Evidence map›Paper›PMID 41536814›Full record

ArticleJournal of clinical and translational science2026

Determinants of publication likelihood and timeliness for clinical studies.

Haoyuan Wang, Le Li, Chuan Hong, Rui Yang, Karen Chiswell, Sara B Calvert, Lesley Curtis, Ali B Abbasi, Scott Michael Palmer, Adrian F Hernandez and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical and translational science, 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

12 authors.

Haoyuan WangDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
Le LiUniversity of Texas at Austin, Austin, TX, USA.ORCID https://orcid.org/0009-0009-3909-452X
Chuan HongDepartment of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.ORCID https://orcid.org/0000-0001-7056-9559
Rui YangDepartment of Biomedical Informatics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Karen ChiswellDuke Clinical Research Institute, Duke University, Durham, NC, USA.
Sara B CalvertDuke Clinical Research Institute, Duke University, Durham, NC, USA.
Lesley CurtisDepartment of Medicine, Duke University, Durham, NC, USA.
Ali B AbbasiDepartment of Surgery, University of California, San Francisco, CA, USA.
Scott Michael PalmerDepartment of Medicine, Duke University, Durham, NC, USA.
Adrian F HernandezDuke Clinical Research Institute, Duke University, Durham, NC, USA.ORCID https://orcid.org/0000-0003-3387-9616
Frank W RockholdDuke Clinical Research Institute, Duke University, Durham, NC, USA.ORCID https://orcid.org/0000-0003-3732-4765
Christopher LindsellDuke Clinical Research Institute, Duke University, Durham, NC, USA.ORCID https://orcid.org/0000-0002-3297-2811

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Timely dissemination of clinical trial results is essential to advance knowledge, guide practice, and improve outcomes, yet many trials remain unpublished, limiting impact. We examine what drives publication and timelines across three major clinical domains. Methods: We analyzed study design and factors associated with dissemination of interventional trials, focusing on cardiovascular disease (CVD), cancer, and COVID-19. A total of 10,785 trials (CVD: 5929; cancer: 4210; COVID-19: 646) were linked to PubMed publications using National Clinical Trial identifiers. Study design, operational, and transparency-related features were assessed as predictors of time to publication, defined as the interval from study completion to first publication, using Cox proportional hazards model. Results: COVID-19 trials had the highest publication rate (49.6%), followed by CVD (42.3%) and cancer (32.9%), likely reflecting pandemic-related prioritization. Faster publication was associated with larger enrollment, more sites, result posting, randomization, DMC presence, and higher blinding levels (all Conclusions: Key study design and operational factors consistently predict whether and when trials are published. Strengthening methodological rigor, result reporting, and multi-site collaboration may accelerate timely dissemination into peer-reviewed literature.

Indexed as

clinical trial featuredisseminationinterventional trialspredictive modelingSurvival analysis

Identifiers

PMID41536814
PMCPMC12797179

What Socratic holds

Textmetadata
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 Socratic graph.