Oncotarget

Meta-Analysis:

Evaluation of the NMP22 BladderChek test for detecting bladder cancer: a systematic review and meta-analysis

Zijie Wang, Hongliang Que, Chuanjian Suo, Zhijian Han, Jun Tao, Zhengkai Huang, Xiaobin Ju, Ruoyun Tan and Min Gu _

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Oncotarget. 2017; 8:100648-100656. https://doi.org/10.18632/oncotarget.22065

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Abstract

Zijie Wang1,*, Hongliang Que1,*, Chuanjian Suo1,*, Zhijian Han1, Jun Tao1, Zhengkai Huang1, Xiaobin Ju1, Ruoyun Tan1 and Min Gu1

1Department of Urology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, China

*These authors contributed equally to this work

Correspondence to:

Min Gu, email: [email protected]

Ruoyun Tan, email: [email protected]

Keywords: bladder cancer, NMP22 BladderChek test, diagnostic, systematic review, meta-analysis

Received: June 19, 2017     Accepted: September 03, 2017     Published: October 23, 2017

ABSTRACT

Background: We examined the usefulness of the nuclear matrix protein 22 (NMP22) BladderChek test for detecting bladder cancer.

Materials and Methods: A literature search was performed using PubMed, Embase, the Cochrane Library, and Web of Science. The diagnostic accuracy of the NMP22 BladderChek test was evaluated via pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under curve (AUC). Inter-study heterogeneity was explored using meta-regression and subgroup analyses.

Results: We included 23 studies in the systematic review and 19 in the quantitative meta-analysis. Overall sensitivity and specificity were 56% (52–59%) and 88% (87–89%), respectively; pooled PLR and NLR were 4.36 (3.02–6.29) and 0.51 (0.40–0.66), respectively; DOR was 9.29 (5.55–15.55) with an AUC of 0.8295. The mean sensitivity for Ta, T1, ≥ T2, Tis, G1, G2, and G3 disease was 13.68%, 29.49%, 74.03%, 34.62%, 44.16%, 56.25%, and 67.34%, respectively.

Conclusions: The NMP22 BladderChek test shows good discrimination ability for detecting bladder cancer and a high-specificity algorithm that can be used for early detection to rule out patients with higher bladder cancer risk. It also has better potential for screening higher-grade and higher-stage tumors, and better diagnostic performance in Asians.


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