scholarly journals ­Silent Existence of Eosinopenia in Sepsis: A Systematic Review and Meta-Analysis

2020 ◽  
Author(s):  
Yao Lin ◽  
Jiabing Rong ◽  
Zhaocai Zhang
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Medical Emergency ◽  
Cochrane Central Register ◽  
Analysis Model ◽  
Potential Biomarker

Abstract BackgroundSepsis is a life-threatening and time-critical medical emergency; therefore, the early diagnosis of sepsis is essential to timely treatment and favorable outcomes for patients susceptible to sepsis. Eosinopenia has been identified as a potential biomarker of sepsis in the past decade. However, its clinical application progress is slow and its recognition is low. Recent studies have again focused on the potential association between Eosinopenia and severe infections. This study analyzed the efficacy of Eosinopenia as a biomarker for diagnosis of sepsis and its correlation with pathophysiology of sepsis.MethodWe searched PubMed, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials CENTRAL databases to identify studies that met the inclusion criteria. Two authors performed data extraction independently. The pooled outcomes were calculated by TP (true positive), FP (false positive), FN (false negative), TN (true negative) by using bivariate meta-analysis model in STATA 14.0 software. Meanwhile, possible mechanisms of sepsis induced Eosinopenia was also analyzed.ResultsSeven studies were included in the present study with a total number of 3842 subjects. The incidence of Eosinopenia based on the enrolled studies varied from 23.2% to 92.7%. For diagnosis of sepsis, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio of Eosinopenia were 0.66 (95%CI [0.53-0.77]), 0.68 (95%CI [0.56-0.79]), 2.09 (95%CI [1.44-3.02]), 0.49 (95%CI [0.34-0.71]) and 4.23 (95%CI [2.15-8.31]), respectively. The area under the summary receiver operator characteristic curve (SROC) was 0.73 (95%CI [0.68-0.76]). Meta-regression analysis revealed that no single parameter accounted for the heterogeneity of pooled outcomes. For each subgroup of different eosinopenia cutoff values (50, 40, ≤25, 100), the sensitivity was 0.61, 0.79, 0.57, 0.54, and the specificity was 0.61, 0.75, 0.83, 0.51, respectively. ConclusionsOur findings suggested that Eosinopenia has a high incidence in sepsis but has no superiority in comparison with conventional biomarkers for diagnosis of sepsis. However, eosinopenia can still be used in clinical diagnosis for sepsis as a simple, convenient, fast and inexpensive biomarker. Therefore, further large clinical trials are still needed to re-evaluate eosinopenia as a biomarker of sepsis.

scholarly journals ­Revisit Eosinopenia as a Biomarker for Diagnosis of Sepsis: A Meta-Analysis

2020 ◽  
Author(s):  
Yao Lin ◽  
Jiabing Rong ◽  
Zhaocai Zhang
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Medical Emergency ◽  
Cochrane Central Register ◽  
Analysis Model ◽  
Potential Biomarker

Abstract BackgroundSepsis is a life-threatening and time-critical medical emergency, therefore, the early diagnosis of sepsis is essential to timely treatment and favorable outcomes for patients susceptible to sepsis. Eosinopenia has been identified as a potential biomarker of sepsis in the past decade. So, we performed a meta-analysis to assess the diagnostic efficacy of eosinopenia for sepsis.MethodWe searched PubMed, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials CENTRAL databases to identify studies that met the inclusion criteria. Two authors performed data extraction independently. The pooled outcomes were calculated by TP (true positive), FP (false positive), FN (false negative), TN (true negative) by using bivariate meta-analysis model in STATA 14.0 software. ResultsSeven studies were included in the present study with a total number of 3842 subjects. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were 0.66 (95%CI [0.53-0.77]), 0.68 (95%CI [0.56-0.79]), 2.09 (95%CI [1.44-3.02]), 0.49 (95%CI [0.34-0.71]) and 4.23 (95%CI [2.15-8.31]), respectively. The area under the summary receiver operator characteristic curve (SROC) was 0.73 (95%CI [0.68-0.76]). Meta-regression analysis revealed that no single parameter accounted for the heterogeneity of pooled outcomes. For each subgroup of different eosinopenia cutoff values (50, 40, <=25, 100), the sensitivity was 0.61, 0.79, 0.57, 0.54, and the specificity was 0.61, 0.75, 0.83, 0.51, respectively. ConclusionsOur findings suggest that eosinopenia shows no superiority in the diagnosis of sepsis. Further large clinical trials are needed to re-evaluate eosinopenia as a biomarker of sepsis.

