So sánh phương pháp

	Nghiên cứu Giai đoạn IV Đối sánh	Thiết kế Nghiên cứu Trường hợp-Đối chứng
Lĩnh vực	Dịch tễ học	Dịch tễ học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1980s–1990s (formalized in post-marketing regulatory frameworks)	1950s (formal methodology); precursors in the 1920s
Người khởi xướng	Regulatory tradition (FDA, EMA); matching methodology from Rosenbaum & Rubin (1983)	Janet Lane-Claypon (early precursors, 1926); formalized by Brian MacMahon and Jerome Cornfield in the 1950s–1960s
Loại	Observational study design	Observational analytic study design
Công trình gốc	Strom, B. L., & Kimmel, S. E. (Eds.). (2005). Textbook of Pharmacoepidemiology. Wiley. ISBN: 978-0470029244	Schlesselman, J.J. (1982). Case-Control Studies: Design, Conduct, Analysis. Oxford University Press. ISBN: 978-0195027860
Tên gọi khác	matched post-marketing surveillance study, Phase IV matched cohort study, matched pharmacoepidemiological study, post-authorization matched safety study	case-referent study, case-control design, retrospective case-control, case-control analysis
Liên quan	5	6
Tóm tắt	A Matched Phase IV study is a post-marketing observational design in which patients who received an approved drug (or intervention) are matched to comparable non-exposed patients — or patients on an alternative therapy — to evaluate real-world safety, effectiveness, or long-term outcomes. Conducted after regulatory approval, it combines the epidemiological rigour of matching with the breadth of post-authorization pharmacovigilance, generating evidence that randomized trials are rarely powered or timed to provide.	A case-control study is a retrospective observational design in which individuals who have developed a disease or outcome of interest (cases) are compared with individuals who have not (controls) to determine whether prior exposure to a putative risk factor differs between the two groups. The primary measure of association is the odds ratio, which approximates the relative risk when the outcome is rare. Case-control studies are especially efficient for investigating rare diseases and generating etiological hypotheses.