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DOI 10.1016/j.wneu.2024.11.103

Медицинская библиотека · World neurosurgery · 2024

Identifying Subgroups with Rapid Tumor Growth Rate in Adult Pituitary Neuroendocrine Tumors: A Comprehensive Analysis of Clinical and Imaging Features.

Zhang Zhe, Li Peng, Yang Xiaojie, Yin Jie, He Junhua, Hu Yanan, Liu Pinan

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

OBJECTIVE

To comprehensively investigate the clinical and imaging features associated with the tumor growth rate (TGR) of pituitary neuroendocrine tumors (PitNETs).

METHODS

The tumor volume was assessed using magnetic resonance imaging. The potential growth-related parameters were compared among different TGR subgroups. Logistic regression analysis and receiver operating characteristic curves were used to identify risk factors and evaluate their diagnostic accuracy for rapid TGR, respectively.

RESULTS

The study included 81 patients with PitNETs who met the inclusion criteria. Receiver operating characteristic curves were used to determine the optimal cut-off values for age and tumor volume at initial diagnosis. The factors significantly associated with rapid TGR were age <55 years, T2 heterogeneity, and Knosp grade ≥3 (P < 0.05). No significant differences were found among other clinical and imaging subgroups. Multivariate regression analysis confirmed that these factors increased the risk of rapid TGR (P < 0.05). The area under the curve for predicting rapid TGR using age <55 years, T2 heterogeneity, Knosp grade ≥3, and a combined model of these factors were 0.677 (95% confidence interval [CI], 0.564-0.777), 0.705 (95% CI, 0.593-0.801), 0.680 (95% CI, 0.567-0.780), and 0.834 (95% CI, 0.735-0908), respectively. Additionally, the expression of cell lineage-specific transcription factors and Ki-67 exhibited a significant correlation with age <55 years and T2 heterogeneity; however, no association was observed with Knosp grade.

CONCLUSIONS

The TGR of PitNETs is associated with age, T2 heterogeneity, and Knosp grade. Integrating these factors improves the accuracy of prediction for TGR. Therefore, understanding the TGR in PitNETs can provide valuable evidence for tailoring individualized treatment strategies for patients.

Для цитирования: Zhang Zhe, Li Peng, Yang Xiaojie, Yin Jie, He Junhua, Hu Yanan, Liu Pinan. Identifying Subgroups with Rapid Tumor Growth Rate in Adult Pituitary Neuroendocrine Tumors: A Comprehensive Analysis of Clinical and Imaging Features.. World neurosurgery. 2024. DOI: 10.1016/j.wneu.2024.11.103.

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