Ali Zare, Mahmood Mahmoodi, Kazem Mohammad, Hojjat Zeraati, Mostafa Hosseini, Kourosh Holakouie Naieni
Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences, Tehran, Iran E-mail :
Asian Pac J Cancer Prev. 2014;15(1):441-7. doi: 10.7314/apjcp.2014.15.1.441.
Multi-state models are appropriate for cancer studies such as gastrectomy which have high mortality statistics. These models can be used to better describe the natural disease process. But reaching that goal requires making assumptions like Markov and homogeneity with time. The present study aims to investigate these hypotheses.
Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. To assess Markov assumption and time homogeneity in modeling transition rates among states of multi-state model, Cox-Snell residuals, Akaikie information criteria and Schoenfeld residuals were used, respectively.
The assessment of Markov assumption based on Cox-Snell residuals and Akaikie information criterion showed that Markov assumption was not held just for transition rate of relapse (state 1-state 2) and for other transition rates - death hazard without relapse (state 1-state 3) and death hazard with relapse (state 2-state 3) - this assumption could also be made. Moreover, the assessment of time homogeneity assumption based on Schoenfeld residuals revealed that this assumption - regarding the general test and each of the variables in the model - was held just for relapse (state 1-state 2) and death hazard with a relapse (state 2-state 3).
Most researchers take account of assumptions such as Markov and time homogeneity in modeling transition rates. These assumptions can make the multi-state model simpler but if these assumptions are not made, they will lead to incorrect inferences and improper fitting.
多状态模型适用于胃癌切除术等死亡率统计较高的癌症研究。这些模型可用于更好地描述疾病的自然进程。但要实现这一目标，需要做出马尔可夫和时间齐性等假设。本研究旨在探讨这些假设。
分析了1995年至1999年在伊朗癌症研究所接受手术的330例胃癌患者的数据。为了评估多状态模型各状态间转移率建模中的马尔可夫假设和时间齐性，分别使用了Cox-Snell残差、赤池信息准则和Schoenfeld残差。
基于Cox-Snell残差和赤池信息准则对马尔可夫假设的评估表明，马尔可夫假设仅在复发转移率（状态1-状态2）方面不成立，而对于其他转移率——无复发死亡风险（状态1-状态3）和复发死亡风险（状态2-状态3）——该假设也成立。此外，基于Schoenfeld残差对时间齐性假设的评估显示，该假设——关于总体检验和模型中的每个变量——仅在复发（状态1-状态2）和复发死亡风险（状态2-状态3）方面成立。
大多数研究人员在对转移率进行建模时会考虑马尔可夫和时间齐性等假设。这些假设可以使多状态模型更简单，但如果不做这些假设，将导致错误的推断和不恰当的拟合。
