Evidence map›Paper›PMID 39368017›Full record

ArticlePharmacoEconomics2025

Managed Entry Agreements for High-Cost, One-Off Potentially Curative Therapies: A Framework and Calculation Tool to Determine Their Suitability.

Marcelien H E Callenbach, Rick A Vreman, Christine Leopold, Aukje K Mantel-Teeuwisse, Wim G Goettsch

Abstract read
In one paragraph

Article in PharmacoEconomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Marcelien H E CallenbachDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0003-2293-0746
Rick A VremanDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands.
Christine LeopoldDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands.
Aukje K Mantel-TeeuwisseDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands.
Wim G GoettschDivision of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Universiteitsweg 99, 3584 CG, Utrecht, The Netherlands. w.g.goettsch@uu.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo construct a framework and calculation tool to compare the consequences of implementing different payment models for high-cost, one-off potentially curative therapies and enable decision making to ultimately enhance timely patient access to innovative health interventions.

methodsA framework outlining steps to determine potentially suitable payment models was developed. Based on the framework, a supporting calculation tool operationalised as an Excel-based model was constructed to quantify the associated costs for an average patient during the timeframe of the intended payment agreement, the total budget impact and associated benefits expressed in quality-adjusted life-years for the total expected lifetime of the patient population. To demonstrate the potential of the framework, three case studies were used: onasemnogene abeparvovec (Zolgensma

resultsPart 1 of the framework presents steps for matching a suitable reimbursement and payment model with the disease and treatment characteristics. The reimbursement and payment models are further specified in Part 2. Part 3 guides end users through the setup of a calculation tool with which the financial impact can be calculated of two payment models: a price discount model and an outcome-based spread payment model with a discount. Part 4 concerns the output of the calculation tool, showing how different payment models lead to different financial consequences under three assumptions of longer term effectiveness.

conclusionsThe presented framework provides decision makers with insight into the financial consequences of their chosen payment model under different assumptions. This can aid reimbursement negotiations by clarifying the optimal choice given a therapy's characteristics.

Indexed as

Models, EconomicReimbursement MechanismsCost-Benefit AnalysisDecision MakingHumansQuality-Adjusted Life Years

Identifiers

PMID39368017
PMCPMC11724790

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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.