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| Monikeskustapausarja× | Monikeskus-kohorttitutkimus× | |
|---|---|---|
| Tieteenala | Epidemiologia | Epidemiologia |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | Mid-to-late 20th century (collaborative multi-site reporting common by 1970s–1980s) | Mid-to-late 20th century (widespread adoption 1970s–1990s) |
| Kehittäjä≠ | Evolved from single-center case series practice; formalized in 20th century clinical reporting | Developed incrementally through large collaborative epidemiological projects (e.g., Framingham Heart Study consortium expansions, 1948 onward; EPIC study, 1992) |
| Tyyppi≠ | Observational descriptive study | Observational longitudinal study |
| Alkuperäislähde≠ | Dekkers, O. M., Vandenbroucke, J. P., Cevallos, M., Renehan, A. G., Altman, D. G., & Egger, M. (2012). COSMOS-E: Guidance on conducting systematic reviews and meta-analyses of observational studies of etiology and prognosis. PLoS Medicine, 9(2), e1001175. link ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Rinnakkaisnimet | multi-site case series, multicentre case series, collaborative case series, multi-institutional case series | multisite cohort study, multi-centre cohort, collaborative cohort study, pooled cohort study |
| Liittyvät≠ | 5 | 6 |
| Tiivistelmä≠ | A multicenter case series is an observational descriptive study in which consecutive or selected patients sharing a defined clinical condition are enrolled and followed at two or more independent clinical sites. By pooling cases across institutions, researchers achieve larger sample sizes and greater demographic and clinical diversity than a single-center series permits, enabling more reliable description of disease presentation, management patterns, and outcomes for rare or uncommon conditions. | 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. |
| ScholarGateAineisto ↗ |
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