2021
DOI: 10.3390/curroncol28050290
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Current Overview of Treatment for Metastatic Bone Disease

Abstract: The number of patients with bone metastasis increases as medical management and surgery improve the overall survival of patients with cancer. Bone metastasis can cause skeletal complications, including bone pain, pathological fractures, spinal cord or nerve root compression, and hypercalcemia. Before initiation of treatment for bone metastasis, it is important to exclude primary bone malignancy, which would require a completely different therapeutic approach. It is essential to select surgical methods consider… Show more

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Cited by 84 publications
(74 citation statements)
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References 192 publications
(303 reference statements)
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“…The management of bone metastases and haematological malignancy around the acetabulum remains a challenge. While some lesions can be managed nonoperatively, 14 larger, lytic, and symptomatic deposits that affect the structural integrity of the acetabulum merit surgery to alleviate pain, prevent fracture, and permit immediate weightbearing.…”
Section: Discussionmentioning
confidence: 99%
“…The management of bone metastases and haematological malignancy around the acetabulum remains a challenge. While some lesions can be managed nonoperatively, 14 larger, lytic, and symptomatic deposits that affect the structural integrity of the acetabulum merit surgery to alleviate pain, prevent fracture, and permit immediate weightbearing.…”
Section: Discussionmentioning
confidence: 99%
“…Prostate cancer often presents with BM, which are typically osteoblastic [ 105 ]. The process behind the development of osteoblastic metastases is still largely unknown but it seems to be related to the tumor production of osteoblastic factors, such as ET-1, growth differentiation factor 15, and bone morphogenic proteins [ 106 ].…”
Section: The Management Of Appendicular Impending and Pathologic Frac...mentioning
confidence: 99%
“…For example, PATHFx is a tool that utilizes patient specific data to generate survival probabilities at varying time points and has been validated in various populations internationally [27]. Other models have attempted to predict survival more accurately using sophisticated machine learning technology [28]. For example, Thio et al have developed a machine learning model which incorporates histology, metastases, previous therapy and a host of patient and laboratory factors.…”
Section: Prognosismentioning
confidence: 99%