Multicentric Prospective Validation of the Zurich Pituitary Score

Pituitary Adenoma Clinical Trial

Official title: Multicentric Prospective Validation of the Zurich Pituitary Score

Status Completed

Clinical Trial Summary

Predictive analytics for GTR, EOR and RV are useful in surgical decision-making, particularly whenever there is no unequivocal indication for surgery. Several factors have been shown to have a role in predicting GTR. Among these, the Knosp classification has proven over the years to be a good predictor of GTR. The score is based on the lateral extension of the adenoma in relation the the intracranial bedding of the internal carotid artery. However, recent literature has demonstrated that the Knosp classification suffers from relatively poor interrater agreement. Moreover the classification was conceived in an era when endoscopic techniques were not available: nowadays endoscopic technique allows visualization and possibly also reaching portions of adenoma which at the time when the Knosp classification was introduced were simply not possible. Lastly, the efficacy of the Knosp's score in predicting also EOR and RV has never been tested. Recently a new score - the Zurich Pituitary Score (ZPS) has been proposed at the University Hospital of Zürich (USZ). The score has proved in the examined series to be more powerful than the Knosp classification in predicting GTR, EOR and RV. A good interrater agreement was also demonstrated. The score however, has been validated only in a monocentric setting with a limited number of patients. The aim of this study is to assess the (1) predictive ability of the ZPS for GTR, EOR, and RV, and (2) the inter-rater agreement of the ZPS in an external validation study.

Clinical Trial Description

In transsphenoidal surgery (TSS) for pituitary adenoma (PA), gross total resection (GTR) is often the target since it has been shown to relevantly influence long term patient outcome. This applies both to functioning adenomas (FA) as well as to non-functioning adenomas (NFPA). Mounting evidence shows that in cases where GTR is not achievable, maximizing extent of resection (EOR) is still highly desirable, particularly in case of FA, with the aim of obtaining the smallest possible residual volume (RV). Predictive analytics for GTR, EOR and RV are useful in surgical decision-making, particularly whenever there is no unequivocal indication for surgery. Several factors have been shown to have a role in predicting GTR. Among these, the Knosp classification has proven over the years to be a good predictor of GTR. The score is based on the lateral extension of the adenoma in relation the the intracranial bedding of the internal carotid artery. However, recent literature has demonstrated that the Knosp classification suffers from relatively poor interrater agreement. Moreover the classification was conceived in an era when endoscopic techniques were not available: nowadays endoscopic technique allows visualization and possibly also reaching portions of adenoma which at the time when the Knosp classification was introduced were simply not possible. Lastly, the efficacy of the Knosp's score in predicting also EOR and RV has never been tested. Recently a new score - the Zurich Pituitary Score (ZPS) has been proposed at the University Hospital of Zürich (USZ). The score has proved in the examined series to be more powerful than the Knosp classification in predicting GTR, EOR and RV. A good interrater agreement was also demonstrated. The score however, has been validated only in a monocentric setting with a limited number of patients. The aim of this study is to assess the (1) predictive ability of the ZPS for GTR, EOR, and RV, and (2) the inter-rater agreement of the ZPS in an external validation study. ;

Related Conditions & MeSH terms

• Adenoma
• Pituitary Adenoma
• Pituitary Diseases
• Pituitary Neoplasms

• NCT number: NCT04076046
• Study type: Observational [Patient Registry]
• Source: University of Zurich
• Status: Completed
• Start date: November 1, 2019
• Completion date: December 1, 2021