Iulita Maria Florencia, Streel Emmanuel, Harrison John
Altoida Inc. Washington District of Columbia USA.
Scottish Brain Sciences Gyleview House South Gyle Edinburgh UK.
Alzheimers Dement (N Y). 2025 Jun 2;11(2):e70114. doi: 10.1002/trc2.70114. eCollection 2025 Apr-Jun.
MCID (minimal clinically important difference) is a patient-centered concept used in clinical research that represents the smallest change that someone living with Alzheimer's disease would identify as important. There are several challenges associated with the universal application of this construct. Alzheimer's disease progresses differently for each individual, complicating the establishment of a universal standard that accounts for individual-level issues. Alzheimer's disease is also a gradual and evolving disorder, and what is perceived as clinically meaningful can vary significantly at early and late disease stages. People living with Alzheimer's disease and caregivers may have differing perspectives on the benefits of treatment outcomes, making it more challenging to establish an appropriate MCID. Moreover, Alzheimer's trials rely on a variety of tests to evaluate cognitive and functional impairments. However, these tests often lack sensitivity to early-stage changes and are affected by variability in rater rankings. Digital biomarkers and advanced health technologies have emerged as a hot topic in modern medicine. They offer a promising approach for detecting real-time, objective clinical differences and improving patient outcomes by enabling continuous monitoring, individualized assessments, and leveraging artificial intelligence learning for complex analytical predictions. However, while these advancements hold great potential, they also raise important considerations around standardization, accuracy, and integration into current clinical frameworks. As new technologies are introduced alongside evolving regulatory frameworks, the primary focus must remain on outcomes that truly matter to people living with Alzheimer's disease and their caregivers, ensuring that the principle of clinical meaningfulness is not lost.
Minimal clinically important difference (MCID) represents the smallest change in a patient's condition that would be considered meaningful, but defining this for Alzheimer's disease is challenging due to its heterogeneity.The perception of what is clinically meaningful may differ at the individual level, at different disease stages within the same individual, and between patient and caregiver.Traditional tests used as endpoints in Alzheimer's trials lack the sensitivity to detect subtle changes and are limited by range restrictions, making them less effective for accurately capturing treatment efficacy.Digital biomarkers and artificial intelligence (AI)-driven health technologies may offer the potential to enhance the detection of clinically meaningful changes by providing continuous, objective monitoring and advanced analytics for individualized patient assessments.Both the United States Food and Drug Administration (FDA) and European Medicines Agency (EMA) are playing pivotal roles in advancing the use of digital health technologies, facilitating the evolution of regulatory frameworks to ensure these innovations are effectively integrated into clinical research and practice.
最小临床重要差异（MCID）是临床研究中使用的以患者为中心的概念，代表阿尔茨海默病患者认为重要的最小变化。该概念的普遍应用存在若干挑战。阿尔茨海默病在每个个体中的进展不同，这使得建立一个考虑个体层面问题的通用标准变得复杂。阿尔茨海默病也是一种渐进性和不断演变的疾病，在疾病早期和晚期，被视为具有临床意义的情况可能有显著差异。阿尔茨海默病患者及其护理人员对治疗结果的益处可能有不同看法，这使得确定合适的MCID更具挑战性。此外，阿尔茨海默病试验依靠多种测试来评估认知和功能损害。然而，这些测试往往对早期变化缺乏敏感性，并且受到评分者排名差异的影响。数字生物标志物和先进健康技术已成为现代医学中的热门话题。它们为检测实时、客观的临床差异并通过实现持续监测、个性化评估以及利用人工智能学习进行复杂分析预测来改善患者预后提供了一种有前景的方法。然而，尽管这些进展具有巨大潜力，但它们也引发了围绕标准化、准确性以及融入当前临床框架的重要考量。随着新技术与不断演变的监管框架一同引入时，主要重点必须始终放在对阿尔茨海默病患者及其护理人员真正重要的结果上，确保不丢失临床意义原则。
最小临床重要差异（MCID）代表患者病情中被认为有意义的最小变化，但由于阿尔茨海默病的异质性，为其定义具有挑战性。在个体层面、同一个体的不同疾病阶段以及患者与护理人员之间，对临床意义的认知可能存在差异。阿尔茨海默病试验中用作终点的传统测试缺乏检测细微变化的敏感性，并且受到范围限制，使其在准确捕捉治疗效果方面效果较差。数字生物标志物和人工智能（AI）驱动的健康技术可能通过提供持续、客观的监测以及用于个性化患者评估的先进分析，增强对临床有意义变化的检测潜力。美国食品药品监督管理局（FDA）和欧洲药品管理局（EMA）在推进数字健康技术的使用方面都发挥着关键作用，促进监管框架的演变，以确保这些创新有效地融入临床研究和实践。
