Abstract
PURPOSE: The aim of this study was to develop a prognostic nomogram which could predict the prognosis of north Chinese patients with autoimmune cerebellar ataxia (ACA) after immunotherapy. METHODS: Patients with an initial diagnosis of ACA who accepted first-line immunotherapy at our hospital from March 2018 to May 2023 were retrospectively reviewed. Modified Rankin Scale (mRS) was used to evaluate neurological outcomes. According to the mRS scores after immunotherapy, patients with ACA were divided into good prognosis group (mRS 0-2) and poor prognosis group (mRS 3-6). The nomogram for poor prognosis of ACA patients were built based on logistic regression analysis. The validation of the prognostic model was evaluated by concordance index (C-index), calibration curves, and decision curve analyses (DCAs). RESULTS: A total of 86 patients with ACA who received immunotherapy at our hospital were included in this study. They were randomly divided into a training cohort (n = 60) and a validation cohort (n = 26) at a ratio of 7:3. Multivariate analyses revealed that that prognostic variables significantly related to the poor prognosis of ACA were age, elevated cerebrospinal fluid (CSF) albumin (ALB) and abnormal magnetic resonance imaging (MRI). The nomogram was constructed based on above 3 factors. The C-index of the nomogram was 0.935 (95% CI: 0.884-0.991) in the training set and 0.933 (95% CI: 0.763-0.994) in the validation set. The calibration plots for the nomogram showed that predictions of risk of poor prognosis were almost consistent with actual observations. The DCAs showed great clinical usefulness of the nomograms. CONCLUSION: We successfully developed a nomogram to predict poor prognosis for ACA patients using risk factors of age, elevated CSF-ALB and abnormal MRI.