Supplementary Material for: The value of circulating tumor DNA in the prognostic diagnosis of bladder cancer: a systematic review and meta-analysis

Objective: The aim of this study was to systematically evaluate the clinical efficacy of ctDNA in the prognostic assessment of bladder cancer, and to provide a basis for its application in individualized treatment and risk stratification management.
Methods: Studies related to ctDNA in prognostic assessment of bladder cancer were screened by systematically searching PubMed, Cochrane Library, Web of Science, Willey library, CNKI and other databases, and the search was from inception to December 2024, and the data were extracted and analyzed by Meta-analysis. A random-effects model was used to calculate SEN, SPE, PLR, NLR, DOR, and AUC, and the heterogeneity among studies and publication bias were also assessed.
Results: A total of 9 papers were included, and the results showed that ctDNA testing had a SEN of 0.68 (95% CI: 0.54-0.78), SPE of 0.76 (95% CI: 0.51-0.90), and an AUC of 0.75 (95% CI: 0.71-0.79), suggesting that it has a moderate level of diagnostic efficacy in the assessment of prognosis in bladder cancer. PLR and NLR were 2.8 (95% CI: 1.24-6.35) and 0.43 (95% CI: 0.28-0.65), respectively, with a DOR of 6.56 (95% CI: 2.12-20.33).Fagan plot analysis showed that the posterior probability of a positive result rose to 74% and the posterior probability of a negative result decreased to 30% when the prior probability was 50%. Deeks funnel plot analysis showed no significant publication bias (P=0.24). However, inter-study heterogeneity was high (all I² values >80%), which may have been influenced by factors such as assay technique, patient characteristics, and follow-up time.
Conclusion: ctDNA demonstrates some clinical application value in the prognostic assessment of bladder cancer, and can assist in predicting patient recurrence and survival. However, its independent predictive efficacy is not enough to replace traditional assessment methods. Future studies should aim to optimize the detection technology, unify the study design, expand the sample size, and combine multi-omics data for joint analysis, in order to further improve its potential application in the prognostic assessment of bladder cancer.