Evidence map›Paper›PMID 37599686›Full record

ArticleFrontiers in nutrition2023

Regression calibration utilizing biomarkers developed from high-dimensional metabolites.

Yiwen Zhang, Ran Dai, Ying Huang, Ross L Prentice, Cheng Zheng

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2023. 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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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.

Yiwen Zhang *Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.
Ran Dai *Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, United States.
Ying HuangPublic Health Science Division, Fred Hutchinson Cancer Center, Seattle, WA, United States.
Ross L PrenticePublic Health Science Division, Fred Hutchinson Cancer Center, Seattle, WA, United States.
Cheng ZhengDepartment of Biostatistics, University of Nebraska Medical Center, Omaha, NE, United States.

Funding

Tracking and Evaluation CoreU54GM115458 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI RIZZO, MATTHEW · 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
Accelerating biomarker development through novel statistical methods for analyzing phase III/IV studiesR01CA277133 · NCI · FRED HUTCHINSON CANCER CENTER · PI Ying Huang · 2023 to 2026
$1.6M
NCI NIH HHS R01 CA119171NCI NIH HHS R01 CA277133NHLBI NIH HHS HHSN268201600001CNHLBI NIH HHS HHSN268201600002CNHLBI NIH HHS HHSN268201600003CNHLBI NIH HHS HHSN268201600004CNHLBI NIH HHS HHSN268201600018CNIGMS NIH HHS U54 GM115458
6 · The paper itself

Abstract

Addressing systematic measurement errors in self-reported data is a critical challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been utilized for error correction when an objectively measured biomarker is available; however, biomarkers for only a few dietary components have been developed. This paper proposes to use high-dimensional objective measurements to construct biomarkers for many more dietary components and to estimate the diet disease associations. It also discusses the challenges in variance estimation in high-dimensional regression methods and presents a variety of techniques to address this issue, including cross-validation, degrees-of-freedom corrected estimators, and refitted cross-validation (RCV). Extensive simulation is performed to study the finite sample performance of the proposed estimators. The proposed method is applied to the Women's Health Initiative cohort data to examine the associations between the sodium/potassium intake ratio and the total cardiovascular disease.

Indexed as

biomarkerfeeding studyhigh-dimensional datameasurement errorregression calibration

Identifiers

PMID37599686
PMCPMC10433218

What Socratic holds

Textmetadata
LicenceCC BY
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.