Time-to-event analysis for sports injury research part 1: time-varying exposures

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

doi:10.1136/bjsports-2018-099408

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Time-to-event analysis for sports injury research part 1: time-varying exposures

Journal article

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Time-to-event analysis for sports injury research part 1: time-varying exposures

Rasmus Oestergaard Nielsen, Michael Lejbach Bertelsen, Daniel Ramskov, Merete Moller, Adam Hulme, Daniel Theisen, Caroline F Finch, Lauren Victoria Fortington, Mohammad Ali Mansournia and Erik Thorlund Parner

British Journal of Sports Medicine, Vol.53(1), pp.61-68

2019

DOI: https://doi.org/10.1136/bjsports-2018-099408

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Abstract

Background 'How much change in training load is too much before injury is sustained, among different athletes?' is a key question in sports medicine and sports science. To address this question the investigator/practitioner must analyse exposure variables that change over time, such as change in training load. Very few studies have included time-varying exposures (eg, training load) and time-varying effect-measure modifiers (eg, previous injury, biomechanics, sleep/stress) when studying sports injury aetiology. Aim To discuss advanced statistical methods suitable for the complex analysis of time-varying exposures such as changes in training load and injury-related outcomes. Content Time-varying exposures and time-varying effect-measure modifiers can be used in time-to-event models to investigate sport injury aetiology. We address four key-questions (i) Does time-to-event modelling allow change in training load to be included as a time-varying exposure for sport injury development? (ii) Why is time-to-event analysis superior to other analytical concepts when analysing training-load related data that changes status over time? (iii) How can researchers include change in training load in a time-to-event analysis? and, (iv) Are researchers able to include other time-varying variables into time-to-event analyses? We emphasise that cleaning datasets, setting up the data, performing analyses with time-varying variables and interpreting the results is time-consuming, and requires dedication. It may need you to ask for assistance from methodological peers as the analytical approaches presented this paper require specialist knowledge and well-honed statistical skills. Conclusion To increase knowledge about the association between changes in training load and injury, we encourage sports injury researchers to collaborate with statisticians and/or methodological epidemiologists to carefully consider applying time-to-event models to prospective sports injury data. This will ensure appropriate interpretation of time-to-event data.

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Title: Time-to-event analysis for sports injury research part 1: time-varying exposures
Authors: Rasmus Oestergaard Nielsen (Author) - Aarhus University, Denmark
Michael Lejbach Bertelsen (Author) - Aarhus University, Denmark
Daniel Ramskov (Author) - Aarhus University, Denmark
Merete Moller (Author) - University of Southern Denmark, Denmark
Adam Hulme (Author) - University of the Sunshine Coast - Faculty of Science, Health, Education and Engineering
Daniel Theisen (Author) - Luxembourg Institute of Health, Luxembourg
Caroline F Finch (Author) - Edith Cowan University
Lauren Victoria Fortington (Author) - Edith Cowan University
Mohammad Ali Mansournia (Author) - Tehran University of Medical Sciences, Iran
Erik Thorlund Parner (Author) - Aarhus University, Denmark
Publication details: British Journal of Sports Medicine, Vol.53(1), pp.61-68
Publisher: B M J Group
Date published: 2019
DOI: 10.1136/bjsports-2018-099408
ISSN: 0306-3674
Copyright note: Copyright © 2018. 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/.
Organisation Unit: Centre for Human Factors and Systems Science; University of the Sunshine Coast, Queensland
Language: English
Record Identifier: 99450900102621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Sport Sciences