Page 53 - Predicting survival in patients with spinal bone metastasesL

INTRODUCTION
Metastases to the spinal column are a frequently observed complication of end stage malignant disease. Dependent on their extent and localization, they cause a variety of clinical symptoms ranging from pain to neurological deficits and even paraplegia. These spinal bone metastases (SBM) most commonly arise from the posterior part of the vertebral body. When they extend into the epidural space and compress the spinal cord, the clinical entity is called malignant epidural spinal cord compression (MESCC)1.
Due to improvements in systemic treatment options for the primary tumor, overall survival times in patients suffering from metastatic disease are on the rise. Most likely, this will result in a prolonged palliative phase in which the incidence of patients presenting with symptomatic SBM will increase. It has been well established that treatment with radiotherapy and/or surgery can be beneficial to patients presenting with pain, neurological deficit or both2-6. However, the most optimal treatment algorithm for individual patients is not optimized yet. In practice, the treating physician will match extent and type of treatment not only to a patient’s clinical presentation, but also to the expected survival time, thus balancing the increase in morbidity and mortality associated with more extensive treatment to the expected gain in quality of life.
Models to aid in therapy selection based on expected survival time have been developed by Tomita7, Tokuhashi8,9, Bauer10,11 and our own group4. These models encompass prognostic factors such as primary tumor type, amount and location of spinal metastases, presence of visceral, brain and extraspinal bone metastases, functional status and neurological status. However, clinical applicability seems limited due to over- or under treatment and especially when predicting short survival the existing models fall short12,13.
The goal of this study was to identify risk factors associated with survival and to develop a validated survival risk stratification model for patients with symptomatic SBM.
IV
PREDICTIVE MODEL
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