Evidence map›Paper›PMID 41502919›Full record

ArticleEClinicalMedicine2026

Multinational cost-utility analysis of panel-based pharmacogenetics-guided treatment of patients enrolled in the U-PGx PREPARE study.

Vasileios Fragoulakis, Jesse J Swen, Margarita-Ioanna Koufaki, Kathrin Blagec, Tanja Blagus, Stefan Böhringer, Anne Cambon-Thomsen, Erika Cecchin, Ka-Chun Cheung, Vera H M Deneer and 31 more

Abstract read
In one paragraph

Article in EClinicalMedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

41 authors.

Vasileios FragoulakisThe Golden Helix Foundation, London, UK.
Jesse J SwenDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands.
Margarita-Ioanna KoufakiThe Golden Helix Foundation, London, UK.
Kathrin BlagecCentre for Medical Statistics, Informatics and Intelligent Systems, Institute of Artificial Intelligence, Medical University of Vienna, Vienna, Austria.
Tanja BlagusPharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Stefan BöhringerThe Golden Helix Foundation, London, UK.
Anne Cambon-ThomsenCNRS, Centre for Epidemiology and Research in Population Health (CERPOP), Université de Toulouse, INSERM, Toulouse, France.
Erika CecchinExperimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy.
Ka-Chun CheungMedicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, Netherlands.
Vera H M DeneerDivision Laboratories, Pharmacy and Biomedical Genetics, Hospital Pharmacy, University Medical Centre Utrecht, Utrecht, Netherlands.
Mathilde DupuiService de Pharmacologie Médicale et Clinique, CEIP-addictovigilance de Toulouse, Faculté de Médecine, CHU, Toulouse, France.
Siv JonssonDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Candace Joefield-RokaDepartment of Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, Vienna, Austria.
Katja S JustInstitute of Clinical Pharmacology, University Hospital RWTH Aachen, Aachen, Germany.
Mats O KarlssonDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Lidija KontaBio.logis Digital Health, Frankfurt am Main, Germany.
Rudolf KoopmannBio.logis Digital Health, Frankfurt am Main, Germany.
Marjolein KriekDepartment of Clinical Genetics, Leiden University Medical Centre, Leiden, Netherlands.
Thorsten LehrClinical Pharmacy, Saarland University, Saarbrücken, Germany.
Lisanne E N MansonDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands.
Emmanuelle Rial-SebbagUniversite de Toulouse III Paul Sabatier, Toulouse, France.
Victoria RollinsonDepartment of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK.
Rossana RoncatoExperimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy.
Matthias SamwaldCentre for Medical Statistics, Informatics and Intelligent Systems, Institute of Artificial Intelligence, Medical University of Vienna, Vienna, Austria.
Elke SchaeffelerDr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
Maria SkokouUniversity of Patras, School of Health Sciences, Department of Pharmacy, Division of Pharmacology and Biosciences, Laboratory of Pharmacogenomics and Individualised Therapy, Patras, Greece.
Matthias SchwabDr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
Daniela SteinbergerBio.logis Digital Health, Frankfurt am Main, Germany.
Julia C StinglDepartment of Clinical Pharmacology and Pharmacoepidemiology, University Hospital Heidelberg, Germany.
Roman TremmelDr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany.
Richard M TurnerDepartment of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK.
Mandy H van RhenenMedicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, Netherlands.
Cathelijne H van der WoudenDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands.
Cristina Lucía Dávila-FajardoClinical Pharmacy Department, Hospital Universitario Virgen de las Nieves, Instituto de Investigación Biosanitaria Granada, Granada, Spain.
Vita DolžanPharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
Munir PirmohamedDepartment of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, The University of Liverpool, Liverpool, UK.
Gere Sunder-PlassmannDepartment of Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, Vienna, Austria.
Giuseppe ToffoliExperimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy.
Henk-Jan GuchelaarDepartment of Clinical Pharmacy and Toxicology, Leiden University Medical Centre, Leiden, Netherlands.
George P PatrinosUniversity of Patras, School of Health Sciences, Department of Pharmacy, Division of Pharmacology and Biosciences, Laboratory of Pharmacogenomics and Individualised Therapy, Patras, Greece.
Christina MitropoulouThe Golden Helix Foundation, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pharmacogenetics (PGx) aims to revolutionize healthcare by individualizing drug doses and medication choices. However, clinical uptake will require positive evaluation evidence of both clinical utility and cost-effectiveness. We have recently demonstrated the clinical utility of this approach, using a panel-based PGx-guided treatment of patients from various indications recruited in seven countries (PREPARE study). Methods: Here, we provide economic evidence from a multinational cost-utility analysis of PGx-guided treatment in 6930 patients participating in the PREPARE study. The study was conducted from March 2017 to June 2020. We used the national healthcare system's perspective in each participating country, including only direct medical costs that budget holders cover. A Visual Analog Scale was used to measure utility and the quality of life was estimated by averaging the Visual Analog Scale scores of participants over four specific time points in the study, namely baseline visit (day 1), week 4, week 12, and 18 months from the baseline visit. Findings: Our analysis showed that the PGx-guided treatment is marginally cost-effective at the threshold of €11,000 QALYs. Cost drivers were hospitalization and ADRs costs, accounting for most of the resources used in both groups (46% and 37.5% in the PGx-guided group versus 49% and 48% in the control group, respectively), as a result of the average duration of hospitalization [1.51 days (95% CI: 1.23-1.82) for the PGx-guided group and 2.37 days (95% CI: 1.95-2.89) for the control group, resulting in a mean difference of 0.86 days (95% CI: 0.37-1.44). The difference in QALYs gained was 0.00178 (95% CI: 0.00176-0.00180). The ICER was €12,020 (95% CI: €10,957-€13,356) per QALY on average (SD: €116). When comparing cost and effectiveness of actionable PGx-guided versus actionable control patients, the total cost for the PGx-guided group was €491 (95% CI: €384-€613), versus €767 (95% CI: €583-€982) in the control group, with an incremental cost difference of €276 (95% CI: €62-€511), favoring the PGx-guided group. Also, the difference in effectiveness was 0.007 QALYs (95% CI: -0.021 to 0.033). Lastly, the difference in the mean total cost was estimated to be €21.4 (95% CI: €19.5-€23.8), while without considering the PGx test cost, indicative of a pre-emptive genetic testing approach, the PGx-guided treatment becomes a cost-saving option, with an estimated savings of approximately €103.6 (€124-€21.4) per patient. Interpretation: These data suggest that panel-based PGx testing is cost-effective, which, together with the clinically beneficial outcomes already demonstrated in the PREPARE study, provides additional evidence of the need to implement PGx into clinical practice. Funding: European Union Horizon 2020.

Indexed as

Cost-utility analysisEconomic evaluationPersonalized medicinePharmacogenetic-guided treatmentPreemptive testingQuality of life

Identifiers

PMID41502919
PMCPMC12768869

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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.