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

Author:

Islim Abdurrahman I123ORCID,Kolamunnage-Dona Ruwanthi1,Mohan Midhun23,Moon Richard D C23,Crofton Anna3,Haylock Brian J4,Rathi Nitika5,Brodbelt Andrew R3,Mills Samantha J6,Jenkinson Michael D13ORCID

Affiliation:

1. Institute of Translational Medicine, University of Liverpool, Liverpool, UK

2. School of Medicine, University of Liverpool, Liverpool, UK

3. Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK

4. Department of Clinical Oncology, The Clatterbridge Cancer Centre NHS Foundation Trust, Wirral, UK

5. Department of Neuropathology, The Walton Centre NHS Foundation Trust, Liverpool, UK

6. Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK

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.

Funder

Health Education England

Academic Foundation Program

National Institute for Health Research

University of Liverpool Library

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Clinical Neurology,Oncology

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