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

Background: Accurate interpretation of 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 paediatric groups, including acromegaly, 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.

Keywords: IGF1; LC-MS/MS; acromegaly; growth hormone deficiency; mass spectrometry.

Year of publication

2026

Journal

European journal of endocrinology

Author(s)

Vos, M.J.
Postma, M.R.
Lentjes, E.G.
Habich-Reijntjes, L.
Kelly, D.
Muller Kobold, A.
et al.

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