Evidence map›Paper›PMID 33866434›Full record

ReviewCurrent treatment options in oncology2021

Circulating Biomarkers for Cardiotoxicity Risk Prediction.

Fei Fei Gong, Gregory J Cascino, Gillian Murtagh, Nausheen Akhter

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current treatment options in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 14 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Fei Fei GongDivision of Cardiology, Northwestern University Feinberg School of Medicine, 676 N St Clair, Suite 600, Chicago, IL, 60611, USA.
Gregory J CascinoDivision of Cardiology, Northwestern University Feinberg School of Medicine, 676 N St Clair, Suite 600, Chicago, IL, 60611, USA.
Gillian MurtaghDiagnostics Division, Abbott Laboratories, 100 Abbott Park Road, CP1-3, Abbott Park, North Chicago, IL, 60064-6094, USA.
Nausheen AkhterDivision of Cardiology, Northwestern University Feinberg School of Medicine, 676 N St Clair, Suite 600, Chicago, IL, 60611, USA. n-akhter@northwestern.edu.ORCID 0000-0001-9423-8578
Northwestern University · USAbbott Fund · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

opinion statementImprovements in cancer survival have led to the emergence of cardiovascular disease as an important determinant of adverse outcome in survivors. Cancer therapeutics-related cardiac dysfunction is the most well-known form of cardiotoxicity. However, newer cancer therapies bring a broader range of cardiotoxicities. The optimal method to identify patients at risk of these complications is unclear, but circulating biomarkers comprise one possible approach. Troponins and natriuretic peptides have garnered the broadest evidence base for cardiotoxicity risk prediction, but other markers are being investigated. In this review, we explore evidence for circulating biomarkers in cardiotoxicity prediction associated with cancer therapies.

Indexed as

Antineoplastic AgentsBiomarkersCardiotoxicityHumansImmune Checkpoint InhibitorsImmunotherapy, AdoptiveNatriuretic Peptide, BrainPeptide FragmentsReceptors, Chimeric AntigenTroponinVascular Endothelial Growth Factor AAntineoplastic AgentsBiomarkersImmune Checkpoint InhibitorsNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)Receptors, Chimeric AntigenTroponinVascular Endothelial Growth Factor ABiomarkersCancer therapyCardiotoxicityRisk prediction

Identifiers

PMID33866434
OpenAlexW3154649629

What OpenQuestion holds

Textmetadata
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.