AIM: Pancreatic cancer is one of the least common tumors, nevertheless it is one of the most lethal. This lethality is mainly due to the fact that the vast majority of patients are diagnosed in an advanced stage. The objective of this work is investigate how different covariates affect the transition to death after a first admission due to pancreatic cancer. METHODS: We analyze the impact of different factors on health related transitions after a first hospital admission related to pancreatic cancer based on a multi state model. RESULTS: Transitions of interest include the transition to death (i.e. survival time), but also the time between a first admission and discharge or between discharge and readmission. We consider comorbidities, the type of admission, and especially the performance of pancreas surgery as covariates with a potential effect on the transition intensities. CONCLUSION: The multi state model allows for a very detailed analysis since all covariate effects may change depending on the current state of the patient. Copyright Â
AIM: Pancreatic cancer is one of the least common tumors, nevertheless it is one of the most lethal. This lethality is mainly due to the fact that the vast majority of patients are diagnosed in an advanced stage. The objective of this work is investigate how different covariates affect the transition to death after a first admission due to pancreatic cancer. METHODS: We analyze the impact of different factors on health related transitions after a first hospital admission related to pancreatic cancer based on a multi state model. RESULTS: Transitions of interest include the transition to death (i.e. survival time), but also the time between a first admission and discharge or between discharge and readmission. We consider comorbidities, the type of admission, and especially the performance of pancreas surgery as covariates with a potential effect on the transition intensities. CONCLUSION: The multi state model allows for a very detailed analysis since all covariate effects may change depending on the current state of the patient. Copyright Â
Authors: Jose F Velez-Serrano; Daniel Velez-Serrano; Valentin Hernandez-Barrera; Rodrigo Jimenez-Garcia; Ana Lopez de Andres; Pilar Carrasco Garrido; Alejandro Álvaro-Meca Journal: PLoS One Date: 2017-06-07 Impact factor: 3.240