Ankaferd versus Immunotherapeutics and Chemotherapeutics in Bladder Cancer

Accurate prognostic tools for cystitis remain limited. This study aimed to develop and validate a nomogram-based prediction model and explore the prognostic value of serum amyloid A (SAA), advanced oxidation protein products (AOPP) and endothelial nitric oxide synthase (eNOS).

A total of 234 patients diagnosed with cystitis from March 2022 to December 2024 were assigned to a training cohort (n = 164) and a validation cohort (n = 70) in a 7:3 ratio. In the training cohort, independent prognostic risk factors were identified through univariate and subsequent multivariate logistic regression. These factors were then incorporated into a prognostic nomogram. The model's performance was assessed using receiver operating characteristic (ROC) curve analysis, calibration plots and decision curve analysis (DCA). An internal validation was subsequently performed using an independent validation set.

In the training cohort, 52 patients (31.71%) experienced a poor prognosis, compared with 22 patients (31.4%) in the validation cohort. No significant differences were observed in baseline characteristics or the incidence of poor prognosis between the two cohorts (p > 0.05). Multivariate analysis identified the following independent risk factors for a poor prognosis: elevated SAA levels, increased AOPP levels, decreased eNOS levels, comorbid diabetes mellitus, age of 60 years or older and a disease duration exceeding 3 months (all p < 0.05). The nomogram demonstrated favourable discriminatory ability, with an area under the ROC curve of 0.838 (95% confidence interval (CI): 0.757-0.919) in the training set and 0.735 (95% CI: 0.588-0.902) in the validation set.

The nomogram incorporating SAA, AOPP, eNOS and clinical factors demonstrates promising prognostic performance for patients with cystitis, serving as a potential tool for the early identification of high-risk individuals and supporting optimised treatment strategies.