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

在临床实践和代表性不足的人群中对特应性皮炎的新型全身治疗进行安全监测的新方法

• 批准号: 10339592
• 负责人: Sebastian G. Schneeweiss
• 金额: $ 76.81万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10339592
• 关键词: Address; Adverse effects; Age; Algorithms; American; Atopic Dermatitis; Bacterial Infections; Child; Clinical; Complement; Complex; Data; Data Analyses; Data Sources; Databases; Dermatologist; Dermatology; Development; Disease; Drug usage; Elderly; Electronic Health Record; Epidemic; Ethnic Origin; Event; Exposure to; Future; Generations; Glare; Health; Healthcare; Immune; Immunologics; Immunomodulators; Immunosuppression; Infection; Investigation; Knowledge; Link; Malignant Neoplasms; Medicaid; Methods; Minority Groups; Minority Women; Modernization; Modification; Monitor; Morbidity - disease rate; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Opportunistic Infections; Outcome; Pathway interactions; Patient-Focused Outcomes; Patients; Pattern; Pharmaceutical Preparations; Pharmacoepidemiology; Placebos; Play; Population; Predisposition; Pregnant Women; Production; Quality of life; Race; Reproducibility; Research; Residual state; Risk; Risk Factors; Risk-Benefit Assessment; Safety; Scanning; Signal Transduction; Source; Subgroup; System; Testing; Time; Uncertainty; Underrepresented Minority; Underrepresented Populations; Update; Variant; Venous; Virus Diseases; Woman; base; beneficiary; child bearing; chronic inflammatory skin; clinical application; clinical decision support; clinical decision-making; clinical practice; cohort; comorbidity; comparative safety; coronavirus disease; cytokine; data mining; design; drug market; economic indicator; experience; flu; follow-up; high risk; immune function; improved; infection risk; inhibitor; innovation; insight; longitudinal analysis; medication safety; minority patient; novel; novel strategies; off-label use; personalized medicine; placebo controlled trial; population based; prior authorization; prospective; racial minority; real time monitoring; reproductive; side effect; skin disorder; socioeconomics; standard care; targeted treatment; treatment choice; trend; venous thromboembolism; young woman

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.

概括： 严重的治疗顽固性特应性皮炎（AD）是一种令人衰弱的状况 影响。皮肤病学经历了具有靶向免疫调节药物（IMD）的出现 治疗AD的前所未有的效率。他们的最佳用途仍然未知，因为他们的安全仍然存在 不充分表征。 基于免疫途径，可以想象一系列严重的副作用，尽管不太可能 他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至关重要 福利风险评估和个性化治疗决策。现有的试验尚未回答这些 问题，不太可能在不久的将来解决。由此导致的不确定性导致 限制性的，但同时对高效IMD的处方，该提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，利用现有数据来源 这会缩短洞察力的时间，并通过高级因果推断提供高有效性发现 方法。纵向医疗保健数据库的分析涵盖了7800万美国人的来源人群 并包括商业保险和医疗补助受益人。新的，急需的安全见解将 反映临床实践，包括通常不包括RCT的人群，例如儿童，女性 生殖年龄，复杂疾病的患者，少数人群和现有危险因素的患者。 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 子集改善了临床深度。我们使用的因果推理方法证明了飞行员数据有效性很高 并通过一种新型的数据挖掘方法来补充他们，以识别未建立的事件。分析完成了 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具针对性的处方并受益于大型患者群体， 包括人口不足的RCT人群：儿童，老年人，孕妇，少数族裔， 患有先前感染，癌症，VTE等的患者。 该项目具有很高的创新性，因为它将直接对安全且有针对性 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 具有添加EHR数据的来源，它基于新的方法来构建因果推断的新方法，以减轻在实地中产生的偏见 皮肤病学的世界数据分析。通过拟议的潜在的加快证据生成 监测系统结合了我们在药物电子学分析中的往绩，这项研究将 有效地缩小知识差距，可在许多代表性不足和高危患者中使用最佳IMD。