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Tollgate-based progression pathways of ALS patients

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Abstract

Objective

To capture ALS progression in arm, leg, speech, swallowing, and breathing segments using a disease-specific staging system, namely tollgate-based ALS staging system (TASS), where tollgates refer to a set of critical clinical events including having slight weakness in arms, needing a wheelchair, needing a feeding tube, etc.

Methods

We compiled a longitudinal dataset from medical records including free-text clinical notes of 514 ALS patients from Mayo Clinic, Rochester-MN. We derived tollgate-based progression pathways of patients up to a 1-year period starting from the first clinic visit. We conducted Kaplan–Meier analyses to estimate the probability of passing each tollgate over time for each functional segment.

Results

At their first clinic visit, 93%, 77%, and 60% of patients displayed some level of limb, bulbar, and breathing weakness, respectively. The proportion of patients at milder tollgate levels (tollgate level < 2) was smaller for arm and leg segments (38% and 46%, respectively) compared to others (> 65%). Patients showed non-uniform TASS pathways, i.e., the likelihood of passing a tollgate differed based on the affected segments at the initial visit. For instance, stratified by impaired segments at the initial visit, patients with limb and breathing impairment were more likely (62%) to use bi-level positive airway pressure device in a year compared to those with bulbar and breathing impairment (26%).

Conclusion

Using TASS, clinicians can inform ALS patients about their individualized likelihood of having critical disabilities and assistive-device needs (e.g., being dependent on wheelchair/ventilation, needing walker/wheelchair or communication devices), and help them better prepare for future.

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References

  1. Morris J (2015) Amyotrophic lateral sclerosis (ALS) and related motor neuron diseases: an overview. Neurodiagn J 55:180–194. https://doi.org/10.1080/21646821.2015.1075181

    Article  PubMed  Google Scholar 

  2. Armon C (2008) From clues to mechanisms: understanding ALS initiation and spread. Neurology 71:872–873. https://doi.org/10.1212/01.wnl.0000325992.50108.60

    Article  PubMed  Google Scholar 

  3. Mazzini L, Mareschi K, Ferrero I et al (2008) Stem cell treatment in amyotrophic lateral sclerosis. J Neurol Sci 265:78–83. https://doi.org/10.1016/j.jns.2007.05.016

    Article  CAS  PubMed  Google Scholar 

  4. Kiernan MC, Vucic S, Cheah BC et al (2011) Amyotrophic lateral sclerosis. Lancet 377:942–955. https://doi.org/10.1016/S0140-6736(10)61156-7

    Article  CAS  PubMed  Google Scholar 

  5. Mitsumoto H, Del Bene M (2000) Improving the quality of life for people with ALS: the challenge ahead. Amyotroph Lateral Scler Other Motor Neuron Disord 1:329–336. https://doi.org/10.1080/146608200300079464

    Article  CAS  PubMed  Google Scholar 

  6. Kimura F, Fujimura C, Ishida S et al (2006) Progression rate of ALSFRS-R at time of diagnosis predicts survival time in ALS. Neurology 66:265–267. https://doi.org/10.1212/01.wnl.0000194316.91908.8a

    Article  CAS  PubMed  Google Scholar 

  7. Kollewe K, Mauss U, Krampfl K et al (2008) ALSFRS-R score and its ratio: a useful predictor for ALS-progression. J Neurol Sci 275:69–73. https://doi.org/10.1016/j.jns.2008.07.016

    Article  PubMed  Google Scholar 

  8. Magnus T, Beck M, Giess R et al (2002) Disease progression in amyotrophic lateral sclerosis: predictors of survival. Muscle Nerve 25:709–714. https://doi.org/10.1002/mus.10090

