文献类型：期刊文献

英文题名：Nomograms for Predicting Risk and Survival of Esophageal Cancer Lung Metastases: a SEER Analysis

作者：He, Wenhui[1,2];Yu, Youzhen[1,2];Yan, Ziting[2];Luo, Na[1,2];Yang, Wenwen[1,3];Li, Fanfan[1,2];Jin, Hongying[1,2];Zhang, Yimei[1,2];Ma, Xiaoli[1,4];Ma, Minjie[1,4]

第一作者：He, Wenhui

通信作者：Ma, MJ[1]

机构：[1]Lanzhou Univ, Hosp 1, Dept Thorac Surg, Donggang West Rd, Lanzhou 730000, Gansu, Peoples R China;[2]Gansu Univ Tradit Chinese Med, Sch Nursing, Lanzhou 730000, Gansu, Peoples R China;[3]Lanzhou Univ, Clin Med Coll 1, Lanzhou 730000, Gansu, Peoples R China;[4]Lanzhou Univ, Hosp 1, Gansu Prov Int Cooperat Base Res & Applicat Key Te, Lanzhou 730000, Gansu, Peoples R China

第一机构：Lanzhou Univ, Hosp 1, Dept Thorac Surg, Donggang West Rd, Lanzhou 730000, Gansu, Peoples R China

通信机构：[1]corresponding author), Lanzhou Univ, Hosp 1, Dept Thorac Surg, Donggang West Rd, Lanzhou 730000, Gansu, Peoples R China.

年份：2024

卷号：15

期号：11

起止页码：3370

外文期刊名：JOURNAL OF CANCER

收录：;Scopus(收录号：2-s2.0-85193058932);WOS:【SCI-EXPANDED(收录号:WOS:001246598800011)】；

基金：Acknowledgments The authors would like to thank the participants of this study for their great contribution to this paper. Special thanks to Director Ma Minjie Ma Xiaoli, Head Nurse for her guidance and help in my study. We thank the Department of Thoracic Surgery of the First Hospital of Lanzhou University for providing resources and platforms. Funding Supported by Natural Science Foundation of Gansu Province (23JRRA1597) , Natural Science Foundation of Gansu Province (21JR1RA118) and Gansu Provincial Youth Science and Technology Fund (21JR1RA107, 18JR3RA305) . Data acquisition The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

语种：英文

外文关键词：SEER; esophageal cancer; lung metastasis; nomogram; Cox regression; logistic regression

摘要：Background: The overall survival rate is notably low for esophageal cancer patients with lung metastases (LM), presenting significant challenges in their treatment. Methods: Through the Surveillance, Epidemiology, and End Results (SEER) program, individuals diagnosed with esophageal cancer between 2010 and 2015 were enrolled. Based on whether esophageal cancer metastasized to the lungs, we used propensity score matching (PSM) to balance correlated variables. Propensity score matching was a critical step in our study that helped to minimize the impact of possible confounders on the study results. We balanced variables related to lung metastases using the PSM method to ensure more accurate comparisons between the study and control groups. Specifically, we performed PSM in the following steps. First, we performed a univariate logistic regression analysis to screen for variables associated with lung metastasis. For each patient, we calculated their propensity scores using a logistic regression model, taking into account several factors, including gender, T-stage, N-stage, surgical history, radiotherapy history, chemotherapy history, and bone/brain/liver metastases. We used a 1:1 matching ratio based on the propensity score to ensure more balanced baseline characteristics between the study and control groups after matching. After matching, we validated the balance of baseline characteristics to ensure that the effect of confounders was minimized. We used logistic regression to identify risk variables for LM, while Cox regression was used to find independent prognostic factors. We then created nomograms and assessed their accuracy using the calibration curve, receiver operating curves (ROC), and C index. Results: In the post-PSM cohort, individuals diagnosed with LM experienced a median overall survival (OS) of 5.0 months (95% confidence interval [ CI ] 4.3-5.7), which was significantly lower than those without LM ( P <0.001). LM has been associated to sex, T stage, N stage, surgery, radiation, chemotherapy, and bone/brain/liver metastases. LM survival was affected by radiation, chemotherapy, and bone/liver metastases. The nomograms' predictive power was proved using the ROC curve, C-index, and validation curve. Conclusion: Patients with LM have a worse chance of surviving esophageal cancer. The nomograms can effectively predict the risk and prognosis of lung metastases from esophageal cancer.