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| Studi Kasus-Kontrol Multisentra× | Studi Kohort Multisentris× | |
|---|---|---|
| Bidang | Epidemiologi | Epidemiologi |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | Mid-20th century; multicenter framework formalised 1970s–1980s | Mid-to-late 20th century (widespread adoption 1970s–1990s) |
| Pencetus≠ | Epidemiology convention; seminal statistical framework by Breslow & Day (IARC, 1980) | Developed incrementally through large collaborative epidemiological projects (e.g., Framingham Heart Study consortium expansions, 1948 onward; EPIC study, 1992) |
| Tipe≠ | Observational analytical epidemiological design | Observational longitudinal study |
| Sumber perintis≠ | Breslow, N. E., & Day, N. E. (1980). Statistical Methods in Cancer Research. Volume I: The Analysis of Case-Control Studies. IARC Scientific Publications No. 32. International Agency for Research on Cancer, Lyon. ISBN: 978-9283211327 | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Alias | multisite case-control study, collaborative case-control study, pooled case-control study, multi-institutional case-control study | multisite cohort study, multi-centre cohort, collaborative cohort study, pooled cohort study |
| Terkait | 6 | 6 |
| Ringkasan≠ | A multicenter case-control study is an observational design that identifies individuals who have developed a disease (cases) and disease-free comparators (controls) across two or more study sites simultaneously. By pooling recruitment across hospitals, clinics, or geographic regions, the design achieves larger sample sizes, captures exposure variability over broader populations, and improves the statistical power needed to detect modest odds ratios for rare or heterogeneous diseases. | A multicenter cohort study follows defined groups of participants at two or more geographically or institutionally distinct sites over time to estimate incidence, identify risk factors, and quantify associations between exposures and outcomes. By pooling data from multiple centers, it achieves statistical power and population diversity that single-site designs cannot match, making it the workhorse of large-scale epidemiological and clinical research. |
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