Newborn Screening Policy Decisions: When, Why, and How Cutoffs are Changed

The goal of newborn screening (NBS) is to identify infants at increased risk for a select set of congenital conditions, for the purpose of improving health outcomes in affected infants. Because it is important to identify infants affected with one of these conditions, laboratory testing cutoff values are set at a level that aims to identify all true positive cases. This absolute goal of identifying all true cases is a cultural norm among newborn screening programs, prompting screening algorithms with a high sensitivity; the trade off being lower specificity and positive predictive values. One of the ethical issues raised, particularly in the last decade of NBS expansion, is the potential negative impact of false positive results for newborns and their families and the healthcare system. False positive results are a challenging component of any screening program, especially when screening for rare conditions in a large population. Cutoff values need to be carefully revised to reduce the number of false positives, without compromising the ability to identify true cases, which generally requires the use of large datasets.

There are several other reasons why NBS algorithms may be revised: implementing testing for a new condition, trends in the population demographics, changes in manufacturers' kit lots, procedural changes (i.e. timing of specimen collection), and for overall quality assurance to improve the specificity, sensitivity and positive predictive value of the tests. Case studies will be presented to demonstrate when, why, and how cutoffs are revised, highlighting the various factors involved in the decision-making process.