Nicholl Jon
Medical Care Research Unit, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK.
J Epidemiol Community Health. 2007 Nov;61(11):1010-3. doi: 10.1136/jech.2007.061747.
Observational studies comparing groups or populations to evaluate services or interventions usually require case-mix adjustment to account for imbalances between the groups being compared. Simulation studies have, however, shown that case-mix adjustment can make any bias worse. One reason this can happen is if the risk factors used in the adjustment are related to the risk in different ways in the groups or populations being compared, and ignoring this commits the "constant risk fallacy". Case-mix adjustment is particularly prone to this problem when the adjustment uses factors that are proxies for the real risk factors. Interactions between risk factors and groups should always be examined before case-mix adjustment in observational studies.
比较不同组或人群以评估服务或干预措施的观察性研究通常需要进行病例组合调整,以考虑被比较组之间的不平衡。然而,模拟研究表明,病例组合调整可能会使任何偏差变得更糟。出现这种情况的一个原因是,如果调整中使用的风险因素在被比较的组或人群中以不同方式与风险相关,而忽略这一点就犯了“恒定风险谬误”。当调整使用的因素是实际风险因素的替代指标时,病例组合调整特别容易出现这个问题。在观察性研究中进行病例组合调整之前,应始终检查风险因素与组之间的相互作用。