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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and validation of a nomogram for a prognostic model for resected pancreatic ductal adenocarcinoma
Tian-Liang Song1, Fan Zhang1, Chong Zhang2
1Department of Oncology Surgery, Lanzhou University Second Hospital, Lanzhou 730030, China; Gansu Province Key Laboratory of Environmental Oncology, Lanzhou 730030, China.
Background:
Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor. Surgical resection is the most promising therapeutic strategy for PDAC, and how to improve the survival rate remains a vital key point. This study aimed to establish and validate a nomogram for predicting the prognosis of resected PDAC.
Methods:
A total of 174 patients with PDAC who underwent surgical resection at Lanzhou University Second Hospital and the First Affiliated Hospital of Zhengzhou University from January 2012 to July 2022 were enrolled. The clinicopathological characteristics and survival data were analyzed by R software (version 4.1.3). Univariate and multivariate Cox regression analyses were used to analyze the effects of clinicopathological characteristics on overall survival (OS).
Results:
Multivariate Cox regression showed that carbohydrate antigen 19-9 (CA19-9) ≥ 476 U/mL, carbohydrate antigen 125 (CA125) ≥ 32 U/mL, fasting blood glucose (FBG) < 6.86 mmol/L, aspartate aminotransferase (AST) ≥ 107 U/L, positive surgical margin, and more than 4 cycles of postoperative chemotherapy were independent prognostic factors for OS. Patients were divided into the high-risk and low-risk groups based on the median risk score calculated by multivariate Cox regression analysis. Kaplan-Meier survival curves revealed that the 5-year survival rates of the high-risk and low-risk groups in the training cohort were 5.8% and 24.3%, respectively, and those in the validation cohort were 0 and 19.0%, respectively (P < 0.05). Receiver operating characteristic (ROC) curve analysis revealed that area under the ROC curve (AUC) of the risk score in the training set and the validation set were 0.855 and 0.838, respectively. The C-indexes of the nomogram in the training set and validation set were 0.788 (95% CI: 0.745-0.831) and 0.773 (95% CI: 0.718-0.828), respectively.
Conclusions:
We developed a nomogram that predicts OS in patients with resected PDAC, and the validation results showed that the nomogram model had a strong predictive ability. Particularly, FBG < 6.86 mmol/L and more than 4 cycles of postoperative chemotherapy can predict better OS of PDAC after surgery.
