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OBJECTIVECancer patients often experience high levels of distress, which are particularly pronounced in the perioperative period. However, there is a dearth of research on distress rates in patients with metastatic spine disease (MSD). This study aims to assess pre- and postoperative distress levels in patients with MSD undergoing surgical intervention, as well as the association between distress and sociodemographic factors. METHODSThe authors retrospectively queried electronic medical records from a single institution for demographic and clinical data on patients with MSD who underwent surgical intervention between 2015 and 2023. Data included pre- (within 30 days of surgery) and postoperative (within 30 and 90 days of surgery) National Comprehensive Cancer Network’s distress thermometer (NCCN-DT) scores. The proportion of patients with clinically significant distress (DT score ≥ 4) at each time point was examined, as well as changes between baseline distress and distress 30 days postoperatively. The association between clinically significant distress and sex, age, race/ethnicity, and marital status was assessed. A p value < 0.05 was considered significant. RESULTSThe study identified 265 patients with complete NCCN-DT questionnaires. Nearly half (47.5%) of the patients were female, with 66.0% identifying as Caucasian/White. The mean (± standard deviation) age at surgery was 61.4 ± 12.1 years. Preoperatively, the mean distress score was 3.6 ± 3.1 (range 0–10), with 89 (46.4%) of 192 patients reporting moderate to severe distress (DT ≥ 4). The mean distress score at 30 days postoperatively was 3.2 ± 3.0 (range 0–10), with 43.8% of patients reporting moderate to severe distress. At 90 days postoperatively, the mean distress score was 2.3 ± 2.5 (range 0–9) with 26.6% of patients reporting moderate to severe levels. Non-White patients had significantly higher preoperative distress than their White counterparts (p = 0.03). CONCLUSIONSDistress is a common experience among patients with MSD undergoing surgical intervention. Preoperatively, nearly half of these patients report moderate to severe distress, with distress levels remaining elevated through the 1st month after surgery. These findings highlight the critical need for timely psychosocial interventions to address distress at key stages of the surgical process. Race-based differences in distress rates emphasize the importance of developing targeted support strategies for more vulnerable groups. 

Abstract BackgroundPrognostic indices for patients with brain metastases (BM) are needed to individualize treatment and stratify clinical trials. Two frequently used tools to estimate survival in patients with BM are the recursive partitioning analysis (RPA) and the diagnosis-specific graded prognostic assessment (DS-GPA). Given recent advances in therapies and improved survival for patients with BM, this study aims to validate and analyze these 2 models in a modern cohort. MethodsPatients diagnosed with BM were identified via our institution’s Tumor Board meetings. Data were retrospectively collected from the date of diagnosis with BM. The concordance of the RPA and GPA was calculated using Harrell’s C index. A Cox proportional hazards model with backwards elimination was used to generate a parsimonious model predictive of survival. ResultsOur study consisted of 206 patients diagnosed with BM between 2010 and 2019. The RPA had a prediction performance characterized by Harrell’s C index of 0.588. The DS-GPA demonstrated a Harrell’s C index of 0.630. A Cox proportional hazards model assessing the effect of age, presence of lung, or liver metastases, and Eastern Cooperative Oncology Group (ECOG) performance status score of 3/4 on survival yielded a Harrell’s C index of 0.616. Revising the analysis with an uncategorized ECOG demonstrated a C index of 0.648. ConclusionsWe found that the performance of the RPA remains unchanged from previous validation studies a decade earlier. The DS-GPA outperformed the RPA in predicting overall survival in our modern cohort. Analyzing variables shared by the RPA and DS-GPA produced a model that performed analogously to the DS-GPA.