Development and validation of a novel prognostic model for patients with surgically resected esophageal squamous cell carcinoma

作者全名："Hu, Haiyang; Zhang, Jun; Yan, Hang; Qin, Chao; Guo, Haiyang; Liu, Tao; Tang, Shengjie; Zhou, Haining"

作者地址："[Hu, Haiyang; Zhang, Jun; Yan, Hang; Qin, Chao; Guo, Haiyang; Liu, Tao; Tang, Shengjie; Zhou, Haining] Chongqing Med Univ, Suining Cent Hosp, Dept Thorac Surg, Affiliated Hosp, Suining, Peoples R China; [Hu, Haiyang; Zhang, Jun; Yan, Hang; Qin, Chao; Liu, Tao; Zhou, Haining] Zunyi Med Univ, Inst Surg, Grad Sch, Zunyi, Peoples R China; [Guo, Haiyang] Chengdu Univ TCM, Inst Surg, Grad Sch, Chengdu, Peoples R China"

通信作者："Zhou, HN (通讯作者)，Chongqing Med Univ, Suining Cent Hosp, Dept Thorac Surg, Affiliated Hosp, Suining, Peoples R China.; Zhou, HN (通讯作者)，Zunyi Med Univ, Inst Surg, Grad Sch, Zunyi, Peoples R China."

来源：FRONTIERS IN ONCOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:000848558000001

JCR分区：Q2

影响因子：4.7

年份：2022

卷号：12

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：esophageal squamous cell carcinoma; prognostic model; nomogram; overall survival; following esophagectomy

摘要："Background and objectivesEsophageal squamous cell carcinoma (ESCC) is the most common pathological type of esophageal malignancy in most regions of the world. The study aimed to identify risk factors and develop a predictive model for ESCC following surgical resection. Patients and methodsA total of 533 ESCC patients who underwent surgical resection from Suining Central Hospital were enrolled in the study. Cox proportional hazards regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to identify significant prognostic factors. A prognostic model was constructed, and the receiver operating characteristic (ROC) curve, concordance index (C-index), and decision cure analysis (DCA) were used to evaluate the discrimination and calibration of the prognostic model. Subsequently, we built a nomogram for overall survival (OS) incorporating the prognostic factors, and a calibration plot was employed to assess the consistency between the predicted survival and the observed survival. Based on the model risk score, we split the patients into two subgroups, low-risk and high-risk, and we analyzed the survival time of these two groups using Kaplan-Meier (K-M) survival plots. ResultsFive independent prognosis factors were identified as independent risk factors for OS in ESCC patients who underwent surgical resection. The C-index, ROC curve, and DCA showed that the prognostic model had good predictive accuracy and discriminatory power in the training cohort and validation cohort than other clinical features. A nomogram consisting of prognosis factors showed some superior net benefit. K-M survival plots showed significant differences in OS between the low-risk and high-risk groups. Similar results were observed in the subgroup analysis based on age, grade, and stage. Univariate and multivariate Cox regression analyses revealed that both risk score and risk group are independent prognostic factors in the patient cohort. ConclusionsThis study put forward a novel prognostic model based on clinical features; biopsy data and blood biomarkers may represent a promising tool for estimating OS in ESCC patients."

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