Retrospective Cohort Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Oct 26, 2022; 10(30): 10882-10895
Published online Oct 26, 2022. doi: 10.12998/wjcc.v10.i30.10882
Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis: A population-based study
Jun-Feng Wang, Hong-Di Lu, Ying Wang, Rui Zhang, Xiang Li, Sheng Wang
Jun-Feng Wang, Hong-Di Lu, Ying Wang, Rui Zhang, Sheng Wang, The First Department of Thoracic Oncology, Jilin Province Tumor Hospital, Changchun 130021, Jilin Province, China
Xiang Li, Big Data Center for Clinical Research, Jilin Province Tumor Hospital, Changchun 130021, Jilin Province, China
Author contributions: Wang JF and Wang S designed the study; Wang JF and Lu HD wrote the manuscript; Wang Y and Zheng R contributed to the data collection; Wang JF, Li X, and Wang S performed the statistical analysis; Li X revised the manuscript; all authors read and approved the final manuscript.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of the Jilin Province Tumor Hospital.
Conflict-of-interest statement: We have no financial relationships to disclose for this article.
Data sharing statement: No additional data are available.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Sheng Wang, MD, PhD, Chief Doctor, The First Department of Thoracic Oncology, Jilin Province Tumor Hospital, No. 1018 Huguang Street, Changchun 130021, Jilin Province, China. wangsh2334@163.com
Received: June 19, 2022
Peer-review started: June 19, 2022
First decision: July 13, 2022
Revised: July 24, 2022
Accepted: September 16, 2022
Article in press: September 16, 2022
Published online: October 26, 2022
Processing time: 123 Days and 12 Hours
Abstract
BACKGROUND

The presence of liver metastasis (LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer (NSCLC) patients. The median overall survival of patients with involvement of the liver is less than 5 mo. At present, identifying prognostic factors and constructing survival prediction nomogram for NSCLC patients with LM (NSCLC-LM) are highly desirable.

AIM

To build a forecasting model to predict the survival time of NSCLC-LM patients.

METHODS

Data on NSCLC-LM patients were collected from the Surveillance, Epidemiology, and End Results database between 2010 and 2018. Joinpoint analysis was used to estimate the incidence trend of NSCLC-LM. Kaplan-Meier curves were constructed to assess survival time. Cox regression was applied to select the independent prognostic predictors of cancer-specific survival (CSS). A nomogram was established and its prognostic performance was evaluated.

RESULTS

The age-adjusted incidence of NSCLC-LM increased from 22.7 per 1000000 in 2010 to 25.2 in 2013, and then declined to 22.1 in 2018. According to the multivariable Cox regression analysis of the training set, age, marital status, sex, race, histological type, T stage, metastatic pattern, and whether the patient received chemotherapy or not were identified as independent prognostic factors for CSS (P < 0.05) and were further used to construct a nomogram. The C-indices of the training and validation sets were 0.726 and 0.722, respectively. The results of decision curve analyses (DCAs) and calibration curves showed that the nomogram was well-discriminated and had great clinical utility.

CONCLUSION

We designed a nomogram model and further constructed a novel risk classification system based on easily accessible clinical factors which demonstrated excellent performance to predict the individual CSS of NSCLC-LM patients.

Keywords: Non-small cell lung cancer; Liver metastasis; Nomogram; Risk classification system

Core Tip: Metastatic disease to distant organs from non-small cell lung cancer (NSCLC) is the main reason for poor survival. The liver is one of the most commonly involved extra-pulmonary sites of metastasis in NSCLC patients. The presence of liver metastasis (LM) is an independent prognostic factor for shorter survival in NSCLC patients. The median overall survival of patients with involvement of the liver is less than 5 mo. At present, identifying prognostic factors and constructing survival prediction nomogram for NSCLC patients with LM (NSCLC-LM) are highly desirable. We aimed to identify independent predictors and further build a novel risk stratification system to predict cancer-specific survival (CSS) of NSCLC-LM patients. To the best of our knowledge, our study was the first Surveillance, Epidemiology, and End Results (SEER)-based study to determine prognostic factors affecting CSS in NSCLC patients with liver involvement.