Objective According to health technology assessment (HTA) methodology, to assess the efficacy and safety of different doses of metoprolol in the treatment of atrial fibrillation (AF). Methods Based on the principles of HTA, we searched some important medical databases including MEDLINE, EMBASE, The Cochrane Library and CMCC, as well as several national special heart disease databases and side effect centers. We selected eligible studies based on the inclusion and exclusion criteria and critically assessed their quality. Results Intravenous metoprolol 10 mg - 15 mg could control rapid ventricular rate in patients with chronic AF. On either rest or exercise, oral metoprolol 150 mg/d had a better control of rapid ventricular rate than 50 mg/d in patients with chronic AF. For preventing postoperative AF (POAF), the intravenous metoprolol 20 mg group and the 30 mg group could decrease the incidence of POAF compared to the 10 mg group. Oral metoprolol 150 mg/d was more effective than 100 mg/d in preventing POAF. In addition, intravenous metoprolol therapy was well-tolerated and more effective than oral metoprolol therapy in preventing atrial fibrillation after cardiac surgery. Results from several national side effect centers demonstrated that the incidence of adverse reactions associated with metoprolol was low. Conclusion Present evidence showed that high dose of metoprolol was superior to low dose in treating AF, however, the evidence available is insufficient. It is suggested that adequate evidence through further studies are needed. The safety profile of different doses of metoprolol is similar.
Objective To evaluate the effectiveness and safety of different doses of interferon alfa (INF-α) in the treatment of chronic hepatitis C (CHC). Methods Such databases as MEDLINE, EMbase, CENTRAL, CBM, CNKI, VIP and WanFang Data were searched to collect the randomized controlled trials (RCTs) on different doses of INF-α in the treatment of CHC published before August, 2012. According to the inclusion and exclusion criteria, two reviewers independently screened literature, extracted data and evaluated the quality of the included studies, and then meta-analysis was performed using RevMan 5.0 software. Results A total of 13 RCTs involving 1 442 patients were included. The results of meta-analysis on different doses of INF-α showed that, a) There was no significant difference in the complete response rate between the 3 MU dose group and the 1 MU dose group (RR=0.83, 95%CI 0.52 to 1.32, P=0.43), but there was significant difference in the sustained response rate between those 2 groups (RR=1.89, 95%CI 1.00 to 3.59, P=0.05); and b) No significant differences were found in the complete response rate among the 3 MU dose group, the 6 MU dose group, and the 1 MU dose group. Conclusion INF-α in dose of 3 MU, 3 times daily, is effective in treating CHC, but it would not rule out that higher dose takes more effective action. When INF-α is used to treat CHC, an individualized medication should be applied according to patients’ tolerance and economic status.
As a valid method in systematic review, dose-response meta-analysis is widely used in investigating the relationship between independent variable and dependent variable, and which usually based on observational studies. With large sample size, observational studies can provide a reasonable amount of statistical power for meta-analysis. However, due to the design defects of observational studies, they tend to introduce many kinds of biases, which may influence the final results that make them deviation from the truth. Given the dead zone of methodology, there is no any bias adjusting method in dose-response meta-analysis. In this article, we will introduce some bias adjusting methods from other observational-study-based meta-analysis and make them suit for dose-response meta-analysis, and then compare the advantages and disadvantages of these methods.
Dose-response meta-analysis serves an important role in investigating the dose-response relationship between independent variables (e.g. dosage) and disease outcomes. Traditional dose-response meta-analysis model is based on one independent variable to consider its own dose-specific effect on the outcome. However, for drug clinical trials, it generally involves two-dimensions of the treatment, such as dosage and course of treatment. These two-dimensions tend to be associated with each other. When neglecting their correlations, the results may be at risk of bias. Moreover, taking account of the "combined effect” of dosage and time on outcome has more clinical value. Therefore, in this article, based on traditional dose-response meta-analysis model, we propose a three-dimension model for dose-response meta-analysis which considers both the effect of dosage and time, to provide a solution for the above-mentioned problems in a traditional model.
