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Updated: Jul 3, 2025

Endoscopic Endonasal Trans-sphenoidal Approach: Minimally Invasive Surgery for Pituitary Adenomas
Published on: January 17, 2018
Development and validation of a prediction model for consistency of pituitary adenoma: the PiTCon score
Alberto Acitores Cancela1,2, Víctor Rodríguez Berrocal3,4, Hector Pian Arias5
1Department of Neurosurgery, Hospital Universitario Ramón y Cajal, Madrid, Spain. alacitores@gmail.com.
Purpose:
Pituitary adenomas (PAs) usually have a soft consistency, facilitating gross total resection. However, 5-13% of PAs with fibrous consistency are challenging to remove entirely and are accompanied by greater morbimortality. This study aims to identify the clinical and radiological characteristics that correlate with PA fibrous consistency preoperatively. A simple scoring system has been proposed to predict incidence of fibrous PAs.
Materials And Methods:
Consecutive interventions (226) were analyzed, all performed through an endoscopic endonasal transsphenoidal approach. Univariable and multivariable logistic regression analysis was performed. Hosmer-Lemeshow test and receiver operating characteristic (ROC) curves were assessed to evaluate the model. A point scoring system (PiTCon) was derived based on the multivariable regression model. Our study aimed to identify the clinical and radiological characteristics that correlate with fibrous tumor consistency preoperatively.
Results:
The best diagnostic accuracy for predicting PA consistency consisted of five predictive factors: age, compressive symptoms, panhypopituitarism, craniocaudal extension of the PA in mm, and prior surgery. The multivariable model achieved good discrimination with an area under the curve (AUC) of the ROC curve being 0.82 and the 95% CI 0.76 to 0.88. Internal validation yielded an optimism-adjusted C-statistic of 0.80 (95% CI 0.74 to 0.86). A point scoring system (PiTCon score) was designed using the best predictive model.
Conclusions:
PA consistency can be estimated preoperatively regarding clinical and radiological characteristics. We propose a point-based scoring system (PiTCon score) that can better guide neurosurgeons in clinical decision-making and surgical risk assessment and help establish and describe patient prognosis.
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