Concussion Risk Between Individual Football Players: Survival Analysis of Recurrent Events and Non-events

Steven Rowson*, Eamon T. Campolettano, Stefan M. Duma, Brian Stemper, Alok Shah, Jaroslaw Harezlak, Larry Riggen, Jason P. Mihalik, Alison Brooks, Kenneth L. Cameron, Steven J. Svoboda, Megan N. Houston, Thomas McAllister, Steven Broglio, Michael McCrea

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Concussion tolerance and head impact exposure are highly variable among football players. Recent findings highlight that head impact data analyses need to be performed at the subject level. In this paper, we describe a method of characterizing concussion risk between individuals using a new survival analysis technique developed with real-world head impact data in mind. Our approach addresses the limitations and challenges seen in previous risk analyses of football head impact data. Specifically, this demonstrative analysis appropriately models risk for a combination of left-censored recurrent events (concussions) and right-censored recurrent non-events (head impacts without concussion). Furthermore, the analysis accounts for uneven impact sampling between players. In brief, we propose using the Consistent Threshold method to develop subject-specific risk curves and then determine average risk point estimates between subjects at injurious magnitude values. We describe an approach for selecting an optimal cumulative distribution function to model risk between subjects by minimizing injury prediction error. We illustrate that small differences in distribution fit can result in large predictive errors.

Original languageEnglish
Pages (from-to)2626-2638
Number of pages13
JournalAnnals of Biomedical Engineering
Issue number11
StatePublished - Nov 2020
Externally publishedYes


  • Angular
  • Biomechanics
  • Injury
  • NCAA-DOD CARE Consortium
  • Risk function
  • Rotational
  • Sensors


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