Evidence map›Paper›PMID 34556161›Full record

ReviewJournal of hematology & oncology2021

Prognostic and predictive biomarker developments in multiple myeloma.

Craig T Wallington-Beddoe, Rachel L Mynott

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of hematology & oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 2 pooled it
–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

81 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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21 more citing papers are in PubMed but not listed here.

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.

Craig T Wallington-BeddoeCollege of Medicine and Public Health, Level 4, Flinders Centre for Innovation in Cancer, Flinders University, Bedford Park, SA, 5042, Australia. craig.wallingtonbeddoe@flinders.edu.au.ORCID 0000-0002-7457-5937
Rachel L MynottCollege of Medicine and Public Health, Level 4, Flinders Centre for Innovation in Cancer, Flinders University, Bedford Park, SA, 5042, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New approaches to stratify multiple myeloma patients based on prognosis and therapeutic decision-making, or prediction, are needed since patients are currently managed in a similar manner regardless of individual risk factors or disease characteristics. However, despite new and improved biomarkers for determining the prognosis of patients, there is currently insufficient information to utilise biomarkers to intensify, reduce or altogether change treatment, nor to target patient-specific biology in a so-called predictive manner. The ever-increasing number and complexity of drug classes to treat multiple myeloma have improved response rates and so clinically useful biomarkers will need to be relevant in the era of such novel therapies. Therefore, the field of multiple myeloma biomarker development is rapidly progressing, spurred on by new technologies and therapeutic approaches, and underpinned by a deeper understanding of tumour biology with individualised patient management the goal. In this review, we describe the main biomarker categories in multiple myeloma and relate these to diagnostic, prognostic and predictive applications.

Indexed as

AnimalsBiomarkers, TumorBone and BonesCytogenetic AnalysisHumansLiquid BiopsyMultiple MyelomaNeoplasm StagingNeoplastic Cells, CirculatingPrognosisTranscriptomeBiomarkers, TumorBiomarkerDiagnosisMultiple myelomaPrognosisTherapy

Identifiers

PMID34556161
PMCPMC8461914

What OpenQuestion holds

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LicenceCC BY
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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.