학술논문

Nomogram for preoperative estimation of microvascular invasion risk in hepatocellular carcinoma
Document Type
article
Source
Translational Oncology, Vol 45, Iss , Pp 101986- (2024)
Subject
Microvascular invasion
Hepatocellular carcinoma
Multivariable logistic regression
Nomogram
Preoperative
Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
Language
English
ISSN
1936-5233
Abstract
Microvascular invasion (MVI) is an adverse prognostic indicator of tumor recurrence after surgery for hepatocellular carcinoma (HCC). Therefore, developing a nomogram for estimating the presence of MVI before liver resection is necessary. We retrospectively included 260 patients with pathologically confirmed HCC at the Fifth Medical Center of Chinese PLA General Hospital between January 2021 and April 2024. The patients were randomly divided into a training cohort (n = 182) for nomogram development, and a validation cohort (n = 78) to confirm the performance of the model (7:3 ratio). Significant clinical variables associated with MVI were then incorporated into the predictive nomogram using both univariate and multivariate logistic analyses. The predictive performance of the nomogram was assessed based on its discrimination, calibration, and clinical utility. Serum carnosine dipeptidase 1 ([CNDP1] OR 2.973; 95 % CI 1.167–7.575; p = 0.022), cirrhosis (OR 8.911; 95 % CI 1.922–41.318; p = 0.005), multiple tumors (OR 4.095; 95 % CI 1.374–12.205; p = 0.011), and tumor diameter ≥3 cm (OR 4.408; 95 % CI 1.780–10.919; p = 0.001) were independent predictors of MVI. Performance of the nomogram based on serum CNDP1, cirrhosis, number of tumors and tumor diameter was achieved with a concordance index of 0.833 (95 % CI 0.771–0.894) and 0.821 (95 % CI 0.720–0.922) in the training and validation cohorts, respectively. It fitted well in the calibration curves, and the decision curve analysis further confirmed its clinical usefulness. The nomogram, incorporating significant clinical variables and imaging features, successfully predicted the personalized risk of MVI in HCC preoperatively.