Objective To analyze the expression differences of FoxP3 protein in papillary thyroid carcinoma (PTC) and nodular goiter, and to explore the correlation between FoxP3 and the clinicopathological characteristics of PTC patients and the therapeutic dose of 131I. Methods Immunohistochemical method was used to detect the expression of FoxP3 protein in 128 cases of PTC tissues (42 cases were treated with 131I after operation) and 20 cases of nodular thyroid tissues, and the relationship between it and the clinicopathological characteristics of PTC patients and the dose of 131I treatment was also analyzed. Results The positive rate of FoxP3 protein expression in PTC tissues was 46.09%, which was higher than that in nodular goiter tissues (0.00%), and the difference was statistically significant (P<0.001). The expression of FoxP3 protein in PTC was correlated with gender, extraglandular invasion and tumor diameter (P values were 0.041, 0.039, and 0.007, respectively), but had no correlation with age, capsular invasion, TNM staging, lymph node metastasis, and distant metastasis (P>0.05). The results of binary logistic regression analysis suggest that tumor diameter was an independent risk factor affecting FoxP3 protein expression [OR=0.389, 95%CI (0.180, 0.840), P=0.016]. By drawing the receiver operating characteristic (ROC) curve, it was shown that the area under the curve (AUC) was 0.643 when the tumor diameter was 1.05 cm, the sensitivity to predict the increase in FoxP3 protein expression was 64.41%, and the specificity was 57.97%, P=0.006. Among 42 patients with PTC who underwent 131I treatment after surgery, the therapeutic dose of 131I was related to the expression of FOXP3 protein (P=0.031). It was shown that patients with positive expression of FoxP3 protein were given more dose of 131I after surgery. Conclusions The positive rate of FoxP3 protein expression in PTC is higher than that of nodular goiter. Its high expression means that the patient has poor pathological characteristics and larger 131I treatment dose, suggesting that FoxP3 may be involved in the malignant progression of PTC.
ObjectiveTo investigate relationship of long non-coding RNA FoxP4-AS1 expression with lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC).MethodsReal time fluorescent quantitative polymerase chain reaction was used to detect the expression level of FoxP4-AS1 in 52 cases of PTC tissues and corresponding adjacent tissues, PTC cells (TPC-1, B-CPAP, K1), and normal thyroid follicular epithelial cells (Nthy-ori3-1). Univariate and multivariate analysis were used to identify the influencing factors of LNM in PTC. Receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of influencing factors of LNM in PTC.ResultsThe expression level of FoxP4-AS1 in the PTC tissues was significantly decreased as compared with the corresponding adjacent tissues (t=7.898, P<0.001), which in the different cells had statistical difference (F=29.866, P<0.001): expression levels in the TPC-1 and K1 cells were lower than Nthy-ori3-1 cells (P<0.05) and in the B-CPAP cells and Nthy-ori3-1 cells had no statistical difference (P>0.05) by multiple comparisons. Univariate analysis showed that the extraglandular invasion (χ2=4.205, P=0.040)and low expression of FoxP4-AS1 (χ2=7.144, P=0.008) were the influencing factors of LNM in PTC. Binary logistic regression analysis showed that extraglandular invasion [OR=9.455, 95%CI (1.120, 79.835), P=0.039] and low expression ofFoxP4-AS1[OR=5.437, 95%CI (1.488, 19.873), P=0.010] were risk factors for LNM of PTC. The area under the ROC curve ofFoxP4-AS1,extraglandular invasion alone, and combination of the two were 0.679, 0.656, and 0.785, respectively.ConclusionsFoxP4-AS1 is down-regulated in PTC. Low level of FoxP4-AS1 is a risk factor for LNM of PTC. Combined detection of expression level of FoxP4-AS1 and extraglandular invasion has a high predictive value for LNM of PTC.
ObjectiveTo evaluate the reporting quality of systematic reviews (SRs)/meta-analyses on acupuncture focusing on literature screening results and explore the influencing factors of the complete reporting.MethodsPubMed, EMbase, CNKI, WanFang Data, and VIP databases were searched to collect SRs/meta-analyses on acupuncture from inception to December 31st, 2019. Two reviewers independently screened literature, extracted data and evaluated the reporting quality of literature screening results of SRs/meta-analyses on acupuncture based on PRISMA statement. Logistic regression model analysis was applied to explore the influencing factors of the complete reporting rate of literature screening results. Statistical analysis was performed by using Excel 2016 and SPSS 16.0 software.ResultsA total of 1 227 SRs/meta-analyses were included. Only 62.3% SRs fully reported the four parts of literature screening results. The parts with a low reporting rate included the number of studies assessed for eligibility (73.2%) and the reasons for exclusions at each stage (67.0%). And the reporting rate of the literature screening flowchart was also low (63.6%). The reporting rate of literature screening results in Chinese SRs was lower than that in English SRs, and there was significantly statistical difference (P<0.001). Multivariate logistic regression analysis showed that the type of published journal, publication year, pages of article and the number of searched databases were correlated with the complete reporting rate of literature screening results (P<0.001).ConclusionsThe complete reporting rate of the literature screening results of SRs on acupuncture is low, especially in Chinese SRs. The complete reporting rate of literature screening results is significantly higher for SRs published after PRISMA statement, in SCI journals, with longer length and more searched databases.
ObjectiveTo establish a hypertension prediction model for middle-aged and elderly people in China and to use the basic public health service database for performance validation. MethodsThe literature related to hypertension was retrieved from the internet. Using meta-analysis to assess the effect value of influencing factors. Statistically significant factors, which were also combined in the database, were extracted as the predictors of the models. The predictors’ effect values were logarithmarithm-transformed as the parameters of the Logit function model and the risk score model. Participants who were never diagnosed with hypertension at the physical examination of health service project of Hongguang Town Health Center in Pidu District of Chengdu from January 1, 2017, to January 1, 2022, were considered as the external validation group. ResultsA total of 15 original studies were involved in the meta-analysis and 11 statistically significant influencing factors for hypertension were identified, including age, female, systolic blood pressure, diastolic blood pressure, BMI, central obesity, triglyceride, smoking, drinking, history of diabetes and family history of hypertension. Of 4997 qualified participants, 684 individuals were identified with hypertension during the five-years follow-up. External validation indicated an AUC of 0.571 for the Logit function model and an AUC of 0.657 for the risk score model. ConclusionIn this study, we developed two different prediction models based on the results of meta-analysis. National basic public health service database is used to verify the models. The risk score model has a better prediction performance, which may help quickly stratify the risk class of the community crowd and strengthen the primary-level assistance system.