ArticleFrontiers in oncology2026
Using period analysis to timely provide serial data on long-term survival for patients with hematological malignancies from Taizhou, Eastern China.
Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: While diagnostic and therapeutic innovations have significantly improved the prognosis of hematological malignancies (HMs), comprehensive data on their survival outcomes in China remain scarce. This study aimed to investigate the up-to-date long-term survival of common HMs in a Chinese population. Methods: In this population-based study, we analyzed data from nine cancer registries in Taizhou, eastern China, covering patients aged ≥15 years diagnosed with HMs between 2009 and 2023. Period analysis was used to estimate overall and stratified 5-, 10-, and 15-year relative survival (RS) by sex, age at diagnosis, region, and subtype, revealing trends in RS over time since diagnosis. Results: The study included a total of 10, 022 HM cases, with a median age at diagnosis of 62 years. During 2019-2023, the overall 5-year RS for all HMs was 57.0%. Among the three major HM types, lymphoma exhibited the highest 5-year RS (64.4%), followed by multiple myeloma (51.1%), while leukemia had the lowest (49.3%). The 10-year and 15-year RS for all HM patients decreased to 46.0% and 37.5%, respectively. Except for leukemia, females had higher 5-, 10-, and 15-year RS than males. For each type of HM, RS was significantly higher in patients aged<60 years than in those aged ≥60 years, and urban areas showed higher RS than rural areas. In terms of subtypes, chronic lymphocytic leukemia and chronic myeloid leukemia had the best long-term survival. The 15-year survival curves for HMs generally declined with longer time since diagnosis. Conclusion: This study is the first to provide timely and accurate long-term survival series data for patients with HMs in Taizhou, eastern China, using period analysis. The results offer crucial evidence for optimizing public health strategies and developing targeted cancer control measures.
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