D3.380 - IL-8 levels in saliva following cigarette smoke extract exposure may serve as a biomarker for predicting COPD development
Background
The updated GOLD report for 2024 emphasizes the importance of timely early diagnosis for prevention of COPD. This requires the need to development of a method for predicting the risk of developing COPD.
Method
This study aimed to develop a model for predicting the risk probability form developing COPD. 41 patients with COPD of II-III GOLD and 43 patients with normal pulmonary function were assessed. In the group of patients with COPD, there were 24 (58.5%) active smokers and 17 (41.5%) non-smoking patients. In the comparison group there were 11 (25.6%) active smokers and 32 (74.4%) non-smokers. Spirometry, oral pharyngeal test with cigarette smoke extract (СSE), and a survey using a СOPD diagnostic questionnaire (CDQ) was performed. The level of IL-8 in the saliva was measured by ELISA. A mathematical model for predicting the probability of risk of developing COPD was developed on the basis of multivariate logistic regression.
Results
During the analysis of logistic regression of the difference in the values of IL-8 initially and after CSE exposure a statistical significance level of p<0.05 was obtained. Based on the data from the ROC curve analysis, the optimal cutoff threshold was determined with optimal sensitivity of 90% and specificity of 70%, which was 3.5. A value <3.5 assesses a low probability of risk of developing COPD in smokers without obstructive pathology, a value ≥3.5 indicates a high probability of risk of developing COPD.
Conclusion
The most significant factors have been identified that make it possible to predict the likelihood of the risk of developing COPD for healthy smokers without obstructive pathology: a СOPD diagnostic questionnaire, smoking index, post-bronchodilator ratio of forced expiratory volume in one second (FEV1) to forced vital capacity (FVC), the difference in IL-8 values in the salivabefore/after CSE exposure, and on their basis a mathematical model has been developed that allows stratification of the probability risk of developing COPD for each patient in a personalized manner.
