Evidence map›Paper›PMID 41523082›Full record

ReviewHemaSphere2026

Navigating the evolving management of smoldering multiple myeloma.

M Bakri Hammami, Rafael R Canevarolo, Ariosto S Silva, Melissa Alsina, Nagi Kumar, Rachid Baz, Kenneth H Shain

Abstract readReview
In one paragraph

Review in HemaSphere, 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

7 authors.

M Bakri HammamiDepartment of Hematology and Oncology Moffitt Cancer Center and Research Institute Tampa Florida USA.ORCID https://orcid.org/0000-0003-3422-5163
Rafael R CanevaroloDepartment of Metabolism and Physiology Moffitt Cancer Center and Research Institute Tampa Florida USA.
Ariosto S SilvaDepartment of Metabolism and Physiology Moffitt Cancer Center and Research Institute Tampa Florida USA.
Melissa AlsinaDepartment of Blood and Marrow Transplant and Cellular Therapies Moffitt Cancer Center and Research Institute Tampa Florida USA.
Nagi KumarDepartment of Cancer Epidemiology Moffitt Cancer Center and Research Institute Tampa Florida USA.
Rachid BazDepartment of Malignant Hematology Moffitt Cancer Center and Research Institute Tampa Florida USA.
Kenneth H ShainDepartment of Malignant Hematology Moffitt Cancer Center and Research Institute Tampa Florida USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smoldering multiple myeloma (SMM) represents an intermediate clinical stage between monoclonal gammopathy of undetermined significance (MGUS) and symptomatic multiple myeloma (MM). SMM carries a highly variable risk of progression to MM, requiring individualized risk stratification to guide management. Historically, risk models relied on static clinical markers reflective of tumor burden to predict progression. While useful, these models failed to capture the underlying biological heterogeneity of the disease. Recent advances have incorporated dynamic biomarkers, cytogenetics, and genomic profiling, providing a more nuanced understanding of disease trajectory. Immune dysregulation and subclonal evolution are now recognized as key drivers of progression, enabling the development of biologically informed risk models. Clinical trials have begun to challenge the traditional watch-and-wait approach by exploring early therapeutic interventions for high-risk SMM patients. However, uncertainty persists as clinicians balance the risks of overtreatment against therapeutic delay in the absence of clearly defined high-risk criteria. This review charts the evolution of SMM from a clinically defined entity to a biologically characterized precursor state, highlighting emerging tools and strategies aimed at improving risk prediction and patient outcomes. As personalized medicine continues to advance, integrating evolving molecular, immunologic, and clinical data will be pivotal in refining the management of SMM.

Identifiers

PMID41523082
PMCPMC12784114

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.