방법 비교

	매칭된 4상 연구	시계열 단절 분석 (Interrupted Time Series, ITS)
분야	역학	인과추론
계열	Process / pipeline	Regression model
기원 연도	1980s–1990s (formalized in post-marketing regulatory frameworks)	2002
창시자	Regulatory tradition (FDA, EMA); matching methodology from Rosenbaum & Rubin (1983)	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
유형	Observational study design	Quasi-experimental segmented regression
원전	Strom, B. L., & Kimmel, S. E. (Eds.). (2005). Textbook of Pharmacoepidemiology. Wiley. ISBN: 978-0470029244	Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355.
별칭	matched post-marketing surveillance study, Phase IV matched cohort study, matched pharmacoepidemiological study, post-authorization matched safety study	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
관련	5	5
요약	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.	Interrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope.