A nomogram to predict overall survival of patients with early stage non-small cell lung cancer

Abstract

Background: Nomograms have been widely used for estimating cancer prognosis. The aim of this study was to construct a clinical nomogram that would well predict overall survival of early stage non-small cell lung cancer (NSCLC) patients after surgery resection.

Methods: A total of 443 patients diagnosed with pathologic stage I and II NSCLC who had undergone curative resection without neoadjuvant chemotherapy or radiotherapy were recruited and analyzed. The log-rank test and multivariate Cox regression analysis were used to select the most significant predictors in the final nomogram for predicting overall survival. Furthermore, the model was validated by bootstrap methods and measured by concordance index (C-index) and calibration plots.

Results: Four independent predictors for overall survival were identified and included into the delineation of the nomogram (tumor differentiation, station of sampled lymph nodes, pathologic T and pathologic N). The model showed comparatively stable discrimination (bootstrap-corrected C-index =0.622, 95% CI: 0.572-0.672) and good calibration.

Conclusions: We successfully developed a nomogram incorporating available clinicopathological variables to predict overall survival of early stage NSCLC patients after surgery resection, which might help clinician select better appropriate treatment decisions.

Keywords: Lung cancer; TNM stage; nomogram; stage I and II; survival.

Figure 1

Kaplan-Meier curves of overall survival according to tumor differentiation (A), station of sampled lymph nodes (B), pathologic T (C) and pathologic N (D).

Figure 2

Postoperative prognostic nomogram for patients with early stage non-small cell lung cancer after surgery resection. To use, for example, the user should find one patient’s differentiation on the differentiation axis, then draw a straight line upward to the point axis to determine how many points toward death the patient receives for differentiation. Do above process again for the other axes (station of sampled lymph nodes, pathologic T stage and pathologic N stage), each time drawing a straight line upward toward point axis. Sum points received for each predictor, and find sum on the total point axis. Draw straight line down to survival-probability axes to find patient’s 3- or 5-year survival probability. LNs, lymph nodes.

Figure 3

The calibration curves for predicting overall survival at 3-year (A) and 5-year (B). Nomogram-predicted probability of overall survival is plotted on the x-axis; actual overall survival is plotted on the y-axis. The solid line along the dashed line (45-degree line) would indicate a perfect calibration model in which the predicted probabilities are close to the actual probabilities.