Evidence map›Paper›PMID 33540472›Full record

ArticleStatistics in medicine2021

Hybrid design evaluating new biomarkers when there is an existing screening test.

Yeonhee Park, Ying Yuan, Jing Ning, Suyu Liu, Ziding Feng

Open access · greenAbstract read
In one paragraph

Article in Statistics in medicine, 2021. 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, top 97% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

5 authors at 3 institutions in 1 country.

Yeonhee ParkDepartment of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA.ORCID 0000-0001-9645-3407
Ying YuanDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0003-3163-480X
Jing NingDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.ORCID 0000-0002-5289-331X
Suyu LiuDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Ziding FengPublic Health Sciences Division, Fred Hutch, Seattle, Washington, USA.
The University of Texas MD Anderson Cancer Center · USFred Hutch Cancer Center · USUniversity of Wisconsin–Madison · US

Funding

The Early Detection Research Network: Data Management and Coordinating CenterU24CA086368 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI RUTH D ETZIONI, Ziding Feng · 2010 to 2026
$75.7M
Consortium for the Study of Chronic Pancreatitis, Diabetes and Pancreatic Cancer: Coordinating and Data Management Center (CSCPDPC-CDMC)U01DK108328 · NIDDK · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Liang Li, Suyu Liu · 2015 to 2026
$32.8M
Consortium on Translational Research in Early Detection of Liver Cancer:Data Management and Coordinating Center (DMCC)U24CA230144 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Ziding Feng · 2018 to 2026
$5.8M
NCI NIH HHS U24 CA086368NCI NIH HHS U24 CA230144NIDDK NIH HHS U01 DK108328
6 · The paper itself

Abstract

Development of cancer screening biomarkers usually follows the Early Detection Research Network 5-Phase guideline in Pepe et al. A key feature of this guide is that the phased development follows a sequential order, moving to the next phase only when the current phase study is complete and has met its target performance. Motivated by a newly funded Newly onset Diabetes cohort study, we propose a design evaluating new biomarkers to discriminate between cases and controls in the presence of an existing screening test. The proposed design achieves two goals: (1) avoiding bias in estimating sensitivity or specificity in predicting cancer at a given time period prior to clinical diagnosis, using data from both screening detected cancers in Phase IV study and clinically diagnosed cancers in Phase III study; and (2) building a panel with biomarkers for Phase III and IV studies based on all data. A simulation study shows that the proposed design outperforms both a conventional method using data in Phase III arm only and a naive method using data in Phase III and IV arms ignoring the difference between the time of screening the detected cancer and the time of clinical diagnosis. The proposed design yields a smaller standard error of the estimation and increases the statistical power to confirm biomarker performance. This proposed method has the potential to shorten the cancer screening biomarker development process, use resources more effectively, and bring benefits to patients quickly.

Indexed as

Diagnostic Tests, RoutineEarly Detection of CancerBiomarkersClinical Trials as TopicCohort StudiesHumansMass ScreeningResearch DesignBiomarkersbiomarker panellogistic regressionmultiple imputationNoD cohort study

Identifiers

PMID33540472
PMCPMC8411462
OpenAlexW3127428342

What OpenQuestion holds

Textmetadata
LicenceTDM
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.