MON-467 Treatment Patterns and Changes in Health States in Patients with Classic Congenital Adrenal Hyperplasia: An Analysis of Data from the CAHtalog™ Registry
Notice bibliographique
Résumé
Abstract Disclosure: G.S. Jeha: Full-time employee of Neurocrine Biosciences, Inc. P.C. White: Recipient of sponsored research support from Neurocrine Biosciences, Inc. and Diurnal Ltd (now Neurocrine UK Ltd) and has previously consulted for Neurocrine Biosciences. K. Lin-Su: None. D. Matos: None. F. Tang: Full-time employee of Cytel. H.S. Friedler: Full-time employee of Cytel. E. Roberts: Full-time employee of Neurocrine Biosciences, Inc. H.K. Cheng: Full-time employee of Neurocrine Biosciences, Inc. G.P. Sen: Full-time employee of Neurocrine Biosciences, Inc. Background: Classic congenital adrenal hyperplasia (CAH) often requires supraphysiologic glucocorticoid (GC) doses to reduce excess androgens. CAHtalog™ is an active US-based registry of patients with classic CAH developed in partnership with CARES Foundation on the PicnicHealth platform. Objective: To analyze treatment patterns and health states in patients in the CAHtalog registry. Methods: Medical records from pediatric (<18 yrs) and adult (≥18 yrs) patients in CAHtalog were abstracted into a deidentified database. GCs were summarized by type (hydrocortisone [HC], dexamethasone [DEX], prednisone [PRED]) and total daily GC dose in hydrocortisone equivalents. Due to the longitudinal nature of the registry, patients could be included in both age groups and multiple GC-treatment groups. Patients who took different GC types and doses over the observation period were counted in multiple categories. Health states for each patient were determined by matching GC records with the nearest androstenedione (A4) record (within the next 365 days). Based on the 95th percentile of cortisol production in healthy persons, GC doses were categorized as “higher” or “lower” (>11 or ≤11 mg/m2/d HCe) for the health state analysis. Based on the upper limit of normal (ULN) for age and sex, A4 was categorized as ≥ULN or <ULN. Transitions through health states based on GC dose (higher to lower, lower to higher) and A4 (≥ULN to <ULN, <ULN to ≥ULN) were analyzed in patients with ≥3 matched GC-A4 records. Results: Among 74 patients (37 adult; 51 pediatric; 14 both) with ≥1 medication record during the observation period, and without a standardized threshold or qualification of androgen control across individuals, the most common GC treatment (77.8% [adult]; 90.2% [pediatric]) at one point in their treatment journey was HC alone (mean±SD daily dose, 22.9±7.4 mg/d [adult]; 11.8±4.1 mg/m2/d [pediatric]), followed by DEX alone (47.2%; 35.1±18.4 mg/d) for adults. For pediatric patients, the next most common GC treatments after HC alone were DEX+HC (7.8%; 23.4±7.7 mg/m2/d) and PRED alone (7.8%, 12.6±9.8 mg/m2/d). Among 51 patients (20 adult; 33 pediatric; 2 both) with ≥3 matched GC-A4 records, health state transitions were observed across an age range of 0–67 yrs (median observation=6.1 yrs). Most (88.2%) patients had ≥1 health state transition and 64.7% had ≥3 health state transitions. Nearly all (98.0%) patients (with 76.5% of matched records) were prescribed higher GC doses and/or had A4 ≥ ULN at least once during their treatment journey. Conclusions: Longitudinal data from patients in the CAHtalog registry show various GC regimens and multiple transitions through health states characterized by higher GC doses and A4 ≥ULN, illustrating the lifelong balancing act between A4 management and GC dosing. These data also suggest that achievement of disease control today (A4 <ULN) does not predict maintenance of control tomorrow. Presentation: Monday, July 14, 2025
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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