Background/Purpose

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. The objective of the study was to explore whether there are differences in initiation rates of a first bDMARD across age, gender and educational status among RA patients.

Methods

Data from the Norwegian NOR-DMARD study (collected between 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 a manual forward step-wise modelling strategy. Models were adjusted for potential clinical confounders  (DAS28, erosive disease, physician global assessment, HAQ, rheumatoid factor, disease duration, and comorbidities) and year of baseline visit. 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, 2005 patients were included (mean age at baseline 55 yrs, 68% females), and 368 patients received a bDMARD in the time of the period of observation (mean time to bDMARD 2.6 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 access to first bDMARD. Effect of lower education was more pronounced in later years (HR low vs. high education= 0.17 and 0.34 in patients who entered the cohort in 2008-2011, in time-varying and baseline models, respectively).

	Time-varying Cox regression model	Baseline predictors Cox regression model
	Hazard ratio [95% CI]
High education (ref.) Medium education Low education	1 0.71* [0.52;0.96] 0.75* [0.57;0.99]	1 0.77 [0.57; 1.05] 0.67* [0.52; 0.87]
Gender (female vs male)	0.84 [0.65;1.03]	0.99 [0.77; 1.27]
Age, years	0.97* [0.96;0.98]	0.97* [0.96; 0.98]
Comorbidities	0.90 [0.78;1.03]	0.92 [0.80; 1.06]
DAS28 (per unit)	1.62* [1.45;1.81]	1.20* [1.08; 1.33]
Erosive disease (at baseline)	2.12* [1.67;2.69]	**
Physician global assessment (0-100)	1.03* [1.03;1.04]	**
Disease duration (>1 year vs. ≤ 1 year)	0.19* [0.11;0.33]	**
HAQ (0-3, per unit)	**	1.42* [1.10; 1.84]
Rheumatoid factor (yes vs. no)	**	1.30 * [1.02; 1.64]
Year of baseline visit 2000-2003 (ref.) 2004-2007 2008-2011	1 2.06* [1.55;2.75] 5.13* [3.52;7.46]	1 1.49* [1.14; 1.96] 3.04* [2.17; 4.26]

*p<0.05, ** not included in the final model

Conclusion

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, pointing at increasing health gaps between education groups. Findings are relevant as the impact of age and education on access might result in avoidable adverse impact on health.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/inequity-level-of-education-is-associated-with-access-to-biologic-dmards-even-in-a-country-with-highly-developed-social-welfare-norway/