ESMO Voice of China Professor He Jianxing and Professor Liang Wenhua's team: China's new lung cancer screening model can detect more stage I lung cancer patients

Editor: Koyuan

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The European Society of Medical Oncology (ESMO) Annual Meeting is the most prestigious and influential oncology conference
in Europe.
The 2022 ESMO Conference will be held in person (Paris, France) and online from September 9 to 13, 2022, covering basic research, translational research and the latest clinical research progress, providing a broad and excellent academic platform
for clinical practice and multidisciplinary discussion.

In the oral report session on the morning of the 11th local time, Professor Liang Wenhua of the First Affiliated Hospital of Guangzhou Medical University orally reported on the progress of a research on
lung cancer screening.
Details are as follows:

Professor
Liang Wenhua

1 Background

Previous studies have shown that people with a history of smoking may benefit
from lung cancer screening.
It is more common
in women and non-smokers in Asian lung cancer patients compared to Europe and the United States.
This study aims to explore the results of lung cancer screening in the general population in China and to explore the predictors of lung cancer to improve the risk assessment model
of lung cancer screening.
The research conducted by the team of Professor He Jianxing and Professor Liang Wenhua of the First Affiliated Hospital of Guangzhou Medical University was announced
at this year's ESMO conference.

2 Method

This study is a large-scale, community-based low-dose spiral CT (LDCT) screening program in which researchers investigated risk factors for early lung cancer screening
.
The investigators screened participants
enrolled between 2015 and 2021.
Eligible participants were residents aged 40-74 from 4 communities in Guangzhou area, and the exclusion criteria were patients diagnosed with lung cancer within the
past 5 years.
The questionnaire includes detailed demographic data, health status
.
Binary logistic regression analysis is used to screen for potential risk factors
.
The primary endpoint was to assess the incidence
of lung cancer in the general population of Guangzhou.
Secondary endpoints included comparing the incidence of lung cancer in high-risk and non-high-risk groups, exploring risk factors for lung cancer in Chinese groups, and cost-effectiveness analysis
.

3 Results

A total of 11,708 participants, including 5,452 men and 6,256 women, were screened for a median age of 59 (IQR, 51-65) years
.
A total of 200 (1.
7%) participants were diagnosed with lung cancer, of which 172 (86%) were in stage
0-I.
37 (19.
6%) and 105 (55.
6%) confirmed cases met the criteria of
NCCN and Chinese screening guidelines, respectively.

Key Results Figure 1: 200 patients diagnosed with lung cancer, 86% of whom had stage I

Detection rates of lung cancer and stage I patients in high- and non-high-risk populations

LDCT screening reduces lung cancer-related deaths in the community and improves survival for
lung cancer patients compared to those who are not screened.

Key Results Figure 2: LDCT screening improves patient survival

The questionnaire collected 109 factors, and the researchers found 8 independent risk/protective factors
associated with lung cancer through multivariate model analysis.
The AUC of this model was 0.
71 (95% CI, 0.
67-0.
75), which was significantly higher than NCCN guidelines (0.
52, 95% CI 0.
50-0.
55) and Chinese screening guidelines (0.
62 95% CI 0.
58-0.
67).

Multivariate analysis of the screening population (high-risk factors)

Filters and patients with stage I-IV lung cancer had higher
AUC values compared with non-smokers (0.
69, 95% CI 0.
64 to 0.
74) and invasive disease (AIS and MIA, 0.
64, 95% CI 0.
57 to 0.
72).

4 Conclusion

Screening using LDCT can detect more patients with
early-stage lung cancer in the community population in Guangzhou.
Mass screening
should be considered for lung cancer detection in non-high-risk groups compared with high-risk groups, as well as higher detection rates in stage I patients.
Personal cancer treatment history, silica exposure, older age, food allergies, and family history of lung cancer were independent predictors
.
A risk prediction model based on individual characteristics combined with carcinoembryonic antigen (CEA) levels can improve the lung cancer risk assessment model
for lung cancer screening.

References:

LBA48-Community-based mass screening with low-dose CT for lung cancer in Guangzhou.
2022 ESMO.