Development of a nomogram for overall survival in patients with esophageal carcinoma: A prospective cohort study in China

被引:0
作者
Yu, Shi-Shi [1 ]
Zheng, Xi [1 ]
Li, Xiao-Sheng [2 ]
Xu, Qian-Jie [3 ]
Zhang, Wei [2 ]
Liao, Zhong-Li [1 ]
Lei, Hai-Ke [2 ]
机构
[1] Chongqing Univ, Canc Hosp, Dept Gastroenterol, Chongqing 400030, Peoples R China
[2] Chongqing Univ, Chongqing Canc Multi Big Data Applicat Engn Res Ct, Canc Hosp, 181 Hanyu Rd, Chongqing 400030, Peoples R China
[3] Chongqing Med Univ, Sch Publ Hlth, Dept Hlth Stat, Chongqing 400016, Peoples R China
关键词
Esophageal carcinoma; High-risk factors; Prognosis; Overall survival; Prediction model; SQUAMOUS-CELL CARCINOMA; LYMPHOCYTE RATIO; CANCER; PLATELET; INDEX;
D O I
10.4251/wjgo.v17.i1.96686
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BACKGROUND Esophageal carcinoma (EC) presents a significant public health issue in China, with its prognosis impacted by myriad factors. The creation of a reliable prognostic model for the overall survival (OS) of EC patients promises to greatly advance the customization of treatment approaches. AIM To create a more systematic and practical model that incorporates clinically significant indicators to support decision-making in clinical settings. METHODS This study utilized data from a prospective longitudinal cohort of 3127 EC patients treated at Chongqing University Cancer Hospital between January 1, 2018, and December 12, 2020. Utilizing the least absolute shrinkage and selection operator regression alongside multivariate Cox regression analyses helped pinpoint pertinent variables for constructing the model. Its efficacy was assessed by concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). RESULTS Nine variables were determined to be significant predictors of OS in EC patients: Body mass index (BMI), Karnofsky performance status, TNM stage, surgery, radiotherapy, chemotherapy, immunotherapy, platelet-to-lymphocyte ratio, and albumin-to-globulin ratio (ALB/GLB). The model demonstrated a C-index of 0.715 (95%CI: 0.701-0.729) in the training cohort and 0.711 (95%CI: 0.689-0.732) in the validation cohort. In the training cohort, AUCs for 1-year, 3-year, and 5-year OS predictions were 0.773, 0.787, and 0.750, respectively; in the validation cohort, they were 0.772, 0.768, and 0.723, respectively, illustrating the model's precision. Calibration curves and DCA verified the model's predictive accuracy and net benefit. CONCLUSION A novel prognostic model for determining the OS of EC patients was successfully developed and validated to help clinicians in devising individualized treatment schemes for EC patients.
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页数:12
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