AUTHOR=Chen Xiao-Yong , Chen Jin-Yuan , Huang Yin-Xing , Xu Jia-Heng , Sun Wei-Wei , Chen Yue- , Ding Chen-Yu , Wang Shuo-Bin , Wu Xi-Yue , Kang De-Zhi , You Hong-Hai , Lin Yuan-Xiang 

TITLE=Establishment and Validation of an Integrated Model to Predict Postoperative Recurrence in Patients With Atypical Meningioma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 11 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.754937

DOI=10.3389/fonc.2021.754937

ISSN=2234-943X

ABSTRACT=Background: To establish an integrated model based on clinical, laboratory, radiological, and pathological factors to predict the postoperative recurrence of atypical meningioma (AM).
Materials and Methods: A 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. 
Results: After 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 grade 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 4 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.
Conclusion: Our study established an integrated model to predict the postoperative recurrence of AM.