scholarly journals Silent existence of eosinopenia in sepsis: a systematic review and meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yao Lin ◽  
Jiabing Rong ◽  
Zhaocai Zhang
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
False Negative ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Medical Emergency ◽  
Cochrane Central Register ◽  
Analysis Model ◽  
Potential Biomarker

Abstract Background Sepsis is a life-threatening and time-critical medical emergency; therefore, the early diagnosis of sepsis is essential to timely treatment and favorable outcomes for patients susceptible to sepsis. Eosinopenia has been identified as a potential biomarker of sepsis in the past decade. However, its clinical application progress is slow and its recognition is low. Recent studies have again focused on the potential association between Eosinopenia and severe infections. This study analyzed the efficacy of Eosinopenia as a biomarker for diagnosis of sepsis and its correlation with pathophysiology of sepsis. Method The protocol for this meta-analysis is available in PROSPERO (CRD42020197664). We searched PubMed, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials CENTRAL databases to identify studies that met the inclusion criteria. Two authors performed data extraction independently. The pooled outcomes were calculated by TP (true positive), FP (false positive), FN (false negative), TN (true negative) by using bivariate meta-analysis model in STATA 14.0 software. Meanwhile, possible mechanisms of sepsis induced Eosinopenia was also analyzed. Results Seven studies were included in the present study with a total number of 3842 subjects. The incidence of Eosinopenia based on the enrolled studies varied from 23.2 to 92.7%. For diagnosis of sepsis, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio of Eosinopenia were 0.66 (95%CI [0.53–0.77]), 0.68 (95%CI [0.56–0.79]), 2.09 (95%CI [1.44–3.02]), 0.49 (95%CI [0.34–0.71]) and 4.23 (95%CI [2.15–8.31]), respectively. The area under the summary receiver operator characteristic curve (SROC) was 0.73 (95%CI [0.68–0.76]). Meta-regression analysis revealed that no single parameter accounted for the heterogeneity of pooled outcomes. For each subgroup of different eosinopenia cutoff values (50, 40, ≤25, 100), the sensitivity was 0.61, 0.79, 0.57, 0.54, and the specificity was 0.61, 0.75, 0.83, 0.51, respectively. Conclusions Our findings suggested that Eosinopenia has a high incidence in sepsis but has no superiority in comparison with conventional biomarkers for diagnosis of sepsis. However, eosinopenia can still be used in clinical diagnosis for sepsis as a simple, convenient, fast and inexpensive biomarker. Therefore, further large clinical trials are still needed to re-evaluate eosinopenia as a biomarker of sepsis.

scholarly journals Diagnostic Value of T-SPOT.TB Assay for Tuberculous Peritonitis: A Meta-Analysis

2020 ◽  
Vol 7 ◽  
Author(s):  
Ying Luo ◽  
Ying Xue ◽  
Liyan Mao ◽  
Qun Lin ◽  
Guoxing Tang ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Abdominal Tuberculosis ◽  
Tuberculous Peritonitis ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Background: Tuberculous peritonitis (TP) is a common form of abdominal tuberculosis (TB). Diagnosing TP remains challenging in clinical practice. The aim of the present meta-analysis was to evaluate the diagnostic accuracy of peripheral blood (PB) T-SPOT and peritoneal fluid (PF) T-SPOT for diagnosing TP.Methods: PubMed, EmBase, Cochrane, Scopus, Google scholar, China national knowledge internet, and Wan-Fang databases were searched for relevant articles from August 1, 2005 to July 5, 2020. Statistical analysis was performed using Stata, Revman, and Meta-Disc software. Diagnostic parameters including pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were determined. Summary receiver operating characteristic curve was used to determine the area under the curve (AUC).Results: Twelve studies were eligible and included in the meta-analysis. The analysis showed that the pooled sensitivity and specificity of PB T-SPOT in diagnosing TP were 0.91 (95% CI, 0.88–0.94) and 0.78 (95% CI, 0.73–0.81), respectively, while the pooled PLR, NLR, and DOR were 4.05 (95% CI, 2.73–6.01), 0.13 (95% CI, 0.07–0.23), and 37.8 (95% CI, 15.04–94.98), respectively. On the other hand, the summary estimates of sensitivity, specificity, PLR, NLR, and DOR of PF T-SPOT for TP diagnosis were 0.90 (95% CI, 0.85–0.94), 0.78 (95% CI, 0.72–0.83), 6.35 (95% CI, 2.67–15.07), 0.14 (95% CI, 0.09–0.21), and 58.22 (95% CI, 28.76–117.83), respectively. Furthermore, the AUC of PB T-SPOT and PF T-SPOT for TP diagnosis were 0.91 and 0.94, respectively.Conclusions: Our results indicate that both PB T-SPOT and PF T-SPOT can be served as sensitive approaches for the diagnosis of TP. However, the unsatisfactory specificities of these two methods limit their application as rule-in tests for TP diagnosis. Furthermore, the standardization of the operating procedure of PF T-SPOT is further needed.

