Objective To assess the efficacy and safety of lipid-modifying agents for metabolism syndrome.Methods We searched The Cochrane Library, MEDLINE, EMbase, the China Biological Medicine Database, VIP and CMAC to 2007. We also did some handsearching and additional searching. Randomized controlled trials of lipidmodifying therapy for metabolic syndrome were included. Two reviewers independently extracted data from the eligible studies and evaluated the quality of the included studies. Meta-analyses were performed for the results of homogeneous studies using The Cochrane Collaboration’s RevMan 4.2.9 software. Results A total of 11 studies involving 1 422 patients with metabolic syndrome were included. The results indicated that there was no significant difference in TG between rosuvastatin and atorvastatin. However, rosuvastatin was more effective than atorvastatin on HDL-c improvement. Atorvastatin decreased TG levels greater than simvastatin, but simvastatin was superior to atorvastatin in HDL-c improvement. Two trials comparing fenofibrate with placebo were heterogeneous for some outcomes: one found no significant difference in improvements to HOMA-index, but the other trial indicated that fenofibrate was superior to placebo in improving QUICKI. However, the two trials revealed that fenofibrate favorably affected TG [WMD= – 1.77, 95%CI (– 2.21, – 1.33)] and HDL-c [WMD= 6.62, 95%CI (2.07, 11.17)] compared with placebo. No significant differences among atorvastatin, fenofibrate, alone or in combination, were observed in the proportion of metabolic syndrome reduction [RR=0.99, 95%CI (0.84, 1.16); RR=1.03, 95%CI (0.88, 1.20); RR=1.01, 95%CI (0.87, 1.18)]. Atorvastatin plus fenofibrate was superior to atorvastatin alone in TG and HDL-c improvement. Simvastatin-fenofibrate combination produced greater effectiveness in improving of HDL-c and TG compared with simvastatin alone. The fenofibrateorlistat combination was similar to fenofibrate in reducing metabolic syndrome [RR=1.15, 95%CI (0.68, 1.95)] and TG improvement, but was more effective than fenofibrate in HOMA-index improvement. This review of the clinical trials shows that the majority of lipid-modulating drugs did not have favorable effects on FPG, BP, BMI and WC. Six studies reported side effects, showing that the side effects for lipid-regulating drugs were mild to moderate, and well tolerated.Conclusion Our results suggest that lipid-regulating drugs in general exhibit beneficial effects on TG and HDL-c, but not on blood glucose and central obesity. The therapeutic effects of lipid-regulating drugs on blood pressure and insulin sensitivity are uncertain and have no positive effects on FPG, BMI and WC. There is insufficient evidence in this review to recommend the use of lipid-modifying drugs for metabolic syndrome due to low methodological quality, small ssamplesize and limited number of the trials. More high-quality and large-scale randomized controlled trials are required.
Clinical practice is very important in clinical pharmacology education. However, there are some deficiencies in this field in China. Clinical trial institutions in China are medical institutions that are qualified to undertake drug clinical trials. There are hardware and software for clinical pharmacology practice, and high-quality teaching personnel with medical, teaching, and scientific research backgrounds in the clinical trial institutions, which can be used as clinical pharmacology teaching practice bases. Therefore, this article discusses the practice of clinical pharmacology teaching reform using clinical trial institutions as a practical platform, and aims to put forward teaching reform ideas that combining students’ clinical pharmacology research practice on the basis of theoretical teaching.
目的 应用基于链式方程的填补方法处理医学研究中的数据缺失，并以填补后完全数据构建联合指标的logistic判别函数，判断其在前列腺癌的预测诊断中的应用价值。 方法 采用模拟研究，针对现实数据缺失情况模拟不同填补集结果，并以此对现实数据进行填补，以完整数据构建logistic判别，进行分析预测。 结果 填补结果随着填补次数的增加而逐渐接近真实值并趋于稳定。联合年龄、血清前列腺特异性抗原值、血流阻力指数及经直肠前列腺超声检查指标的logistic判别分析结果的灵敏度为82.39%，特异度为74.86%。 结论 联合指标分析可提高前列腺癌的诊断预测水平，以减轻患者穿刺痛苦。
ObjectivesTo explore the value of neural networks (NN) in estimating propensity score, and to compare the performance of propensity score methods based on both logistic regression (LR) and NN.MethodsData sets including ten binary or continuous covariates, binary treatment variable and continuous outcome variable were simulated by SAS 9.2 software, and 5 scenarios differing by non-linear and/or non-additive associations between treatment assignment and covariates were set up. The sample sizes 500, 1000, 2000, 5000 and 10000 were considered. Propensity scores were estimated using either LR or NN model using only partial covariates associated with the outcome (methods LR1, NN1), or all covariates associated with either outcome or treatment (methods LR2, NN2). The average treatment effect (ATE) estimates, standard error (SE), bias, and mean square error (MSE) of ATE among the different models were compared.ResultsThe 95% confidence intervals of the average treatment effect were narrower in NN than that in LR models. SE, bias and MSE increased with the increasing complexity of non-linear and/or non-additive associations between the treatment and covariates, and smaller SE, bias, and MSE were observed in LR1 than LR2, and in NN1 than NN2. NN generally produced less bias than LR under most scenarios when variables associated with the outcome were introduced. SE and MSE decreased with the increasing sample size for both LR and NN models.ConclusionsNN for estimating propensity scores may be less biased and produce more precise estimates for ATE than LR in a meaningful manner when the complex association between treatment and covariates exists.
Objective To assess the tolerability and safety of Yinhuang injection in Chinese healthy volunteers. Methods Thirty-two healthy subjects were enrolled in the single-dose study. Each subject was administered one of the seven doses of 40, 120, 240, 320, 400, 480, and 560 mg, respectively, by intravenous injection. The sample sizes were 2, 4, 6, 6, 6, 4 and 4, respectively, for each dose group. Twelve healthy subjects were enrolled in the multi-dose study. The subjects in the lower dose group were administered 240 mg and the subjects in the higher dose group were administered 400 mg Yinhuang by intravenous injection once a day for consecutive 7 days. The sample sizes for both groups were 6. The safety was evaluated based on clinical symptoms, vital signs, physical examinations, electrocardiogram (ECG), laboratory tests and adverse events. All analyses were performed by using the software package SAS version 9.1. T-test and analysis of variance were used for continuous variables. Chi-square test and Fisher’s exact test were used for categorical variables.Results A total of 44 healthy volunteers completed the tolerance test. No serious adverse event and clinically significant changes in vital signs, ECG and laboratory tests were found in both single-dose groups and multi-dose groups. Among two mild adverse events, dizziness occurred in one subject in 480 mg dose group in the single-dose trial, which was probably related to the experimental drug. Conclusion Yinhuang injection is safe and well-tolerated in Chinese healthy subjects after administration of single-doses (40-560 mg) and multi-doses (240-400 mg once a day for consecutive 7 days). The maximum-tolerated dose of Yinhuang injection is at 560 mg in the single-dose trial. The dose regimen of 240-400 mg a day is recommended for phase II study.