Determining the Survival Rate in Children with ALL in the Northeast of Iran via Competing Risks Approach

• Main Authors: Anahita Saeedi, Ahmadreza Baghestani, Hossein Bonakchi, Abbas Khosravi, Hamid Farhangi, Zahra Badiei, Ali Ghasemi, Abdollah Banihashem, Maryam Forouzannejhad
• Format: Article
• Language: English
• Published: Shiraz University of Medical Sciences 2020-07-01
• Series: Middle East Journal of Cancer
• Subjects: survival analysis; acute lymphoblastic leukemia; parametric competing risks model; cumulative incidence probability
• Online Access: https://mejc.sums.ac.ir/article_46726.html

Background: We designed this study to assess the significant prognostic factors of both recurrence and death in patients with acute lymphoblastic leukemia in a university-based hospital using a parametric competing risks model. Methods: In this retrospective study, we included 417 patients with acute lymphoblastic leukemia. Staining of bone marrow smears with Giemsa method confirmed the diagnosis, justifying at least 25% lymphoblast. Treatment of patients was based on the Berlin-Frankfurt-Münster (BFM) protocol. We considered the first recurrence of cancer as the event of interest and non-relapse mortality as a competing risk. The employed two-parameter Weibull model accounted for both the interest and the competing events. Results: The relapse-free survival and the five-year overall mortality rates of patients were 85.9% and 74%, respectively. The majority of the patients (72.7%) did not experience any event during the study period. We explained these events as first recurrence and non-relapse mortality, which occurred in 44 (10.6%) and 70 (16.8%) of the patients in the given order. The cumulative incident probability of the first recurrence and non-relapse mortality, were 13.43% and 18.61%, respectively. Conclusion: Based on the model, we identified white blood cell count and central nervous system involvement as important prognostic factors in determining the incidence rate. Therefore, they must be considered in the selection of treatment plan and risk stratification.