Published online May 14, 2020. doi: 10.3748/wjg.v26.i18.2247
Peer-review started: February 13, 2020
First decision: March 15, 2020
Revised: March 19, 2020
Accepted: April 24, 2020
Article in press: April 24, 2020
Published online: May 14, 2020
Processing time: 90 Days and 23.1 Hours
The non-invasive and easy-to-perform diagnostic techniques to predict complications in cirrhotic patients are required in clinical practice. Up to now, the clinical use of liver stiffness measurement (LSM), computed tomography (CT), and magnetic resonance imaging (MRI), as non-invasive diagnostic methods to diagnose esophageal varices (EV) and to predict high-bleeding-risk EV (HREV) in cirrhotic patients, is controversial.
The LSM, CT, and MRI for the diagnosis of EV and prediction of HREV, promising non-invasive diagnostic methods to predict complications in cirrhotic patients, are required in clinical practice. However, the accuracy, sensitivity, and specificity varied in different studies. The overall accuracy, sensitivity, and specificity of LSM, CT, and MRI in the diagnosis of EV and prediction of HREV in cirrhotic patients have not stated.
This is a very important and interesting systematic review and meta-analysis aimed to determine the overall accuracy and sensitivity of three non-invasive methods to diagnose EV and predict the risk of bleeding in patients with liver cirrhosis.
We performed literature searches by using selected keywords in PubMed, Embase, Cochrane, CNKI, and Wanfang databases for full-text articles published in English and Chinese. All statistical analyses were conducted using Stata12.0, MetaDisc1.4, and RevMan5.3. Summary sensitivity and specificity, positive likelihood ratio and negative likelihood ratio, diagnostic odds ratio, and the area under the summary receiver operating characteristic curves that evaluated the accuracy of LSM, CT, and MRI as candidates for diagnosing EV and predicting HREV in cirrhotic patients were analyzed. The random-effects model was used to combine effect quantity. The quality of the articles was assessed using the quality assessment of diagnostic accuracy studies-2 tool. Heterogeneity was examined by Q-statistic test and I2 index, and sources of heterogeneity were explored using meta-regression and subgroup analysis. Publication bias was evaluated using Deek’s funnel plot.
Overall, 18, 17, and 7 relevant articles on the accuracy of LSM, CT, and MRI in diagnosing EV and predicting HREV were retrieved. CT had higher accuracy than LSM and MRI in diagnosing EV and predicting HREV with areas under the summary receiver operating characteristic curves of 0.91 (95%CI: 0.88-0.93) and 0.94 (95%CI: 0.91-0.96), respectively. The sensitivities of LSM, CT, and MRI in diagnosing EV and predicting HREV were 0.84 (95%CI: 0.78-0.89), 0.91 (95%CI: 0.87-0.94), and 0.81 (95%CI: 0.76-0.86), and 0.81 (95%CI: 0.75-0.86), 0.88 (95%CI: 0.82-0.92), and 0.80 (95%CI: 0.72-0.86), respectively. The specificities were 0.71 (95%CI: 0.60-0.80), 0.75 (95%CI: 0.68-0.82), and 0.82 (95%CI: 0.70-0.89), and 0.73 (95%CI: 0.66-0.80), 0.87 (95%CI: 0.81-0.92), and 0.72 (95%CI: 0.62-0.80) , respectively. The positive likelihood ratios were 2.91, 3.67, and 4.44, and 3.04, 6.90, and 2.83, respectively. The negative likelihood ratios were 0.22, 0.12, and 0.23, and 0.26, 0.14, and 0.28, respectively. The diagnostic odds ratios were 13.01, 30.98, and 19.58, and 11.93, 49.99, and 10.00, respectively. A significant heterogeneity was observed in all analyses (P < 0.05). CT scanner was identified to be the source of heterogeneity. There was no significant difference in diagnostic threshold effects (P > 0.05) or publication bias (P > 0.05). To determine the risk for bleeding of EV using a non-invasive method might have important clinical applications in daily practice. The study gives an overall view of the problem, and for sure does give clinical details which could be useful in making decisions in everyday practice.
Based on the meta-analysis of observational studies, CT has higher accuracy in evaluating EV and HREV than LSM and MRI in cirrhotic patients. It is suggested that CT, a non-invasive diagnostic method, is the best choice for the diagnosis of EV and prediction of HREV in cirrhotic patients compared with LSM and MRI.
The results are very important with significant applications for clinicians in making decisions in daily practice for treatment of cirrhotic patients with portal hypertension. In future, the head-to-head or direct comparisons of these non-invasive methods in the same series of patients are required to confirm the predictive value, especially by using artificial intelligence technique.