Validation of lung cancer polygenic risk scores in a high-risk case-control cohort.

PURPOSE: Screening with low-dose computed tomography reduces lung cancer (LC) mortality. Risk prediction models used for screening selection do not include genetic variables. Here, we investigated the performance of previously published polygenic risk scores (PRSs) for LC, considering their potential to improve screening selection. METHODS: We validated 9 PRSs in a high-risk case-control cohort, comprising genotype data from 652 surgical patients with LC and 550 cancer-free, high-risk (PLCOM2012 score ≥ 1.51%) participants of the Manchester Lung Health Check, a community-based LC screening program (n = 550). Discrimination (area under the curve [AUC]) between cases and controls was assessed for each PRS independently and alongside clinical risk factors. RESULTS: Median age was 67 years, 53% were female, 46% were current smokers, and 76% were National Lung Screening Trial eligible. Median PLCOM2012 score among controls was 3.4%, 80% of cases were early stage. All PRSs significantly improved discrimination, AUC increased between +0.002 (P = .02) and +0.015 (P < .0001), compared with clinical risk factors alone. The best-performing PRS had an independent AUC of 0.59. Two novel loci, in the DAPK1 and MAGI2 genes, were significantly associated with LC risk. CONCLUSION: PRSs may improve LC risk prediction and screening selection. Further research, particularly examining clinical utility and cost-effectiveness, is required.

Explaining differences in the frequency of lung cancer detection between the National Lung Screening Trial and community-based screening in Manchester, UK.

BACKGROUND: The frequency of lung cancer detection in the Manchester Lung Health Checks (MLHCs), a community-based screening service, was higher than in the National Lung Screening Trial (NLST) over two screening rounds. We aimed to identify the potential reasons for this difference. METHODS: We analyzed individual-level data from NLST and MLHCs, restricting to MLHCs participants who met NLST eligibility criteria. We calculated 'detection ratios' comparing the frequency of lung cancer detection in MLHCs vs NLST, first after excluding NLST participants ineligible by MLHC eligibility criteria (6-year lung cancer risk ≥ 1.51 %), and then after standardization to remove the influence of different distributions of baseline lung cancer risk. RESULTS: Among the 1,079 MLHCs participants who met NLST eligibility criteria, 4.7% were diagnosed with lung cancer over two screening rounds compared with 1.7% in NLST, giving an initial detection ratio of 2.6 (95%CI 2.2-3.0). This was reduced to 2.2 (95%CI 1.3-2.3) after imposing the MLHCs eligibility criterion on NLST, and further to 1.6 (95%CI 1.2-2.1) after removing the influence of different risk distributions. In stratified analyses, the standardized detection ratio was particularly elevated in individuals who were older, living in areas of high socioeconomic disadvantage, or had an FEV/FVC ratio less than 60. CONCLUSIONS: The 2.6-fold higher lung cancer detection in the community-based MLHCs vs NLST is partly explained by differences in eligibility criteria and baseline risk distributions. The residual 60% increase may relate to higher detection in certain risk groups, including older participants, those with more obstructive lung disease, and those living in areas of socioeconomic disadvantage.

Risk perception and disease knowledge in attendees of a community-based lung cancer screening programme.

