4.5 Review

Incidental intracranial meningiomas: a systematic review and meta-analysis of prognostic factors and outcomes

Journal

JOURNAL OF NEURO-ONCOLOGY
Volume 142, Issue 2, Pages 211-221

Publisher

SPRINGER
DOI: 10.1007/s11060-019-03104-3

Keywords

Asymptomatic; Incidental; Meningioma; Meta-analysis; Systematic review

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BackgroundIncidental discovery accounts for 30% of newly-diagnosed intracranial meningiomas. There is no consensus on their optimal management. This review aimed to evaluate the outcomes of different management strategies for these tumors.MethodsUsing established systematic review methods, six databases were scanned up to September 2017. Pooled event proportions were estimated using a random effects model. Meta-regression of prognostic factors was performed using individual patient data.ResultsTwenty studies (2130 patients) were included. Initial management strategies at diagnosis were: surgery (27.3%), stereotactic radiosurgery (22.0%) and active monitoring (50.7%) with a weighted mean follow-up of 49.5months (SD=29.3). The definition of meningioma growth and monitoring regimens varied widely impeding relevant meta-analysis. The pooled risk of symptom development in patients actively monitored was 8.1% (95% CI 2.7-16.1). Associated factors were peritumoral edema (OR 8.72 [95% CI 0.35-14.90]) and meningioma diameter3cm (OR 34.90 [95% CI 5.17-160.40]). The pooled proportion of intervention after a duration of active monitoring was 24.8% (95% CI 7.5-48.0). Weighted mean time-to-intervention was 24.8months (SD=18.2). The pooled risks of morbidity following surgery and radiosurgery, accounting for cross-over, were 11.8% (95% CI 3.7-23.5) and 32.0% (95% CI 10.6-70.5) respectively. The pooled proportion of operated meningioma being WHO grade I was 94.0% (95% CI 88.2-97.9).ConclusionThe management of incidental meningioma varies widely. Most patients who clinically or radiologically progressed did so within 5years of diagnosis. Intervention at diagnosis may lead to unnecessary overtreatment. Prospective data is needed to develop a risk calculator to better inform management strategies.

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