Abstract Disclosure: M.D. Ettleson: None. G.C. Penna: Consulting Fee; Self; Ipsen, Bayer, Inc.. W. Wan: None. I.M. Bensenor: None. N. Laiteerapong: None. A.C. Bianco: Consulting Fee; Self; Abbvie. Classification of TSH Trajectories During Levothyroxine Treatment in the ELSA-Brasil Cohort Introduction: Hypothyroidism is a common endocrine disorder for which levothyroxine (LT4) serves as the primary treatment. Periods during which thyroid stimulating hormone (TSH) levels are outside the normal range have been associated with adverse cardiovascular outcomes, including mortality. In practice, serial TSH levels are measured over time to ensure therapeutic LT4 treatment is maintained. However, there is no measure of the quality of treatment maintenance over time. TSH trajectory classification represents a novel approach to define the adequacy of LT4 treatment for hypothyroidism over time utilizing multiple observation points. Methods: With longitudinal clinical data, including thyroid function from a large prospective study, we aimed to define classes of TSH trajectories and examine changes in cardiovascular (CV) health markers over a 9 year study period with three observation points. Growth mixture modeling (GMM), including latent class growth analysis (LCGA), was used to classify LT4-treated individuals participating in the Longitudinal Study of Adult Health in Brazil (ELSA-Brasil) based on serial TSH levels. Repeated measure analyses were then utilized to measure within-class changes in blood pressure, lipid levels, hemoglobin A1c, and CV-related medication utilization. Results: From the 621 LT4-treated study participants, the best-fit GMM approach identified four TSH trajectory classes, as defined by their relationship to the normal TSH range: 1) High-high normal TSH, 2) Normal TSH, 3) Normal-to-low TSH, and 4) Low-to-normal TSH. Notably, the average baseline LT4 dose was lowest in the high-high normal TSH group (77.7 mcg, p <0.001). There were no significant differences in CV health markers between the classes at baseline. At least one significant difference in CV markers occurred in all classes, highlighted by the low-to-normal class, in which total and HDL cholesterol, triglycerides, and A1c all increased significantly (p = 0.049, p <0.001, p <0.001, and p = 0.001, respectively). Medication utilization increased in all classes over the study period. Conclusion: GMM/LCGA represents a viable approach to define and examine LT4 treatment by TSH trajectory. In the future, more comprehensive datasets will allow for more complex trajectory modeling and analysis of clinical outcome differences between trajectory classes. Defining the adequacy of LT4 treatment using a longitudinal scope could allow clinicians to more accurately communicate treatment progress and identify patients at risk for adverse CV outcomes. Presentation: 6/3/2024