OBJECTIVES: In England, a risk-based approach is used to determine eligibility for lung cancer screening. Ensuring effective communication and counselling of risk is therefore increasingly important. In this study, we explore the perception of lung cancer risk in attendees of a community-based screening service, located in socio-economically deprived areas of Manchester. We analyse responses based on demographic variables, calculated risk score and screening eligibility. MATERIALS AND METHODS: The Manchester Lung Health Check (LHC) programme invited ever smokers, age 55-80, to a lung cancer risk assessment in which their 6-year risk was calculated (using the PLCOM2012 model). Those at high risk (PLCOM2012 score ≥ 1.51%) were eligible for low dose CT (LDCT) screening. Prior to their assessment, attendees were invited to complete the study questionnaire, which assessed absolute and comparative risk perception, disease knowledge (incidence, survival, and risk factors), lung cancer specific worry, and mental health. RESULTS: 371 participants completed the questionnaire; 66% (n = 243) had linked clinical data. Perceived absolute risk was markedly higher than calculated risk (median: 20% vs. 1%; p < 0.001) and higher in women than men (25% vs. 15%; p = 0.001). There was no correlation between perceived absolute and calculated risk. Overall, 30% classified themselves at higher, and 21% at lower, lung cancer risk compared to others their age. Median PLCOM2012 score increased with perceived comparative risk (p = 0.004). Those eligible for screening were more likely to: classify themselves at higher comparative risk (41% vs. 21%; p < 0.0001), report lung cancer-specific worry (27% vs. 10%; p = 0.001) and have indications of depression (20% vs. 10%; p = 0.05). Family history of lung cancer was significantly associated with higher comparative risk (adjOR 4.03, 95%CI 1.74-9.3; p = 0.001). CONCLUSION: Employing comparative rather than absolute risk may assist risk counselling. Further research is required to determine the optimal approach to risk communication in this setting.

Targeting lung cancer screening to individuals at greatest risk: the role of genetic factors.

Lung cancer (LC) is the most common global cancer. An individual's risk of developing LC is mediated by an array of factors, including family history of the disease. Considerable research into genetic risk factors for LC has taken place in recent years, with both low-penetrance and high-penetrance variants implicated in increasing or decreasing a person's risk of the disease. LC is the leading cause of cancer death worldwide; poor survival is driven by late onset of non-specific symptoms, resulting in late-stage diagnoses. Evidence for the efficacy of screening in detecting cancer earlier, thereby reducing lung-cancer specific mortality, is now well established. To ensure the cost-effectiveness of a screening programme and to limit the potential harms to participants, a risk threshold for screening eligibility is required. Risk prediction models (RPMs), which provide an individual's personal risk of LC over a particular period based on a large number of risk factors, may improve the selection of high-risk individuals for LC screening when compared with generalised eligibility criteria that only consider smoking history and age. No currently used RPM integrates genetic risk factors into its calculation of risk. This review provides an overview of the evidence for LC screening, screening related harms and the use of RPMs in screening cohort selection. It gives a synopsis of the known genetic risk factors for lung cancer and discusses the evidence for including them in RPMs, focusing in particular on the use of polygenic risk scores to increase the accuracy of targeted lung cancer screening.

Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme.

INTRODUCTION: Low-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Liverpool Lung Project model (LLPv2)) and National Lung Screening Trial (NLST) eligibility criteria in a community-based screening programme. METHODS: Ever-smokers aged 55-74, from deprived areas of Manchester, were invited to a Lung Health Check (LHC). Individuals at higher risk (PLCOM2012 score ≥1.51%) were offered annual LDCT screening over two rounds. LLPv2 score was calculated but not used for screening selection; ≥2.5% and ≥5% thresholds were used for analysis. RESULTS: PLCOM2012 ≥1.51% selected 56% (n=1429) of LHC attendees for screening. LLPv2 ≥2.5% also selected 56% (n=1430) whereas NLST (47%, n=1188) and LLPv2 ≥5% (33%, n=826) selected fewer. Over two screening rounds 62 individuals were diagnosed with LC; representing 87% (n=62/71) of 6-year incidence predicted by mean PLCOM2012 score (5.0%). 26% (n=16/62) of individuals with LC were not eligible for screening using LLPv2 ≥5%, 18% (n=11/62) with NLST criteria and 7% (n=5/62) with LLPv2 ≥2.5%. NLST eligible Manchester attendees had 2.5 times the LC detection rate than NLST participants after two annual screens (≈4.3% (n=51/1188) vs 1.7% (n=438/26 309); p<0.0001). Adverse measures of health, including airflow obstruction, respiratory symptoms and cardiovascular disease, were positively correlated with LC risk. Coronary artery calcification was predictive of LC (adjOR 2.50, 95% CI 1.11 to 5.64; p=0.028). CONCLUSION: Prospective comparisons of risk prediction tools are required to optimise screening selection in different settings. The PLCOM2012 model may underestimate risk in deprived UK populations; further research focused on model calibration is required.