Development and validation of a risk prediction model for occult peritoneal metastasis in patients with colorectal cancer

doi:10.3969/j.issn.1006-7795.2023.01.017

Abstract

Abstract: Objective We aimed to develop and validate a risk prediction model for occult peritoneal metastasis of colorectal cancer (CRC) by using hematologic parameters and clinicopathological features. Methods The data of 710 CRC patients who underwent surgery in Zhongnan Hospital of Wuhan University from July 2015 to July 2021 were retrospectively collected and divided into training set and internal validation set according to the ratio of 3∶1 based on the operation times. A total of 193 CRC patients in Jingzhou Central Hospital of Yangtze University from July 2019 to July 2021 were collected as an independent external validation set. A prediction model was established based on the predictors selected by the least absolute shrinkage and selective operator-Logistic (LASSO-Logistic) algorithm. Based on the model, the nomogram was developed for preoperative prediction of occult peritoneal metastasis of CRC. The performance and clinical benefit of nomogram were validated from the aspects of discrimination, calibration ability and clinical net benefit. Results Six predictors were screened from hematologic parameters and clinicopathological features: tumor pathological type, depth of invasion, imaging ascites, carbohydrate antigen 125 (CA125), carbohydrate antigen 199 (CA199) and D-dimer. The model combining hematological parameter and clinicopathological feature was established. Based on the combination model, a nomogram was constructed for preoperative prediction of occult peritoneal metastasis in CRC. The area under the receiver operating characteristic curve (AUC) of the nomogram were 0.956 (95%CI: 0.936－0.975), 0.891 (95%CI: 0.857－0.925) and 0.901 (95%CI: 0.860－0.942) in the training set, internal validation set and external validation set, respectively. The calibration curve and clinical decision analysis curve verified the good calibration ability and clinical net benefit of the model. In the training set, the Youden index was used to obtain the best cut-off value of 206.6, the sensitivity was 94.3%, the specificity was 86.6%, and the Kappa value was 0.753, indicating that the prediction results of the model had high authenticity and consistency with the actual situation, and the model had good clinical prediction performance. Conclusion A risk prediction model for CRC occult peritoneal metastases was constructed by combining hematological parameters and clinicopathological features. The model has good discrimination, calibration ability and clinical net benefit, which can provide reference for the diagnosis and treatment of CRC occult peritoneal metastases.

Key words: colorectal cancer (CRC), occult peritoneal metastasis, risk prediction model, nomogram, preoperative prediction

CLC Number:

R735.3

Zhong Panyi, Zhang Zilong, Dou Rongzhang, Tao Haoran, Wang Shouchao, Hu Yingchao, Yang Chaogang, Wang Shuyi, Xiong Bin. Development and validation of a risk prediction model for occult peritoneal metastasis in patients with colorectal cancer[J]. Journal of Capital Medical University, doi: 10.3969/j.issn.1006-7795.2023.01.017.

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