Reproducible research practices and transparency in reproductive endocrinology and infertility articles

Objective: To analyse the published literature in reproductive endocrinology and infertility (REI) to examine the transparency and the use of reproducible research practices of the scientific literature and to identify possible avenues for improvement. Design: Meta-epidemiologic study. We examined the first 20 consecutive full-text original articles presenting primary data from five REI-specific journals for 2013 and for 2018, and eligible REI articles published in 2013–2018 in five high-impact general journals. Eligible articles were required to be full-text original articles, presenting primary data. Setting: Not applicable. Patient(s): Not applicable. Intervention(s): Not applicable. Main Outcome Measure(s): Each article was assessed for study type, trial registration, protocol and raw data availability, funding and conflict of interest declarations, inclusion in subsequent systematic reviews and/or meta-analyses, sample size, and whether the work claimed to be novel or replication. Sample sizes and citation counts also were obtained. Result(s): A total of 222 articles were deemed eligible; 98 from REI journals published in 2013, 90 from REI journals published in 2018, and 34 from high-impact journals. There were 37 studies registered, 15 contained a protocol, and two stated actively that they were willing to share data. Most studies provided a statement about funding and conflicts of interest. Two articles explicitly described themselves as replications. All randomized controlled trial published in REI journals were registered prospectively; many meta-analyses were not registered. High-impact journal articles had a greater median sample size and more citations and were more likely to be registered, to have a protocol, and to claim novelty explicitly when compared with REI 2013 and 2018 articles. Conclusion(s): Research in REI can be improved in prospective registration, routine availability of protocols, wider sharing of raw data whenever feasible, and more emphasis on replication.