Patient Median-Based Quality Control in Lamotrigine Therapeutic Drug Monitoring: A 15-Year Retrospective Study

<b>Background/Objectives:</b> Lamotrigine is an anticonvulsant and mood stabilizer with wide interindividual pharmacokinetic variability, necessitating therapeutic drug monitoring (TDM). Patient-based quality control (PBQC) strategies, such as tracking median drug concentrations, may complement traditional quality assurance in routine laboratory practice. <b>Methods:</b> We retrospectively analyzed 15,963 lamotrigine results collected between February 2011 and December 2025 at Uppsala University Hospital, Uppsala. Data included age, sex, sampling date, and lamotrigine concentrations. Assays were performed using the Architect platform from February 2011 to January 2021, after which the Cobas Pro c 503 platform was implemented. Yearly patient medians were calculated, and trends, seasonal variation, and method agreement were assessed. <b>Results:</b> Of all the results, 5967 were from males and 9996 from females. Median concentrations were slightly higher in males (15.20 µmol/L) than in females (13.71 µmol/L), representing a weak but statistically significant difference (Spearman R = -0.048; <i>p</i> < 0.0001). The total number of reported results increased steadily over time, from 402 in 2011 to more than 1500 annually by 2024-2025. Median lamotrigine concentrations increased from 11.85 µmol/L in 2011 to 17.40 µmol/L in 2025 (Spearman R = 0.047; <i>p</i> < 0.0001). Seasonal variation in sample volume was observed, with peaks in November and troughs in July and December, but median concentrations remained stable (CV = 3.49%). Method comparison showed strong agreement between Architect and Cobas assays (R² = 0.97). <b>Conclusions:</b> Patient median lamotrigine concentrations serve as a robust PBQC tool, capable of detecting subtle analytical shifts while remaining resilient to seasonal fluctuations and platform transitions. This approach enhances confidence in assay reliability and supports safer therapeutic decision-making in real-world TDM practice.