Evidence map›Paper›PMID 34649622›Full record

ReviewBiomarker research2021

Minimal residual disease in multiple myeloma: current status.

Hong Ding, Juan Xu, Zhimei Lin, Jingcao Huang, Fangfang Wang, Yan Yang, Yushan Cui, Hongmei Luo, Yuhan Gao, Xinyu Zhai and 3 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Biomarker research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Noncoding RNome as Enabling Biomarkers for Precision Health.International journal of molecular sciences · 2022
    Review
  11. Review
  12. 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

13 authors.

Hong DingDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Juan XuDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Zhimei LinDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Jingcao HuangDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Fangfang WangDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Yan YangDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Yushan CuiDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Hongmei LuoDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Yuhan GaoDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Xinyu ZhaiDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Weicui PangDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China.
Li ZhangDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China. zhangli@scu.edu.cn.
Yuhuan ZhengDepartment of Hematology, West China Hospital, and State Key Laboratory of Biotherapy and Cancer Center, Sichuan University, #37 GuoXue Xiang Street, Chengdu, China. zhengyuhuan@scu.edu.cn.ORCID http://orcid.org/0000-0002-5855-4343

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM) is a treatable plasma cell cancer with no cure. Clinical evidence shows that the status of minimal residual disease (MRD) after treatment is an independent prognostic factor of MM. MRD indicates the depth of post-therapeutic remission. In this review article, we outlined the major clinical trials that have determined the prognostic value of MRD in MM. We also reviewed different methods that were used for MM MRD assessment. Most important, we reviewed our current understanding of MM MRD biology. MRD studies strongly indicate that MRD is not a uniform declination of whole MM tumor population. Rather, MM MRD exhibits unique signatures of cytogenetic aberration and gene expression profiles, unlike those of MM cells before therapy. Diagnostic high-risk MM and low-risk MM exhibited a diversity of MRD features. Clonal evaluation may occur at the MRD stage in MM. The dynamics from the diagnostic MM to MRD correlate with the disease prognosis. Lastly, on the aspect of omics, we performed data-based analysis to address the biological features underlying the course of diagnostic-to-MRD MM. To summarize, the MRD stage of disease represents a critical step in MM pathogenesis and progression. Demonstration of MM MRD biology should help us to deal with the curative difficulties.

Indexed as

BiologyGene expressionMinimal residual diseaseMultiple myelomaOmics

Identifiers

PMID34649622
PMCPMC8515655

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.