Propensity score analysis of lung cancer risk in a population with high prevalence of non-smoking related lung cancer

Abstract Background Lung cancer has been the leading cause of cancer-related mortality worldwide among both men and women in recent years. There is an increase in the incidence of nonsmoking-related lung cancer in recent years. The purpose of the present study was to investigate multiple potential r...

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Bibliographic Details
Main Authors: Kuei-Feng Lin, Hsiu-Fu Wu, Wei-Chun Huang, Pei-Ling Tang, Ming-Ting Wu, Fu-Zong Wu
Format: Article
Language:English
Published: BMC 2017-09-01
Series:BMC Pulmonary Medicine
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Online Access:http://link.springer.com/article/10.1186/s12890-017-0465-8
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Summary:Abstract Background Lung cancer has been the leading cause of cancer-related mortality worldwide among both men and women in recent years. There is an increase in the incidence of nonsmoking-related lung cancer in recent years. The purpose of the present study was to investigate multiple potential risk factors for nonsmoking-related lung cancer among Asian Ethnic Groups. Methods We used a propensity score-mated cohort analysis for this study. We retrospectively review the medical record of 1975 asymptomatic healthy subjects (40 ~ 80 years old) who voluntarily underwent low-dose chest CT from August 2013 to October 2014. Clinical information and nodule characteristics were recorded. Results A propensity score-mated cohort analysis was applied to adjust for potential bias and to create two comparable groups according to family history of lung cancer. For our primary analysis, we matched 392 pairs of subjects with family history of lung cancer and subjects without history. Logistic regression showed that female gender and a family history of lung cancer were the two most important predictor of lung cancer in the endemic area with high prevalence of nonsmoking-related lung cancer (OR = 11.199, 95% CI = 1.444–86.862; OR = 2.831, 95% CI = 1.000136–8.015). In addition, the number of nodules was higher in subjects with family history of lung cancer in comparison with subjects without family history of lung cancer (OR = 1.309, 95% CI = 1.066–1.607). Conclusions In conclusion, risk-based prediction model based on the family history of lung cancer and female gender can potentially improve efficiency of lung cancer screening programs in Taiwan.
ISSN:1471-2466