According to the heterogeneity between dose-response data across different studies and the potential nonlinear trend within the dose-response relationship, there are several models for trend estimation from summarized dose-response data, with applications to meta-analysis. However, up to now, there is no guideline of conducting a metaanalysis of dose-response data. After summarizing the previous papers, this paper focuses on how to select the right model for conducting a meta-analysis of dose-response data based on the heterogeneity across different studies, the goodness of fit, and the P value of overall association between exposure and event. Then a preliminary statistical process of conducting a meta-analysis of dose-response data is proposed.
Restricted cubic spline function is an ideal model in trend approximation, which is widely used in doseresponse meta-analysis. The spline function, based on parameter technique, is a smoothly joined piecewise polynomial of each knot, with a cubic polynomial in each sub-interval of the slope which fits well in the non-linear trend by changing the number and (or) the sites of the knots. We have introduced the methodology of linear and non-linear slope model in dose-response meta-analysis in the previous article, and in this one, we will give a more detailed discussion on restricted cubic spline function mainly in the following aspects: model building, parameters pooling and knots selecting.
ObjectiveTo investigate the therapeutic effects of different doses of tanshinone ⅡA microemulsion on radioactive lung injury. MethodsSeventy-two Wistar rats were randomly divided into a healthy control group,a model group,a liposome microemulsion treatment group,a tanshinone ⅡA microemulsion high-dose group,a tanshinone ⅡA microemulsion middle-dose group,and a tanshinone ⅡA microemulsion low-dose group.Radiation-induced lung injury model was established by irradiation of radiotherapy instrument.In addition to the control group,other groups received 6MV X radiation with one dosage of 22Gy.Four rats in each group were sacrificed on 7th,14th,and 28th day,respectively.Lung tissues were sampled to analyze the pathological changes by HE staining and the Smad7 mRNA expression by RT-PCR.The level of glutathione(GSH)in peripheral blood was determined by ultraviolet spectrophotometric method. ResultsIn the model group and four treatment groups,lung tissue biopsy showed the pathological changes gradually from pulmonary alveolitis to fibrosis.The level of Smad7 mRNA in lung tissue and GSH in peripheral blood were higher in the high-dose group,the middle-dose group and the low-dose group than those in the model group at all time points(P<0.05),and were highest in the high-dose group.There was no significant differences in the level of Smad7 mRNA in lung tissue and GSH in peripheral blood between the liposome microemulsion treatment group and the middle-dose group. ConclusionTanshinone ⅡA microemulsion has treatment effect on lung injury in a dose dependent manner.
Does-response meta-analysis, which has being developed for more than 30 years, is a type of regression function and can be both linear and non-linear model. It plays an important role in investigating the relationship between dependent and independent variable. With its special advantages, dose-response meta-analysis has been widely used in evidence-based practice and decision. Currently there are several models can be used to perform dose-response metaanalysis with various advantages and disadvantages. It is vital to choose best model to perform dose-response metaanalysis in evidence-based practice. In this paper, we briefly introduce and summarize the methodology of dose-response meta-analysis.
This article reviews Chinese nomenclature of renal replacement therapy and extracorporeal blood purification currently utilized to manage acute kidney injury and other organ dysfunction syndromes in critically ill patients, based on the recent reports of a consensus expert conference of Nomenclature Standardization Initiative Alliance. We provide a detailed description of the performance characteristics of membranes, filters, transmembrane transport of solutes and fluid, flows, and methods of measurement of delivered treatment, common definitions, components, techniques, and operations of the machines and platforms as well as the renal replacement therapy techniques in detail with the relevant technologies, procedures, operations, and recent developments in other extracorporeal therapies, including therapeutic plasma exchange, multiple organ support therapy, liver support, lung support, and blood purification in sepsis. We believe this nomenclature review will serve future use of terminology in publications, research, clinical operations and therapy platforms to enable consistent data collection and comparison.
Dose-response relationship model has been widely used in epidemiology studies, as well as in evidence-based medicine area. In dose-response meta-analysis, the results are highly depended on the raw data. However, many primary studies did not provide sufficient data and led the difficulties in data analysis. The efficiency and response rate of collecting the raw data from original authors were always low, thus, evaluating and transforming the missing data is very important. In this paper, we summarized several types of missing data, and introduced how to estimate the missing data and transform the effect measure using the existed information.