Objective To assess efficacy of mepivacaine on local anesthesia in dentistry and oral surgery and its safety. Methods Parallel group, stratified randomization, double blinded, muti-center clinical trial was designed. Two percent lidocaine with adrenaline in same cartridge was as control. Healthy patients with deep decay, pulpitis needed operative dentistry, or indication for extraction of the teeth, which located in the maxilla or front part of the mandible were included. Results Except 17 cases, 127 patients fulfilled inclusion criteria: 66 in treatment group and 61 in control group, dental filling for 60 and extraction for 67 cases, male 55 and female 72, average at 38.84 + 12.06 years. Submucous infiltration of 1.5 ml mepivacaine at labial or buccal side of the alveolar process produced onset of anesthesia in the median of 60 seconds which was same as that of lidocaine, anesthesia duration for 146.7 minutes with the median of 125 minutes, permitting painless filling or extractions. In the treatment group 81.82% freed of pain, while 15.15% had slight pain but received no extra local anesthetic for implementation of the treatment procedures, making the successful rate of 96.97%. In the mepivacaine group, 13.64% of the cases had transient elevation of the systolic pressure to the level of 145-162 mmHg, 8.33% diastolic pressure to the level of 91-93 mmHg. Only one case had transient palpitation in half minute after one minute injection of the drug with no medical care needed. All the cardiovascular reactions might result from adrenaline containing in the injections. Conclusion Mepivacaine is an effective, safe and reliable anesthetic agent for dentistry and oral surgery.
In order to improve the efficiency and guarantee the quality of the research of cross-regional multi-center clinical trials, with the combination of WIN 2003 Server IIS, SQL Server 2005 database and ASP.Net programming techniques, the Pocock and Simon minimized randomization system model facing the network was put forward, and this system based on that model was developed. The two sides in this system can achieve cooperation process from screening subjects, random allocation and drug management to filling electronic case report form. Moreover, the customers of this system can also publish official documents, exchange information and take full use of other available assistant functions through the office automation platform.
Objective To compare the balance of simple randomization, stratified blocked randomization and minimization. Methods Monte Carlo technique was employed to simulate the treatment allocation of simple randomization, stratified blocked randomization and minimization respectively, then the balance of treatment allocation in each group and the balance for every prognostic factor were compared. Results The simulation demonstrated that minimization provides the best performance to ensure balance in the number of patients between groups and prognostic factors. Balance in prognostic factors achieved with stratified blocked randomization was similar to that achieved with simple randomization. Conclusion Minimization offers the best balance in the number of patients and prognostic factors between groups.
Objective To introduce the use of Central Randomization System in clinical trials. Methods We discussed the application of Central Randomization System in clinical trials from object management, drug management and user management, and made a brief description of minimization method. Results Central Randomization Systems can guarantee the nnplementation of the scheme of randomization, and can be used in clinical trials with minimization. Conclusion Central Randomization Systems are feasible in clinical trials especially in traditional Chinese medicine and open clinical trials.
This article introduces a dynamical stratified blocked randomized algorithm when the static stratified blocked randomized algorithm is not suitable to resolve the problem caused by uncertain stratified factors and levels during calculation of the sample size at the stage of clinical trial design. Prior to the start of the clinical trial, a list of random numbers is created by blocked randomized algorithm. During field implementation, a block of random numbers is dynamically allocated to a stratify level. Thereafter, a subject is randomized into different groups in that block. The study of Chinese medicine for gastric cancer anemia and blood hypercoagulability is used as an example to illustrate how to design and implement dynamic stratified block randomized algorithm. The results show that the dynamic stratified block randomized algorithm is more flexible and adaptable than the static stratified blocked randomized algorithm. However, its application is more complex and requires higher standards in clinical trials.
Due to the competition of new drug research and clinical requirement, speeding up drug development and marketing requires faster and more flexible clinical trial design that meets the ethical requirements. Different adaptive designs have emerged in clinical trials of different stages and purposes, for trial efficiency improvement. Adaptive design is more widely used in the field of oncology. Compared with traditional design, adaptive design is more complicated and requires higher level of methodology from researchers. Therefore, implementing adaptive design requires careful consideration and adequate preparation. This paper aims to summarize the design of adaptive methods used in different trial stages so as to provide reference for clinical research designers and implementers.
Randomized controlled trial has been the "gold standard" for clinical trials, in which randomization serves as a fundamental principle of clinical trials and plays an important role in balancing covariates. The allocation probability in traditional design is fixed, while that in adaptive randomization can alter during the experiment according to the specified plan to achieve the purposes of balancing the sample size, maximizing the benefit of patient, or balancing covariates etc. In this study, the adaptive randomization methods applied in clinical trials are discussed to explore their advantages and disadvantages for providing reference for the randomization of clinical trials.
Propensity score methods belong to an analytical approach by incorporating the measured covariates and mimicking randomization to enhance the comparability between groups, hence reducing the impact of potential confounding in observational studies. Propensity score methods have been increasingly used in observational studies. This paper illustrates the principle and the methods based on the propensity score, in combination with its application in observational studies. It also compares results from propensity score methods with those from multivariable regression and randomized controlled trials. It was found that currently there has been a lack of recommendations for the selection of propensity score methods. Differences may exist when comparing results from propensity score methods with findings from typical regression analyses and randomized controlled trials.
Mendelian randomization is a special type of instrumental variable analysis. Its application in the medical field increases in popularity because of its obvious advantages and the rapid development of genomics. This article aimed to introduce the basic concepts, principles, common methods, and limitations of Mendelian randomization. It is expected to provide guidance for researchers to conduct Mendelian randomization studies.
Mendelian randomization (MR) studies use genetic variants as instrumental variables to explore the effects of exposures on health outcomes. STROBE-MR (strengthening the reporting of observational studies in epidemiology using Mendelian randomization) assists authors in reporting their MR studies clearly and transparently, and helpfully to improve the quality of MR. This paper interpreted the STROBE-MR, aiming to help Chinese scholars better understand, disseminate, and apply it.