Evidence map›Paper›PMID 41813601›Full record

ArticleInternational journal of cancer2026

Quantifying the contribution of modifiable risk factors for progression of MGUS to multiple myeloma in a Veteran population.

Mei Wang, Byron Sigel, Lawrence Liu, John H Huber, Mengmeng Ji, Martin W Schoen, Kristen M Sanfilippo, Theodore S Thomas, Graham A Colditz, Sylvia H Hsu and 2 more

Abstract read
In one paragraph

Article in International journal of cancer, 2026. 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
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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Mei WangResearch Service, St. Louis Veterans Affairs Medical Center, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-3560-9460
Byron SigelDepartment of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-1792-618X
Lawrence LiuCity of Hope Comprehensive Cancer Center, Duarte, California, USA.ORCID https://orcid.org/0000-0001-8559-7739
John H HuberDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0001-5245-5187
Mengmeng JiResearch Service, St. Louis Veterans Affairs Medical Center, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-1205-0369
Martin W SchoenResearch Service, St. Louis Veterans Affairs Medical Center, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0001-6388-5553
Kristen M SanfilippoResearch Service, St. Louis Veterans Affairs Medical Center, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-0433-7845
Theodore S ThomasResearch Service, St. Louis Veterans Affairs Medical Center, St. Louis, Missouri, USA.
Graham A ColditzDivision of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-7307-0291
Sylvia H HsuSchulich School of Business, York University, Toronto, Ontario, Canada.ORCID https://orcid.org/0000-0001-5872-9556
Shi-Yi WangYale School of Public Health, Yale University, New Haven, Connecticut, USA.ORCID https://orcid.org/0000-0002-3294-5784
Su-Hsin ChangResearch Service, St. Louis Veterans Affairs Medical Center, St. Louis, Missouri, USA.

Funding

Comparative modeling of multiple myeloma across myeloma control continuuum: prevention, treatment, and disparity reductionU01CA265735 · NCI · WASHINGTON UNIVERSITY · PI CHANG, SU-HSIN, WANG, SHIYI · 2021 to 2025
$3.2M
Addressing racial disparities in monoclonal gammopathy of undetermined significance and progression to multiple myeloma from a prevention perspectiveR01CA253475 · NCI · WASHINGTON UNIVERSITY · PI CHANG, SU-HSIN · 2020 to 2022
$1.1M
Alvin J. Siteman Cancer CenterFundation for Barnes-Jewish HospitalNCI NIH HHS R01 CA253475NCI NIH HHS U01 CA265735NIH HHS R01 CA253475NIH HHS U01 CA265735
6 · The paper itself

Abstract

Multiple myeloma (MM) is the most common plasma cell dyscrasia in the United States with tremendously high burden. MM is preceded by a premalignant condition, monoclonal gammopathy of undetermined significance (MGUS). Although several risk factors for progression have been identified (e.g., older age, male sex, black race, obesity, chemical exposure), their relative contributions remain unclear. Unlike other malignancies, such evidence is lacking for MM despite its high burden. To identify potential intervention strategies that can effectively prevent progression in patients with MGUS, we quantified contributions of the identified modifiable risk factors in the United States Veteran population with MGUS. Compared to the general population, this population is particularly vulnerable to MM as its higher proportions of male and older age as well as the potential prior Agent Orange exposure. We conducted a retrospective cohort study in the Veterans Health Administration and calculated multivariable-adjusted population attributable fractions (aPAFs) of progression accounting for competing risk of death. The aPAF estimates the proportion of progression burden in the population with MGUS that is statistically attributable to a specific risk factor, independent of other factors. In the cohort of 35,073 Veterans with MGUS, among all evaluated risk factors (both modifiable and non-modifiable), excess body mass index (BMI ≥25 kg/m

Indexed as

Monoclonal Gammopathy of Undetermined SignificanceMultiple MyelomaVeteransAgedDisease ProgressionFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsUnited Statesmodifiable risk factormonoclonal gammopathy of undetermined significancemultiple myelomapopulation attributable fractionveterans

Identifiers

PMID41813601
PMCPMC13004480

What Socratic holds

Textmetadata
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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 Socratic graph.