Objective To review randomized controlled trials of blood pressure (BP) lowering therapy on stroke prevention to provide evidence for clinical practice. Methods We searched Medline (1966-2003.6) and the large-sample randomized controlled trials on BP lowering regimen in patients with stroke history were reviewed. Endpoints included the ocurrance of stroke, coronary heart disease and mortality. Results Three trials of PATS, PROGRESS and HOPE were analysed. The review showed that stroke recurrent risk was reduced by 28%, CHD risk decreased by 15% and total mortality risk reduced by 11% in BP lowering treatment group compared with placebo control group. Stroke risk was reduced not only in hypertensive patients with previous cerebrovascular diseases but also in non-hypertensive patients. Conclusions BP lowering therapy is beneficial for the secondary prevention of stroke.
ObjectiveTo systematically evaluate the efficacy of neoadjuvant chemoradiotherapy or chemotherapy followed by surgery versus definitive chemoradiation in stage ⅢA-N2 non-small cell lung cancer (NSCLC).MethodsWe searched PubMed, EMbase, Web of Science and The Cochrane Library to collect clinical studies on the efficacy comparison between neoadjuvant chemoradiotherapy or chemotherapy followed by surgery and definitive chemoradiation in stage ⅢA-N2 NSCLC from inception to September 2022. The meta-analysis was performed by using RevMan 5.3 software.ResultsA total of 9 studies (3 randomized controlled trials and 6 retrospective cohort studies) with 12 801 patients were included. The results of meta-analysis showed that there was no statistical difference in the progression-free survival rate between the inductive treatment followed by surgery (including lobectomy and pneumonectomy) and definitive chemoradiation (HR=0.99, 95%CI 0.86-1.15, P=0.91). Compared with definitive chemoradiation, the overall survival (OS) rate in the inductive treatment followed by surgery (including lobectomy and pneumonectomy) was lower (HR=1.24, 95%CI 1.09-1.42, P=0.001), while the OS rate in the inductive treatment followed by lobectomy was higher (HR=0.55, 95%CI 0.51-0.61, P<0.000 01). And the local recurrence rate in the inductive treatment followed by surgery was reduced (OR=0.44, 95%CI 0.36-0.55, P<0.000 01).ConclusionNeoadjuvant chemoradiotherapy or chemotherapy followed by lobectomy is superior to definitive chemoradiation in OS and it has a lower local recurrence rate, so lobectomy should be one of the multidisciplinary treatments for selected ⅢA-N2 NSCLC patients.
Objective To explore the relationship between obesity and the three targets including blood pressure, glucose, and lipid. Methods A total of 181 adult Tibetans who underwent physical examination between March and September 2015 at Xigaze People's Hospital were enrolled in this study. Their obesity degrees were assessed with body mass index (BMI) and waist circumference (WC) respectively. The levels of blood pressure, glucose, and lipid were compared at the different levels of BMI or WC. Results The incidence of systematic obesity and central obesity in these adults were 57.5% and 79.0%, respectively. Compared the overweight group with the normal BMI group, the systolic pressure and diastolic pressure of the former were 9.26 mm Hg (1 mm Hg=0.133 kPa) [95% confidence interval (CI) (3.46, 15.07) mm Hg, P=0.002] and 7.76 mm Hg [95%CI (3.96, 11.57) mm Hg, P<0.001] higher, respectively. Similarly, the systolic pressure and diastolic pressure of the central obesity group were 8.24 mm Hg [95%CI (1.03, 15.46) mm Hg,P=0.026] and 6.79 mm Hg [95%CI (2.03, 11.55) mm Hg, P=0.006] higher than those in the normal WC group, respectively. For the normal WC or normal BMI subjects, the detection rate of dyslipidemia reached up to 50.0% and 52.6%. Conclusions With the increase of BMI/WC values, the level of blood pressure rises. Even though WC or BMI is normal, the detection rate of dyslipidemia is high.
Objective To explore the independent risk factors for tumor invasiveness of ground-glass nodules and establish a tumor invasiveness prediction model. Methods A retrospective analysis was performed in 389 patients with ground-glass nodules admitted to the Department of Thoracic Surgery in the First Hospital of Lanzhou University from June 2018 to May 2021 with definite pathological findings, including clinical data, imaging features and tumor markers. A total of 242 patients were included in the study according to inclusion criteria, including 107 males and 135 females, with an average age of 57.98±9.57 years. CT data of included patients were imported into the artificial intelligence system in DICOM format. The artificial intelligence system recognized, automatically calculated and output the characteristics of pulmonary nodules, such as standard diameter, solid component size, volume, average CT value, maximum CT value, minimum CT value, central CT value, and whether there were lobulation, burr sign, pleural depression and blood vessel passing. The patients were divided into two groups: a preinvasive lesions group (atypical adenomatoid hyperplasia/adenocarcinoma in situ) and an invasive lesions group (minimally invasive adenocarcinoma/invasive adenocarcinoma). Univariate and multivariate analyses were used to screen the independent risk factors for tumor invasiveness of ground-glass nodules and then a prediction model was established. The receiver operating characteristic (ROC) curve was drawn, and the critical value was calculated. The sensitivity and specificity were obtained according to the Yorden index. Results Univariate and multivariate analyses showed that central CT value, Cyfra21-1, solid component size, nodular nature and burr of the nodules were independent risk factors for the diagnosis of tumor invasiveness of ground-glass nodules. The optimum critical value of the above indicators between preinvasive lesions and invasive lesions were –309.00 Hu, 3.23 ng/mL, 8.65 mm, respectively. The prediction model formula for tumor invasiveness probability was logit (P)=0.982–(3.369×nodular nature)+(0.921×solid component size)+(0.002×central CT value)+(0.526×Cyfra21-1)–(0.0953×burr). The areas under the curve obtained by plotting the ROC curve using the regression probabilities of regression model was 0.908. The accuracy rate was 91.3%. Conclusion The logistic regression model established in this study can well predict the tumor invasiveness of ground-glass nodules by CT and tumor markers with high predictive value.
