Construction of a Nomogram for Predicting Survival in Elderly Patients With Lung Adenocarcinoma: A Retrospective Cohort Study

Abstract

Elderly patients with non-small-cell lung cancer (NSCLC) exhibit worse reactions to anticancer treatments. Adenocarcinoma (AC) is the predominant histologic subtype of NSCLC, is diverse and heterogeneous, and shows different outcomes and responses to treatment. The aim of this study was to establish a nomogram that includes the important prognostic factors based on the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. We collected 53,694 patients of older than 60 who have been diagnosed with lung AC from the SEER database. Univariate and multivariate Cox regression analyses were used to screen the independent prognostic factors, which were used to construct a nomogram for predicting survival rates in elderly AC patients. The nomogram was evaluated using the concordance index (C-index), calibration curves, net reclassification index (NRI), integrated discrimination improvement (IDI), and decision-curve analysis (DCA). Elderly AC patients were randomly divided into a training cohort and validation cohort. The nomogram model included the following 11 prognostic factors: age, sex, race, marital status, tumor site, histologic grade, American Joint Committee for Cancer (AJCC) stage, surgery status, radiotherapy status, chemotherapy status, and insurance type. The C-indexes of the training and validation cohorts for cancer-specific survival (CSS) (0.832 and 0.832, respectively) based on the nomogram model were higher than those of the AJCC model (0.777 and 0.774, respectively). The CSS discrimination performance as indicated by the AUC was better in the nomogram model than the AJCC model at 1, 3, and 5 years in both the training cohort (0.888 vs. 0.833, 0.887 vs. 0.837, and 0.876 vs. 0.830, respectively) and the validation cohort (0.890 vs. 0.832, 0.883 vs. 0.834, and 0.880 vs. 0.831, respectively). The predicted CSS probabilities showed optimal agreement with the actual observations in nomogram calibration plots. The NRI, IDI, and DCA for the 1-, 3-, and 5-year follow-up examinations verified the clinical usability and practical decision-making effects of the new model. We have developed a reliable nomogram for determining the prognosis of elderly AC patients, which demonstrated excellent discrimination and clinical usability and more accurate prognosis predictions. The nomogram may improve clinical decision-making and prognosis predictions for elderly AC patients.

Keywords: adenocarcinoma; elderly patients; nomogram; non-small-cell lung cancer; survival prediction.

Figure 1

A flow diagram of patient selection process.

Figure 2

Nomogram predicted 1-, 3-, and 5-year lung adenocarcinoma cancer-specific survival for patients with 11 available factors, including age, sex, race, marital status, tumor site, grade, AJCC stage, surgery, radiation, chemotherapy, and insurance. AJCC, the American Joint Committee for Cancer; NOS, not otherwise specified lung cancer.

Figure 3

The effect of AJCC staging, surgical treatment, chemotherapy treatment, histologic grade, and age at diagnosis on the cancer-specific survival and overall survival of elderly patients with lung adenocarcinoma. Kaplan–Meier curves for cancer-specific survival (P < 0.001) and overall survival (P < 0.001).

Figure 4

ROC curves and calibration plots for predicting patients-specific survival at 1-, 3-, and 5-year in the training cohorts. (A) ROC curves of the Nomogram and AJCC stage in prediction of prognosis at 1-, 3-, and 5-year point in the training set. (B) The calibration plots for predicting patient survival at 1-, 3-, and 5-year point in the training set. ROC, receiver operating characteristic curve; AUC, areas under the ROC curve.

Figure 5

ROC curves and calibration plots for predicting patients-specific survival at 1-, 3-, and 5-year in the validation cohorts. (A) ROC curves of the Nomogram and AJCC stage in prediction of prognosis at 1-, 3-, and 5-year point in the validation cohorts. (B) The calibration plots for predicting patient survival at 1-, 3-, and 5-year point in the validation cohorts. ROC, receiver operating characteristic curve; AUC, areas under the ROC curve.

Figure 6

Decision curve analysis for the Nomogram and AJCC stage in prediction of prognosis of elderly lung adenocarcinoma patients at 1-year (A), 3-year (B), and 5-year (C) CSS point in the validation cohorts.