University Musculoskeletal Oncology Unit, Division of Orthopaedic Surgery, Department of Surgery, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada.
Cancer. 2010 Mar 15;116(6):1553-9. doi: 10.1002/cncr.24949.
The objective of the current study was to formulate a scoring system to enable decision making for prophylactic stabilization of the femur after surgical resection of a soft tissue sarcoma (STS) of the thigh.
A logistic regression model was developed using patient variables collected from a prospectively collected database. The study group included 22 patients who developed a radiation-related pathological fracture of the femur after surgery and radiotherapy for an STS of the thigh. The control group of 79 patients received similar treatment but did not sustain a fracture. No patients received chemotherapy. The mean follow-up was 8.6 years. The variables examined were age, gender, tumor size, radiation dose (low [50 grays (Gy)] vs high [> or = 60 Gy]), extent of periosteal stripping (<10 cm, 10-20 cm, and >20 cm), and thigh compartment involvement (posterior, adductor, anterior or other [ie, abductors and groin]).
On the basis of an optimal regression model, the ability to predict radiation-associated fracture risk was 91% sensitive and 81% specific. The area under the receiver operating characteristic curve was 0.9, which supports this model as a very accurate predictor of fracture risk.
Radiation-related fractures of the femur after combined surgery and radiotherapy for STS are uncommon, but are difficult to manage and their nonunion rate is extremely high. The results of the current study suggest that it is possible to predict radiation-associated pathological fracture risk using patient and treatment variables with high sensitivity and specificity. This would allow for the identification of high-risk patients and treatment with either close follow-up or prophylactic intramedullary nail stabilization. The presentation of this model as a nomogram will facilitate its clinical use.
本研究的目的是制定一个评分系统，以便在大腿软组织肉瘤（STS）手术后进行放射治疗时，对股骨进行预防性稳定。
使用从前瞻性收集的数据库中收集的患者变量，开发了一个逻辑回归模型。研究组包括 22 名患者，他们在接受大腿 STS 手术后接受放射治疗，发生了与放射相关的股骨病理性骨折。对照组 79 名患者接受了类似的治疗，但没有发生骨折。没有患者接受化疗。平均随访 8.6 年。检查的变量包括年龄、性别、肿瘤大小、放射剂量（低[50 戈瑞（Gy）]与高[≥60 Gy]）、骨膜剥离程度（<10 cm、10-20 cm 和>20 cm）和大腿间隔受累（后、内收肌、前或其他[即外展肌和腹股沟]）。
基于最佳回归模型，预测放射相关骨折风险的能力为 91%敏感和 81%特异。接受者操作特征曲线下面积为 0.9，支持该模型作为骨折风险的非常准确预测器。
STS 联合手术和放射治疗后发生的与放射相关的股骨骨折并不常见，但难以处理，其不愈合率极高。本研究的结果表明，使用患者和治疗变量可以以高灵敏度和特异性预测放射相关的病理性骨折风险。这将允许识别高风险患者，并通过密切随访或预防性髓内钉稳定进行治疗。该模型作为诺模图呈现，将便于其临床应用。
