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M. Miller
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P1.06 - Poster Session/ Screening and Early Detection (ID 218)
- Event: WCLC 2015
- Type: Poster
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/07/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P1.06-003 - Low-Dose CT Lung Cancer Screening in the Community: A Prospective Cohort Study Incorporating a Gene-Based Lung Cancer Risk Test (ID 879)
09:30 - 09:30 | Author(s): M. Miller
- Abstract
Background:
Following the publication of the National Lung Screening Trial (NLST) results in 2011, CT screening for lung cancer is now widely recommended in the US. However concerns remain with regards to patient selection according to risk level and overdiagnosis.Moreover adherence outside screening trials is typically about 50-60% and has been shown to be highly dependent on an individual's risk perception. This feasibility study explores the relevance of gene-based data on lung cancer risk assessment and adherence to screening, in a pilot screening program.
Methods:
This feasibility study was initiated in 2010 prior to NLST results being published. Following local media-based advertising, 157 current or former smokers (>50 years old with ≥20 pack year history), volunteered for lung cancer risk assessment and CT screening (using the IELCAP protocol). Participants were followed up for a mean of 2.4 years.At baseline CT screening, participants were assigned their lung cancer risk category according to a published and prospectively validated gene-based risk algorithm. This algorithm combines clinical risk variables with risk genotypes, derived from analysis of 20 risk single nucleotide polymorphisms (SNPS), to derive a composite lung cancer risk score categorised as moderate, high or very high.
Results:
SNP genotype results contributed to overall lung cancer risk in 88% of participants compared to the contribution from age = 68%, family history of lung cancer = 29% and self reported chronic obstructive pulmonary disease =15%. The SNP genotype results were the sole basis of risk in 18% of participants and contributed to risk in a further 70% of participants (total 88%). Adding SNP scores to the clinical risk score re-assigned screening participants into different risk categories in 28% (44/157) of participants (Figure 1). Importantly, timely adherence to the CT screening protocol was two-fold greater in those with a very high risk score compared to the high and moderate risk categories (71% vs 52% vs 52% respectively, OR =2.3, P<0.05). Figure 1
Conclusion:
In this feasibility study of a pilot community-based CT screening program we found gene-based risk assessment was of interest to all screening volunteers. As part of risk assessment, personalised SNP data made the greatest contribution to overall assignment of lung cancer risk in association with established clinical variables and significantly improved screening adherence. We conclude that gene-based risk stratification helps assign lung cancer risk and appears to improve adherence to screening.
