机构:[1]Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing重点科室诊疗科室神经外科神经外科首都医科大学附属天坛医院[2]China National Clinical Research Center for Neurological Diseases, Beijing[3]Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing[4]Beijing Key Laboratory of Brain Tumor, Beijing, People’s Republic of China
OBJECTIVE: To develop a method to distinguish atypical meningiomas (AMs) with malignant progression (MP) from primary AMs without a clinical history. METHODS: The clinical, radiologic, and pathologic data of 33 previously Simpson grade I resected (if any) as well as no radiotherapy treated intracranial AMs between January 2008 and December 2015 were reviewed. Immunohistochemical staining for connexin 43 (Cx43) and Ki-67 was performed. Descriptive analysis and univariate and multivariate logistic regression analyses were used to explore independent predictors of MP. A multivariable logistic model was developed to estimate the risk of MP, and its diagnostic value was determined from a receiver operating characteristic curve. RESULTS: There were 11 AMs (33.3%) with histopathologically confirmed MP from benign meningiomas. The other 22 (66.7%) were initially diagnosed AMs with no histopathologically confirmedMP during a median 60.5 months (range, 42e126 months) of follow-up. Univariate and multivariate logistic analyses showed that irregular tumor shape (P = 0.010) and lowCx43 expression (P=0.010) were independent predictors of the presence of MP, and the predicted probability was calculated by the following formula: P =1/[1+exp.{1.218-(3.2023xShape)+(3.8143xCx43)}]. P > 0.5 for an irregularly shaped (score 1) AM with low Cx43 expression (score 0) indicated a high probability of MP. The sensitivity, specificity, positive predictive value, negative predictive value, and overall predictive accuracy were 63.6, 95.6, 87.5, 84.0, and 84.8%, respectively. CONCLUSIONS: Low Cx43 expression and irregular tumor shape were independent predictors of the presence of MP. The relevant logistic regression model was found to be effective in distinguishing MP-AMs from primary AMs.
基金:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China [81472370]
第一作者机构:[1]Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing[2]China National Clinical Research Center for Neurological Diseases, Beijing[3]Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing[4]Beijing Key Laboratory of Brain Tumor, Beijing, People’s Republic of China
通讯作者:
通讯机构:[1]Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing[2]China National Clinical Research Center for Neurological Diseases, Beijing[3]Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing[4]Beijing Key Laboratory of Brain Tumor, Beijing, People’s Republic of China
推荐引用方式(GB/T 7714):
Zhang Qing,Jia Gui-Jun,Zhang Guo-Bin,et al.A Logistic Regression Model for Detecting the Presence of Malignant Progression in Atypical Meningiomas[J].WORLD NEUROSURGERY.2019,126:E392-E401.doi:10.1016/j.wneu.2019.02.062.
APA:
Zhang, Qing,Jia, Gui-Jun,Zhang, Guo-Bin,Wang, Liang,Wu, Zhen...&Zhang, Jun-Ting.(2019).A Logistic Regression Model for Detecting the Presence of Malignant Progression in Atypical Meningiomas.WORLD NEUROSURGERY,126,
MLA:
Zhang, Qing,et al."A Logistic Regression Model for Detecting the Presence of Malignant Progression in Atypical Meningiomas".WORLD NEUROSURGERY 126.(2019):E392-E401