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预测有哮喘症状的学龄前儿童患哮喘:研究的基本原理和设计。

Predicting asthma in preschool children with asthma symptoms: study rationale and design.

机构信息

The Generation R Study Group, Erasmus MC, Rotterdam, The Netherlands.

出版信息

BMC Pulm Med. 2012 Oct 16;12:65. doi: 10.1186/1471-2466-12-65.

DOI:10.1186/1471-2466-12-65
PMID:23067313
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3515509/
Abstract

BACKGROUND

In well-child care it is difficult to determine whether preschool children with asthma symptoms actually have or will develop asthma at school age. The PIAMA (Prevention and Incidence of Asthma and Mite Allergy) Risk Score has been proposed as an instrument that predicts asthma at school age, using eight easy obtainable parameters, assessed at the time of first asthma symptoms at preschool age. The aim of this study is to present the rationale and design of a study 1) to externally validate and update the PIAMA Risk Score, 2) to develop an Asthma Risk Appraisal Tool to predict asthma at school age in (specific subgroups of) preschool children with asthma symptoms and 3) to test implementation of the Asthma Risk Appraisal Tool in well-child care.

METHODS AND DESIGN

The study will be performed within the framework of Generation R, a prospective multi-ethnic cohort study. In total, consent for postnatal follow-up was obtained from 7893 children, born between 2002 and 2006. At preschool age the PIAMA Risk Score will be assessed and used to predict asthma at school age. Discrimination (C-index) and calibration will be assessed for the external validation. We will study whether the predictive ability of the PIAMA Risk Score can be improved by removing or adding predictors (e.g. preterm birth). The (updated) PIAMA Risk Score will be converted to the Asthma Risk Appraisal Tool- to predict asthma at school age in preschool children with asthma symptoms. Additionally, we will conduct a pilot study to test implementation of the Asthma Risk Appraisal Tool in well-child care.

DISCUSSION

Application of the Asthma Risk Appraisal Tool in well-child care will help to distinguish preschool children at high- and low-risk of developing asthma at school age when asthma symptoms appear.This study will increase knowledge about the validity of the PIAMA risk score and might improve risk assessment of developing asthma at school age in (specific subgroups of) preschool children, who present with asthma symptoms at well-child care.

摘要

背景

在儿童保健中,很难确定有哮喘症状的学龄前儿童是否实际上或将来会在学龄期患上哮喘。PIAMA(预防和发生哮喘和螨变应性)风险评分已被提出作为一种工具,使用在学龄前首次出现哮喘症状时评估的八个容易获得的参数来预测学龄期哮喘。本研究的目的是介绍一项研究的原理和设计,该研究旨在:1)对外验证和更新 PIAMA 风险评分;2)开发一种哮喘风险评估工具,以预测有哮喘症状的学龄前儿童(特定亚组)在学龄期的哮喘;3)测试哮喘风险评估工具在儿童保健中的实施情况。

方法和设计

该研究将在 Generation R 框架内进行,这是一项前瞻性的多民族队列研究。共有 7893 名儿童在 2002 年至 2006 年期间出生,其父母同意进行产后随访。在学龄前,将评估 PIAMA 风险评分并用于预测学龄期的哮喘。将评估外部验证的区分度(C 指数)和校准。我们将研究通过去除或添加预测因子(例如早产),PIAMA 风险评分的预测能力是否可以提高。(更新后的)PIAMA 风险评分将转换为哮喘风险评估工具,以预测有哮喘症状的学龄前儿童的学龄期哮喘。此外,我们将进行一项试点研究,以测试哮喘风险评估工具在儿童保健中的实施情况。

讨论

在儿童保健中应用哮喘风险评估工具将有助于区分出现哮喘症状时具有高风险和低风险发展为学龄期哮喘的学龄前儿童。本研究将增加对 PIAMA 风险评分有效性的了解,并可能改善有哮喘症状的学龄前儿童(特定亚组)在学龄期发展为哮喘的风险评估。

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本文引用的文献

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Pediatr Allergy Immunol. 2011 Nov;22(7):652-9. doi: 10.1111/j.1399-3038.2011.01193.x. Epub 2011 Jul 13.
2
Validation of the Asthma Predictive Index and comparison with simpler clinical prediction rules.哮喘预测指数的验证及与更简单的临床预测规则的比较。
J Allergy Clin Immunol. 2011 Jun;127(6):1466-72.e6. doi: 10.1016/j.jaci.2011.03.001. Epub 2011 Mar 31.
3
The Generation R Study: design and cohort update 2010.《生育队列研究:设计与 2010 年队列更新》
Eur J Epidemiol. 2010 Nov;25(11):823-41. doi: 10.1007/s10654-010-9516-7. Epub 2010 Oct 22.
4
Early detection and counselling intervention of asthma symptoms in preschool children: study design of a cluster randomised controlled trial.幼儿哮喘症状的早期检测和咨询干预:一项整群随机对照试验的研究设计。
BMC Public Health. 2010 Sep 15;10:555. doi: 10.1186/1471-2458-10-555.
5
External validity of risk models: Use of benchmark values to disentangle a case-mix effect from incorrect coefficients.风险模型的外部有效性:使用基准值来区分病例组合效应和不正确的系数。
Am J Epidemiol. 2010 Oct 15;172(8):971-80. doi: 10.1093/aje/kwq223. Epub 2010 Aug 31.
6
Predicting the long-term prognosis of children with symptoms suggestive of asthma at preschool age.预测学龄前有哮喘疑似症状儿童的长期预后。
J Allergy Clin Immunol. 2009 Nov;124(5):903-10.e1-7. doi: 10.1016/j.jaci.2009.06.045. Epub 2009 Aug 8.
7
Wheezing in childhood: incidence, longitudinal patterns and factors predicting persistence.儿童喘息:发病率、纵向模式及预测持续存在的因素
Eur Respir J. 2008 Sep;32(3):585-92. doi: 10.1183/09031936.00066307. Epub 2008 May 14.
8
Severity of obstructive airways disease by age 2 years predicts asthma at 10 years of age.2岁时阻塞性气道疾病的严重程度可预测10岁时是否患哮喘。
Thorax. 2008 Jan;63(1):8-13. doi: 10.1136/thx.2006.060616. Epub 2007 Jul 5.
9
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J Clin Epidemiol. 2006 Nov;59(11):1207-12. doi: 10.1016/j.jclinepi.2006.02.011. Epub 2006 Aug 24.
10
Substantial effective sample sizes were required for external validation studies of predictive logistic regression models.预测性逻辑回归模型的外部验证研究需要大量有效的样本量。
J Clin Epidemiol. 2005 May;58(5):475-83. doi: 10.1016/j.jclinepi.2004.06.017.