SingapOre Lung Cancer Screening Through Integrating CT With Other biomarkErs (SOLSTICE)

Singapore General Hospital, National Heart Centre Singapore, Changi General Hospital, Sengkang General Hospital, Genome Institute of Singapore, National University of Singapore, Duke-NUS Graduate Medical School

This is a single arm screening study. All eligible participants will be subjected to low dose CT (LDCT) screening and biomarker testing. The primary aim of the study is to determine the feasibility of conducting LDCT screening in at-risk populations for lung cancer in Singapore: For the smoker population, LDCT screening for lung cancer will be implemented in accordance to Academy of Medicine, Singapore screening test guidelines with the aim of investigating the feasibility of instituting lung cancer screening clinical service in Singapore. For the non-smoker population, LDCT screening for lung cancer will be introduced to systematically collect baseline data to better understand and provide evidence for lung adenocarcinoma in never-smoker phenotype that is unique to East Asia/Singapore. This will help address unmet needs in local population research as reported by Academy of Medicine, Singapore, to validate risk factors and inform future screening guidelines for the at-risk population. Screening results will be reported based on Lung CT Screening Reporting & Data System (Lung-RADS).

This is a single arm cohort screening study. Briefly, this prospective study will involve screening the general population with risk factors for lung cancers with the aim of investigating the feasibility of implementing LDCT screening in the local context. Both smokers and non-smokers with the known risk factor of family history of lung cancer up to 2nd degree are eligible to participate in the study. Depending on emerging epidemiological data, additional high-risk cohorts may be included in this study. Subject demographics, smoking history, exposure to the aforementioned environmental factors, family history of lung cancer, history of tuberculosis and comorbidity will be captured in detail. The age range for inclusion is 55 to 74 years. Given the higher proportion of never-smoker lung cancer in Singapore, we aim to recruit 650 non-smoking and 350 smoking individuals for our study. LDCT scan results will be reported based on the Lung-RADS classification. Participants will be stratified into various Lung-RADS groups based on the CT appearance and size of nodules. An alphanumeric Lung-RADS score will be assigned to each subject which will guide the downstream management of screened participants. Participants with LDCT scan results of Lung-RADS score 2 and above will be referred to the nodule clinic under SingHealth DUKE-NUS Lung Centre for standardized follow-ups and/or diagnostic evaluation. These patients will undergo clinical surveillance (up to maximum of 5 years depending on their nodules) and will be managed as per current clinical practice. Participants with LDCT scan results of Lung-RADS score of 1 will undergo further screening surveillance which will end after 2 years if they have no nodules detected.

Low Dose CT (LDCT) Screening, Lung CT Screening Reporting & Data System (Lung-RADS), Lung cancer screening in smokers and non-smokers

LDCT scan results will be reported based on the Lung-RADS classification. Participants will be stratified into various Lung-RADS groups based on the CT appearance and size of nodules. An alphanumeric Lung-RADS score will be assigned to each subject which will guide the downstream management of screened participants. All subjects will be required to donate drawn blood samples (up to 30 ml) at every LDCT visit during screening surveillance, and at every LDCT/CT scan and/or biopsy visits during clinical surveillance for blood-based biomarker assays development and characterization. Subjects may also be asked to provide a sample of urine, saliva and breath for biomarker discovery.

Compliance with LDCT screens for patients with lung-RADS 1 from baseline till end of screening surveillance.

The utility of blood-based biomarker assays in improving the performance of LDCT to detect lung cancer and discriminate risk of malignancy. (1)

Diagnostic accuracy and discrimination ability of biomarker assay in the detection of lung cancer will be assessed via sensitivity, specificity, PPV, NPV and area under curve (AUC) of the receiver operating characteristic curve.

The utility of blood-based biomarker assays in improving the performance of LDCT to detect lung cancer and discriminate risk of malignancy. (2)

Changes in biomarker levels over time in relation to lung cancer diagnosis. Time series plot of biomarker levels by whether participants have lung cancer diagnosed will be created. Linear mixed effect models will be used to assess the changes in biomarker levels over time in the group of participants with lung cancer diagnosed, and to compare whether the changes observed are different from those experienced by the group of patients with no lung cancer diagnosed.

Comparison of the diagnostic performance of each combination of a biomarker assay and LDCT screening against that of LDCT screening.

A biomarker assay that can accurately diagnose lung cancer will then be combined with LDCT screening via a re-definition of what constitute a positive screening test (e.g. Lung-RADS 3 to 4X or biomarker assay above a certain threshold). The additional diagnostic value of a biomarker assay will be assessed by comparing the diagnostic performance of the combination of the biomarker assay and LDCT screening against that based on LDCT screening alone.

Screen detected lung cancer rate at baseline, and interval cancers detected between screening rounds.

Identification of radiomic biomarkers that can improve the diagnostic accuracy of LDCT screening. Screening LDCT imaging data as well as data from subsequent staging imaging studies of participants with proven screening-detected lung cancer will be evaluated. The lung tumour(s) will be segmented and quantitative features extracted using semi-automated software systems. The extracted quantitative features will be analysed in combination with clinical and pathological data to develop models that predict tumour characteristics or treatment response.

For gene-environment-lifestyle interaction analysis, interactions between genetic variants (by means of genotyping of samples collected) and environmental risk factors (gathered from Life-Style questionnaire administered) will be assessed using a 2 degree of freedom joint test, which provides a joint test for genotype and genotype-environment interaction terms. GWAS association tests will be performed using significant SNPs that were previously reported in the literature and combined with questionnaire data on environmental exposures and lifestyles. All statistical analyses will be conducted using R version 3.5. All tests are considered significant with a p-value of less than 0.06. False discovery rates (FDR) will be calculated using the Benjamini and Hochberg method to account for multiple comparisons.

Inclusion Criteria: Smoker: Participant is willing and able to give informed consent for participation in the study Male or female, aged 55-74 years of age No prior history of cancer ECOG 0/1 Current or former smokers with at least 30 pack years of smoking history Willing to comply with study follow-up schedule and tests Willing to cover the costs of downstream standard of care management and investigations including doctor's fee, CT scan and biopsy etc. A Singapore citizen/Permanent Resident of Singapore Non-Smoker: Participant is willing and able to give informed consent for participation in the study Male, or female, aged 55-74 years of age No prior history of cancer ECOG 0/1 Never smoker, or has smoked less than 10 pack-years and has quit smoking for at least 15 years Family history of lung cancer up to 2nd degree relatives Willing to comply with study follow-up schedule and tests Willing to cover the costs of downstream standard of care management and investigations including doctor's fee, CT scan and biopsy etc. A Singapore citizen/Permanent Resident of Singapore Exclusion Criteria: Uncontrolled medical comorbidity on enrolment Previous diagnosis of cancer Bleeding diathesis that will preclude blood sampling Fear of blood draw or needles Pregnancy