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A common question in sports injury research is ‘what proportion of athletes sustained an injury over a certain time period?’. In cross-sectional studies, where data are collected at a single point in time, the prevalence proportion is simply the number of injured athletes divided by the total sample. In prospective cohort studies, caution is needed as the injury incidence proportion (proportion of newly injured athletes during the observation period) is likely to be underestimated by simply using the approach that is valid for cross-sectional studies. As a part of the BJSM methods matter series,1 we here compare the analytical approaches for cross-sectional studies and prospective cohort studies (ie, without censoring and with censoring, respectively) to help the reader accurately estimate incidence proportion in prospective studies.
Cumulative incidence proportion (CIP)
To describe the proportion of sports injuries occurring over a given time period, one can calculate the CIP. The CIP can be calculated with or without censoring (in this paper, we discuss the concept of ‘right censoring’, but use the term ‘censoring’ only). For instance, the number of injured runners in a 1-year prospective cohort study was 252 of 931.2 Hence, the CIP calculated without censoring is 27% …
Contributors JJ drafted the editorial, while the remaining co-authors revised it for important intellectual content.
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 for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.