Evidence map›Paper›PMID 37989969›Full record

ArticlePharmacoEconomics2024

Using Real-World Data to Inform Value-Based Contracts for Cell and Gene Therapies in Medicaid.

Antal Zemplenyi, Jim Leonard, Michael J DiStefano, Kelly E Anderson, Garth C Wright, Nicholas D Mendola, Kavita Nair, R Brett McQueen

Open access · hybridAbstract read
In one paragraph

Article in PharmacoEconomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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  5. 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

8 authors at 2 institutions in 2 countries.

Antal ZemplenyiSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. antal.zemplenyi@cuanschutz.edu.
Jim LeonardColorado Department of Health Care Policy and Finance, Denver, CO, USA.
Michael J DiStefanoSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Kelly E AndersonSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Garth C WrightSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Nicholas D MendolaSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Kavita NairSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
R Brett McQueenSkaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
University of Colorado Anschutz Medical Campus · USUniversity of Pecs · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveHigh upfront costs and long-term benefit uncertainties of gene therapies challenge Medicaid budgets, making value-based contracts a potential solution. However, value-based contract design is hindered by cost-offset uncertainty. The aim of this study is to determine actual cost-offsets for valoctocogene roxaparvovec (hemophilia A) and etranacogene dezaparvovec (hemophilia B) from Colorado Medicaid's perspective, defining payback periods and its uncertainty from the perspective of Colorado Medicaid.

methodsThis cost analysis used 2018-2022 data from the Colorado Department of Health Care Policy & Financing to determine standard-of-care costs and employed cost simulation models to estimate the cost of Medicaid if patients switched to gene therapy versus if they did not. Data encompassed medical and pharmacy expenses of Colorado Medicaid enrollees. Identified cohorts were patients aged 18+ with ICD-10-CM codes D66 (hemophilia A) and D67 (hemophilia B). Severe hemophilia A required ≥ 6 claims per year for factor therapies or emicizumab, while moderate/severe hemophilia B necessitated ≥ 4 claims per year for factor therapies. Patients were included in the cohort in the year they first met the criteria and were subsequently retained in the cohort for the duration of the observation period. Standard-of-care included factor VIII replacement therapy/emicizumab for hemophilia A and factor IX replacement therapies for hemophilia B. Simulated patients received valoctocogene roxaparvovec or etranacogene dezaparvovec. Main measures were annual standard-of-care costs, cost offset, and breakeven time when using gene therapies.

resultsColorado Medicaid's standard-of-care costs for hemophilia A and B were $426,000 [standard deviation (SD) $353,000] and $546,000 (SD $542,000) annually, respectively. Substituting standard-of-care with gene therapy for eligible patients yielded 8-year and 6-year average breakeven times, using real-world costs, compared with 5 years with published economic evaluation costs. Substantial variability in real-world standard-of-care costs resulted in a 48% and 59% probability of breakeven within 10 years for hemophilia A and B, respectively. Altering eligibility criteria significantly influenced breakeven time.

conclusionsReal-world data indicates substantial uncertainty and extended payback periods for gene therapy costs. Utilizing real-world data, Medicaid can negotiate value-based contracts to manage budget fluctuations, share risk with manufacturers, and enhance patient access to innovative treatments.

Indexed as

Hemophilia AHemophilia BCost-Benefit AnalysisGenetic TherapyHumansMedicaidUnited States

Identifiers

PMID37989969
PMCPMC10861602
OpenAlexW4388856565

What OpenQuestion holds

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LicenceCC BY-NC
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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.