TY - JOUR
T1 - Optimizing the Dutch newborn screening for congenital hypothyroidism by incorporating amino acids and acylcarnitines in a machine learning-based model
AU - Jansen, Heleen I.
AU - van Haeringen, Marije
AU - Bouva, Marelle J.
AU - den Elzen, Wendy P. J.
AU - Bruinstroop, Eveline
AU - van der Ploeg, Catharina P. B.
AU - van Trotsenburg, A. S. Paul
AU - Zwaveling-Soonawala, Nitash
AU - Heijboer, Annemieke C.
AU - Bosch, Annet M.
AU - de Jonge, Robert
AU - Hoogendoorn, Mark
AU - Boelen, Anita
N1 - Funding Information: The authors would like to thank Marie-Louise A. Heijnen of the National Institute for Public Health and the Environment (RIVM) for her contribution to the accessibility of the data. Publisher Copyright: © 2023 the author(s) Published by Bioscientifica Ltd.
PY - 2023
Y1 - 2023
N2 - Objective: Congenital hypothyroidism (CH) is an inborn thyroid hormone (TH) deficiency mostly caused by thyroidal (primary CH) or hypothalamic/pituitary (central CH) disturbances. Most CH newborn screening (NBS) programs are thyroid-stimulating-hormone (TSH) based, thereby only detecting primary CH. The Dutch NBS is based on measuring total thyroxine (T4) from dried blood spots, aiming to detect primary and central CH at the cost of more false-positive referrals (FPRs) (positive predictive value (PPV) of 21% in 2007–2017). An artificial PPV of 26% was yielded when using a machine learning-based model on the adjusted dataset described based on the Dutch CH NBS. Recently, amino acids (AAs) and acylcarnitines (ACs) have been shown to be associated with TH concentration. We therefore aimed to investigate whether AAs and ACs measured during NBS can contribute to better performance of the CH screening in the Netherlands by using a revised machine learning-based model.
AB - Objective: Congenital hypothyroidism (CH) is an inborn thyroid hormone (TH) deficiency mostly caused by thyroidal (primary CH) or hypothalamic/pituitary (central CH) disturbances. Most CH newborn screening (NBS) programs are thyroid-stimulating-hormone (TSH) based, thereby only detecting primary CH. The Dutch NBS is based on measuring total thyroxine (T4) from dried blood spots, aiming to detect primary and central CH at the cost of more false-positive referrals (FPRs) (positive predictive value (PPV) of 21% in 2007–2017). An artificial PPV of 26% was yielded when using a machine learning-based model on the adjusted dataset described based on the Dutch CH NBS. Recently, amino acids (AAs) and acylcarnitines (ACs) have been shown to be associated with TH concentration. We therefore aimed to investigate whether AAs and ACs measured during NBS can contribute to better performance of the CH screening in the Netherlands by using a revised machine learning-based model.
KW - acylcarnitines
KW - amino acids
KW - congenital hypothyroidism
KW - machine learning based
KW - newborn screening
UR - http://www.scopus.com/inward/record.url?scp=85177234134&partnerID=8YFLogxK
U2 - https://doi.org/10.1530/ETJ-23-0141
DO - https://doi.org/10.1530/ETJ-23-0141
M3 - Article
C2 - 37855424
SN - 2235-0640
VL - 12
JO - European thyroid journal
JF - European thyroid journal
IS - 6
M1 - e230141
ER -