Purpose To establish a reliable nomogram model to predict the risk of major adverse pregnancy outcomes in pregnant women with adenomyosis, and to provide a reference tool for the hierarchical management and the prenatal examination of pregnant women.
Methods We collected the clinical data of pregnant women with adenomyosis who were treated in the First Affiliated Hospital of Chongqing Medical University and the Women and Children’s Hospital of Chongqing Medical University from January 2014 to June 2020. They were divided into the training cohort and the validation cohort, respectively.
In the training cohort, we screened out risk factors associated with major adverse pregnancy outcomes and established a model, which was subsequently validated.
Results In the training cohort, we found that natural conception or not, type of adenomyosis, previous parity, history of infertility or adverse pregnancy outcomes, history of uterine body surgerywere associated with major adverse pregnancy outcomes of pregnant women with adenomyosis, and based on these factors, a nomogram model was constructed. The calibration curves of the model were well fitted in both the training and validation cohorts. The receiver operating characteristic curve (ROC curve) showed that the area under the curve (AUC) was 0.862 and 0.836 in the training and validation cohorts, respectively. The optimal risk threshold of the model was 0.24, and this threshold can be applied to risk stratification of pregnant women.
Conclusion The nomogram model established in this study can reliably predict the risk of major APO in pregnant women with AD.
We aim to investigate the methylation status, protein expression and clinical significance of the steroidogenic factor-1(SF-1) in endometrial carcinoma (EC), and explore the effect of abnormal methylation of SF-1 on the biological behaviour of EC. Bisulfite sequencing (BSP), western blotting (WB), and immunohistochemical were used to detect the methylation status and protein expression of SF-1 in EC tissues, paracancerous tissues and normal endometrial tissues. DNA methyltransferase inhibitor 5-Aza-CdR were used to treat HEC-1-A cell lines to demethylate SF-1. After treatment, WB and qPCR were used to detect the expression of SF-1 and its downstream target genes. Cell proliferation and apoptosis were detected by the EdU fluorescent labelling method and flow cytometry between the groups. Compared with paracancerous tissues and normal endometrial tissues, the expression of SF-1 protein in EC tissues was significantly increased (P﹤0.05). The percentage of methylated cytosine in the promoter region of the SF-1 gene in EC tissues (8.2%) was significantly lower than that in paracancerous tissues by 40.9% (P<0.05). Compared with the control group, after 5-Aza-CdR treatment, the methylation level of the SF-1 gene was significantly reduced (P﹤0.05), the expressions of SF-1 and its downstream target genes were significantly increased (P <0.05), the cell proliferation was enhanced and the cell apoptosis was significantly reduced (P <0.05). In conclusion, in EC, SF-1 gene was hypomethylated and the expression of SF-1 was increased, which promotes cell proliferation and inhibits cell apoptosis. SF-1 may become a new molecular target for early diagnosis and treatment in EC.
Changes in health-related quality of life (HRQOL) among elderly patients with cancer before and after receiving curative treatment, such as chemotherapy, have always been an important consideration in physician–patient treatment decision-making. Although frailty assessment can help predict the effects of chemotherapy, there is a lack of relevant literature on its effectiveness in predicting post-chemotherapy HRQOL. Therefore, this study investigated the early predictive value of pre-chemotherapy frailty assessment for post-chemotherapy HRQOL among elderly patients with cancer receiving curative chemotherapy. From September 2016 to November 2018, this study enrolled elderly patients with cancer aged ≥ 65 years (N = 178), who were expected to receive chemotherapy at three hospitals in Taiwan. The mean age of patients was 71.70 years (SD = 5.46 years) and half of them were female (n = 96, 53.9%). A comprehensive geriatric assessment was performed to measure frailty in 178 participants one week before receiving chemotherapy (T0). Further, the HRQOL of the elderly patients with cancer was assessed again, four weeks after chemotherapy (T1). After controlling for demographic variables, this study evaluated the predictive value of frailty for HRQOL using a hierarchical regression analysis. A total of 103 (57.9%) participants met the frailty criteria. The results showed that 31.1%–56.7% of the variance in the seven domains of HRQOL could be explained by demographic variables and the presence or absence of frailty. This suggests that the presence or absence of frailty is an important predictor of the illness burden domain (β = 9.5; p < .05) of HRQOL. Frailty affects the illness burden domain of HRQOL in elderly patients with cancer. Finally, the administration of frailty assessments before treatment is recommended as a reference for patient treatment decision-making.
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