Evaluation of Predatory Journal Publication in Systematic Reviews in the Top Five Oncology Journals: A Cross-Sectional Analysis

Research output: Contribution to conferencePosterpeer-review

Abstract

Introduction: In 2012, Jeffrey Beall coined the term “predatory journal” to describe journals that used the open-access model to exploit inexperienced researchers. Predatory journals are problematic as many lack the formal peer-review processes found within their scientific counterparts. This may result in the publication of faulty data and potentially influence patient care by misleading clinician readers. Through this problem, the journals are profiting from charging fees for publications that lack any merit. This method prevents potential publications from reaching reputable sources. Even more dangerous is that predatory publications could be unknowingly cited in other medical literature, such as systematic reviews and clinical practice guidelines (creating faulty resources for clinicians). Thus, our goal was to identify the use of predatory journals in systematic reviews published in the top five high impact oncology journals. We sought to study the characteristics of any predatory published studies in order to recognize associations between systematic reviews containing predatory journals.

Methods: Using a cross-sectional design, we searched PubMed using search-strings for systematic reviews published in the top five oncology journals based on Google Scholar Metrics’ five-year h-index — Journal of Clinical Oncology, The Lancet. Oncology, Clinical Cancer Research, Annals of Oncology, and Cancer Research. We included the 10 most recent systematic reviews from each journal. Studies met inclusion criteria if they were a systematic review/meta analysis and published in English. The extracted primary study’s publishing journals were then compared to a list of known or suspected predatory journals, Beall’s List. If a study was determined to be published by a predatory journal, additional items were extracted from both the systematic review and the predatory study in a masked duplicate fashion using a pilot-tested Google Form by investigators A.R. and A.D.

Results: Four out of five of the top oncology journals published a systematic review with a primary study published in a predatory journal. In total, 8 systematic reviews (8/50, 16%) contained 18 primary studies published within one of two predatory journals — Genetics and Molecular Research and Oncotarget. Three systematic reviews included more than one predatory publication. One systematic review published by Budach, et al. contained seven predatory publications in their included studies sample. Annals of Oncology included no systematic reviews with a predatory publication. One systematic review by Konstantinopoulos et al., which also served as a clinical practice guideline, included two primary studies that were published in a predatory journal. Collectively, the 18 predatory publications have been cited 670 times.

Conclusion: In conclusion, we found predatory publications to be present in a number of oncology systematic reviews, as well as, in a clinical practice guideline. The purpose of this study was not to explore the accuracy of predatory publications nor the influence they may have on clinical decision making; however, future research is warranted to determine their impact on appropriate healthcare treatment plans. In the future, researchers and clinicians alike should beware of the effect predatory journals have on those individuals who click “submit.”
Original languageAmerican English
Pages82
StatePublished - 22 Feb 2021
EventOklahoma State University Center for Health Sciences Research Days 2021: Poster presentation - Oklahoma State University Center for Health Sciences Campus, Tulsa, United States
Duration: 22 Feb 202126 Feb 2021

Conference

ConferenceOklahoma State University Center for Health Sciences Research Days 2021
Country/TerritoryUnited States
CityTulsa
Period22/02/2126/02/21

Keywords

  • Oncology
  • Predatory Journals
  • Systematic Review
  • Cross-Sectional Analysis

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