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Μελέτη Φάσης IV με Ζεύγη×Αντίστροφη Πιθανότητα Στάθμισης Θεραπείας (IPW / IPTW)×
ΠεδίοΕπιδημιολογίαΑιτιακή Συμπερασματολογία
ΟικογένειαProcess / pipelineRegression model
Έτος προέλευσης1980s–1990s (formalized in post-marketing regulatory frameworks)2000
ΔημιουργόςRegulatory tradition (FDA, EMA); matching methodology from Rosenbaum & Rubin (1983)Robins, Hernán & Brumback
ΤύποςObservational study designCausal inference weighting estimator
Θεμελιώδης πηγήStrom, B. L., & Kimmel, S. E. (Eds.). (2005). Textbook of Pharmacoepidemiology. Wiley. ISBN: 978-0470029244Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗
Εναλλακτικές ονομασίεςmatched post-marketing surveillance study, Phase IV matched cohort study, matched pharmacoepidemiological study, post-authorization matched safety studyIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Συναφείς55
ΣύνοψηA 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.Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.
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ScholarGateΣύγκριση μεθόδων: Matched Phase IV Study · Inverse Probability Weighting. Ανακτήθηκε στις 2026-06-18 από https://scholargate.app/el/compare