American Association of Clinical Endocrinology Consensus Statement: Algorithm for Management of Adults with Dyslipidemia – 2025 Update

Objective: To provide visual guidance in concise algorithms and tables to assist with clinical decision making in the management of adults with dyslipidemia to reduce risk of ASCVD and triglyceride-induced pancreatitis. Methods: An international multidisciplinary task force of clinical experts was convened to update the 2020 AACE algorithm for dyslipidemia. Literature searches informed the creation of visual guidance graphics and supporting narratives that reflect consensus of the task force. Results: The 2025 algorithm for the management of adults with dyslipidemia includes the following sections: (1) guiding principles for patient-centered management of dyslipidemia; (2) risk assessment and testing for dyslipidemia; (3) identifying genetic dyslipidemias; (4) specific lifestyle recommendations for adults with dyslipidemia; (5) targeting LDL-cholesterol with pharmacologic therapy for ASCVD prevention in adults; (6) approach to statin-associated muscle symptoms in adults; (7) management of adults with hypertriglyceridemia; (8) management of special populations with dyslipidemia (older adults, adults receiving transgender care or HIV control, adults with autoimmune disorders, survivors of childhood cancers, adults with organ transplantation); (9) management of hypercholesterolemia in pregnant and lactating individuals; (10) management of hypertriglyceridemia in pregnant and lactating individuals; and (11) FDA-approved medications for dyslipidemia. Conclusions: This 2025 dyslipidemia algorithm update aligns with the 2025 AACE Clinical Practice Guideline for Pharmacologic Management of Adults with Dyslipidemia and other recent AACE guidance. The algorithm is also in agreement with guidance provided by the other international bodies represented within this task force. This update emphasizes ASCVD risk assessment, addresses pancreatitis risk, and highlights individualized pharmacotherapy. The algorithm includes considerations on health equity, cost effectiveness, and the benefits and harms of different management options.