The illness-death model is the simplest multistate model where the transition from the initial state 0 to the absorbing state 2 may involve an intermediate state 1 (e.g., disease relapse). The impact of the transition into state 1 on the subsequent transition hazard to state 2 enables insight to be gained into the disease evolution. The standard approach of analysis is modeling the transition hazards from 0 to 2 and from 1 to 2, including time to illness as a time-varying covariate and measuring time from origin even after transition into state 1. The hazard from 1 to 2 can be also modeled separately using only patients in state 1, measuring time from illness and including time to illness as a fixed covariate. A recently proposed approach is a model where time after the transition into state 1 is measured in both scales and time to illness is included as a time-varying covariate. Another possibility is a model where time after transition into state 1 is measured only from illness and time to illness is included as a fixed covariate. Through theoretical reasoning and simulation protocols, we discuss the use of these models and we develop a practical strategy aiming to (a) validate the properties of the illness-death process, (b) estimate the impact of time to illness on the hazard from state 1 to 2, and (c) quantify the impact that the transition into state 1 has on the hazard of the absorbing state. The strategy is also applied to a literature dataset on diabetes.

Tassistro, E., Bernasconi, D., Rebora, P., Valsecchi, M., Antolini, L. (2020). Modeling the hazard of transition into the absorbing state in the illness-death model. BIOMETRICAL JOURNAL, 62(3 Special Issue: Statistical Models for Complex Data in Clinical and Epidemiological Research May 2020), 836-851 [10.1002/bimj.201800267].

Modeling the hazard of transition into the absorbing state in the illness-death model

Tassistro, E;Bernasconi, DP
;
Rebora, P;Valsecchi, MG;Antolini, L
2020

Abstract

The illness-death model is the simplest multistate model where the transition from the initial state 0 to the absorbing state 2 may involve an intermediate state 1 (e.g., disease relapse). The impact of the transition into state 1 on the subsequent transition hazard to state 2 enables insight to be gained into the disease evolution. The standard approach of analysis is modeling the transition hazards from 0 to 2 and from 1 to 2, including time to illness as a time-varying covariate and measuring time from origin even after transition into state 1. The hazard from 1 to 2 can be also modeled separately using only patients in state 1, measuring time from illness and including time to illness as a fixed covariate. A recently proposed approach is a model where time after the transition into state 1 is measured in both scales and time to illness is included as a time-varying covariate. Another possibility is a model where time after transition into state 1 is measured only from illness and time to illness is included as a fixed covariate. Through theoretical reasoning and simulation protocols, we discuss the use of these models and we develop a practical strategy aiming to (a) validate the properties of the illness-death process, (b) estimate the impact of time to illness on the hazard from state 1 to 2, and (c) quantify the impact that the transition into state 1 has on the hazard of the absorbing state. The strategy is also applied to a literature dataset on diabetes.
Articolo in rivista - Articolo scientifico
illness-death; Markov model; survival; time scales; transition hazard
English
12-set-2019
2020
62
3 Special Issue: Statistical Models for Complex Data in Clinical and Epidemiological Research May 2020
836
851
reserved
Tassistro, E., Bernasconi, D., Rebora, P., Valsecchi, M., Antolini, L. (2020). Modeling the hazard of transition into the absorbing state in the illness-death model. BIOMETRICAL JOURNAL, 62(3 Special Issue: Statistical Models for Complex Data in Clinical and Epidemiological Research May 2020), 836-851 [10.1002/bimj.201800267].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/254155
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