ObjectiveTo establish a machine learning model based on computed tomography (CT) radiomics for preoperatively predicting invasive degree of lung ground-glass nodules (GGNs). MethodsWe retrospectively analyzed the clinical data of GGNs patients whose solid component less than 3 cm in the Department of Thoracic Surgery of Shanghai Pulmonary Hospital from March 2021 to July 2021 and the First Hospital of Lanzhou University from January 2019 to May 2022. The lesions were divided into pre-invasiveness and invasiveness according to postoperative pathological results, and the patients were randomly divided into a training set and a test set in a ratio of 7∶3. Radiomic features (1 317) were extracted from CT images of each patient, the max-relevance and min-redundancy (mRMR) was used to screen the top 100 features with the most relevant categories, least absolute shrinkage and selection operator (LASSO) was used to select radiomic features, and the support vector machine (SVM) classifier was used to establish the prediction model. We calculated the area under the curve (AUC), sensitivity, specificity, accuracy, negative predictive value, positive predictive value to evaluate the performance of the model, drawing calibration and decision curves of the prediction model to evaluate the accuracy and clinical benefit of the model, analyzed the performance in the training set and subgroups with different nodule diameters, and compared the prediction performance of this model with Mayo and Brock models. Two primary thoracic surgeons were required to evaluate the invasiveness of GGNs to investigate the clinical utility of the model. ResultsA total of 400 patients were divided into the training set (n=280) and the test set (n=120) according to the admission criteria. There were 267 females and 133 males with an average age of 52.4±12.7 years. Finally, 8 radiomic features were screened out from the training set data to build SVM model. The AUC, sensitivity and specificity of the model in the training and test sets were 0.91, 0.89, 0.75 and 0.86, 0.92, 0.60, respectively. The model showed good prediction performance in the training set 0-10 mm, 10-20 mm and the test set 0-10 mm, 10-20 mm subgroups, with AUC values of 0.82, 0.88, 0.84, 0.72, respectively. The AUC of SVM model was significantly better than that of Mayo model (0.73) and Brock model (0.73). With the help of this model, the AUC value, sensitivity, specificity and accuracy of thoracic surgeons A and B in distinguishing invasive or non-invasive adenocarcinoma were significantly improved. ConclusionThe SVM model based on radiomics is helpful to distinguish non-invasive lesions from invasive lesions, and has stable predictive performance for GGNs of different sizes and has better prediction performance than Mayo and Brock models. It can help clinicians to more accurately judge the invasiveness of GGNs, to make more appropriate diagnosis and treatment decisions, and achieve accurate treatment.
ObjectiveThis study aims to conduct a bibliometric analysis of the dataset obtained from a systematic review of Model-Based Meta-Analysis (MBMA) studies to uncover research trends in MBMA. MethodsWe conducted a systematic search across databases including Embase, MEDLINE, Cochrane Library, Web of Science, CNKI, VIP, WanFang Data, and Sinomed. Relevant literature pertaining to MBMA was screened and included. Qualitative and quantitative analyses were performed to assess author contributions, temporal trends, national distribution, and disease prevalence. ResultsA total of 129 articles were included in the analysis, most published in being China (n=48), the United States (n=47), and the United Kingdom (n=7). The time span covered by these articles ranged from 2005 to 2023. A total of 531 researchers contributed to the included studies, with first authors from 15 different countries. The compilation encompassed 402 keywords, with the three most frequently used being “Meta-analysis” (n=28), “Model-based meta-analysis” (n=27), and “Pharmacokinetics” (n=14). The study covered 16 distinct disease categories, with the top three neoplasms (n=16), neurological disorders (n=14), and endocrine and metabolic diseases (n=13). ConclusionBibliometric analysis showed that the number of MBMA studies has increased significantly over the past three years, using a variety of key diseases as carriers. However, this new type of quantitative research has not yet attracted sufficient attention, and the research power is still concentrated in China and the United States; Moreover, a core group of authors has not yet been formed, it is necessary for scholars from various countries to strengthen multidisciplinary cooperation and communication to promote the production and translation of high-quality evidence.