考克伦 Q 检验可用于评估诊断准确性研究中似然比的异质性。
Cochran's Q test was useful to assess heterogeneity in likelihood ratios in studies of diagnostic accuracy.
机构信息
INSERM U1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, 53, avenue de l'Observatoire, 75014 Paris, France; Department of Pediatrics, Necker-Enfants Malades Hospital, Assistance Publique-Hôpitaux de Paris, Paris Descartes University, 149, rue de Sèvres, 75015 Paris, France; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, The Netherlands.
INSERM U1153, Obstetrical, Perinatal and Pediatric Epidemiology Research Team, Center for Epidemiology and Biostatistics Sorbonne Paris Cité (CRESS), Paris Descartes University, 53, avenue de l'Observatoire, 75014 Paris, France; Department of Pediatrics, Necker-Enfants Malades Hospital, Assistance Publique-Hôpitaux de Paris, Paris Descartes University, 149, rue de Sèvres, 75015 Paris, France.
出版信息
J Clin Epidemiol. 2015 Mar;68(3):299-306. doi: 10.1016/j.jclinepi.2014.09.005. Epub 2014 Oct 23.
OBJECTIVES
Empirical evaluations have demonstrated that diagnostic accuracy frequently shows significant heterogeneity between subgroups of patients within a study. We propose to use Cochran's Q test to assess heterogeneity in diagnostic likelihood ratios (LRs).
STUDY DESIGN AND SETTING
We reanalyzed published data of six articles that showed within-study heterogeneity in diagnostic accuracy. We used the Q test to assess heterogeneity in LRs and compared the results of the Q test with those obtained using another method for stratified analysis of LRs, based on subgroup confidence intervals. We also studied the behavior of the Q test using hypothetical data.
RESULTS
The Q test detected significant heterogeneity in LRs in all six example data sets. The Q test detected significant heterogeneity in LRs more frequently than the confidence interval approach (38% vs. 20%). When applied to hypothetical data, the Q test would be able to detect relatively small variations in LRs, of about a twofold increase, in a study including 300 participants.
CONCLUSION
Reanalysis of published data using the Q test can be easily performed to assess heterogeneity in diagnostic LRs between subgroups of patients, potentially providing important information to clinicians who base their decisions on published LRs.
目的
实证评估表明，诊断准确性在研究中的患者亚组之间经常表现出显著的异质性。我们建议使用 Cochran's Q 检验来评估诊断似然比（LR）的异质性。
研究设计和设置
我们重新分析了六篇显示诊断准确性存在组内异质性的已发表文献的数据。我们使用 Q 检验来评估 LR 的异质性，并将 Q 检验的结果与基于亚组置信区间的 LR 分层分析的另一种方法的结果进行比较。我们还使用假设数据研究了 Q 检验的行为。
结果
Q 检验在所有六个示例数据集的 LR 中均检测到显著的异质性。Q 检验在 LR 中检测到显著的异质性比置信区间方法更频繁（38%比 20%）。当应用于假设数据时，Q 检验将能够检测到在包括 300 名参与者的研究中，LR 相对较小的变化，约为两倍的增加。
结论
使用 Q 检验重新分析已发表的数据，可以轻松评估患者亚组之间诊断 LR 的异质性，为基于已发表 LR 做出决策的临床医生提供重要信息。
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