Hidden Markov models for the onset and progression of bronchiolitis obliterans syndrome in lung transplant recipients

Abstract

Chronic rejection in lung transplant recipients is monitored by repeated measurement of forced expiratory volume in one second (FEV1). This marker is measured at irregular intervals and is also affected by covariates and short-term fluctuation. This paper describes the use of hidden Markov models for the underlying staged functional decline. Maximum likelihood methods are used to simultaneously estimate disease progression rates and the effects of mismeasurement and covariates.