Clinical radiology · 2025
A nomogram based on radiological features and immunoscore for predicting meningioma recurrence.
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Han T, Long C, Liu X, Zhang Y, Sun J, Zhou F, Si Y, Zhang B, Zhang P, Zhou J
Аннотация
AIM: This study aimed to develop a nomogram based on clinical, radiological features, and immunoscore for predicting meningioma recurrence.
MATERIALS AND METHODS: We retrospectively collected clinical, radiological, and pathological data of 109 meningioma patients who underwent surgical resection at our hospital. Patients were categorised into recurrence and non-recurrence groups according to postoperative follow-up. CD8+ T, CD4+ T, and PD-L1 expression levels were assessed via immunohistochemical staining of paraffin-embedded specimens using the threshold method. Whole-tumour histogram analysis provided T1C histogram parameters reflecting tumour heterogeneity. Univariate and multivariate COX regression analyses identified independent risk factors for meningioma recurrence, whereas Kaplan-Meier analysis examined the impact of variables such as immunoscore and entropy on recurrence. The nomogram's predictive efficacy was assessed using the C-index at 12 months, 24 months, and 36 months.
RESULTS: Immunoscore (hazard ratio [HR] = 3.574, 95% confidence interval [CI: 1.520-8.404], P=.004), entropy (HR=4.387, 95%CI [1.635-11.773], P=.003), grade (HR=2.649, 95%CI: [1.242-5.650], P=.012), and dural tail sign (HR=0.495, 95%CI [0.248-0.989], P=0.047) were identified as independent predictors of meningioma recurrence. Based on these independent risk factors, a nomogram was constructed, with C-index predicting the recurrence of meningiomas at 12 months, 24 months, and 36 months, which were 0.780, 0.794, and 0.747, respectively.
CONCLUSION: These findings underscore the nomogram's potential to advance precision medicine approaches in managing meningioma recurrence, offering a promising avenue for enhancing patient care and outcomes.
MATERIALS AND METHODS: We retrospectively collected clinical, radiological, and pathological data of 109 meningioma patients who underwent surgical resection at our hospital. Patients were categorised into recurrence and non-recurrence groups according to postoperative follow-up. CD8+ T, CD4+ T, and PD-L1 expression levels were assessed via immunohistochemical staining of paraffin-embedded specimens using the threshold method. Whole-tumour histogram analysis provided T1C histogram parameters reflecting tumour heterogeneity. Univariate and multivariate COX regression analyses identified independent risk factors for meningioma recurrence, whereas Kaplan-Meier analysis examined the impact of variables such as immunoscore and entropy on recurrence. The nomogram's predictive efficacy was assessed using the C-index at 12 months, 24 months, and 36 months.
RESULTS: Immunoscore (hazard ratio [HR] = 3.574, 95% confidence interval [CI: 1.520-8.404], P=.004), entropy (HR=4.387, 95%CI [1.635-11.773], P=.003), grade (HR=2.649, 95%CI: [1.242-5.650], P=.012), and dural tail sign (HR=0.495, 95%CI [0.248-0.989], P=0.047) were identified as independent predictors of meningioma recurrence. Based on these independent risk factors, a nomogram was constructed, with C-index predicting the recurrence of meningiomas at 12 months, 24 months, and 36 months, which were 0.780, 0.794, and 0.747, respectively.
CONCLUSION: These findings underscore the nomogram's potential to advance precision medicine approaches in managing meningioma recurrence, offering a promising avenue for enhancing patient care and outcomes.