T. Mezei, J. Báskay, P. Pollner, A. Horváth, Z. Nagy, G. Czigléczki, P. Banczerowski
{"title":"[新的,创新的预后计算器为转移性脊柱肿瘤患者]。","authors":"T. Mezei, J. Báskay, P. Pollner, A. Horváth, Z. Nagy, G. Czigléczki, P. Banczerowski","doi":"10.18071/isz.75.0117","DOIUrl":null,"url":null,"abstract":"Background and purpose\nThe aim of our research was to create a scoring system that predicts prognosis and recommends therapeutic options for patients with metastatic spine tumor. Increasing oncological treatment opportunities and prolonged survival have led to a growing need to address clinical symptoms caused by meta-stases of the primary tumor. Spinal metastases can cause a significant reduction in quality of life due to the caused neurological deficits. A scoring system that predicts prognosis with sufficient accuracy could help us to achieve personalised treatment options.\n\n\nMethods\nMethods - We performed a retrospective clinical research of data from patients over 18 years of age who underwent surgery due to symptomatic spinal metastasis at the National Institute of Mental Disorders, Neurology and Neurosurgery between 2008 and 2018. Data from 454 patients were analysed. Survival analysis (Kaplan-Meier, log-rank, Cox model) was performed, network science-based correlation analysis was used to select the proper prognostic factors of our scoring system, such that its C value (predictive ability index) was maximized.\n\n\nResults\nMultivariate Cox analysis resulted in the identification of 5 independent prognostic factors (primary tumour type, age, ambulatory status, internal organ metastases, serum protein level). Our system predicted with an average accuracy of 70.6% over the 10-year study period.\n\n\nConclusion\nOur large case series of surgical dataset of patients with symptomatic spinal metastasis was used to create a risk calculator system that can help in the choice of therapy. Our risk calculator is also available online at https://emk.semmelweis.hu/gerincmet.","PeriodicalId":50394,"journal":{"name":"Ideggyogyaszati Szemle-Clinical Neuroscience","volume":"75 3-04 1","pages":"117-127"},"PeriodicalIF":0.9000,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[New, innovative prognosis calculator for patients with metastatic spinal tumors].\",\"authors\":\"T. Mezei, J. Báskay, P. Pollner, A. Horváth, Z. Nagy, G. Czigléczki, P. Banczerowski\",\"doi\":\"10.18071/isz.75.0117\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background and purpose\\nThe aim of our research was to create a scoring system that predicts prognosis and recommends therapeutic options for patients with metastatic spine tumor. Increasing oncological treatment opportunities and prolonged survival have led to a growing need to address clinical symptoms caused by meta-stases of the primary tumor. Spinal metastases can cause a significant reduction in quality of life due to the caused neurological deficits. A scoring system that predicts prognosis with sufficient accuracy could help us to achieve personalised treatment options.\\n\\n\\nMethods\\nMethods - We performed a retrospective clinical research of data from patients over 18 years of age who underwent surgery due to symptomatic spinal metastasis at the National Institute of Mental Disorders, Neurology and Neurosurgery between 2008 and 2018. Data from 454 patients were analysed. Survival analysis (Kaplan-Meier, log-rank, Cox model) was performed, network science-based correlation analysis was used to select the proper prognostic factors of our scoring system, such that its C value (predictive ability index) was maximized.\\n\\n\\nResults\\nMultivariate Cox analysis resulted in the identification of 5 independent prognostic factors (primary tumour type, age, ambulatory status, internal organ metastases, serum protein level). Our system predicted with an average accuracy of 70.6% over the 10-year study period.\\n\\n\\nConclusion\\nOur large case series of surgical dataset of patients with symptomatic spinal metastasis was used to create a risk calculator system that can help in the choice of therapy. 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[New, innovative prognosis calculator for patients with metastatic spinal tumors].
Background and purpose
The aim of our research was to create a scoring system that predicts prognosis and recommends therapeutic options for patients with metastatic spine tumor. Increasing oncological treatment opportunities and prolonged survival have led to a growing need to address clinical symptoms caused by meta-stases of the primary tumor. Spinal metastases can cause a significant reduction in quality of life due to the caused neurological deficits. A scoring system that predicts prognosis with sufficient accuracy could help us to achieve personalised treatment options.
Methods
Methods - We performed a retrospective clinical research of data from patients over 18 years of age who underwent surgery due to symptomatic spinal metastasis at the National Institute of Mental Disorders, Neurology and Neurosurgery between 2008 and 2018. Data from 454 patients were analysed. Survival analysis (Kaplan-Meier, log-rank, Cox model) was performed, network science-based correlation analysis was used to select the proper prognostic factors of our scoring system, such that its C value (predictive ability index) was maximized.
Results
Multivariate Cox analysis resulted in the identification of 5 independent prognostic factors (primary tumour type, age, ambulatory status, internal organ metastases, serum protein level). Our system predicted with an average accuracy of 70.6% over the 10-year study period.
Conclusion
Our large case series of surgical dataset of patients with symptomatic spinal metastasis was used to create a risk calculator system that can help in the choice of therapy. Our risk calculator is also available online at https://emk.semmelweis.hu/gerincmet.
期刊介绍:
The aim of Clinical Neuroscience (Ideggyógyászati Szemle) is to provide a forum for the exchange of clinical and scientific information for a multidisciplinary community. The Clinical Neuroscience will be of primary interest to neurologists, neurosurgeons, psychiatrist and clinical specialized psycholigists, neuroradiologists and clinical neurophysiologists, but original works in basic or computer science, epidemiology, pharmacology, etc., relating to the clinical practice with involvement of the central nervous system are also welcome.