Commentary: Reporting standards are needed for evaluations of risk reclassification.
Commentary: Reporting standards are needed for evaluations of risk reclassification.
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评论：风险重新分类评估需要报告标准。
DOI：
10.1093/ije/dyr083
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发表时间：
2011
影响因子：
7.7
通讯作者：
Janes,Holly
中科院分区：
文献类型：
--
作者：
Pepe,MargaretS;Janes,Holly
近年来已经开发了新的方法来量化通过在一组基线风险预测因子中添加新的标记物所获得的预测性能的改善。Tzoulaki等人的论文1涉及风险重新分类技术，并特别关注净重新分类改进（NRI）指数。他们的综述表明，风险重新分类分析的使用在实践中非常普遍，自引入以来仅3年就发表了51篇使用该技术的论文。令人遗憾和震惊的是，审查表明，报告的质量令人沮丧。调查人员似乎对风险重新分类指标的作用和解释感到困惑。关于如何报告风险重新分类分析结果的指南将有助于作者、评审员和整个领域。风险重新分类表最早是由库克引入的。2该表是通过选择具有临床意义的风险类别，并根据基线风险模型和扩展风险模型计算的风险对个体进行交叉分类而构建的。表1的顶部面板提供了说明。Cook和Ridker 3围绕风险重新分类表开发了一个完整的分析策略，包括新的假设检验和一个名为“正确重新分类百分比”的新指标。然而，这些分析技术的价值是值得怀疑的，结果可能会产生误导。4 Pencina等人5认为，重新分类表本身是有问题的，至少Cook提出的是这样，因为它没有区分发生事件的受试者（病例）和没有发生事件的受试者（对照）。他们建议构建单独的事件和非事件重新分类表，如表1的中间和底部面板所示。对角线上方的线对应于扩展模型与基线模型相比更高的风险，代表对发生事件的受试者的预测改善。相应地，对角线下方的条目表示对它们的较差预测。事件-NRI是事件重新分类表中对角线上方与对角线下方的受试者比例之间的差异。使用类似的逻辑，根据非事件重新分类表计算非事件NRI，方法是取对角线下方与对角线上方受试者比例之间的差异。在Pencina的论文发表后，NRI的总结指数立即在文献中流行起来，
New approaches have been developed in recent years to quantify the improvement in prediction performance gained by adding a novel marker to a set of baseline predictors of risk. The paper by Tzoulaki et al. 1 concerns risk reclassification techniques and focuses specifically on the net reclassification improvement (NRI) index. Their review shows that use of risk reclassification analysis is extremely common in practice, with 51 papers using the technique published in only 3 years since its introduction. Unfortunately and alarmingly, the review shows that the quality of reporting is dismal. Investigators seem confused about the roles and interpretations of risk reclassification metrics. Guidance on how to report results of risk reclassification analysis would be helpful to authors, reviewers and the field in general. The risk reclassification table was first introduced by Cook. 2 The table is constructed by choosing clinically meaningful risk categories and cross-classifying individuals according to their risks calculated with the baseline risk model and with the expanded risk model. The top panel of Table 1 provides an illustration. Cook and Ridker3 developed a whole analysis strategy around the risk reclassification table including new hypothesis tests and a new metric called ‘percent correct reclassification’. However, the value of these analysis techniques is doubtful and results can be misleading. 4 Pencina et al. 5 argued that the reclassification table itself was problematic, at least as proposed by Cook, because it did not distinguish between subjects with events (cases) and subjects without events (controls). They suggested constructing separate event and non-event reclassification tables as shown in the middle and bottom panels of Table 1. Entries above the diagonal correspond to risks that are higher with the expanded vs baseline model, representing improved prediction for subjects with events. Correspondingly, entries below the diagonal represent worse prediction for them. The event-NRI is the difference between the proportions of subjects above vs below the diagonal in the event reclassification table. Using a similar logic, the non-event-NRI is calculated from the non-event reclassification table by taking the difference between the proportions of subjects below vs above the diagonal. The NRI summary index that gained immediate popularity in the literature following Pencina’s paper is the sum,