ABSTRACT
We conducted a meta-analysis to compare the EBV DNA and VCA-IgA in diagnosis of Nasopharyngeal Carcinoma, and provide important evidence for screening method of NPC. Three databases, Medline [from Jan. 1966 to Jan. 2012], EMBASE [from January 1988 to Jan. 2012] and Chinese Biomedical Database [from January 1980 to Jan. 2012] were used to detect the role of EBV DNA and VCA-IgA in diagnosis of NPC. Meta-DiSc statistical software was used for analysis. Twenty seven case-control and cohort studies were included in final analysis. A total of 1554 cases and 2932 controls were included in our meta-analysis. The Sensitivity specificity, positive likelihood [+LR] and likelihood negative [-LR] of EBV-DNA in diagnosis of NPC were 0.75[0.72-0.76], 0.87[0.85-0.88], 6.98[4.50-10.83] and 0.18[0.11-0.29], respectively, and they were 0.83[0.81-0.85], 0.85[0.83-0.86], 10.89[5.41-21.93] and 0.20[0.14-0.29] for VCA-IgA. The SROC for EBV DNA detection was 0.939, while this was 0.936 for VCA-IgA detection. The subgroup analysis showed EBV-DNA had larger areas under the summary receiver operator curve when compared with VCA-IgA in high quality and low quality studies. Our meta-analysis indicated the EBV DNA had higher sensitivity and specificity in diagnosis of NPC
Subject(s)
Herpesvirus 4, Human , Antigens, Viral , DNA, ViralABSTRACT
Hidden Markov model (HMM) used in the research of protein is a new field of bioinformatics. Nowadays large amount of data about protein sequences and structures have been obtained. Traditional methods of protein analysis are no longer used. Biologists have updated their research methods with computer technology and statistics, which can deal with large amount of data. HMM can be used to distinguish protein sequence with the same characteristics. A family of protein from SCOP database was selected, through which a HMM model representing the family was obtained, and then the model was utilized to analyze protein sequences. Results indicate that HMM can express particular family of protein, and recognize the given protein sequences of the family from many sequences.