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内脏脂肪面积对接受根治性胃切除术患者预后的影响及列线图构建

Effect of visceral fat area on prognosis of patients undergoing radical gastrectomy and construction of nomogram.

作者信息

Huang Zhicheng, Zheng Baohua, Wang Zhiwei, Chen Xiaobin, Wang Yu

机构信息

Department of General Surgery, Fuzhou General Teaching Hospital, Fujian University of Traditional Chinese Medicine, 900th Hospital of Joint Logistics Support Force, Fuzhou, 350025, China.

出版信息

World J Surg Oncol. 2025 Feb 1;23(1):33. doi: 10.1186/s12957-024-03623-y.

Abstract

BACKGROUND

We aim to investigate the impact of visceral fat area (VFA) on the prognosis of patients following radical gastric resection and develop a nomogram prediction model to forecast the prognosis of gastric cancer patients.

METHODS

We retrospectively analyzed 156 patients who underwent laparoscopic radical gastrectomy for distal gastric cancer in the 900th hospital of the Joint Logistics Support Force from April 2018 to April 2020. We collected the CT image data and clinicopathological data one week prior to the operation and then used software to calculate the VFA, dividing it into two groups: a low VFA group (n = 71) and a high VFA group (n = 85). We compared the clinicopathological characteristics and early postoperative complications of the two groups. The Pearson χ test was used to analyze the correlation between body mass index (BMI) and VFA. We used the Kaplan-Meier method to draw the survival curve, analyzed the independent risk factors affecting the prognosis of gastric cancer patients using univariate and multivariate Cox regression models, and established a nomogram model for patient prognosis prediction.

RESULTS

The results of CT showed that VFA value was (95.89 ± 41.40) cm², and body mass index (BMI) was positively correlated with VFA value (r = 0.291, P < 0.001). The ROC curve shows that VFA can predict the prognosis of patients with gastric cancer significantly better than BMI (AUC = 0.826 vs. AUC = 0.707, P = 0.016). The incidence of incision fat liquefaction, pancreatic fistula, and abdominal infection in the high VFA group was higher than that in the low VFA group (P < 0.05). We followed up with all patients for 0.5-48.5 months, with a median follow-up time of 30 months. We used the Kaplan-Meier method to draw the survival curve. The results showed that the overall survival rate of patients in the high VFA group was significantly higher than that in the low VFA group (χ = 38.208, P < 0.001), and the high BMI group was significantly higher than that in the low BMI group (χ = 29.767, P < 0.001). Age, the degree of differentiation, complications after surgery, VFA, ASA grading, and TNM staging were all found to have independent effects on the prognosis of gastric cancer patients (Multivariate Cox regression analysis). Multivariate Cox regression analysis led to the construction of a nomogram prediction model for the total survival of gastric cancer patients. Its internal verification C-index was 0.881 (95% CI: 0.852-0.910), and the calibration chart showed good consistency.

CONCLUSIONS

Age, differentiation degree, postoperative complications, VFA, ASA grading, and TNM staging are independent influencing factors for the prognosis of patients with gastric cancer. The constructed nomogram has excellent prediction accuracy and is helpful to evaluate the prognosis of patients.

摘要

背景

我们旨在研究内脏脂肪面积(VFA)对胃癌根治术后患者预后的影响,并建立列线图预测模型来预测胃癌患者的预后。

方法

我们回顾性分析了2018年4月至2020年4月在联勤保障部队第900医院接受腹腔镜远端胃癌根治术的156例患者。我们收集了术前一周的CT图像数据和临床病理数据,然后使用软件计算VFA,将其分为两组:低VFA组(n = 71)和高VFA组(n = 85)。我们比较了两组的临床病理特征和术后早期并发症。采用Pearson χ检验分析体重指数(BMI)与VFA之间的相关性。我们使用Kaplan-Meier法绘制生存曲线,采用单因素和多因素Cox回归模型分析影响胃癌患者预后的独立危险因素,并建立患者预后预测的列线图模型。

结果

CT结果显示,VFA值为(95.89±41.40)cm²,体重指数(BMI)与VFA值呈正相关(r = 0.291,P < 0.001)。ROC曲线显示,VFA预测胃癌患者预后的能力明显优于BMI(AUC = 0.826 vs. AUC = 0.707,P = 0.016)。高VFA组的切口脂肪液化、胰瘘和腹腔感染发生率高于低VFA组(P < 0.05)。我们对所有患者进行了0.5 - 48.5个月的随访,中位随访时间为30个月。我们使用Kaplan-Meier法绘制生存曲线。结果显示,高VFA组患者的总生存率明显高于低VFA组(χ = 38.208,P < 0.001),高BMI组明显高于低BMI组(χ = 29.767,P < 0.001)。年龄、分化程度、术后并发症、VFA、ASA分级和TNM分期均被发现对胃癌患者的预后有独立影响(多因素Cox回归分析)。多因素Cox回归分析导致构建了胃癌患者总生存的列线图预测模型。其内部验证C指数为0.881(95%CI:0.852 - 0.910),校准图显示出良好的一致性。

结论

年龄、分化程度、术后并发症、VFA、ASA分级和TNM分期是胃癌患者预后的独立影响因素。构建的列线图具有出色的预测准确性,有助于评估患者的预后。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edc1/11786549/5b90fb396e99/12957_2024_3623_Fig1_HTML.jpg

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