Comparative Risks and Benefits of Pharmacological Therapies for Older Patients with Inflammatory Bowel Diseases

老年炎症性肠病患者药物治疗的风险和益处比较

• 批准号: 9919547
• 负责人: Siddharth Singh
• 金额: $ 20.4万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9919547
• 关键词: Adrenal Cortex Hormones; Adult; Affect; Algorithms; Benefits and Risks; Biological; Biological Response Modifier Therapy; Cardiovascular system; Cessation of life; Clinical Data; Clinical Informatics; Combined Modality Therapy; Comparative Effectiveness Research; Computerized Medical Record; Data; Data Sources; Databases; Disease; Effectiveness; Elderly; Environment; Fracture; Funding; Future; Goals; Healthcare; Hospitalization; Hospitals; Immunomodulators; Incidence; Infection; Inflammatory Bowel Diseases; Informatics; Infrastructure; Intestines; K-Series Research Career Programs; Link; Malignant Neoplasms; Medicare; Medicare claim; Mentors; Mentorship; Methods; Modeling; Observational Study; Operative Surgical Procedures; Outcome; Patient risk; Patients; Pattern; Pharmacology; Phenotype; Predictive Analytics; Prevalence; Reporting; Research; Research Methodology; Risk; Risk Estimate; Safety; Sample Size; Severity of illness; Site; Steroids; Techniques; Testing; Therapeutic; Therapeutic immunosuppression; Thromboembolism; Treatment Effectiveness; base; burden of illness; career; clinical practice; cohort; comorbidity; comparative; comparative effectiveness; compare effectiveness; cost; disorder risk; effectiveness research; evidence base; experience; follow-up; health management; high risk; individualized medicine; innovation; machine learning algorithm; mortality; mortality risk; multiple chronic conditions; novel; older patient; optimal treatments; patient oriented; personalized medicine; population health; privacy preservation; risk minimization; skills; treatment risk; treatment strategy; young adult

PROJECT SUMMARY/ABSTRACT The prevalence of inflammatory bowel diseases (IBD) in older adults (≥65y) is rising, and there is limited evidence-based guidance on treating these older adults. In older patients with multi-morbidity, treatment decisions should factor in not only risk of disease complications, but also treatment complications and non-IBD, extra-intestinal complications. Hence, to inform optimal treatment approach, a comprehensive assessment of comparative effects of different therapies on all of these outcomes is warranted. Existing single-center observational studies are limited by small sample size, and missing data due to fragmented health care, whereas administrative claims-based studies are limited by lack of detailed clinical data; these limitations can be overcome by linking the two data sources. In this patient-oriented mentored career development award proposal, Dr. Siddharth Singh proposes to: (Aim #1.1) characterize disease burden and treatment patterns, (Aim #1.2) assess and predict risks of death, disease, treatment and extra-intestinal complications using machine-learning algorithms and (Aim #2.1) compare overall effectiveness and (Aim #2.2) safety of different treatment strategies in older patients with IBD. This will be studied using a highly innovative informatics-based approach in a multi-site, electronic medical record (EMR)-based cohort of older patients with IBD, linked to their corresponding Medicare claims. The EMR-based cohort will facilitate phenotyping and disease severity assessment, and linkage to Medicare claims will augment exposure and outcome ascertainment, overcoming challenges of fragmentation of healthcare and short follow-up. The central hypothesis is that, that older adults have systematically different risk profiles than younger adults, and using biologic monotherapy is a safer and more effective approach to treating IBD, as compared to using long-term corticosteroids alone, non-biologic immunomodulator monotherapy, and combination therapy of biologics and immunomodulators. The access to the advanced infrastructure of pSCANNER (Patient-centered Scalable National Network for Effectiveness Research), one of 13 PCORI-funded Clinical Data Research Networks, and entire Medicare database, in a highly supportive and conducive environment at UCSD, with cross-disciplinary mentorship by a collaborative and experienced team of mentors and advisors from diverse backgrounds (clinical informatics, comparative effectiveness research, IBD therapeutics) is a key strength of this application. Besides directly informing clinical practice on treatment approaches in older patients with IBD, this proposal will enhance the career of the candidate by providing unique skills in applied clinical informatics, privacy-preserving record linkage techniques, predictive analytics, and comparative effectiveness research, and create a multi-institutional, EMR- based cohort of well-characterized IBD patients, linked with Medicare claims. This will ultimately contribute to the candidate's long-term goal of establishing an independent IBD research career focusing on comparative effectiveness research and population health management using novel informatics-based approaches.

项目摘要/摘要 炎症性肠病在老年人中的患病率(≥65Y)正在上升，而且有限 治疗这些老年人的循证指导。在高龄多发病患者中，治疗 决策不仅应考虑疾病并发症的风险，还应考虑治疗并发症和非IBD， 肠外并发症。因此，为了提供最佳治疗方法，全面评估 比较不同疗法对所有这些结果的影响是有必要的。现有单中心 观察性研究受到样本量小，以及由于医疗保健支离破碎而缺少数据的限制， 尽管基于行政索赔的研究因缺乏详细的临床数据而受到限制，但这些限制可能 通过链接这两个数据源来克服。在这个以病人为导向的导师职业发展奖中 在提案中，Siddharth Singh博士提议：(目标1.1)描述疾病负担和治疗模式， (目标#1.2)评估和预测死亡、疾病、治疗和肠道外并发症的风险 机器学习算法和(目标#2.1)比较不同算法的总体有效性和(目标#2.2)安全性 老年IBD患者的治疗策略。这将使用高度创新的信息学基础来研究 在多地点、基于电子病历(EMR)的老年IBD患者队列中的方法，与 他们相应的医疗保险索赔。基于EMR的队列将有助于表型和疾病严重程度 评估和与医疗保险索赔的联系将增加风险敞口和结果确定，克服 医疗保健支离破碎和短期随访的挑战。中心假设是，老年人 与年轻人有系统地不同的风险特征，使用生物单一疗法是更安全和 与单独使用长期非生物皮质类固醇相比，更有效的治疗IBD的方法 免疫调节剂单一治疗，以及生物制剂和免疫调节剂的联合治疗。访问 PSCANNER(以患者为中心的可扩展高效国家网络)的先进基础设施 研究)，13个PCORI资助的临床数据研究网络之一，以及整个医疗保险数据库，在一个 加州大学圣地亚哥分校高度支持和有利的环境，由协作性的跨学科指导 由来自不同背景的经验丰富的导师和顾问组成的团队(临床信息学、比较 有效性研究，IBD疗法)是这一应用的关键优势。除了直接告知临床 关于老年IBD患者治疗方法的实践，这项建议将促进 应聘者通过提供应用临床信息学、隐私保护记录链接方面的独特技能 技术、预测分析和比较有效性研究，并创建一个多机构的EMR- 以特征良好的IBD患者为基础的队列，与医疗保险索赔有关。这最终将有助于 候选人的长期目标是建立一个独立的IBD研究生涯，专注于比较 使用新的基于信息学的方法进行有效性研究和人口健康管理。