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Migration-adjusted lung cancer burden in China: a population data-based Bayesian spatial modeling approach
Shuxiu Hao1,2,3, Guijin Li1,2,3, Huixin Sun4
1Chinese Center for Endemic Disease Control, Harbin Medical University, Harbin, China.
JNCI Cancer Spectrum
|March 16, 2026
Summary
China's cancer surveillance misses millions of migrants, skewing lung cancer data. A new model using resident population data offers a more accurate picture, revealing significant disparities in incidence and mortality.
Area of Science:
- Epidemiology
- Public Health
- Biostatistics
Background:
- Cancer surveillance in China relies on household registration, excluding the significant migrant population.
- This exclusion leads to selection bias and misestimation of the true cancer burden.
- Accurate lung cancer burden assessment requires including resident populations.
Purpose of the Study:
- To estimate lung cancer incidence and mortality among the resident population in mainland China.
- To adjust for inter-provincial migration in cancer burden estimations.
- To compare the accuracy of different modeling approaches for cancer surveillance.
Main Methods:
- Developed a Bayesian integrated nested Laplace approximation with stochastic partial differential equation (INLA-SPDE) model.
- Utilized 2016 data from 487 cancer registries and multidimensional covariates.
- Incorporated adjustments for inter-provincial migration.
Main Results:
- The INLA-SPDE model demonstrated superior estimation accuracy compared to the Bayesian hierarchical linear model.
- Significant disparities in lung cancer incidence and mortality were found between resident and registered populations in Henan, Guangdong, and Shanghai.
- Shanghai exhibited the largest rate differences, with incidence and mortality rates significantly differing from registered population estimates.
Conclusions:
- Household registration-based surveillance overestimates lung cancer burden in high-immigration regions and underestimates it in high-emigration regions.
- Disparities in lung cancer incidence and mortality are influenced by migration patterns.
- Transitioning to resident population-based registration is recommended for improved accuracy in cancer surveillance, especially in areas with high migration.
