Differential laboratory monitoring in autoimmune disease: a matched case-control study from Qatar primary care

To examine whether patients with autoimmune diseases receive differential cardiometabolic and inflammatory laboratory monitoring compared to matched controls in primary care, and to identify predictors of monitoring patterns. We conducted a matched case-control study using electronic health records from the Primary Health Care Corporation (PHCC), Qatar (January 2015 to December 2024). Adults with Hashimoto’s thyroiditis, rheumatoid arthritis (RA), or systemic lupus erythematosus (SLE) were matched 1:2 to controls without autoimmune disease on age and sex. Primary outcomes were receipt of cardiometabolic tests (haemoglobin A1c HbA1c, complete lipid panel) and inflammatory markers (C-reactive protein CRP, erythrocyte sedimentation rate ESR). We used conditional logistic regression adjusting for comorbidities, medications, and healthcare utilisation. Among 27,911 participants (9,356 cases, 18,555 controls; mean age 46.7 years; 74.4% female) in 9,356 matched sets, we observed divergent monitoring patterns. Compared to controls, patients with RA had significantly lower odds of HbA1c monitoring (OR 0.77, 95% CI 0.69–0.85) and complete lipid panels (OR 0.74, 95% CI 0.67–0.82). Similar patterns were observed for SLE (HbA1c: OR 0.67, 95% CI 0.57–0.80; lipid: OR 0.60, 95% CI 0.51–0.70). Conversely, RA patients had 4.2-fold higher odds of CRP testing and 4.4-fold higher odds of ESR testing; SLE patients showed similar elevations (3.7-fold and 4.2-fold, respectively). Hashimoto’s patients showed modestly increased monitoring across all test types (HbA1c: OR 1.45, 95% CI 1.23–1.70). Despite elevated cardiovascular risk, patients with systemic autoimmune diseases (RA, SLE) receive less cardiometabolic laboratory monitoring than matched controls while receiving substantially more inflammatory marker testing. This differential monitoring pattern — which we describe as a “monitoring gap paradox” and which persisted across sensitivity analyses — is consistent with care coordination challenges at the primary care–specialty interface. The observational design precludes inferences about the underlying causes, but the findings identify a potential quality improvement opportunity warranting further investigation.