Abstract
Rationale: Cystic Fibrosis (CF) newborn screening (NBS)
algorithms in the USA 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.
Objectives: Generate a database of CF NBS algorithms in the USA
and identify processes that may potentially lead to missed diagnoses or
lead to health care disparities. Methods: We 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 . Results: There was 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 varied widely, with 2 states analyzing
only for the F508del variant and 4 states incorporating CFTR gene
sequencing. The other states used CFTR variant panels ranging
from 23 to 365 CFTR variants. Conclusions: CF NBS
algorithms vary widely amongst the different states in the USA, 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.