Article Text

Download PDFPDF

Time-to-event analysis for sports injury research part 2: time-varying outcomes
  1. Rasmus Oestergaard Nielsen1,
  2. Michael Lejbach Bertelsen1,
  3. Daniel Ramskov1,2,
  4. Merete Møller3,
  5. Adam Hulme4,
  6. Daniel Theisen5,
  7. Caroline F Finch6,
  8. Lauren Victoria Fortington6,7,
  9. Mohammad Ali Mansournia8,9,
  10. Erik Thorlund Parner10
  1. 1 Department of Public Health, Section for Sports Science, Aarhus University, Aarhus, Denmark
  2. 2 Department of Physiotherapy, University College Northern Denmark, Aalborg, Denmark
  3. 3 Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark
  4. 4 Centre for Human Factors and Sociotechnical Systems, Faculty of Arts, Business and Law, University of the Sunshine Coast, Maroochydore DC, Queensland, Australia
  5. 5 Sports Medicine Research Laboratory, Luxembourg Institute of Health, Luxembourg, Luxembourg
  6. 6 Australian Centre for Research into Injury in Sport and its Prevention, School of Medical and Health Sciences, Edith Cowan University, Perth, Western Australia, Australia
  7. 7 Faculty of Science and Technology, Federation University Australia, Ballarat, Victoria, Australia
  8. 8 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran
  9. 9 Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran
  10. 10 Department of Public Health, Section for Biostatistics, Aarhus University, Aarhus, Denmark
  1. Correspondence to Dr Rasmus Oestergaard Nielsen, Department of Public Health, Section for Sports Science, Aarhus University, Aarhus 8000, Denmark; roen{at}ph.au.dk

Abstract

Background Time-to-event modelling is underutilised in sports injury research. Still, sports injury researchers have been encouraged to consider time-to-event analyses as a powerful alternative to other statistical methods. Therefore, it is important to shed light on statistical approaches suitable for analysing training load related key-questions within the sports injury domain.

Content In the present article, we illuminate: (i) the possibilities of including time-varying outcomes in time-to-event analyses, (ii) how to deal with a situation where different types of sports injuries are included in the analyses (ie, competing risks), and (iii) how to deal with the situation where multiple subsequent injuries occur in the same athlete.

Conclusion Time-to-event analyses can handle time-varying outcomes, competing risk and multiple subsequent injuries. Although powerful, time-to-event has important requirements: researchers are encouraged to carefully consider prior to any data collection that five injuries per exposure state or transition is needed to avoid conducting statistical analyses on time-to-event data leading to biased results. This requirement becomes particularly difficult to accommodate when a stratified analysis is required as the number of variables increases exponentially for each additional strata included. In future sports injury research, we need stratified analyses if the target of our research is to respond to the question: ‘how much change in training load is too much before injury is sustained, among athletes with different characteristics?’ Responding to this question using multiple time-varying exposures (and outcomes) requires millions of injuries. This should not be a barrier for future research, but collaborations across borders to collecting the amount of data needed seems to be an important step forward.

  • injury
  • statistics
  • training load

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

View Full Text

Statistics from Altmetric.com

Footnotes

  • Contributors All authors contributed equally in writing the educational review. DR performed the analyses leading to the results in Table 2 and Figure 2.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent Obtained.

  • Ethics approval Local ethics committee central Denmark region (N-20140069)

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

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Linked Articles

  • Education reviews
    Rasmus Oestergaard Nielsen Michael Lejbach Bertelsen Daniel Ramskov Merete Møller Adam Hulme Daniel Theisen Caroline F Finch Lauren Victoria Fortington Mohammad Ali Mansournia Erik Thorlund Parner