Objective To use a meta-analysis method to establish quantitatively the association between the HER-2/neu gene amplification/enhanced protein expression status and the 5-year post-operative survival rate or median survival time in women with epithelial ovarian carcinoma. Methods We searched and screened Chinese and English literature published since 1989 to collect all retrospective cohort studies on the prognostic significance of HER-2/neu status in this population. The survival data were analyzed using Ludwig’s centered signed rank and the DerSimonian-Laird method. Results In total, 25 studies involving 3 251 patients were included. HER-2/neu was positive in 27.1% (95%CI 0 to 54.8%) of patients, which was not related to the pathological stage, type or grade of epithelial ovarian carcinoma. In HER-2/neu positive cases, the median survival time was shortened by 0.65 years, and the 5-year survival rate was lowered. The hazard ratio (HR) for mortality was 1.22 (95%C 1.09 to 1.36). By subgroup analysis, HER-2/neu protein expression was found to be most significant in prognostic assessment. Patients with a b positive value of HER-2/neu had an increased HR for the 5-year survival; and platinum-based chemotherapy was demonstrated to be less effective in HER-2/neu positive ovarian carcinoma. Conclusion In gynecological oncology, it is reasonable to measure HER-2/neu as a routine pathological marker to predict a patient’s prognosis and to determine the most appropriate adjuvant chemotherapy regimen.
ObjectiveTo explore the value of a radiomics model based on ultrasound imaging in predicting the HER-2 status of breast cancer prior to surgery.MethodsA total of 230 patients with invasive breast cancer were retrospectively analyzed, all the patients underwent preoperative breast ultrasound examination. According to the order of examination time, the patients were categorized into training group (n=115) and validation group (n=115). Image J software was used to manually delineate the lesion area in the ultrasound image along the tumor boundary. Pyradiomics was used to extract 1 820 features from each lesion area, and three statistical methods were used to screen features. A logistic regression model was used to construct ultrasound imaging radiomics model. The receive operating characteristic curve (ROC), calibration curve and decision curve were used to evaluate the performance and value of ultrasound imaging radiomics model in predicting HER-2 status.ResultsNine key image features were identified to construct ultrasound imaging radiomics model. The area of under the ROC curve of the model in the training group and the validation group were 0.82 (95%CI 0.74 to 0.90) and 0.81 (95%CI 0.72 to 0.89), respectively. The calibration curve showed that the model had a good calibration in both the training and validation groups.ConclusionsUltrasound-based imaging radiomics model is of significant value in predicting the HER-2 status of breast cancer prior to surgery.