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Related Experiment Video

Updated: Nov 14, 2025

Clinical Testing and Spinal Cord Removal in a Mouse Model for Amyotrophic Lateral Sclerosis ALS
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Prognostic models for amyotrophic lateral sclerosis: a systematic review.

Lu Xu1, Bingjie He1, Yunjing Zhang1

  • 1Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing, 100191, China.

Journal of Neurology
|March 11, 2021
PubMed
Summary

This review found many prognostic models for amyotrophic lateral sclerosis (ALS), but their usefulness is questionable due to methodological issues and lack of validation. Future ALS models need better predictors and independent validation.

Keywords:
Amyotrophic lateral sclerosisMotor neuron diseaseNeurodegenerative diseasesPrognostic modelSystematic review

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Area of Science:

  • Neurology
  • Biostatistics
  • Medical Informatics

Background:

  • Numerous prognostic models for amyotrophic lateral sclerosis (ALS) have been developed.
  • A comprehensive evaluation of these existing ALS prognostic models is lacking.
  • This study aims to map and assess the contribution of current ALS prognostic models.

Purpose of the Study:

  • To systematically review and evaluate prognostic models for amyotrophic lateral sclerosis (ALS).
  • To identify methodological strengths and weaknesses in current ALS modeling strategies.
  • To provide recommendations for improving future prognostic model development and validation in ALS.

Main Methods:

  • Searched major databases (Medline, Embase, Web of Science, Cochrane Library) up to February 2021.
  • Included studies developing or validating prognostic models for ALS.
  • Extracted data on modeling methods and methodological quality.

Main Results:

  • Included 28 studies with 34 ALS prognostic models; 19 models underwent external validation.
  • Survival (56%) and progression (35%) were primary outcomes; common predictors included age and disease duration.
  • Machine learning was the predominant method (47%), but most models lacked presentation (74%) and robust validation (discrimination 35%, calibration 6%).

Conclusions:

  • The clinical utility of current ALS prognostic models is questionable due to methodological limitations and insufficient independent external validation.
  • Future research should focus on incorporating novel predictors, conducting rigorous external validation, and performing head-to-head comparisons of existing models.
  • One model by Westeneng et al. showed promise with low risk of bias and good performance, suggesting a potential reliable tool for practice.