Article in Cancer prevention research (Philadelphia, Pa.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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
25 authors.
Prasoona KarraDepartment of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, Utah.ORCID 0009-0008-5209-9846
Sheetal HardikarDepartment of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, Utah.ORCID 0000-0003-0292-6168
Maci WinnCancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, Utah.ORCID 0000-0001-7363-0626
Garnet L AndersonDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington.ORCID 0000-0001-5087-7837
Benjamin HaalandCancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, Utah.ORCID 0000-0002-6270-6303
Aladdin H ShadyabHerbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, California.ORCID 0000-0002-9693-0522
Marian L NeuhouserDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington.ORCID 0000-0002-3876-0000
Rebecca A Seguin-FowlerInstitute for Advancing Health through Agriculture, Texas A&M University System, College Station, Texas.ORCID 0000-0002-5115-2341
Marcia L StefanickStanford Prevention Research Center, Stanford, California.ORCID 0000-0002-0284-6996
Xiaochen ZhangDepartment of Internal Medicine, The Ohio State University College of Medicine and Comprehensive Cancer Center, Columbus, Ohio.ORCID 0000-0003-3086-1285
Ting-Yuan David ChengDepartment of Internal Medicine, The Ohio State University College of Medicine and Comprehensive Cancer Center, Columbus, Ohio.ORCID 0000-0002-4105-828X
Yangbo SunUniversity of Tennessee Health Science Center, Memphis, Tennessee.ORCID 0000-0003-0377-4450
Nazmus SaquibSulaiman AlRajhi University, Al Bukayriyah, Kingdom of Saudi Arabia.ORCID 0000-0002-2819-2839
Margaret S PichardoDepartment of Surgery, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.ORCID 0000-0002-9132-4400
Su Yon JungTranslational Sciences Section, School of Nursing, Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California.ORCID 0000-0002-0513-1830
Fred K TabungDepartment of Internal Medicine, The Ohio State University College of Medicine and Comprehensive Cancer Center, Columbus, Ohio.ORCID 0000-0001-8193-7150
Scott A SummersDepartment of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, Utah.ORCID 0000-0002-4919-0592
William L HollandDepartment of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, Utah.ORCID 0000-0001-9950-1435
Thunder JaliliDepartment of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, Utah.ORCID 0000-0002-7821-2287
Marc J GunterCancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-5472-6761
Mary C PlaydonDepartment of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, Utah.ORCID 0000-0001-6082-0447
Funding
Translational Therapeutics Research Program (TT)P30CA016058 · NCI · OHIO STATE UNIVERSITY · PI Daniel G. Stover · 1985 to 2026
$132.3M
Ceramides as novel drivers of metabolic dysfunction and colorectal cancerU01CA272529 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Mary Christine Playdon, SCOTT A SUMMERS · 2022 to 2026
$4.7M
The Role of Ceramides in the Pancreatic Beta CellR01DK130296 · NIDDK · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI HOLLAND, WILLIAM L, SUMMERS, SCOTT A · 2022 to 2025
$2.2M
Diabetes, Medications and the Cost-Effectiveness of Screening for Colorectal NeoplasiaK07CA222060 · NCI · UNIVERSITY OF UTAH · PI HARDIKAR, SHEETAL · 2018 to 2022
$791k
Blood metabolite profiles and risk of developing endometrial cancerR00CA218694 · NCI · UNIVERSITY OF UTAH · PI PLAYDON, MARY CHRISTINE · 2018 to 2020
$747k
Lifestyle modification and cancer risk across the cancer control continuumK00CA253745 · NCI · OHIO STATE UNIVERSITY · PI ZHANG, XIAOCHEN · 2022 to 2025
$387k
Metabolic health phenotype, accelerated aging and obesity-related cancer risk and mortalityK00CA264400 · NCI · DARTMOUTH COLLEGE · PI KARRA, PRASOONA · 2022 to 2024
$300k
Metabolic health phenotype, accelerated aging and obesity-related cancer risk and mortalityF99CA264400 · NCI · UNIVERSITY OF UTAH · PI KARRA, PRASOONA · 2021 to 2022
$36k
Division of Cancer Prevention, National Cancer Institute (DCP, NCI) 5R00CA218694-03Division of Cancer Prevention, National Cancer Institute (DCP, NCI) F99CA264400Division of Cancer Prevention, National Cancer Institute (DCP, NCI) K00CA253745Huntsman Cancer Institute, University of Utah (HCI) P30CA040214NCI NIH HHS F99 CA264400NCI NIH HHS K00 CA253745NCI NIH HHS K00 CA264400NCI NIH HHS K07 CA222060NCI NIH HHS P30 CA016058NCI NIH HHS R00 CA218694NCI NIH HHS U01 CA272529NIDDK NIH HHS R01 DK130296World Health Organization 001
6 · The paper itself
Abstract
Body mass index (BMI) may misclassify obesity-related cancer (ORC) risk, as metabolic dysfunction can occur across BMI levels. We hypothesized that metabolic dysfunction at any BMI increases ORC risk compared with normal BMI without metabolic dysfunction. Postmenopausal women (n = 20,593) in the Women's Health Initiative with baseline metabolic dysfunction biomarkers [blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, fasting glucose, homeostatic model assessment for insulin resistance (HOMA-IR), and high-sensitive C-reactive protein (hs-CRP)] were included. Metabolic phenotype (metabolically healthy normal weight, metabolically unhealthy normal weight, metabolically healthy overweight/obese, and metabolically unhealthy overweight/obese) was classified using four definitions of metabolic dysfunction: (i) Wildman criteria, (ii) National Cholesterol Education Program Adult Treatment Panel III, (iii) HOMA-IR, and (iv) hs-CRP. Multivariable Cox proportional hazards regression, with death as a competing risk, was used to assess the association between metabolic phenotype and ORC risk. After a median (IQR) follow-up duration of 21 (IQR, 15-22) years, 2,367 women developed an ORC. The risk of any ORC was elevated among metabolically unhealthy normal weight (HR = 1.12, 95% CI, 0.90-1.39), metabolically healthy overweight/obese (HR = 1.15, 95% CI, 1.00-1.32), and metabolically unhealthy overweight/obese (HR = 1.35, 95% CI, 1.18-1.54) individuals compared with metabolically healthy normal weight individuals using Wildman criteria. The results were similar using Adult Treatment Panel III criteria, hs-CRP alone, or HOMA-IR alone to define metabolic phenotype. Individuals with overweight or obesity with or without metabolic dysfunction were at higher risk of ORCs compared with metabolically healthy normal weight individuals. The magnitude of risk was greater among those with metabolic dysfunction, although the CIs of each category overlapped. Prevention Relevance: Recognizing metabolic dysfunction as a significant risk factor for ORCs underscores the importance of preventive measures targeting metabolic health improvement across all BMI categories.
Indexed as
NeoplasmsObesityAgedBiomarkersBody Mass IndexFemaleFollow-Up StudiesHumansInsulin ResistanceMiddle AgedPhenotypePostmenopauseRisk FactorsWomen's HealthBiomarkers
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.
Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women's Health Initiative. · full record | OpenQuestion