We read with interest the article of recent advances in clinical practice of hepatocellular carcinoma (HCC) treatment by Bruix et al in Gut. 1 In this review, the Barcelona Clinic Liver Cancer (BCLC) Group recommended sorafenib as the standard treatment for BCLC-C stage (advanced stage) HCC. However, application of sorafenib as first treatment for advanced HCC worldwide was low according to a multiregional, large-scale, longitudinal cohort study.2 This may be attributed to some limitations of sorafenib: low response rate, modest survival advantage, complex mechanism underlying acquired resistance and high-level heterogeneity of individual response.3 4 Recently, evidence from an individual patient data meta-analysis of phase III randomised controlled trial showed no improvement in overall survival attributable to sorafenib for HBV-related HCC.5 Therefore, more alternative strategies are highly required.6 Hepatic arterial infusion (HAI) chemotherapy (HAIC) attracted more attentions in recent years due to high response rates and …

MiR-200c inhibits breast cancer proliferation by targeting KRAS

Background: Visual interpretation of ultrasound (US) images alone may not be sensitive enough to detect important features of potentially malignant thyroid nodules. The aim of this study was to develop a radiomics score using US imaging to predict the probability for malignancy of thyroid nodules as compared with the Thyroid Imaging, Reporting, and Data System (TI-RADS) scoring criteria proposed by the American College of Radiology (ACR). Methods: One hundred thirty-seven pathologically proven thyroid nodules from hospital 1 were enrolled as a training cohort, while 95 nodules from hospital 2 served as the validation cohort. A radiomics score using US images was developed from the training cohort. Two junior and two senior radiologists reviewed all images and scored each nodule according to the 2017 updated ACR TI-RADS scoring criteria. Univariate logistic regression analysis was used to develop the prediction models based on the radiomics score and ACR scores. The performance of the models was evaluated and compared with respect to discrimination, calibration, and clinical application in the validation cohort. Results: Univariate regression indicated that the radiomics score and ACR scores were predictors for thyroid nodule malignancy (all p < 0.001). Five prediction models were built based on the above scores. The radiomics score showed good discrimination with an AUC of 0.921 in the training cohort and 0.931 in the validation cohort, which was significantly better than the ACR scores of junior radiologists in both cohorts. Although five models showed good calibration (all p > 0.05), the model based on the radiomics score presented the lowest errors (E max = 0.073 or E aver = 0.028) in predicting and calibrating probabilities. Decision curve analysis demonstrated that the model using the radiomics score added more benefit than using the ACR scores of junior radiologists. Conclusion: Compared with ACR TI-RADS evaluation by junior radiologists, the radiomics score showed good performance in predicting malignancy of thyroid nodules in our set of histologically verified thyroid nodules from two tertiary hospitals.