scholarly journals The Diagnostic Accuracy of HE4 in Lung Cancer: A Meta-Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Daye Cheng ◽  
Ying Sun ◽  
Hu He
Keyword(s):  
Lung Cancer ◽  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Large Sample Size ◽  
Summary Receiver Operating Characteristic ◽  
Diagnosis Of Lung Cancer

The diagnostic value of serum HE4 in patients with lung cancer remains controversial. Thus, we performed a systematic review and meta-analysis to assess the diagnostic accuracy of serum HE4 for lung cancer. We conducted a comprehensive literature search in PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI), and WANFANG databases between Jan. 1966 and Nov. 2014. The diagnostic sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic curve (SROC) were pooled by Meta-DiSc 1.4 software. A total of seven articles including 715 cases and 549 controls were included for analysis. The summary estimates for serum HE4 in the diagnosis of lung cancer in these studies were pooled SEN 0.72 (95% CI: 0.68–0.75), SPE 0.85 (95% CI: 0.81–0.88), PLR 4.68 (95% CI: 3.23–6.78), NLR 0.31 (95% CI: 0.24–0.39), and DOR 17.14 (95% CI: 9.72–30.20), and the area under the curve (AUC) was 0.8557. This meta-analysis indicated that serum HE4 is a potential tool in the diagnosis of lung cancer. In addition, considering the high heterogeneity and potential publication bias, further studies with rigorous design and large sample size are needed in the future.

scholarly journals Artificial Intelligence in Gastric Cancer: Identifying Gastric Cancer Using Endoscopic Images with Convolutional Neural Network

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5253
Author(s):  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
Bruno Andreas Walther ◽  
Ming-Chin Lin ◽  
Yu-Chuan (Jack) Li
Keyword(s):  
Gastric Cancer ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Work Load ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Gastric cancer (GC) is one of the most newly diagnosed cancers and the fifth leading cause of death globally. Identification of early gastric cancer (EGC) can ensure quick treatment and reduce significant mortality. Therefore, we aimed to conduct a systematic review with a meta-analysis of current literature to evaluate the performance of the CNN model in detecting EGC. We conducted a systematic search in the online databases (e.g., PubMed, Embase, and Web of Science) for all relevant original studies on the subject of CNN in EGC published between January 1, 2010, and March 26, 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 was used to assess the risk of bias. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Moreover, a summary receiver operating characteristic curve (SROC) was plotted. Of the 171 studies retrieved, 15 studies met inclusion criteria. The application of the CNN model in the diagnosis of EGC achieved a SROC of 0.95, with corresponding sensitivity of 0.89 (0.88–0.89), and specificity of 0.89 (0.89–0.90). Pooled sensitivity and specificity for experts endoscopists were 0.77 (0.76–0.78), and 0.92 (0.91–0.93), respectively. However, the overall SROC for the CNN model and expert endoscopists was 0.95 and 0.90. The findings of this comprehensive study show that CNN model exhibited comparable performance to endoscopists in the diagnosis of EGC using digital endoscopy images. Given its scalability, the CNN model could enhance the performance of endoscopists to correctly stratify EGC patients and reduce work load.

scholarly journals The value of miR-155 as a biomarker for the diagnosis and prognosis of lung cancer: a systematic review with meta-analysis

2019 ◽  
Author(s):  
Chuchu Shao ◽  
Fengming Yang ◽  
Zhiqiang Qin ◽  
Xinming Jing ◽  
Yongqian Shu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Systematic Review ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Disease Free Survival ◽  
Negative Likelihood Ratio ◽  
Free Survival ◽  
Diagnosis And Prognosis ◽  
Potential Biomarker

