Iranian Journal of

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Background and Objectives: 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.

Methods: 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.

Results: 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<0.01).Also, according to the estimated coefficients from both methods,there was a little difference between them.

Conclusion: 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.

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Background and Objectives: In many medical situations, people can experience recurrent events with a terminal event. If the terminal event is considered a censor in this type of data, the assumption of independence in the analysis of survival data may be violated. This study was conducted to investigate joint modeling of frequent events and a final event (death) in breast cancer patients using a frailty model.
 
Methods: In this retrospective cohort study, 443 patients with breast cancer registered at the Hospital of Shohadaye Tajrish Cancer Research Center were studied. The model of Liu (2004) was applied for joint modeling of recurrent events and a terminal event in which a shared frailty with gamma-distribution was used. Data modeling and data analysis were done using the R software.
 
Results: Four hundred and forty three women with breast cancer were studied. Univariate and multivariate analysis were performed in these patients. Of these, 338 cases (76.3%) had recurrence events, and 105 (23.7%) were censored. The obtained results of joint frailty model indicated that the relative risk of relapse in patients with a positive first-degree family history was 36% higher than that of other people (P<0.05). The relative risk of relapse in patients with stage 3 disease was 19% more than other stages and also the relative risk of relapse in patients with chemotherapy was 2.5 times higher than those without chemotherapy.
 
Conclusion: In this study, the presented model, in addition to simultaneous modeling capability of the event, could help prevent a higher prevalence of the terminal event (death) and thus reduce the adverse effects of reversible diseases.