scholarly journals FP09.02 Calibration of the LLP Lung Cancer Risk Stratification Model: Prospective Validation in the UKLS Cohort of 76,000 People

2021 ◽  
Vol 16 (3) ◽  
pp. S212
Author(s):  
J. Field ◽  
D. Vulkan ◽  
M. Davies ◽  
S. Duffy ◽  
R. Gabe
2018 ◽  
Vol 27 (2) ◽  
pp. 87-92 ◽  
Author(s):  
Hiroaki Harada ◽  
Kazuaki Miyamaoto ◽  
Masami Kimura ◽  
Tetsuro Ishigami ◽  
Kiyomi Taniyama ◽  
...  

Background Assuming that the entire airway is affected by the same inhaled carcinogen, similar molecular alterations may occur in the lung and oral cavity. Thus, we hypothesized that DNA methylation profiles in the oral epithelium may be a promising biomarker for lung cancer risk stratification. Methods A methylation-specific polymerase chain reaction was performed on oral epithelium from 16 patients with lung cancer and 32 controls without lung cancer. Genes showing aberrant methylation profiles in the oral epithelium were compared between patients and controls. Results The analysis revealed that HOXD11 and PCDHGB6 were methylated more frequently in patients than in controls ( p = 0.0055 and p = 0.0247, respectively). Combined analyses indicated that 8 of 16 (50%) patients and 3 of 32 (9.4%) controls showed DNA methylation in both genes ( p = 0.0016). Among the population limited to current and former smokers, 6 of 11 (54.5%) patients showed methylation in both genes, compared to 1 of 17 (5.9%) controls ( p = 0.0037). In a subgroup analysis limited to the population above 50-years old, 8 of 16 (50%) patients and 2 of 16 (12.5%) controls showed methylation in both genes ( p = 0.0221). Conclusions The results of this study indicate that specific gene methylation in the oral epithelium might be a promising biomarker for lung cancer risk assessment, especially among smokers. Risk stratification through the analysis of DNA methylation profiles in the oral epithelium may be a useful and less invasive first-step approach in an efficient two-step lung cancer screening strategy.


2021 ◽  
pp. 137-151
Author(s):  
Rohit Rastogi ◽  
Mukund Rastogi ◽  
D. K. Chaturvedi ◽  
Sheelu Sagar ◽  
Neeti Tandon

2020 ◽  
Vol 12 (6) ◽  
pp. 3303-3316
Author(s):  
Ali Khawaja ◽  
Brian J. Bartholmai ◽  
Srinivasan Rajagopalan ◽  
Ronald A. Karwoski ◽  
Cyril Varghese ◽  
...  

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e110157 ◽  
Author(s):  
Andrew J. Radosevich ◽  
Nikhil N. Mutyal ◽  
Jeremy D. Rogers ◽  
Bradley Gould ◽  
Thomas A. Hensing ◽  
...  

Thorax ◽  
2020 ◽  
pp. thoraxjnl-2020-215158
Author(s):  
John K Field ◽  
Daniel Vulkan ◽  
Michael P A Davies ◽  
Stephen W Duffy ◽  
Rhian Gabe

BackgroundEarly detection of lung cancer saves lives, as demonstrated by the two largest published low-dose CT screening trials. Optimal implementation depends on our ability to identify those most at risk.MethodsVersion 2 of the Liverpool Lung Project risk score (LLPv2) was developed from case-control data in Liverpool and further adapted when applied for selection of subjects for the UK Lung Screening Trial. The objective was to produce version 3 (LLPv3) of the model, by calibration to national figures for 2017. We validated both LLPv2 and LLPv3 using questionnaire data from 75 958 individuals, followed up for lung cancer over 5 years. We validated both discrimination, using receiver operating characteristic (ROC) analysis, and absolute incidence, by comparing deciles of predicted incidence with observed incidence. We calculated proportionate difference as the percentage excess or deficit of observed cancers compared with those predicted. We also carried out Hosmer-Lemeshow tests.ResultsThere were 599 lung cancers diagnosed over 5 years. The discrimination of both LLPv2 and LLPv3 was significant with an area under the ROC curve of 0.81 (95% CI 0.79 to 0.82). However, LLPv2 overestimated absolute risk in the population. The proportionate difference was −58.3% (95% CI −61.6% to −54.8%), that is, the actual number of cancers was only 42% of the number predicted.In LLPv3, calibrated to national 2017 figures, the proportionate difference was −22.0% (95% CI −28.1% to −15.5%).ConclusionsWhile LLPv2 and LLPv3 have the same discriminatory power, LLPv3 improves the absolute lung cancer risk prediction and should be considered for use in further UK implementation studies.


2021 ◽  
Author(s):  
Naisi Zhao ◽  
Mengyuan Ruan ◽  
Devin C. Koestler ◽  
Jiayun Lu ◽  
Carmen J. Marsit ◽  
...  

AbstractBackgroundTo reduce lung cancer burden in the US, a better understanding of biological mechanisms in early disease development could provide new opportunities for risk stratification.MethodsIn a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 men and women in the 1989 CLUE II cohort. Median time from blood drawn to diagnosis was 14 years for all participants. We compared DNA methylation levels by case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years based smoking methylation score. Stratification analyses were conducted by time from blood draw to diagnosis, histology, and smoking status.ResultsWe identified sixteen single CpG sites and forty DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10−7). For the DMRs, we found that CpG sites in the HOXA4 region were hypermethylated in cases compared to controls.ConclusionThe single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing new insights into the biological processes of early lung cancer development and potential biomarkers for lung cancer risk stratification.


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