Journal of School of Public Health and

  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.

Background and Aim: Gastric cancer is one the most common gastrointestinal tract cancers in Iran, with East-Azerbaijan Province ranking second in the country. The objectives of this research were to determine the feasibility of using cure models in survival analysis and factors affecting short-term and long-term patient survival rates using the mixture cure cox model.

Materials and Methods: We used the available information on 184 patients diagnosed with gastric cancer in East-Azerbaijan Province cities referring to medical centers during the period 2009-2010 and followed up for 5 years.

Results: The median of survival time was 8.33 months (95% CI = 5.9-10.6). Fitting the univariate and final cox cure models showed that in the short-term survival the effect of the chemotherapy factor was statistically significant (Hazard ratio =0.49, 95% CI = 0.34, 0.69, p-value <0.001).

Conclusion: If the population under study consists of two groups of susceptible and non-susceptible individuals for the intended incident, the mixture cure models can be used for the discrete analysis of long-term and short-term survival of patients diagnosed with gastric cancer and identification of variables affecting the two survival rates.

Background and Aim: Breast cancer is one of the most prevalent cancers in women and is the second cause of mortality due to cancer in women, with lung cancer being the first.

Materials and Methods: In this study we followed all the cases for 5 years, patients from West-Azerbaijan and East-Azerbaijan Provinces that diagnosed with breast cancer in 2009 and 2010 that attended to health cares. Using multivariate cure cox model for the influence of variables in this study.

Results: In this study 171 cases which suffering from breast cancer had the mean age of 55.9 ± 12.9 and the range of 23 to 89 years, in time of cancer diagnosis. Mean of patients follow-up was 51.7± 23.4 months with range of 11 days to 78 months. Overalls 52 death occurred and patient survival rate of 5 years was estimated 60. 6 percent. Eventually the two variables which are economic status and emergency hospitalization were found the two factors of pre-warning in long term survival of patient suffering from breast cancer.

Conclusion: Due to the findings, it seems using cure model in patients suffering from breast cancer was better than classical survival models.