ReviewNeurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics2015
Being PRO-ACTive: What can a Clinical Trial Database Reveal About ALS?
Review in Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic and Comprehensive Review on Disease-Causing Genes in Amyotrophic Lateral Sclerosis.Journal of molecular neuroscience : MN · 2020Pooled it
- Rasagiline for amyotrophic lateral sclerosis: A randomized, controlled trial.Muscle & nerve · 2019Trial
- Development of a machine learning-based survival prediction model for ALS inclusive of the advanced-stage population.Amyotrophic lateral sclerosis & frontotemporal degeneration · 2026Article
- Dynamic effects of prognostic factors and individual survival prediction for amyotrophic lateral sclerosis disease.Annals of clinical and translational neurology · 2023Article
- Towards a Machine Learning Empowered Prognostic Model for Predicting Disease Progression for Amyotrophic Lateral Sclerosis.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Ibudilast (MN-166) in amyotrophic lateral sclerosis- an open label, safety and pharmacodynamic trial.NeuroImage. Clinical · 2021Article
- Does including machine learning predictions in ALS clinical trial analysis improve statistical power?Annals of clinical and translational neurology · 2020Article
- Insights into Amyotrophic Lateral Sclerosis from a Machine Learning Perspective.Journal of clinical medicine · 2019Article
- Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering.Neuroinformatics · 2019Article
- Epidemiology of ALS in Korea using nationwide big data.Journal of neurology, neurosurgery, and psychiatry · 2019Article
- Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach.Scientific reports · 2019Article
- Using automated electronic medical record data extraction to model ALS survival and progression.BMC neurology · 2018Article
- Improved stratification of ALS clinical trials using predicted survival.Annals of clinical and translational neurology · 2018Article
- Using an onset-anchored Bayesian hierarchical model to improve predictions for amyotrophic lateral sclerosis disease progression.BMC medical research methodology · 2018Article
- Unraveling the Complexity of Amyotrophic Lateral Sclerosis Survival Prediction.Frontiers in neuroinformatics · 2018Article
- Article
- Predicting disease progression in amyotrophic lateral sclerosis.Annals of clinical and translational neurology · 2016Article
- The Spectrum of Motor Neuron Diseases: From Childhood Spinal Muscular Atrophy to Adult Amyotrophic Lateral Sclerosis.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advancing research and clinical care, and conducting successful and cost-effective clinical trials requires characterizing a given patient population. To gather a sufficiently large cohort of patients in rare diseases such as amyotrophic lateral sclerosis (ALS), we developed the Pooled Resource Open-Access ALS Clinical Trials (PRO-ACT) platform. The PRO-ACT database currently consists of >8600 ALS patient records from 17 completed clinical trials, and more trials are being incorporated. The database was launched in an open-access mode in December 2012; since then, >400 researchers from >40 countries have requested the data. This review gives an overview on the research enabled by this resource, through several examples of research already carried out with the goal of improving patient care and understanding the disease. These examples include predicting ALS progression, the simulation of future ALS clinical trials, the verification of previously proposed predictive features, the discovery of novel predictors of ALS progression and survival, the newly identified stratification of patients based on their disease progression profiles, and the development of tools for better clinical trial recruitment and monitoring. Results from these approaches clearly demonstrate the value of large datasets for developing a better understanding of ALS natural history, prognostic factors, patient stratification, and more. The increasing use by the community suggests that further analyses of the PRO-ACT database will continue to reveal more information about this disease that has for so long defied our understanding.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.