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.