Abstract
In the field of cardio-thoracic surgery, valve function is monitored over time after surgery. The motivation for our research comes from a study which includes patients who received a human tissue valve in the aortic position. These patients are followed prospectively over time by standardized echocardiographic assessment of valve function. Loss of follow-up could be caused by valve intervention or the death of the patient. One of the main characteristics of the human valve is that its durability is limited. Therefore, it is of interest to obtain a prognostic model in order for the physicians to scan trends in valve function over time and plan their next intervention, accounting for the characteristics of the data. Several authors have focused on deriving predictions under the standard joint modeling of longitudinal and survival data framework that assumes a constant effect for the coefficient that links the longitudinal and survival outcomes. However, in our case, this may be a restrictive assumption. Since the valve degenerates, the association between the biomarker with survival may change over time. To improve dynamic predictions, we propose a Bayesian joint model that allows a time-varying coefficient to link the longitudinal and the survival processes, using P-splines. We evaluate the performance of the model in terms of discrimination and calibration, while accounting for censoring.
Highlights
In the field of cardio-thoracic surgery, valve function is monitored periodically over time after heart valve surgery
To further facilitate improving the derived predictions from the joint model, we model the baseline hazard with the same P-splines approach
To assess the predictive performance of the varying-coefficient joint model (VCJM) and to compare it to the coefficient joint model (CCJM), we focus on discrimination and calibration
Summary
In the field of cardio-thoracic surgery, valve function is monitored periodically over time after heart valve surgery. Aortic gradient (AG) (mmHg) is one of the continuous echocardiographic markers that measures valve (dys)function, where high values indicate a worsening of the patient’s condition. It measures aortic stenosis which occurs when the opening of the aortic valve located between the left ventricle of the heart and the aorta is narrowed. During the follow-up period after surgery, patients may require an intervention or may die. In total 296 patients who survived aortic valve or root replacement with an allograft valve were followed over time. It is important for the physicians to have a prognostic tool in order to carefully monitor trends in valve function over time and plan a future re-intervention
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