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Improved patient selection by stratified surgical intervention: Aarhus Spinal Metastases Algorithm.
Miao Wang1, Cody E Bünger1, Haisheng Li1
1Department of Orthopaedic E, Aarhus University Hospital (NBG), Noerrebrogade 44, Bldg 1A, DK-8000 Aarhus C, Denmark.
Summary
The Aarhus Spinal Metastases Algorithm (ASMA) aids surgeons in selecting optimal surgical treatments for spinal metastases by considering life expectancy and tumor classification. This algorithm helps evaluate patient risks and improve surgical outcomes.
Area of Science:
- Spine Surgery
- Oncology
- Clinical Decision Support
Background:
- Spinal metastases present a significant challenge for surgeons due to the lack of a gold standard treatment.
- The Aarhus Spinal Metastases Algorithm (ASMA) was developed to guide surgical intervention selection.
Purpose of the Study:
- To evaluate the clinical outcomes of surgical interventions stratified by the ASMA.
- The ASMA combines life expectancy and anatomical classification for informed surgical decision-making.
Main Methods:
- Retrospective analysis of a prospective database of 515 spinal metastatic patients (1992-2012).
- Patients were classified into five surgical groups using the revised Tokuhashi score (TS) and Tomita anatomical classification (TC).
- Survival time and neurological function (Frankel score) were assessed pre- and post-operatively.
Main Results:
- Overall median survival was 6.8 months.
- Median survival varied significantly across ASMA groups, ranging from 2.1 to 36.0 months.
- Postoperative neurological function was maintained or improved in 92.3% of patients, with a 30-day mortality rate of 7.5%.
Conclusions:
- The ASMA provides a tool to help surgeons evaluate spinal metastases patients.
- It aids in selecting optimal surgical options and avoiding life-threatening risks by considering life expectancy and anatomical classification.
- The algorithm assists in discriminating surgical risks for improved patient management.
