Evidence map›Paper›PMID 29121889›Full record

ArticleBMC cancer2017

Prevalence and associated factors of medication non-adherence in hematological-oncological patients in their home situation.

Linda Bouwman, Corien M Eeltink, Otto Visser, Jeroen J W M Janssen, Jolanda M Maaskant

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
3.9field-weighted citation impact, top 7% 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

43 citing papers in PubMed, 72 citations in OpenAlex.

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  8. Comprehensive assessment of pain characteristics, quality of life, and pain management in cancer patients: a multi-center cross-sectional study.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
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  13. Immunomodulator adherence in multiple myeloma patients with lower socioeconomic status: a retrospective study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
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  16. Can Technology Solve the Problem of Medication Nonadherence?Mayo Clinic proceedings. Digital health · 2024
    Review
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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 at 2 institutions in 1 country.

Linda BouwmanDepartment of Hematology, VU University Medical Center, Amsterdam, the Netherlands.
Corien M EeltinkDepartment of Hematology, VU University Medical Center, Amsterdam, the Netherlands. c.eeltink@vumc.nl.
Otto VisserDepartment of Hematology, VU University Medical Center, Amsterdam, the Netherlands.
Jeroen J W M JanssenDepartment of Hematology, VU University Medical Center, Amsterdam, the Netherlands.
Jolanda M MaaskantEmma Children's Hospital, Academic Medical Center, Amsterdam, the Netherlands.
Amsterdam UMC Location VUmc · NLAcademic Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMedication non-adherence is associated with poor health outcomes and increased health care costs. Depending on definitions, reported non-adherence rates in cancer patients ranges between 16 and 100%, which illustrates a serious problem. In malignancy, non-adherence reduces chances of achievement of treatment response and may thereby lead to progression or even relapse. Except for Chronic Myeloid Leukemia (CML), the extent of non-adherence has not been investigated in hematological-oncological patients in an outpatient setting. In order to explore ways to optimize cancer treatment results, this study aimed to assess the prevalence of self-administered medication non-adherence and to identify potential associated factors in hematological-oncological patients in their home situation.

methodsThis is an exploratory cross-sectional study, carried out at the outpatient clinic of the Department of Hematology at the VU University medical center, Amsterdam, the Netherlands between February and April 2014. Hematological-oncological outpatients were sent questionnaires retrieving information on patient characteristics, medication adherence, beliefs about medication, anxiety, depression, coping, and quality of life. We performed uni- and multivariable analysis to identify predictors for medication non-adherence.

resultsIn total, 472 participants were approached of which 259 (55%) completed the questionnaire and met eligibility criteria. Prevalence of adherence in this group (140 male; 54,1%; median age 60 (18-91)) was 50%. In univariate analysis, (lower) age, (higher) education level, living alone, working, perception of receiving insufficient social support, use of bisphosphonates, depression, helplessness (ICQ), global health, role function, emotional function, cognitive function, social functioning, fatigue, dyspnea, diarrhea were found to be significantly related (p = <0.20) to medication non-adherence. In multivariable analysis, younger age, (higher) education level and fatigue remained significantly related (p = <0.10) to medication non-adherence.

conclusionsThis cross-sectional study shows that 50% of the participants were non-adherent. Lower age, living alone and perception of insufficient social support were associated factors of non-adherence in hematological-oncological adult patients in their home-situation.

Indexed as

Medication AdherenceSelf CareAdolescentAdultAgedAged, 80 and overAntineoplastic AgentsCross-Sectional StudiesFemaleHematologic NeoplasmsHumansMaleMiddle AgedNetherlandsPrevalenceRetrospective StudiesAntineoplastic AgentsAssociated factorsHematological-oncological patientsNon-adherence

Identifiers

PMID29121889
PMCPMC5679497
OpenAlexW2767252525

What OpenQuestion holds

Textmetadata
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.