A dynamic nomogram for predicting the risk of asthma: Development and validation in a database study. Issue 7 (14th June 2021)

• Record Type: Journal Article
• Authors: Yang, Lifen; Li, Meihua; Zheng, Qinling; Ren, Chaofeng; Ma, Wei; Yang, Yanxia
• Is Part Of: Journal of clinical laboratory analysis. Volume 35:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-14
• Subjects: asthma -- dynamic nomogram -- NHANES database -- smoking duration; Diagnosis, Laboratory -- Periodicals; Medical laboratory technology -- Periodicals; 616
• DOI: 10.1002/jcla.23820
• Languages: English
• ISSNs: 0887-8013

Abstract

Abstract: Background: Asthma remains a serious health problem with increasing prevalence and incidence. This study was to develop and validate a dynamic nomogram for predicting asthma risk. Methods: Totally 597 subjects whose age ≥18 years old with asthma, an accurate age at first cigarette, and clear smoking status were selected from the National Health and Nutrition Examination Survey (NHANES) database (2013–2018). The dataset was randomly split into the training set and the testing set at a ratio of 4:6. Simple and multiple logistic regressions were used for identifying independent predictors. Then the nomogram was developed and internally validated using data from the testing set. The receiver operator characteristic (ROC) curve was used for assessing the performance of the nomogram. Results: According to the simple and multiple logistic regressions, smoking ≥40 years, female gender, the age for the first smoking, having close relative with asthma were independently associated with the risk of an asthma attack. The nomogram was thereby developed with the link of https://yanglifen.shinyapps.io/Dynamic_Nomogram_for_Asthma/ . The ROC analyses showed an AUC of 0.726 (0.724–0.728) with a sensitivity of 0.887 (0.847–0.928) in the training set, and an AUC of 0.702 (0.700–0.703) with a sensitivity of 0.860 (0.804–0.916) in the testing set, fitting well in calibration curves. Decision curve analysis further confirmed the clinical usefulness of the nomogram. Conclusion: Our dynamic nomogram could help clinicians to assess the individual probability of asthma attack, which was helpful for improving the treatment and prognosis of asthma. Abstract : We developed and internally validated a dynamic nomogram to help clinicians to estimate the individual probability of asthma, which was useful for improving the treatment and prognosis of asthma.