Penetrating the “Black box”: Prediction of early Bronchiolitis obliterans in Pediatric Hematopoietic Stem Cell Transplant Recipients

穿透“黑匣子”：预测儿科造血干细胞移植受者早期闭塞性细支气管炎

• 批准号: 10293181
• 负责人: Kasiani Myers
• 金额: $ 64.96万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10293181
• 关键词: Address; Adult; Algorithms; Behavior; Biological Markers; Blinded; Blood; Bronchiolitis Obliterans; Caring; Child; Childhood; Climacteric; Clinic; Clinical; Clinical Data; Clinical Trials; Cystic Fibrosis; Data; Data Analyses; Detection; Development; Diagnosis; Diagnostic; Disease; Early Diagnosis; Early Intervention; Enzyme-Linked Immunosorbent Assay; Evaluation; Evolution; Fibrosis; Future; Generations; Goals; Health Care Costs; Hematopoietic Stem Cell Transplantation; Hospitalization; Immune; Immune response; Incidence; Individual; Inflammation; Inflammatory; Intervention; Knowledge; Lung; Lung diseases; Mass Spectrum Analysis; Medical; Monitor; Morbidity - disease rate; Obstructive Lung Diseases; Outcome; Pathway interactions; Patients; Performance; Plasma; Plasma Proteins; Population; Prevention; Prevention trial; Probability; Procedures; Prospective Studies; Protein Isoforms; Proteomics; Pulmonary Function Test/Forced Expiratory Volume 1; Research; Risk; Sampling; Sensitivity and Specificity; Severity of illness; Spirometry; Statistical Data Interpretation; Supportive care; Syndrome; Techniques; Testing; Therapeutic Intervention; Time; TimeLine; Transplant Recipients; Transplantation; Validation; Work; active method; airway obstruction; biomarker validation; candidate marker; clinical Diagnosis; cohort; cost; exhaustion; graft vs host disease; high risk; improved; individual patient; innovation; longitudinal analysis; mortality; new therapeutic target; novel; novel marker; optimal treatments; patient population; point of care; post-transplant; prediction algorithm; predictive marker; predictive modeling; predictive tools; preventive intervention; prophylactic; prospective; protein biomarkers; pulmonary function; pulmonary function decline; repository; respiratory; risk stratification; screening; tandem mass spectrometry; tool; treatment trial; young adult

Abstract Bronchiolitis obliterans syndrome (BOS) is an obstructive lung disease caused by a combination of inflammation and immune response that is irreversible in its late stage. Children with BOS are typically diagnosed late because they are unable to perform spirometry, and morbidity and mortality are high. The long-term goal of this work is to improve survival and reduce morbidity from BOS by identifying strategies for accurate screening and prediction of BOS in children and young adults after HSCT and using these tools to identify novel drug targets for early intervention or prevention of BOS. The objective of this application is to validate novel predictive plasma protein biomarkers and establish a dynamic prediction model for BOS for early diagnosis, risk stratification and disease trajectory prediction for BOS after HSCT. We will achieve these goals through the following specific aims: 1) Validate longitudinal predictive performance of newly discovered plasma biomarkers of BOS risk in samples from banked and prospective studies by mass spectrometry and ELISA in both pediatric and adult cohorts. 2) Optimize and validate our dynamic prediction algorithm using pulmonary function and clinical data as well as biomarker levels (needed when no spirometry can be obtained) as covariates to project risks of BOS and rapid BOS lung-function decline to inform treatment decisions. There are currently no biomarkers or predictive tools for BOS so this work is entirely novel. The use of a dynamic prediction algorithm in this clinical setting is innovative allowing for the first time the ability to predict and diagnose early lung disease in HSCT subjects prior to the clinical diagnosis of BOS. Identification of BOS risk and stratification of screening and treatment procedures according to risk and predicted disease course would allow us to modify post-transplant care and reduce morbidity and mortality. We will use our data to inform prospective clinical trials of both early active treatment prior to development of early fibrosis and to test novel prophylactic therapies to reduce incidence in high risk individuals. Our studies will provide blood biomarkers that can be used as frequently as necessary without requiring active participation from small and often very sick children. Our preliminary biomarker and HSCT specific algorithm data demonstrate detection of BOS as soon as 2 weeks to 6 months prior to clinical diagnosis of BOS. This work is both significant and vital because improvements in HSCT techniques and supportive care have led to improved survival. Improved survival increases the number of children at risk for late complications of HSCT that are associated with life-changing morbidity and late mortality and there is urgent need to address these issues. This work will advance prediction and early diagnosis of BOS, as well as providing the framework for future prevention and treatment trials.

抽象的 支气管炎闭塞综合征（BOS）是由炎症组合引起的阻塞性肺疾病 和免疫反应在后期是不可逆转的。 BOS的儿童通常被诊断出来 因为他们无法执行肺活量法，因此发病率和死亡率很高。这个长期目标 工作是通过确定准确筛查的策略和 HSCT后儿童和年轻人的BOS预测，并使用这些工具来识别新型药物靶标 用于早期干预或预防BOS。该应用的目的是验证新型预测等离子体 蛋白质生物标志物并建立了BOS的动态预测模型，用于早期诊断，风险分层和 HSCT后BOS的疾病轨迹预测。我们将通过以下具体实现这些目标 目的：1）验证新发现的BOS风险等离子体生物标志物的纵向预测性能 小儿和成人的质谱和ELISA的库存和前瞻性研究的样品 同伙。 2）使用肺功能和临床数据优化和验证我们的动态预测算法 以及生物标志物水平（如果无法获得肺活量测定法），则可以作为BOS和BOS风险的协变量 快速的BOS肺部功能下降以为治疗决定提供了信息。目前没有生物标志物或预测性 BOS的工具，因此这项工作完全是新颖的。在这种临床环境中的动态预测算法的使用是 创新允许首次预测和诊断在HSCT受试者中预测和诊断早期肺部疾病的能力 进行BOS的临床诊断。识别BOS风险和筛查和治疗的分层 根据风险和预测疾病课程的程序将使我们能够修改移植后护理和 降低发病率和死亡率。我们将使用我们的数据来告知两个早期活跃的前瞻性临床试验 在开发早期纤维化之前的治疗和测试新型预防性疗法以降低发生率 高风险个人。我们的研究将提供可以在必要时频繁使用的血液生物标志物 不需要从小且经常病的孩子积极参与。我们的初步生物标志物和 HSCT特异性算法数据显示，在临床前2周到6个月，BOS的检测 BOS诊断。这项工作既重要又至关重要，因为HSCT技术的改进和 支持性护理导致生存改善。提高的生存增加了迟到风险的儿童人数 与改变生命的发病率和晚期死亡相关的HSCT并发症，紧急 需要解决这些问题。这项工作将提高BOS的预测和早期诊断，并提供 未来预防和治疗试验的框架。