Diagnostic value of urinary survivin as a biomarker for bladder cancer: a systematic review and meta-analysis of published studies

  • Zhenzhen Liang
  • Rui Xin
  • Yinghui Yu
  • Rui Wang
  • Chunpeng Wang
  • Xin Liu
Original Article
  • 78 Downloads

Abstract

Objective

This study is a meta-analysis and aims to determine the value of urinary survivin for detecting bladder cancer (BC) on the basis of preceding statistical performance and to compare their diagnostic value.

Materials and methods

Considering that the urinary survivin data were from both RNA and protein levels, the key words “bladder cancer” AND “survivin” and “bladder cancer” AND “survivin RNA” were used; and PubMed, Web of Science, and Cochrane Library were systematically searched to identify relevant articles. The methodological quality of each study was assessed by QUADAS-2. Data were analyzed by STATA 12.0 and Meta-disc v.1.4 software package. A random-effects model was used and subgroup analysis was carried out to identify possible sources of heterogeneity.

Results

Nine articles for survivin protein test with 789 patients and 684 controls, and 12 articles for survivin RNA test with 880 patients and 922 controls were identified. The results showed that the pooled sensitivity was 0.79 (95% CI 0.73, 0.84), specificity was 0.87 (95% CI 0.79, 0.92) of the survivin protein test for bladder cancer, and the sensitivity and specificity was 0.84 (95% CI 0.79, 0.88) and 0.94 (95% CI 0.89, 0.97) of the survivin RNA test. The AUC of the two approaches was 0.89 (95% CI 0.86, 0.91) and 0.94 (95% CI 0.92, 0.96), respectively.

Conclusions

The survivin protein and survivin RNA both had great potential as biomarkers for BC detection, and survivin RNA showed higher accuracy than survivin protein on BC diagnosis.

Keywords

Bladder cancer Survivin Diagnosis Meta-analysis 

Notes

Acknowledgements

This study was supported by Technology Project of the Department of Health of Jilin Province (Grant No. 2016J044).

Authors’ contribution

Protocol/project development XL. Data collection or management XL, ZZL, QZ. Data analysis ZZL, RX. Investigation CPW, QZ. Methodology XL. Project administration ZZL. Software FS. Supervision RX. Validation XL. Visualization ZZL, QZ. Writing—original draft ZZL, FS, QZ. Writing—review and editing XL, CPW.

Compliance with ethical standards

Conflicts of interest

None declared.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Epidemiology and Statistics, School of Public HealthJilin UniversityChangchunChina
  2. 2.Department RadiologyThe 2nd Hospital Affiliated to Jilin UniversityChangchunChina
  3. 3.School of Mathematics and StatisticsNortheast Normal UniversityChangchunChina

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