    Article  CAS  PubMed  Google Scholar 

  9. Brooks BR (1996) Natural history of ALS: symptoms, strength, pulmonary function, and disability. Neurology 47:S71–S82

    Article  CAS  PubMed  Google Scholar 

  10. Louwerse ES, Visser CE, Bossuyt PMM, Weverling GJ (1997) Amyotrophic lateral sclerosis: mortality risk during the course of the disease and prognostic factors. J Neurol Sci 152:S10–S17. https://doi.org/10.1016/S0022-510X(97)00238-4

    Article  PubMed  Google Scholar 

  11. Chio A, Mora G, Leone M et al (2002) Early symptom progression rate is related to ALS outcome: a prospective population-based study. Neurology 59:99–103. https://doi.org/10.1212/WNL.59.1.99

    Article  CAS  PubMed  Google Scholar 

  12. Balendra R, Jones A, Jivraj N et al (2014) Estimating clinical stage of amyotrophic lateral sclerosis from the ALS Functional Rating Scale. Amyotroph Lateral Scler Front Degener 15:279–284. https://doi.org/10.3109/21678421.2014.897357

    Article  Google Scholar 

  13. Chiò A, Hammond ER, Mora G et al (2013) Development and evaluation of a clinical staging system for amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. https://doi.org/10.1136/jnnp-2013-306589

    Article  PubMed  Google Scholar 

  14. Turner MR, Scaber J, Goodfellow JA et al (2010) The diagnostic pathway and prognosis in bulbar-onset amyotrophic lateral sclerosis. J Neurol Sci 294:81–85. https://doi.org/10.1016/j.jns.2010.03.028

    Article  PubMed  Google Scholar 

  15. Bromberg MB, Brownell AA, Forshew DA, Swenson M (2010) A timeline for predicting durable medical equipment needs and interventions for amyotrophic lateral sclerosis patients. Amyotroph Lateral Scler 11:110–115. https://doi.org/10.3109/17482960902835970

    Article  PubMed  Google Scholar 

  16. Balendra R, Jones A, Jivraj N et al (2015) Use of clinical staging in amyotrophic lateral sclerosis for phase 3 clinical trials. J Neurol Neurosurg Psychiatry 86:45–49. https://doi.org/10.1136/jnnp-2013-306865

    Article  PubMed  Google Scholar 

  17. Roche JC, Rojas-Garcia R, Scott KM et al (2012) A proposed staging system for amyotrophic lateral sclerosis. Brain 135:847–852. https://doi.org/10.1093/brain/awr351

    Article  PubMed  PubMed Central  Google Scholar 

  18. Orrell RW, Habgood JJ, Malaspina A et al (1999) Clinical characteristics of SOD1 gene mutations in UK families with ALS. J Neurol Sci 169:56–60. https://doi.org/10.1016/S0022-510X(99)00216-6

    Article  CAS  PubMed  Google Scholar 

  19. Bird S (2006) NLTK: the natural language Toolkit Steven. In: Proceedings of the COLING/ACL on Interactive presentation sessions. Association for Computational Linguistics, Morristown, NJ, USA, pp 69–72

  20. Loh W-Y (2011) Classification and regression trees. Wiley Interdiscip Rev Data Min Knowl Discov 1:14–23. https://doi.org/10.1002/widm.8

    Article  Google Scholar 

  21. Lane P (2008) Handling drop-out in longitudinal clinical trials: a comparison of the LOCF and MMRM approaches. Pharm Stat 7:93–106. https://doi.org/10.1002/pst.267

    Article  PubMed  Google Scholar 

  22. Chow GC, Lin A-L (1971) Best linear unbiased interpolation, distribution, and extrapolation of time series by related series. Rev Econ Stat 53:372–375. https://doi.org/10.2307/1928739

    Article  Google Scholar 

  23. Van Buuren S, Groothuis-Oudshoorn K (2011) Multivariate imputation by chained equations. J Stat Softw 45:1–67. https://doi.org/10.1177/0962280206074463

    Article  Google Scholar 

  24. Therneau TM, Lumley T (2017) A package for survival analysis in R Version 2.41-2 2–41. https://cran.r-project.org/web/packages/survival/survival.pdf

