Competing Risks and Analysis of Patients with Brain Stroke: Cumulative Incidence Function and Cause-Specific Hazard Approach

Abstract

Introduction: In the presence of competing risks, patients with brain stroke (BS) experience death by various causes, such as diabetes, and heart disease, and other causes in the follow-up. This study aimed to model the survival in patients with BS in the presence of these competing risk of death using cumulative incidence function (CIF) and cause-specific hazard (CSH) models. Methods: In the study, 332 patients with the definitive diagnosis of BS were followed up for 10 years, and their mortality status due to BS or other causes was evaluated. In addition, significance tests and parameters were estimated by using STATA 14 software by considering the CIF and CSH model. Results: The median follow-up time was 20.68 months for patients who died due to BS and 68.50 months for patients who died due to other causes. In the CIF model, Sex [BS: cumulative incidence hazard ratio (SHR) = 2.35, 90% confidence interval (CI) = (1.76-3.14)], Employment status [BS: 2.04(1.50-2.75)], History of blood pressure[BS: 1.64(1.25-2.14)], Heart disease[BS: 1.47(1.13-1.94)], Cerebrovascular accident type[BS: 0.77(0.69-0.87)]; age [Other case: 59-68 years, 2.61 (1.13-6.06) and ≥76 years: 3.03 (1.32-6.92)] were directly related to hazard of death. The CSH model resulted in similar estimates except for age [BS: 69-75 years; 1.31(1.18-1.45), ≥76 years; 1.37(1.23-1.53); other case: age 59-68 years 1.91 (1.22-2.99) and 69-75 years; 1.89 (1.21-2.96) and ≥76 years: 2.14 (1.36-3.37)], Sex[BS: 1.38(1.07-1.79)], History of blood pressure [BS: 1.57(1.20-2.05)], Heart disease [BS:1.44(1.09-1.91)] were directly related to hazard of death. Conclusion: The estimation of CIF analysis, along with CSH one for the competing risks, is suggested to provide more precise information about patients’ status in order to support adopted clinical decisions when aiming at assessing health related to a specific cause economically and determining the probability of occurring an intended event among other causes.