Evidence map›Paper›PMID 39853431›Full record

ArticleArchives of dermatological research2025

The impact of imprecise case definitions in electronic health record research: a melanoma case-study from the Million Veteran Program.

Lee Wheless, Dominique Mosley, Daniel Dochtermann, Saiju Pyarajan, Katlyn Gonzalez, Rachel Weiss, Kyle Maas, Siwei Zhang, Lydia Yao, Yaomin Xu and 11 more

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of dermatological research, 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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. 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

21 authors.

Lee Wheless *Tennessee Valley Healthcare System VA Medical Center, 719 Thompson Lane, Suite 26300, Nashville, TN, 37215, USA. lee.e.wheless@vumc.org.
Dominique Mosley *Vanderbilt University School of Medicine, Nashville, TN, USA.
Daniel DochtermannVA Boston Healthcare System, Boston, MA, USA.
Saiju PyarajanVA Boston Healthcare System, Boston, MA, USA.
Katlyn GonzalezVanderbilt University School of Medicine, Nashville, TN, USA.
Rachel WeissDepartment of Dermatology, Nashville, TN, USA.
Kyle MaasVanderbilt University School of Medicine, Nashville, TN, USA.
Siwei ZhangDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
Lydia YaoDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
Yaomin XuDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
Christopher MaddenState University of New York Downstate College of Medicine, Brooklyn, NY, USA.
Jacqueline IkeMeharry Medical College, Nashville, TN, USA.
Isabelle T SmithVanderbilt University, Nashville, TN, USA.
Sarah GrossarthQuillen College of Medicine, East Tennessee State University, Johnson City, TN, USA.
Otis WilsonTennessee Valley Healthcare System VA Medical Center, 719 Thompson Lane, Suite 26300, Nashville, TN, 37215, USA.
Adriana HungTennessee Valley Healthcare System VA Medical Center, 719 Thompson Lane, Suite 26300, Nashville, TN, 37215, USA.
Nathanael R FillmoreVA Boston Healthcare System, Boston, MA, USA.
Kevin BrownDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Maria Teresa LandiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
Rebecca I HartmanVA Boston Healthcare System, Boston, MA, USA.
VA Million Veteran Program

Funding

CSRD VA I01 CX001897CSRD VA IK2 CX002452CSRD VA IK2 CX002531
6 · The paper itself

Abstract

Cases for a disease can be defined broadly using diagnostic codes, or narrowly using gold-standard confirmation that often is not available in large administrative datasets. These different definitions can have significant impacts on the results and conclusions of studies. We conducted this study to assess how using melanoma phecodes versus histologic confirmation for invasive or in situ melanoma impacts the results of a genome-wide association study (GWAS) using the Million Veteran Program. Melanoma status was determined three ways: (1) by the presence of two or more phecodes, (2) histologically-confirmed invasive melanoma, and (3) histologically-confirmed melanoma in situ. We conducted a GWAS for variants with minor allele frequencies of 1% or greater. There were 45,665 cases in the phecode cohort, 5364 cases in the confirmed invasive melanoma cohort, and 4792 cases in the confirmed melanoma in situ cohort. There were 20,457 variants significant at the genome-wide level in the phecode cohort, 2582 in the invasive melanoma cohort, and 1989 in the melanoma in situ cohort. Most of the variants identified in the phecode cohort did not replicate in the histologically-confirmed cohorts. The different case definitions led to large differences in sample size and variants associated at the genome-wide level. Unvalidated and imprecise case definitions can lead to less accurate results. Investigators should use validated phenotypes when gold-standard definitions are not available.

Indexed as

Electronic Health RecordsMelanomaSkin NeoplasmsAgedFemaleGene FrequencyGenome-Wide Association StudyHumansMaleMiddle AgedUnited StatesVeteransCohort studyEpidemiologySkin cancer

Identifiers

What OpenQuestion holds

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Registered trials

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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.