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Review
. 2025 Apr 11;17(8):1296.
doi: 10.3390/cancers17081296.

Current Concepts in the Management and Treatment of Spinal Metastases-A Systematic Literature Review

Affiliations
Review

Current Concepts in the Management and Treatment of Spinal Metastases-A Systematic Literature Review

Adriana Palacio Giraldo et al. Cancers (Basel). .

Abstract

Background: The advent of novel cancer therapies has significantly improved both life expectancy and quality of life for cancer patients. However, this has also led to an increased incidence of metastases, particularly spinal metastases, which pose a significant clinical challenge due to their potential to compromise spinal stability, mobility and neurological function.

Objective: The aim of this study is to identify current symptom scores, determine the diagnosis, evaluate treatment modalities, and review prognostic scores and management algorithms for spinal metastases to aid in therapeutic decision making.

Methods: A systematic literature review was conducted in PubMed focusing on available full-text review articles published in English between 1 January 2012 and 1 July 2022. The search terms were "spinal metastasis OR spinal metastases OR spine metastasis OR spine metastases AND treatment OR management".

Results: Several treatment algorithms, including NOMS (neurology, oncology, mechanical stability, and systemic disease) and LMNOP (localization, mechanical instability, neurology, oncology), have been proposed to guide clinical decision making. However, the development of prognostic scores that incorporate the impact of newer treatment modalities remains an important area of research.

Conclusions: Effective management of spinal metastases requires a multidisciplinary approach, with emphasis on early diagnosis. Treatment decisions are individualized. Further research is essential to refine treatment strategies and improve patient outcomes.

Keywords: management algorithm; metastatic spinal disease; spinal metastasis; treatment options.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
PRISMA flowchart of literature search and analysis [19].
Figure 2
Figure 2
Proposed algorithm system for the evaluation of the KPS. (In this traffic light model, green indicates no symptoms. As the patient's condition worsens, the color shifts through a spectrum until it reaches black, which indicates death) [39].
Figure 3
Figure 3
NOMS decision framework divided into: (a) low-grade ESCC; (b) high-grade ESCC [14,16,21,32]. * Given that surgical separation is not a viable option and the high complication rate associated with SBRT alone in high-grade ESCC, cEBRT is recommended as the initial treatment, with SBRT reserved for cases without improvement [21,32].

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