Development and validation of a Cox model nomogram to predict the recurrence of pulmonary aspergillosis after antifungal therapy

Abstract Background: Recurrence after antifungal therapy is a challenging complication of pulmonary aspergillosis (PA). However, the exact factors associated with the recurrence of PA are still unclear. The aim of this study was to develop and validate a Cox model nomogram for the prediction of the recurrence of PA after antifungal therapy.Methods: A total of 105 patients with PA were enrolled in this retrospective cohort study from January 2018 to December 2020 and followed up at least 12 month. The risk factors for the recurrence of PA were identified and the prediction model was developed using R software. Results: All 105 patients received effective antifungal therapy during their first admission; PA recurred in 18 patients during the follow-up period (mean, 5.5±5.2 months). Cox univariate analysis showed that immune deficiency, C-reactive protein level, galactomannan test (GM test), wheezing, pleural thickening, lung nodules, and prednisone therapy were prognostic factors for overall recurrence of PA after antifungal therapy (P<0.1). Multivariate Cox analysis indicated that pleural thickening and prednisone therapy were independent risk factors for the recurrence of PA (P<0.05). The nomogram plot was constructed based on the results of the univariate and multivariate analyses. The C-index of the predictive model was 0.90, 0.83, 0.81, and 0.81 for the 2- , 4-, 6-, and 8- month follow-up timepoints, respectively. The area under the receiver operating characteristic curve was 0.78, 0.63, and 0.61 for the 3-, 6-, and 12-month follow-up timepoints, respectively. The calibration curve showed a consistent tendency with the actual curve for the 3-month and 6-month follow-up timepoints.Conclusion: Pleural thickening on computed tomography images and prednisone therapy are independent predictive factors for the recurrence of PA after antifungal therapy. The nomogram developed in this study provided accurate individualized estimates for predicting the recurrence of PA.