A nomogram for predicting the risk of major postoperative complications for patients with meningioma.

Abstract

To identify risk factors for major postoperative complications in meningioma patients and to construct and validate a nomogram that identify patients at high risk of these complications. The medical records of meningioma patients who underwent surgical resection in our hospital from January 2018 to December 2020 were collected. The patients were divided into a training set (815 cases from the main campus in 2018 and 2019) and a validation set (300 cases from two other campuses in 2020). Major postoperative complications were defined as any new neurological deficits and complications classified as Clavien-Dindo Grading (CDG) II or higher. Univariate and multivariate analyses were conducted using the training set to identify independent risk factors. A nomogram was constructed based on these results. And then validated the nomogram through bootstrap re-sampling in both the training and validation sets. The concordance index (C-index) and the area under the curve (AUC) were used to assess the discriminative ability of the nomogram. The Hosmer-Lemeshow test was performed to evaluate the goodness-of-fit. The optimal cutoff point for the nomogram was calculated using Youden's index. In the training set, 135 cases (16.56%) experienced major postoperative complications. The independent risk factors identified were male sex, recurrent tumors, American Society of Anesthesiologists (ASA) class III-IV, preoperative Karnofsky Performance Scale (KPS) score < 80, preoperative serum albumin < 35g/L, tumor in the skull base or central sulcus area, subtotal tumor resection (STR), allogeneic blood transfusion, and larger tumor size. A nomogram was constructed based on these risk factors. It demonstrated good predictive performance, with a C-index of 0.919 for the training set and 0.872 for the validation set. The area under the curve (AUC) > 0.7 indicated satisfactory discriminative ability. The Hosmer-Lemeshow test showed no significant deviation from the predicted probabilities. And the cutoff for nomogram total points was about 200 (specificity 0.881 and sensitivity 0.834). The constructed nomogram demonstrated robust predictive performance for major postoperative complications in meningioma patients. This model can be used by surgeons as a reference in clinical decision-making.