Evidence map›Paper›PMID 39544252›Full record

ArticleRisk management and healthcare policy2024

Regulated Pricing Decisions and Diagnostic Test Choices in Personalized Medicine: Navigating the Implications Within Legal Frameworks.

Zibin Cui, Xiangdong Liu, Zehua Feng, Zhengzong Huang

Abstract read
In one paragraph

Article in Risk management and healthcare policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Zibin Cui *School of Management, Guangdong University of Technology, Guangzhou, People's Republic of China.
Xiangdong Liu *Faculty of Humanities and Social Sciences, Macao Polytechnic University, Macao, People's Republic of China.
Zehua FengSchool of Law, Guangdong University of Technology, Guangzhou, People's Republic of China.ORCID 0000-0002-6838-0893
Zhengzong HuangCollege of Humanities and Social Science, Shenzhen Technology University, Shenzhen, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The emerging risk of personalized medicine is driving drug manufacturers to seek collaborations with advanced diagnostic firms, aiming to improve detection and treatment outcomes. However, the government's regulated pricing in personalized medicine affects manufacturers' strategic decisions, particularly regarding the selection of diagnostic partners. In this context, this study investigates whether the government should regulate the price of personalized medicine and how the government's regulated pricing decisions affect drug manufacturers' diagnostic test choices. Methods: A stylized analytical model was developed, employing game-theoretic analysis. Numerical studies are also conducted to validate our results. Results: The study reveals that in the absence of the government's regulated pricing, drug manufacturers benefit from partnering with high-level diagnostic firms, enhancing consumer surplus and social welfare. However, when the government regulates pricing, the choice of partnering with a high-level diagnostic firm depends on specific conditions, such as low patient sensitivity to treatment failure and a low unit cost coefficient of diagnostic effort. The government's decision to regulate prices is influenced by three key parameters: patients' sensitivity to treatment failure, the unit cost coefficient of the diagnostic test effort, and the proportion of the price of specialized drugs in the regulated pricing. Conclusions: The findings underscore the importance of legal frameworks in the personalized medicine industry. The absence of the government's regulated pricing incentivizes collaborations with high-level diagnostic firms, enhancing consumer surplus and social welfare. However, government intervention in pricing makes such decisions contingent on specific conditions, requiring nuanced regulatory policies that balance the interests of patients, manufacturers, and diagnostic firms.

Indexed as

game theorygovernmentpartnershippersonalized medicineregulated pricing

Identifiers

PMID39544252
PMCPMC11561735

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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.