Long-term effectiveness of BPH/LUTS pharmacological therapies and using machine learning based predictive analytics to tailor treatment

BPH/LUTS 药物治疗的长期有效性，并使用基于机器学习的预测分析来定制治疗

• 批准号: 10618734
• 负责人: Marvin Epolian Langston
• 金额: $ 15.31万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-04 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10618734
• 关键词: 5 Alpha-Reductase Inhibitor; Acute; Address; Adrenergic Antagonists; Adrenergic alpha-Antagonists; Age; Alternative Therapies; Anti-Cholinergics; Asian Americans; Benign; Benign Prostatic Hypertrophy; Big Data; Caring; Cessation of life; Clinical; Combined Modality Therapy; Complex; Coupled; Data; Data Set; Data Sources; Diagnosis; Disease Progression; Effectiveness; Electronic Health Record; Epidemiology; Etiology; Exhibits; Funding; Future; Goals; Gold; Grant; Health; Healthcare; High Prevalence; Hispanic; Histologic; Hyperplasia; Incidence; Investigation; K-Series Research Career Programs; Laboratories; Machine Learning; Malignant neoplasm of prostate; Methodology; Methods; Modality; Muscle Tonus; Muscle relaxation phase; Newly Diagnosed; Nodule; Observational Study; Operative Surgical Procedures; Outcome; Overactive Bladder; Patients; Pharmacological Treatment; Pharmacology; Phenotype; Population; Predictive Analytics; Predictive Factor; Prevalence; Progressive Disease; Prostate; Prostatic Diseases; Quality of life; Race; Reporting; Research; Research Design; Risk; Scientist; Secondary to; Smooth Muscle; Source; Surveys; Symptoms; Time; Training; Translating; Treatment Effectiveness; Treatment Failure; Urinary Retention; Urology; Validation; Work; associated symptom; base; black men; clinical phenotype; cohort; comparative effectiveness; compare effectiveness; cost; effectiveness evaluation; electronic data; ethnic difference; experience; high risk; improved; individualized medicine; inhibitor; innovation; lower urinary tract symptoms; member; men; novel; older men; personalized approach; personalized medicine; phosphoric diester hydrolase; predictive modeling; prevent; prostatitis; racial and ethnic; risk prediction model; skills; symptom management; tool; translational scientist; treatment strategy; urologic

PROJECT SUMMARY/ABSTRACT This Career Development Award will support Dr. Marvin Langston in his transition to independence as a translational researcher. His long-term research goals include understanding the etiology and outcomes of urologic conditions with an emphasis on prostate diseases (prostate cancer, prostatitis, and lower urinary tract symptoms secondary to benign prostatic hyperplasia (BPH/LUTS)); developing and validating clinical tools to improve and personalize treatment options; and implementing these tools in “real world” clinical settings. BPH/LUTS is an extremely common set of conditions among older men and can be considered a progressive disease, mainly characterized by deteriorating LUTS over time which causes considerable bother and decreased quality of life, urinary retention, and death in rare cases. Conventional pharmacological treatment strategies fail in preventing long-term clinical outcomes in about 30% of treated patients. Despite a high volume of pharmacological research, there have been very limited advances in therapy for BPH/LUTS in recent years. Therefore, innovative and well-designed studies are needed to understand the long-term comparative effectiveness of contemporary BPH/LUTS pharmacological therapies while leveraging the clinical covariates that can be captured in “big data” sources such as the electronic health record. To address these limitations, In Aim 1, Dr. Langston will evaluate the long-term comparative effectiveness of BPH/LUTS pharmacological therapies in an observational study drawn from the Kaiser Permanente membership population, a fully integrated healthcare network. If well designed studies demonstrate that contemporary pharmacological approaches are not more effective at preventing long-term BPH/LUTS progression than conventional approaches alone, then personalized treatment options may ultimately provide the best strategy for reducing long-term BPH/LUTS progression. Therefore, in Aim 2 Dr. Langston will develop and validate predictive models using demographic, clinical, and laboratory data available at the time of BPH/LUTS diagnosis to identify patients at increased risk of long-term BPH/LUTS clinical outcomes (acute urinary retention and BPH surgery) using machine learning based predictive analytics. As the volume, availability, and access to electronic data increases, so does the need for scientists with the content and methodologic expertise to correctly use and translate these data into improved urology care. This K01 provides the training for Dr. Langston to meet this challenge as a translational researcher and compete successfully for future R01 funding.

项目摘要/摘要 该职业发展奖将支持Marvin Langston博士过渡到独立 翻译的研究人员。他的长期研究目标包括了解病因和结果 泌尿科状况，重点是前列腺疾病（前列腺癌，前列腺炎和较低的尿路 继发于良性前列腺增生（BPH/LUTS）的症状）；开发和验证临床工具 改善和个性化治疗选择；并在“现实世界”临床环境中实施这些工具。 BPH/LUTS是老年男性中极为普遍的条件，可以被视为 进行性疾病，主要是随着时间的流逝而恶化的特征 在极少数情况下，改善了生活质量，保留率和死亡。常规药品 治疗策略无法预防约30％的治疗患者的长期临床结局。尽管有 大量的药物研究，BPH/LUTS的治疗进展非常有限 近年来。因此，需要创新且精心设计的研究以了解长期 当代BPH/LUTS药物疗法的比较有效性在利用临床的同时 可以在“大数据”来源（例如电子健康记录）中捕获的协变量。 为了解决这些限制，在AIM 1中，Langston博士将评估长期比较 BPH/LUTS药理学疗法的有效性在从Kaiser绘制的检查研究中 永久会员人口，一个完全集成的医疗网络。如果设计精良 证明当代药物方法在预防长期方面不太有效 BPH/LUTS的进展比单独的传统方法，那么个性化的治疗选择可能 最终提供了减少长期BPH/LUTS进展的最佳策略。因此，在AIM 2 Dr. Langston将使用可用的人口统计学，临床和实验室数据来开发和验证预测模型 在BPH/LUTS诊断时，识别长期BPH/LUTS临床风险增加的患者 使用基于机器学习的预测分析的结果（急性尿位率和BPH手术）。 随着数量，可用性和对电子数据的访问的增加，对科学家的需求也会增加 内容和方法论专业知识可正确使用并将这些数据转化为改进的泌尿科护理。 该K01为Langston博士提供了培训，以应对这一挑战，作为翻译的研究人员和 成功竞争未来的R01资金。