Objective：This meta-analysis sought to assess the overall diagnostic efficacy of long-noncoding RNA（lncRNA）MALAT-1 in lung cancer. Methods：Relevant studies were searched and obtained through the online PubMed，EMbase，EBSCO，CNKI，and Wanfang databases. Data were extracted and study quality of the included studies was assessed. The pooled effect sizes were synthesized and the summary receiver operator characteristic（SROC）curve was plotted using a bivariate meta-analysis model. Sensitivity analysis and meta-regression test were undertaken to identify the potential causes of study heterogeneity. Publication bias was judged by Deeks’ funnel plot asymmetry test. The Z test was used to analyze the difference among pooled AUC values. Results：Five studies comprised of 433 lung cancer patients and 384 paired controls were included. The SROC displayed that the pooled sensitivity，specificity，and area under curve（AUC）of MALAT-1 testing for diagnosing lung cancer were 0.71（95% CI：0.67-0.74），0.82（95% CI：0.79-0.84），and 0.89，respectively. Stratified analyses based on pathological type showed that MALAT-1 testing yielded an AUC of 0.91 in identifying non-small-cell lung cancer（NSCLC），and the AUC was 0.93 in confirming lung squamous cell carcinoma，which was better than that in lung adenocarcinoma（AUC=0.84；Z=1.97，P < 0.05）；moreover，serum-based MALAT-1 testing achieved an efficacy better than plasma-based analysis（AUC：0.94 vs. 0.88；Z=8.96，P < 0.01）. Study based on ethnicity showed that MALAT-1 harbored an AUC of 0.89 in Asian-based analysis，which was equal to that in Caucasian-based analysis（AUC=0.82；Z=1.11，P > 0.05）. Deeks’ funnel plot asymmetry test manifested no clear publication bias among studies（P=0.865）. Conclusion：Circulating MALAT-1 testing reveals promising diagnostic efficacy in identification of lung cancer and therefore might be popularized as auxiliary biomarkers for NSCLC，especially for lung squamous cell carcinoma detection.