OA09.07 Association Between Outdoor Air Pollution And Lung Cancer in Female Never Smokers

Using a Polygenic Risk Score to Improve the Risk Prediction of Non-Small Cell Lung Cancer in Taiwan

PURPOSE

Low-dose computed tomography (LDCT) can help reducing lung cancer mortality. In Taiwan, the existing screening criteria revolve around smoking habits and family history of lung cancer. The role of genetic variation in non-small cell lung cancer (NSCLC) development is increasingly recognized. In this study, we aimed to investigate the potential benefits of polygenic risk scores (PRSs) in predicting NSCLC and enhancing the effectiveness of screening programs.

METHODS

We conducted a retrospective cohort study that included participants without prior diagnosis of lung cancer and later received LDCT for lung cancer screening. Genetic data for these participants were obtained from the project of Taiwan Precision Medicine Initiative. We adopted the model of genome-wide association study-derived PRS calculation using 19 susceptibility loci associated with the risk of NSCLC as reported by Dai et al.

RESULTS

We studied a total of 2,287 participants (1,197 male, 1,090 female). More female participants developed NSCLC during the follow-up period (4.4% v 2.5%, P = .015). The only risk factor of NSCLC diagnosis among male participants was age. Among female participants, independent risk factors of NSCLC diagnosis were age (adjusted hazard ratio [aHR], 1.08 [95% CI, 1.04 to 1.11]), a family history of lung cancer (aHR, 3.21 [95% CI, 1.78 to 5.77]), and PRS fourth quartile (aHR, 2.97 [95% CI, 1.25 to 7.07]). We used the receiver operating characteristics to show an AUC value of 0.741 for the conventional model. With the further incorporation of PRS, the AUC rose to 0.778.

CONCLUSION

The evaluation of PRS for NSCLC prediction holds promise for enhancing the effectiveness of lung cancer screening in Taiwan especially in women. By incorporating genetic information, screening criteria can be tailored to identify individuals at higher risks of NSCLC.

Low-Dose Computed Tomography Screening in Relatives With a Family History of Lung Cancer

INTRODUCTION

The role of a family history of lung cancer (LCFH) in screening using low-dose computed tomography (LDCT) has not been prospectively investigated with long-term follow-up.

METHODS

A multicenter prospective study with up to three rounds of annual LDCT screening was conducted to determine the detection rate of lung cancer (LC) in asymptomatic first- or second-degree relatives of LCFH.

RESULTS

From 2007 to 2011, there were 1102 participants enrolled, including 805 and 297 from simplex and multiplex families (MFs), respectively (54.2% women and 70.0% never-smokers). The last follow-up date was May 5, 2021. The overall LC detection rate was 4.5% (50 of 1102). The detection rate in MF was 9.4% (19 of 202) and 4.4% (4 of 91) in never-smokers and in those who smoked, respectively. The corresponding rates for simplex families were 3.7% (21 of 569) and 2.7% (6 of 223), respectively. Of these, 68.0% and 22.0% of cases with stage I and IV diseases, respectively. LC diagnoses within a 3-year interval from the initial screening tend to be younger, have a higher detection rate, and have stage I disease; thereafter, more stage III-IV disease and 66.7% (16 of 24) with negative or semipositive nodules in initial computed tomography scans. Within the 6-year interval, only maternal (modified rate ratio = 4.46, 95% confidence interval: 2.32-8.56) or maternal relative history of LC (modified rate ratio = 5.41, 95% confidence interval: 2.84-10.30) increased the risk of LC.

CONCLUSIONS

LCFH is a risk factor for LC and is increased with MF history, among never-smokers, younger adults, and those with maternal relatives with LC. Randomized controlled trials are needed to confirm the mortality benefit of LDCT screening in those with LCFH.

Spatial Analysis of Built Environment Risk for Respiratory Health and Its Implication for Urban Planning: A Case Study of Shanghai

Urban planning has been proven and is expected to promote public health by improving the built environment. With a focus on respiratory health, this paper explores the impact of the built environment on the incidence of lung cancer and its planning implications. While the occurrence of lung cancer is a complicated and cumulative process, it would be valuable to discover the potential risks of the built environment. Based on the data of 52,009 lung cancer cases in Shanghai, China from 2009 to 2013, this paper adopts spatial analytical methods to unravel the spatial distribution of lung cancer cases. With the assistance of geographic information system and Geo-Detector, this paper identifies certain built environments that are correlated with the distribution pattern of lung cancer cases in Shanghai, including the percentage of industrial land (which explains 28% of the cases), location factors (11%), and the percentages of cultivated land and green space (6% and 5%, respectively). Based on the quantitative study, this paper facilitates additional consideration and planning intervention measures for respiratory health such as green buffering. It is an ecological study to illustrate correlation that provides approaches for further study to unravel the causality of disease incidence and the built environment.