Editorial: Estimating Survivorship in the Face of Competing Risks

Wongworawat, Montri D.; Dobbs, Matthew B.; Gebhardt, Mark C.; Gioe, Terence J.; Leopold, Seth S.; Manner, Paul; Rimnac, Clare M.; Porcher, Raphaël

doi:10.1007/s11999-015-4182-4

Cited by 45 publications

(29 citation statements)

References 10 publications

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“…Meier estimator overestimates the probability of events of interest in the presence of competing risks [1,8]. For example, if a study seeks to examine the durability of a particular arthroplasty implant (so the event of interest is revision), and a substantial proportion of the patients die, the Kaplan-Meier approach will overestimate the frequency of revision, since patients who have died cannot subsequently undergo revision.…”

Section: T Is Well Known That the Kaplan-mentioning

confidence: 99%

“…The more frequent the competing events, the more KaplanMeier-based estimates will depart from the true probability of occurrence of the event of interest. In light of this, alternative analytic approaches that account for the occurrence of such competing events have been developed to estimate the cumulative incidence [1,8]. While these issues are mathematically demonstrated and have been illustrated in various medical domains [2,3,6], they have received less attention in orthopaedic research until recently [7,8].…”

Section: T Is Well Known That the Kaplan-mentioning

confidence: 99%

“…In light of this, alternative analytic approaches that account for the occurrence of such competing events have been developed to estimate the cumulative incidence [1,8]. While these issues are mathematically demonstrated and have been illustrated in various medical domains [2,3,6], they have received less attention in orthopaedic research until recently [7,8]. But while some work has been done in individual datasets [8], to my knowledge, no study has taken a broader look at the influence of the phenomenon of competing risks on Kaplan-Meier survivorship estimates across orthopaedics more generally.…”

Section: T Is Well Known That the Kaplan-mentioning

confidence: 99%

“…Going a step further, CORR 1 has announced that it will begin asking authors to consider using cumulative incidence analyses instead of KaplanMeier survivorship estimates in studies where the frequency of competing risks is high enough to matter [8]. Such initiative is also likely to impact both research and practice, and I suspect that such competing risks analyses will become the standard approach in the field, as it has in other domains such as hematology, for instance.…”

Section: Where Do We Need To Go?mentioning

confidence: 99%

See 3 more Smart Citations

CORR Insights®: Kaplan-Meier Survival Analysis Overestimates the Risk of Revision Arthroplasty: A Meta-analysis

Porcher

2015

Clinical Orthopaedics &Amp; Related Research

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Section: T Is Well Known That the Kaplan-mentioning

confidence: 99%

Section: T Is Well Known That the Kaplan-mentioning

confidence: 99%

Section: T Is Well Known That the Kaplan-mentioning

confidence: 99%

Section: Where Do We Need To Go?mentioning

confidence: 99%

See 2 more Smart Citations

CORR Insights®: Kaplan-Meier Survival Analysis Overestimates the Risk of Revision Arthroplasty: A Meta-analysis

Porcher

2015

Clinical Orthopaedics &Amp; Related Research

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“…Although arthroplasty surgeons may still be somewhat unfamiliar with reporting revision rates using the cumulative incidence methodology, its use in both our field and others has been reported for some time [1,3,30]. The cumulative incidence method reports the probability of failure as a result of the event of interest in the presence of competing risks [14].…”

Section: Introductionmentioning

confidence: 99%

What Can We Learn From 20-year Followup Studies of Hip Replacement?

Martin

Callaghan

Gao

et al. 2016

Clinical Orthopaedics &Amp; Related Research

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Background A patient who dies during the followup period of a study about total hip arthroplasty (THA) cannot subsequently undergo a revision. The presence of competing events (such as deaths, in a study on implant durability) violates an assumption of the commonly used Kaplan-Meier (KM) survivorship approach. In that setting, KM-based estimates of revision frequencies will be high relative to alternative approaches that account for competing events such as cumulative incidence methods. However, the degree to which this difference is clinically relevant, and the degree to which it affects different ages of patient cohorts, has been poorly characterized in orthopaedic clinical research. Questions/purposes The purpose of this study was to compare KM with cumulative incidence survivorship estimators to evaluate the degree to which the competing event of death influences the reporting of implant survivorship at long-term followup after THA in patients both younger than and older than 50 years of age. Methods We retrospectively reviewed 758 cemented THAs from a prospectively maintained single-surgeon registry, who were followed for a minimum of 20 years or until death. Revision rates were compared between those younger than or older than age 50 years using both KM and cumulative incidence methods. Patient survivorship was calculated using KM methods. A total of 21% (23 of 109) of the cohort who were younger than 50 years at the time of THA died during the 20-year followup period compared with 72% (467 of 649) who were older than 50 years at the time of surgery (p \ 0.001). Results In the cumulative incidence analysis, 19% of the younger than age 50 years cohort underwent a revision for aseptic causes within 20 years as compared with 5% in the older than age 50 years cohort (p \ 0.001). The KM method overestimated the risk of revision (23% versus 8.3%, p \ 0.001), which represents a 21% and 66% relative increase for the younger than/older than age 50 years groups, respectively. Conclusions The KM method overestimated the risk of revision compared with the cumulative incidence method, and the difference was particularly notable in the elderly cohort. Future long-term followup studies on elderly cohorts should report results using survivorship curves that take into account the competing risk of patient death. We

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