Advances in congenital adrenal hyperplasia newborn screening: 11-ketotestosterone and 21-deoxycortisone as additional discriminatory biomarkers
Bibliographic record
Abstract
BACKGROUND: A major limitation of newborn screening (NBS) for congenital adrenal hyperplasia (CAH) is the lack of specificity of the fluoroimmunoassay (FIA) currently used for 17-hydroxyprogesterone (17OHP) determination. This issue is more pronounced in newborns, due to elevated levels of interfering compounds. Fluoroimmunoassay at our NBS centre in Ile-de-France has a false-positive rate of around 80% and a predictive positive value of 16% for first- and second-tier measurements from dried blood spots. Recently, tandem mass spectrometry (LC-MS/MS) has gained international recognition as a complementary tool to FIA testing. Currently, the most frequently used biomarkers are 17OHP and 21-deoxycortisol, used either alone or in combination with steroid ratios such as cortisol or 4-androstenedione. Concurrently, the class of 11-oxygenate-androgens-such as 11-ketotestosterone-and more recently 11-oxygenate pregnanes-such as 21-deoxycortisone-has attracted growing interest in the diagnosis of 21-hydroxylase deficiency. These derivatives result from the combined action of 11-beta hydroxysteroid dehydrogenase and 11-beta hydroxylase. METHODS: We propose a revisited LC-MS/MS steroid profile, enriched with these classes of biomarkers, to be included in the CAH NBS algorithm. This combination could be used as a multi-steroid approach implemented using a machine learning model. RESULTS: Our preliminary results suggest that these oxygenated androgen/pregnane steroids are significantly discriminative to streamline the NBS process for CAH. We have demonstrated this in 2 different NBS centres, in the greater Paris region and in Brittany, France. CONCLUSION: This new algorithm could have an important impact on reducing the number of recall and family stress related to NBS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".