Incorporation of second-tier tests and secondary biomarkers to improve positive predictive value (PPV) rate in newborn metabolic screening program

J Clin Lab Anal. 2022 Jul;36(7):e24471. doi: 10.1002/jcla.24471. Epub 2022 May 2.


Background: Nowadays, neonatal screening has become an essential part of routine newborn care in the world. This is a non-invasive evaluation that evaluated inborn errors of metabolisms (IEMs) using tandem mass spectrometry (LC-MS/MS) for the evaluation of the baby's risk of certain metabolic disorders.

Methods: This retrospective study was conducted on 39987 Iranian newborns who were referred to Nilou Medical Laboratory, Tehran, Iran, for newborn screening programs of IEMs. We incorporated second-tier tests and secondary biomarkers to improve positive predictive value (PPV).

Results: Statistical data were recorded via call interviewing in 6-8 months after their screening tests. The overall prevalence of IEM was 1:975. The mean age of all participants was 3.9 ± 1.1 days; 5.1% of participants were over 13 days and 7.7% were preterm or underweight. A total of 11384 (29.4%) of the cases were born in a consanguineous family. The type of delivery was the cesarean section in 8332 (51.3%) valid cases. The neonatal screening results had an overall negative predictive value (NPV) of 100% and the overall PPV of 40.2%. The false-positive rate was 0.15%.

Conclusion: This study showed a high incidence of metabolic disease due to a high rate of consanguineous marriages in Iran and indicated that incorporation of second-tier tests and secondary biomarkers improves PPV of neonatal screening programs.

Keywords: mass spectrometry; neonatal screening; second-tier biomarkers.

MeSH terms

  • Biomarkers
  • Cesarean Section
  • Chromatography, Liquid
  • Female
  • Humans
  • Infant, Newborn
  • Iran / epidemiology
  • Metabolic Diseases* / diagnosis
  • Metabolic Diseases* / epidemiology
  • Metabolism, Inborn Errors* / diagnosis
  • Neonatal Screening / methods
  • Predictive Value of Tests
  • Pregnancy
  • Retrospective Studies
  • Tandem Mass Spectrometry


  • Biomarkers