ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2026
The Multiethnic Cohort: A Resource for the Study of Genetic and Nongenetic Cancer Risk across Populations.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
David BogumilDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0002-5001-1088
Xin ShengDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0002-6844-2740
Peggy WanDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0009-0002-3922-2746
Lucy XiaDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0002-2470-7559
Loreall PoolerDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0001-5388-6640
Iona ChengDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California.ORCID 0000-0003-4132-2893
Samantha A StreicherEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.ORCID 0000-0002-0455-2131
Brian Z HuangDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0001-8645-5142
Fei ChenDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0002-1679-9932
Daniel O StramDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0001-7099-9022
Jiayi ShenDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0003-0701-9831
Gillian KingDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0009-0004-0832-9369
Charleston W K ChiangDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0002-0668-7865
Chrissie M OngacoCenter for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0009-0008-3881-1593
Marcia AdamsCenter for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0009-0004-6604-1638
Ivy McMullenCenter for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0009-0003-7543-9720
Peng ZhangCenter for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-1182-1392
Hua LingCenter for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-4414-8413
Michelle MawhinneyCenter for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0009-0007-2901-4915
Kimberly F DohenyCenter for Inherited Disease Research, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0001-8806-5738
Loïc Le MarchandEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.ORCID 0000-0001-5013-980X
Lynne R WilkensEpidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii.ORCID 0000-0001-8408-4536
Christopher A HaimanDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0002-0097-9971
David V ContiDepartment of Population and Public Health Sciences, Keck School of Medicine of University of Southern California, Los Angeles, California.ORCID 0000-0002-2941-7833
Funding
USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Saul Priceman · 1985 to 2026
$181.4M
Understanding Population Differences in Cancer: The MEC StudyU01CA164973 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI HAIMAN, CHRISTOPHER ALAN, LE MARCHAND, LOIC · 2015 to 2025
$37.4M
Statistical Methods for Integrative Genomics in CancerP01CA196569 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI William JAMES GAUDERMAN · 2016 to 2026
$25.5M
Training Grant in Genomic Analysis and InterpretationT32ES013678 · NIEHS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI GAUDERMAN, WILLIAM JAMES, MCCONNELL, ROB S · 2006 to 2023
$5.6M
Leveraging Prospective Cancer Epidemiology Cohorts and Novel Methods to Improve Polygenic Risk ScoresU01CA261339 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fei Chen, David V Conti · 2021 to 2026
$5.2M
Multidisciplinary Training in Ethnic Diversity and Cancer DisparitiesT32CA229110 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI HAIMAN, CHRISTOPHER ALAN, LE MARCHAND, LOIC · 2019 to 2023
$2.1M
National Cancer Institute (NCI) CA U01 CA164973National Cancer Institute (NCI) P01CA196569National Cancer Institute (NCI) P30CA014089National Cancer Institute (NCI) T32CA229110National Cancer Institute (NCI) U01CA261339National Institute of Environmental Health Sciences (DEHS) T32ES013678National Institutes of Health (NIH) X01HG010416NCI NIH HHS P01 CA196569NCI NIH HHS P30 CA014089NCI NIH HHS T32 CA229110NCI NIH HHS U01 CA164973NCI NIH HHS U01 CA261339NIEHS NIH HHS T32 ES013678
6 · The paper itself
Abstract
backgroundThe Multiethnic Cohort Study (MEC) is a US prospective cohort of more than 215,000 participants, designed to investigate variation in risk factors and disease across diverse racial and ethnic groups. More than 74,000 participants contributed biospecimens for genetic studies. We describe this subcohort and demonstrate the types of analyses it enables.
methodsThe MEC recruited adults aged 45 to 75 in California and Hawaii between 1993 and 1996. Cancer diagnoses were identified via state tumor registries. The MEC Genetics Database includes 73,139 participants with germline genotype data. We evaluated genetic similarity, its relationship with self-reported race/ethnicity, and baseline characteristics, including neighborhood socioeconomic status (nSES). Using breast, colorectal, and prostate cancer as examples, we conducted genome-wide association studies (GWAS), assessed nongenetic risk factors, and performed time-to-event analyses.
resultsParticipants included 10,962 African Americans, 24,234 Japanese Americans, 17,242 Latinos, 5,488 Native Hawaiians, 14,649 Whites, and 564 others. Principal component analysis showed substantial diversity. Multiethnic GWAS replicated known variants with effective control of population stratification. Polygenic risk score (PRS) effects varied across groups. Time-to-event models revealed associations between cancer incidence and nSES, population descriptors, and genetic similarity.
conclusionsThe MEC Genetics Database enables multiancestry analyses of genetic and nongenetic cancer risk, supporting research on disparities, polygenic traits, and integrated risk prediction. IMPACT: Example analyses using these resources show the relationship between population descriptors, PRSs, and common cancer risk factors that require special consideration in genetic analyses.
Indexed as
EthnicityNeoplasmsAgedCaliforniaCohort StudiesFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreGenome-Wide Association StudyHawaiiHumansMaleMiddle AgedProspective StudiesRisk Factors
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
The Multiethnic Cohort: A Resource for the Study of Genetic and Nongenetic Cancer Risk across Populations. · full record | OpenQuestion