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Research paper
A clinical tool for predicting survival in ALS
  1. Jonathan A Knibb1,
  2. Noa Keren2,
  3. Anna Kulka2,
  4. P Nigel Leigh3,
  5. Sarah Martin2,
  6. Christopher E Shaw2,
  7. Miho Tsuda4,
  8. Ammar Al-Chalabi2
  1. 1Brighton and Sussex University Hospitals NHS Trust, Royal Sussex County Hospital, Brighton, UK
  2. 2Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
  3. 3Trafford Centre for Biomedical Research, Brighton and Sussex Medical School, Falmer, UK
  4. 4Macclesfield District General Hospital, Macclesfield, Cheshire, UK
  1. Correspondence to Professor Ammar Al-Chalabi, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK; ammar.al-chalabi{at}kcl.ac.uk

Abstract

Background Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis.

Methods 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval.

Findings Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median.

Interpretation A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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Footnotes

  • Contributors JAK and AA-C were involved in the conception, design of the study and data interpretation. NK, AK, PNL, SM, CES, MT, AA-C contributed to the acquisition of the data. JAK analysed the data. All authors were involved in critically revising the manuscript and approving the final version to be submitted, and agreed to be accountable for all aspects of the work. The corresponding author had full access to all the data in the study and has final responsibility for the decision to submit for publication.

  • Funding This work was funded by the UK Medical Research Council and Economic and Social Research Council under the aegis of the EU Joint Programme—Neurodegenerative Disease research project. AAC and CES receive salary support from the National Institute for Health Research (NIHR) Biomedical Research Centre and Dementia Biomedical Research Unit at South London and Maudsley NHS Trust and King's College London. The work leading up to this publication was funded by the European Community's Health Seventh Framework Programme (FP7/2007–2013; grant agreement number 259867). The funding sources had no role in writing the manuscript or deciding to submit it for publication.

  • Competing interests PNL reports grants from MND Association Funding to support MND Clinic from 1995 to 2010, during the conduct of the study. CES reports consultancy and/or collaborative relationships with Glaxo Smith Kline, Vertex Pharmaceuticals, Chronos Therapeutics and Eli Lilly; he receives no personal gain and has never had any shares of any sort. AAC reports grants from EU FP7, grants from EU JPND—MRC and ESRC, grants from NIHR BRC in Mental Health and Dementia BRU, during the conduct of the study. All other authors declare no conflicts of interest.

  • Ethics approval The study was approved by the local ethics committees of King's College Hospital (15/LO/0810) and South London and Maudsley (222/02) NHS Foundation Trusts.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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