BACKGROUND CONTEXT: Although the surgical and oncological therapies of primary spinal tumors (PSTs) have changed significantly over the last few decades, the prognosis of this rare disease is still poor. The decision-making process in the multidisciplinary management is handicapped by the lack of large-scale population-based prognostic studies. PURPOSE: The objective of the present study was to investigate preoperative factors associated with PST mortality and to develop a predictive scoring system of poor survival. STUDY DESIGN: This is a large-scale ambispective cohort study. PATIENT SAMPLE: The study included 323 consecutive patients with PSTs, treated surgically over an 18-year period at a tertiary care spine referral center for a population of 10 million. OUTCOME MEASURE: Survival was the outcome measure. METHODS: Patients were randomly divided into a training cohort (n=273) and a validation cohort (n=50). In the training cohort, 12 preoperative factors were investigated using Cox proportional hazard models. Based on the mortality-related variables, a simple scoring system of mortality was created, and three groups of patients were identified. Kaplan-Meier and log-rank analyses were used to compare the survival in the three groups. The model performance was assessed by measuring the discriminative ability (c-index) of the model and by applying a pseudo-R(2) goodness-of-fit test (Nagelkerke R(2), RN(2)). Internal validation was performed using bootstrapping in the training cohort and assessing the discrimination and explained variation of the model in the validation cohort. RESULTS: Patient age, spinal region, tumor grade, spinal pain, motor deficit, and myelopathy/cauda equina syndrome were significantly associated with poor survival in the multivariate analysis (p<.001, RN(2)=0.799). Based on these variables, we developed the Primary Spinal Tumor Mortality Score (PSTMS), where an eight-point scale was divided into three categories (low, medium, and high mortality). The three PSTMS categories were significantly associated with the overall survival (p<.001, RN(2)=0.811, c=0.82). The model performance remained similarly high in the validation cohort (RN(2)=0.831, c=0.81). CONCLUSIONS: The present study identifies six predictive variables for mortality in PSTs. Using these six variables, an easy-to-use scoring system was developed that can be applied to the estimation of postoperative survival in all types of PST patients.
RCT Entities:
BACKGROUND CONTEXT: Although the surgical and oncological therapies of primary spinal tumors (PSTs) have changed significantly over the last few decades, the prognosis of this rare disease is still poor. The decision-making process in the multidisciplinary management is handicapped by the lack of large-scale population-based prognostic studies. PURPOSE: The objective of the present study was to investigate preoperative factors associated with PST mortality and to develop a predictive scoring system of poor survival. STUDY DESIGN: This is a large-scale ambispective cohort study. PATIENT SAMPLE: The study included 323 consecutive patients with PSTs, treated surgically over an 18-year period at a tertiary care spine referral center for a population of 10 million. OUTCOME MEASURE: Survival was the outcome measure. METHODS:Patients were randomly divided into a training cohort (n=273) and a validation cohort (n=50). In the training cohort, 12 preoperative factors were investigated using Cox proportional hazard models. Based on the mortality-related variables, a simple scoring system of mortality was created, and three groups of patients were identified. Kaplan-Meier and log-rank analyses were used to compare the survival in the three groups. The model performance was assessed by measuring the discriminative ability (c-index) of the model and by applying a pseudo-R(2) goodness-of-fit test (Nagelkerke R(2), RN(2)). Internal validation was performed using bootstrapping in the training cohort and assessing the discrimination and explained variation of the model in the validation cohort. RESULTS:Patient age, spinal region, tumor grade, spinal pain, motor deficit, and myelopathy/cauda equina syndrome were significantly associated with poor survival in the multivariate analysis (p<.001, RN(2)=0.799). Based on these variables, we developed the Primary Spinal Tumor Mortality Score (PSTMS), where an eight-point scale was divided into three categories (low, medium, and high mortality). The three PSTMS categories were significantly associated with the overall survival (p<.001, RN(2)=0.811, c=0.82). The model performance remained similarly high in the validation cohort (RN(2)=0.831, c=0.81). CONCLUSIONS: The present study identifies six predictive variables for mortality in PSTs. Using these six variables, an easy-to-use scoring system was developed that can be applied to the estimation of postoperative survival in all types of PSTpatients.
Authors: Péter Pál Varga; Zsolt Szövérfi; Charles G Fisher; Stefano Boriani; Ziya L Gokaslan; Mark B Dekutoski; Dean Chou; Nasir A Quraishi; Jeremy J Reynolds; Alessandro Luzzati; Richard Williams; Michael G Fehlings; Niccole M Germscheid; Aron Lazary; Laurence D Rhines Journal: Eur Spine J Date: 2014-12-23 Impact factor: 3.134
Authors: Malte Mohme; Klaus Christian Mende; Theresa Krätzig; Rosemarie Plaetke; Kerim Beseoglu; Julian Hagedorn; Hans-Jakob Steiger; Frank W Floeth; Sven O Eicker Journal: Neurosurg Rev Date: 2016-10-07 Impact factor: 3.042
Authors: Nisaharan Srikandarajah; Martin Wilby; Simon Clark; Adam Noble; Paula Williamson; Tony Marson Journal: Spine (Phila Pa 1976) Date: 2018-09-01 Impact factor: 3.241