  25. Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. Source J Am Stat Assoc 53:457–481. https://doi.org/10.2307/2281868

    Article  Google Scholar 

  26. Rich JT, Neely JG, Paniello RC et al (2010) A practical guide to understanding Kaplan–Meier curves. Otolaryngol Head Neck Surg 143:331–336. https://doi.org/10.1016/j.otohns.2010.05.007

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ingre C, Roos PM, Piehl F et al (2015) Risk factors for amyotrophic lateral sclerosis. Clin Epidemiol 7:181–193. https://doi.org/10.2147/CLEP.S37505

    Article  PubMed  PubMed Central  Google Scholar 

  28. Manjaly ZR, Scott KM, Abhinav K et al (2010) The sex ratio in amyotrophic lateral sclerosis: a population based study. Amyotroph Lateral Scler 11:439–442. https://doi.org/10.3109/17482961003610853

    Article  PubMed  PubMed Central  Google Scholar 

  29. Maier A, Holm T, Wicks P et al (2012) Online assessment of ALS functional rating scale compares well to in-clinic evaluation: a prospective trial. Amyotroph Lateral Scler 13:210–216. https://doi.org/10.3109/17482968.2011.633268

    Article  PubMed  PubMed Central  Google Scholar 

  30. Gautier G, Verschueren A, Monnier A et al (2010) ALS with respiratory onset: Clinical features and effects of non-invasive ventilation on the prognosis. Amyotroph Lateral Scler 11:379–382. https://doi.org/10.3109/17482960903426543

    Article  PubMed  Google Scholar 

  31. Cedarbaum JM, Stambler N (2001) Disease status and use of ventilatory support by ALS patients. Amyotroph lateral Scler other Mot neuron Disord 2:19–22

    Article  CAS  Google Scholar 

  32. Qureshi MM, Hayden D, Urbinelli L et al (2006) Analysis of factors that modify susceptibility and rate of progression in amyotrophic lateral sclerosis (ALS). Amyotroph Lateral Scler 7:173–182. https://doi.org/10.1080/14660820600640596

    Article  PubMed  Google Scholar 

  33. Küffner R, Zach N, Norel R et al (2015) Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression. Nat Biotechnol 33:51–57. https://doi.org/10.1038/nbt.3051

    Article  CAS  PubMed  Google Scholar 

  34. Hothorn T, Jung HH (2014) RandomForest4Life: A Random Forest for predicting ALS disease progression. Amyotroph Lateral Scler Front Degener 15:444–452. https://doi.org/10.3109/21678421.2014.893361

    Article  Google Scholar 

  35. Proudfoot M, Jones A, Talbot K et al (2016) The ALSFRS as an outcome measure in therapeutic trials and its relationship to symptom onset. Amyotroph Lateral Scler Front Degener 17:414–425. https://doi.org/10.3109/21678421.2016.1140786

    Article  CAS  Google Scholar 

  36. Franchignoni F, Mora G, Giordano A et al (2013) Evidence of multidimensionality in the ALSFRS-R Scale: a critical appraisal on its measurement properties using Rasch analysis. J Neurol Neurosurg Psychiatry 84:1340–1345. https://doi.org/10.1136/jnnp-2012-304701

    Article  PubMed  Google Scholar 

  37. Montes J, Levy G, Albert S et al (2006) Development and evaluation of a self-administered version of the ALSFRS-R. Neurology 67:1294–1296

    Article  CAS  PubMed  Google Scholar 

  38. Böcker FM, Seibold I, Neundörfer B (1990) Disability in everyday tasks and subjective status of patients with advanced amyotrophic lateral sclerosis. Fortschr Neurol Psychiatr 58:224–236. https://doi.org/10.1055/s-2007-1001186

    Article  PubMed  Google Scholar 

  39. Al-Chalabi A, Hardiman O (2013) The epidemiology of ALS: a conspiracy of genes, environment and time. Nat Rev Neurol 9:617–628. https://doi.org/10.1038/nrneurol.2013.203

