Abstract PR07: Lung cancer incidence and risk factors in never-smoking Asian American, Native Hawaiian, and Pacific Islander women: A multilevel dataset of electronic health record, cancer registry, and environmental data
Authors: DeRouen Mindy C. , Thompson Caroline , Canchola Alison J. , Jin Anqi , Nie Siaxing , Jain Jennifer , Shariff-Marco Salma , Lichetensztajn Daphne Y. , Daida Yihe , Wong Carmen , Li Yuqing , Patel Manali I. , Wakelee Heather A. , Liang Su-Ying , Waitzfelder Beth E. , Cheng Iona , Gomez Scarlett L. 
Published: September 2020

Abstract
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, smoking status, and lung cancer histology have been calculated; as well as incidence rate ratios by race/ethnicity.
Results: The cohort comprises over 2.3 million individuals (250,000 AANHPI females) followed up to 15 years for incident lung cancer. It includes over 6,000 incident lung cancer cases, of which 558 are AANHPI females. Among AANHPI female groups, proportions of lung cancers among never-smokers range from 31% among Native Hawaiian to 88% among Chinese females. Incidence rates of never-smoking lung cancer are highest among Native Hawaiian females (AAIR, 28.7) and Asian females reporting multiple races/ethnicities (AAIR, 27.8).
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. Ongoing work will include longitudinal analyses of lung cancer risk among never-smoking AANHPI females, including absolute risk modeling, examining six exposure domains representing known and putative lung cancer risk factors.
This abstract is also being presented as Poster A104.
Citation Format: Mindy C. DeRouen, Caroline Thompson, Alison J. Canchola, Anqi Jin, Siaxing Nie, Jennifer Jain, Salma Shariff-Marco, Daphne Y. Lichetensztajn, Yihe Daida, Carmen Wong, Yuqing Li, Manali I. Patel, Heather A. Wakelee, 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: A multilevel dataset of electronic health record, cancer registry, and environmental data [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR07.