Should the number of acute exacerbations in the previous year be used to guide treatments in COPD?
Should the number of acute exacerbations in the previous year be used to guide treatments in COPD?
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上一年的急性加重次数是否应用于指导COPD的治疗？
DOI：
10.1183/13993003.02122-2020
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发表时间：
2021-03
期刊：
影响因子：
--
通讯作者：
Sin DD
中科院分区：
文献类型：
--
作者：
Sadatsafavi M;McCormack J;Petkau J;Lynd LD;Lee TY;Sin DD
在慢性阻塞性肺疾病 (COPD) 的当代治疗中，基于 12 个月 COPD 急性加重 (AECOPD) 病史的频繁加重表型是治疗建议的主要决定因素。然而，关于这种表型随时间的稳定性存在相当多的争论。我们使用事件发生时间分析的基本原理来证明频繁加重表型的变异有两个主要来源：潜在 AECOPD 发生率的变异性和个体 AECOPD 发生的随机性。我们重新分析了两个大型队列的数据，即慢性阻塞性肺病纵向评估以识别预测替代终点 (ECLIPSE) 研究和慢性阻塞性肺病亚群和中间结果研究 (SPIROMICS)，使用贝叶斯模型分离了这些变异性来源。然后，我们根据这些结果评估了频繁加剧表型的稳定性。在这两个队列中，AECOPD 的模式强烈支持存在个体特定的潜在 AECOPD 发生率，该发生率随着时间的推移保持稳定（贝叶斯因子小于 0.001）。尽管如此，观察到的 AECOPD 发生率在个体患者中每年可能存在显着差异。对于那些潜在发生率为 0.8–3.1 事件·年−1 的患者，基于观察到的发生率的频繁加重分类在连续两年内由于偶然因素而发生超过 30% 的变化。对于那些潜在发生率为 1.2–2.2 事件·年−1 的事件，该值会增加到 45% 以上。虽然潜在的 AECOPD 发生率是一个稳定的特征，但基于观察到的 AECOPD 模式的频繁加重表型却不稳定，以至于其为治疗决策提供信息的适用性值得质疑。需要评估较长持续时间内的 AECOPD 病史或使用多变量预测模型是否可以导致更稳定的表型分析。根据前一年观察到的事件数量对 COPD 恶化频率进行二分法会导致表型本质上不稳定，以至于它们对于指导治疗决策的适用性应受到严重质疑 https://bit.ly/34nFClc
In contemporary management of chronic obstructive pulmonary disease (COPD), the frequent exacerbator phenotype, based on a 12-month history of acute exacerbation of COPD (AECOPD), is a major determinant of therapeutic recommendations. However, there is considerable debate as to the stability of this phenotype over time. We used fundamental principles in time-to-event analysis to demonstrate that variation in the frequent exacerbator phenotype has two major sources: variability in the underlying AECOPD rate and randomness in the occurrence of individual AECOPDs. We re-analysed data from two large cohorts, the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study and the SubPopulations and InteRmediate OutcoMes In COPD Study (SPIROMICS), using a Bayesian model that separated these sources of variability. We then evaluated the stability of the frequent exacerbator phenotype based on these results. In both cohorts, the pattern of AECOPDs strongly supported the presence of an individual-specific underlying AECOPD rate which is stable over time (Bayes Factor less than 0.001). Despite this, the observed AECOPD rate can vary markedly year-to-year within individual patients. For those with an underlying rate of 0.8–3.1 events·year−1, the frequent exacerbator classification, based on the observed rate, changes more than 30% of the time over two consecutive years due to chance alone. This value increases to more than 45% for those with an underlying rate of 1.2–2.2 events·year−1. While the underlying AECOPD rate is a stable trait, the frequent exacerbator phenotype based on observed AECOPD patterns is unstable, so much so that its suitability for informing treatment decisions should be questioned. Whether evaluating AECOPD history over longer durations or using multivariate prediction models can result in more stable phenotyping needs to be evaluated. Dichotomisation of COPD exacerbation frequencies based on observed number of events in the previous year results in phenotypes that are inherently unstable, so much so that their suitability for informing treatment decisions should be seriously questioned https://bit.ly/34nFClc
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发表时间：
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影响因子：
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