Bayesian Parametric Survival Analysis of Patients With Non-Hodgkin’s Lymphoma in Yazd, Iran, During 2009-2019 - Hossein Fallahzadeh; Seyed Mohammad Reza Mortazavizadeh; Mahdieh Momayyezi; Shokouh Fouladvand (Epidemiology and Health System Journal)
Background and aims: Non-Hodgkin’s lymphoma (NHL) is one of two main types of lymphoma. This present study aimed to investigate the survival rate in patients with NHL. Methods: This analytical survival-type study examined 372 patients with NHL referred to Shahid Sadoughi Hospital in Yazd in 2009-2019. The data were extracted from patients’ files. STATA/17 software, the Kaplan-Meier method, and Bayesian parametric survival analysis were used for data analysis. Results: The overall survival rate and the mean overall survival time were 65% and 129±17.94 months, respectively. According to the Kaplan-Meier method, the survival rates of 1, 2, 3, 5, and 10 years were 86%, 80%, 76%, 69.5%, and 52%. The results revealed that men, people over 70 years old, patients with the NHL.T-cell subtype, patients with involvement in the chest, inguinal, and abdominal-pelvic regions, and patients in stage III or IV of the disease had a shorter survival time. In addition, survival time was shorter in patients with disease recurrence at the primary site. The variables of gender (hazard ratio [HR]=0.65; 95% confidence interval [CI]: 0.44‒0.93), type of treatment (HR=3.43; 95% CI: 1.58‒6.16), stage of disease (HR=2.87; 95% CI: 2.09‒3.57), and involvement site (HR=1.45:95%; CI: 1.03‒1.99) had a significant effect on survival time using the Bayesian parametric regression model. Conclusion: If patients are identified at an early stage, they have the best chance of survival. In chronic lymphocytic leukemia (CLL) patients, the best survival is achieved without treatment. At the same time, in other types of cancer, chemotherapy offers the best survival.