A Quantified Risk-Scoring System for the Recurrence of Meningiomas: Results From a Retrospective Study of 392 Patients

Zhangzhang Zhu; Chengde Wang; Jiadong Xu; Chunyong Wang; Lei Xia; Qun Li; Jianglong Lu; Lin Cai; Weiming Zheng; Zhipeng Su

doi:10.3389/fonc.2020.585313

A Quantified Risk-Scoring System for the Recurrence of Meningiomas: Results From a Retrospective Study of 392 Patients

Front Oncol. 2020 Oct 5:10:585313. doi: 10.3389/fonc.2020.585313. eCollection 2020.

Authors

Zhangzhang Zhu¹, Chengde Wang¹, Jiadong Xu¹, Chunyong Wang², Lei Xia¹, Qun Li¹, Jianglong Lu¹, Lin Cai¹, Weiming Zheng¹, Zhipeng Su^{1

3}

Affiliations

¹ Department of Neurosurgery, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
² Department of General Surgery, Zhuji People's Hospital of Zhejiang Province, Shaoxing, China.
³ Department of Neurosurgery, Wencheng County People's Hospital, Wenzhou, China.

Abstract

Aim: This study aimed to identify the independent risk factors of recurrence in patients undergoing primary resection of meningioma and construct a scoring system for the prediction of the risk of postoperative recurrence. Materials and Methods: The clinical data of 591 patients who underwent primary surgical resection for meningioma at the First Affiliated Hospital of Wenzhou Medical University between November 2010 and December 2016 were retrospectively reviewed. The clinical, radiological, and pathological characteristics were evaluated, and the independent risk factors for recurrence were identified via receiver operating characteristic (ROC) curve and logistic analyses. A scoring system that included these independent risk factors was used to construct a risk-predicting model that was evaluated via a ROC curve analysis. The recurrences of different subgroups were observed by Kaplan-Meier's curves. Results: The clinical data of 392 patients with meningioma were used to construct the scoring system. The logistic analysis showed that sex (OR = 2.793, 95% CI = 1.076-7.249, P = 0.035), heterogeneous tumor enhancement (OR = 4.452, 95% CI = 1.714-11.559, P = 0.002), brain invasion (OR = 2.650, 95% CI = 1.043-6.733, P = 0.041), Simpson's removal grade (OR = 5.139, 95% CI = 1.355-19.489, P = 0.016), and pathological grade (OR = 3.282, 95% CI = 1.123-9.595, P = 0.030) were independent risk factors for recurrence. A scoring system was developed and used to divide the patients into the following four subgroups: subgroup 1 with scores of 0-75 (n = 249), subgroup 2 with scores of 76-154 (n = 88), subgroup 3 with scores of 155-215 (n = 46), and subgroup 4 with scores of 216-275 (n = 9). The incidences of recurrence in each subgroup were as follows: subgroup 1, 1.2%; subgroup 2, 5.7%; subgroup 3, 26.1%; and subgroup 4, 66.7% (P < 0.001). The scoring system reliably predicted the postoperative recurrence of meningioma with a high area under the ROC curve. Conclusions: Our scoring system is a simple and reliable instrument for identifying meningioma patients at risk of postoperative recurrence and could help in optimizing individualized clinical treatment.

Keywords: meningioma; prognosis; recurrence; risk model; scoring system.