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

项目摘要/摘要 我们试图验证一种定量方法来预测癌症病理性椎体骨折(PVF)的风险。 在这些并发症发生前接受放射治疗的转移性脊柱疾病的患者。 椎骨是骨转移最常见的部位。放射治疗的目的是缓解疼痛和 降低门静脉瘘的风险。然而，PVF是一种常见的并发症，高达39%的患者在6岁以下 放疗后几个月。估计骨折风险的临床指南仍然具有主观性，而且 特异性和敏感性。改进的PVF风险预测将有助于选择是否、如何以及何时 在PVF发生前进行干预。这种个体化预测在临床实践中是不可行的。 作为我们之前NIH拨款的一部分，我们开发了一种基于计算机断层扫描(CT)的结构 分析(CT-SAP)，以成功地预测失败的人脊柱溶解缺陷。基于这些 这项观察性前瞻性研究的目标有三个：1)测试 CT-SAP的性能(提供骨结构和钙含量的快照)和骨转换 预测脊柱骨折基线风险的标记物(提供疾病轨迹的指示) 一组接受放射治疗的脊柱骨转移患者。为此，我们将收购 标准的临床CT和血清样本按患者的放射治疗计划进行。从CT中，我们将推导出 椎体强度(CT-SAP)和椎体负荷的个体化估计，以计算负荷/ 治疗和未治疗椎体的强度比，并测量骨骼标志物的值 从血清样本中吸收和形成。我们将测试脊椎的独立关联性 与治疗后6个月内观察到的椎体骨折的载荷/强度比和标志值进行比较。 这一新的数据将提供关于辐射和转移性疾病对基线和 在这一患者队列中，脊柱骨折的短期风险。2)建立脊柱的性能 不稳定肿瘤评分(SINS)预测患者术后6个月内椎体骨折的风险 治疗并测试是否添加负荷/强度比(CT-SAP)和骨转换风险模型， 独立和组合，提高了模型的性能。这将建立一个新的范例 该患者队列中骨折基线风险的个体化预测。3)对建立的模型进行测试 通过获取和分析在3个月内预测PVF演变风险的性能 作为标准临床护理的一部分，在治疗后3、6和9个月收集CT扫描和血清样本。 这一时间段为评估低风险与高风险PVF的影响提供了临床上有意义的指南。 为这些预期寿命短的虚弱人口的健康和生活质量而努力。成功完成这项工作 该项目将解决我们对这些患者进行个性化评估和管理的能力方面的一个严重差距。

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.