Evidence map›Paper›PMID 37162533›Full record

ArticleCancer chemotherapy and pharmacology2023

Advanced statistics identification of participant and treatment predictors associated with severe adverse effects induced by fluoropyrimidine-based chemotherapy.

Samantha K Korver, Joanne M Bowen, Rachel J Gibson, Imogen A Ball, Kate R Secombe, Taylor J Wain, Richard M Logan, Jonathan Tuke, Kelly R Mead, Alison M Richards and 3 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer chemotherapy and pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
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 at 3 institutions in 1 country.

Samantha K KorverDiscipline of Pharmacology, School of Biomedicine, The University of Adelaide, L2 Helen Mayo South, Adelaide, SA, 5000, Australia.
Joanne M BowenDiscipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia.
Rachel J GibsonSchool of Allied Health Science and Practice, The University of Adelaide, Adelaide, Australia.
Imogen A BallDiscipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia.
Kate R SecombeDiscipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia.
Taylor J WainDiscipline of Pharmacology, School of Biomedicine, The University of Adelaide, L2 Helen Mayo South, Adelaide, SA, 5000, Australia.
Richard M LoganAdelaide Dental School, The University of Adelaide, Adelaide, Australia.
Jonathan TukeSchool of Mathematical Sciences, The University of Adelaide, Adelaide, Australia.
Kelly R MeadFlinders Medical Centre, Bedford Park, Australia.
Alison M RichardsFlinders Medical Centre, Bedford Park, Australia.
Christos S KarapetisFlinders Medical Centre, Bedford Park, Australia.
Dorothy M KeefeDiscipline of Medicine, The University of Adelaide, Adelaide, Australia.
Janet K CollerDiscipline of Pharmacology, School of Biomedicine, The University of Adelaide, L2 Helen Mayo South, Adelaide, SA, 5000, Australia. janet.coller@adelaide.edu.au.ORCID http://orcid.org/0000-0002-8273-5048
The University of Adelaide · AUFlinders Medical Centre · AUFlinders University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAdverse effects following fluoropyrimidine-based chemotherapy regimens are common. However, there are no current accepted diagnostic markers for prediction prior to treatment, and the underlying mechanisms remain unclear. This study aimed to determine genetic and non-genetic predictors of adverse effects.

methodsGenomic DNA was analyzed for 25 single nucleotide polymorphisms (SNPs). Demographics, comorbidities, cancer and fluoropyrimidine-based chemotherapy regimen types, and adverse effect data were obtained from clinical records for 155 Australian White participants. Associations were determined by bivariate analysis, logistic regression modeling and Bayesian network analysis.

resultsTwelve different adverse effects were observed in the participants, the most common severe adverse effect was diarrhea (12.9%). Bivariate analysis revealed associations between all adverse effects except neutropenia, between genetic and non-genetic predictors, and between 8 genetic and 12 non-genetic predictors with more than 1 adverse effect. Logistic regression modeling of adverse effects revealed a greater/sole role for six genetic predictors in overall gastrointestinal toxicity, nausea and/or vomiting, constipation, and neutropenia, and for nine non-genetic predictors in diarrhea, mucositis, neuropathy, generalized pain, hand-foot syndrome, skin toxicity, cardiotoxicity and fatigue. The Bayesian network analysis revealed less directly associated predictors (one genetic and six non-genetic) with adverse effects and confirmed associations between six adverse effects, eight genetic predictors and nine non-genetic predictors.

conclusionThis study is the first to link both genetic and non-genetic predictors with adverse effects following fluoropyrimidine-based chemotherapy. Collectively, we report a wealth of information that warrants further investigation to elucidate the clinical significance, especially associations with genetic predictors and adverse effects.

Indexed as

Drug-Related Side Effects and Adverse ReactionsNeutropeniaAntimetabolitesAntineoplastic Combined Chemotherapy ProtocolsAustraliaBayes TheoremDiarrheaFluorouracilHumansAntimetabolitesFluorouracilAdverse effectsBayesian network analysisFluoropyrimidine-based chemotherapyLogistic modelingRisk

Identifiers

PMID37162533
PMCPMC10191967
OpenAlexW4376121152

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.