STUDY OF MULTI-CENTER CLINICAL TRIALS

多中心临床试验（MCCT）是临床试验的重要工具。 临床研究人员的设备。 多个站点使用共同的 评估治疗安全性和疗效的治疗方案 MCCT。 如果感兴趣的疾病相对罕见，MCCT 可以 在短时间内招募所需数量的样本患者。 尽管各中心遵循相同的临床方案，但 临床中心可能是变异性的重要来源。 当 分析数据时，必须对行为做出假设 临床中心设置。 具体来说，中心集的行为是否 是固定效应还是随机效应？ 如果将中心集视为 随机且设置的中心数较少，对评估的影响 治疗效果可能会受到严重影响。 本研究的目的 是为了证明临床中心组的可变性 会影响治疗效果的解释。 在第一个模型中，我们改变了中心的数量，但保持了平均值 和治疗效果常数的方差。 如果有五个中心 使用后，无论何种情况，治疗效果均具有统计学显着性 中心集是否被视为随机效应或固定效应。 当中心数量从五个减少到两个时，治疗 在固定效应模型中具有统计显着性，但是 在随机效应模型中不显着。 在第二次模拟中， 我们改变了每个治疗组反应之间的平均差异 医疗中心，治疗的固定效应显着 模型。 该治疗在随机效应模型中不显着， 在第三次模拟中，我们改变了治疗组的方差 每个医疗中心的响应。 在固定效应模型中，治疗 意义重大。 在随机效应模型中，治疗是 不显着。 模拟研究显示治疗效果存在显着差异 取决于该组中心是否被视为具有固定和 随机效应。 解释结果需要理解和 指导数据分析的假设的合理性。

The Multi-Center Clinical Trial (MCCT) is an important tool in the clinical researcher's armamentarium. Multiple sites using a common treatment protocol to assess treatment safety and efficacy characterize the MCCT. If the disease of interest is relatively rare, an MCCT can enroll the desired number of sample patients in a short period of time. Even though centers follow the same clinical protocol, the set of clinical centers may be a significant source of variability. When analyzing the data, assumptions must be made regarding the behavior of the clinical centers set. Specifically, does the set of centers behave as a Fixed or Random effect? If the set of centers is regarded as random and the set number of centers is small, the effect on assessing treatment results may be seriously affected. The purpose of this study was to demonstrate how the variability of the set of clinical centers can affect the interpretation of the effect of treatment. In the first model, we varied the number of centers but held the mean and variance of the treatment effect constant. If five centers were used, treatment effect was statistically significant regardless of whether the set of centers was treated as a random or fixed effect. When the number of centers was decreased from five to two, treatment was statistically significant in the fixed effects model, but non-significant in the random effects model. In the second simulation, we varied the mean difference between treatment group response in each medical center, and treatment was significant in the fixed effects model. The treatment was non-significant in the random effects model, In the third simulation, we varied the variance of treatment group response in each medical center. In the fixed effects models, treatment was significant. In the random effects model, treatment was non-significant. Simulation studies revealed significant differences in treatment effect depending on whether the set of centers was treated as having fixed and random effects. Interpreting the results requires an understanding and justification of the assumptions guiding the data analyses.