Department of Medicine, Division of Allergy Pulmonary and Critical Care Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee 37232-8300, USA.
Ann Allergy Asthma Immunol. 2010 Sep;105(3):203-10. doi: 10.1016/j.anai.2010.06.020.
The criteria used to identify persons with asthma in epidemiologic studies are varying and, depending on the method used, can be challenging and resource consuming.
To develop a nomogram (scoring system) to identify adult patients with asthma using a combination of variables collected via a validated questionnaire.
We studied the first 268 women aged 40 to 69 years in the Shanghai Women's Asthma and Allergy Study who reported signs and symptoms of asthma and underwent either methacholine challenge testing or test of reversibility during the asthma screening survey between 2003 and 2007. These women were defined as having definite asthma (n=106) or not (n=162). Multivariable logistic regression analysis was performed to develop a predictive model for identifying asthma using survey information alone.
Clinically relevant questions were used for the predictive multivariable logistic regression model and included the following: ever wheezing or whistling in the chest, current medication use for asthma, self-reported ever asthma, self-reported ever allergic rhinitis, family history of allergy, and age. The area under the receiver operating characteristic curve of the prediction model was 0.75 (95% confidence interval, 0.69-0.81). A nomogram was developed to assess the individual probability of asthma based on individually weighted variables in the predictive model.
In clinical or epidemiologic studies, this asthma nomogram could be used as a tool to assess the probability of asthma for an individual patient by incorporating asthma-related predictor variables obtained through a field questionnaire.
在流行病学研究中,用于识别哮喘患者的标准各不相同,并且根据所使用的方法,可能具有挑战性并且需要耗费资源。
开发一种列线图(评分系统),使用通过经过验证的问卷收集的组合变量来识别成年哮喘患者。
我们研究了 2003 年至 2007 年间在上海妇女哮喘和过敏研究中报告有哮喘迹象和症状的前 268 名年龄在 40 至 69 岁之间的女性,这些女性接受了乙酰甲胆碱挑战测试或哮喘筛查期间的可逆性测试。这些女性被定义为患有明确的哮喘(n=106)或没有哮喘(n=162)。进行多变量逻辑回归分析,以使用调查信息单独开发用于识别哮喘的预测模型。
使用临床相关问题进行了预测多变量逻辑回归模型,包括以下内容:曾经有过胸部喘息或哨声、目前使用哮喘药物、自我报告曾有过哮喘、自我报告曾有过过敏性鼻炎、过敏家族史和年龄。预测模型的受试者工作特征曲线下面积为 0.75(95%置信区间,0.69-0.81)。开发了一个列线图,以根据预测模型中个体加权变量评估个体哮喘的概率。
在临床或流行病学研究中,该哮喘列线图可作为一种工具,通过纳入通过现场问卷获得的与哮喘相关的预测变量,评估个体患者患哮喘的可能性。