The clinical respiratory journal · 2023
Investigations of the distant metastatic non-small cell lung cancer without local lymph node involvement: Real world data from a large database.
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Huang Bao-Wen, Wang Wen-Qin, Cai Jing-Sheng, Zhang Su-Wen
Аннотация
INTRODUCTION: This study aimed to investigate the presentations and survival outcomes of the distant metastatic non-small cell lung cancer (NSCLC) without lymph node involvement to obtain a clearer picture of this special subgroup of metastatic NSCLC.
METHOD: A least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis was used to select the prognostic variables. A nomogram and corresponding risk-classifying systems were constructed. The C-index and calibration curves were used to evaluate the performance of the model. Overall survival (OS) curves were plotted using the Kaplan-Meier method, and the log-rank test was used to compare OS differences between groups. Propensity score matching (PSM) was performed to reduce bias.
RESULT: A total of 12 610 NSCLC patients with M1 category (N0 group: 3045 cases; N1-3 group: 9565 cases) were included. Regarding the N0 group, multivariate analysis demonstrated that age, sex, race, surgery, grade, tumor size, and M category were independent prognostic factors. A nomogram and corresponding risk-classifying systems were formulated. Favorable validation results were obtained from the C-index, calibration curves, and survival comparisons. Survival curves demonstrated that N0 NSCLC patients had better survival than N1-3 NSCLC patients both before and after PSM. Furthermore, the survival of resected N0M1 patients was superior to that of those without surgery.
CONCLUSION: In this study, a prognostic nomogram and risk-classifying systems designed for the T1-4N0M1 NSCLC patients showed acceptable performance. Primary lung tumor resection might be a feasible treatment for this population subset. Additionally, we proposed that lymph node stage might have a place in the forthcoming tumor-node-metastasis (TNM) staging proposal for NSCLC patients with M1 category.
METHOD: A least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis was used to select the prognostic variables. A nomogram and corresponding risk-classifying systems were constructed. The C-index and calibration curves were used to evaluate the performance of the model. Overall survival (OS) curves were plotted using the Kaplan-Meier method, and the log-rank test was used to compare OS differences between groups. Propensity score matching (PSM) was performed to reduce bias.
RESULT: A total of 12 610 NSCLC patients with M1 category (N0 group: 3045 cases; N1-3 group: 9565 cases) were included. Regarding the N0 group, multivariate analysis demonstrated that age, sex, race, surgery, grade, tumor size, and M category were independent prognostic factors. A nomogram and corresponding risk-classifying systems were formulated. Favorable validation results were obtained from the C-index, calibration curves, and survival comparisons. Survival curves demonstrated that N0 NSCLC patients had better survival than N1-3 NSCLC patients both before and after PSM. Furthermore, the survival of resected N0M1 patients was superior to that of those without surgery.
CONCLUSION: In this study, a prognostic nomogram and risk-classifying systems designed for the T1-4N0M1 NSCLC patients showed acceptable performance. Primary lung tumor resection might be a feasible treatment for this population subset. Additionally, we proposed that lymph node stage might have a place in the forthcoming tumor-node-metastasis (TNM) staging proposal for NSCLC patients with M1 category.