| Literature DB >> 30509965 |
Zhanzhan Li1, Yanyan Li2, Jun Fu1, Na Li1, Liangfang Shen3.
Abstract
We conducted comprehensive analyses to assess the diagnostic ability of miRNA-451 in cancers. A systematic online search was conducted in PubMed, Web of Science, China's national knowledge infrastructure, and VIP databases from inception to July 31, 2017. The bivariate random effect model was used for calculating sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under cure (AUC). The whole pooled sensitivity and specificity were 0.85 (0.77-0.90) and 0.85 (0.78-0.90) with their 95% confidence interval (95%CI), respectively. The pooled AUC was 0.91 (95%CI: 0.89-0.94). Positive likelihood ratio was 5.57 (95%CI: 3.74-8.31), negative likelihood ratio was 0.18 (95%CI: 0.11-0.28), and diagnostic odds ratio was 31.33 (95%CI: 15.19-64.61). Among Asian population, the sensitivity and specificity were 0.85 (95%CI: 0.77-0.91) and 0.86 (95%CI: 0.78-0.91), respectively. The positive likelihood ratio and negative likelihood ratio were 5.87 (95%CI: 3.78-9.12) and 0.17 (95%CI: 0.11-0.28). The diagnostic odds ratio and AUC were 34.31 (15.51-75.91) and 0.92 (0.89-0.94). The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and AUC for digestive system cancer were 0.83, 0.88, 6.87, 0.20, 35.13, and 0.92, respectively. The other cancers were 0.87, 0.81, 4.55, 0.16, 28.51, and 0.90, respectively. For sample source, the results still remain consistent. Our results indicated miRNA-451 has a moderate diagnostic ability for cancers, and could be a potential early screening biomarker, and considered as an adjuvant diagnostic index when being combined with other clinical examinations.Entities:
Keywords: Cancer; Meta-analysis; MicroRNA-451; Tumor marker
Mesh:
Substances:
Year: 2019 PMID: 30509965 PMCID: PMC6331668 DOI: 10.1042/BSR20180653
Source DB: PubMed Journal: Biosci Rep ISSN: 0144-8463 Impact factor: 3.840
Figure 1Flow diagram of studies selection
General characteristics of included studies in the meta-analysis
| Author | Year of publication | Region | Type of cancer | Source of sample | Methods of examination | Gold standard |
|---|---|---|---|---|---|---|
| Zhang | 2015 | Asia | Thyroid carcinoma | Serum | qRT-PCR | Tissue pathology |
| Yang | 2017 | Asia | Esophageal cancer | Serum | qRT-PCR | Tissue pathology |
| Xie | 2013 | Asia | Esophageal cancer | Saliva | qRT-PCR | Tissue pathology |
| Xie | 2013 | Asia | Esophageal cancer | Saliva | qRT-PCR | Tissue pathology |
| Zhu | 2014 | Asia | Gastric cancer | Plasma | qRT-PCR | Tissue pathology |
| Zhu | 2014 | Asia | Gastric cancer | Plasma | qRT-PCR | Tissue pathology |
| Redova | 2012 | Europe | Renal cell carcinoma | Serum | qRT-PCR | Tissue pathology |
| Pei | 2014 | Asia | Hepatocellular carcinoma | Serum | Real-time PCR | Tissue pathology |
| Konishi | 2012 | Asia | Gastric cancer | Plasma | qRT-PCR | Tissue pathology |
| Phua | 2014 | Asia | Colorectal cancer | Feces | Real-time PCR | Tissue pathology |
| Ng | 2013 | Asia | Breast cancer | Plasma | qRT-PCR | Tissue pathology |
| Luo | 2014 | Asia | Breast cancer | Serum | qRT-PCR | Tissue pathology |
Parameters of included studies in the meta-analysis
| Author | Year | Sample size (case/control) | Total | TP | FP | FN | TN | Sensitivity (%) | Specificity (%) |
|---|---|---|---|---|---|---|---|---|---|
| Zhang | 2015 | 60/60 | 120 | 47 | 18 | 13 | 42 | 78 | 70 |
| Yang | 2017 | 50/20 | 70 | 44 | 3 | 6 | 17 | 88 | 85 |
| Xie | 2013 | 39/19 | 58 | 20 | 3 | 19 | 16 | 85 | 58 |
| Xie | 2013 | 39/19 | 58 | 33 | 8 | 6 | 11 | 51 | 84 |
| Zhu | 2014 | 48/102 | 150 | 33 | 11 | 15 | 91 | 81 | 83 |
| Zhu | 2014 | 72/18 | 90 | 58 | 3 | 14 | 15 | 69 | 89 |
| Redova | 2012 | 90/35 | 125 | 73 | 8 | 17 | 27 | 81 | 77 |
| Pei | 2014 | 66/40 | 106 | 63 | 7 | 3 | 33 | 95 | 82 |
| Konishi | 2012 | 56/30 | 86 | 54 | 0 | 2 | 30 | 96 | 97 |
| Phua | 2014 | 17/28 | 45 | 15 | 0 | 2 | 28 | 88 | 97 |
| Ng | 2013 | 70/50 | 120 | 58 | 4 | 12 | 46 | 83 | 92 |
| Luo | 2014 | 60/29 | 89 | 56 | 6 | 4 | 23 | 93 | 79 |
Summary estimated of diagnostic performance of miR-451 for cancer detection
| Category | SEN (95%CI) | SPE (95%CI) | PLR (95%CI) | NLR (95%CI) | DOR (95%CI) | AUC (95%CI) |
|---|---|---|---|---|---|---|
| 0.85 [0.77–0.90] | 0.85 [0.78–0.90] | 5.57 [3.74–8.31] | 0.18 [0.11–0.28] | 31.33 [15.19–64.61] | 0.91 [0.89–0.94] | |
| Asian | 0.85 [0.77–0.91] | 0.86 [0.78–0.91] | 5.87 [3.78–9.12] | 0.17 [0.11–0.28] | 34.31 [15.51–75.91] | 0.92 [0.89–0.94] |
| Digestive system | 0.83 [0.70–0.91] | 0.88 [0.78–0.94] | 6.87 [3.40–13.90] | 0.20 [0.10–0.37] | 35.13 [10.65–115.93] | 0.92 [0.90–0.94] |
| Other types | 0.87 [0.79–0.92] | 0.81 [0.73–0.87] | 4.55 [3.04–6.80] | 0.16 [0.10–0.27] | 28.51 [12.66–64.20] | 0.90 [0.87–0.92] |
| Serum-based | 0.87 [0.83–0.90] | 0.77 [0.70–0.83] | 3.75 [2.69–5.24] | 0.16 [0.09–0.28] | 27.03 [10.78–67.75] | 0.82 [0.66–0.98] |
| Plasma-based | 0.83 [0.74–0.92] | 0.91 [0.88–0.95] | 8.48 [4.79–15.01] | 0.18 [0.11–0.39] | 55.18 [17.70–172.07] | 0.96 [0.899–1.00] |
Figure 2Forest plot of pooled and each study’s sensitivity of miRNA-451 for cancer
Figure 3Forest plot of pooled and each study’s specificity of miRNA-451 for cancer
Figure 4The symmetric receiver operating characteristic curve of miRNA-451 for cancer
Figure 5Fagan diagram evaluating the overall diagnostic value of miRNA-451 for cancer (If the pre-test probability is 20% for a patient, the post-test probability will be 59% with a PLR of 6)
Figure 6Line regression plot of publication bias (The closer to 0 degree the angel between X-ray gets, the lesser the publication bias gets)