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Purpose <p>Accurate survival prediction is paramount for selecting appropriate candidates for minimally invasive surgery (MIS) among patients with spinal metastases. Traditional scoring systems often neglect the host’s systemic inflammatory response. This study aimed to develop a prognostic nomogram integrating the Glasgow Prognostic Score (GPS) and Lymphocyte-to-Monocyte Ratio (LMR) and evaluate its efficacy against the established Katagiri and SORG systems.</p> Methods and materials <p>A retrospective study was conducted on 172 patients who underwent MIS (percutaneous vertebroplasty and/or radiofrequency ablation) for spinal metastases. Patients were divided into training (<i>n</i> = 120) and testing (<i>n</i> = 52) cohorts. Independent prognostic factors were identified using multivariate Cox regression to construct a nomogram. Model performance was evaluated using Area Under the Curve (AUC), calibration plots, Decision Curve Analysis (DCA), Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI).</p> Results <p>Multivariate analysis identified eight independent prognostic factors: clinical profile, surgical modality, systemic therapy, analgesic use, bone metastasis, visceral metastasis, LMR, and GPS. The new nomogram demonstrated excellent discrimination with 12-month AUCs of 0.886 (training) and 0.831 (testing), significantly outperforming the Katagiri (AUC 0.740) and SORG (AUC 0.710) systems (<i>p</i> &lt; 0.001). Calibration plots revealed high agreement between predicted and observed survival. Furthermore, the new model showed significantly improved predictive accuracy over Katagiri (NRI 0.415; IDI 0.227) and SORG (NRI 0.391; IDI 0.289) at 12 months. A risk score cutoff of 2.09 effectively stratified patients into low- and high-risk groups (<i>p</i> &lt; 0.001).</p> Conclusions <p>By integrating objective inflammatory-nutritional markers with clinical factors, this novel nomogram provides enhanced survival prediction compared to traditional anatomical scoring systems. It serves as a robust tool for guiding personalized palliative decision-making in the era of modern systemic therapy.</p>

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A novel inflammatory-nutritional nomogram for predicting survival after minimally invasive surgery for spinal metastases: a comparison with the Katagiri and SORG systems

  • 期刊论文

  • 发表日期：

    2026年7月1日

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  • Cheng Chen,
  • Ruoou Chen,
  • Dajun Zeng,
  • Gaojian Tao,
  • Ying Huang

摘要

Purpose

Accurate survival prediction is paramount for selecting appropriate candidates for minimally invasive surgery (MIS) among patients with spinal metastases. Traditional scoring systems often neglect the host’s systemic inflammatory response. This study aimed to develop a prognostic nomogram integrating the Glasgow Prognostic Score (GPS) and Lymphocyte-to-Monocyte Ratio (LMR) and evaluate its efficacy against the established Katagiri and SORG systems.

Methods and materials

A retrospective study was conducted on 172 patients who underwent MIS (percutaneous vertebroplasty and/or radiofrequency ablation) for spinal metastases. Patients were divided into training (n = 120) and testing (n = 52) cohorts. Independent prognostic factors were identified using multivariate Cox regression to construct a nomogram. Model performance was evaluated using Area Under the Curve (AUC), calibration plots, Decision Curve Analysis (DCA), Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI).

Results

Multivariate analysis identified eight independent prognostic factors: clinical profile, surgical modality, systemic therapy, analgesic use, bone metastasis, visceral metastasis, LMR, and GPS. The new nomogram demonstrated excellent discrimination with 12-month AUCs of 0.886 (training) and 0.831 (testing), significantly outperforming the Katagiri (AUC 0.740) and SORG (AUC 0.710) systems (p < 0.001). Calibration plots revealed high agreement between predicted and observed survival. Furthermore, the new model showed significantly improved predictive accuracy over Katagiri (NRI 0.415; IDI 0.227) and SORG (NRI 0.391; IDI 0.289) at 12 months. A risk score cutoff of 2.09 effectively stratified patients into low- and high-risk groups (p < 0.001).

Conclusions

By integrating objective inflammatory-nutritional markers with clinical factors, this novel nomogram provides enhanced survival prediction compared to traditional anatomical scoring systems. It serves as a robust tool for guiding personalized palliative decision-making in the era of modern systemic therapy.