Evidence map›Paper›PMID 40047060›Full record

ArticleCancer medicine2025

Difference-Makers for Collecting Sexual Orientation and Gender Identity Data in Oncology Settings.

Mandi L Pratt-Chapman, Edward J Miech, Megan A Mullins, Shine Chang, Gwendolyn P Quinn, Shail Maingi, Matthew B Schabath, Charles Kamen

Abstract read
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In one paragraph

Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

8 authors.

Mandi L Pratt-ChapmanDepartment of Medicine, GW Cancer Center, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.ORCID https://orcid.org/0000-0002-9303-7659
Edward J MiechDepartment of Emergency Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Megan A MullinsO'Donnell School of Public Health, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0003-2753-9068
Shine ChangDivision of Cancer Prevention and Population Sciences, Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Gwendolyn P QuinnDepartments of OB-GYN, Population Health, Perlmutter Cancer Center, Grossman School of Medicine, New York University, New York City, New York, USA.ORCID https://orcid.org/0000-0002-4208-9889
Shail MaingiDana-Farber Cancer Institute, Cancer Care Equity Program, Boston, Massachusetts, USA.
Matthew B SchabathDepartment of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.ORCID https://orcid.org/0000-0003-3241-3216
Charles KamenUniversity of Rochester Medical Center, Rochester, New York, USA.ORCID https://orcid.org/0000-0002-4219-4320

Funding

American Society of Clinical Oncology
6 · The paper itself

Abstract

purposeThe purpose of this analysis was to identify key difference-making conditions that distinguish oncology institutions that collect sexual orientation and gender identity (SOGI) data across a sample of American Society of Clinical Oncology (ASCO) members.

methodsFrom October to November 2020, an anonymous 54-item web-based survey was distributed to ASCO members. Coincidence analysis was used to identify difference-making conditions for the collection of SOGI data.

resultsASCO members' responses to just three items consistently distinguished practices that reported collecting both SO and GI data (n = 25) from those who did not (n = 20): (1)."Do you ask your patients what pronouns they want you to use for them?"; (2) "Institutional leadership supports collecting SOGI data from patients"; and (3)"Does the electronic health record (EHR) at your institution have a specific section to collect information about patients' SOGI?" The positive model exhibited both reliability (consistency = 0.87, or 20/23) and explanatory breadth (coverage = 0.80, or 20/25). The negative model for SOGI data collection consisted of different responses to the same three items and likewise showed both reliability (consistency = 0.94, or 16/17) and explanatory breadth (coverage = 0.80, or 16/20).

conclusionsSpecific levels of leadership support, frequency of asking patients about pronouns, and the presence or absence of EHR record structure were difference-makers for collecting SOGI data in this sample. The study underscores the importance of leadership support, structured data fields, and attention to patient pronouns, which are aligned with the ASCO and National Institutes of Health calls to action.

Indexed as

Data CollectionGender IdentityMedical OncologySexual BehaviorElectronic Health RecordsFemaleHumansMaleSurveys and QuestionnairesUnited Statescoincidence analysisgender identityimplementationoncologysexual orientation

Identifiers

PMID40047060
PMCPMC11883291

What OpenQuestion holds

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LicenceCC BY
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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.