Evidence map›Paper›PMID 42480210›Full record

ArticleBlood advances2026

Evolution of real-world frontline treatment patterns in multiple myeloma.

Alexander Lazzaro, Kaelyn Nannini, Cenk Yildirim, Linden Huhmann, John M Culnan, June K Corrigan, Danne Elbers, Nhan V Do, Mary Brophy, Nikhil Munshi and 2 more

Abstract read
In one paragraph

Article in Blood advances, 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

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

12 authors.

Alexander LazzaroSection of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston, MA.ORCID 0009-0009-5790-0767
Kaelyn NanniniCooperative Studies Program Informatics Center, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.
Cenk YildirimCooperative Studies Program Informatics Center, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.
Linden HuhmannCooperative Studies Program Informatics Center, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.ORCID 0000-0002-2266-7610
John M CulnanCooperative Studies Program Informatics Center, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.ORCID 0000-0001-7327-1053
June K CorriganCooperative Studies Program Informatics Center, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.
Danne ElbersCooperative Studies Program Informatics Center, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.ORCID 0000-0002-0454-0173
Nhan V DoSection of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston, MA.
Mary BrophySection of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston, MA.
Nikhil MunshiSection of Hematology, VA Boston Healthcare System, West Roxbury, MA.
Nathanael R FillmoreSection of General Internal Medicine, Department of Medicine, Boston Medical Center, Boston, MA.ORCID 0000-0002-8058-3423
Camille V EdwardsCooperative Studies Program Informatics Center, Massachusetts Veterans Epidemiology Research and Information Center, Boston, MA.ORCID 0000-0002-2601-0667

Funding

AIM-AHEAD Coordinating Center - All Four CoresOT2OD032581 · OD · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI Paul Avillach, Bettina M. Beech · 2021 to 2026
$168.7M
Targeting Genomic Instability and Evolution in MyelomaP01CA155258 · NCI · DANA-FARBER CANCER INST · PI Nikhil C. Munshi · 2011 to 2026
$32.5M
BLRD VA I01 BX001584National Institutes of Health (NIH), National Cancer Institute (NCI) 3P01-CA155258-07S1National Institutes of Health (NIH), National Cancer Institute (NCI) 3P01-CA155258-07S2NCI NIH HHS P01 CA155258NIAID NIH HHS P01-155252-07NIH HHS OT2 OD032581
6 · The paper itself

Abstract

abstractThe number of Food and Drug Administration-approved treatments for multiple myeloma (MM), the second most common hematologic malignant neoplasm, has increased substantially over the past 2 decades. Treatment decisions have become more complex over time, and there is variable adoption of new agents in clinical practice. Survival trends have improved with novel therapies; however, these trends are not equitably distributed across patient populations. Although randomized clinical trials have guide treatment strategies, their exclusion of older, medically complex, and socioeconomically disadvantaged patients limits applicability to real-world outcomes. Understanding the natural history of MM and how treatment patterns have changed over time is essential for informing optimal MM care in clinical practice. We retrospectively evaluated 20 135 patients with newly diagnosed MM from the national Veterans Affairs (VA) health system between 2000 and 2024. The VA offers a unique setting to study these patterns in the equal-access context, in which cost is less of a factor, allowing us to assess trends in treatment decisions and outcomes across diverse strata. We analyzed overall survival by treatment regimen, diagnosis era, and sociodemographic features. Lower socioeconomic status as approximated by the area deprivation index was independently associated with increased mortality despite equal health care access. Outcomes continue to improve across treatment eras, although follow-up in the most recent cohort is limited and long-term survival remains incompletely characterized. These findings underscore the need for implementing strategies to address the structural and social barriers to optimal MM care.

Indexed as

Multiple MyelomaAgedAged, 80 and overFemaleHumansMaleMiddle AgedRetrospective StudiesTreatment OutcomeUnited States

Identifiers

PMID42480210
PMCPMC13594729

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.