An Externally Validated Dynamic Nomogram for Predicting Unfavorable Prognosis in Patients With Aneurysmal Subarachnoid Hemorrhage

Abstract

Background: Aneurysmal subarachnoid hemorrhage (aSAH) leads to severe disability and functional dependence. However, no reliable method exists to predict the clinical prognosis after aSAH. Thus, this study aimed to develop a web-based dynamic nomogram to precisely evaluate the risk of poor outcomes in patients with aSAH.Methods: Clinical patient data were retrospectively analyzed at two medical centers. One center with 126 patients was used to develop the model. Least absolute shrinkage and selection operator (LASSO) analysis was used to select the optimal variables. Multivariable logistic regression was applied to identify independent prognostic factors and construct a nomogram based on the selected variables. The C-index and Hosmer–Lemeshow p-value and Brier score was used to reflect the discrimination and calibration capacities of the model. Receiver operating characteristic curve and calibration curve (1,000 bootstrap resamples) were generated for internal validation, while another center with 84 patients was used to validate the model externally. Decision curve analysis (DCA) and clinical impact curves (CICs) were used to evaluate the clinical usefulness of the nomogram.Results: Unfavorable prognosis was observed in 46 (37%) patients in the training cohort and 24 (29%) patients in the external validation cohort. The independent prognostic factors of the nomogram, including neutrophil-to-lymphocyte ratio (NLR) (p = 0.005), World Federation of Neurosurgical Societies (WFNS) grade (p = 0.002), and delayed cerebral ischemia (DCI) (p = 0.0003), were identified using LASSO and multivariable logistic regression. A dynamic nomogram (https://hu-ping.shinyapps.io/DynNomapp/) was developed. The nomogram model demonstrated excellent discrimination, with a bias-corrected C-index of 0.85, and calibration capacities (Hosmer–Lemeshow p-value, 0.412; Brier score, 0.12) in the training cohort. Application of the model to the external validation cohort yielded a C-index of 0.84 and a Brier score of 0.13. Both DCA and CIC showed a superior overall net benefit over the entire range of threshold probabilities.Conclusion: This study identified that NLR on admission, WFNS grade, and DCI independently predicted unfavorable prognosis in patients with aSAH. These factors were used to develop a web-based dynamic nomogram application to calculate the precise probability of a poor patient outcome. This tool will benefit personalized treatment and patient management and help neurosurgeons make better clinical decisions.

A novel visual dynamic nomogram to online predict the risk of unfavorable outcome in elderly aSAH patients after endovascular coiling: A retrospective study

“…Our nomogram showed better performance, in spite of requiring only 4 variables for calculating probability versus 5 and 9. Our nomogram might seem consistent with the published performance of the dynamic nomogram (AUC 0.885) ( Hu et al, 2021 ). Smaller data, however, was used for establishing the dynamic nomogram compared with our nomogram.…”

“…Our nomogram showed better performance. To our knowledge, four nomograms were developed and the performance of the nomograms yielded AUCs ranging from 0.784 to 0.885 ( Zhang et al, 2020 ; Hu et al, 2021 ; Wang et al, 2021 ; Yan et al, 2021 ). Two nomograms reached an AUC of 0.831 and 0.851 for incorporating free fatty acids and SIRI, respectively ( Zhang et al, 2020 ; Wang et al, 2021 ).…”

“…In our investigation for prediction nomograms of aSAH outcome, four prediction models were developed in whole aSAH patients, but not in elderly aSAH patients. The performance of these prediction nomograms yielded AUCs ranging from 0.784 to 0.885 ( Zhang et al, 2020 ; Hu et al, 2021 ; Wang et al, 2021 ; Yan et al, 2021 ). These previous studies, although not predicting elderly patients, have proven the efficacy and potential of nomogram approaches in aSAH medical fields.…”

Neutrophil to lymphocyte ratio predicting poor outcome after aneurysmal subarachnoid hemorrhage: A retrospective study and updated meta-analysis

“…found that NLR was negatively correlated with mean cerebral blood flow (mCBF) in brain CT perfusion scan of aSAH patients, and positively correlated with mean transit time (MTT) and mean time to peak (mTTP), suggesting slow and insufficient cerebral blood flow ( 5 ). Many studies have reported that elevated NLR can predict DCI occurrence after aSAH ( 9 , 22 , 23 ), whereas some studies have denied the correlation between them ( 19 ), so we conducted a meta-analysis of relevant literature. As mentioned above, our results show that elevated NLR is significantly correlated with the DCI occurrence after aSAH.…”

A Comparison of LASSO Regression and Tree-Based Models for Delayed Cerebral Ischemia in Elderly Patients With Subarachnoid Hemorrhage

“…The LASSO regression as a special method performs well when reducing data dimensions and multicollinearity among features. For instance, our previous study ( 26 ) used the LASSO method to select three optimal variables for establishing a dynamic nomogram for predicting an unfavorable prognosis after aSAH in the case of limited effective sample size. In this study, the optimal independent risk factor for DCI prediction in elderly patients were CT value of subarachnoid clots and aneurysmal treatment method.…”