4.5 Article

Long-term survival and conditional survival of cancer patients in Japan using population-based cancer registry data

Journal

CANCER SCIENCE
Volume 105, Issue 11, Pages 1480-1486

Publisher

WILEY-BLACKWELL
DOI: 10.1111/cas.12525

Keywords

Cancer; cancer registry; conditional survival; period analysis; survival

Categories

Funding

  1. Ministry of Health, Labour and Welfare of Japan
  2. Grants-in-Aid for Scientific Research [24701042] Funding Source: KAKEN

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Although we usually report 5-year cancer survival using population-based cancer registry data, nowadays many cancer patients survive longer and need to be followed-up for more than 5years. Long-term cancer survival figures are scarce in Japan. Here we report 10-year cancer survival and conditional survival using an established statistical approach. We received data on 1387489 cancer cases from six prefectural population-based cancer registries in Japan, diagnosed between 1993 and 2009 and followed-up for at least 5years. We estimated the 10-year relative survival of patients who were followed-up between 2002 and 2006 using period analysis. Using this 10-year survival, we also calculated the conditional 5-year survival for cancer survivors who lived for some years after diagnosis. We reported 10-year survival and conditional survival of 23 types of cancer for 15-99-year-old patients and four types of cancer for children (0-14years old) and adolescent and young adults (15-29years old) patients by sex. Variation in 10-year cancer survival by site was wide, from 5% for pancreatic cancer to 95% for female thyroid cancer. Approximately 70-80% of children and adolescent and young adult cancer patients survived for more than 10years. Conditional 5-year survival for most cancer sites increased according to years, whereas those for liver cancer and multiple myeloma did not increase. We reported 10-year cancer survival and conditional survival using population-based cancer registries in Japan. It is important for patients and clinicians to report these relevant figures using population-based data.

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