Abstract Background: Recently, a growing number of studies have reported the coorelation between miR-155 and the diagnosis and prognosis of lung cancer, but results of these researches were still controversial due to insufficient sample size. Thus, we carried out the systematic review and meta-analysis to figure out whether miR-155 could be a screening tool in the detection and prognosis of lung cancer. Methods: A meta-analysis of 13 articles with 19 studies was performed by retrieving the PubMed, Embase and Web of Science. We screened all correlated literaters until December 1st, 2018. For the diagnosis analysis of miR-155 in lung cancer, sensitivity(SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and area under the ROC curve (AUC) were pooled to evaluate the accuracy of miRNA-155 in the diagnosis of lung cancer. For the prognosis analysis of miR-155 in lung cancer, the pooled HRs and 95% CIs of miR-155 for overall survival/disease free survival/progression-free survival (OS/DFS/PFS) were calculated. In addition, Subgroup and meta-regression analyses were performed to distinguish the potential sources of heterogeneity between studies. Results: For the diagnostic analysis of miR-155 in lung cancer, the pooled SEN and SPE were 0.82 (95% CI: 0.72-0.88) and 0.78 (95% CI: 0.71-0.84), respectively. Besides, the pooled PLR was 3.75 (95% CI: 2.76-5.10), NLR was 0.23 (95% CI: 0.15-0.37), DOR was 15.99 (95% CI: 8.11-31.52) and AUC was 0.87 (95% CI: 0.84-0.90), indicating a significant value of miR-155 in the lung cancer detection. For the prognostic analysis of miR-155 in lung cancer, up-regulated miRNA-155 expression was not significantly associated with a poor OS (pooled HR = 1.26, 95% CI: 0.66-2.40) or DFS/PFS (pooled HR = 1.28, 95% CI: 0.82-1.97). Conclusions: The present meta-analysis demonstrated that miR-155 could be a potential biomarker for the detection of lung cancer but not an effective biomarker for predicting the outcomes of lung cancer. Furthermore, more well-designed researches with larger cohorts were warranted to confirm the value of miR-155 for the diagnosis and prognosis of lung cancer.

scholarly journals Diagnostic value of circulating tumor DNA as an effective biomarker in cervical cancer: a meta-analysis

2019 ◽  
Author(s):  
Yulan Gu ◽  
Chuandan Wan ◽  
Jiaming Qiu ◽  
Yanhong Cui ◽  
Tingwang Jiang
Keyword(s):  
Cervical Cancer ◽  
Likelihood Ratio ◽  
Large Scale ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Value ◽  
Circulating Tumor Dna ◽  
Tumor Dna

AbstractThe applications of liquid biopsy have attracted much attention in biomedical research in recent years. Circulating cell-free DNA (cfDNA) in the serum may serve as a unique tumor marker in various types of cancer. Circulating tumor DNA (ctDNA) is a type of serum cfDNA found in patients with cancer and contains abundant information regarding tumor characteristics, highlighting its potential diagnostic value in the clinical setting. However, the diagnostic value of cfDNA as a biomarker in cervical cancer remains unclear. Here, we performed a meta-analysis to evaluate the applications of ctDNA as a biomarker in cervical cancer. A systematic literature search was performed using PubMed, Embase, and WANFANG MED ONLINE databases up to March 18, 2019. All literature was analyzed using Meta Disc 1.4 and STATA 14.0 software. Diagnostic measures of accuracy of ctDNA in cervical cancer were pooled and investigated. Fifteen studies comprising 1109 patients with cervical cancer met our inclusion criteria and were subjected to analysis. The pooled sensitivity and specificity were 0.52 (95% confidence interval [CI], 0.33–0.71) and 0.97 (95% CI, 0.91–0.99), respectively. The pooled positive likelihood ratio and negative likelihood ratio were 16.0 (95% CI, 5.5–46.4) and 0.50 (95% CI, 0.33–0.75), respectively. The diagnostic odds ratio was 32 (95% CI, 10–108), and the area under the summary receiver operating characteristic curve was 0.92 (95% CI, 0.90– 0.94). There was no significant publication bias observed. In the included studies, ctDNA showed clear diagnostic value for diagnosing and monitoring cervical cancer. Our meta-analysis suggested that detection of human papilloma virus ctDNA in patients with cervical cancer could be used as a noninvasive early dynamic biomarker of tumors, with high specificity and moderate sensitivity. Further large-scale prospective studies are required to validate the factors that may influence the accuracy of cervical cancer diagnosis and monitoring.

