Chronic obstructive pulmonary disease (COPD) and lung cancer screening

Abstract

The primary aim of lung cancer screening is to improve survival from lung cancer by identifying early stage non-small cell lung cancers and prolong survival through their surgical removal. In a analysis of 10,054 screening participants from the National Lung Screening Trial (NLST) we show that the risk of lung cancer, according to the PLCOm2012 model, is closely related to the likelihood of having chronic obstructive pulmonary disease (COPD). Those at greatest risk for lung cancer have the highest prevalence of COPD and greater likelihood of dying of a non-lung cancer cause. This "competing cause of death" effect occurs because smokers eligible for lung cancer screening have a high prevalence of comorbid disease and greater likelihood of dying from cardiovascular disease, respiratory disease or other cancers. This means high risk smokers at greatest risk of lung cancer may not necessarily benefit from screening due to greater inoperability and premature death. In this analysis we show that the benefit of annual computed tomography (CT) screening is greatest in those with normal lung function or only mild-to-moderate COPD. We found no mortality benefit in those with severe or very severe COPD (GOLD 3-4). We also show that the efficiency of screening, based on optimizing the number of lung cancer deaths averted per 1,000 persons screened, is best achieved by screening those at intermediate risk. By combining clinical risk variables with a gene-based risk score, even greater reductions in lung cancer mortality can be achieved with CT. We suggest a biomarker-led outcomes-based approach may help to better define which eligible smokers might defer screening (low risk of lung cancer), discontinue screening (high risk of overtreatment with little benefit) or continue screening to achieve the greatest reduction in lung cancer mortality.

Incorporating Baseline Lung Function in Lung Cancer Screening

“…We have previously reported several post hoc analyses from the National Lung Screening Trial (NLST), in which participants underwent spirometric assessment before randomization to annual CT or chest radiography (CXR). [5][6][7] We found that 34% of this subgroup had airflow limitation (COPD), and 65% of those with airflow limitation had not yet been diagnosed with COPD. 5 This is in line with the findings of those undergoing "lung health checks."…”

Consecutive Hypoxia Decreases Expression of NOTCH3, HEY1, CC10, and FOXJ1 via NKX2-1 Downregulation and Intermittent Hypoxia-Reoxygenation Increases Expression of BMP4, NOTCH1, MKI67, OCT4, and MUC5AC via HIF1A Upregulation in Human Bronchial Epithelial Cells

“…In the submerged cultures under normoxia, although the OCT4 mRNA level showed a nearly 3-fold increase in DHBE cells compared to the level in NHBE cells ( Figure 10A ), the OCT4 protein level was comparable between NHBE and DHBE cells ( Figure 9K ). Given that multiple lines of evidence have shown the positive correlation between COPD and lung cancers ( Raviv et al, 2011 ; Durham and Adcock, 2015 ; Spyratos et al, 2017 ; Young and Hopkins, 2018 ; Parris et al, 2019 ), which are generally characterized by increased OCT4 protein expression in the malignant airway epithelial tissues ( Chen et al, 2008 ; Karoubi et al, 2009 ; Chiou et al, 2010 ; Zhang X. et al, 2010 ; Bora-Singhal et al, 2015 ), it is plausible that increased OCT4 mRNA expression in the undifferentiated DHBE cells, which preceded increased OCT4 protein expression, may be a predisposing factor for lung cancer development in the COPD population. On the other hand, surprisingly, the OCT4 mRNA levels were comparable among the differentiated NHBE and DHBE tissues cultured under normoxia, intermittent H/R or consecutive hypoxia ( Figure 10I ), which may be primarily attributable to the dramatically reduced expression levels of OCT4 in the ALI-cultured and differentiated HBE tissues, which showed at least 50% decreases compared to the levels in the submerged and undifferentiated HBE cells ( Figure 10J ).…”

Answer/comment to Prof. Tammemagi’s article “Selecting lung cancer screenees using risk prediction models—where do we go from here”

“…We believe that including any type of information that increases the predictive accuracy of a model is desirable, but it should be simple and accurate. Surprisingly, a recent study shows that a reduction in lung cancer mortality from CT is greatest in those with normal lung function and those with undiagnosed COPD (7). This seems to be due to the competing risk of death from other smoke-related disorders such as respiratory failure or cardiovascular disease in those with severe COPD.…”