Validation of Prediction Models for Mismatch Repair Gene Mutations in Koreans.
- Author:
Soo Young LEE
1
;
Duck Woo KIM
;
Young Kyoung SHIN
;
Myong Hoon IHN
;
Sung Min LEE
;
Heung Kwon OH
;
Ja Lok KU
;
Seung Yong JEONG
;
Jae Bong LEE
;
Soyeon AHN
;
Sungho WON
;
Sung Bum KANG
Author Information
- Publication Type:Original Article
- Keywords: Hereditary nonpolyposis colorectal neoplasms; Prediction model; Genetic testing; Mismatch repair gene
- MeSH: Area Under Curve; Colorectal Neoplasms; Colorectal Neoplasms, Hereditary Nonpolyposis; DNA Mismatch Repair*; Genetic Association Studies; Genetic Testing; Germ-Line Mutation; Humans; ROC Curve; Sensitivity and Specificity
- From:Cancer Research and Treatment 2016;48(2):668-675
- CountryRepublic of Korea
- Language:English
- Abstract: PURPOSE: Lynch syndrome, the commonest hereditary colorectal cancer syndrome, is caused by germline mutations in mismatch repair (MMR) genes. Three recently developed prediction models for MMR gene mutations based on family history and clinical features (MMRPredict, PREMM1,2,6, and MMRPro) have been validated only in Western countries. In this study, we propose validating these prediction models in the Korean population. MATERIALS AND METHODS: We collected MMR gene analysis data from 188 individuals in the Korean Hereditary Tumor Registry. The probability of gene mutation was calculated using three prediction models, and the overall diagnostic value of each model compared using receiver operator characteristic (ROC) curves and area under the ROC curve (AUC). Quantitative test characteristics were calculated at sensitivities of 90%, 95%, and 98%. RESULTS: Of the individuals analyzed, 101 satisfied Amsterdam criteria II, and 87 were suspected hereditary nonpolyposis colorectal cancer. MMR mutations were identified in 62 of the 188 subjects (33.0%). All three prediction models showed a poor predictive value of AUC (MMRPredict, 0.683; PREMM1,2,6, 0.709; MMRPro, 0.590). Within the range of acceptable sensitivity (> 90%), PREMM1,2,6 demonstrated higher specificity than the other models. CONCLUSION: In the Korean population, overall predictive values of the three models (MMRPredict, PREMM1,2,6, MMRPro) for MMR gene mutations are poor, compared with their performance in Western populations. A new prediction model is therefore required for the Korean population to detect MMR mutation carriers, reflecting ethnic differences in genotype-phenotype associations.
