthopaedics, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
  10. Department of Rheumatology, Royal North Shore Hospital, NSW, Sydney, Australia
  11. Northern Clinical School, Institute of Bone and Joint Research, University of Sydney, Sydney, NSW, Australia
  12. Department of Epidemiology & Preventive Medicine, School of Public Health and Preventative Medicine, Monash University, Melbourne, VIc, Australia

Background: Despite improved treatments for inflammatory arthritis, including the use of biologics, opioids are prescribed among patients with inflammatory rheumatic diseases. The aim of this study was to determine the effect of socio-economic status on opioid use in people with inflammatory arthritis using the Australian Bureau of Statistics (ABS) Socio-Economic Indexes for Areas (SEIFA) score Index of Advantage/Disadvantage (IRSAD) where SEIFA 1= lowest quintile and SEIFA 5= highest quintile.

Methods: The Australian Rheumatology Association Database (ARAD) is an observational database that collects outcome data for people with rheumatoid arthritis (RA), ankylosing spondylitis (AS), psoriatic arthritis (PsA) and juvenile idiopathic arthritis (JIA). Participants complete semi-annual then annual questionnaires, which includes demographic and social details, self-reported medical history and medication use, and quality of life scales. We used the longitudinal questionnaires to examine opioid use between 2002 and 2018. Opioids were classified as high potency versus low potency. Record linkage with PBS data was used to validate self-report data. Multilevel mixed logistic and ordinal regression was used to analyse the data.

Results: In 5,634 ARAD participants 19% had taken a high potency opioid and 46% a low potency opioid. High potency use was particularly increased in the lower SES participants in all groups except JIA. In the patients with RA (the largest disease group subset) in a univariate model those from lower SEIFAs were more likely to be on high potency opioids (OR 4.48 (95% CI 3.0-6.6)). Even after adjusting for age, gender, disease duration, NSAIDs, prednisone and biologic treatment, employment status, smoking, alcohol and self-report physical disability, lowest quintile SEIFA OR was 2.15 (95% CI 1.4-2.3). Younger age, females and those on NSAIDs and steroids (but not biologics) and those with higher self-report functional disability had higher opioid use. The transitional probabilities of opioid use between did not change significantly. Patients once started remain on opioids. We also found an increasing use of higher potency opioids over time. 

Conclusions: Opioid use, particularly the higher potency opioids, was increased in persons with inflammatory arthritis from lower SES using SEIFA/IRSAD, a marker that includes community infrastructure and resources regarding disadvantage and advantage. Future research includes exploration of factors predictive of initiation and cessation using MBS linkage data.