Establishment and validation of nomogram model based on perioperative HSP90α and LMR in predicting textbook outcome of intrahepatic cholangiocarcinoma
10.3760/cma.j.cn113884-20240722-00225
- VernacularTitle:基于术前HSP90α、LMR构建预测肝内胆管癌术后教科书式结局的列线图模型及模型评估
- Author:
Jing QI
1
;
Lijiao WANG
;
Xiuping XIAO
;
Hui WANG
;
Chunyan WANG
;
Yanli LIU
;
Tianwen HE
Author Information
1. 承德市中心医院消化内科，承德 067000
- Keywords:
HSP90 heat-shock proteins;
Cholangiocarcinoma;
Lymphocytes;
Monocytes;
Nomograms;
Textbook outcome
- From:
Chinese Journal of Hepatobiliary Surgery
2024;30(11):845-850
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a predictive model based on preoperative heat shock protein 90 alpha (HSP90 alpha) and lymphocyte count/monocyte ratio (LMR), for prediction of the textbook outcome (TO) of intrahepatic cholangiocarcinoma after surgery, and evaluate the predictive value of the model.Methods:Retrospective analysis of data from 210 patients with intrahepatic cholangiocarcinoma admitted to Chengde Central Hospital from January 2022 to December 2023, including 122 males and 88 females, aged (61.3±5.5) years. The patients were randomly divided into a training set (147 cases) and a validation set (63 cases) according to a ratio of 7: 3. According to whether the patients achieved TO after surgery, the patients in the training set were divided into a TO group ( n=39) and a non-TO group ( n=108). The conditions of tumor length < 5 cm, lymph node metastasis, large vessel invasion, preoperative HSP90α decrease, and preoperative LMR increase were compared between the two groups. Based on the training set, univariate and multivariate logistic regression were used to analyze the influencing factors of postoperative TO in patients with intrahepatic cholangiocarcinoma. Based on multi-factor results, R 4.3.0 software was used to construct a prediction model for TO. The model was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DSA). Results:Multivariate logistic regression analysis showed that the tumor diameter < 5 cm ( OR=1.917, 95% CI: 1.104-4.024), no lymph node metastasis ( OR=2.489, 95% CI: 1.030-3.619), and no invasion of large vessels ( OR=2.565, 95% CI: 2.097-5.093), the decrease of HSP90α before surgery ( OR=3.161, 95% CI: 2.536-5.358), and the increase of LMR before surgery ( OR=2.088, 95% CI: 1.454-4.262) were the influencing factors for patients TO achieve postoperative TO (all P<0.05). A correlation nomogram model was built based on the above indicators. The area under the curve of the model predicting the postoperative TO of the patients in the training set and the test set were 0.875 (95% CI: 0.782-0.938) and 0.860 (95% CI: 0.767-0.912), respectively, indicating good predictive value of the model. The calibration curve was basically consistent with the standard curve, indicating that the model has good consistency and accuracy. DCA results showed that the models had good clinical net benefit in the threshold probability range of 0.1~0.8. Conclusion:The nomogram model based on perioperative HSP90α and LMR has good accuracy and clinical applicability in predicting the possibility of achieving TO after surgery for cholangiocarcinoma, which can provide a reference for clinical treatment.
