Objective: To assess the time from completion to publication of randomized controlled trials (RCTs) on connective tissue diseases (CTDs), investigate the factors associated with, and explore the influence of significance of study results on time to publication (time-lag publication bias).

Methods: We included interventional, phase 2/3, 3, or 4 RCTs on CTDs registered in Clinicaltrials.gov from 2000 to 2016, whose results had been published in a peer-review journal less than 5 years after their completion. Main trial features, including the significance of primary outcome results, were collected. Time to publication was the time from study completion to the earliest publication date. Multivariable linear regression was used to identify factors associated with time to publication.

Results: We included 62 studies, mostly phase 3 (61%) trials on pharmacologic treatments (94%); we recruited patients with systemic lupus (55%) or systemic sclerosis (23%) and planned to enroll a median of 131 (IQR [interquartile range]: 61-288) patients. Twenty-two (35%) reported at least a statistically significant primary outcome. Median time to publication was 28 months (IQR: 17-36). In a multivariable analysis, time to publication progressively improved over time (faster publication in recent years, with the average time to publication decreasing by 1.3 [95% CI: 0.3-2.3] months per year) and was not influenced by the significance of primary outcome results, funder, impact factor of the journal, number of recruiting countries, and comparator.

Conclusion: A high proportion of CTDs-RCTs is published beyond 2 years from completion. We did not find evidence of time-lag publication bias, and time to publication improved over time.

Title	Published in	Year	Views	Downloads

Prospective registration of trials : where we are, why, and how we could get better	Journal of clinical epidemiology	2024	55	161
Time to Publication and Time‐Lag Publication Bias for Randomized Trials on Connective Tissue Diseases	ACR open rheumatology	2023	58	149
A nonparametric statistical procedure for the detection of marine pollution	Journal of Applied Statistics	2019	288	0

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