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Prediction of multiple recurrent events: A comparison of extended cox models in bladder cancer

American Journal of Epidemiology Aug 10, 2017

Smedinga H, et al. – The physicians conducted this work to determine the utility of extensions of the Cox proportional hazards model for repeated events in this context. They targeted on gap time in the detailed analyses, allowing for clinically meaningful predictions. Moreover, variance–correction models may be feasible whether predictor selection is part of the model development. In addition, frailty models may be feasible when within–subject correlation is strong.

Methods
  • Physicians examined 531 Dutch patients with bladder cancer (1990–2012) with information on 7 prespecified predictors at the time of diagnosis of the primary and recurrent tumors.
  • In this study, 3 aspects of model variants were considered: how to model time to the repeated events (calendar time, gap time, elapsed time); the number of preceding events (predictor, stratum variable); and the within–subject correlation (ignored in a simple Cox model, robust standard errors in a variance–correction model, random effect in a frailty model).

Results
  • They exhibited evidence that first to fourth recurrences of bladder cancer occurred in 313, 174, 103, and 66 patients, respectively, with median calendar follow–up times of 1.1, 2.5, 3.8, and 4.5 years, respectively.
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