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Original Research

The Incidence and Risk Analysis of Lung Cancer Development in Patients with Chronic Obstructive Pulmonary Disease: Possible Effectiveness of Annual CT-Screening

, , ORCID Icon, , , , , , , , , , , , , & show all
Pages 739-749 | Published online: 25 Mar 2021

Figures & data

Figure 1 Study outline. We enrolled 253 stable COPD patients. Of the enrolled patients, eight were excluded from the analysis due to missing blood data, while two were excluded due to missing Asthma-COPD overlap (ACO) data. Eight patients were excluded because of a short follow-up period (less than six months). Additionally, nine patients were excluded because they had a history of lung cancer, and two patients were excluded because they had lung cancer at enrollment. Therefore, we analyzed 224 patients with stable COPD.

Figure 1 Study outline. We enrolled 253 stable COPD patients. Of the enrolled patients, eight were excluded from the analysis due to missing blood data, while two were excluded due to missing Asthma-COPD overlap (ACO) data. Eight patients were excluded because of a short follow-up period (less than six months). Additionally, nine patients were excluded because they had a history of lung cancer, and two patients were excluded because they had lung cancer at enrollment. Therefore, we analyzed 224 patients with stable COPD.

Table 1 Patient Characteristics

Table 2 Comparison of the Characteristics of Patients Who Developed Lung Cancer with Those Who Did Not

Figure 2 Survival curves. A survival curve analysis according to the Kaplan–Meier method showed that mortality was significantly increased in the lung cancer development group compared with the group that did not develop lung cancer.

Figure 2 Survival curves. A survival curve analysis according to the Kaplan–Meier method showed that mortality was significantly increased in the lung cancer development group compared with the group that did not develop lung cancer.

Table 3 Characteristics of Patients Who Developed Lung Cancer

Table 4 Univariate and Multivariate Logistic Regression Analyses for Discriminating the Subjects Who Developed Lung Cancer