Fracture Risk of Long Bone Metastases: A Review of Current and New Decision-Making Tools for Prophylactic Surgery

Abstract

Long bone pathological fractures very much reflect bone metastases morbidity in many types of cancer. Bearing in mind that they not only compromise patient function but also survival, identifying impending fractures before the actual event is one of the main concerns for tumor boards. Indeed, timely prophylactic surgery has been demonstrated to increase patient quality of life as well as survival. However, early surgery for long bone metastases remains controversial as the current fracture risk assessment tools lack accuracy. This review first focuses on the gold standard Mirels rating system. It then explores other unique imaging thresholds such as axial or circumferential cortical involvement and the merits of nuclear imaging tools. To overcome the lack of specificity, other fracture prediction strategies have focused on biomechanical models based on quantitative computed tomography (CT): computed tomography rigidity analysis (CT-RA) and finite element analysis (CT-FEA). Despite their higher specificities in impending fracture assessment, their limited availability, along with a need for standardization, have limited their use in everyday practice. Currently, the prediction of long bone pathologic fractures is a multifactorial process. In this regard, machine learning could potentially be of value by taking into account clinical survival prediction as well as clinical and improved CT-RA/FEA data.

The low and disproportionate utilization of antiresorptive therapy in patients with osseous metastasis

“…Mosher et al [16] assessed outcomes in patients with pathologic fractures and found patients who sustained pathologic fractures were younger, female, had non-commercial insurance, increased blood transfusions, length of stay/hospitalization, total cost of care, and in-hospital mortality compared to patients who underwent prophylactic fixation for osseous metastases, similar to our results. Contrary to our study, literature has identified patients with breast cancer to be at increased risk of pathologic fracture, likely due to a prolonged survival time compared to other tumors [17] . We hypothesize our study did not observe an increased risk due to the increased proportion of breast cancer patients receiving antiresorptive therapy and possibly duration of follow-up.…”

Evaluation of Bone and Soft Tissue Tumors of the Shoulder Girdle

“…Bone metastases lead to pain, hypercalcemia, and complications such as medullar compression and pathological fracture. Long bone pathological fractures are the most severe complications which have high mortality rates [ 22 ]. According to a study by Saad et al, Pathological fractures have been linked to significantly lower survival rates for breast cancer, multiple myeloma, and prostate cancer [ 23 ].…”

A Multiparametric MRI-Based Radiomics Nomogram for Preoperative Prediction of Survival Stratification in Glioblastoma Patients With Standard Treatment

“…For the two cohorts, the discriminative ability of the radiomics nomogram was quantitatively measured using AUC, and the calibration curves were plotted based on observed probabilities and the nomogram-estimated probabilities ( 15 ). To evaluate the clinical utility of the radiomics nomogram, the decision curve analysis (DCA) was executed by calculating the net benefits at different threshold probabilities in the combined training and validation cohorts ( 16 ). The flowchart of this research is shown in Figure 1 .…”