Abstract

To ensure that each newborn receives an equitable test of the highest possible sensitivity, we recognized the necessity to reassess immunoreactive trypsinogen and DNA issues in cystic fibrosis newborn screening algorithms. Our objectives included clarification of various factors that influence immunoreactive trypsinogen concentrations and resolution of long-standing questions about variations in immunoreactive trypsinogen levels among newborns. Immunoreactive trypsinogen data on 660443 newborns who were born between July 1, 1994, and June 30, 2004, were abstracted from the Wisconsin State Laboratory of Hygiene databases and deidentified for analysis. Using a compiled data set, we analyzed various demographic characteristics to determine their role, if any, in immunoreactive trypsinogen variation. Specifically, season of birth, reagent lot, and birth weight were examined. Sensitivities of the most common cystic fibrosis newborn screening protocols, namely immunoreactive trypsinogen/immunoreactive trypsinogen and immunoreactive trypsinogen/DNA, were also investigated. Mean and 95th percentile immunoreactive trypsinogen levels were shown to vary by both season and reagent lot number and affect sensitivity of the assay. Low birth weight infants had significantly higher immunoreactive trypsinogen values than normal birth weight infants. Sensitivities were also found to vary on the basis of the algorithm used, with the highest sensitivity of 96.2% calculated for an immunoreactive trypsinogen/DNA protocol with 23 cystic fibrosis transmembrane conductance regulator mutation analyses compared with 80.2% with the immunoreactive trypsinogen/immunoreactive trypsinogen method used in 9 states. Floating, rather than fixed, cutoff values for the initial immunoreactive trypsinogen portion of any cystic fibrosis newborn screening protocol are generally necessary on the basis of the seasonal and reagent lot variations observed. Because of its lower sensitivity, immunoreactive trypsinogen/immunoreactive trypsinogen does not optimize detection of patients with cystic fibrosis.

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