Evidence map›Paper›PMID 41174062›Full record

ArticleCommunications medicine2025

Digital health technology use in clinical trials of rare diseases: a systematic review.

Xiangyun Mao, Dian Zeng, Xiaocong Wang, David A Pearce, Gareth Baynam, Niels H Chavannes, Wendy K Chung, Honghan Wu, Yih-Chung Tham, Shuyang Zhang and 2 more

Abstract read
In one paragraph

Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
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

12 authors.

Xiangyun Mao *Vanke School of Public Health, Tsinghua University, Beijing, China.ORCID http://orcid.org/0009-0000-0233-5523
Dian Zeng *Tsinghua Medicine, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-5592-9584
Xiaocong WangTsinghua Medicine, Tsinghua University, Beijing, China.
David A PearceDepartment of Pediatrics, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA.
Gareth BaynamRare Care Centre, Perth Children's Hospital, Perth, WA, Australia.ORCID http://orcid.org/0000-0003-4920-9553
Niels H ChavannesDepartment of Public Health and Primary Care, National eHealth Living Lab, Leiden University Medical Center, Leiden, The Netherlands.
Wendy K ChungDepartment of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0003-3438-5685
Honghan WuInstitute of Health Informatics, University College London, London, United Kingdom.ORCID http://orcid.org/0000-0002-0213-5668
Yih-Chung ThamDepartment of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0002-6752-797X
Shuyang ZhangState Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. shuyangzhang103@nrdrs.org.ORCID http://orcid.org/0000-0002-1532-0029
Guanqiao LiVanke School of Public Health, Tsinghua University, Beijing, China. guanqiaoli@tsinghua.edu.cn.ORCID http://orcid.org/0000-0002-3626-7220
Tien Yin WongSchool of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China. ophwty@nus.edu.sg.ORCID http://orcid.org/0000-0002-8448-1264

Funding

National Natural Science Foundation of China (National Science Foundation of China) 72374119
6 · The paper itself

Abstract

backgroundRare disease clinical trials face unique challenges, resulting in low enrollment and limited retention. Digital health technologies (DHTs), when applied through a patient-centric lens, offer promising solutions to these challenges by enhancing data collection efficiency, improving patient engagement, and supporting long-term health care.

methodsThis study investigates DHT application in clinical studies across the ten most-studied rare diseases and was registered with PROSPERO (registration number: CRD420251088025). Up to June 26 2024, a total of 262 studies were identified through ClinicalTrials.gov, the International Clinical Trials Registry Platform, Cochrane Central Register of Controlled Trials, PubMed, and Web of Science. DHT applications were classified into patient recruitment, digital treatment, data monitoring and collection, outcome assessment, remote follow-up, and long-term care management based on scenarios and functionalities.

resultsAmong all DHT applications, data monitoring and collection was the most prevalent (31.3%), serving primarily to enable continuous tracking of physiological parameters relevant to specific rare disease conditions. Digital treatment is featured in 57 studies (21.8%), most commonly as digital physiotherapy. A notable increase in DHT adoption is observed from 2017-2020 to 2021-2024 across nearly all ten diseases. Between 2021 and 2024, cystic fibrosis shows the highest proportion of DHT-enabled trials relative to all studies conducted for that disease (29.7%).

conclusionsOur findings reveal a growing trend toward digital integration in rare disease trials to support decentralized, scalable, and patient-centered research models. We propose a "4A" conceptual framework-Accessibility, Agility, Awareness, and Adaptability to accelerate therapeutic development and expand access to care for these underserved rare disease populations.

Identifiers

PMID41174062
PMCPMC12578828

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.