Evidence map›Paper›PMID 30466416›Full record

ArticleBMC cancer2018

Prevalence of drug-drug interactions in oncology patients enrolled on National Clinical Trials Network oncology clinical trials.

Lauren A Marcath, Taylor D Coe, Emily K Hoylman, Bruce G Redman, Daniel L Hertz

Abstract read
In one paragraph

Article in BMC cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Trial
  2. Article
  3. Assessment of potential drug interactions in rheumatology: a comparative study of decision support software.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026
    Article
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  7. Review
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  9. Article
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  11. Evaluation of Clinical Pharmacy Services for Phase 1 Clinical Trials.Journal of hematology oncology pharmacy · 2022
    Article
  12. Potential Drug Interactions Between Psychotropics and Intravenous Chemotherapeutics Used by Patients With Cancer.The Journal of pharmacy technology : jPT : official publication of the Association of Pharmacy Technicians · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Article
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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

5 authors.

Lauren A MarcathDepartment of Clinical Pharmacy, University of Michigan, College of Pharmacy, Ann Arbor, MI, 48109-1065, USA.
Taylor D CoeDepartment of Clinical Pharmacy, University of Michigan, College of Pharmacy, Ann Arbor, MI, 48109-1065, USA.
Emily K HoylmanDepartment of Clinical Pharmacy, University of Michigan, College of Pharmacy, Ann Arbor, MI, 48109-1065, USA.
Bruce G RedmanDepartment of Internal Medicine - Hematology/Oncology, University of Michigan, Michigan Medicine, Ann Arbor, MI, 48109-1065, USA.
Daniel L HertzDepartment of Clinical Pharmacy, University of Michigan, College of Pharmacy, Ann Arbor, MI, 48109-1065, USA. dlhertz@umich.edu.ORCID http://orcid.org/0000-0003-0501-1035

Funding

SWOG Network Group Operations Center of the NCTNU10CA180888 · NCI · UNIVERSITY OF CALIFORNIA AT DAVIS · PI PRIMO N. LARA · 2014 to 2026
$152.1M
NCI NIH HHS U10 CA180888
6 · The paper itself

Abstract

backgroundDrug-drug interactions (DDIs) in subjects enrolling in clinical trials can impact not only safety of the patient but also study drug outcomes and data validity. This makes it critical to adequately screen and manage DDIs. The study objective was to determine the prevalence of DDIs involving study medications in subjects enrolling in National Clinical Trials Network (NCTN) clinical trials at a single institution. DDIs were evaluated based on study protocol recommendations for concomitant medication use (i.e. exclude, avoid or use caution), screening via DDI tool, and pharmacist review.

methodsSubjects enrolled in NCTN trials of commercially available agents between January 2013 and August 2017 were included if a complete medication list was available. Complete medication lists were collected from the date of enrollment or the next available date then screened utilizing protocol guidance and the DDI screening tool, Lexicomp® Drug Interactions (Wolters Kluwer, Hudson, OH). Interactions were reviewed for clinical relevance: defined as a DDI that would require a medication change to ensure study agent safety and efficacy at enrollment.

resultsOne hundred and twenty-eight subjects enrolled in 35 clinical trials were included. Protocol guidance detected 15 unique DDI pairs that should be avoided or used with caution in 10.2% (13/128) of subjects. The majority of these subjects did not have a clinically relevant DDI (69.2%, 9/13) based on pharmacist review. Lexicomp® detected moderate to major DDIs in 24.2% (31/128) of subjects, with 9.4% (12/128) having a clinically relevant DDI.

conclusionsThis study confirms a high prevalence of DDIs present in subjects enrolling in oncology clinical trials. Further efforts should be made to improve methods to detect and manage DDIs in patients enrolling on clinical trials to ensure patient safety and trial data validity.

Indexed as

Drug InteractionsClinical Trials as TopicFemaleHumansMaleMedical OncologyNeoplasmsPrevalenceOncology clinical trial drug interaction

Identifiers

PMID30466416
PMCPMC6249716

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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.