Risk factor identification and nomogram-based predictive model development for recurrence of pituitary adenomas following transsphenoidal surgery: a dual-center retrospective study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective: To identify independent risk factors for pituitary adenoma recurrence after transsphenoidal surgery and construct and validate a nomogram for recurrence risk quantification. Methods: We retrospectively collected clinical data of 469 patients with pituitary adenomas from Fuzhou 900 Hospital and Huashan Hospital of Fudan University. LASSO regression was applied to screen potential predictive factors, followed by multivariate Logistic regression to identify independent prognostic factors. Nomograms were subsequently constructed to evaluate the model's discriminative ability, calibration, and clinical utility. Results: 0.05). The model had AUC 0.905 [95%CI (0.8254, 0.9847)], C-index 0.905, sensitivity 85%, specificity 86.4%, with good calibration and clinical net benefits (DCA: 0.05-0.90 threshold). Conclusion: The nomogram, which is the first to integrate clival invasion with modified Knosp classification and extent of resection, effectively predicts pituitary adenoma recurrence after transsphenoidal surgery and shows promising clinical utility.
Source: Frontiers in Surgery
Authors: Xingjian Yang, Wenxian Yang, Pengwei Hou, Yuyang Chen, Jun Li, Jiansheng Zhong, Shousen Wang, Hongjie Chen
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7141602766
