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新辅助治疗的局部晚期食管鳞状细胞癌术后房颤的预测列线图

Predictive nomogram for postoperative atrial fibrillation in locally advanced esophageal squamous carcinoma cell with neoadjuvant treatment.

作者信息

Fang Meiqin, Chen Mingduan, Du Xiaoqiang, Chen Shuchen

机构信息

Fujian Key Laboratory of Vascular Aging, Fujian Medical University, Fuzhou, China.

Department of Geriatrics, Fujian Medical University Union Hospital, Fuzhou, China.

出版信息

Front Surg. 2023 Jan 4;9:1089930. doi: 10.3389/fsurg.2022.1089930. eCollection 2022.

DOI:10.3389/fsurg.2022.1089930
PMID:36684273
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9845906/
Abstract

BACKGROUND

Neoadjuvant therapy following minimally invasive esophagectomy is recommended as the standard treatment for locally advanced esophageal squamous carcinoma cells (ESCC). Postoperative atrial fibrillation (POAF) after esophagectomy is common. We aimed to determine the risk factors and construct a nomogram model to predict the incidence of POAF among patients receiving neoadjuvant therapy.

METHODS

We retrospectively included patients with ESCC receiving neoadjuvant chemotherapy (nCT), neoadjuvant chemoradiotherapy (nCRT), or neoadjuvant immunochemotherapy (nICT) following minimally invasive esophagectomy (MIE) for analysis. Patients without a history of AF who did not have any AF before surgery and who developed new AF after surgery, were defined as having POAF. We applied a LASSO regression analysis to avoid the collinearity of variables and screen the risk factors. We then applied a multivariate regression analysis to select independent risk factors and constructed a nomogram model to predict POAF. We used the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve to evaluate the nomogram model.

RESULTS

A total of 202 patients were included for analysis, with 35 patients receiving nCRT, 88 patients receiving nCT, and 79 patients receiving nICT. POAF occurred in 34 (16.83%) patients. There was no significant difference in the distribution of neoadjuvant types between the POAF group and the no POAF group. There was a significant increase in postoperative hospital stay ( = 0.04), hospital expenses ( = 0.01), and comprehensive complication index ( < 0.001). The LASSO analysis screened the following as risk factors: blood loss; ejection fraction (EF); forced expiratory volume in 1 s; preoperative albumin (Alb); postoperative hemoglobin (Hb); preoperative Hb; hypertension; time to surgery; age; and left atrial (LA) diameter. Further, preoperative Alb ≤41.2 g/L ( < 0.001), preoperative Hb >149 g/L ( = 0.01), EF >67.61% ( = 0.008), and LA diameter >32.9 mm ( = 0.03) were determined as independent risk factors of POAF in the multivariate logistic analysis. The nomogram had an area under the curve (AUC) of 0.77. The Briser score of the calibration curve was 0.12. The DCA confirmed good clinical value.

CONCLUSIONS

Preoperative Alb ≤41.2 g/L, LA diameter >32.9 mm, preoperative Hb >149 g/L, and EF >67.61% were determined as the risk factors for POAF among patients with ESCC. A novel and valuable nomogram was constructed and validated to help clinicians evaluate the risk of POAF and take personalized treatment plans.

摘要

背景

微创食管切除术后的新辅助治疗被推荐为局部晚期食管鳞状细胞癌(ESCC)的标准治疗方法。食管切除术后的术后房颤(POAF)很常见。我们旨在确定危险因素并构建列线图模型,以预测接受新辅助治疗的患者中POAF的发生率。

方法

我们回顾性纳入了接受微创食管切除术(MIE)后接受新辅助化疗(nCT)、新辅助放化疗(nCRT)或新辅助免疫化疗(nICT)的ESCC患者进行分析。无房颤病史、术前无任何房颤且术后出现新发房颤的患者被定义为患有POAF。我们应用LASSO回归分析以避免变量的共线性并筛选危险因素。然后我们应用多因素回归分析选择独立危险因素并构建列线图模型以预测POAF。我们使用受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)曲线来评估列线图模型。

结果

共纳入202例患者进行分析,其中35例接受nCRT,88例接受nCT,79例接受nICT。34例(16.83%)患者发生POAF。POAF组和无POAF组之间新辅助治疗类型的分布无显著差异。术后住院时间(=0.04)、住院费用(=0.01)和综合并发症指数(<0.001)显著增加。LASSO分析筛选出以下危险因素:失血量;射血分数(EF);第1秒用力呼气量;术前白蛋白(Alb);术后血红蛋白(Hb);术前Hb;高血压;手术时间;年龄;以及左心房(LA)直径。此外,在多因素逻辑分析中,术前Alb≤41.2 g/L(<0.001)、术前Hb>149 g/L(=0.01)、EF>67.61%(=0.008)和LA直径>32.9 mm(=0.03)被确定为POAF的独立危险因素。列线图的曲线下面积(AUC)为0.77。校准曲线的Briser评分为0.12。DCA证实了良好的临床价值。

结论

术前Alb≤41.2 g/L、LA直径>32.9 mm、术前Hb>149 g/L和EF>67.61%被确定为ESCC患者中POAF的危险因素。构建并验证了一种新颖且有价值的列线图,以帮助临床医生评估POAF的风险并制定个性化治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/814f7899a992/fsurg-09-1089930-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/1b3645042271/fsurg-09-1089930-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/9bdc1613315b/fsurg-09-1089930-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/3e168469fd9a/fsurg-09-1089930-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/814f7899a992/fsurg-09-1089930-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/1b3645042271/fsurg-09-1089930-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/9bdc1613315b/fsurg-09-1089930-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/3e168469fd9a/fsurg-09-1089930-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf26/9845906/814f7899a992/fsurg-09-1089930-g004.jpg

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