Optimal DNA tier for the IRT/DNA algorithm determined by CFTR mutation results over 14years of newborn screening

Mei W. Baker; Molly Groose; Gary Hoffman; Michael Rock; Hara Levy; Philip M. Farrell

doi:10.1016/j.jcf.2011.02.001

Optimal DNA tier for the IRT/DNA algorithm determined by CFTR mutation results over 14years of newborn screening

Mei W. Baker, Molly Groose, Gary Hoffman, Michael Rock, Hara Levy, Philip M. Farrell^*

^*Corresponding author for this work

Pediatrics

Research output: Contribution to journal › Article › peer-review

27 Scopus citations

Abstract

Background: There has been great variation and uncertainty about how many and what CFTR mutations to include in cystic fibrosis (CF) newborn screening algorithms, and very little research on this topic using large populations of newborns. Methods: We reviewed Wisconsin screening results for 1994-2008 to identify an ideal panel. Results: Upon analyzing approximately 1 million screening results, we found it optimal to use a 23 CFTR mutation panel as a second tier when an immunoreactive trypsinogen (IRT)/DNA algorithm was applied for CF screening. This panel in association with a 96th percentile IRT cutoff gave a sensitivity of 97.3%, but restricting the DNA tier to F508del was associated with 90% (P < 0001). Conclusions: Although CFTR panel selection has been challenging, our data show that a 23 mutation method optimizes sensitivity and is advantageous. The IRT cutoff value, however, is actually more critical than DNA in determining CF newborn screening sensitivity.

Original language	English (US)
Pages (from-to)	278-281
Number of pages	4
Journal	Journal of Cystic Fibrosis
Volume	10
Issue number	4
DOIs	https://doi.org/10.1016/j.jcf.2011.02.001
State	Published - Jul 2011

Keywords

Cystic fibrosis transmembrane conductance regulator
Immunoreactive trypsinogen
Sensitivity

ASJC Scopus subject areas

Pediatrics, Perinatology, and Child Health
Pulmonary and Respiratory Medicine

Access to Document

10.1016/j.jcf.2011.02.001

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title = "Optimal DNA tier for the IRT/DNA algorithm determined by CFTR mutation results over 14years of newborn screening",

abstract = "Background: There has been great variation and uncertainty about how many and what CFTR mutations to include in cystic fibrosis (CF) newborn screening algorithms, and very little research on this topic using large populations of newborns. Methods: We reviewed Wisconsin screening results for 1994-2008 to identify an ideal panel. Results: Upon analyzing approximately 1 million screening results, we found it optimal to use a 23 CFTR mutation panel as a second tier when an immunoreactive trypsinogen (IRT)/DNA algorithm was applied for CF screening. This panel in association with a 96th percentile IRT cutoff gave a sensitivity of 97.3%, but restricting the DNA tier to F508del was associated with 90% (P < 0001). Conclusions: Although CFTR panel selection has been challenging, our data show that a 23 mutation method optimizes sensitivity and is advantageous. The IRT cutoff value, however, is actually more critical than DNA in determining CF newborn screening sensitivity.",

keywords = "Cystic fibrosis transmembrane conductance regulator, Immunoreactive trypsinogen, Sensitivity",

author = "Baker, {Mei W.} and Molly Groose and Gary Hoffman and Michael Rock and Hara Levy and Farrell, {Philip M.}",

note = "Funding Information: We are grateful to the late Ronald H. Laessig, PhD for his seminal leadership role in the Wisconsin Newborn Screening Program and to both of Charles Brokopp, Dr.PH, and Daniel Kurtyz, MD for their current overall leadership of the WSLH and perspectives on newborn screening issues. We also thank Karen Kennedy-Parker, who assisted with the data acquisition, Anita Laxova who assisted in the organization of this study and IRB approvals, and Zhanhai Li, PhD who performed the statistical analyses reported herein. Dr. Farrell is supported by Cystic Fibrosis Foundation grant A001-5-01 and National Institutes of Health grant DK 34108 .",

year = "2011",

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doi = "10.1016/j.jcf.2011.02.001",

language = "English (US)",

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AU - Baker, Mei W.

AU - Groose, Molly

AU - Hoffman, Gary

AU - Rock, Michael

AU - Levy, Hara

AU - Farrell, Philip M.

N1 - Funding Information: We are grateful to the late Ronald H. Laessig, PhD for his seminal leadership role in the Wisconsin Newborn Screening Program and to both of Charles Brokopp, Dr.PH, and Daniel Kurtyz, MD for their current overall leadership of the WSLH and perspectives on newborn screening issues. We also thank Karen Kennedy-Parker, who assisted with the data acquisition, Anita Laxova who assisted in the organization of this study and IRB approvals, and Zhanhai Li, PhD who performed the statistical analyses reported herein. Dr. Farrell is supported by Cystic Fibrosis Foundation grant A001-5-01 and National Institutes of Health grant DK 34108 .

PY - 2011/7

Y1 - 2011/7

N2 - Background: There has been great variation and uncertainty about how many and what CFTR mutations to include in cystic fibrosis (CF) newborn screening algorithms, and very little research on this topic using large populations of newborns. Methods: We reviewed Wisconsin screening results for 1994-2008 to identify an ideal panel. Results: Upon analyzing approximately 1 million screening results, we found it optimal to use a 23 CFTR mutation panel as a second tier when an immunoreactive trypsinogen (IRT)/DNA algorithm was applied for CF screening. This panel in association with a 96th percentile IRT cutoff gave a sensitivity of 97.3%, but restricting the DNA tier to F508del was associated with 90% (P < 0001). Conclusions: Although CFTR panel selection has been challenging, our data show that a 23 mutation method optimizes sensitivity and is advantageous. The IRT cutoff value, however, is actually more critical than DNA in determining CF newborn screening sensitivity.

AB - Background: There has been great variation and uncertainty about how many and what CFTR mutations to include in cystic fibrosis (CF) newborn screening algorithms, and very little research on this topic using large populations of newborns. Methods: We reviewed Wisconsin screening results for 1994-2008 to identify an ideal panel. Results: Upon analyzing approximately 1 million screening results, we found it optimal to use a 23 CFTR mutation panel as a second tier when an immunoreactive trypsinogen (IRT)/DNA algorithm was applied for CF screening. This panel in association with a 96th percentile IRT cutoff gave a sensitivity of 97.3%, but restricting the DNA tier to F508del was associated with 90% (P < 0001). Conclusions: Although CFTR panel selection has been challenging, our data show that a 23 mutation method optimizes sensitivity and is advantageous. The IRT cutoff value, however, is actually more critical than DNA in determining CF newborn screening sensitivity.

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