Evidence map›Paper›PMID 41507534›Full record

ArticleJournal of patient-reported outcomes2026

Application of patient-reported outcomes in clinical trials of traditional Chinese medicine registered in international clinical trials registry platform, from 2010 to 2022: a cross-sectional study.

Yuanyuan Lin, Xiaowen Zhang, Zhenqian Xu, Lin Liu, Chen Shen, Mei Han, Huijuan Cao, Yutong Fei, Jianping Liu, Hongguo Rong and 1 more

Abstract read
In one paragraph

Article in Journal of patient-reported outcomes, 2026. 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
0cells of the map it votes in
0citing 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

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

11 authors.

Yuanyuan LinCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Xiaowen ZhangCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Zhenqian XuCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Lin LiuCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Chen ShenCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Mei HanCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Huijuan CaoCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Yutong FeiCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Jianping LiuCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Hongguo RongCenter for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China. hgrong@hsc.pku.edu.cn.ORCID http://orcid.org/0000-0003-4536-4396
Chunxia ZhouThe Second Medical Center of PLA General Hospital, Beijing, 100853, China. chouroutou@126.com.

Funding

High-level traditional Chinese medicine key subjects construction project of National Administration of Traditional Chinese Medicine--Evidence-based Traditional Chinese Medicine zyyzdxk-2023249
6 · The paper itself

Abstract

purposePatient-reported outcomes (PROs) assist patients and clinicians in assessing treatment effectiveness and enhancing healthcare quality. This study aims to explore and analyze the application and characteristics of PROs in clinical trials of Traditional Chinese Medicine (TCM).

methodsThis cross-sectional study was based on randomized clinical trials of TCM between January 1, 2010, and December 31, 2022 in International Clinical Trials Registry Platform. For each included trial, data including study phase, design, participant demographics, target diseases, PROs, and PRO measurements were extracted. Trials were categorized into three groups: (1) recorded specified patient-reported outcome tools, (2) referenced patient subjective outcomes without specified tools, and (3) did not mention any PROs. Further descriptive statistical analysis were conducted on the most commonly used PRO tools in different countries and for different diseases.

resultsAmong a total of 7783 eligible trials, 4858 (62.4%) listed explicit PRO tools, and 850 (10.9%) referenced PROs without specified tools. The most common conditions evaluated by PRO tools were musculoskeletal diseases (935 trials, 19.2%), symptoms (714, 14.7%), and neurological diseases (500, 10.3%). Frequently used PRO tools included the Visual Analogue Scale (VAS), 36-item Short-Form Health Questionnaire, and Pittsburgh Sleep Quality Index. Regionally, most PRO-related trials were in the Western Pacific (3904, 68.4%) and fewest in Africa (8, 0.1%). Countries conducting the most PRO-related trials were China, Iran, the USA, South Korea, and Brazil, focusing on musculoskeletal, symptoms, neurological, genitourinary, and digestive diseases, with varying popular disease-specific PRO tools by country. Musculoskeletal diseases were the primary focus in China, Brazil, and South Korea.

conclusionsThe use of PROs in TCM clinical trials has grown during the study period. However, there was an uneven regional distribution of PRO application and a lack of standardized, reliable PRO tools tailored for TCM. Great efforts are needed to enhance the quality and promote the use of PRO tools in TCM clinical research.

Indexed as

Medicine, Chinese TraditionalPatient Reported Outcome MeasuresRegistriesCross-Sectional StudiesHumansRandomized Controlled Trials as TopicClinical trialsCross-sectional studyOutcome studyPatient-reported outcomesTraditional Chinese medicine

Identifiers

PMID41507534
PMCPMC12881188

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.