0212: Biomarker-Guided Therapeutic Calculator for Personalized Management in Pregnant Patients with Autoimmune Rheumatic Diseases

Background/Purpose: Therapeutic decisions during pregnancy in women with autoimmune rheumatic diseases (ARDs) such as SLE, APS, RA, and Sjögren’s syndrome require a personalized approach due to heterogeneous risk profiles and complex disease interactions. We developed and validated a treatment recommendation algorithm based on a comprehensive meta-analysis of over 100 studies assessing predictive biomarkers, clinical factors, and treatment outcomes during pregnancy in ARDs.

Methods: Using PRISMA guidelines, we performed a systematic review and meta-analysis to identify evidence-based therapeutic associations across ARDs. Key biomarkers were mapped to treatment responses, including lupus anticoagulant (LAC), anti-β2GP1, anti-cardiolipin, anti-SSA/Ro, anti-dsDNA, complement components (C3/C4, sC5b-9), NLR, disease activity indices, and prior pregnancy loss or thrombosis. We assigned intervention thresholds and created a decision matrix matching biomarker-risk profiles with pharmacologic and non-pharmacologic strategies, including hydroxychloroquine (HCQ), low-dose aspirin (AAS), low molecular weight heparin (LMWH), corticosteroids, and immunosuppressives.

Results: The calculator integrates 9 core biomarker-based indications for treatment. For instance, the presence of LAC and high-titer antiphospholipid antibodies indicated LMWH+AAS (OR for APO reduction: 1.29); anti-Ro positivity triggered HCQ to prevent fetal AV block (risk reduction from 18% to 7.5%). Active lupus (SLEDAI >4 or hypocomplementemia) prompted corticosteroid and azathioprine use; elevated NLR or chemerin levels served as adjunctive inflammation markers. Each therapeutic output is supported by published OR/RR values and is adjustable to disease context and trimester.

Conclusion: We present a personalized therapeutic calculator to optimize pregnancy outcomes in ARD patients. It translates biomarker profiles into actionable treatment recommendations with literature-based justification. The tool is undergoing academic licensing and is not publicly available. Future trials will evaluate its implementation impact in multidisciplinary care models.