Comparing Deflazacort and Prednisone in Duchenne Muscular Dystrophy
Bibliographic record
Abstract
Deflazacort and prednisone/prednisolone are the current standard of care for patients with Duchenne muscular dystrophy (DMD) based on evidence that they improve muscle strength, improve timed motor function, delay loss of ambulation, improve pulmonary function, reduce the need for scoliosis surgery, delay onset of cardiomyopathy, and increase survival. Both have been used off-label for many years (choice dependent on patient preference, cost, and geographic location) before FDA approval of deflazacort for DMD in 2017. In this review, we compare deflazacort and prednisone/prednisolone in terms of their key pharmacological features, relative efficacy, and safety profiles in patients with DMD. Differentiating features include lipid solubility, pharmacokinetics, changes in gene expression profiles, affinity for the mineralocorticoid receptor, and impact on glucose metabolism. Evidence from randomized clinical trials, prospective studies, meta-analyses, and post-hoc analyses suggests that patients receiving deflazacort experience similar or slower rates of functional decline compared with those receiving prednisone/prednisolone. Regarding side effects, weight gain and behavior side effects appear to be greater with prednisone/prednisolone than with deflazacort, whereas bone health, growth parameters, and cataracts appear worse with deflazacort.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".