Development and validation of a prediction model for airflow obstruction in older Chinese: Guangzhou Biobank Cohort Study. (November 2020)

• Record Type: Journal Article
• Authors: Pan, Jing; Adab, Peymane; Cheng, K.K.; Jiang, Chao Qiang; Zhang, Wei Sen; Zhu, Feng; Jin, Ya Li; Thomas, G. Neil; Steyerberg, Ewout W.; Lam, Tai Hing
• Is Part Of: Respiratory medicine. Volume 173(2020)
• Publication Date: 2020-11
• Subjects: Airflow obstruction -- Prediction model; Chest -- Diseases -- Periodicals; Chest -- Diseases -- Great Britain -- Periodicals; Respiratory organs -- Diseases -- Periodicals; Respiratory Tract Diseases -- Periodicals; Appareil respiratoire -- Maladies -- Périodiques; Thorax -- Maladies -- Périodiques; Appareil respiratoire -- Maladies -- Traitement -- Périodiques; Electronic journals; 616.2
• DOI: 10.1016/j.rmed.2020.106158
• Languages: English
• ISSNs: 0954-6111

Abstract

Abstract: Objective: To develop and validate a prediction model for airflow obstruction (AO) in older Chinese. Methods. Design: Multivariable logistic regression analysis in large population cohort of Chinese aged ≥50 years. Participants: Model development: 8762 Chinese aged ≥50 years were selected from the early phase recruits to the Guangzhou Biobank Cohort Study (GBCS) (recruited from September 2003 to May 2006). Internal validation: 100 bootstrap samples drawn with replacement from the development sample. External validation: 8395 Chinese aged ≥50 years from later phase GBCS (recruited from September 2006 to January 2008). Outcomes: AO was defined by a forced expiratory volume in 1 s/forced vital capacity ratio < lower limits of normal. Results: 839 (9.6%) and 764 (9.1%) individuals had AO in the development and temporal validation samples respectively. The predictors in the prediction model included sex, age, body mass index groups, smoking status, presence of respiratory symptoms, and history of asthma. Model development and validation was stratified by sex. Model performance including calibration (calibration-in-the-large −0.017 vs. −0.157; and calibration slope 0.88 vs. 1.02), discrimination (C-statistic 0.72 vs. 0.63 with 95% confidence interval 0.69–0.75 vs. 0.62–0.73) and clinical usefulness (decision curve analysis) in the external temporal validation sample were more satisfactory in men than that in women. Prediction models with risk thresholds (13% in men and 7% in women) and easy-to-use nomograms were developed to assess the probability of AO. Conclusion: The diagnostic models based on readily available epidemiologic and clinical information with satisfactory performance can assist physicians to identify older individuals at high risk of AO and may improve the efficiency of spirometry for active case finding. Further validation beyond the Chinese population is warranted. Highlights: Based on a large cohort of older Chinese, we developed and validated prediction models for AO stratified by sex. Model performance was more satisfactory in men than that in women. The models may improve the efficiency of spirometry for active case finding.