• Ozge Pasin, Ahmet Dirican, Handan Ankarali, Rian Disci, and Hasan Karanlik.
• Department of Biostatistics, Faculty of Medicine, Istanbul University, Istanbul, Turkey. E-mail. ozgepasin90@yahoo.com.tr.
• Saudi Med J. 2020 May 1; 41 (5): 491-498.

ObjectivesTo investigate the effects of risk factors on recurrence and death in breast cancer patients, taking into account the dependence between recurrence and death as well as the heterogeneity among individuals. The other aim of this study was to make predictions of death risks with a dynamic model that includes patient's history and different horizons. Methods: The data of 465 patients who had undergone surgery at the Istanbul University Oncology Institute,  Istanbul, Turkey, between 2009 and 2016 were used. For data analysis in this retrospective study, the authors applied the joint frailty model, and the predictions were obtained using dynamic prediction methods that consider the patient's history. The Brier score was used to evaluate the accuracy of the estimations.ResultsA positive relationship was found between recurrence and death, and heterogeneity was found among patients (p less than 0.001, p=1.008, p=2.945). The effects of Cerb-B2, tumor type, remaining lymph nodes, neoadjuvant chemotherapy, and surgery type were statistically significant for death and recurrence (p less than 0.05, relative risk [death, recurrence] = [2.5, 11.86], [2.065, 2.798], [1.852, 3.113], [4.211, 9.366], [1.521,1.991]). The Brier score values used in the evaluation of the predictions obtained by the dynamic prediction methods were found to be below 0.30. Conclusion: The use of joint frailty models is recommended for the detection of heterogeneity effects and dependence between recurrence and death. Through models in survival analysis, researchers can obtain more accurate parameter estimates. A significant variance of frailty indicates different death risks for the same characteristics.

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