Context: Measurement of plasma steroids is necessary for diagnosis of congenital adrenal hyperplasia (CAH). We sought to establish an efficient strategy for detection and subtyping of CAH with a machine-learning algorithm.
Methods: Clinical phenotype and genetic testing were used to provide CAH diagnosis and subtype. We profiled 13 major steroid hormones by liquid chromatography-tandem mass spectrometry. A multiclassifier system was established to distinguish 11β-hydroxylase deficiency (11βOHD), 17α-hydroxylase/17,20-lyase deficiency (17OHD), and 21α-hydroxylase deficiency (21OHD) in a discovery cohort (n = 226). It was then validated in an independent cohort (n = 111) and finally applied in a perspective cohort of 256 patients. The diagnostic performance on the basis of area under receiver operating characteristic curves (AUCs) was evaluated.
Results: A cascade logistic regression model, we named the "Steroidogenesis Score", was able to discriminate the 3 most common CAH subtypes: 11βOHD, 17OHD, and 21OHD. In the perspective application cohort, the steroidogenesis score had a high diagnostic accuracy for all 3 subtypes, 11βOHD (AUC, 0.994; 95% CI, 0.983-1.000), 17OHD (AUC, 0.993; 95% CI, 0.985-1.000), and 21OHD (AUC, 0.979; 95% CI, 0.964-0.994). For nonclassic 21OHD patients, the tool presented with significantly higher sensitivity compared with measurement of basal 17α-hydroxyprogesterone (17OHP) (0.973 vs 0.840, P = 0.005) and was not inferior to measurement of basal vs stimulated 17OHP (0.973 vs 0.947, P = 0.681).
Conclusions: The steroidogenesis score was biochemically interpretable and showed high accuracy in identifying CAH patients, especially for nonclassic 21OHD patients, thus offering a standardized approach to diagnose and subtype CAH.
Keywords: congenital adrenal hyperplasia; diagnosis; liquid chromatography-tandem mass spectrometry; subtype.
© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society.