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. 2022 Aug;13(15):2210-2222.
doi: 10.1111/1759-7714.14549. Epub 2022 Jul 11.

Investigation on the incidence and risk factors of lung cancer among Chinese hospital employees

Zi-Hao Chen  1   2 , Zhi-Yong Chen  2 , Jing Kang  2   3 , Xiang-Peng Chu  1   2 , Rui Fu  1   2 , Jia-Tao Zhang  2   3 , Yi-Fan Qi  1   2 , Jing-Hua Chen  4 , Jun-Tao Lin  2 , Ben-Yuan Jiang  2 , Xue-Ning Yang  2 , Yi-Long Wu  2 , Wen-Zhao Zhong  1   2 , Qiang Nie  1   2
Affiliations

Investigation on the incidence and risk factors of lung cancer among Chinese hospital employees

Zi-Hao Chen et al. Thorac Cancer. 2022 Aug.

Abstract

Objective: In recent years, the lung cancer incidence has grown and the population is younger. We intend to find out the true detection rate of pulmonary nodules and the incidence of lung cancer in the population and search for the risk factors.

Method: Hospital employees ≥40 years old who underwent low-dose computed tomography (CT) lung cancer screening from January 2019 to March 2022 were selected to record CT-imaging characteristics, pathology, staging, and questionnaires to investigate past history, smoking history, diet, mental health, etc. PM2.5 and radiation intake in radiation-related occupation received monitoring in hospital.

Result: The detection rate of suspicious pulmonary nodules was 9.1% (233/2552), and the incidence rate of lung cancer (including adenocarcinoma in situ) was 4.0% (103/2552). Morbidity among doctors, nurses, technicians, administers, and logistics was no difference (p = 0.184), but higher in women than in men (4.7% vs 2.4% p = 0.002). The invasiveness increased with age and CT density of nodules (p = 0.018). The relationship between lung cancer morbidity and PM2.5 was not clear (p = 0.543); and no lung cancer has been found in employees related ionizing radiation.

Conclusion: The high screening rate has brought about a high incidence of lung cancer. At present, the risk factor analysis of lung cancer based on small samples cannot find the direct cause. Most of the ground glass opacity (GGO)s detected by LDCT screening are indolent, but there are also rapidly progressive lung cancer. A predictive model to identify active and indolent GGO is necessary.

Keywords: PM2.5; early screening; ionizing radiation; pulmonary nodules; risk factors.

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Conflict of interest statement

No potential conflict of interest was reported by the authors.

Figures

FIGURE 1
FIGURE 1
Decision‐making for pulmonary nodules.
FIGURE 2
FIGURE 2
The annual cumulative number of physical examinations, the number of suspicious pulmonary nodules detected, and the number of resections are line graphs.
FIGURE 3
FIGURE 3
Risk for lung cancer among hospital employees.
FIGURE 4
FIGURE 4
GGO types and proportions of nodules screened by LDCT, and the proportion of corresponding pathological types.
FIGURE 5
FIGURE 5
Imaging features of three invasive adenocarcinomas with pure ground glass nodules smaller than 6 mm.
FIGURE 6
FIGURE 6
Imaging, pathology, age‐related bubble charts, the invasiveness of nodules increased with age and CT density of nodules (p = 0.018).
FIGURE 7
FIGURE 7
Distribution of occupational types/departments and the ratio of male to female of lung cancer incidence in the hospital population.
FIGURE 8
FIGURE 8
Monthly mean value of PM2.5 at each monitoring point in different buildings.
FIGURE 9
FIGURE 9
Dust concentration map with the building location and the incidence of lung cancer. (a) Adjacent relationship and topographic map of hospital building distribution, (b) histogram of lung cancer incidence between different buildings, (c) grayscale map generated by dust monitor based on PM2.5 concentration, (d) 25 monitors through equal the gray points are connected to form a PM2.5 concentration contour map. (e) Generate a plane heat map based on the contour map visualization. (f) Combine the topographic map to form a visual schematic diagram of the fitting of the three‐dimensional dust concentration map with the building location and the incidence of lung cancer.
FIGURE 10
FIGURE 10
Line chart of PM2.5 in the hospital area compared to the district where the hospital is located.
FIGURE 11
FIGURE 11
Quantitative box plot of annual ionizing radiation uptake for different radiation‐related occupations.
See this image and copyright information in PMC

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