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Risk calculations for cystic fibrosis in neonatal screening by immunoreactive trypsinogen and CFTR mutation tests

  1. Author:
    Ogino, S.
    Flodman, P.
    Wilson, R. B.
    Gold, B.
    Grody, W. W.

  2. Author Address

    Harvard Univ, Sch Med, Brigham & Womens Hosp, Dept Pathol, Boston, MA 02115 USA. Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02115 USA. Univ Calif Irvine, Dept Pediat, Irvine, CA 92717 USA. Univ Penn, Med Ctr, Dept Pathol & Lab Med, Philadelphia, PA 19104 USA. NCI, Lab Genom Divers, Human Genet Sect, Frederick, MD 21701 USA. Univ Calif Los Angeles, Sch Med, Dept Pathol & Lab Med, Los Angeles, CA 90024 USA. Univ Calif Los Angeles, Sch Med, Dept Human Genet, Los Angeles, CA 90024 USA. Univ Calif Los Angeles, Sch Med, Dept Pediat, Los Angeles, CA 90024 USA Ogino, S, Harvard Univ, Sch Med, Brigham & Womens Hosp, Dept Pathol, 75 Francis St, Boston, MA 02115 USA
    1. Year: 2005
    2. Date: MAY-JUN
  2. Journal: Genetics in Medicine
    1. 7
    2. 5
    3. Pages: 317-327
  4. Type of Article: Article
  1. Abstract:

    Purpose: Although neonatal screening (or newborn screening) for cystic fibrosis (CF) is commonly practiced, systematic methods for accurate risk calculations are currently lacking. Methods and Results: We evaluated characteristics of the immunoreactive trypsinogen (IRT) test using the published data. The probability that a neonate has a positive IRT test, if the neonate is affected, a carrier, or a noncarrier, is approximate to 1, 0.041, or 0.011, respectively. We provide methods to calculate genetic risks for a variety of commonly encountered scenarios in which neonates are positive by the IRT test. Conclusion: Our Bayesian methods permit CF disease probabilities to be calculated accurately, taking into account all relevant information

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External Sources

  1. View record in Web of Science®
  2. WOS: 000229401900005

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