This study focused on children as well as adolescents and young adults (AYAs) and aimed to examine trends in survival of leukemia over time using population-based cancer registry data from Osaka, Japan. The study subjects comprised 2254 children (0-14 years) and 2,905 AYAs (15-39 years) who were diagnosed with leukemia during 1975-2011. Leukemia was divided into four types: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic myeloid leukemia (CML), and other leukemias. We analyzed 5-year overall survival probability (5y-OS), using the Kaplan-Meier method and expressed time trends using the joinpoint regression model. For recently diagnosed (2006-2011) patients, a Cox proportional hazards model was applied to determine predictors of 5y-OS, using age group, gender, and treatment hospital as covariates. Over the 37-year period, 5y-OS greatly improved among both children and AYAs, for each leukemia type. Among AYAs, 5y-OS of ALL improved, especially after 2000 (65% in 2006-2011), when the pediatric regimen was introduced but was still lower than that among children (87% in 2006-2011, P < .001). Survival improvement was most remarkable in CML, and its 5y-OS was over 90% among both children and AYAs after the introduction of molecularly targeted therapy with tyrosine kinase inhibitors. Among patients with recently diagnosed AML, the risk of death was significantly higher for patients treated at nondesignated hospitals than those treated at designated cancer care hospitals. The changes in survival improvement coincided with the introduction of treatment regimens or molecularly targeted therapies. Patient centralization might be one option which would improve survival.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935797PMC
http://dx.doi.org/10.1111/cas.14808DOI Listing

Publication Analysis

Top Keywords

trends survival
8
leukemia
8
survival leukemia
8
adolescents young
8
young adults
8
osaka japan
8
japan study
8
myeloid leukemia
8
children
5
leukemia children
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!