Use of Smoothing Methods for Estimating the Coefficients of Time Dependent Rate Models in Survival Analysis and its Application in Psoriasis Disease

In studies in which each person may experience an event at different times, they are recurrent events.One of the most popular approaches in analyzing recurrent event is obtaining an estimate of the means/rate of events at different times. In this context,one of the things that could help to better understand the effect of this factor on the response is determining the variability due to quantitative variables in the rate of events over time. In this study,we applied kernel and B-spline methods to estimate coefficients in the time dependent-coefficients rate model and showed its application in data of psoriasis.
In this study,data of patients with psoriasis who had a relapse leading to hospitalization in the Dermatology Department of Imam Khomeini Hospital,between 2005 and June 2013 were used. To investigate the relapse rate during these years,time-dependent coefficients rate model was used and the variability of these effects was assessed using the Wald test. Both b-Spline and kernel methods were used for estimating time varying coefficients in the time-dependent rate model.Finally,the results of the methods were compared based on estimates obtained.
The results of this study showed that according to Wald test,the effect of the variables such as the season on the occurrence of psoriasis was significantly different (P-value When the effect of a variable on the occurrence of the events is different at different time, then time-dependent coefficients rate model may provide a better estimate of the effect of variable on response.