Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma
BackgroundThis study aims to establish an integrated model based on clinical, laboratory, radiological, and pathological factors to predict the postoperative recurrence of atypical meningioma (AM).Materials and MethodsA retrospective study of 183 patients with AM was conducted. Patients were randoml...
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Frontiers Media S.A.
2021-10-01
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Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2021.754937/full |
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Article |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiao-Yong Chen Jin-Yuan Chen Yin-Xing Huang Jia-Heng Xu Wei-Wei Sun Yue- Chen Chen-Yu Ding Chen-Yu Ding Shuo-Bin Wang Xi-Yue Wu De-Zhi Kang De-Zhi Kang De-Zhi Kang Hong-Hai You Yuan-Xiang Lin |
spellingShingle |
Xiao-Yong Chen Jin-Yuan Chen Yin-Xing Huang Jia-Heng Xu Wei-Wei Sun Yue- Chen Chen-Yu Ding Chen-Yu Ding Shuo-Bin Wang Xi-Yue Wu De-Zhi Kang De-Zhi Kang De-Zhi Kang Hong-Hai You Yuan-Xiang Lin Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma Frontiers in Oncology atypical meningioma recurrence predict LASSO nomogram model |
author_facet |
Xiao-Yong Chen Jin-Yuan Chen Yin-Xing Huang Jia-Heng Xu Wei-Wei Sun Yue- Chen Chen-Yu Ding Chen-Yu Ding Shuo-Bin Wang Xi-Yue Wu De-Zhi Kang De-Zhi Kang De-Zhi Kang Hong-Hai You Yuan-Xiang Lin |
author_sort |
Xiao-Yong Chen |
title |
Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma |
title_short |
Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma |
title_full |
Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma |
title_fullStr |
Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma |
title_full_unstemmed |
Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma |
title_sort |
establishment and validation of an integrated model to predict postoperative recurrence in patients with atypical meningioma |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Oncology |
issn |
2234-943X |
publishDate |
2021-10-01 |
description |
BackgroundThis study aims to establish an integrated model based on clinical, laboratory, radiological, and pathological factors to predict the postoperative recurrence of atypical meningioma (AM).Materials and MethodsA retrospective study of 183 patients with AM was conducted. Patients were randomly divided into a training cohort (n = 128) and an external validation cohort (n = 55). Univariable and multivariable Cox regression analyses, the least absolute shrinkage and selection operator (LASSO) regression analysis, time-dependent receiver operating characteristic (ROC) curve analysis, and evaluation of clinical usage were used to select variables for the final nomogram model.ResultsAfter multivariable Cox analysis, serum fibrinogen >2.95 g/L (hazard ratio (HR), 2.43; 95% confidence interval (CI), 1.05–5.63; p = 0.039), tumor located in skull base (HR, 6.59; 95% CI, 2.46-17.68; p < 0.001), Simpson grades III–IV (HR, 2.73; 95% CI, 1.01–7.34; p = 0.047), tumor diameter >4.91 cm (HR, 7.10; 95% CI, 2.52–19.95; p < 0.001), and mitotic level ≥4/high power field (HR, 2.80; 95% CI, 1.16–6.74; p = 0.021) were independently associated with AM recurrence. Mitotic level was excluded after LASSO analysis, and it did not improve the predictive performance and clinical usage of the model. Therefore, the other four factors were integrated into the nomogram model, which showed good discrimination abilities in training cohort (C-index, 0.822; 95% CI, 0.759–0.885) and validation cohort (C-index, 0.817; 95% CI, 0.716–0.918) and good match between the predicted and observed probability of recurrence-free survival.ConclusionOur study established an integrated model to predict the postoperative recurrence of AM. |
topic |
atypical meningioma recurrence predict LASSO nomogram model |
url |
https://www.frontiersin.org/articles/10.3389/fonc.2021.754937/full |
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doaj-3a1670a18ed6440b867ca2ac6f17ee2b2021-10-07T07:10:32ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-10-011110.3389/fonc.2021.754937754937Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical MeningiomaXiao-Yong Chen0Jin-Yuan Chen1Yin-Xing Huang2Jia-Heng Xu3Wei-Wei Sun4Yue- Chen5Chen-Yu Ding6Chen-Yu Ding7Shuo-Bin Wang8Xi-Yue Wu9De-Zhi Kang10De-Zhi Kang11De-Zhi Kang12Hong-Hai You13Yuan-Xiang Lin14Department of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Ophthalmology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaKey Laboratory of Radiation Biology of Fujian Higher Education Institutions, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Neurosurgery, Neurosurgical Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaBackgroundThis study aims to establish an integrated model based on clinical, laboratory, radiological, and pathological factors to predict the postoperative recurrence of atypical meningioma (AM).Materials and MethodsA retrospective study of 183 patients with AM was conducted. Patients were randomly divided into a training cohort (n = 128) and an external validation cohort (n = 55). Univariable and multivariable Cox regression analyses, the least absolute shrinkage and selection operator (LASSO) regression analysis, time-dependent receiver operating characteristic (ROC) curve analysis, and evaluation of clinical usage were used to select variables for the final nomogram model.ResultsAfter multivariable Cox analysis, serum fibrinogen >2.95 g/L (hazard ratio (HR), 2.43; 95% confidence interval (CI), 1.05–5.63; p = 0.039), tumor located in skull base (HR, 6.59; 95% CI, 2.46-17.68; p < 0.001), Simpson grades III–IV (HR, 2.73; 95% CI, 1.01–7.34; p = 0.047), tumor diameter >4.91 cm (HR, 7.10; 95% CI, 2.52–19.95; p < 0.001), and mitotic level ≥4/high power field (HR, 2.80; 95% CI, 1.16–6.74; p = 0.021) were independently associated with AM recurrence. Mitotic level was excluded after LASSO analysis, and it did not improve the predictive performance and clinical usage of the model. Therefore, the other four factors were integrated into the nomogram model, which showed good discrimination abilities in training cohort (C-index, 0.822; 95% CI, 0.759–0.885) and validation cohort (C-index, 0.817; 95% CI, 0.716–0.918) and good match between the predicted and observed probability of recurrence-free survival.ConclusionOur study established an integrated model to predict the postoperative recurrence of AM.https://www.frontiersin.org/articles/10.3389/fonc.2021.754937/fullatypical meningiomarecurrencepredictLASSOnomogrammodel |