title: Is high resolution melting analysis (HRMA) accurate for detection of human disease-associated mutations? A meta analysis.
abstract: BACKGROUND
  High Resolution Melting Analysis (HRMA) is becoming the preferred method for mutation detection. However, its accuracy in the individual clinical diagnostic setting is variable. To assess the diagnostic accuracy of HRMA for human mutations in comparison to DNA sequencing in different routine clinical settings, we have conducted a meta-analysis of published reports.
  
  
  RESULTS
  Out of 195 publications obtained from the initial search criteria, thirty-four studies assessing the accuracy of HRMA were included in the meta-analysis. We found that HRMA was a highly sensitive test for detecting disease-associated mutations in humans. Overall, the summary sensitivity was 97.5% (95% confidence interval (CI): 96.8-98.5; I(2) = 27.0%). Subgroup analysis showed even higher sensitivity for non-HR-1 instruments (sensitivity 98.7% (95%CI: 97.7-99.3; I(2) = 0.0%)) and an eligible sample size subgroup (sensitivity 99.3% (95%CI: 98.1-99.8; I(2) = 0.0%)). HRMA specificity showed considerable heterogeneity between studies. Sensitivity of the techniques was influenced by sample size and instrument type but by not sample source or dye type.
  
  
  CONCLUSIONS
  These findings show that HRMA is a highly sensitive, simple and low-cost test to detect human disease-associated mutations, especially for samples with mutations of low incidence. The burden on DNA sequencing could be significantly reduced by the implementation of HRMA, but it should be recognized that its sensitivity varies according to the number of samples with/without mutations, and positive results require DNA sequencing for confirmation.
authors.affiliation: Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
authors.forename: Bing-Sheng
authors.initials: BS
authors.lastname: Li
authors.forename: Xin-Ying
authors.initials: XY
authors.lastname: Wang
authors.forename: Feng-Li
authors.initials: FL
authors.lastname: Ma
authors.forename: Bo
authors.initials: B
authors.lastname: Jiang
authors.forename: Xiao-Xiao
authors.initials: XX
authors.lastname: Song
authors.forename: An-Gao
authors.initials: AG
authors.lastname: Xu
mesh_terms: D004252:DNA Mutational Analysis / Q000379:methods*; D004194:Disease / Q000235:genetics*; D006801:Humans; D016013:Likelihood Functions; D015999:Multivariate Analysis; D009154:Mutation / Q000235:genetics*; D009691:Nucleic Acid Denaturation; D016017:Odds Ratio; D012044:Regression Analysis