Department of Neurosurgery, Tangdu Hospital, Air Force Medical University, Xi'an, China.
Department of Pathology, Tangdu Hospital, Air Force Medical University, Xi'an, China.
Clin Endocrinol (Oxf). 2021 Jul;95(1):134-142. doi: 10.1111/cen.14465. Epub 2021 May 10.
The aim of this study was to establish a preoperative prediction method for sparsely granulated (SG) growth hormone (GH)-secreting pituitary adenoma, an aggressive tumour subtype with high recurrence risk, in acromegaly patients.
Eighty-three patients with GH-secreting pituitary adenomas were included in this study. GH measurements, cytokeratin immunostaining and electron microscopy were performed to detect granulation patterns. Preoperative factors, including general, radiological and endocrinological features and acute octreotide suppression test outcomes, were compared between SG and densely granulated (DG) groups. The predictive capabilities of these features were analysed using a receiver operating characteristic (ROC) curve, and the most predictive features were combined to establish a grading scale.
Thirty-nine of the 83 patients had SG GH-secreting pituitary adenomas; 44 had DG tumours. SG tumours tended to occur in younger patients and have larger diameters and volumes, higher Knosp grades, lower GH indexes and normalized insulin-like growth factor-1 (IGF-1) level, and a lower ∆GH% after octreotide treatment. The tumour size, Knosp grade, GH index and ∆GH% after octreotide treatment had good predictive performance, with area under the curve (AUC) values ranging from 0.70 to 0.80. Combining four parameters, including diameter, Knosp grade, GH index and ∆GH% after octreotide treatment, we established a grading scale for predicting SG GH-secreting pituitary adenomas with an AUC of 0.84 and relatively high sensitivity and specificity.
We propose a predictive method for distinguishing SG and DG GH-secreting pituitary adenomas preoperatively. This method will help physicians identify candidates for presurgical medical treatment and neurosurgeons determine radical surgical strategies for high-risk tumours.
本研究旨在建立一种术前预测方法，用于预测肢端肥大症患者中侵袭性高复发风险的稀疏颗粒（SG）生长激素（GH）分泌垂体腺瘤。
本研究纳入了 83 例 GH 分泌垂体腺瘤患者。进行 GH 测量、细胞角蛋白免疫染色和电子显微镜检查以检测颗粒模式。比较 SG 和密集颗粒（DG）组患者的术前因素，包括一般、放射学和内分泌特征以及急性奥曲肽抑制试验结果。使用受试者工作特征（ROC）曲线分析这些特征的预测能力，并将最具预测性的特征组合建立分级量表。
83 例患者中，39 例为 SG GH 分泌性垂体腺瘤，44 例为 DG 肿瘤。SG 肿瘤倾向于发生在年轻患者中，且直径和体积较大，Knosp 分级较高，GH 指数和胰岛素样生长因子-1（IGF-1）水平正常化程度较低，奥曲肽治疗后 GH 下降百分比（∆GH%）较低。肿瘤大小、Knosp 分级、GH 指数和奥曲肽治疗后的 ∆GH%具有良好的预测性能，曲线下面积（AUC）值范围为 0.70 至 0.80。结合直径、Knosp 分级、GH 指数和奥曲肽治疗后的 ∆GH%四个参数，我们建立了一个预测 SG GH 分泌性垂体腺瘤的分级量表，AUC 为 0.84，具有较高的敏感性和特异性。
我们提出了一种术前区分 SG 和 DG GH 分泌性垂体腺瘤的预测方法。该方法将有助于医生识别需要术前药物治疗的候选者，并帮助神经外科医生确定高危肿瘤的根治性手术策略。
