A Systematic Review and Meta-Analysis of Clinicopathologic Factors Predicting Upper Urinary Tract Recurrence After Radical Cystectomy for Urothelial Bladder Cancer
Language English Country United States Media print-electronic
Document type Meta-Analysis, Systematic Review, Journal Article
PubMed
36513557
DOI
10.1016/j.clgc.2022.11.002
PII: S1558-7673(22)00236-1
Knihovny.cz E-resources
- Keywords
- Relapse, Survellance, Transitional cell carcinoma, Ureteral margin, Urothelial carcinoma,
- MeSH
- Cystectomy methods MeSH
- Carcinoma, Transitional Cell * surgery pathology MeSH
- Humans MeSH
- Neoplasm Recurrence, Local epidemiology surgery MeSH
- Urinary Tract * pathology MeSH
- Urinary Bladder pathology MeSH
- Urinary Bladder Neoplasms * surgery pathology MeSH
- Prognosis MeSH
- Retrospective Studies MeSH
- Models, Statistical MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Meta-Analysis MeSH
- Systematic Review MeSH
To identify risk factors for upper urinary tract recurrence (UUTR) in patients treated with radical cystectomy (RC) for urothelial bladder carcinoma (UBC). The PubMed, Web of Science, and Cochrane Library were searched on March 2022 to identify relevant studies according to the Preferred Reporting Items for Systematic Review (PRISMA) statement. We included studies that provided multivariate logistic regression analyses. The pooled UUTR rate was calculated using a fixed effect model. We identified 235 papers, of which seven and 6 articles, comprising a total of 8981 and 8404 UBC patients, were selected for qualitative and quantitative analyses, respectively. Overall, 418 (4.65%) patients were diagnosed with UUTR within a median time of 1.4 to 3.1 years after RC. Risk factors for UUTR were surgical margin (hazard ratio [HR] 3.41, 95% confidence interval [CI] 2.59-4.49, P < .00001), preoperative hydronephrosis (HR: 1.74, 95% CI: 1.25-2.43, P = .001), ureteral margin (HR: 4.34, 95% CI: 2.75-6.85, P < .00001), and pT stage (HR: 2.69, 95% CI: 1.37-5.27, P < .004). Incorporation of established risk factors into a clinical prediction model might aid in the decision-making process regarding the intensity and type of surveillance protocols after RC as well as help determine the pretest probability of UUTR.
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