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Development and Validation of a Machine Learning-Based Nomogram for Prediction of Intrahepatic Cholangiocarcinoma in Patients with Intrahepatic Lithiasis
51 Pages Posted: 13 Dec 2019
More...Abstract
Background: Accurate diagnosis of intrahepatic cholangiocarcinoma (ICC) caused by intrahepatic lithiasis (IHL) is crucial for timely and effective surgical intervention. The aim of the present study was to develop a nomogram to identify ICC associated with IHL (IHL-ICC).
Methods: The study included 2269 patients with IHL, who got pathological diagnosis after hepatectomy or diagnostic biopsy. Machine learning algorithms including Lasso regression and random forest were used to identify important features out of the available features. Univariate and multivariate logistic regression analyses were used to reconfirm the features and develop the nomogram. The nomogram was externally validated in two independent cohorts.
Results: The seven potential predictors were revealed for IHL-ICC, including age, abdominal pain, vomiting, comprehensive imagological diagnosis, alkaline phosphatase, carcinoembryonic antigen (CEA), and cancer antigen (CA) 19-9. The optimal cutoff value was 2.05μg/L for serum CEA and 133.65 U/mL for serum CA 19-9. The accuracy of the nomogram in predicting ICC was 82.6%. The area under the curve (AUC) of nomogram in training cohort was 0.867. The AUC for the validation set was 0.881 from the Second Affiliated Hospital of Wenzhou Medical University, and 0.938 from the First Affiliated Hospital of FuJian Medical University.
Conclusions: The nomogram holds promise as a novel and accurate tool to predict IHL-ICC, which can identify lesions in IHL timely for hepatectomy or avoid unnecessary surgical resection.
Funding Statement: This study was funded by Zhejiang Provincial Top Key Discipline of Surgery Wenzhou Medical University (2008-255).
Declaration of Interests: No conflict of interest exits in the submission of this manuscript.
Ethics Approval Statement: All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board (IRB) of the First Affiliated Hospital of Wenzhou Medical University and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Keywords: Intrahepatic cholangiocarcinoma; intrahepatic lithiasis; risk factors; nomogram; machine learning
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