ArticleJournal of neurology, neurosurgery, and psychiatry2019
Critical design considerations for time-to-event endpoints in amyotrophic lateral sclerosis clinical trials.
Article in Journal of neurology, neurosurgery, and psychiatry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Herbal medicine for amyotrophic lateral sclerosis: A systematic review and meta-analysis.Frontiers in pharmacology · 2022Pooled it
- Review
- Time-to-event analysis mitigates the impact of symptomatic therapy on therapeutic benefit in Parkinson's disease trials.NPJ Parkinson's disease · 2025Article
- Living systematic review and comprehensive network meta-analysis of ALS clinical trials: study protocol.BMJ open · 2024Article
- Development and Evaluation of a Simulation-Based Algorithm to Optimize the Planning of Interim Analyses for Clinical Trials in ALS.Neurology · 2023Article
- Article
- Composite endpoint for ALS clinical trials based on patient preference: Patient-Ranked Order of Function (PROOF).Journal of neurology, neurosurgery, and psychiatry · 2022Article
- Functional Loss and Mortality in Randomized Clinical Trials for Amyotrophic Lateral Sclerosis: To Combine, or Not to Combine-That is the Estimand.Clinical pharmacology and therapeutics · 2022Review
- A Road Map for Remote Digital Health Technology for Motor Neuron Disease.Journal of medical Internet research · 2021Article
- Innovating Clinical Trials for Amyotrophic Lateral Sclerosis: Challenging the Established Order.Neurology · 2021Article
- TDP-43 proteinopathies: a new wave of neurodegenerative diseases.Journal of neurology, neurosurgery, and psychiatry · 2020Review
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundFunding and resources for low prevalent neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS) are limited, and optimising their use is vital for efficient drug development. In this study, we review the design assumptions for pivotal ALS clinical trials with time-to-event endpoints and provide optimised settings for future trials.
methodsWe extracted design settings from 13 completed placebo-controlled trials. Optimal assumptions were estimated using parametric survival models in individual participant data (n=4991). Designs were compared in terms of sample size, trial duration, drug use and costs.
resultsPrevious trials overestimated the hazard rate by 18.9% (95% CI 3.4% to 34.5%, p=0.021). The median expected HR was 0.56 (range 0.33-0.66). Additionally, we found evidence for an increasing mean hazard rate over time (Weibull shape parameter of 2.03, 95% CI 1.93 to 2.15, p<0.001), which affects the design and planning of future clinical trials. Incorporating accrual time and assuming an increasing hazard rate at the design stage reduced sample size by 33.2% (95% CI 27.9 to 39.4), trial duration by 17.4% (95% CI 11.6 to 23.3), drug use by 14.3% (95% CI 9.6 to 19.0) and follow-up costs by 21.2% (95% CI 15.6 to 26.8).
conclusionsImplementing distributional knowledge and incorporating accrual at the design stage could achieve large gains in the efficiency of ALS clinical trials with time-to-event endpoints. We provide an open-source platform that helps investigators to make more accurate sample size calculations and optimise the use of their available resources.
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Registered trials
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