Low-Dose Acetylsalicylic Acid Treatment in Non-Skull-Base Meningiomas: Impact on Tumor Proliferation and Seizure Burden.
Johannes WachÁgi GüresirHartmut VatterUlrich HerrlingerAlbert BeckerMarieta TomaMichael HölzelErdem GüresirPublished in: Cancers (2022)
MIB-1 index is an important predictor of meningioma progression and was found to be correlated with COX-2 expression. However, the impact of low-dose acetylsalicylic acid (ASA) on MIB-1 index and clinical symptoms is unclear. Between 2009 and 2022, 710 patients with clinical data, tumor-imaging data, inflammatory laboratory (plasma fibrinogen, serum C-reactive protein) data, and neuropathological reports underwent surgery for primary cranial WHO grade 1 and 2 meningioma. ASA intake was found to be significantly associated with a low MIB-1 labeling index in female patients ≥ 60 years. Multivariable analysis demonstrated that female patients ≥ 60 years with a non-skull-base meningioma taking ASA had a significantly lower MIB-1 index (OR: 2.6, 95%: 1.0-6.6, p = 0.04). Furthermore, the intake of ASA was independently associated with a reduced burden of symptomatic epilepsy at presentation in non-skull-base meningiomas in both genders (OR: 3.8, 95%CI: 1.3-10.6, p = 0.03). ASA intake might have an anti-proliferative effect in the subgroup of elderly female patients with non-skull-base meningiomas. Furthermore, anti-inflammatory therapy seems to reduce the burden of symptomatic epilepsy in non-skull-base meningiomas. Further research is needed to investigate the role of anti-inflammatory therapy in non-skull-base meningiomas.
Keyphrases
- low dose
- end stage renal disease
- anti inflammatory
- newly diagnosed
- ejection fraction
- chronic kidney disease
- electronic health record
- prognostic factors
- peritoneal dialysis
- minimally invasive
- poor prognosis
- clinical trial
- signaling pathway
- high resolution
- randomized controlled trial
- patient reported outcomes
- stem cells
- coronary artery disease
- depressive symptoms
- weight gain
- long non coding rna
- photodynamic therapy
- deep learning
- binding protein
- weight loss
- fluorescence imaging