Variation in cystic fibrosis newborn screening algorithms in the United States

RationaleCystic fibrosis (CF) newborn screening (NBS) algorithms in the United States vary by state. Differences in CF NBS algorithms could potentially affect the detection rate of CF newborns and lead to disparities in CF diagnosis amongst different racial and ethnic groups. ObjectivesGenerate a database of CF NBS algorithms in the United States and identify processes that may potentially lead to missed diagnoses or lead to healthcare disparities. MethodsWe sent an online survey to state and regional CF and NBS leaders about the type and threshold of immunoreactive trypsinogen (IRT) cutoff used and methods used for CFTR gene variant analysis. Follow-up by email and phone was done to ensure a response from every state, clarify responses, and resolve discordances. ResultsThere is wide variation in the NBS algorithms employed by different states. Approximately half the states use a floating IRT cutoff, and half use a fixed IRT cutoff. CFTR variant analysis also varies widely, with two states analyzing only for the F508del variant and four states incorporating CFTR gene sequencing. The other states use CFTR variant panels ranging from 23 to 365 CFTR variants. ConclusionsCF NBS algorithms vary widely amongst the different states in the United States, which affects the ability of CF NBS to diagnose newborn infants with CF consistently and uniformly across the country and potentially may miss more infants with CF from minority populations. Our results identify an important area for quality improvement in CF NBS.

Automated summary

There are wide variations in CF newborn screening algorithms among different states in the United States, which may result in disparities in CF diagnosis among different racial and ethnic groups. This highlights the need for quality improvement in CF newborn screening.