مقایسهٔ روش‌ها

	آزمایش بالینی تصادفی چندمرکزی	کارآزمایی بالینی تصادفی فراتحلیلی
حوزه	اپیدمیولوژی	اپیدمیولوژی
خانواده	Process / pipeline	Process / pipeline
سال پیدایش	1970s–1980s (widespread adoption for large-scale efficacy trials)	1976 (Glass coinage of meta-analysis); 1993 (Cochrane Collaboration formalization)
پدیدآور	Evolved from single-center RCT methodology; consolidated through landmark trials such as the MRC streptomycin trial (1948) and large cardiovascular mega-trials of the 1970s–1980s	Gene V. Glass (meta-analysis method); Cochrane Collaboration (systematic RCT pooling standards)
نوع	Interventional experimental design	Quantitative evidence-synthesis design
منبع بنیادین	Friedman, L. M., Furberg, C. D., DeMets, D. L., Reboussin, D. M., & Granger, C. B. (2015). Fundamentals of Clinical Trials (5th ed.). Springer. ISBN: 978-3319185385	Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds.). (2019). Cochrane Handbook for Systematic Reviews of Interventions (2nd ed.). Wiley-Blackwell. ISBN: 978-1119536628
نام‌های دیگر	multi-site RCT, multicenter RCT, multinational randomized trial, multicenter controlled trial	meta-analytic RCT, MA-RCT, meta-analysis of RCTs, pooled randomized trial analysis
مرتبط	6	3
خلاصه	A multicenter randomized clinical trial (RCT) is an experimental study in which eligible participants are randomly assigned to intervention or control arms simultaneously across two or more clinical sites. By combining the rigor of randomization with enrollment from geographically or institutionally diverse centers, this design produces large samples and externally valid effect estimates that single-center trials rarely achieve. It is the regulatory gold standard for confirmatory efficacy and safety evaluation of new treatments.	A meta-analytic randomized clinical trial is a formal evidence-synthesis method that identifies, appraises, and statistically combines the results of multiple randomized clinical trials addressing the same clinical question. By pooling trial-level data, it produces a single, more precise estimate of treatment effect and quantifies between-trial heterogeneity, sitting at the apex of the evidence hierarchy for evaluating healthcare interventions.