    Article  CAS  PubMed  Google Scholar 

  40. Swinnen B, Robberecht W (2014) The phenotypic variability of amyotrophic lateral sclerosis. Nat Rev Neurol 10:661–670. https://doi.org/10.1038/nrneurol.2014.184

    Article  PubMed  Google Scholar 

  41. Pimentel M, Morales W, Chua K et al (2011) Effects of rifaximin treatment and retreatment in nonconstipated IBS subjects. Dig Dis Sci 56:2067–2072. https://doi.org/10.1007/s10620-011-1728-5

    Article  CAS  PubMed  Google Scholar 

  42. Tripepi G, Heinze G, Jager KJ et al (2013) Risk prediction models. Nephrol Dial Transplant 28:1975–1980. https://doi.org/10.1093/ndt/gft095

    Article  PubMed  Google Scholar 

  43. Atassi N, Berry J, Shui A et al (2014) The PRO-ACT database. Neurology 83:1719–1725

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Sedgwick P (2014) Spearman’s rank correlation coefficient. BMJ 349:g7327. https://doi.org/10.1136/bmj.g7327

    Article  PubMed  Google Scholar 

  45. Cedarbaum JM, Stambler N, Malta E et al (1999) The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function. J Neurol Sci 169:13–21. https://doi.org/10.1016/S0022-510X(99)00210-5

    Article  CAS  PubMed  Google Scholar 

  46. Gordon PH, Miller RG, Moore DH (2004) ALSFRS-R. Amyotroph Lateral Scler Other. Mot Neuron Disord 5:90–93. https://doi.org/10.1080/17434470410019906

    Article  Google Scholar 

  47. Reich-Slotky R, Andrews J, Cheng B et al (2013) Body mass index (BMI) as predictor of ALSFRS-R score decline in ALS patients. Amyotroph Lateral Scler Front Degener 14:212–216. https://doi.org/10.3109/21678421.2013.770028

    Article  Google Scholar 

  48. Davis LJ, Offord KP (1997) Logistic regression. J Pers Assess 68:497–507. https://doi.org/10.1207/s15327752jpa6803_3

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This research is partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grants 113788 and 113790). This work is also funded in part by the Mayo Clinic Department of Neurology and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery.

Author information

Author notes

  1. Brian A. Crum, Mustafa Y. Sir contributed equally as senior authors to this work.

Authors and Affiliations

  1. Harvard Medical School, Boston, 25 Shattuck St, Boston, MA, 02115, USA

    Özden O. Dalgıç

  2. Institute for Technology Assessment, Massachusetts General Hospital, 101 Merrimac Street, Boston, MA, 02114, USA

    Özden O. Dalgıç

  3. Department of Managements Sciences, University of Waterloo, 200 University Ave., Waterloo, ON, N2L3G1, Canada

    F. Safa Erenay

  4. Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA

    Kalyan S. Pasupathy & Mustafa Y. Sir

  5. Mayo Kern Center for the Science of Health Care Delivery, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA

    Kalyan S. Pasupathy & Mustafa Y. Sir

  6. Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, 400 Daniels Hall, Raleigh, NC, 27695, USA

    Osman Y. Özaltın

  7. Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA

    Brian A. Crum

  8. Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, 200 First Street SW, Rochester, MN, 55905, USA

    Mustafa Y. Sir

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  1. Özden O. Dalgıç
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Correspondence to Mustafa Y. Sir.

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This study was reviewed by the Mayo Clinic Institutional Review Board and deemed as an exempt study.

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Dalgıç, Ö.O., Erenay, F.S., Pasupathy, K.S. et al. Tollgate-based progression pathways of ALS patients. J Neurol 266, 755–765 (2019). https://doi.org/10.1007/s00415-019-09199-y

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  • DOI: https://doi.org/10.1007/s00415-019-09199-y

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