A New Perspective on Drugs for Duchenne Muscular Dystrophy: Proposals for Better Respiratory Outcomes and Improved Regulatory Pathways
Bibliographic record
Abstract
New drugs for Duchenne muscular dystrophy (DMD) are emerging rapidly. However, we and others believe these drugs are achieving regulatory approval prematurely. It is the cardiorespiratory complications of DMD that cause the disease's major morbidities and that determine survival. Thus, to be truly effective, a new drug must improve cardiorespiratory function; instead, new drugs are approved for patient use via accelerated regulatory pathways that rely on surrogate outcome measures with unproven clinical benefits (such as tissue levels of non-biologic, truncated dystrophin) and on scales that reflect muscle strength (such as small improvements in timed activities). In DMD, cardiorespiratory complications occur in "older" individuals who are in the non-ambulatory stage of the disease. In contrast, accelerated approvals are based on data from young, ambulatory subjects, a group that essentially never experiences cardiorespiratory complications. When drug studies do obtain cardiorespiratory data, their methodologies are suboptimal. We critically review these methodologies in detail, including problems with the use of threshold levels of respiratory function as outcome measures; problems with the use of historical controls, whose results vary widely, and are influenced by uncontrolled variables related to their observational nature; and the limitations of using percent predicted forced vital capacity (FVC %pred), and its single rate of decline across a wide range of age and function, as a preferred respiratory outcome measure. We discuss the advantages of an alternative respiratory outcome, the absolute value of FVC with aging (the "Rideau plot"). Unlike FVC %pred, the Rideau plot considers distinct phenotypes rather than aggregating all individuals into a single respiratory trajectory. Key features of the Rideau plot can show the nature and timing of a drug's effect on respiratory function, making it a potentially better outcome measure for assessing the respiratory effects of a drug. With this article, we use our respiratory perspective to critically examine the DMD drug development process and to propose improvements in study methodologies and in the regulatory processes that approve new drugs.
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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 | 0.031 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.008 | 0.020 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.022 | 0.022 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".