https://scholars.lib.ntu.edu.tw/handle/123456789/629661
標題: | Bias propagation in network meta-analysis models | 作者: | Li, Hua Shih, Ming-Chieh Song, Cheng-Jie YU-KANG TU |
關鍵字: | Bayesian methods; arm-based model; contrast-based model; network meta-analysis | 公開日期: | 三月-2023 | 出版社: | WILEY | 卷: | 14 | 期: | 2 | 起(迄)頁: | 247 - 265 | 來源出版物: | Research Synthesis Methods | 摘要: | Network meta-analysis combines direct and indirect evidence to compare multiple treatments. As direct evidence for one treatment contrast may be indirect evidence for other treatment contrasts, biases in the direct evidence for one treatment contrast may affect not only the estimate for this particular treatment contrast but also estimates of other treatment contrasts. Because network structure determines how direct and indirect evidence are combined and weighted, the impact of biased evidence will be determined by the network geometry. Thus, this study's aim was to investigate how the impact of biased evidence spreads across the whole network and how the propagation of bias is influenced by the network structure. In addition to the popular Lu & Ades model, we also investigate bias propagation in the baseline model and arm-based model to compare the effects of bias in the different models. We undertook extensive simulations under different scenarios to explore how the impact of bias may be affected by the location of the bias, network geometry and the statistical model. Our results showed that the structure of a network has an important impact on how the bias spreads across the network, and this is especially true for the Lu & Ades model. The impact of bias is more likely to be diluted by other unbiased evidence in a well-connected network. We also used a real network meta-analysis to demonstrate how to use the new knowledge about bias propagation to explain questionable results from the original analysis. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145030334&doi=10.1002%2fjrsm.1614&partnerID=40&md5=8f3085005458d4f31f6703f1e616e950 https://scholars.lib.ntu.edu.tw/handle/123456789/629661 |
ISSN: | 1759-2879 | DOI: | 10.1002/jrsm.1614 |
顯示於: | 流行病學與預防醫學研究所 |
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