Evidence map›Paper›PMID 39428462›Full record

ArticleOrphanet journal of rare diseases2024

Establishment of a value assessment framework for orphan medicinal products in China.

Handong Chen, Yuliang Xiang, Xian Tang, Ming Hu

Abstract read
In one paragraph

Article in Orphanet journal of rare diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Handong ChenWest China School of Pharmacy, Sichuan University, 17 Renmin South Road (3rd Section), Chengdu, China.
Yuliang XiangWest China School of Pharmacy, Sichuan University, 17 Renmin South Road (3rd Section), Chengdu, China.
Xian TangWest China School of Pharmacy, Sichuan University, 17 Renmin South Road (3rd Section), Chengdu, China.
Ming HuWest China School of Pharmacy, Sichuan University, 17 Renmin South Road (3rd Section), Chengdu, China. huming@scu.edu.cn.

Funding

National Natural Science Foundation of China Project 72374151
6 · The paper itself

Abstract

backgroundThis study aimed to establish a suitable value assessment framework for orphan medicinal products in China based on the multi-criteria decision analysis (MCDA) method.

methodsFirst, a draft framework of the MCDA criteria was built based on a systematic literature evaluation and the EVIDEM framework tools. Second, stakeholder groups were formed and expert opinions were collected through the brainstorming and expert consultation methods. Third, from the perspective of stakeholders, the five-point weighting method and a two-step percentile distribution method were employed to weigh the quantitative criteria in the framework for orphan drug value evaluation. Meanwhile, from the public perspective, a survey was conducted on a sample of 71 people to obtain the scoring scale of the framework for orphan drugs through a two-step percentile distribution method. Finally, based on the synthetization and comparison of all evidence and methods, we developed the framework criteria and scoring scale for the orphan medicinal products.

resultsCombined with the stakeholder selection and suggestions in the stakeholder workshop, the framework criteria for the evaluation were constructed based on China's national conditions, which included 11 quantitative and 8 qualitative criteria. The two-step percentile distribution method was selected as the weighting method.

conclusionsMCDA is feasible for the value assessment of orphan drugs in China and can be used as a supplementary tool for drug access decisions in medical insurance. It is suggested to further improve the value assessment framework of orphan medicinal products, scientifically evaluate the MCDA framework weighting method, explore a framework system suitable for China's national conditions.

Indexed as

Orphan Drug ProductionChinaDecision Support TechniquesHumansRare DiseasesCriteriaEVIDEMMCDAOrphan medicinal productsValue assessment framework

Identifiers

PMID39428462
PMCPMC11492536

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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.