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 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.
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
17 authors.
Shuo WangDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0003-4627-8625
Zexi RaoDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0001-9640-3725
Anne H BlaesDivision of Hematology, Oncology and Transplantation, Department of Medicine, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0002-5433-4810
Josef CoreshOptimal Aging Institute, NYU Grossman School of Medicine, New York, NY, United States.ORCID 0000-0002-4598-0669
Corinne E JoshuDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-5100-172X
James S PankowDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, United States.
Bharat ThyagarajanDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0001-6968-6985
Ruth DubinDivision of Nephrology, University of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID 0000-0002-0498-1980
Rajat DeoDivision of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-8250-2607
Seamus P WheltonJohns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Michael J BlahaJohns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease, Johns Hopkins University School of Medicine, Baltimore, MD, United States.ORCID 0000-0001-5138-9683
Catherine H MarshallDepartment of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.ORCID 0000-0002-2653-4110
Jerome I RotterInstitute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical Center, Torrance, CA, United States.ORCID 0000-0001-7191-1723
Peter GanzDivision of Cardiology, Zuckerberg San Francisco General Hospital, San Francisco, CA, United States.ORCID 0000-0002-0437-8882
Weihua GuanDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0002-0956-9821
Elizabeth A PlatzDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-3676-8954
Anna PrizmentDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0003-1932-6548
Funding
UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MILES Frome WILKINSON · 2003 to 2026
$40.4M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UM1TR004405 · NCATS · UNIVERSITY OF MINNESOTA · PI Bruce R Blazar, Damien A Fair · 2023 to 2026
$30.8M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
Task Area A Core Study Operations.Task Area A shall encompass annual follow-up of cohort members, clinical endpoints ascertainment, study coordination activities, maintenance of the database and biosp75N92020D00001 · NHLBI · UNIVERSITY OF WASHINGTON · PI MCCLELLAND, ROBYN LEAGH · 2020 to 2025
$17.2M
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
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00003 · NHLBI · UNIVERSITY OF MINNESOTA · PI LUTSEY, PAMELA L. · 2022 to 2025
$5.1M
Task Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00005 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WATSON, KAROL E · 2020 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
backgroundTo estimate biological age, we developed a proteomic aging clock in cancer-free participants (CaPAC) and examined its association with mortality in long-term cancer survivors (LTCS, >2 years between cancer diagnosis and blood collection) and cancer-free participants in the Atherosclerosis Risk in Communities (ARIC) and Multi-Ethnic Study of Atherosclerosis (MESA) studies.
methodsARIC measured 4712 proteins using SomaScan in plasma samples collected at 3 visits, including Visit 5 (2011-2013) from 806 LTCS and 3699 cancer-free participants, all aged 66-90. Among 2466 randomly selected cancer-free participants, we developed CaPAC using elastic net regression. Age acceleration was calculated as residuals of CaPAC regressed on chronological age (CaPACAccel). We used multivariable Cox proportional hazards regression to calculate hazard ratios (HRs) for the associations of CaPACAccel with all-cause and cancer mortality in LTCS and all-cause mortality in the remaining cancer-free participants. We replicated the analysis of all-cause mortality in MESA.
resultsIn LCTS, CaPACAccel was associated with increased all-cause mortality in both ARIC (HR per 1 SD = 1.42, 95% confidence interval [CI] = 1.24 to 1.62; P < .001) and MESA (1.62, 1.12 to 2.33; P = .009). Also, in ARIC, CaPACAccel was associated with all-cause mortality in breast (1.54, 1.05 to 2.25; P = .028) and colorectal LTCS (1.96, 1.19 to 3.22; P = .008). Additionally, CaPACAccel was associated with cancer mortality in LTCS (1.34, 1.09 to 1.64; P = .005) in ARIC. In MESA, limited sample size precluded us from examining individual cancers and cause-specific mortality. In cancer-free participants, the associations of CaPACAccel with all-cause mortality were similar across studies.
conclusionProteomic aging clocks hold promise as a predictor of all-cause and cancer mortality in LTCS.
Indexed as
AgingCancer SurvivorsNeoplasmsProteomicsAgedAged, 80 and overFemaleHumansMaleProportional Hazards ModelsRisk 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.
Proteomic aging clocks and the risk of mortality among long-term cancer survivors. · full record | OpenQuestion