Prognostic factors of survival in patients with lung cancer after low-dose computed tomography screening: a multivariate analysis of a lung cancer screening cohort in China - Jun Li; Hui-Lin Xu; Wei-Xi Li; Xiao-Yu Ma; Xiao-Hua Liu; Zuo-Feng Zhang (BMC Cancer)
Abstract Objective This study aimed to evaluate the prognostic factors influencing the survival of patients with lung cancer identified from a lung cancer screening cohort in the community. Methods A total of 25,310 eligible participants were enrolled in this population-based prospective cohort study, derived from a community lung cancer screening program started from 2013 to 2017. Survival analyses were conducted using the Kaplan–Meier method and the log-rank test. Cox proportional hazards regression models were utilized to identify prognostic factors, including demographic characteristics, risk factors, low-dose CT (LDCT) screening, and treatment information. Results The screening cohort identified a total of 429 patients with lung cancer (276 men, 153 women) during the study period. The 1-year, 3-year, and 5-year survival rates were 74.4%, 59.4% and 54.5%, respectively. The prognostic factors discovered by the multivariate analysis include gender (male vs. female, HR: 2.96, 95% CI: 1.88–4.64), age (HR: 1.02, 95% CI: 1.00–1.05), personal monthly income (2000–3999 CNY vs. < 2000 CNY, HR: 0.70, 95% CI: 0.52–0.95), pathological type (small cell carcinoma vs. adenocarcinoma, HR: 2.55, 95% CI: 1.39–4.66), stage (IV vs. 0-I, HR: 5.21, 95% CI: 2.78–9.75; III vs. 0-I, HR: 3.81, 95% CI: 1.88–7.74), surgery (yes vs. no, HR: 0.36, 95% CI: 0.23–0.57), and KPS (HR: 0.98, 95% CI: 0.98–0.99) among lung cancer patients identified by the basic model. Furthermore, solid nodule (non-solid nodule vs. solid nodule, HR: 0.47, 95% CI: 0.23–0.96) and larger-sized nodule (HR: 1.02, 95% CI: 1.00–1.03) were associated with a worse prognosis for lung cancer in the LDCT screening model. Conclusion Prognostic factors of patients with lung cancer detected by LDCT screening were identified, which could potentially guide clinicians in the decision-making process for lung cancer management and treatment. Further studies with larger sample sizes and more detailed follow-up data are warranted for prognostic prediction.