Applying a data integrative and convergence epidemiology approach to study multilevel risk factors for cancer in distinct AANHPI populations

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 lung cancers among AANHPI females occur among never-smokers, but incidence rates of lung cancer according to smoking status have not been available. Purpose: With a large, integrated dataset of electronic health record data from two healthcare systems—Sutter Health in Northern California and Kaiser Permanente Hawai9i—linked to state cancer registry data on incident lung cancer diagnoses 2000-2013, we describe incidence of lung cancer according to smoking status among females across detailed race and ethnicity. Methods: We calculated age-adjusted incidence rates for lung cancer according to smoking status and detailed race and ethnicity among females, focusing on AANHPI ethnic groups, and assessed relative incidence across racial and ethnic groups. The study population included N=1,222,694 females (n=244,147 AANHPI), n=3,297 (n=535) of whom were diagnosed with lung cancer. We examined relative incidence across group defined by detailed race and ethnicity. We also provided incidence of lung cancer among AANHPI males who never smoked in a supplement. Results: Among AANHPI female groups, proportions of lung cancers among never-smokers ranged from 25% among Native Hawaiian to 80% among Chinese females. Incidence of lung cancer among never-smoking AANHPI females as an aggregate was 17.1 per 100,000 (95% CI: 14.9, 19.4), but rates varied widely across ethnic groups. Never-smoking Chinese females had the highest rate (22.8; 95% CI: 17.3, 29.1). Except for Japanese females, incidence among every never-smoking AANHPI female ethnic group was higher than that of all never-smoking females combined. Never-smoking AANHPI males also have higher incidence of lung cancer compared to other groups defined by race and ethnicity. Conclusions: The integrative data analysis approach offers great advantages over traditional cancer cohorts, but it does require substantial time and effort to assure data confidentiality, integrity, and transparency to provide robust results. However, with convergence epidemiology—in this case leveraging needed expertise in data science and analysis to answer an epidemiology question—it is also a valuable approach to study disparate cancer outcomes among small populations. Illustrating this, our study is the first to document high rates of lung cancer among never-smoking AANHPI ethnic groups, dispels the myth that AANHPI females are at overall reduced risk of lung cancer, and demonstrates the need to disaggregate this highly diverse population. Results should inform lung cancer prevention strategies among AANHPI populations. Citation Format: MIndy C. DeRouen, Alison J. Canchola, Caroline A. Thompson, Anqi Jin, Sixiang Nie, Carmen Wong, Daphne Lichtensztajn, Laura Allen, Manali I. Patel, Yihe G. Daida, Harold S. Luft, Salma Shariff-Marco, Peggy Reynolds, Heather A. Wakelee, Su-Ying Liang, Beth E. Waitzfelder, Iona Cheng, Scarlett L. Gomez. Applying a data integrative and convergence epidemiology approach to study multilevel risk factors for cancer in distinct AANHPI populations [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr IA-21.