Evidence map›Paper›PMID 40509873›Full record

ArticleJournal of the National Cancer Institute2025

Trends in uterine cancer incidence and mortality: insights from a natural history model.

William D Hazelton, Matthew Prest, Ling Chen, Kevin Rouse, Elena B Elkin, Jennifer S Ferris, Xiao Xu, Nina A Bickell, Chung Yin Kong, Stephanie Blank and 7 more

Abstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

17 authors.

William D HazeltonDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States.ORCID 0000-0002-7975-5080
Matthew PrestColumbia University Irving Cancer Research Center, New York, NY, United States.ORCID 0000-0002-3956-516X
Ling ChenColumbia University Irving Cancer Research Center, New York, NY, United States.ORCID 0000-0001-9646-6697
Kevin RouseColumbia University Irving Cancer Research Center, New York, NY, United States.ORCID 0009-0009-6021-5154
Elena B ElkinColumbia University Irving Cancer Research Center, New York, NY, United States.
Jennifer S FerrisColumbia University Irving Cancer Research Center, New York, NY, United States.
Xiao XuColumbia University Irving Cancer Research Center, New York, NY, United States.ORCID 0000-0001-6519-1731
Nina A BickellTisch Cancer Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Chung Yin KongTisch Cancer Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0001-6431-7830
Stephanie BlankTisch Cancer Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0003-0605-6753
Eric J FeuerNational Cancer Institute, Bethesda, MD, United States.ORCID 0000-0003-4842-7751
Goli SamimiNational Cancer Institute, Bethesda, MD, United States.ORCID 0000-0002-0674-003X
Brandy M Heckman-StoddardNational Cancer Institute, Bethesda, MD, United States.ORCID 0000-0003-1686-7154
Tracy M LayneTisch Cancer Center, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID 0000-0002-3733-4886
Jason D WrightColumbia University Irving Cancer Research Center, New York, NY, United States.ORCID 0000-0001-6390-825X
Evan R MyersDepartment of Obstetrics and Gynecology, Duke University School of Medicine, Duke Cancer Institute, Durham, NC, United States.ORCID 0000-0002-9053-9864
Laura J HavrileskyDepartment of Obstetrics and Gynecology, Duke University School of Medicine, Duke Cancer Institute, Durham, NC, United States.ORCID 0000-0002-4259-5992

Funding

Comparative Modeling for the Prevention and Control of Uterine CancerU01CA265739 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BICKELL, NINA A., BLANK, STEPHANIE V. · 2021 to 2025
$4.2M
Cancer Intervention and Surveillance Modeling Network Uterine Incubator U01CA265739NCI NIH HHSNCI NIH HHS U01 CA265739NIH HHS
6 · The paper itself

Abstract

backgroundUterine cancer incidence and mortality are increasing, with concomitant disparities in outcomes between racial groups. Natural history modeling can evaluate risk factors, predict future trends, and simulate approaches to reducing mortality and disparities.

methodsWe designed a natural history model of uterine cancer using a multistage clonal expansion design. The model is informed by National Health and Nutrition Examination Survey, National Health Examination Survey, age, time period, birth cohort, and birth certificate data on reproductive histories and body mass index (BMI). We fit and calibrated the model to Surveillance, Epidemiology, and End Results data by race and ethnicity as well as histologic subgroup. We projected future incidence and estimated the degree of contribution of BMI, reproductive history, and competing hysterectomy to excess uterine cancer incidence.

resultsThe model accurately replicated Surveillance, Epidemiology, and End Results incidence for endometrioid, nonendometrioid, and sarcoma subgroups for non-Hispanic Black and non-Hispanic White patients. For endometrioid, nonendometrioid, and sarcomas, BMI-attributable risks are greater for non-Hispanic White than for non-Hispanic Black patients; reproductive history-attributable risks are greater for non-Hispanic Black patients. Between 2018 and 2050, endometrioid incidence is projected to rise by 64.9% in non-Hispanic Black individuals and17.5% in non-Hispanic White individuals; the projected rise for the nonendometrioid subgroup is 41.4% in non-Hispanic Black individuals and 22.5% in non-Hispanic White individuals; the sarcoma incidence projected increase is 36% in non-Hispanic Black individuals and 29.2% in non-Hispanic White individuals.

conclusionsUterine cancer risk is substantially explained by reproductive history and BMI, with differences observed between non-Hispanic Black and non-Hispanic White individuals and future projections indicating perpetuation of disparities. Lower rates of hysterectomy and rising obesity rates will likely contribute to continued increases in uterine cancer incidence.

Indexed as

Uterine NeoplasmsAdultAgedBlack or African AmericanBody Mass IndexFemaleHumansHysterectomyIncidenceMiddle AgedNutrition SurveysReproductive HistoryRisk FactorsSEER ProgramUnited StatesWhite

Identifiers

PMID40509873
PMCPMC12415960

What Socratic holds

Textmetadata
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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.