Published online Jun 7, 2018. doi: 10.3748/wjg.v24.i21.2269
Peer-review started: February 12, 2018
First decision: February 23, 2018
Revised: February 27, 2018
Accepted: March 18, 2018
Article in press: March 18, 2018
Published online: June 7, 2018
To investigate the value of multiparameter joint analysis in the early diagnosis of gastric cancer (GC) in clinical practice.
Concentrations of CEA, CA724 and three kinds of cytokines (TNF-α, IL-6 and IL-8) in 176 GC patients, 117 atypical hyperplasia patients, and 204 healthy control individuals were used for building the diagnostic model, then 58 GC patients, 41 atypical hyperplasia patients, and 66 healthy control individuals were enrolled independently. The joints of the indicators were analyzed by binary logistic regression analysis method.
For discriminating the healthy control group and the GC group, IL-6 had the best diagnostic value, and the area under curve (AUC) of joint analysis was 0.95 (0.93-0.97). For the early stage and advanced stage GC, the AUC were 0.95 (0.92-0.98) and 0.95 (0.92-0.97). For discriminating the atypical hyperplasia group and GC group, CA724 had the best diagnostic value, and the AUC of joint analysis was 0.97 (0.95-0.99). For the early stage and advanced stage GC groups, the AUC were 0.98 (0.96-0.99) and 0.96 (0.94-0.98). After evaluation, for discriminating the GC, early stage GC and advanced cancer group from the healthy control group, the diagnostic sensitivity was 89.66%, 84.21% and 92.31%, respectively, and the specificity was 92.42%, 90.91% and 90.91%. For discriminating the GC, early stage GC and advanced cancer groups from the atypical hyperplasia group, the diagnostic sensitivity was 87.93%, 78.95% and 92.31%, respectively, and the specificity was 87.80%, 85.37% and 90.24%.
We have built a diagnostic model including CEA, CA724, IL-6, IL-8, and TNF-α. It may provide potential assistance as a screening method for the early detection of GC.
Core tip: We aimed to use multiparameter joint analysis for improving sensitivity and specificity for detection of gastric cancer. By combining CEA, CA724, IL-6, IL-8 and TNF-α, we built a diagnostic model, which may provide potential assistance as a screening method for the early detection of gastric cancer.