Evidence mapPaperPMID 41706224Full record

ReviewClinical and experimental medicine2026

An odyssey of monoclonal gammopathies: focusing on precursors and the progression from MGUS and SMM to multiple Myeloma, with a brief overview of novel therapeutic strategies.

Xin Xin, Chunhui Fan, Ran Sheng, Xiuchong Li, Xing Zhu, Yongsheng Huang, Hamideh Rahmani Seraji, Dilbar Urazbaeva, Zamira Atamuratova, Abdullaeva Dilbar Ubaydullaevna

Abstract readReview
In one paragraph

Review in Clinical and experimental medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

10 authors.

Xin XinCollege of Traditional Chinese Medicine, Changchun University of Traditional Chinese Medicine, Changchun, China.
Chunhui FanDepartment of Cardiovascular Disease, Zhenjiang Hospital of Traditional Chinese Medicine, Zhenjiang, China.
Ran ShengCollege of Traditional Chinese Medicine, Changchun University of Traditional Chinese Medicine, Changchun, China.
Xiuchong LiCollege of Traditional Chinese Medicine, Changchun University of Traditional Chinese Medicine, Changchun, China.
Xing ZhuCardiology Department, Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, China.
Yongsheng HuangCardiology Department, Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, China. paperpub198800@gmail.com.
Hamideh Rahmani SerajiDepartment of Hematology and Oncology, Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. rahmaniseraji63.hr@gmail.com.
Dilbar UrazbaevaDepartment of Psychology and Medicine, Mamun university, Khiva, Uzbekistan.ORCID http://orcid.org/0009-0008-2248-6239
Zamira AtamuratovaDepartment of Pedagogy and psychology, Urgench state university, Urgench, Uzbekistan.ORCID http://orcid.org/0009-0005-3555-4489
Abdullaeva Dilbar UbaydullaevnaDepartment of Applied Psychology, National Pedagogical University of Uzbekistan, Tashkent, Uzbekistan.ORCID http://orcid.org/0009-0007-4567-0576

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monoclonal gammopathies span a continuum from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) to overt multiple myeloma (MM). This gradual clonal evolution is driven by primary cytogenetic lesions, secondary genomic events, and epigenetic remodeling within a permissive bone-marrow microenvironment. Traditional biomarkers (serum M-protein and free-light-chain ratios) provide useful but incomplete prognostic information because they do not capture spatial heterogeneity or temporal clonal dynamics. Recent advances highlight circulating tumor cells (CTCs), minimal residual disease (MRD) assessment via next-generation flow (NGF) and sequencing (NGS), and liquid biopsy approaches as minimally invasive tools that refine risk stratification and anticipate malignant progression. Therapeutic paradigms have shifted from melphalan-based chemotherapy and autologous stem cell transplantation to triplet and quadruplet combinations incorporating immunomodulatory drugs, proteasome inhibitors, and monoclonal antibodies, while next-generation immunotherapies, BCMA-directed CAR-T cells, bispecific antibodies, and cereblon E3 ligase modulators, offer unprecedented depth of response. Yet major challenges persist, including predicting individual progression in precursor states, overcoming drug resistance and relapse, managing therapy-associated toxicities, and ensuring access to advanced therapies across heterogeneous patient populations. Integrating multi-omics profiling, artificial intelligence (AI)-based analytics, and dynamic biomarkers promises to transform the natural history of these disorders, shifting the trajectory of monoclonal gammopathies from inevitable progression toward durable remission and potential cure. This review delineates the biological continuum underpinning disease progression from MGUS and SMM to MM, and provides a concise overview of recent advances in molecular diagnostics and novel therapeutic strategies within this context.

Indexed as

Monoclonal Gammopathy of Undetermined SignificanceMultiple MyelomaParaproteinemiasSmoldering Multiple MyelomaBiomarkers, TumorDisease ProgressionHumansImmunotherapyNeoplastic Cells, CirculatingBiomarkers, TumorCirculating tumor cells (CTCs)ImmunotherapyMinimal residual disease (MRD)Monoclonal gammopathiesMonoclonal gammopathy of undetermined significance (MGUS)Multiple myeloma (MM)Smoldering multiple myeloma (SMM)

Identifiers

PMID41706224
PMCPMC12932283

What Socratic holds

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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.