Evidence map›Paper›PMID 42781377›Full record

ArticleHemaSphere2026

Dynamic risk stratification in smoldering multiple myeloma: Integrating evolving biomarkers with the 2/20/20 Model.

Theresia Akhlaghi, David Nemirovsky, Kylee H Maclachlan, Ross S Firestone, Neha Korde, Sham Mailankody, Alexander M Lesokhin, Hani Hassoun, Dhwani Patel, Urvi A Shah and 10 more

Abstract read
In one paragraph

Article 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

20 authors.

Theresia AkhlaghiMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.ORCID https://orcid.org/0000-0002-8826-4646
David NemirovskyDepartment of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York New York USA.
Kylee H MaclachlanMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.ORCID https://orcid.org/0000-0001-7873-4854
Ross S FirestoneMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Neha KordeMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Sham MailankodyMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Alexander M LesokhinMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Hani HassounMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Dhwani PatelMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Urvi A ShahMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Carlyn R TanMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Heather J LandauAdult Bone Marrow Transplant Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Gunjan L ShahAdult Bone Marrow Transplant Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Michael ScordoAdult Bone Marrow Transplant Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Anish K SimhalDepartment of Medical Physics Memorial Sloan Kettering Cancer Center New York New York USA.
Ola LandgrenMyeloma Service, Sylvester Comprehensive Cancer Center University of Miami Miami Florida USA.
Sergio A GiraltAdult Bone Marrow Transplant Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Saad Z UsmaniMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.
Andriy DerkachDepartment of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York New York USA.
Malin HultcrantzMyeloma Service, Department of Medicine Memorial Sloan Kettering Cancer Center New York New York USA.ORCID https://orcid.org/0000-0002-9045-6495

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Smoldering multiple myeloma (SMM) is a heterogeneous precursor with variable risk of progression to multiple myeloma (MM). Current risk models rely on baseline features, limiting predictive accuracy. We aimed to define evolving risk factors and integrate them with the 2/20/20 model to improve risk stratification. We analyzed 323 SMM patients diagnosed per IMWG 2014 criteria at Memorial Sloan Kettering Cancer Center (2002-2019). Serial M-protein and free light chain-ratio (FLCr) measurements were assessed during the first year following diagnosis. Using a multivariable Cox proportional hazards model adjusted for baseline 2/20/20 risk, age, and sex, we defined optimal cut-offs for evolving M-protein (eMP) as an increase of ≥0.4 g/dL and evolving FLCr (eFLCr) as an increase of ≥40% within the first year. Both eMP and eFLCr were independently associated with progression to MM (hazard ratio [HR] 2.8, 95% confidence interval [CI] 1.5-5.5; and HR 2.9, 95% CI 1.8-4.8). Median time to progression was 18 months for eMP and 41 months for eFLCr, compared to 130 versus 201 months without eMP and eFLCr, respectively. Integrating evolving biomarkers into the 2/20/20 model improved performance (c-index 0.79 vs. 0.70). Patients with both high baseline risk and evolving markers had 2- and 5-year progression rates of 41% and 83%, respectively, while low-risk patients without evolving disease exhibited a stable course resembling monoclonal gammopathy of undetermined significance (MGUS) with a 5-year progression rate of 8%. These findings support incorporating dynamic biomarkers into existing models to improve risk stratification and inform clinical decision-making in SMM.

Identifiers

PMID42781377
PMCPMC13598806

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.