In India, lung cancer is the 2nd most common in males and 4th overall in cancer incidence with 81,784 new cases and 75,031 deaths with a 5-year prevalence of 1,13,990 as per GLOBOCAN 2022. Air pollution, particularly fine particulate matter (PM2.5), has been identified as a significant risk factor for lung cancer in never-smokers. India is showing an increasing incidence of lung cancer and there is a need to understand air pollution given many cities in India have been reported to be the most polluted in the world. Evidence of causal associations between PM2.5 and an increased likelihood of lung cancer with underlying biological mechanisms are now fully known. Current evidence focuses on individual pollutants, overlooking potential interactions among multiple risk factors that could amplify lung cancer risks. There is paucity of data on vulnerability of groups like children, older adults, and individuals with pre-existing health conditions, who may face disproportionate risks from poor air quality. The long-term effects of chronic exposure to air pollutants and their cumulative contribution to lung cancer risk remain understudied. Centre for Advanced Research on AIRCARE is essential to bridge these research gaps, providing a holistic understanding of air pollution's role in lung cancer to plan prevention and policy strategies. The study will be conducted at AIIMS, Delhi, and areas in Delhi and NCR with varying levels of PM 2.5 exposure and will encompass regions with diverse socio-economic profiles and industrial activities to capture the heterogeneity of exposure and risk. Subjects and controls will be enrolled to ensure a suitable representation of various demographic, socio-economic and air pollution exposure parameters. A subset of the cohort will be selected for genotyping, focusing on individuals with extreme exposure levels and/or lung cancer cases and controls for genetic interaction studies.
Adults aged 18 years or older, Histologically confirmed diagnosis of lung cancer, Residing in Delhi/National Capital Region (NCR)
Individuals aged below 18 years, individuals without a histologically confirmed diagnosis of lung cancer
The study will enrol an estimated 3230 participants (1615 lung cancer cases and 1615 controls). Diagnosed lung cancer cases from the outpatient department and Delhi cancer registry (DCR) will be included. Controls will be recruited from the family members of lung cancer patients to get the matched population in terms of PM 2.5 exposure.
Cohort
Prospective
Not listed
PM 2.5 exposure
The primary outcome will be measured in terms of histologically confirmed incidence of lung cancer. The interaction effects between air pollution (PM2.5) and other risk factors (smoking, Alcohol consumption, occupational exposures, genetic susceptibility) on lung cancer incidence and cumulative risk of lung cancer associated with combined exposure to air pollution and other risk factors will be evaluated.
Risk Stratification Model
The primary outcome will be measured based on the performance of the risk stratification model in predicting lung cancer risk, assessed by area under the receiver operating characteristic (AUROC) curve, sensitivity and specificity at predefined risk thresholds, and using calibration plots, to assess the agreement between predicted and observed risks.
Biomarker Identification
Primary Outcome will be measured by identification of biomarkers that are significantly associated with air pollution-related lung cancer, and the predictive ability of the biomarkers to discern between cases and controls.
Identifying Vulnerable Groups
Primary Outcome will be measured with differences in lung cancer incidence rates across vulnerable subgroups, and hazard ratios for lung cancer associated with air pollution exposure in each vulnerable subgroup.
Exposure Interaction Effects
Secondary Outcomes will be measured with the impact of interaction effects on lung cancer histological subtypes, modification of lung cancer risk by genetic variants in the presence of air pollution exposure, changes in biomarker profiles associated with combined exposures, and synergistic effects of PM 2.5 and other risk factors.
Modelling Epidemiology
The secondary Outcomes will be measured in terms of the positive predictive value (PPV) and negative predictive value (NPV) of the model, the impact of the model on lung cancer detection rates and stage distribution, and the model's ability to correctly categorize risk in prespecified subgroups.
Variation in Biomarker Levels
Secondary Outcomes will be measured in terms of the association between biomarker levels and air pollution exposure levels, temporal changes in biomarker levels associated with lung cancer development, association between biomarker levels and lung cancer histological subtypes, usefulness of biomarker panels for early lung cancer detection, and ability of the biomarkers to predict treatment response.
Characterisation of Vulnerable Groups
Secondary Outcomes will be measured with differences in lung cancer mortality rates across vulnerable subgroups, levels of biomarkers in vulnerable subgroups, and the impact of socioeconomic factors on the increased risk.
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All India Institute of Medical Sciences
Lead sponsor
Bristol-Myers Squibb
Collaborator
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