He Wenhui, Yu Youzhen, Yan Ziting, Luo Na, Yang Wenwen, Li Fanfan, Jin Hongying, Zhang Yimei, Ma Xiaoli, Ma Minjie
Department of Thoracic Surgery, the First Hospital of Lanzhou University, Lanzhou 730000, Gansu Province, China.
School of Nursing, Gansu University of Traditional Chinese Medicine, Lanzhou730000, Gansu Province, China.
J Cancer. 2024 Apr 23;15(11):3370-3380. doi: 10.7150/jca.92389. eCollection 2024.
The overall survival rate is notably low for esophageal cancer patients with lung metastases (LM), presenting significant challenges in their treatment. 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. In the post-PSM cohort, individuals diagnosed with LM experienced a median overall survival (OS) of 5.0 months (95% confidence interval [] 4.3-5.7), which was significantly lower than those without LM (<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. 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.
对于发生肺转移（LM）的食管癌患者，其总生存率显著较低，这给他们的治疗带来了重大挑战。通过监测、流行病学和最终结果（SEER）计划，纳入了2010年至2015年间被诊断为食管癌的个体。根据食管癌是否转移至肺部，我们使用倾向评分匹配（PSM）来平衡相关变量。倾向评分匹配是我们研究中的关键步骤，有助于将可能的混杂因素对研究结果的影响降至最低。我们使用PSM方法平衡与肺转移相关的变量，以确保研究组和对照组之间进行更准确的比较。具体而言，我们按以下步骤进行PSM。首先，我们进行单因素逻辑回归分析以筛选与肺转移相关的变量。对于每位患者，我们使用逻辑回归模型计算他们的倾向评分，同时考虑几个因素，包括性别、T分期、N分期、手术史、放疗史、化疗史以及骨/脑/肝转移。我们基于倾向评分使用1:1匹配比例，以确保匹配后研究组和对照组之间的基线特征更加平衡。匹配后，我们验证了基线特征的平衡性，以确保混杂因素的影响降至最低。我们使用逻辑回归来识别LM的风险变量，而使用Cox回归来寻找独立的预后因素。然后我们创建列线图，并使用校准曲线、受试者工作特征曲线（ROC）和C指数评估其准确性。在PSM后的队列中，被诊断为LM的个体的中位总生存期（OS）为5.0个月（95%置信区间[4.3 - 5.7]），这显著低于未发生LM的个体（<0.001）。LM与性别、T分期、N分期、手术、放疗、化疗以及骨/脑/肝转移有关。LM的生存期受放疗、化疗以及骨/肝转移的影响。使用ROC曲线、C指数和验证曲线证明了列线图的预测能力。发生LM的患者食管癌存活几率更差。列线图可以有效预测食管癌肺转移的风险和预后。
