March 3, 2026Open Access

Predicting resection success in giant pituitary adenomas: morphologic determinants and a preoperative multivariate model

Key Points

Surgical success correlates with tumor volume and multilobulated morphology, indicating crucial predictive factors.
The model achieved an area under the curve of 0.88, demonstrating strong predictive accuracy for resection outcomes.
Assessment using multivariate logistic regression analyzed clinical and radiological variables from 60 cases over eight years.
The findings suggest improved preoperative planning for giant pituitary adenoma surgeries based on identified morphological determinants.

Abstract

We retrospectively analyzed 60 consecutive patients with giant pituitary adenomas who underwent endoscopic transsphenoidal surgery (ETSS) at a tertiary pituitary center between 2015 and 2023. Clinical, radiological, hormonal, and surgical variables were collected from medical records. Tumor volume, cranial extension pattern, Hardy and Knosp classifications, and multilobulated morphology were evaluated using preoperative MRI. Surgical outcomes, complications, and postoperative endocrine and visual results were recorded. Predictors of resection extent were assessed using multivariate logistic regression, and a preoperative prediction model was developed and evaluated with ROC analysis.

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Cite This Study

Ozaydin et al. (Fri,) studied this question.

synapsesocial.com/papers/69a75fa3c6e9836116a2b268 https://doi.org/https://doi.org/10.3389/fendo.2026.1759071

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