Characterizing the Occurrence of Key Clinical Milestones in Duchenne Muscular Dystrophy in the United States Using Real-World Data
Bibliographic record
Abstract
BACKGROUND: Data on the clinical course of Duchenne muscular dystrophy (DMD) exist from well-characterized clinical cohorts but estimates from real-world populations are fewer. OBJECTIVE: The objective was to estimate the prevalence of key clinical milestones by age, among real-world commercially-insured DMD patients in the United States. METHODS: MarketScan claims (2013-2018) were used to identify males with DMD. The percentages with wheelchair use or experiencing scoliosis, neurologic/neuropsychiatric involvement, cardiomyopathy, and respiratory involvement were tabulated; as were the median (interquartile range [IQR]) ages at first observed occurrence within the claims data. RESULTS: Among DMD patients (n = 1,964), the median (IQR) baseline age was 15 (9-21) years, and median follow-up was 1.7 years. Wheelchair use was observed in 55% of those aged 8 to 13 years at cohort entry; scoliosis, among 38% of those 8 to 10 and 52% of those 11 to 13 years; neurologic/neuropsychiatric involvement, among 41-43% of those 8 to 13 years; respiratory involvement, among 45% of those 14 to 19 years; and cardiomyopathy, among 68% of those 14 to 16 and 58% of those 17 to 19 years. CONCLUSIONS: The prevalence of key clinical milestones across ages was broadly consistent with published findings. Variability in estimates reflect clinical heterogeneity; these contemporary estimates from real-world data help characterize clinical outcomes in DMD.
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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 | 0.001 | 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 | 0.001 | 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".