Article in Journal of the National Cancer Institute, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
0numbers the graph read from it
0cells of the map it votes in
3citing 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.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
24 authors.
Meng RuDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-1439-6451
Christopher DouvilleDepartment of Oncology, Johns Hopkins University School of Medicine, and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, United States.ORCID 0000-0002-2510-4151
Aghiles GuenounGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.ORCID 0009-0001-0660-6228
Hana ZahedGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.ORCID 0000-0002-5731-8859
Christie M BallantyneDepartment of Medicine, Baylor College of Medicine, Houston, TX, United States.
Kenneth R ButlerDepartment of Medicine, University of Mississippi Medical Center, Jackson, MS, United States.ORCID 0000-0003-3198-8835
Josef CoreshDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-4598-0669
David J CouperDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID 0000-0002-4313-9235
Panagis GaliatsatosDepartment of Oncology, Johns Hopkins University School of Medicine, and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, United States.
Marc J GunterCancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, United Kingdom.
Ron C HoogeveenDepartment of Medicine, Baylor College of Medicine, Houston, TX, United States.ORCID 0000-0003-2399-4653
Mattias JohanssonGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.ORCID 0000-0002-3116-5081
Corinne E JoshuDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-5100-172X
P Martijn KolijnInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
Christina M LillAgeing Epidemiology Research Unit, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-2805-1307
Jiayun LuDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-5592-6658
Michael T MarroneDepartment of Public Health Sciences, Medical University of South Carolina, Charleston, SC, United States.ORCID 0000-0003-1568-9499
Giovanna MasalaClinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network, Florence, Italy.ORCID 0000-0002-5758-9069
David C MullerCancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-2350-0417
Anna E PrizmentDepartment of Laboratory Medicine and Pathology, University of Minnesota Twin Cities, Minneapolis, MN, United States.ORCID 0000-0003-1932-6548
Raul Zamora-RosUnit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute, Barcelona, Spain.ORCID 0000-0002-6236-6804
Nilanjan ChatterjeeDepartment of Oncology, Johns Hopkins University School of Medicine, and the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, United States.ORCID 0000-0002-9060-008X
Adrienne TinDepartment of Medicine, University of Mississippi Medical Center, Jackson, MS, United States.ORCID 0000-0002-4207-5866
Elizabeth A PlatzDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-3676-8954
Funding
Building on GWAS for NHLBI-disease: the CHARGE consortiumRC2HL102419 · NHLBI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A. · 2009 to 2010
$27.6M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - COORDINATING CENTER - TASK AREA B.2 AND B.375N92022D00001 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI COUPER, DAVID · 2022 to 2025
$13.7M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00003 · NHLBI · UNIVERSITY OF MINNESOTA · PI LUTSEY, PAMELA · 2022 to 2025
$5.1M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00005 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WAGENKNECHT, LYNNE · 2022 to 2025
$5.0M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00004 · NHLBI · UNIVERSITY OF MISSISSIPPI MED CTR · PI WINDHAM, BEVERLY GWEN · 2022 to 2025
$4.8M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00002 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CORESH, JOSEF · 2022 to 2025
$4.7M
Enhancing ARIC Infrastructure to Yield a New Cancer Epidemiology CohortU01CA164975 · NCI · JOHNS HOPKINS UNIVERSITY · PI PLATZ, ELIZABETH A. · 2012 to 2018
$3.8M
Profiling Cardiovascular Events and Biomarkers in the Very Old to Improve Personalized Approaches for the Prevention of Cardiac and Vascular DiseaseR01HL134320 · NHLBI · BAYLOR COLLEGE OF MEDICINE · PI BALLANTYNE, CHRISTIE MITCHELL, SELVIN, ELIZABETH · 2016 to 2019
$3.1M
An Integrated Genetic and Epigenetic Approach to Cerebral Small Vessel DiseaseR01NS087541 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A., FORNAGE, MYRIAM · 2014 to 2017
backgroundSelf-reported smoking may not fully capture individualized risk of smoking-related cancer, but circulating proteins may reflect biological consequences of smoking. Thus, we developed a score based on smoking-related proteins and evaluated its association with smoking-related cancer.
methodsThis prospective cohort study included 10 563 participants aged 47-70 years in the Atherosclerosis Risk in Communities study. Plasma proteins were measured using the SomaScan Platform (SomaLogic Operating Co, Inc). The score was constructed from proteins associated with current smoking, pack-years, or recent quitting identified by linear regression and elastic net regression. Cox regression was used to estimate adjusted hazard ratios and 95% confidence intervals (CIs). We confirmed the association in a case-cohort study in the European Prospective Investigation into Cancer and Nutrition.
resultsAdjusted hazard ratios comparing score quartiles 4 to 1 for total incidence and mortality of 13 smoking-related cancers were 3.89 (95% CI = 3.06 to 4.96) and 5.73 (95% CI = 4.08 to 8.06) before and 2.28 (95% CI = 1.65 to 3.15) and 2.07 (95% CI = 1.74 to 4.10) after adjusting for self-reported smoking. Adjusted hazard ratios for lung cancer were 12.1 (95% CI = 7.11 to 20.6) and 14.2 (95% CI = 7.58 to 26.8) before and 3.04 (95% CI = 1.59 to 5.81) and 4.12 (95% CI = 1.99 to 8.53) after adjusting. In European Prospective Investigation into Cancer and Nutrition, adjusted hazard ratios for lung cancer were 9.47 (95% CI = 6.82 to 13.15) before and 2.23 (95% CI = 1.48 to 3.35) after adjusting.
conclusionThe smoking-related protein score provided relative risk information for smoking-associated cancers beyond self-reported smoking, which was confirmed in an independent cohort. Such a score may be considered for use in risk stratification for prevention and cancer screening in settings in which detailed smoking history cannot be obtained.
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.
A smoking-related plasma protein score and smoking-related cancer risk and mortality in the Atherosclerosis Risk in Communities study. · full record | OpenQuestion