Evidence mapPaperPMID 39811556Full record

ArticleERJ open research2025

Cost-effectiveness of follow-up algorithms for chronic thromboembolic pulmonary hypertension in pulmonary embolism survivors.

Dieuwke Luijten, Wilbert B van den Hout, Gudula J A M Boon, Stefano Barco, Harm Jan Bogaard, Marion Delcroix, Karl-Friedrich Kreitner, Matthias Held, Menno V Huisman, Luis Jara-Palomares and 11 more

Abstract read
In one paragraph

Article in ERJ open research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

21 authors.

Dieuwke LuijtenDepartment of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0003-4776-0587
Wilbert B van den HoutDepartment of Biomedical Data Science - Medical Decision Making, Leiden University Medical Center, Leiden, The Netherlands.
Gudula J A M BoonDepartment of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands.
Stefano BarcoCenter for Thrombosis and Hemostasis, University Medical Centre of the Johannes Gutenberg University, Mainz, Germany.ORCID https://orcid.org/0000-0002-2618-347X
Harm Jan BogaardDepartment of Pulmonary Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
Marion DelcroixClinical Dept of Respiratory Diseases, University Hospitals of Leuven and Laboratory of Respiratory Diseases and Thoracic Surgery (BREATHE), Dept of Chronic Diseases and Metabolism (CHROMETA), KU Leuven - University of Leuven, Leuven, Belgium.ORCID https://orcid.org/0000-0001-8394-9809
Karl-Friedrich KreitnerDepartment of Radiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.
Matthias HeldMedizinische Klinik mit Schwerpunkt Pneumologie und Beatmungsmedizin, Missioklinik Klinikum Würzburg Mitte, Würzburg, Germany.
Menno V HuismanDepartment of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0003-1423-5348
Luis Jara-PalomaresRespiratory Department, Virgen del Rocío Hospital, Seville, Spain.ORCID https://orcid.org/0000-0002-4125-3376
Stavros V KonstantinidesCenter for Thrombosis and Hemostasis, University Medical Centre of the Johannes Gutenberg University, Mainz, Germany.ORCID https://orcid.org/0000-0001-6359-7279
Lucia J M KroftDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0002-4734-8616
Albert T A MairuhuDepartment of Internal Medicine, Haga Teaching Hospital, The Hague, The Netherlands.
Lilian J MeijboomDepartment of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-7528-8307
Thijs E van MensDepartment of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands.
Maarten K NinaberDepartment of Pulmonology, Leiden University Medical Center, Leiden, The Netherlands.
Esther J NossentDepartment of Pulmonary Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0003-3854-4137
Piotr PruszczykDepartment of Internal Medicine and Cardiology, Medical University of Warsaw, Warszawa, Poland.ORCID https://orcid.org/0000-0002-9768-0000
Luca ValerioCenter for Thrombosis and Hemostasis, University Medical Centre of the Johannes Gutenberg University, Mainz, Germany.ORCID https://orcid.org/0000-0003-4466-0724
Anton Vonk NoordegraafDepartment of Pulmonary Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-4057-758X
Frederikus A KlokDepartment of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, The Netherlands.ORCID https://orcid.org/0000-0001-9961-0754

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Achieving an early diagnosis of chronic thromboembolic pulmonary hypertension (CTEPH) in pulmonary embolism (PE) survivors results in better quality of life and survival. Importantly, dedicated follow-up strategies to achieve an earlier CTEPH diagnosis involve costs that were not explicitly incorporated in the models assessing their cost-effectiveness. We performed an economic evaluation of 11 distinct PE follow-up algorithms to determine which should be preferred. Materials and methods: 11 different PE follow-up algorithms and one hypothetical scenario without a dedicated CTEPH follow-up algorithm were included in a Markov model. Diagnostic accuracy of consecutive tests was estimated from patient-level data of the InShape II study (n=424). The lifelong costs per CTEPH patient were compared and related to quality-adjusted life-years (QALYs) for each scenario. Results: Compared to not performing dedicated follow-up, the integrated follow-up algorithms are associated with an estimated increase of 0.89-1.2 QALYs against an incremental cost-effectiveness ratio (ICER) of EUR 25 700-46 300 per QALY per CTEPH patient. When comparing different algorithms with each other, the maximum differences were 0.27 QALYs and EUR 27 600. The most cost-effective algorithm was the InShape IV algorithm, with an ICER of EUR 26 700 per QALY compared to the next best algorithm. Conclusion: Subjecting all PE survivors to any of the currently established dedicated follow-up algorithms to detect CTEPH is cost-effective and preferred above not performing a dedicated follow-up, evaluated against the Dutch acceptability threshold of EUR 50 000 per QALY. The model can be used to identify the locally preferred algorithm from an economical point-of-view within local logistical possibilities.

Identifiers

PMID39811556
PMCPMC11726578

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.