BACKGROUND: Lynch syndrome is caused by germline mismatch repair (MMR) gene mutations. The PREMM(1,2,6) model predicts the likelihood of a MMR gene mutation based on personal and family cancer history. OBJECTIVE: To compare strategies using PREMM(1,2,6) and tumour testing (microsatellite instability (MSI) and/or immunohistochemistry (IHC) staining) to identify mutation carriers. DESIGN: Data from population-based or clinic-based patients with colorectal cancers enrolled through the Colon Cancer Family Registry were analysed. Evaluation included MSI, IHC and germline mutation analysis for MLH1, MSH2, MSH6 and PMS2. Personal and family cancer histories were used to calculate PREMM(1,2,6) predictions. Discriminative ability to identify carriers from non-carriers using the area under the receiver operating characteristic curve (AUC) was assessed. Predictions were based on logistic regression models for (1) cancer assessment using PREMM(1,2,6), (2) MSI, (3) IHC for loss of any MMR protein expression, (4) MSI+IHC, (5) PREMM(1,2,6)+MSI, (6) PREMM(1,2,6)+IHC, (7) PREMM(1,2,6)+IHC+MSI. RESULTS: Among 1651 subjects, 239 (14%) had mutations (90 MLH1, 125 MSH2, 24 MSH6). PREMM(1,2,6) discriminated well with AUC 0.90 (95% CI 0.88 to 0.92). MSI alone, IHC alone, or MSI+IHC each had lower AUCs: 0.77, 0.82 and 0.82, respectively. The added value of IHC+PREMM(1,2,6) was slightly greater than PREMM(1,2,6)+MSI (AUC 0.94 vs 0.93). Adding MSI to PREMM(1,2,6)+IHC did not improve discrimination. CONCLUSION: PREMM(1,2,6) and IHC showed excellent performance in distinguishing mutation carriers from non-carriers and performed best when combined. MSI may have a greater role in distinguishing Lynch syndrome from other familial colorectal cancer subtypes among cases with high PREMM(1,2,6) scores where genetic evaluation does not disclose a MMR mutation.
BACKGROUND:Lynch syndrome is caused by germline mismatch repair (MMR) gene mutations. The PREMM(1,2,6) model predicts the likelihood of a MMR gene mutation based on personal and family cancer history. OBJECTIVE: To compare strategies using PREMM(1,2,6) and tumour testing (microsatellite instability (MSI) and/or immunohistochemistry (IHC) staining) to identify mutation carriers. DESIGN: Data from population-based or clinic-based patients with colorectal cancers enrolled through the Colon Cancer Family Registry were analysed. Evaluation included MSI, IHC and germline mutation analysis for MLH1, MSH2, MSH6 and PMS2. Personal and family cancer histories were used to calculate PREMM(1,2,6) predictions. Discriminative ability to identify carriers from non-carriers using the area under the receiver operating characteristic curve (AUC) was assessed. Predictions were based on logistic regression models for (1) cancer assessment using PREMM(1,2,6), (2) MSI, (3) IHC for loss of any MMR protein expression, (4) MSI+IHC, (5) PREMM(1,2,6)+MSI, (6) PREMM(1,2,6)+IHC, (7) PREMM(1,2,6)+IHC+MSI. RESULTS: Among 1651 subjects, 239 (14%) had mutations (90 MLH1, 125 MSH2, 24 MSH6). PREMM(1,2,6) discriminated well with AUC 0.90 (95% CI 0.88 to 0.92). MSI alone, IHC alone, or MSI+IHC each had lower AUCs: 0.77, 0.82 and 0.82, respectively. The added value of IHC+PREMM(1,2,6) was slightly greater than PREMM(1,2,6)+MSI (AUC 0.94 vs 0.93). Adding MSI to PREMM(1,2,6)+IHC did not improve discrimination. CONCLUSION: PREMM(1,2,6) and IHC showed excellent performance in distinguishing mutation carriers from non-carriers and performed best when combined. MSI may have a greater role in distinguishing Lynch syndrome from other familial colorectal cancer subtypes among cases with high PREMM(1,2,6) scores where genetic evaluation does not disclose a MMR mutation.
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Authors: J Balmaña; F Balaguer; S Castellví-Bel; E W Steyerberg; M Andreu; X Llor; R Jover; A Castells; S Syngal Journal: J Med Genet Date: 2008-06-25 Impact factor: 6.318
Authors: Daniel G Luba; James A DiSario; Colleen Rock; Devki Saraiya; Kelsey Moyes; Krystal Brown; Kristen Rushton; Maydeen M Ogara; Mona Raphael; Dayna Zimmerman; Kimmie Garrido; Evelyn Silguero; Jonathan Nelson; Matthew B Yurgelun; Fay Kastrinos; Richard J Wenstrup; Sapna Syngal Journal: Clin Gastroenterol Hepatol Date: 2017-06-28 Impact factor: 11.382