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： 严重治疗顽固性特应性皮炎 (AD) 是一种使人衰弱的疾病，影响大量人口 靶向免疫调节药物 (IMD) 的出现对皮肤科产生了影响。 由于它们的安全性仍然存在，因此它们在治疗 AD 方面的最佳用途仍然未知。 特征不够充分。 根据免疫途径，可以想象一系列严重的副作用，尽管不太可能 它们都会在临床实践中发挥作用，量化或反驳这些副作用对于临床至关重要。 现有的试验尚未回答这些问题。 问题，并且不太可能在不久的将来解决这些问题，由此产生的不确定性导致两者都过度。 对高效 IMD 的限制性但也是积极的处方，该提案旨在解决这一明显问题 知识差距。 我们提出利用现有数据源的基于人群的前瞻性药物安全监测系统 通过高级因果推理缩短获得见解的时间并提供高有效性的结果 纵向医疗保健数据库的分析覆盖了超过 7800 万美国人。 并包括商业保险和医疗补助受益人将提供新的和迫切需要的安全见解。 反映临床实践，包括通常被排除在随机对照试验之外的人群，如儿童、妇女 育龄人群、复杂疾病患者、少数民族人群以及已有危险因素的患者。 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 我们使用因果推理方法，在试点数据中证明了较高的有效性。 并用新颖的数据挖掘方法对其进行补充，以识别未预料到的事件。 具有最高的透明度和可重复性来支持临床决策。 在临床实践中优化使用 IMD 将导致更有针对性的处方并使大量患者群体受益， 包括随机对照试验中代表性不足的人群：儿童、老年人、孕妇、少数族裔、 患有既往感染、癌症、静脉血栓栓塞等疾病的患者。 该项目具有高度创新性，因为它将产生关于安全和有针对性的直接适用的临床见解。 利用现有的索赔数据使用新型免疫调节药物（IMD）治疗特应性皮炎。 它建立在因果推理的新颖方法的基础上，以减少现实中出现的偏见 通过拟议的前瞻性加速证据生成。 监测系统结合我们在药物流行病学分析方面的记录，这项研究将 有效地弥补了许多代表性不足和高风险患者最佳 IMD 使用的知识差距。