Evidence map›Paper›PMID 35642720›Full record

ArticleJournal of cellular and molecular medicine2022

Frequency of benign neutropenia among Black versus White individuals undergoing a bone marrow assessment.

Scott C Borinstein, David Agamasu, Jonathan S Schildcrout, Lisa Bastarache, Minoo Bagheri, Lea K Davis, Dan M Roden, C Michael Stein, Sara L Van Driest, Jonathan D Mosley

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Ancestry,Lupus science & medicine · 2022
    Article
  7. Article
  8. 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

10 authors at 2 institutions in 1 country.

Scott C BorinsteinDepartment of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.ORCID 0000-0002-1721-1520
David AgamasuMeharry Medical College, Nashville, Tennessee, USA.
Jonathan S SchildcroutDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Lisa BastaracheDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Minoo BagheriDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Lea K DavisDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Dan M RodenDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
C Michael SteinDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Sara L Van DriestDepartment of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jonathan D MosleyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Vanderbilt University Medical Center · USMeharry Medical College · US

Funding

The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
From GWAS to PheWAS: Scanning the EMR Phenome for Gene-disease AssociationsR01LM010685 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BASTARACHE, LISA · 2011 to 2022
$6.3M
VGM: Vanderbilt Genomic Medicine Training ProgramT32HG008341 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Nancy J Cox, Joseph F. Peterson · 2016 to 2026
$2.8M
Leveraging common genetic variation to reduce misclassification of non-diseased individuals and unnecessary health care utilization attributable to surrogate biomarkersR01GM130791 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MOSLEY, JONATHAN DAVID · 2019 to 2023
$2.3M
NCATS NIH HHS UL1 TR000445NCATS NIH HHS UL1TR000445NHGRI NIH HHS T32 HG008341NIGMS NIH HHS R01 GM130791NLM NIH HHS R01 LM010685
6 · The paper itself

Abstract

Healthy individuals in the United States identified as having Black race have lower neutrophil counts, on average, than individuals identified as having White race, which could result in more negative diagnostic evaluations for neutropenia. To test this hypothesis, the proportion of evaluations where the final diagnosis was clinically insignificant neutropenia for Black and White individuals who underwent an evaluation by a haematologist that included a bone marrow (BM) biopsy to investigate neutropenia was assessed. 172 individuals without prior haematological diagnoses who underwent a haematological evaluation to investigate neutropenia. Individuals diagnosed with clinically insignificant neutropenia between Black and White individuals were compared using a propensity-score-adjusted logistic regression. Of 172 individuals, 42 (24%) were classified as Black race, 86 (50%) were males, and the 79 (46%) were over 18 years old. A BM biopsy did not identify pathology in 95% (40 of 42) of Black individuals and 68% (89 of 130) of White Individuals. Black individuals (25 of 42 [60%]) received a final diagnosis of clinically insignificant neutropenia, compared to White individuals (12 of 130 [9%]) (adjusted odds ratio =7.9, 95% CI: 3.1 - 21.1). We conclude that black individuals were more likely to receive a diagnosis of clinically insignificant neutropenia after haematological assessment.

Indexed as

Bone MarrowNeutropeniaAdolescentFemaleHumansLeukocyte CountMaleOdds RatioUnited StatesWhite Peoplebone marrow biopsyneutropeniaracial differences

Identifiers

PMID35642720
PMCPMC9258701
OpenAlexW4281703754

What OpenQuestion 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 OpenQuestion graph.