A nomogram to predict prognosis of patients with lung adenosquamous carcinoma: a population-based study

BACKGROUND: Adenosquamous carcinoma (ASC) of the lung is an infrequent variant of lung cancer. This study aimed to identify independent risk factors and to develop a predictive model for the prognosis of ASC patients. METHODS: Patient data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database (2004 to 2016) and database in our department (2010 to 2014). Overall survival (OS) was evaluated by the Kaplan-Meier method. Significant prognostic factors were identified by univariate analysis (UVA) and multivariate analysis (MVA) using the Cox proportional hazards regression. Competing risk model analyses were performed using cancer-specific survival outcomes. A nomogram was developed to predict patient 3-year and 5-year OS and was validated using data from the two databases. RESULTS: A total of 4,600 patients with ASC were included and divided into a training cohort (n=3,202) and two validation cohorts (n=1,372, n=26). Patients with ASC had significantly older age, lower grades of tumor differentiation or incidences of nodal, and distant invasions than adenocarcinoma and squamous cell carcinoma (SCC) of the lung (P<0.001), while the median survival time of ASC patients was intermediate [21.0 (19.3–22.7) months]. Age, sex, primary site of tumor, histological grade, T stage, N stage, M stage of the tumor, as well as surgery to the primary tumor site and chemotherapy were identified as independent factors for ASC (P<0.001). A reliable nomogram was established with a group of validation plots and concordance indices (C-indices) (internal: 0.755±0.010; external: 0.748±0.049 and 0.721±0.045). CONCLUSIONS: Age, sex, primary site of tumor, histological grade, T stage, N stage, M stage of the tumor, as well as surgery to the primary site of tumors and chemotherapy were independent risk factors for ASC patients. A validated nomogram was constructed to predict the prognosis based on the patient clinical characteristics.