Neuroendocrinology Unit, Department of Endocrinology and Nutrition, Hospital Universitario Ramón y Cajal, Madrid, Spain.
Neuroendocrinology Unit, Department of Neurosurgery, Hospital Universitario Ramón y Cajal, Madrid, Spain.
J Endocrinol Invest. 2021 Jan;44(1):183-193. doi: 10.1007/s40618-020-01296-4. Epub 2020 May 21.
To identify presurgical clinical, hormonal and radiological variables associated with surgical remission in acromegaly and develop a predictive model for surgical remission.
Ambispective study of acromegaly surgical patients followed in two Spanish tertiary hospitals. Patients operated by the same neurosurgeon by endonasal endoscopic transsphenoidal approach (n = 49) were included to develop the predictive model, and patients operated by other neurosurgeons (n = 37) were used for external validation of the predictive model. The predictive model was developed with a multivariate logistic regression model based on the 2000 criteria.
86 acromegalic patients were included. 49 patients, 83.7% with macroadenomas and 32.7% with Knosp grade > 2, were included for the development of the predictive model. The overall rate of surgical remission with the 2000 criteria was 73.5% and 51.0% with the 2010 criteria. Using the 2000 criteria, variables associated with surgical remission were: older age (OR = 1.1, p = 0.001), lower basal presurgical GH levels (OR = 0.9, p = 0.003), Knosp 0-2 (OR = 34.1, p < 0.0001) and lower maximum pituitary adenoma diameter (OR = 0.9, p = 0.019). The model with the best diagnostic accuracy to predict surgical remission combined age, Knosp 0-2 and presurgical GH levels (AIC = 29.7, AUC = 0.95) with a sensitivity of 93.8% and a specificity of 75.0%. The estimated loss of prediction with the external validation (n = 37) was 4.2%.
The predictive model with the best diagnosis accuracy for surgical remission combined age, Knosp 0-2 and presurgical GH levels, with a sensitivity of 93.8% and a specificity of 75.0%. This model could be very useful to select candidates to preoperative medical treatment and planning the follow-up.
确定与肢端肥大症手术缓解相关的术前临床、激素和影像学变量，并建立手术缓解的预测模型。
对在西班牙两家三级医院接受治疗的肢端肥大症手术患者进行前瞻性研究。纳入由同一位神经外科医生通过经鼻内镜蝶窦入路（n=49）进行手术的患者来建立预测模型，并纳入由其他神经外科医生（n=37）进行手术的患者来验证预测模型。预测模型是基于 2000 年标准通过多变量逻辑回归模型建立的。
共纳入 86 例肢端肥大症患者。其中 49 例患者（83.7%为大腺瘤，32.7% Knosp 分级>2）被纳入预测模型的建立。根据 2000 年标准，总体手术缓解率为 73.5%，根据 2010 年标准为 51.0%。根据 2000 年标准，与手术缓解相关的变量为：年龄较大（OR=1.1，p=0.001）、术前 GH 水平较低（OR=0.9，p=0.003）、Knosp 0-2（OR=34.1，p<0.0001）和最大垂体腺瘤直径较小（OR=0.9，p=0.019）。预测手术缓解的最佳诊断准确性的模型结合了年龄、Knosp 0-2 和术前 GH 水平（AIC=29.7，AUC=0.95），其敏感性为 93.8%，特异性为 75.0%。在外部验证（n=37）中，预计预测值会损失 4.2%。
该预测模型的诊断准确性最佳，与手术缓解相关的变量包括年龄、Knosp 0-2 和术前 GH 水平，其敏感性为 93.8%，特异性为 75.0%。该模型对于选择术前药物治疗的候选者和规划随访非常有用。
