Evidence map›Paper›PMID 34290698›Full record

ReviewFrontiers in immunology2021

Predictive Role of Immune Profiling for Survival of Multiple Myeloma Patients.

Liu Zhaoyun, Fu Rong

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.1field-weighted citation impact, top 10% of its field
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

18 citing papers in PubMed, 35 citations in OpenAlex.

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  15. [Clinical significance and pathogenesis analysis of Moesin in multiple myeloma].Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi · 2023
    Article
  16. Article
  17. Article
  18. Advances in the application of Raman spectroscopy in haematological tumours.Frontiers in bioengineering and biotechnology · 2022
    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

2 authors at 1 institution in 1 country.

Liu ZhaoyunDepartment of Hematology, Tianjin Medical University General Hospital, Tianjin, China.
Fu RongDepartment of Hematology, Tianjin Medical University General Hospital, Tianjin, China.
Tianjin Medical University General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite new efficacy drugs and cell therapy have been used for multiple myeloma (MM) patients, some patients will relapse over time. We wonder the immune system play a vital role as well as MM cell during the development of disease. It is clear that the characteristic of myeloma cell is associated with the survival of MM patients. However, the link between the immune profiling and the prognosis of the disease is still not entirely clear. As more study focus on the role of immunity on multiple myeloma pathogenesis. There are plenty of study about the predictive role of immunity on the survival of multiple myeloma patients. Up to mow, the majority reviews published have focused on the immunotherapy and immune pathogenesis. It is indispensable to overlook the predictive role of immunity on multiple myeloma patients. Here, we give a review of vital previous works and recent progress related to the predictive role of immune profiling on multiple myeloma, such as absolute lymphocyte count, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocytes and cytokines.

Indexed as

BiomarkersCytokinesDisease ManagementDisease SusceptibilityHumansLeukocyte CountLymphocyte CountLymphocytesMultiple MyelomaMyeloid-Derived Suppressor CellsNeutrophilsPrognosisBiomarkersCytokinesimmune profilingimmunologymultiple myelomaprognosissurvival predication

Identifiers

PMID34290698
PMCPMC8287504
OpenAlexW3179554506

What OpenQuestion holds

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LicenceCC BY
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.