{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T03:28:45Z","timestamp":1791084525074,"version":"4.1.0"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"vor","delay-in-days":6,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"International Fund for Congenital Adrenal Hyperplasia"},{"name":"French Anti-Doping Agency"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Nonclassical 21-hydroxylase deficiency (NC21OHD) is a rare autosomal recessive disorder that is frequently misdiagnosed as polycystic ovary syndrome (PCOS) because of their overlapping clinical and biochemical presentations. The conventional diagnostic method, the cosyntropin stimulation test, is invasive, time consuming, and difficult to implement in routine clinical practice. To overcome these limitations, we previously developed a proof-of-concept machine learning model integrating basal serum steroid profiling by liquid chromatography with tandem mass spectrometry (LC\u2013MS\/MS) to identify NC21OHD without the need for dynamic stimulation testing. The present study aimed to validate and refine this model in a larger, multicentric cohort to evaluate its diagnostic performance in distinguishing NC21OHD from PCOS based on baseline steroid signatures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This tricentric study included 447 women: 263 with PCOS and 59 with NC21OHD in the training set (Piti\u00e9-Salp\u00eatri\u00e8re Hospital, Paris), and 104 PCOS and 21 NC21OHD in 2 independent validation cohorts (Saint-Antoine Hospital, Paris; Bordeaux University Hospital). Twenty serum steroids were quantified by LC\u2013MS\/MS and analyzed using orthogonal partial least squares discriminant analysis. Model robustness was assessed by internal cross-validation and external validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>20-steroid model achieved complete separation between NC21OHD and PCOS in both external validation cohorts (accuracy = 100%). The most discriminant metabolites were 21-deoxycortisone, 21-deoxycortisol, and 17-hydroxyprogesterone. Simplified 3- and 6-steroid models demonstrated reduced sensitivity (\u223c90%) and specificity (\u223c97%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Machine learning combined with basal LC\u2013MS\/MS steroid profiling enables accurate identification of NC21OHD without dynamic stimulation. This approach could simplify diagnosis, improve patient comfort, and support large-scale screening of hyperandrogenic women.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ejendo\/lvag114","type":"journal-article","created":{"date-parts":[[2026,7,5]],"date-time":"2026-07-05T11:32:30Z","timestamp":1783251150000},"page":"86-95","source":"Crossref","is-referenced-by-count":1,"title":["Using machine learning to discriminate non-classical 21-hydroxylase deficiency from polycystic ovary syndrome: an external validation study"],"prefix":"10.1093","volume":"195","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-3621-1987","authenticated-orcid":false,"given":"Tatiana","family":"Lecot-Connan","sequence":"first","affiliation":[{"name":"D\u00e9partement de M\u00e9tabolomique Clinique, H\u00f4pital Saint Antoine, AP-HP. Sorbonne Universit\u00e9 , 27 Rue Chaligny, Paris 75012 ,","place":["France"]},{"name":"Sorbonne Universit\u00e9, Service d\u2019Endocrinologie et M\u00e9decine de la Reproduction, Centre de R\u00e9f\u00e9rence des Maladies Endocriniennes Rares de la Croissance et du D\u00e9veloppement (CRESCENDO), Centre de R\u00e9f\u00e9rence des Pathologies Gyn\u00e9cologiques Rares (PGR), Inserm CIC 1901 Piti\u00e9 Salp\u00eatri\u00e8re, Endo-ERN, H\u00f4pital Piti\u00e9-Salp\u00eatri\u00e8re, AP-HP , Paris 75013 ,","place":["France"]},{"name":"Saint Antoine Research Center, Sorbonne Universit\u00e9, INSERM UMR 938 , Paris 75012 ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4175-4816","authenticated-orcid":false,"given":"Guillaume","family":"Bachelot","sequence":"additional","affiliation":[{"name":"D\u00e9partement de M\u00e9tabolomique Clinique, H\u00f4pital Saint Antoine, AP-HP. Sorbonne Universit\u00e9 , 27 Rue Chaligny, Paris 75012 ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruno","family":"Donadille","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, Service D\u2019Endocrinologie, Diab\u00e9tologie et M\u00e9decine de la Reproduction, H\u00f4pital Saint Antoine, AP-HP; Centre de R\u00e9f\u00e9rence des Maladies Endocriniennes Rares de la Croissance et du D\u00e9veloppement (CRESCENDO), Fili\u00e8re FIRENDO, R\u00e9seau Endo-ERN , Paris 75012 ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Camille","family":"Sayed","sequence":"additional","affiliation":[{"name":"Service d\u2019Endocrinologie Diab\u00e9tologie, AP-HP, H\u00f4pital Henri Mondor , Cr\u00e9teil 94000 ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9286-5631","authenticated-orcid":false,"given":"Jacques","family":"Young","sequence":"additional","affiliation":[{"name":"Service d\u2019Endocrinologie et des Maladies de la Reproduction, H\u00f4pital Bic\u00eatre, AP-HP, et Paris Saclay University , Le Kremlin-Bic\u00eatre 94275 ,","place":["France"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean","family":"Fiet","sequence":"additional","affiliation":[{"name":"D\u00e9partement de M\u00e9tabolomique Clinique, H\u00f4pital Saint Antoine, AP-HP. 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