A prognostic model to personalize monitoring regimes for patients with incidental asymptomatic meningiomas. Issue 2 (11th October 2019)

• Record Type: Journal Article
• Authors: Islim, Abdurrahman I; Kolamunnage-Dona, Ruwanthi; Mohan, Midhun; Moon, Richard D C; Crofton, Anna; Haylock, Brian J; Rathi, Nitika; Brodbelt, Andrew R; Mills, Samantha J; Jenkinson, Michael D
• Is Part Of: Neuro-oncology. Volume 22:Issue 2(2020)
• Page Start: 278
• Page End: 289
• Publication Date: 2019-10-11
• Subjects: asymptomatic -- incidental -- meningioma -- prognosis -- risk score; Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noz160
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Background: Asymptomatic meningioma is a common incidental finding with no consensus on the optimal management strategy. We aimed to develop a prognostic model to guide personalized monitoring of incidental meningioma patients. Methods: A prognostic model of disease progression was developed in a retrospective cohort (2007–2015), defined as: symptom development, meningioma-specific mortality, meningioma growth or loss of window of curability. Secondary endpoints included non-meningioma-specific mortality and intervention. Results: Included were 441 patients (459 meningiomas). Over a median of 55 months (interquartile range, 37–80), 44 patients had meningioma progression and 57 died (non-meningioma-specific). Forty-four had intervention (at presentation, n = 6; progression, n = 20; nonprogression, n = 18). Model parameters were based on statistical and clinical considerations and included: increasing meningioma volume (hazard ratio [HR] 2.17; 95% CI: 1.53–3.09), meningioma hyperintensity (HR 10.6; 95% CI: 5.39–21.0), peritumoral signal change (HR 1.58; 95% CI: 0.65–3.85), and proximity to critical neurovascular structures (HR 1.38; 95% CI: 0.74–2.56). Patients were stratified based on these imaging parameters into low-, medium- and high-risk groups and 5-year disease progression rates were 3%, 28%, and 75%, respectively. After 5 years of follow-up, the risk of disease progression plateaued in all groups. Patients with an age-adjusted Charlson comorbidity index ≥6 (eg, an 80-year-old with chronic kidney disease) were 15 times more likely to die of other causes than to receive intervention at 5 years following diagnosis, regardless of risk group. Conclusions: The model shows that there is little benefit to rigorous monitoring in low-risk and older patients with comorbidities. Risk-stratified follow-up has the potential to reduce patient anxiety and associated health care costs.