Development and Validation of a Prognostic Model to Predict Overall Survival for Lung Adenocarcinoma: A Population-Based Study From the SEER Database and the Chinese Multicenter Lung Cancer Database

Abstract

Background: Lung adenocarcinoma (LUAD) is the most common subtype of non-small-cell lung cancer (NSCLC). The aim of our study was to determine prognostic risk factors and establish a novel nomogram for lung adenocarcinoma patients. Methods: This retrospective cohort study is based on the Surveillance, Epidemiology, and End Results (SEER) database and the Chinese multicenter lung cancer database. We selected 22,368 eligible LUAD patients diagnosed between 2010 and 2015 from the SEER database and screened them based on the inclusion and exclusion criteria. Subsequently, the patients were randomly divided into the training cohort (n = 15,657) and the testing cohort (n = 6711), with a ratio of 7:3. Meanwhile, 736 eligible LUAD patients from the Chinese multicenter lung cancer database diagnosed between 2011 and 2021 were considered as the validation cohort. Results: We established a nomogram based on each independent prognostic factor analysis for 1-, 3-, and 5-year overall survival (OS) . For the training cohort, the area under the curves (AUCs) for predicting the 1-, 3-, and 5-year OS were 0.806, 0.856, and 0.886. For the testing cohort, AUCs for predicting the 1-, 3-, and 5-year OS were 0.804, 0.849, and 0.873. For the validation cohort, AUCs for predicting the 1-, 3-, and 5-year OS were 0.86, 0.874, and 0.861. The calibration curves were observed to be closer to the ideal 45° dotted line with regard to 1-, 3-, and 5-year OS in the training cohort, the testing cohort, and the validation cohort. The decision curve analysis (DCA) plots indicated that the established nomogram had greater net benefits in comparison with the Tumor-Node-Metastasis (TNM) staging system for predicting 1-, 3-, and 5-year OS of lung adenocarcinoma patients. The Kaplan-Meier curves indicated that patients' survival in the low-risk group was better than that in the high-risk group (P < .001). Conclusion: The nomogram performed very well with excellent predictive ability in both the US population and the Chinese population.

Keywords: LUAD; SEER; nomogram; overall survival; prognosis.

Figure 1.

The flowchart of the patient selection in the present study from (A) the Surveillance, Epidemiology, and End Results (SEER) database and (B) the Chinese multicenter lung cancer database.

Figure 2.

Kaplan–Meier survival curves of overall survival (OS) based on (A) age, (B) sex, (C) T stage, (D) N stage, (E) M stage, (F) bone metastasis, (G) brain metastasis, (H) liver metastasis, (I) and surgery.

Figure 3.

Nomogram predicted 1-, 3-, and 5-year overall survival (OS) in lung adenocarcinoma (LUAD) patients. The factors of age, sex, T stage, N stage, M stage, bone metastasis, brain metastasis, liver metastasis, and surgery were included in the model.

Figure 4.

Receiver operating characteristic (ROC) curves of the nomogram for predicting survival prognosis at the 1-, 3-, and 5-year points in (A) the training cohort, (B) the testing cohort, (C) and the validation cohort.

Figure 5.

Time-dependent receiver operating characteristic (ROC) curves of the nomogram in the training cohort, the testing cohort, and the validation cohort.

Figure 6.

Calibration curves of the nomogram for predicting survival prognosis at the 1-, 3-, and 5-year points in (A) the training cohort, (B) the training cohort, (C) and the validation cohort.

Figure 7.

Decision curve analysis (DCA) of the nomogram and TNM staging system for predicting survival prognosis at the 1-, 3-, and 5-year points in (A) the training cohort, (B) the training cohort, and (C) the validation cohort.

Figure 8.

Kaplan–Meier curves of overall survival (OS) stratified by risk classification system in the (A) training cohort, (B) the testing cohort, and (C) the validation cohort.