Evidence map›Paper›PMID 36653783›Full record

ReviewCost effectiveness and resource allocation : C/E2023

Use of real-world evidence to support regulatory decisions on medical devices in China and a unique opportunity to gain accelerated approval in "Boao Lecheng Pilot Zone".

Jiahe Li, Lichang Liu, Haijun Cao, Mei Yang, Xin Sun

Abstract readReview
In one paragraph

Review in Cost effectiveness and resource allocation : C/E, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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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

5 authors.

Jiahe LiHappy Life Tech, Boston, MA, 02494, USA.
Lichang LiuHappy Life Tech, Shanghai, 200233, China.
Haijun CaoHappy Life Tech, Shanghai, 200233, China.
Mei YangHappy Life Tech, Short Hills, NJ, 07078, USA.
Xin SunChinese Evidence-based Medicine Center, and NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, West China Hospital, Sichuan University, Chengdu, 610041, China. sunx79@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article aims to summarize the development and challenges of real-world data (RWD) and real-world evidence (RWE) in China and introduce a unique opportunity for medical devices to gain accelerated regulatory approval in China by utilizing RWE generated in a free trade pilot zone "Boao Lecheng" in Hainan Province. In 2020, the National Medical Products Administration (NMPA) issued a draft guideline on the "Use of real-world data to support clinical evaluation for medical devices", suggesting that RWE derived from RWD could support clinical evaluation throughout the life cycle of a medical device. Meanwhile, the Chinese government has allowed qualified RWD collected in Boao Lecheng to support registration application of innovative medical devices and drugs in China. These medical devices and drugs should have been approved abroad, but not in China yet, and met urgent and unmet medical needs in China. The article also presents the successful story of an innovative Glaucoma drainage tube as the first medical device approved in China using RWE generated in Boao Lecheng in 2020. Although we are witnessing an increased interest in RWE, a few challenges remain, e.g., limited data accessibility and data sharing, concerns on data quality, etc. Collaborations among relevant stakeholders in the RWE research are vital to address the challenges.

Indexed as

ChinaMedical deviceReal-world dataReal-world evidenceRegulatory decision

Identifiers

PMID36653783
PMCPMC9850538

What OpenQuestion holds

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LicenceCC BY
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 OpenQuestion graph.