Evidence map›Paper›PMID 41328526›Full record

Observational studyAmerican journal of epidemiology2026

Calibrated dietary patterns and cancer risk in the women's health initiative cohorts.

Xiaochen Zhang, Sowmya Vasan, Cheng Zheng, Ross L Prentice, Sandi L Navarro, Lesley Tinker, Daniel Raftery, G A Nagana Gowda, Linda Van Horn, Yangbo Sun and 4 more

Abstract readObservational Study
In one paragraph

Observational study in American journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

14 authors.

Xiaochen ZhangPublic Health Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.ORCID 0000-0003-3086-1285
Sowmya VasanWomen's Health Initiative Coordinating Center, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.
Cheng ZhengDepartment of Biostatistics, College of Public Health, University of Nebraska Medical Center, 984375 Nebraska Medical Center, Omaha, NE 68198, United States.ORCID 0000-0002-6562-870X
Ross L PrenticePublic Health Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.
Sandi L NavarroPublic Health Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.
Lesley TinkerWomen's Health Initiative Coordinating Center, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.
Daniel RafteryPublic Health Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.
G A Nagana GowdaNorthwest Metabolomics Research Center, Mitochondria and Metabolism Center, Anesthesiology and Pain Medicine, University of Washington, 850 Republican Street, Room C429, Seattle, WA 98109, United States.
Linda Van HornPreventive Medicine, Feinberg School of Medicine, Northwestern University, 680 North Lake shore Drive #1400, Chicago, IL 60651, United States.ORCID 0000-0002-1362-5806
Yangbo SunDepartment of Preventive Medicine, College of Medicine, University of Tennessee Health Science Center, 66 N. Pauline, suite 633, Memphis, TN 38163, United States.
Fred K TabungDivision of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University Comprehensive Cancer Center, 410 West 12th Avenue, 302B Wiseman Hall/CCC, Columbus, OH 43210, United States.
Kathy PanHematology/Oncology, Kaiser Permanente, 9400 E Rosecrans Ave, Bellflower, CA 90706, United States.ORCID 0000-0003-3546-2566
Johanna W LampePublic Health Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.
Marian L NeuhouserPublic Health Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, United States.

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Eric Collisson · 1985 to 2026
$296.4M
Nutrition and Physical Activity Assessment Study (NPAAS)R01CA119171 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian L Neuhouser · 2006 to 2026
$14.3M
Lifestyle modification and cancer risk across the cancer control continuumK00CA253745 · NCI · OHIO STATE UNIVERSITY · PI ZHANG, XIAOCHEN · 2022 to 2025
$387k
NCI NIH HHS K00 CA253745NCI NIH HHS P30 CA015704NCI NIH HHS R01 CA119171NHLBI NIH HHS HHSN268201600001CNHLBI NIH HHS HHSN268201600002CNHLBI NIH HHS HHSN268201600003CNHLBI NIH HHS HHSN268201600004CNHLBI NIH HHS HHSN268201600018CWomen's Health Initiative (WHI) Program, which is supported by the National Heart, Lung, and Blood Institute HHSN268201600001CWomen's Health Initiative (WHI) Program, which is supported by the National Heart, Lung, and Blood Institute HHSN268201600002CWomen's Health Initiative (WHI) Program, which is supported by the National Heart, Lung, and Blood Institute HHSN268201600003CWomen's Health Initiative (WHI) Program, which is supported by the National Heart, Lung, and Blood Institute HHSN268201600004CWomen's Health Initiative (WHI) Program, which is supported by the National Heart, Lung, and Blood Institute HHSN268201600018C
6 · The paper itself

Abstract

We developed calibration equations using metabolomics from fasting blood and 24-hour urine for Healthy Eating Index 2010 (HEI-2010) and Alternative Healthy Eating Index 2010 to address measurement error from self-reported diet. We examined associations between metabolomic-calibrated dietary patterns and cancer risk in the Women's Health Initiative (WHI) (n = 108 522). Metabolomic signatures were created from a WHI Feeding (n = 153; 2010-2014) and WHI Observational Study (n = 450; 2006-2009). Dietary patterns were regressed on metabolites using the feeding study food intake records. Metabolomic-based dietary patterns were estimated from 24-hour dietary recalls, food frequency questionnaire and 4-day food record in the Observational Study using a stepwise approach. Cox regression estimated cancer risk of metabolomic-calibrated dietary patterns with a median follow-up of 15.8 years. Adjusted R2 for HEI-2010 and Alternative Healthy Eating Index 2010 calibration equations were 57.5% and 48.8% for food frequency questionnaire, 61.6% and 62.6% for 4-day food record, and 52.5% and 53.2% for dietary recalls. Without calibration, a 20% increment in HEI-2010 was associated with lower risk of colorectal (HR, 0.94; 95% CI, 0.90-0.99), lung (HR, 0.90; 95% CI, 0.86-0.94), bladder (HR, 0.86; 95% CI, 0.75-0.99), and total invasive cancers (HR, 0.98; 95% CI, 0.96-0.99). With metabolomic calibration, higher HEI-2010 was associated with lower risk of lung (HR, 0.79; 95% CI, 0.71-0.88) and total invasive cancers (HR, 0.96; 95% CI, 0.92-1.00). Metabolomic-calibrated dietary patterns might mitigate measurement errors and strengthen diet-cancer associations. Trial registration:  www.whi.org.

Indexed as

DietDiet, HealthyFeeding BehaviorNeoplasmsAgedCalibrationDiet RecordsFemaleHumansMetabolomicsMiddle AgedProportional Hazards ModelsRisk FactorsWomen's Healthcancer riskdietary patternsmetabolomicspostmenopausal women

Identifiers

PMID41328526
PMCPMC13267413

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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 Socratic graph.