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使用个体条件概率预测哮喘恶化的未来风险。

Predicting future risk of asthma exacerbations using individual conditional probabilities.

机构信息

Division of Respiratory Medicine, Department of Paediatrics, Inselspital and University of Bern, Bern, Switzerland.

出版信息

J Allergy Clin Immunol. 2011 Jun;127(6):1494-502.e3. doi: 10.1016/j.jaci.2011.01.018. Epub 2011 Feb 18.

Abstract

BACKGROUND

Determination of future risk of exacerbations is a key issue in the management of asthma. We previously developed a method to calculate conditional probabilities (π) of future decreases in lung function by using the daily fluctuations in peak expiratory flow (PEF).

OBJECTIVE

We aimed to extend calculation of π values to individual patients, validated by using electronically recorded data from 2 past clinical trials.

METHODS

Twice-daily PEF data were analyzed from 78 patients with severe (study A) and 61 patients with poorly controlled (study B) asthma. For each patient, the π value was calculated from 5000 PEF data points simulated based on the correlation and distribution properties of observed PEF. Given an initial PEF, the π value was defined as the probability of a decrease in PEF to less than 80% of predicted value on 2 consecutive days within a month. These probabilities were then compared with actual occurrences of such events and clinically defined exacerbations within the following month.

RESULTS

π Values were related to actual occurrences of decreases in PEF (adjusted R(2) > 0.800 for both studies). Every increase of 10% in π value was associated with an odds ratio of having a future exacerbation of 1.24 (95% CI, 1.07-1.43) for study A and 1.13 (95% CI, 1.02-1.26) for study B, with better sensitivity and specificity than clinic-measured FEV(1).

CONCLUSION

These results from 2 independent datasets with differing asthmatic populations and differing exacerbation criteria provide support that clinically relevant quantification of individual future risk of exacerbations is possible.

摘要

背景

确定哮喘恶化的未来风险是管理哮喘的关键问题。我们之前开发了一种方法,通过使用呼气峰流速(PEF)的日常波动来计算肺功能未来下降的条件概率(π)。

目的

我们旨在通过使用来自过去两项临床试验的电子记录数据来扩展对个体患者的π值计算,并对其进行验证。

方法

对 78 例严重哮喘(研究 A)和 61 例控制不佳的哮喘(研究 B)患者进行了每日两次的 PEF 数据分析。对于每个患者,根据观察到的 PEF 的相关性和分布特性,从 5000 个 PEF 数据点模拟中计算π值。给定初始 PEF,π值定义为在一个月内连续两天 PEF 下降到预测值的 80%以下的概率。然后将这些概率与实际发生的此类事件以及随后一个月内临床定义的恶化进行比较。

结果

π 值与实际发生的 PEF 下降有关(两项研究的调整 R²均大于 0.800)。π 值每增加 10%,未来发生恶化的几率比增加 1.24(95%CI,1.07-1.43),对于研究 A;增加 1.13(95%CI,1.02-1.26),对于研究 B,比临床测量的 FEV1 具有更好的敏感性和特异性。

结论

这两项来自具有不同哮喘人群和不同恶化标准的独立数据集的结果提供了支持,表明可以对个体未来恶化的风险进行临床相关的量化。

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