Evidence map›Paper›PMID 28289895›Full record

ArticleJournal of cancer research and clinical oncology2017

Factors influencing adherence in CML and ways to improvement: Results of a patient-driven survey of 2546 patients in 63 countries.

Jan Geissler, Giora Sharf, Felice Bombaci, Mina Daban, Jan De Jong, Tony Gavin, Jana Pelouchova, Euzebiusz Dziwinski, Joerg Hasford, Verena Sophia Hoffmann

Open access · greenAbstract readMulticenter Study
In one paragraph

Article in Journal of cancer research and clinical oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
6.2field-weighted citation impact, top 3% 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

47 citing papers in PubMed, 90 citations in OpenAlex.

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  12. A smart pill bottle and text messaging intervention for promoting medication adherence in patients with chronic myeloid leukemia: a pilot study of txt4 TKI.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
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  18. An investigation of the use of app technology to support clinical management of patients with chronic myeloid leukaemia (CML).Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners · 2023
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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

10 authors at 5 institutions in 5 countries.

Jan GeisslerLeukemia Patient Advocates Foundation, Bern, Switzerland. jan@cmladvocates.net.
Giora SharfLeukemia Patient Advocates Foundation, Bern, Switzerland.
Felice BombaciGruppo AIL Pazienti Leucemia Mieloide Cronica, Rome, Italy.
Mina DabanLMC France, Marseille, France.
Jan De JongStichting Hematon, Utrecht, The Netherlands.
Tony GavinLeukaemia CARE, Worcester, UK.
Jana PelouchovaDiagnoza CML, Prague, Czech Republic.
Euzebiusz DziwinskiPolish Nationwide Association for CML Patients Aid, Warsaw, Poland.
Joerg HasfordInstitute for Medical Information Sciences, Biometry, and Epidemiology, Ludwig-Maximilians-Universitaet, Munich, Germany.
Verena Sophia HoffmannInstitute for Medical Information Sciences, Biometry, and Epidemiology, Ludwig-Maximilians-Universitaet, Munich, Germany.
Stiftung Patientensicherheit Schweiz · CHZimmer Biomet (Germany) · DEChildren's Cancer and Leukaemia Group · GBCKD Blansko Engineering (Czechia) · CZLaboratoire Mémoire et Cognition · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimal adherence to CML therapy is of key importance to maximize treatment effectiveness. Two clinical studies (ADAGIO and Hammersmith) have proven a clear correlation between adherence and achieving optimal treatment response and have revealed that non-adherence is common in CML patients (Marin et al. in J Clin Oncol 28(24):2381-2388, 2010, Noens et al. in Haematologica 99(33):437-447, 2014). The aim of this study is to assess the extent of suboptimal adherence and to investigate motivations and behavioural patterns of adherence in a worldwide patient sample. Questionnaires were provided by the CML Advocates Network and were filled in by patients online and offline. Patient characteristics, treatment and motivations were collected. Adherence was assessed by the 8-item Morisky Medication Adherence scale. Logistic regression models were fitted to investigate the influence of different factors on adherence. Overall, 2 546 questionnaires from 63 countries and 79 CML patient organisations were evaluable. 32.7% of participants were highly adherent, 46.5% were in the medium and 20.7% in the low adherence group. Factors increasing the probability of being in the high adherence group are older age, male sex, management of side effects, only one tablet per day and feeling well informed about CML by the doctor. More than 2 years since diagnosis were significantly lowering the chance as was the use of reminding tools. Living arrangements, multiple medication and personal payment obligations increased the probability to be at least in the medium adherent group. This is the most comprehensive study conducted to date to gain knowledge about factors causing non-adherence in CML. Better information on the disease, medication and management of side effects, supported by haematologists, is key to improve adherence.

Indexed as

Drug MonitoringAdolescentAdultAgedAged, 80 and overAge FactorsAntineoplastic AgentsFemaleHumansLeukemia, Myelogenous, Chronic, BCR-ABL PositiveMaleMiddle AgedSex FactorsSurveys and QuestionnairesYoung AdultAntineoplastic AgentsAdherence patient motivationsBehavioural patterns of adherenceChronic myeloid leukaemiaCML treatment adherenceDriving factors of nonadherenceFactors causing nonadherenceHaematologyMolecular responseMorisky Medication Adherence scaleOptimal adherencePatient advocacyPatient-driven surveyTyrosine kinase inhibitors

Identifiers

PMID28289895
PMCPMC11819081
OpenAlexW2597213291

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.