Predicting Fracture Risk in Patients Treated with Radiotherapy for Spinal Metastatic Disease

预测脊柱转移性疾病放射治疗患者的骨折风险

• 批准号: 10655309
• 负责人: RON N ALKALAY
• 金额: $ 68.11万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10655309
• 关键词: Address; Adverse event; Aftercare; Blood; Bone Resorption; Bone structure; Calcium; Cancer Patient; Clinical; Clinical Protocols; Complication; Data; Defect; Development; Disease; Evaluation; Failure; Goals; Grant; Guidelines; Health; Human; Immobilization; Individual; Information Management; Life Expectancy; Lytic; Malignant Neoplasms; Measurement; Measures; Mechanics; Metastatic Neoplasm to the Bone; Methods; Modeling; Morbidity - disease rate; Musculoskeletal Development; Neoplasm Metastasis; Neurologic Deficit; Osteogenesis; Pain; Pathologic; Patient risk; Patients; Performance; Population; Positioning Attribute; Predictive Value; Prospective Studies; Prospective cohort; Protocols documentation; Quality of life; ROC Curve; Radiation; Radiation therapy; Risk; Risk Marker; Risk Reduction; Sampling; Scanning; Sensitivity and Specificity; Serum; Site; Spinal; Spinal Diseases; Spinal Fractures; Systemic Therapy; Testing; Time; United States National Institutes of Health; Vertebral Bone; Vertebral column; Work; X-Ray Computed Tomography; bone loss; bone turnover; clinical care; clinical practice; clinical predictive model; clinically significant; cohort; cost; follow-up; fracture risk; high risk; improved; neoplastic; neural; novel; palliate; palliative; performance tests; personalized predictions; personalized risk prediction; predictive marker; predictive modeling; prognostic value; radiation effect; risk prediction; risk prediction model; skeletal; spine bone structure; tumor; tumor progression

Project Summary/Abstract We seek to validate a quantitative method to predict the risk of pathologic vertebral fracture (PVF) in cancer patients treated with radiotherapy for metastatic spine disease before the onset of these complications. Vertebral bone is the most frequent site of skeletal metastasis. Radiation therapy aims to palliate pain and reduce the risk of PVF. However, PVF are a common complication afflicting up to 39% of patients within 6 months after-radiotherapy. Clinical guidelines for estimating fracture risk remain subjective and suffer from low specificity and sensitivity. Improved prediction of PVF risk would facilitate selection of whether, how, and when to intervene prior to the occurrence of PVF. Such individualized prediction is not available in clinical practice. As part of our previous NIH grant, we have developed a computed tomography (CT) based structural analysis (CT-SAP) to successfully predict the failure of human spines with lytic defects. Based on these accomplishments, the objectives of this observational prospective study are threefold: 1) To test the performance of CT-SAP (providing a snapshot of bone structure and calcium content) and bone turnover markers (providing an indication of disease trajectory) for predicting the baseline risk of vertebral fractures in a cohort of patients treated with radiotherapy for spinal bone metastases. For this purpose, we will acquire the standard clinical CT and serum sample at the patient's radiotherapy planning. From the CT, we will derive individualized estimates of vertebral strength (CT-SAP) and vertebral loading to compute the loading / strength ratio for both treated and untreated vertebrae, and measure the value for markers for bone resorption and formation from the serum sample. We will test the independent association of the vertebral loading / strength ratio and marker value with the observed vertebral fractures within 6 months after treatment. This novel data will provide information on the effect of radiation and metastatic disease on the baseline and short term risk of vertebral fracture in this patient cohort. 2) To establish the performance of the spinal instability neoplastic score (SINS) for predicting the patient's risk of vertebral fracture within 6 months after treatment and test whether adding the load / strength ratio (CT-SAP) and bone turnover risk models, independently and combined, improves the model's performance. This will establish a new paradigm for individualized prediction of baseline risk for fracture in this patient cohort. 3) To test the established model performance for predicting the evolving risk of PVF within a 3 month interval by acquiring and analyzing the CT scans and serum samples collected at 3, 6, and 9 months after treatment as part of standard clinical care. This time period provides clinically meaningful guidelines for assessing the impact of a low vs. high risk of PVF to the health and quality of life of this infirm population with short life expectancy. Successful completion of this project will address a critical gap in our ability to individualize evaluation and management of these patients.

项目摘要/摘要 我们寻求验证一种定量方法，以预测癌症病理椎骨骨折（PVF）的风险 在这些并发症发作之前，接受了放疗的转移性脊柱疾病的患者。 椎骨是骨骼转移最常见的部位。放射疗法旨在减轻疼痛和 降低PVF的风险。但是，PVF是一种常见的并发症，折磨了6％的患者中的39％ 放射治疗后几个月。估计骨折风险的临床指南仍然是主观的，并且患有低 特异性和灵敏度。改善PVF风险的预测将有助于选择是否，方式和何时 在发生PVF之前进行干预。这种个性化的预测在临床实践中不可用。 作为我们以前的NIH赠款的一部分，我们开发了基于计算机断层扫描（CT）的结构 分析（CT-SAP）成功预测了裂解缺陷的人棘失败。基于这些 成就，这项观察性前瞻性研究的目标是三个方面：1）测试 CT-SAP的性能（提供骨结构和钙含量的快照）和骨转换 标记（提供疾病轨迹的指示），以预测椎骨骨折的基线风险 接受放射疗法治疗脊柱骨转移的患者队列。为此，我们将获得 患者放射疗法计划中的标准临床CT和血清样品。从CT，我们将得出 个性化椎骨强度（CT-SAP）和椎骨负荷的个性化估计值，以计算负载 / 治疗和未处理椎骨的强度比，并测量骨骼标记的值 血清样品的吸收和形成。我们将测试椎骨的独立关联 在治疗后6个月内，载荷 /强度比和标记值与观察到的椎骨骨折。 这个新的数据将提供有关辐射和转移性疾病对基线和基线影响的影响的信息 该患者队列中椎骨骨折的短期风险。 2）建立脊柱的性能 不稳定性肿瘤评分（SINS），用于预测患者在6个月内的椎骨骨折风险 处理和测试是否增加负载 /强度比（CT-SAP）和骨转换风险模型， 独立并结合起来，改善了模型的性能。这将建立一个新的范式 该患者队列中骨折基线风险的个性化预测。 3）测试已建立的模型 通过获取和分析，可以在3个月内预测PVF的不断发展的风险的绩效 作为标准临床护理的一部分，在治疗后3、6和9个月收集的CT扫描和血清样品。 这个时期提供了评估低PVF风险和高风险的影响的临床有意义的指南 对于预期寿命较短的虚弱人群的健康和生活质量。成功完成 项目将解决我们个性化这些患者评估和管理的能力的关键差距。