A Nomogram to Predict Long-Term Survival Outcomes of Patients Who Undergo Pneumonectomy for Non-small Cell Lung Cancer With Stage I-IIIB
A Nomogram to Predict Long-Term Survival Outcomes of Patients Who Undergo Pneumonectomy for Non-small Cell Lung Cancer With Stage I-IIIB
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Background: In this study, we aim to establish a nomogram to predict the prognosis of non-small cell lung cancer (NSCLC) patients with stage I-IIIB disease after pneumonectomy.Methods: Patients selected from the Surveillance, Epidemiology, and baby silicone mold End Results (SEER, N = 2,373) database were divided into two cohorts, namely a training cohort (SEER-T, N = 1,196) and an internal validation cohort (SEER-V, N = 1,177).Two cohorts were dichotomized into low- and high-risk subgroups by the optimal risk prognostic score (PS).The model was validated by indices of concordance (C-index) and calibration plots.
Kaplan-Meier analysis and the log-rank tests were used to compare survival curves between the groups.The primary observational endpoint was cancer-specific survival (CSS).Results: The nomogram comprised six factors as independent prognostic indictors; it significantly distinguished between low- and high-risk groups (all P < 0.05).
The unadjusted 5-year CSS rates of high-risk and low-risk groups were 33 and 60% (SEER-T), 34 and 55% (SEER-V), respectively; the C-index of this nomogram in predicting CSS was higher than that in the 8th TNM staging system (SEER-T, 0.629 vs.0.584, P < 0.
001; SEER-V, 0.609 vs.0.576, P < 0.
001).In addition, the PS might be a significant negative indictor on CSS of patients with white patients [unadjusted hazard ration (HR) 1.008, P < 0.001], black patients (unadjusted HR 1.
007, P < 0.001), and Asian or Pacific Islander (unadjusted HR 1.008, P = 0.008).
In cases with squamous cell carcinoma (unadjusted HR 1.008, P < 0.001) or adenocarcinoma (unadjusted HR 1.008, P < 0.
001), PS yazhi design saree also might be a significant risk factor.Conclusions: For post-pneumonectomy NSCLC patients, the nomogram may predict their survival with acceptable accuracy and further distinguish high-risk patients from low-risk patients.