Prognosis after Palliative Surgery for Patients with Spinal Metastasis: Comparison of Predicted and Actual Survival

Abstract

Prediction of prognosis is a key factor in therapeutic decision making due to recent the development of therapeutic options for spinal metastases. The aim of the study was to examine predictive scoring systems and identify prognostic factors for 6–month mortality after palliative surgery. The participants were 75 patients with spinal metastases who underwent palliative surgery and had a minimum follow–up period of 1 year. Associations of actual survival with categories based on the revised Tokuhashi score and new Katagiri score were evaluated. Univariate and multivariate analyses were performed to identify prognostic factors for 6–month mortality after palliative surgery. The median actual survival period was longer than those predicted using the scoring systems. However, 21.3% of patients died of cancers within 6 months after surgery. A higher CRP/albumin ratio (odds ratio: 0.39; cut–off 0.409) and absence of postoperative adjuvant therapy (odds ratio: 7.15) were independent risk factors for 6–month mortality. There was no association of mortality with primary site, severity of sarcopenia, or other biomarkers. These results suggest that careful consideration is needed to determine whether palliative surgery is the best option for patients with a high preoperative CRP/albumin ratio and/or absence of postoperative adjuvant therapy, regardless of predictions made from scoring systems.

Risk factors for 90-day readmission in metastatic spine tumors in South Korea: A nationwide population-based study from 2012 to 2019

“…In general, surgery is performed for patients with a high life expectancy of more than 6 months. 15 In the current study, among the 15,815 patients with metastatic spine tumors, 13,974 patients received surgical treatment, and only 1,841 patients received radiotherapy, con rming the preference for surgical treatment. In addition, the 3-year survival rate was higher in the surgical group (72.69%) than in the radiotherapy group (17.21%), and this can be because surgical intervention is mainly performed for patients who are expected to have a good prognosis and higher life expectancy.…”

Development and internal validation of machine-learning models for predicting survival in patients who underwent surgery for spinal metastases

“…An updated review of the treatment strategy for spinal metastasis by Hong et al [ 27 ] in 2022 classified the decision-making system as follows: First, classification-based prognostic models, such as the Tomita et al [ 12 ], Tokuhashi et al [ 10 ], Bauer and Wedin [ 11 ], and Katagiri et al [ 20 ] scoring systems, estimate patient survival using various prognostic factors, such as the type of primary cancer and presence of visceral metastasis. Despite their usage, recent studies have highlighted their poor accuracy, partly because of their inability to account for advancements in cancer treatments [ 28 - 30 ]. This has resulted in the development of “second-generation models.” Many previous studies have utilized machine-learning algorithms to develop decision-making systems with satisfactory accuracy in predicting survival [ 31 , 32 ].…”

A new era in the management of spinal metastasis

“…However, recent cancer therapeutic developments, such as novel chemotherapies, hormonal therapies, molecular targeted therapies, and immune therapies, have rendered these scoring systems inaccurate (50)(51)(52)(53). Thus, the Bauer scoring system was recently modified into the New England Spinal Metastasis Score (NESMS) (54).…”