In a competing risks analysis, interest lies in the cause-specific cumulative incidence function (CIF) which is usually obtained in a modelling framework by either (1) transforming on all of the cause-specific hazard (CSH) or (2) through its direct relationship with the subdistribution hazard (SDH) function. We expand on current competing risks methodology from within the flexible parametric survival modelling framework (FPM) and focus on approach (2). This models all cause-specific CIFs simultaneously and is more useful when prognostic related questions are to be answered. We propose the direct FPM approach for the cause-specific CIF which models the (log-cumulative) baseline hazard without the requirement of numerical integration leading to benefits in computational time. It is also easy to make out-of-sample predictions to estimate more useful measures and alternative link functions can be incorporated, for example, the logit link. To implement the methods, a new estimation command, stpm2cr, is introduced and useful predictions from the model are demonstrated through an illustrative Melanoma dataset.

中文翻译：

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stpm2cr：一种灵活的参数竞争风险模型，使用直接似然法来计算特定原因的累积发生率函数。


在竞争风险分析中，兴趣在于特定原因累积发生率函数 (CIF)，该函数通常在建模框架中通过 (1) 对所有特定原因危害 (CSH) 进行转换或 (2) 通过其与次分布风险 (SDH) 函数有直接关系。我们在灵活的参数生存建模框架 (FPM) 中扩展了当前的竞争风险方法，并重点关注方法 (2)。该模型同时对所有特定原因的 CIF 进行建模，并且在回答与预后相关的问题时更有用。我们提出针对特定原因 CIF 的直接 FPM 方法，该方法对（对数累积）基线危险进行建模，无需数值积分，从而节省了计算时间。进行样本外预测以估计更有用的度量也很容易，并且可以合并替代链接函数，例如 logit 链接。为了实现这些方法，引入了新的估计命令 stpm2cr，并通过说明性黑色素瘤数据集演示了模型的有用预测。