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| 多施設用量反応解析× | 用量反応分析× | |
|---|---|---|
| 分野 | 疫学 | 疫学 |
| 系統 | Process / pipeline | Process / pipeline |
| 提唱年≠ | 1992 (foundational trend methods); refined 2000s–2010s | Conceptual roots 16th century; modern epidemiological application mid-20th century |
| 提唱者≠ | Greenland & Longnecker; extended by Orsini et al. | Paracelsus (conceptual foundation); formalized by John Snow and later Bradford Hill |
| 種類≠ | Quantitative epidemiological analysis | Quantitative analytical method |
| 原典≠ | Greenland, S., & Longnecker, M. P. (1992). Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. American Journal of Epidemiology, 135(11), 1301-1309. DOI ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| 別名 | pooled dose-response analysis, multicenter exposure-response analysis, multi-site dose-response modeling, collaborative dose-response study | exposure-response analysis, concentration-response modeling, dose-response modeling, DRA |
| 関連≠ | 2 | 4 |
| 概要≠ | Multicenter dose-response analysis estimates the quantitative shape of the relationship between a graded exposure and a health outcome by pooling data or effect estimates across two or more study centers. Using flexible regression tools such as restricted cubic splines or fractional polynomials within a two-stage meta-analytic framework, it characterizes whether the relationship is linear, supra-linear, threshold-based, or J-shaped — providing far greater statistical power and generalizability than any single center could achieve alone. | Dose-response analysis quantifies the relationship between the magnitude of an exposure (the dose) and the probability or rate of an outcome (the response). It is a core analytical strategy in epidemiology and toxicology, providing evidence that increasing exposure systematically increases — or decreases — the risk of disease. A demonstrated dose-response gradient is one of Bradford Hill's classic criteria supporting causal inference. |
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