2020
DOI: 10.1016/j.jclinepi.2020.03.004
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Ignoring competing events in the analysis of survival data may lead to biased results: a nonmathematical illustration of competing risk analysis

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Cited by 109 publications
(106 citation statements)
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“…We considered statistically significant difference if p value is equal or less than 0.050. Then, assuming that death has to be considered an event that precludes the occurrence of our event of interest, that is diagnosis of dementia, we performed competing risk models, with death as a competitive event [ 17 – 19 ]. Considering the prediction nature of our main research aim, we fitted univariable Fine and Gray’s semiparametric proportional sub-distribution hazards models to obtain sub-hazard ratios (SHRs), with 95% CI, representing the effect of each risk factor on the cumulative incidence function (CIF) of dementia and death in a competing risk situation [ 20 – 22 ].…”
Section: Methodsmentioning
confidence: 99%
“…We considered statistically significant difference if p value is equal or less than 0.050. Then, assuming that death has to be considered an event that precludes the occurrence of our event of interest, that is diagnosis of dementia, we performed competing risk models, with death as a competitive event [ 17 – 19 ]. Considering the prediction nature of our main research aim, we fitted univariable Fine and Gray’s semiparametric proportional sub-distribution hazards models to obtain sub-hazard ratios (SHRs), with 95% CI, representing the effect of each risk factor on the cumulative incidence function (CIF) of dementia and death in a competing risk situation [ 20 – 22 ].…”
Section: Methodsmentioning
confidence: 99%
“…At the end of followup, 13 patients (19.4%) were alive and disease-free, 20 patients (29.9%) were alive with a new RCC recurrence, 23 patients (34.3%) died of disease, and 11 patients (16.4%) died of other causes. Because the absolute percentage of deaths from other causes was in excess of 10%, the adoption of a competing risk model was justified (20).…”
Section: Recurrence and Survival Analysismentioning
confidence: 99%
“…The subdistribution hazard ratio (SHR) for assessing the risk of developing dementia for an individual factor was calculated using the cmprsk library in the R package, which allows adjustment for socio-demographic and clinical variables. The SHR is a way of expressing the instantaneous risk of developing a given event in an individual who has not yet experienced such an event (at risk), when taking into account a competing risk, such as death [40]. A higher SHR would mean a higher risk of developing AD for this factor, taking into account death as a competing risk.…”
Section: Discussionmentioning
confidence: 99%