Elevated air quality index and fine particulate matter levels contribute to the poor prognosis and progression of nonsmall‐cell lung cancer: A cohort study combined with external validation. (21st March 2022)

• Record Type: Journal Article
• Authors: Li, Jing; Wei, Xiaoying; Gu, Ling; Qiu, Linya; Xiang, Mengqi; Zhang, Huachuan; Xia, Lei; Pan, Wenying; Yang, Zhenyu; Zhou, Xiaoli; Zeng, Daxiong; Jiang, Junhong
• Is Part Of: Cancer medicine. Volume 11:Number 17(2022)
• Page Start: 3272
• Page End: 3281
• Publication Date: 2022-03-21
• Subjects: air quality index -- NSCLC -- PM2.5 -- prediction model -- prognosis; 616.994005
• DOI: 10.1002/cam4.4701
• Languages: English
• ISSNs: 2045-7634

Abstract

Abstract: Background: Poor air quality can result in a variety of respiratory disorders. However, the air quality index (AQI) and the level of fine particulate matter (PM2.5) on the progression and prognosis of nonsmall‐cell lung cancer (NSCLC) are unclear. Methods: We launched a cohort study focused on the relationship between air quality and overall survival as well as progression, incorporating data from 590 patients with NSCLC in our medical center between November 1, 2013 and March 1, 2016. Forty‐nine patients from Sichuan Cancer Hospital were used for validation. Results: Cases with poorer AQI 6 months before NSCLC diagnosis were more likely to progress to stage III to IV NSCLC than controls (OR = 2.61, 95% CI 1.35–5.24, p = 0.005). Similarly, if exposed to high levels of PM2.5 during these 6 months, overall survival was poor (HR [95% CI] = 1.53 [1.13, 2.07], p = 0.006). According to multivariate analysis, age, gender, KPS, PM2.5, hyperlipemia, and NSCLC stage were independent risk factors of overall survival. A predictive model developed by these factors above yielded a favorable agreement (C‐index = 0.758) on the calibration curve. External validation was conducted by 46 patients from Sichuan Cancer Hospital displaying an AUC of 0.724 (0.684–0.763). Conclusions: PM2.5 and AQI levels affect disease progression and long‐term survival in NSCLC patients. An overall survival prediction model based on the PM2.5 level can help clinicians predict the risk of death in NSCLC.