Competing risks occur frequently in the analysis of survival data. A competing risk is an event whose occurrence precludes the occurrence of the primary event of interest. In a study examining time to death attributable to cardiovascular causes, death attributable to noncardiovascular causes is a competing risk. When estimating the crude incidence of outcomes, analysts should use the cumulative...

OBJECTIVES The Kaplan-Meier estimation is widely used in orthopedics to calculate the probability of revision surgery. Using data from a long-term follow-up study, we aimed to assess the amount of bias introduced by the Kaplan-Meier estimator in a competing risk setting. METHODS We describe both the Kaplan-Meier estimator and the competing risk model, and explain why the competing risk model ...

Interest in survival analysis is to look and capture the information about the occurrence of events, i.e., death. In human life different types of events may happen at the same time. Sometimes, few events completely interrupt or make subtle changes on the occurrence of an event of interest. The method to capture information about the specific event of interest along with other events is known a...

Background: Value of neoadjuvant chemotherapy (NACT) is still controversial in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). Based on competing risk analysis model, we aim at evaluating the efficacy of NACT in decreasing cancer-specific mortality for LA-NPC (except T3-4N0) treated by intensity-modulated radiotherapy (IMRT). Methods: Data on 957 patients with LA-NPC were retrospecti...

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BACKGROUND Different definitions and estimates of overdiagnosis in mammographic screening reflect a substantial need to investigate and understand the complexity of the issue. This modeling study aims to estimate the number of overdiagnosed women, defined as those diagnosed with breast cancer who die from any cause within the lead-time period. METHODS We used numbers from incidence and death ...

Competing Risk (CR) event is one that a patient may experience (other than the event of interest) which can prevent the event of interest from occurring. A naive use of classical survival analysis methods in the presence of CR leads to a bias by overestimating the probability of disease incidence. Hence it is important to account for CR events when estimating disease incidence. This can be done...

Article history: Received 19 December 2016 Accepted 21 December 2016 Available online 23 December 2016 rarely detected early, and the prognosis remains poor (Pourhoseingholi et al., 2009) and recent study indicated association between MetS and increasing risk of gastric adenocarcinoma (Lin et al., 2015). The main finding of Hu and colleagues is an important issue, not only for clinicians who ar...

This paper generalizes existing econometric models for censored competing risks by introducing a new flexible specification based on a piecewise linear baseline hazard, time-varying regressors, and unobserved individual heterogeneity distributed as an infinite mixture of Generalized Inverse Gaussian (GIG) densities, nesting the gamma kernel as a special case. A common correlated latent time eff...

Objectives Methods accounting for competing risks in time-to-event problems are becoming common in mainstream statistical analyses. Standard approaches include those based on log-rank type tests [1] and cumulative incidence regression [2]. These approaches are based on weighting competing events by the censoring distribution. The usual cumulative incidence regression uses weights based on the p...