A novel, efficient, randomized selection trial comparing combinations of drug therapy for ALS
Bibliographic record
Abstract
Combining agents with different mechanisms of action may be necessary for meaningful results in treating ALS. The combinations of minocycline-creatine and celecoxib-creatine have additive effects in the murine model. New trial designs are needed to efficiently screen the growing number of potential neuroprotective agents. Our objective was to assess two drug combinations in ALS using a novel phase II trial design. We conducted a randomized, double-blind selection trial in sequential pools of 60 patients. Participants received minocycline (100 mg)-creatine (10 g) twice daily or celecoxib (400 mg)-creatine (10 g) twice daily for six months. The primary objective was treatment selection based on which combination best slowed deterioration in the ALS Functional Rating Scale-Revised (ALSFRS-R); the trial could be stopped after one pool if the difference between the two arms was adequately large. At trial conclusion, each arm was compared to a historical control group in a futility analysis. Safety measures were also examined. After the first patient pool, the mean six-month decline in ALSFRS-R was 5.27 (SD=5.54) in the celecoxib-creatine group and 6.47 (SD=9.14) in the minocycline-creatine group. The corresponding decline was 5.82 (SD=6.77) in the historical controls. The difference between the two sample means exceeded the stopping criterion. The null hypothesis of superiority was not rejected in the futility analysis. Skin rash occurred more frequently in the celecoxib-creatine group. In conclusion, the celecoxib-creatine combination was selected as preferable to the minocycline-creatine combination for further evaluation. This phase II design was efficient, leading to treatment selection after just 60 patients, and can be used in other phase II trials to assess different agents.
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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 | 0.028 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".