Prognostic factors for changes in the timed 4-stair climb in patients with Duchenne muscular dystrophy, and implications for measuring drug efficacy: A multi-institutional collaboration
Bibliographic record
Abstract
The timed 4-stair climb (4SC) assessment has been used to measure function in Duchenne muscular dystrophy (DMD) practice and research. We sought to identify prognostic factors for changes in 4SC, assess their consistency across data sources, and the extent to which prognostic scores could be useful in DMD clinical trial design and analysis. Data from patients with DMD in the placebo arm of a phase 3 trial (Tadalafil DMD trial) and two real-world sources (Universitaire Ziekenhuizen, Leuven, Belgium [Leuven] and Cincinnati Children's Hospital Medical Center [CCHMC]) were analyzed. One-year changes in 4SC completion time and velocity (stairs/second) were analyzed. Prognostic models included age, height, weight, steroid use, and multiple timed function tests and were developed using multivariable regression, separately in each data source. Simulations were used to quantify impacts on trial sample size requirements. Data on 1-year changes in 4SC were available from the Tadalafil DMD trial (n = 92) Leuven (n = 67), and CCHMC (n = 212). Models incorporating multiple timed function tests, height, and weight significantly improved prognostic accuracy for 1-year change in 4SC (R2: 29%-36% for 4SC velocity, and 29%-34% for 4SC time) compared to models including only age, baseline 4SC and steroid duration (R2:8%-17% for 4SC velocity and 2%-13% for 4SC time). Measures of walking and rising ability contributed important prognostic information for changes in 4SC. In a randomized trial with equal allocation to treatment and placebo, adjustment for such a prognostic score would enable detection (at 80% power) of a treatment effect of 0.25 stairs/second with 100-120 patients, compared to 170-190 patients without prognostic score adjustment. Combining measures of ambulatory function doubled prognostic accuracy for 1-year changes in 4SC completion time and velocity. Randomized clinical trials incorporating a validated prognostic score could reduce sample size requirements by approximately 40%. Knowledge of important prognostic factors can also inform adjusted comparisons to external controls.
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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 | 0.000 | 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 | 0.000 | 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".