Abstract IA37: Lung cancer incidence and risk factors in never-smoking Asian American, Native Hawaiian, and Pacific Islander women: The development of a multilevel integrated dataset of EHR, cancer registry, and environmental data

Background: For Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females, lung cancer is one of the most common cancers and the leading cause of cancer death. More than half of AANHPI female lung cancers occur in never-smokers, and contributing risk factors among never-smokers remain largely unknown. Until now, there was no single sufficiently-large data source to document lung cancer incidence rates by smoking status and sex among specific AANHPI ethnic groups, which is central to understanding and reducing the burden of this disease in this population. We assembled a large-scale cohort to quantify the burden of lung cancer by smoking status among single- and multiethnic AANHPI groups, with an emphasis on identifying the underlying factors driving lung cancer risk among never-smoking AANHPI females. Methods: Assembly of the cohort involved (1) harmonizing and pooling electronic health record (EHR) data on known and putative lung cancer risk factors from two large health systems (i.e., Northern California Sutter Health system and Kaiser Permanente Hawaii [KPH]); (2) linking EHR data from Sutter and KPH with tumor and diagnosis data from the California Cancer Registry and Hawaii Tumor Registry, respectively; (3) geocoding and linking the Sutter portion of the cohort to regional air pollutant data and data on specific neighborhood contextual factors from the California Neighborhoods Data System; and (4) developing neighborhood contextual variables to enhance the geocoded data for KPH cohort members. Incidence rates stratified by sex, detailed race/ethnicity, and smoking status were calculated. Results: The cohort comprises 1.8 million individuals, including 750,000 females of whom 190,000 are AANHPI females, with up to 15 years9 follow-up for incident lung cancer. It includes over 24,000 incident lung cancer cases, of which 10,595 are females and over 1,500 are single- and multiethnic AANHPI females. The cohort has high representation of Asian Indian, Chinese, Japanese, Filipino, Korean, and Pacific Islander never-smoking females in addition to multiple multiethnic AANHPI ethnic groups. Ongoing analyses, including overall and histologic cell-type specific incidence rates of lung cancer by sex, race/ethnicity, and smoking status will be presented. Conclusions: We have assembled a large, integrated dataset well suited to study multilevel risk of lung cancer that will serve as a critical evidence base to inform screening, research, and public health priorities, especially among AANHPI females. Future work will include longitudinal analyses of lung cancer risk among never-smoking AANHPI females, including absolute risk modeling, examining six exposure domains representing putative lung cancer risk factors: second-hand smoke, previous lung diseases, infections, reproductive history and hormone exposure, body size, and neighborhood environmental factors, including measures of particulate matter, traffic density, neighborhood socioeconomic status, and ethnic enclave. Citation Format: Mindy C. DeRouen, Salma Shariff-Marco, Daphne Lichtensztajn, Anqi Jin, Yihe G. Daida, Alison J. Canchola, Yuqing Li, Jennifer Jain, Laura Allen, Sixiang Nie, Carmen Wong, Robert Haile, Manali Patel, Peggy Reynolds, Heather Wakelee, Hal Luft, Caroline Thompson, Su-Ying Liang, Beth E. Waitzfelder, Iona Cheng, Scarlett L. Gomez. Lung cancer incidence and risk factors in never-smoking Asian American, Native Hawaiian, and Pacific Islander women: The development of a multilevel integrated dataset of EHR, cancer registry, and environmental data [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr IA37.