Journal
ONCOTARGET
Volume 8, Issue 59, Pages 100648-100656Publisher
IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.22065
Keywords
bladder cancer; NMP22 BladderChek test; diagnostic; systematic review; meta-analysis
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Funding
- National Natural Science Foundation of China [81570676, 81100532, 81470981]
- Science and Education Health Project of Jiangsu Province for Important Talent [RC2011055]
- 333 High Level Talents Project in Jiangsu Province, China [BRA2015469, BRA2016514]
- Standardized Diagnosis and Treatment Research Program of Key Diseases in Jiangsu Province, China [BE2016791]
- Open Project Program of Health Department of Jiangsu Province, China [JSY-2-2016-099]
- Jiangsu Province Six Talents Peak from Department of Human Resources, Social Security Office of Jiangsu Province, China [2010WSN-56, 2011-WS-033]
- General Program of Health Department of Jiangsu Province, China [H2009907]
- Priority Academic Program Development of Jiangsu Higher Education Institutions [JX10231801]
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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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