Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma
This study aims to establish an integrated model based on clinical, laboratory, radiological, and pathological factors to predict the postoperative recurrence of atypical meningioma (AM). A retrospective study of 183 patients with AM was conducted. Patients were randomly divided into a training coho...
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Published in | Frontiers in oncology Vol. 11; p. 754937 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
07.10.2021
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Subjects | |
Online Access | Get full text |
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Summary: | This study aims to establish an integrated model based on clinical, laboratory, radiological, and pathological factors to predict the postoperative recurrence of atypical meningioma (AM).
A retrospective study of 183 patients with AM was conducted. Patients were randomly divided into a training cohort (
= 128) and an external validation cohort (
= 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.
After multivariable Cox analysis, serum fibrinogen >2.95 g/L (hazard ratio (HR), 2.43; 95% confidence interval (CI), 1.05-5.63;
= 0.039), tumor located in skull base (HR, 6.59; 95% CI, 2.46-17.68;
< 0.001), Simpson grades III-IV (HR, 2.73; 95% CI, 1.01-7.34;
= 0.047), tumor diameter >4.91 cm (HR, 7.10; 95% CI, 2.52-19.95;
< 0.001), and mitotic level ≥4/high power field (HR, 2.80; 95% CI, 1.16-6.74;
= 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.
Our study established an integrated model to predict the postoperative recurrence of AM. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Soichi Oya, Saitama Medical University, Japan; Bharat Guthikonda, Louisiana State University Health Shreveport, United States Edited by: Hailiang Tang, Fudan University, China These authors have contributed equally to this work and share first authorship This article was submitted to Neuro-Oncology and Neurosurgical Oncology, a section of the journal Frontiers in Oncology |
ISSN: | 2234-943X 2234-943X |
DOI: | 10.3389/fonc.2021.754937 |