The GLOBOCAN 2022 cancer estimates: Data sources, methods, and a snapshot of the cancer burden worldwide
The data sources and methods used to develop global cancer incidence and mortality statistics—the GLOBOCAN estimates—for the year 2022 are documented in this article, alongside a brief overview of the global cancer burden. The estimates, made available in 185 countries or territories worldwide for 3...
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Published in | International journal of cancer Vol. 156; no. 7; pp. 1336 - 1346 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Hoboken, USA
John Wiley & Sons, Inc
01.04.2025
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | The data sources and methods used to develop global cancer incidence and mortality statistics—the GLOBOCAN estimates—for the year 2022 are documented in this article, alongside a brief overview of the global cancer burden. The estimates, made available in 185 countries or territories worldwide for 36 cancer sites by sex and age, are based on the best available local data sources, namely population‐based cancer registries (for incidence) and national vital statistics (for mortality). In males, lung cancer was the most commonly diagnosed cancer worldwide in 2022 (1.57 million new cases [95% UI: 1.56–1.58]), followed by prostate cancer (1.47 million [1.46–1.48]). With 2.30 million (2.28–2.30) new cases estimated in 2022, breast cancer was the most diagnosed cancer in females, followed by lung cancer (0.91 million [0.90–0.91 million]) and cervical cancer (0.66 million [0.66–0.67]). The most common causes of cancer death in males and females were lung cancer (1.23 million [1.22–1.24]) and breast cancer (0.67 million [0.66–0.67]), respectively.
What's new?
This report details the data sources and methods used to build IARC's GLOBOCAN database of cancer incidence and mortality estimates in 185 countries or territories for the year 2022. The core methods remain unchanged from previous iterations, and accord with the principles of transparency and reproducibility at the national level. Uncertainty intervals (UIs) for the estimates are provided to account for major sources of error over and above random variation, namely the timeliness, representativeness and quality of the underlying data sources. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 0020-7136 1097-0215 1097-0215 |
DOI: | 10.1002/ijc.35278 |