Correlation between lymphoma and second primary malignant tumor

Abstract

Although studies have investigated the risk of second primary malignancies (SPMs) associated with lymphoma of various sites, limited studies have investigated risk of lymphoma with different SPMs and risk factors related to different SPMs. We conducted a retrospective cohort study to evaluate the cumulative incidence and risk factors of different secondary SPMs in patients previously diagnosed as lymphoma, and to compare the survival rates of SPMs and primary malignant tumors. Retrospective analysis was performed on data obtained from Surveillance, Epidemiology, and End Results database. Patients with an initial primary malignancy diagnosis of lymphoma between 2000 and 2019 were included in the study. The statistical analysis was conducted from March 2022 to January 2023. The development of an SPM defined as any type of malignant tumor 292,210 patients remained in final cohort, including 35,220 patients with secondary primary malignant tumor. The cumulative incidence of SPMs during 20 years of follow-up is 1.95% in combined respiratory system, 0.14% in central nervous system, is 0.82% hepatobiliary pancreatic system, is 1.31% in urinary system, is 1.92% digestive tract. Multivariate competitive risk model analysis showed that Different characteristics of lymphoma patients were associated with secondary different types of SPMS. The risk of secondary SPMs in lymphoma patients after radiotherapy and chemotherapy varies with the change of diagnosis time, diagnosis age and incubation period. Propensity score matching and Kaplan–Meier analysis showed that the survival rate of secondary tumor was significantly lower than that of matched primary malignant tumor. This study reminds us to consider the possibility of SPMs in the initial treatment of lymphoma patients, and develop a follow-up plan according to the characteristics of patients to reduce the risk of SPMs. Occurring more than 6 months after the diagnosis of lymphoma. The cumulative incidence of SPMs was estimated by Fine-Gray competing risk regression. Poisson regression was used to evaluate the therapeutic factors associated risk for SPMs in patients undergoing radiotherapy or chemotherapy. The Kaplan–Meier method was used to assess the survival outcomes of patients with SPMs.