Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Canada; Arthritis Research Canada, Richmond, BC, Canada; McCaig Institute for Bone and Joint Health, Calgary, Canada.
School of Population and Public Health, University of British Columbia, Vancouver, Canada; Arthritis Research Canada, Richmond, BC, Canada.
Best Pract Res Clin Rheumatol. 2022 Dec;36(4):101812. doi: 10.1016/j.berh.2022.101812. Epub 2023 Jan 16.
The last few decades have seen major therapeutic advancements in rheumatoid arthritis (RA) therapeutics. New disease-modifying antirheumatic drugs (DMARDs) have continued to emerge, creating more choices for people. However, no therapeutic works for all patients. Each has its own inherent benefits, risks, costs, dosing, and monitoring considerations. In parallel, there has been a focus on personalized medicine initiatives that tailor therapeutic decisions to patients based on their unique characteristics or biomarkers. Personalized effect estimates require an understanding of a patient's baseline probability of response to treatment and data on the comparative effectiveness of the available treatments. However, even if accurate risk prediction models are available, trade-offs often still need to be made between treatments. In this paper, we review the history of RA therapeutics and progress that has been made toward personalized risk predictive models for DMARDs, outlining where knowledge gaps still exist. We further review why patient preferences play a key role in a holistic view of personalized medicine and how this links with shared decision-making. We argue that a "preference misdiagnosis" may be equally important as a medical misdiagnosis but is often overlooked.
过去几十年中，类风湿关节炎（RA）的治疗取得了重大进展。新的疾病修饰抗风湿药物（DMARD）不断涌现，为患者提供了更多的选择。然而，没有一种治疗方法适用于所有患者。每种治疗方法都有其自身的固有优势、风险、成本、剂量和监测注意事项。与此同时，人们也越来越关注个性化医疗倡议，根据患者的独特特征或生物标志物来为他们量身定制治疗决策。个性化疗效估计需要了解患者对治疗的基础反应概率以及现有治疗方法的比较疗效数据。但是，即使有准确的风险预测模型，治疗之间通常仍需要进行权衡。在本文中，我们回顾了 RA 治疗的历史以及在 DMARD 个性化风险预测模型方面取得的进展，概述了仍然存在知识空白的地方。我们进一步探讨了为什么患者偏好在个性化医疗的整体观点中起着关键作用，以及这如何与共同决策相关联。我们认为，“偏好误诊”可能与医疗误诊同样重要，但往往被忽视。
