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Incidence and Characteristics of Multiple Primary Cancers: A 20-Year Retrospective Study of a Single Cancer Center in Korea.

Jin-Hee KwonHeyjin KimJin Kyung LeeYoung Jun HongHye Jin KangYoon Jung Jang
Published in: Cancers (2024)
Rising cancer survival rates have led to an increased risk of multiple primary cancers (MPCs). Data on MPCs in South Korea are limited. This study aimed to address incidence and clinical characteristics of MPCs in a single cancer center in Korea during a 20-year period. We retrospectively analyzed 96,174 cancer patients at the Korea Cancer Center Hospital between 2003 and 2022, identifying 2167 patients with metachronous MPCs based on Surveillance, Epidemiology, and End Results SEER criteria. We categorized patients by cancer type (15 major solid cancer groups and 3 major hematologic cancer groups), including pathological diagnosis, assessed latency periods, and relative risks (RRs) for developing MPCs. The overall MPC incidence was 2.3%. Breast cancer (15.7%) was the most common primary cancer, and lung cancer (15.2%) was the most frequent second primary cancer. The median latency period for second primary cancers was 4.1 years. Decreasing latency periods for third and fourth primary cancers were observed (2.1 years and 1.6 years, respectively). Most cancers maintained their dominant pathological type despite notable changes in the prevalence of specific pathologies for certain types of second primaries. Lymphoma showed the highest RR (2.1) for developing MPCs. Significant associations were found between specific primary and subsequent cancers, including breast-ovary, thyroid-breast, stomach-pancreas, colorectal-head and neck, lung-prostate, and lymphoma-myeloid neoplasms. These findings contribute to a better understanding of MPC occurrence. They can inform future research on their etiology and development of improved management strategies.
Keyphrases
  • papillary thyroid
  • squamous cell
  • childhood cancer
  • lymph node metastasis
  • healthcare
  • risk assessment
  • risk factors
  • acute myeloid leukemia
  • newly diagnosed
  • dendritic cells
  • big data
  • electronic health record