Development and validation of radiomics nomogram for metastatic status of epithelial ovarian cancer.

To develop and validate an enhanced CT-based radiomics nomogram for evaluating preoperative metastasis risk of epithelial ovarian cancer (EOC). One hundred and nine patients with histologically confirmed EOC were retrospectively enrolled. The volume of interest (VOI) was delineated in preoperative enhanced CT images, and 851 radiomics features were extracted. The radiomics features were selected by the least absolute shrinkage and selection operator (LASSO), and the rad-score was calculated using the formula of the radiomics label. A clinical model, radiomics model, and combined model were constructed using the logistic regression classification algorithm. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the diagnostic performance of the models. Seventy-five patients (68.8%) were histologically confirmed to have metastasis. Eleven optimal radiomics features were retained by the LASSO algorithm to develop the radiomic model. The combined model for evaluating metastasis of EOC achieved area under the curve (AUC) values of 0.929 (95% CI 0.8593-0.9996) in the training cohort and 0.909 (95% CI 0.7921-1.0000) in the test cohort. To facilitate clinical use, a radiomic nomogram was built by combining the clinical characteristics with rad-score. The DCA indicated that the nomogram had the most significant net benefit when the threshold probability exceeded 15%, surpassing the benefits of both the treat-all and treat-none strategies. Compared with clinical model and radiomics model, the radiomics nomogram has the best diagnostic performance in evaluating EOC metastasis. The nomogram is a useful and convenient tool for clinical doctors to develop personalized treatment plans for EOC patients.

Preoperative alkaline phosphatase-to-platelet count ratio as a prognostic factor for hepatocellular carcinoma with microvascular invasion.

OBJECTIVES: The association between platelet status and hepatocellular carcinoma (HCC) prognoses remains controversial. Herein, we aimed to clarify the prognostic value of multiple platelet-related biomarkers, including platelet count, platelet/lymphocyte ratio (PLR), aspartate aminotransferase to platelet ratio index (APRI), and alkaline phosphatase-to-platelet count ratio index (APPRI) in HCC with microvascular invasion (MVI) after curative resection or liver transplantation. MATERIALS AND METHODS: A retrospective review of 169 patients with solitary HCC and MVI who underwent resection or liver transplantation between January 2015 and December 2018 was conducted. Preoperative clinical, laboratory, pathologic, and imaging data were collected and analyzed. Overall survival (OS) and disease-free survival (DFS) were defined as the clinical endpoints. Univariate and multivariate Cox proportional hazards regression analyses were conducted to investigate potential predictors of DFS and OS. RESULTS: Multivariate Cox regression analyses revealed that maximum tumor diameter, poor cell differentiation, and APPRI were independent predictors of DFS; while poor cell differentiation, APRI, APPRI, prothrombin time, and alpha-fetoprotein were independent prognostic factors for OS. The 1-, 3-, and 5-year DFS rates were 66.90%, 48.40%, and 37.40% for patients with APPRI ≤0.74 and 40.40%, 24.20%,and 24.20% for patients with APPRI>0.74. The corresponding rates of OS over 1, 3, and 5 years were 92.40%, 88.10% and 77.70%, and 72.30%, 38.20%, and 19.10%, respectively. The DFS and OS rates of patients whose APPRI was more than 0.74 were substantially lower than those of patients whose APPRI was less than or equal to 0.74 (p = 0.002 and p < 0.001, respectively). CONCLUSION: Elevated preoperative APPRI is a noninvasive, simple, and easily assessable parameter linked to poor prognosis in individuals with single HCC and MVI after resection or liver transplantation.