Comparative Study of the Efficacy of the Ovarian-Adnexa Reporting and Data System Ultrasound Combined With Contrast-Enhanced Ultrasound and the ADNEX MR Scoring System in the Diagnosis of Adnexal Masses.

OBJECTIVE: The aims of this study were to develop the Ovarian-Adnexa Reporting and Data System (O-RADS) and O-RADS + contrast-enhanced ultrasound (O-RADS CEUS) scoring system to distinguish adnexal masses (AMs) and to compare the diagnostic efficacy of these systems with that of a magnetic resonance imaging scoring system (ADNEX MR). METHODS: We retrospectively evaluated 278 ovarian masses from 240 patients between May 2017 and July 2022. Pathology and adequate follow-up were used as reference standards for comparing the validity of O-RADS, O-RADS CEUS and ADNEX MR scoring to diagnose AMs. Area under the curve (AUC), sensitivity and specificity were calculated. The inter-class correlation coefficient (ICC) was calculated to evaluate inter-reader agreement (IRA) between the two sonographers and two radiologists who analyzed the findings with the three modalities. RESULTS: The AUCs of O-RADS, O-RADS CEUS and ADNEX MR scores were 0.928 (95% confidence interval [CI]: 0.895-0.956), 0.951(95% CI: 0.919-0.973) and 0.964 (95% CI: 0.935-0.983), respectively. Their sensitivities were 95.7%, 94.3 and 91.4%, and their specificities were 81.3%, 92.3% and 97.1%, respectively. The three modalities had accuracies of 84.9%, 92.8% and 95.7%, respectively. O-RADS had the highest sensitivity but significantly lower specificity (p < 0.001), whereas the ADNEX MR scoring had the highest specificity (p < 0.001) but lower sensitivity (p < 0.001). O-RADS CEUS had intermediate sensitivity and specificity (p < 0.001). CONCLUSION: The addition of CEUS significantly improves the efficacy of O-RADS in diagnosing AMs. The diagnostic efficacy of the combination is comparable to that of the ADNEX MR scoring system.

A prognostic risk model for ovarian cancer based on gene expression profiles from gene expression omnibus database.

This study explored prognostic genes of ovarian cancer and built a prognostic model based on these genes to predict patient's survival, which is of great significance for improving treatment of ovarian cancer. GSE26712 dataset was downloaded from Gene Expression Omnibus database as training set, while OV-AU dataset was downloaded from ICGC website as validation set. All genes in GSE26712 were analyzed by univariate Cox regression, Lasso regression, and multivariate Cox regression analyses. Then prognosis-related feature genes were screened to construct a multivariate risk model. Meanwhile, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed on samples in the high/low-risk groups using Gene Set Enrichment Analysis (GSEA) software. Finally, survival curve and receiver operating characteristic curve were drawn to verify the validity of the model. Ten feature genes related to prognosis of ovarian cancer were obtained: CMTM6, COLGALT1, F2R, GPR39, IGFBP3, RNF121, MTMR9, ORAI2, SNAI2, ZBTB16. GSEA enrichment analysis showed that there were notable differences in biological pathways such as gap junctions and homologous recombination between the high/low-risk groups. Through further verification of training set and validation set, the 10-gene prognostic model was found to be effective for the prognosis of ovarian cancer patients. In this study, we constructed a 10-gene prognostic model which predicted the prognosis of ovarian cancer patients well by integrating clinical prognostic parameters. It may have certain reference value for subsequent clinical treatment research of ovarian cancer patients and help in clinical treatment decision-making.

High expression of survivin predicts poor prognosis in cervical squamous cell carcinoma treated with paclitaxel and carboplatin.

Lack of effective biomarkers is one of the challenges in current neoadjuvant chemotherapy to predict drug response and sensitivity of cervical squamous cell carcinoma (CSCC). The present study was designed to investigate the correlation of the expression of survivin, an inhibitor of apoptosis with the prognosis of CSCC patients undergoing neoadjuvant chemotherapy.A total of 117 CSCC patients treated with paclitaxel and carboplatin between May 2015 and April 2017 in the Second Hospital of Lanzhou University were retrospectively analyzed. The pathologic diagnosis and classification of CSCC were based on the Guidelines of the International Federation of Gynaecology and Obstetrics (FIGO). The efficacy was defined as complete remission (CR), partial remission (PR), and stability disease (SD). The expressions of survivin, vascular endothelial growth factor (VEGF), and Ki67 were determined with immunohistochemistry. Data were analyzed with SPSS software.Univariate analysis showed that survivin expression had no correlation with ages, FIGO stage, macroscopic type, lymphovascular invasion, depth of lymphovascular invasion, lymph node metastasis, and tumor size among 117 CSCC patients. However, survivin expression was positively correlated with pathological grade (R = 0.691, P < .001). Multivariate analysis revealed that survivin expression was independently correlated with grades (P < .001). In addition, the analysis of correlation indicated that survivin expression is positively correlated with VEGF expression (R = 0.820, P < .001) and Ki67 expression (R = 0.673, P < .001). The numbers (percentages) of complete remission (CR), partial remission (PR), and stability disease (SD) were 11 (9.4%), 91 (77.8%), and 15 (12.8%) respectively after the treatment of paclitaxel and carboplatin. Univariate analysis showed that efficacy of treatment was negatively correlated with pathological grade (R = 0.513, P < .001), Ki67 expression (R = 0.586, P < .001), VEGF expression (R = 0.476, P < .001) and survivin expression (R = 0.519, P < .001). Multivariate analysis revealed that efficacy of treatment was independently correlated with grades (P = .028), Ki67 (P < .001), and survivin expression (P = .015).The results suggested that survivin expression is negatively correlated with the prognosis of CSCC patients treated with paclitaxel and carboplatin. Therefore, survivin expression might be a marker for prognosis in CSCC following neoadjuvant chemotherapy.