השוואת שיטות

	ניסוי קליני רב-מרכזי אקראי	מטא-אנליזה של ניסויים קליניים אקראיים
תחום	אפידמיולוגיה	אפידמיולוגיה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1970s–1980s (widespread adoption for large-scale efficacy trials)	1976 (Glass coinage of meta-analysis); 1993 (Cochrane Collaboration formalization)
הוגה השיטה	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)
סוג	Interventional experimental design	Quantitative evidence-synthesis design
מקור מכונן	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
כינויים	multi-site RCT, multicenter RCT, multinational randomized trial, multicenter controlled trial	meta-analytic RCT, MA-RCT, meta-analysis of RCTs, pooled randomized trial analysis
קשורות	6	3
תקציר	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.