Evidence map›Paper›PMID 34905061›Full record

ArticleThe Journal of nutrition2022

Biomarker-Based Methods and Study Designs to Calibrate Dietary Intake for Assessing Diet-Disease Associations.

Ying Huang, Cheng Zheng, Lesley F Tinker, Marian L Neuhouser, Ross L Prentice

Open access · greenAbstract read
In one paragraph

Article in The Journal of nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.2field-weighted citation impact, top 12% of its field
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

11 citing papers in PubMed, 15 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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

5 authors at 3 institutions in 1 country.

Ying HuangDivision of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.ORCID 0000-0002-9655-7502
Cheng ZhengDepartment of Biostatistics, University of Nebraska Medical Center, Omaha, NE, USA.ORCID 0000-0002-6562-870X
Lesley F TinkerDivision of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Marian L NeuhouserDivision of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Ross L PrenticeDivision of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
University of Washington · USFred Hutch Cancer Center · USUniversity of Nebraska Medical Center · US

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian Esvelt · 1985 to 2026
$296.4M
Tracking and Evaluation CoreU54GM115458 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI PHILIBERT, INGRID · 2016 to 2025
$42.8M
Nutrition and Physical Activity Assessment Study (NPAAS)R01CA119171 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian L Neuhouser · 2006 to 2026
$14.3M
NCI NIH HHS P30 CA015704NCI NIH HHS R01 CA119171NIDA NIH HHS HHSN271201600004CNIDA NIH HHS HHSN271201600004INIGMS NIH HHS U54 GM115458
6 · The paper itself

Abstract

backgroundDietary biomarkers measured in biospecimens can play an important role in correcting for random and systematic measurement error in self-reported nutrient intake when assessing diet-disease associations. To date, high-quality biomarkers for calibrating self-reported dietary intake have only been developed for a few nutrients.

objectivesTo investigate new study designs and regression calibration approaches for calibrating self-reported nutrient intake for use in disease association analyses.

methodsWe studied 3 regression calibration approaches: 1) an existing approach built on a calibration cohort assuming the existence of an objective biomarker (i.e., biomarker with random independent measurement error), 2) a proposed approach using a biomarker development cohort, and 3) a proposed 2-stage approach using both cohorts. We conducted simulation studies to compare the performance of different study designs/methods for estimating diet-disease associations and applied suitable methods to examine the association of sodium and potassium intake with cardiovascular disease (CVD) risk in Women's Health Initiative cohorts.

resultsSimulation studies showed that the first approach can lead to biased association estimation when the objective biomarker assumption is violated; the second and third proposed approaches obviate the need for such an objective biomarker. Precision for estimating the association depends critically on sample size of the biomarker development cohort and the strength of the self-reported nutrient intake. Analyses based on the second and third approaches support previously reported significant findings using the first approach about associations of the ratio of sodium to potassium intake with CVD risk while providing efficiency gain for some outcomes.

conclusionsSelf-reported dietary intake needs to be calibrated for measurement error correction in diet-disease association analyses. When there are no existing objective biomarkers that can be used for calibration purpose, controlled feeding studies can be used to develop new biomarkers for use in calibration or can be used to calibrate self-reported dietary intake directly.

Indexed as

Cardiovascular DiseasesDietBiomarkersEatingFemaleHumansPotassiumSodiumBiomarkersPotassiumSodiumbiomarkercardiovascular diseasedietmeasurement errorregression calibrationstudy design

Identifiers

PMID34905061
PMCPMC8891186
OpenAlexW4200559359

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.