Assessing Markov and Time Homogeneity Assumptions in Multi-state Models: Application in Patients with Gastric Cancer Undergoing Surgery in the Iran Cancer Institute

Zare, Ali; Mahmoodi, Mahmood; Mohammad, Kazem; Zeraati, Hojjat; Hosseini, Mostafa; Naieni, Kourosh Holakouie

추천

검색

자료유형: 학술저널

저자정보: Zare, Ali (Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences) Mahmoodi, Mahmood (Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences) Mohammad, Kazem (Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences) Zeraati, Hojjat (Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences) Hosseini, Mostafa (Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences) Naieni, Kourosh Holakouie (Department of Epidemiology and Biostatistics, Tehran University of Medical Sciences)

저널정보: 아시아태평양암예방학회 Asian Pacific journal of cancer prevention : APJCP Asian Pacific journal of cancer prevention : APJCP 제15권 제1호

발행연도: 2014.1

수록면: 441 - 447 (7page)

이용수

📌

연구주제

📖

연구배경

🔬

연구방법

🏆

연구결과

초록· 키워드

오류제보하기

Background: 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. Materials and Methods: 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. Results: 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 ${\rightarrow}$ state 2) and for other transition rates - death hazard without relapse (state 1 ${\rightarrow}$ state 3) and death hazard with relapse (state 2 ${\rightarrow}$ 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 ${\rightarrow}$ state 2) and death hazard with a relapse (state 2 ${\rightarrow}$ state 3). Conclusions: 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.

#Akaikie information criterion #Cox-Snell and Schoenfeld residuals #gastric cancer #multi-state model

참고문헌 (0)

참고문헌 신청

참고문헌이 DBpia에서 서비스 중이라면, [참고문헌 신청]을 통해 등록해보세요

이 논문의 저자 정보

Zare, Ali

소속기관 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical