New approaches to safety monitoring of novel systemic treatments for atopic dermatitis in clinical practice and underrepresented populations

总结： 严重治疗难治性特应性皮炎（AD）是一种使人衰弱的疾病， 冲击皮肤病学已经经历了靶向免疫调节药物（IMD）的出现， 治疗AD的前所未有的疗效。它们的最佳用途仍然未知，因为它们的安全性仍然存在 不充分的特点。 一系列严重的副作用是可以想象的基础上的免疫途径，虽然它是不太可能的， 它们都将在临床实践中发挥作用。量化或反驳这些不良反应对于临床研究至关重要。 获益-风险评估和个性化治疗决策。现有的试验没有回答这些问题 这些问题，不太可能在不久的将来解决。由此产生的不确定性导致双方过度 限制但也积极处方高效的IMD，这项建议旨在关闭这一明显的 知识差距。 我们提出了一个基于人群的前瞻性药物安全监测系统，利用现有的数据源 这缩短了洞察力的时间，并通过先进的因果推理提供了高有效性的发现， 方法.纵向医疗保健数据库的分析涵盖了> 7800万美国人的源人群 包括商业保险和医疗补助受益人。新的和迫切需要的安全见解将 反映临床实践，包括通常被排除在RCT之外的人群，如儿童、女性、 育龄期、复杂疾病患者、少数民族人群和存在风险因素的患者。 索赔数据源的规模增加了统计能力以及与电子健康记录的联系， 子集提高了临床深度。我们使用的因果推理方法，在试点数据中表现出较高的有效性 并用一种新的数据挖掘方法来补充它们，以识别意外事件。分析已经完成 具有最高的透明度和可重复性，以支持临床决策。这个项目的发现， IMD在临床实践中的最佳使用将导致更有针对性的处方并使大患者群体受益， 包括RCT中代表性不足的人群：儿童、老年人、孕妇、少数民族， 既存感染、癌症、VTE等患者。 该项目具有高度创新性，因为它将产生直接适用的临床见解， 使用新的免疫调节药物（IMD）治疗特应性皮炎。利用现有索赔数据 来源与添加EHR数据，它建立在因果推理的新方法，以减轻偏见产生的真实的- 皮肤病学世界数据分析。通过拟定的前瞻性研究加速证据生成 监测系统结合我们在药物流行病学分析中的跟踪记录，本研究将 有效地缩小知识差距，在许多代表性不足和高风险患者中实现IMD的最佳使用。

Summary: Severe treatment recalcitrant atopic dermatitis (AD) is a debilitating condition with substantial population impact. Dermatology has experienced the emergence of targeted immuno-modulating drugs (IMDs) that have unprecedented efficacy in treating AD. Their optimal use is still unknown because their safety remains insufficiently characterized. A range of serious side effects are conceivable based on the immunologic pathways although it is unlikely that they will all play out in clinical practice. Quantifying or refuting these adverse effects is critical for a clinical benefit-risk assessment and personalized treatment decisions. Existing trials have not answered these questions and are unlikely to address them in the near future. The resulting uncertainty has led to both overly restrictive but also aggressive prescribing of highly efficacious IMDs and this proposal aims to close this glaring knowledge gap. We propose a population-based prospective drug safety monitoring system leveraging existing data sources that shortens the time to insights and provides high validity findings through advanced causal inference methods. Analyses of longitudinal healthcare databases cover a source population of >78 million Americans and include commercially insured and Medicaid beneficiaries. New and urgently needed safety insights will reflect clinical practice, including populations typically excluded from RCTs, like children, women in reproductive age, patients with complex diseases, minority populations, and patients with existing risk factors. The size of the claims data source increases statistical power and the linkage to electronic health records in subsets improves clinical depth. We use causal inference methods that demonstrated high validity in pilot data and complement them with a novel data mining approach to identify unsuspected events. Analyses are done with highest transparency and reproducibility to support clinical decision making. This project’s finding on the optimal use of IMDs in clinical practice will lead to more targeted prescribing and benefit large patient groups, including populations underrepresented in RCTs: children, older adults, pregnant women, racial minorities, patients with pre-existing infections, cancers, VTE and others. This project is highly innovative as it will generate directly applicable clinical insights on the safe and targeted use of new immuno-modulating drugs (IMDs) to treat atopic dermatitis. Leveraging existing claims data sources with added EHR data it builds on novel methods for causal inference to mitigate biases arising in real- world data analyses in dermatology. The expedited evidence generation via the proposed prospective monitoring system combined with our track record in pharmacoepidemiologic analyses, this research will efficiently close knowledge gaps for optimal IMD use in many underrepresented and high-risk patients.