Department of Epidemiology, Gillings School of Global Public Health.
Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, North Carolina.
Curr Opin Rheumatol. 2024 Mar 1;36(2):108-112. doi: 10.1097/BOR.0000000000000985. Epub 2023 Oct 19.
This review highlights recently published studies on osteoarthritis (OA) epidemiology, including topics related to understudied populations and joints, imaging, and advancements in artificial intelligence (AI) methods.
Contemporary research has improved our understanding of the burden of OA in typically understudied regions, including ethnic and racial minorities in high-income countries, the Middle East and North Africa (MENA) and Latin America. Efforts have also been made to explore the burden and risk factors in OA in previously understudied joints, such as the hand, foot, and ankle. Advancements in OA imaging techniques have occurred alongside the developments of AI methods aiming to predict disease phenotypes, progression, and outcomes.
Continuing efforts to expand our knowledge around OA in understudied populations will allow for the creation of targeted and specific interventions and inform policy changes aimed at reducing disease burden in these groups. The burden and disability associated with OA is notable in understudied joints, warranting further research efforts that may lead to effective therapeutic options. AI methods show promising results of predicting OA phenotypes and progression, which also may encourage the creation of targeted disease modifying OA drugs (DMOADs).
目的综述：本文重点介绍了最近发表的关于骨关节炎（OA）流行病学的研究，包括针对研究较少的人群和关节、影像学以及人工智能（AI）方法进展的相关主题。
最新发现：当代研究提高了我们对 OA 在通常研究较少的地区的负担的认识，包括高收入国家中的少数民族和种族、中东和北非（MENA）以及拉丁美洲。还努力探索以前研究较少的关节（如手、脚和脚踝）中的 OA 负担和危险因素。随着旨在预测疾病表型、进展和结果的 AI 方法的发展，OA 成像技术也取得了进展。
总结：继续努力扩大我们对研究较少人群中 OA 的认识，将有助于制定针对这些人群的有针对性和具体的干预措施，并为旨在减轻这些人群疾病负担的政策变化提供信息。在研究较少的关节中，OA 相关的负担和残疾是显著的，这需要进一步的研究努力，可能会带来有效的治疗选择。AI 方法在预测 OA 表型和进展方面显示出有希望的结果，这也可能鼓励开发针对疾病的 OA 药物（DMOADs）。
