Clinical performance of an IGF1 LC-MS/MS assay and associated normative dataset in routine endocrinology.

BACKGROUND: Accurate interpretation of insulin-like growth factor-1 (IGF1) requires both analytically robust measurement and appropriate reference data. Most available IGF1 normative datasets are based on ligand-binding assays (LBA), limiting their applicability to liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods that provide higher analytical specificity. OBJECTIVE: To evaluate the clinical performance of an in-house developed LC-MS/MS IGF1 assay in combination with a method-matched normative dataset derived from the Dutch Lifelines cohort, and to compare it with a commonly used LBA. METHODS: Paired IGF1 results (n = 2057) were obtained using LC-MS/MS and the IDS iSYS LBA. Standard deviation scores (SDS) were calculated using assay-specific normative datasets. Agreement was assessed by regression, Bland-Altman, and weighted Cohen's κ analyses. Clinical validity was evaluated by comparing extreme SDS values with diagnostic categories adjudicated by endocrinologists. RESULTS: The LC-MS/MS method showed a proportional bias of -27% versus IDS iSYS and yielded symmetrically distributed SDS around zero, whereas IDS iSYS results were positively skewed. Categorical agreement was fair (κ = 0.39). LC-MS/MS-derived SDS corresponded more closely with clinical diagnoses across adult and pediatric groups, including acromegaly, growth hormone (GH) deficiency, and GH replacement therapy. CONCLUSIONS: Our LC-MS/MS IGF1 assay integrated with its own population-based normative dataset demonstrated superior alignment with clinical assessment compared with LBA results. In our setting, this method provides a clinically reliable benchmark for IGF1 interpretation and may serve as a reference for IGF1 harmonization and broader adoption of the Lifelines normative dataset in routine endocrinology.