A Novel Approach to Improve Newborn Screening for Congenital Hypothyroidism by Integrating Covariate-Adjusted Results of Different Tests into CLIR Customized Interpretive Tools

Autor: Christopher Nixon, Amy C Smith, Anna Fornari, Andrew P. Norgan, Sainan Wei, Lars Mørkrid, Norma P. Tavakoli, Vaneet Arora, Bobby J Miller, Joseph J. Orsini, Rolf Zetterström, Rolf D. Pettersen, Gregg Marquardt, Piero Rinaldo, Robert J. Currier, Patricia L. Hall, Michele Caggana, Amy L Piazza, Hao Tang, Stephanie D Stoway, Neil R Schubauer, Henrik Åhlman, Alexander D. Rowe, Arthur Hagar
Jazyk: angličtina
Rok vydání: 2021
Předmět:
0301 basic medicine
Multivariate statistics
endocrine system
endocrine system diseases
Computer science
dual scatter plot
thyroid-stimulating hormone
030209 endocrinology & metabolism
Pediatrics
Article
RJ1-570
03 medical and health sciences
0302 clinical medicine
Immunology and Microbiology (miscellaneous)
Covariate
Statistics
False positive paradox
medicine
false positives
thyroxine
Polynomial regression
Newborn screening
newborn screening
covariate-adjusted reference intervals
Obstetrics and Gynecology
congenital hypothyroidism
bioinformatics
Collaborative Laboratory Integrated Reports (CLIR)
single condition tool
medicine.disease
Congenital hypothyroidism
030104 developmental biology
Specimen collection
Sequential analysis
Pediatrics
Perinatology and Child Health
hormones
hormone substitutes
and hormone antagonists
Zdroj: International Journal of Neonatal Screening
Volume 7
Issue 2
International Journal of Neonatal Screening, Vol 7, Iss 23, p 23 (2021)
ISSN: 2409-515X
DOI: 10.3390/ijns7020023
Popis: Newborn screening for congenital hypothyroidism remains challenging decades after broad implementation worldwide. Testing protocols are not uniform in terms of targets (TSH and/or T4) and protocols (parallel vs. sequential testing
one or two specimen collection times), and specificity (with or without collection of a second specimen) is overall poor. The purpose of this retrospective study is to investigate the potential impact of multivariate pattern recognition software (CLIR) to improve the post-analytical interpretation of screening results. Seven programs contributed reference data (N = 1,970,536) and two sets of true (TP, N = 1369 combined) and false (FP, N = 15,201) positive cases for validation and verification purposes, respectively. Data were adjusted for age at collection, birth weight, and location using polynomial regression models of the fifth degree to create three-dimensional regression surfaces. Customized Single Condition Tools and Dual Scatter Plots were created using CLIR to optimize the differential diagnosis between TP and FP cases in the validation set. Verification testing correctly identified 446/454 (98%) of the TP cases, and could have prevented 1931/5447 (35%) of the FP cases, with variable impact among locations (range 4% to 50%). CLIR tools either as made here or preferably standardized to the recommended uniform screening panel could improve performance of newborn screening for congenital hypothyroidism.
Databáze: OpenAIRE
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