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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Apr 15, 2026
Open Peer Review Period: Apr 15, 2026 - Jun 10, 2026
Date Accepted: Aug 26, 2026
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Temporal Trends in Lung Cancer and Histological Subtype Incidence and Bayesian Projections to 2030 in China: Population-Based Quantitative Study

Su X, Li J, Hu X

Temporal Trends in Lung Cancer and Histological Subtype Incidence and Bayesian Projections to 2030 in China: Population-Based Quantitative Study

JMIR Public Health Surveill 2026;12:e98324

DOI: 10.2196/98324

PMID: 42837657

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Temporal trend in lung cancer and subtype incidence rates and Bayesian projection to 2030: A population-based study in China

  • Xing Su; 
  • Jing Li; 
  • Xiaowei Hu

ABSTRACT

Background:

Lung cancer is the leading cause of cancer-related death globally, with a significant burden in China, which accounts for over a third of the world's new cases and 40% of related mortalities. Despite evidence that low-dose computed tomography screening can reduce mortality, its limited uptake in China means most patients are diagnosed at an advanced stage, contributing to a low 5-year survival rate compared to developed countries. While overall incidence trends have been well-documented, there is a scarcity of population-based data on the temporal trends of different histological subtypes of lung cancer in China.

Objective:

The study aimed to analyze cancer registry data to assess lung cancer trends (2001-2020) and forecast further incidence rates (2020-2030).

Methods:

The study utilized population-based surveillance data from the Xihu Cancer Registry, from 2001 to 2020. Statistical analyses were conducted to assess the burden of each tumor subtype, including the average annual percentage change (AAPC) to evaluate temporal trends and the Bayesian age-period-cohort (BAPC) model to forecast incidence rates up until 2030.

Results:

The results showed a substantial increase in lung cancer incidence rates in Xihu, particularly among younger individuals. Adenocarcinoma exhibited a consistent and significant increase in both males and females, while other histological types remained stable or slightly decreased. Joinpoint regression analysis revealed long-term trends of increasing adenocarcinoma (AAPC = 35.1 ,95% CI: 14.2 to 50.2) and large cell + other specified carcinoma (AAPC = 32.7, 95% CI: 12.5 to 45.7), and decreasing unspecified carcinoma (AAPC = -3.1, 95% CI: -14.2 to -1.1). The ASIR of adenocarcinoma was projected to continue rising and become the dominant histological subtype in the future.

Conclusions:

The increase in lung cancer incidence, particularly among females, underscores the need for effective prevention and control strategies, including targeted interventions to reduce smoking prevalence.


 Citation

Please cite as:

Su X, Li J, Hu X

Temporal Trends in Lung Cancer and Histological Subtype Incidence and Bayesian Projections to 2030 in China: Population-Based Quantitative Study

JMIR Public Health Surveill 2026;12:e98324

DOI: 10.2196/98324

PMID: 42837657

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