Development of AOSpine BOnE (Bone Osteobiologics and Evidence) Classification. Issue 7 (October 2020)

• Record Type: Journal Article
• Authors: Wang, Jeffrey C.; Yoon, S. Tim; Brodke, Darrel S.; Park, Jong-Beom; Hsieh, Patrick; Meisel, Hans-Joerg; Buser, Zorica
• Is Part Of: Global spine journal. Volume 10:Issue 7(2020)
• Page Start: 871
• Page End: 874
• Publication Date: 2020-10
• Subjects: osteobiologics -- classification -- BOnE -- level of evidence -- spine fusion; Spine -- Diseases -- Periodicals; Spine -- Diseases -- Treatment -- Periodicals; Spine -- Abnormalities -- Periodicals; Spine -- Surgery -- Periodicals; 616.73
• DOI: 10.1177/2192568219880176
• Languages: English
• ISSNs: 2192-5682

Abstract

Study Design: Classification development. Objectives: The aim of our study was to develop a 3-tier classification for the levels of evidence for osteobiologics and provide a description of the principles by which osteobiologics can be evaluated. BOnE (Bone Osteobiologics and Evidence) classification evaluates each osteobiologic based on the available evidence, and if the published evidence is based on clinical, in vivo or in vitro studies. Methods: The process of establishing the BOnE classification included 5 face-to-face meetings and 2 web calls among members of the AOSpine Knowledge Forum Degenerative. Results: The 3 levels of evidence were determined based on the type of data on osteobiologics: level A for human studies, level B for animal studies, and level C for in vitro studies, with level A being the highest level of evidence. Each level was organized into 4 subgroups (eg, A1, A2, A3, and A4). Conclusions: The use and the variety of osteobiologics for spine fusion has dramatically increased over the past few decades; however, literature on their effectiveness is inconclusive. Several prior systematic reviews developed by AOSpine Knowledge Forum Degenerative reported low level of evidence primarily due to the high risk of bias, small sample size, lack of control groups, and limited patient-reported outcomes. BOnE classification will provide a universal platform for research studies and journal publications to classify a new or an existing product and will allow for creating decision-making algorithms for surgical planning.