探討左截切半競爭風險資料之對比風險模型的迴歸參數估計

Abstract

隨著醫學的進步，長期追蹤研究中描述疾病演化狀態的多狀態資料便廣泛的被討論。部分競爭風險資料便是一種終止事件會使中繼事件設限之多狀態資料。將截切部分競爭風險資料加上人工截切後，以競爭風險資料型態進行討論是較為簡易的分析方法。由於左截切部分競爭風險資料不同於左截切競爭風險資料之收集方式，若將左截切部分競爭風險資料以競爭風險資料型態進行分析，則會因人工截切而捨棄部分觀測資料中的資料訊息，此時若人工截切刪去過多觀測資料的中繼事件訊息，則容易造成參數估計的不穩定。因此本文利用對比風險模式，在假設獨立截切與設限的條件下，分別考慮中繼事件時間與終止事件時間獨立與相依的情況，討論不使用人工截切之對比風險模式的迴歸參數估計方式。藉由模擬評估所提之估計方式與傳統左截切競爭風險資料型態的迴歸參數估計方法在不同觀測比例上的表現。本文亦將所提之參數估計方法應用至大腸直腸癌的實際資料上。

In the development of the medical science, the multi-state data consisting of the course of disease progression are frequently encountered in longitudinal studies. The semicompeting risks data is a type of multi-state data where an intermediate event may be censored by a terminal event. When the terminal event is subject to left truncation, the naive regression analysis for the intermediate event based on the competing risks data in the presence of left truncation, only use part of data and the information of the observed intermediate event may be excluded by artificial truncation which may lead to large efficiency loss. For estimating the regression parameters in the relative risks model of the cause-specific hazard function for the intermediate event, estimation methods using all intermediate event information are developed under the situations of the independent and dependent terminal events respectively. Simulation studies are conducted to compare the performance of the proposed and naive estimators. Finally, we also apply those methods to analyze a colon cancer data set.