Application of CLIR-Based Post-Analytical Tools to Dutch NBS Data Demonstrates Its Potential Impact on the Performance of CPT1, GA-1, IVA and MSUD Screening in a Disorder-Specific Way.

Newborn screening (NBS) for inborn errors of metabolism is challenged by high false-positive rates, which may lead to parental anxiety and increased healthcare costs associated with diagnostic follow-up. False-positive results often arise from changes in metabolite concentrations that mimic metabolic disorders as a consequence of differences in perinatal factors or nutritional status. To address this, Collaborative Laboratory Integrative Reports (CLIR) and the associated post-analytical tools (PATs) using multivariate interpretation and covariate-adjusted reference intervals may be used to improve specificity of NBS algorithms. In the current study, we examined whether CLIR can be applied to optimize the Dutch NBS program by reducing the false-positive rates. We developed and validated a CLIR-based PAT for CPT1 deficiency, GA-I, IVA and MSUD within the Dutch NBS program. Single-condition tools (SCTs) and multivariate approaches, including marker ratios and covariate adjustments, were evaluated for their ability to discriminate true- and false-positive referrals. For CPT1 deficiency, age-adjusted SCT combined with birthweight, location correction, and the C18:1/methionine ratio substantially reduced false positives. For GA-I, C3DC-based ratios improved specificity while preserving true-positive detection, potentially reflecting postnatal renal immaturity in some cases. For IVA, the dual scatter plot fully separated true- and false-positive referrals, highlighting the limitations of single-marker screening. For MSUD, differences between false-positive and true-positive cases were more pronounced, yet a similar number of false positives were still referred; valine-related markers contributed to false positives, while leucine and the Xle/Phe ratio better identified true positives. CLIR-based post-analytical tools enhanced NBS specificity through covariate-aware, multivariate interpretation. This provides important input for decision makers in both the Dutch NBS, as well as the NBS community worldwide.