MON-467 Treatment Patterns and Changes in Health States in Patients with Classic Congenital Adrenal Hyperplasia: An Analysis of Data from the CAHtalog™ Registry
Bibliographic record
Abstract
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 Presentation: Monday, July 14, 2025
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".