Reducing False Positives in Newborn Screening: The Role of Perinatal Factors in the Dutch NBS Program.

Abstract

Background/Objectives: Dutch newborn screening is an important public health program designed to detect conditions early in life, enabling timely interventions that can prevent mortality, morbidity, and long-term disabilities. However, the program also faces certain challenges. One such issue is obtaining and maintaining a high positive predictive value (PPV); another is that newborn screening (NBS) in the Netherlands is intended for all newborn babies until the age of six months. This means comparing infants at different ages may introduce variability that complicates data interpretation. To support the optimization of the program, we systematically analyzed population-level tandem mass spectrometry (MS/MS) data to explore postnatal metabolic changes. Methods: We evaluated the impact of covariates-including birth weight, gestational age, age at blood collection, and biological sex-on metabolite profiles using retrospective newborn screening (NBS) data. Special emphasis was placed on the combined effects of these covariates. The analysis was based on data from 985,629 newborns collected between 2018 and 2024. Results: Specifically, (extremely) preterm infants exhibit altered levels of several amino acids and acylcarnitines. Moreover, we observed multiplicative effects of gestational age and birth weight on several metabolic markers. Biological sex however, does not have an impact. The largest impact of the age of sampling was observed on the C0/C16+C18 ratio, which may impact screening performance for CPT1 deficiency. Conclusions: Covariate-adjusted reference values could improve the performance of the Dutch newborn screening.