Evidence map›Paper›PMID 39443518›Full record

ArticleNature communications2024

Socio-demographic and genetic risk factors for drug adherence and persistence across 5 common medication classes.

Mattia Cordioli, Andrea Corbetta, Hanna Maria Kariis, Sakari Jukarainen, Pekka Vartiainen, Tuomo Kiiskinen, Matteo Ferro, FinnGen, Estonian Biobank Research Team, Markus Perola and 5 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Personality Genomics.Annual review of psychology · 2026
    Review
  4. Time Trends of Body Mass Index and its Impact on Glycemic Control Among Finnish Patients with Type 2 Diabetes.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Article
  5. Article
  6. Article
  7. Review
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

15 authors.

Mattia Cordioli *Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-4872-0520
Andrea Corbetta *Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.ORCID 0009-0001-8006-1211
Hanna Maria Kariis *Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Sakari JukarainenInstitute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.ORCID 0000-0001-8169-8954
Pekka VartiainenInstitute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.ORCID 0000-0001-5803-9571
Tuomo KiiskinenInstitute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-6306-8227
Matteo FerroInstitute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
FinnGen
Estonian Biobank Research Team
Markus PerolaThe Finnish Institute for Health and Welfare, Helsinki, Finland.
Mikko NiemiDepartment of Clinical Pharmacology, University of Helsinki, Helsinki, Finland.ORCID 0000-0003-4550-2189
Samuli RipattiInstitute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-0504-1202
Kelli LehtoEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Lili MilaniEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Andrea GannaInstitute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland. andrea.ganna@helsinki.fi.ORCID 0000-0002-8147-240X

Funding

Academy of Finland (Suomen Akatemia) 323116EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 945733EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 101016775
6 · The paper itself

Abstract

Low drug adherence is a major obstacle to the benefits of pharmacotherapies and it is therefore important to identify factors associated with discontinuing or being poorly adherent to a prescribed treatment regimen. Using high-quality nationwide health registry data and genome-wide genotyping, we evaluate the impact of socio-demographic and genetic risk factors on adherence and persistence for 5 common medication classes that require long-term, regular therapy (N = 1,814,591 individuals from Finnish nationwide registries, 217,005 with genetic data from Finland and Estonia). Need for social assistance and immigration status show a notable negative effect on persistence and adherence across the examined medications (odd ratios between 0.48 and 0.82 for persistence and between 1.1% to 4.3% decrease in adherence) while demographic and health factors show comparably modest or inconsistent effects. A genome-wide scan does not identify genetic variants associated with the two phenotypes, while some pharmacogenes (i.e. CYP2C9 and SLCO1B1) are modestly associated with persistence, but not with adherence. We observe significant genetic correlations between medication adherence and participation in research studies. Overall, our findings suggest that socio-economically disadvantaged groups would benefit from targeted interventions to improve the dispensing and uptake of pharmacological treatments.

Indexed as

Drug MonitoringAdultAgedCytochrome P-450 CYP2C9EstoniaFemaleFinlandGenome-Wide Association StudyGenotypeHumansLiver-Specific Organic Anion Transporter 1MaleMiddle AgedRegistriesRisk FactorsSocioeconomic FactorsCYP2C9 protein, humanCytochrome P-450 CYP2C9Liver-Specific Organic Anion Transporter 1SLCO1B1 protein, human

Identifiers

PMID39443518
PMCPMC11500092

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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.