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The diagnostic value of parallel detection of cytokeratin 19 fragment-based tumor markers in malignant pleural effusion: a systematic review and metaanalysis

Background: Cytokeratin 19 Fragment (CYFRA 21-1) is one of the commonly used tumor markers in clinical practice. The examination of CYFRA 21-1 in pleural effusions may help establish the diagnosis of Malignant Pleural Effusion (MPE). However, given the relatively low sensitivity, it is often used in combination with other tumor markers. Thus, we performed this systematic review and meta-analysis, aiming to explore the diagnostic performance of parallel diagnostic algorithms based on CYFRA 21-1 in MPE.

Material and Methods: The databases of Pubmed, Embase and the Cochrane Library were searched from their inception to February 2015 for eligible studies. We included studies that reported the performance of CYFRA 21-1 plus another tumor marker for diagnosing MPE. The STATA software was employed for data analysis, using the bivariate random-effects model. However, when only less than four records were included, the Meta-Disc software was used for data processing.

Results: Eleven studies assessed the diagnostic performance of pleural CYFRA 21-1 plus CEA for MPE. The pooled data showed that the sensitivity was 88% (76%-94%) and the specificity was 87% (83%-90%). The Positive Likelihood Ratio (PLR) was 6.6 (4.8-8.9), and the negative LR (NLR) was 0.14 (0.07-0.29). Four studies reported the diagnostic accuracy of pleural CYFRA 21-1 plus serum CYFRA 21-1 in MPE. The aggregated results revealed that the sensitivity was 76% (66%-84%), with a specificity of 87% (75%-93%). The PLR was 5.7 (2.8-11.5), with a NLR of 0.28 (0.19-0.41).

Conclusions: The parallel diagnostic algorithms, including pleural CYFRA 21-1 plus CEA, and pleural CYFRA 21-1 plus serum CYFRA 21-1, showed satisfactory and reliable diagnostic values in MPE. When compared with single tumor marker, the parallel test substantially increased the sensitivity and the diagnostic accuracy.

Author(s): Yan Gu, Xiaojuan Qiao, Lihong Wang, Xiuhua Fu