Smedinga Hilde, Steyerberg Ewout W, Beukers Willemien, van Klaveren David, Zwarthoff Ellen C, Vergouwe Yvonne
Am J Epidemiol. 2017 Sep 1;186(5):612-623. doi: 10.1093/aje/kwx133.
Recurrence of bladder cancer can occur repeatedly in the same patient after treatment of the primary tumor. Models predicting the risk of a next recurrence may inform individualized decision-making on surveillance frequency. We aimed to assess the usefulness of extensions of the Cox proportional hazards model for repeated events in this context. We analyzed 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. We considered 3 aspects of model variants: 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). 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. We focused on gap time in the detailed analyses, allowing for clinically meaningful predictions. Variance-correction models may be useful if predictor selection is part of the model development. Frailty models may be useful when within-subject correlation is strong.
原发性肿瘤治疗后，膀胱癌复发可在同一患者中反复发生。预测下一次复发风险的模型可为监测频率的个体化决策提供依据。我们旨在评估在这种情况下Cox比例风险模型扩展用于重复事件的有效性。我们分析了531例荷兰膀胱癌患者（1990 - 2012年），这些患者在原发性肿瘤和复发性肿瘤诊断时具有7个预先指定预测因素的信息。我们考虑了模型变体的3个方面：如何对重复事件的时间进行建模（日历时间、间隔时间、经过时间）；先前事件的数量（预测因素、分层变量）；以及个体内相关性（简单Cox模型中忽略，方差校正模型中使用稳健标准误，脆弱模型中使用随机效应）。膀胱癌的首次至第四次复发分别发生在313、174、103和66例患者中，日历随访时间中位数分别为1.1、2.5、3.8和4.5年。在详细分析中，我们重点关注间隔时间，以便进行具有临床意义的预测。如果预测因素选择是模型开发的一部分，方差校正模型可能有用。当个体内相关性较强时，脆弱模型可能有用。
