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A prognostic model to personalize monitoring regimes for patients with incidental asymptomatic meningiomas

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 re...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7032634/
https://www.ncbi.nlm.nih.gov/pubmed/31603516
http://dx.doi.org/10.1093/neuonc/noz160
Descripción
Sumario: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.