Journal of School of Public Health and

---

Background and Aim: Many researchers have studied survival (time to death) of gastric cancer patients. Although gastric cancer diagnosed in early stages can be cured by surgery, chance of relapse still exists after operation. Hence, we should consider both events, that is, relapse of the disease and death, in order to be able to make a more precise estimation for survival of the patients. The purpose of this study was to use the competing risks method to estimate the cumulative incidence functions (CIF) of the relapse of disease and death and consequently to estimate the postoperative disease-free survival.
Materials and Methods: A total of 330 patients admitted to Iran Cancer Institute and operated between March 1995 and March 1999 were enrolled in the study. They were followed up for at least 5 years to estimate their 5-year disease-free survival. Information on their demographic, clinical, and therapeutic characteristics, as well as on the type and time of occurrence of the first event (relapse of disease or death) after surgery was collected from their medical records. The direct parametric method was applied to estimate CIFs of relapse of the disease and death, while to adjust the effects of some covariates the parametric regression model was used. Data analysis was done using the R software and a p-value <0.05 was considered statistically significant. The findings were compared with the results obtained on the basis of data analysis in which the competing events were not considered.
Results: The median follow-up time was 37.9 months. Of all the patients 13% experienced relapse and 60.9% death as the first event after surgery. The CIFs of relapse of disease and death 5 years after operation, with due consideration of covariates, were estimated at 11.0% and 68.6%, respectively. Age, stage of disease, and complementary treatment were statistically associated with the CIF of death, while only complementary treatment was related to the CIF of relapse. Older patients and those in more advanced stages of disease were more likely to die after operation. Moreover, while complementary treatment after operation decreased the CIF of relapse of disease, it increased the CIF of death. The disease-free survival of patients 5 years after surgery was 20.(consideringtheeffectsofsomecovariates).
Conclusion: The competing risks method is recommended for analyzing survival data because of its capability in considering different events and, therefore, making it possible to make more precise estimations. By using this method, considering smaller variance estimates for model parameters and also narrow confidence intervals for the cumulative incidence functions of competing events, it is expected to obtain more precise results. Unfortunately, the results have revealed that the disease-free survival of gastric cancer patients is low in Iran.

---

  Background and Aim: In many diagnostic studies, including surveying the survival of patients with gastric cancer where each individual after surgery can experience more than one type of event, and the occurrence of one type of event hinders the occurrence of other types of events, the question of competing risk is raised. For checking the effect of each covariate on the occurrence of any event and estimating the hazard function, Cox and Fine and Gray models are used. In the event that the assumptions of two models do not hold, using them will be an incorrect course of action. One way to overcome this problem is to use models that have higher flexibility.

  Materials and Methods: In this study, the demographic, clinical and therapeutic characteristics of 330 patients with gastric cancer who referred from January 1996 to April 2000 to the Cancer Institute of Iran Imam Khomeini Hospital and underwent surgery, including their type, and the time of occurrence of the first event (locoreginal replace/death) for each patient from medical records were collected and evaluated. Using this information, the cumulative hazard function of relapse of disease was plotted by means of three models Cox, Fine and Gray and the flexible one, and was checked against the observed cumulative incidence function of recurrence of disease and, finally, their performance was evaluated.

  Results: Nearly, for each event, the proportionality assumption holds for all the variables . According to the graph of cumulative incidence function for the event of interest (recurrence), it can be seen that the Cox model, has overestimated the cumulative incidence function and the curves of two other models are very similar and also similar to the observed curve. However, the cumulative incidence function of the flexible model is smoother than the others.

  Conclusion: In the competing risk framework, Cox model is not very useful in practice while it seems that the flexible model is not only a good alternative to the Fine and Gray model but will also be superior to it when the assumption of proportionality does not hold.