Diagnostic value of HOX transcript antisense RNA for cancer detection: a meta-analysis

2020 ◽  
Vol 14 (5) ◽  
pp. 401-411
Author(s):  
Weihao Kong ◽  
Mingwei Yang ◽  
Yunfeng Zhu ◽  
Xiaomin Zuo ◽  
Hengyi Wang ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Antisense Rna ◽  
Noncoding Rna ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Sensitivity Specificity

Aim: Numerous studies have investigated the diagnostic role of long noncoding RNA HOX transcript antisense RNA in cancers, but its diagnostic efficacy is inconsistent. Methods: The PubMed, Embase, Web of Science and Cochrane Library databases are used to retrieve relevant studies. The bivariate effect model was used to compute the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve. Results: A total of 13 studies were included in this meta-analysis. The combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the receiver operating characteristic curve were: 0.77, 0.83, 4.7, 0.28, 17 and 0.87, respectively. Deeks’ funnel plot test (p = 0.103) indicated no publication bias. Conclusion: Long noncoding RNA HOX transcript antisense RNA may be a useful biomarker for cancer detection.

scholarly journals The value of ultrasound in diagnosis of pneumoperitoneum in emergent or critical conditions: A meta-analysis

2018 ◽  
Vol 26 (2) ◽  
pp. 111-117 ◽  
Author(s):  
Libing Jiang ◽  
Jing Wu ◽  
Xia Feng
Keyword(s):  
Confidence Interval ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Abdominal Ultrasound ◽  
Critical Conditions ◽  
Cochrane Library ◽  
Summary Receiver Operating Characteristic

Background: Hollow organs perforation is a life-threatening condition. Early diagnosis and emergent intervention are important. Bedside ultrasound may be an alternative diagnostic tool for this condition. Objective: The aim of this study was to explore the diagnostic value of ultrasound of pneumoperitoneum in emergent or critical conditions through meta-analysis. Methods: PubMed, EMBASE, and Cochrane Library were systematically searched for potential studies. Then, two reviewers performed the processes of study selection, data extraction, and quality assessment independently. Finally, diagnostic indexes were analyzed with STATA 12.0 software (Serial No. 40120519635). Results: A total of five studies with moderate to high quality were eligible for meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio and their 95% confidence interval were 0.91 (95% confidence interval = 0.86–0.94), 0.96 (95% confidence interval = 0.75–0.99), 22.05 (95% confidence interval = 3.10–156.96), and 0.10 (95% confidence interval = 0.07–0.15), respectively. The area under the summary receiver operating characteristic curve was 0.92 (95% confidence interval = 0.90–0.94). Conclusion: Abdominal ultrasound is a useful alternative tool in diagnosing of pneumoperitoneum. However, due to limited evidence, it is not yet indicated for routine clinical use.

scholarly journals Pentraxin 3 as a promising biomarker for cancer detection: a systematic review and meta-analysis

2019 ◽  
Author(s):  
Qindong Liang ◽  
Guangjie Zhang ◽  
Huaan Huang ◽  
Nai Xing ◽  
Shangchun Sheng ◽  
...  
Keyword(s):  
Systematic Review ◽  
Likelihood Ratio ◽  
Cancer Detection ◽  
Large Scale ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Cochrane Library ◽  
Pentraxin 3 ◽  
Potential Biomarker

Abstract Background Mounting studies reported that circulating pentraxin 3 (PTX3) expression level was significantly different between cancer patients and healthy groups, suggesting that PTX3 may be a potential biomarker for cancer detection. However, the results were inconsistent. In this paper, a systematic review and meta-analysis was performed to quantitatively assess the diagnostic value of PTX3 in cancer detection.Methods A comprehensive computerized literature search was conducted in Embase, PubMed, Cochrane Library, Web of Science, Chinese National Knowledge Infrastructure (CNKI) from inception to July 31, 2019. Eligible studies were identified and raw data were extracted. Diagnostic estimates were synthesized using STATA (version 12.0) and MetaDisc (version 1.4) statistical software.Results Overall, 9 studies from 8 citations with a total of 1408 cancer patiens and 3116 controls were included in this meta-analysis. The global sensitivity was 0.70 (95% confidence interval (CI): 0.67 – 0.72), and the specificity was 0.77 (95% CI: 0.75 – 0.78). The pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and the diagnostic odds ratio (DOR) were 2.86 (95% CI: 2.29 – 3.56), 0.40 (95% CI: 0.32 – 0.50) and 7.38 (95% CI: 5.05 – 10.78), respectively. The merged AUC was 0.80 (95% CI: 0.76 – 0.83).Conclusion The serum PTX3 appears to be a reliable biomarker for cancer detection though large-scale multicenter studies are needed.

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