Global patterns of cancer transitions: A modelling study

Int J Cancer. 2023 Nov 1;153(9):1612-1622. doi: 10.1002/ijc.34650. Epub 2023 Aug 7.

Abstract

Cancer is a major contributor to global disease burden. Many countries experienced or are experiencing the transition that non-infection-related cancers replace infection-related cancers. We aimed to characterise burden changes for major types of cancers and identify global transition patterns. We focused on 10 most common cancers worldwide and extracted age-standardised incidence and mortality in 204 countries and territories from 1990 to 2019 through the Global Burden of Disease Study. Two-stage modelling design was used. First, we applied growth mixture models (GMMs) to identify distinct trajectories for incidence and mortality of each cancer type. Next, we performed latent class analysis to detect cancer transition patterns based on the categorisation results from GMMs. Kruskal-Wallis H tests were conducted to evaluate associations between transition patterns and socioeconomic indicators. Three distinct patterns were identified as unfavourable, intermediate and favourable stages. Trajectories of lung and breast cancers had the strongest association with transition patterns among men and women. The unfavourable stage was characterised by rapid increases in lung, breast and colorectal cancers alongside stable or decreasing burden of gastric, cervical, oesophageal and liver cancers. In contrast, the favourable stage exhibited rapid declines in most cancers. The unfavourable stage was associated with lower sociodemographic index, health expenditure, gross domestic product per capita and higher maternal mortality ratio (P < .001 for all associations). Our findings suggest that unfavourable, intermediate and favourable transition patterns exist. Countries and territories in the unfavourable stage tend to be socioeconomically disadvantaged, and tailored intervention strategies are needed in these resource-limited settings.

Keywords: cancer transition; global health; health disparities; latent class model.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms* / epidemiology
  • Female
  • Global Burden of Disease
  • Global Health
  • Humans
  • Male
  • Socioeconomic Factors