The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history
We developed and validated a model to estimate the risks of mutations in the mismatch repair (MMR) genes MLH1, MSH2, and MSH6 based on personal and family history of cancer. Data were analyzed from 4539 probands tested for mutations in MLH1, MSH2, and MSH6. A multivariable polytomous logistic regres...
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creator | Kastrinos, Fay Steyerberg, Ewout W Mercado, Rowena Balmaña, Judith Holter, Spring Gallinger, Steven Siegmund, Kimberly D Church, James M Jenkins, Mark A Lindor, Noralane M Thibodeau, Stephen N Burbidge, Lynn Anne Wenstrup, Richard J Syngal, Sapna |
description | We developed and validated a model to estimate the risks of mutations in the mismatch repair (MMR) genes MLH1, MSH2, and MSH6 based on personal and family history of cancer.
Data were analyzed from 4539 probands tested for mutations in MLH1, MSH2, and MSH6. A multivariable polytomous logistic regression model (PREMM(1,2,6)) was developed to predict the overall risk of MMR gene mutations and the risk of mutation in each of the 3 genes. The discriminative ability of the model was validated in 1827 population-based colorectal cancer (CRC) cases.
Twelve percent of the original cohort carried pathogenic mutations (204 in MLH1, 250 in MSH2, and 71 in MSH6). The PREMM(1,2,6) model incorporated the following factors from the probands and first- and second-degree relatives (odds ratio; 95% confidence intervals [CIs]): male sex (1.9; 1.5-2.4), a CRC (4.3; 3.3-5.6), multiple CRCs (13.7; 8.5-22), endometrial cancer (6.1; 4.6-8.2), and extracolonic cancers (3.3; 2.4-4.6). The areas under the receiver operating characteristic curves were 0.86 (95% CI, 0.82-0.91) for MLH1 mutation carriers, 0.87 (95% CI, 0.83-0.92) for MSH2, and 0.81 (95% CI, 0.69-0.93) for MSH6; in validation, they were 0.88 for the overall cohort (95% CI, 0.86-0.90) and the population-based cases (95% CI, 0.83-0.92).
We developed the PREMM(1,2,6) model, which incorporates information on cancer history from probands and their relatives to estimate an individual's risk of mutations in the MMR genes MLH1, MSH2, and MSH6. This Web-based decision making tool can be used to assess risk of hereditary CRC and guide clinical management. |
doi_str_mv | 10.1053/j.gastro.2010.08.021 |
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Data were analyzed from 4539 probands tested for mutations in MLH1, MSH2, and MSH6. A multivariable polytomous logistic regression model (PREMM(1,2,6)) was developed to predict the overall risk of MMR gene mutations and the risk of mutation in each of the 3 genes. The discriminative ability of the model was validated in 1827 population-based colorectal cancer (CRC) cases.
Twelve percent of the original cohort carried pathogenic mutations (204 in MLH1, 250 in MSH2, and 71 in MSH6). The PREMM(1,2,6) model incorporated the following factors from the probands and first- and second-degree relatives (odds ratio; 95% confidence intervals [CIs]): male sex (1.9; 1.5-2.4), a CRC (4.3; 3.3-5.6), multiple CRCs (13.7; 8.5-22), endometrial cancer (6.1; 4.6-8.2), and extracolonic cancers (3.3; 2.4-4.6). The areas under the receiver operating characteristic curves were 0.86 (95% CI, 0.82-0.91) for MLH1 mutation carriers, 0.87 (95% CI, 0.83-0.92) for MSH2, and 0.81 (95% CI, 0.69-0.93) for MSH6; in validation, they were 0.88 for the overall cohort (95% CI, 0.86-0.90) and the population-based cases (95% CI, 0.83-0.92).
We developed the PREMM(1,2,6) model, which incorporates information on cancer history from probands and their relatives to estimate an individual's risk of mutations in the MMR genes MLH1, MSH2, and MSH6. This Web-based decision making tool can be used to assess risk of hereditary CRC and guide clinical management.</description><identifier>EISSN: 1528-0012</identifier><identifier>DOI: 10.1053/j.gastro.2010.08.021</identifier><identifier>PMID: 20727894</identifier><language>eng</language><publisher>United States</publisher><subject>Adaptor Proteins, Signal Transducing - genetics ; Adult ; Cohort Studies ; Colorectal Neoplasms - epidemiology ; Colorectal Neoplasms - genetics ; DNA Mismatch Repair ; DNA-Binding Proteins - genetics ; Endometrial Neoplasms - epidemiology ; Endometrial Neoplasms - genetics ; Female ; Genetic Predisposition to Disease ; Genetic Testing ; Germ-Line Mutation ; Humans ; Logistic Models ; Male ; Middle Aged ; Models, Genetic ; MutL Protein Homolog 1 ; MutS Homolog 2 Protein - genetics ; Neoplasms - epidemiology ; Neoplasms - genetics ; Nuclear Proteins - genetics ; Pedigree ; Risk</subject><ispartof>Gastroenterology (New York, N.Y. 1943), 2011-01, Vol.140 (1), p.73-81</ispartof><rights>Copyright © 2011 AGA Institute. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/20727894$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kastrinos, Fay</creatorcontrib><creatorcontrib>Steyerberg, Ewout W</creatorcontrib><creatorcontrib>Mercado, Rowena</creatorcontrib><creatorcontrib>Balmaña, Judith</creatorcontrib><creatorcontrib>Holter, Spring</creatorcontrib><creatorcontrib>Gallinger, Steven</creatorcontrib><creatorcontrib>Siegmund, Kimberly D</creatorcontrib><creatorcontrib>Church, James M</creatorcontrib><creatorcontrib>Jenkins, Mark A</creatorcontrib><creatorcontrib>Lindor, Noralane M</creatorcontrib><creatorcontrib>Thibodeau, Stephen N</creatorcontrib><creatorcontrib>Burbidge, Lynn Anne</creatorcontrib><creatorcontrib>Wenstrup, Richard J</creatorcontrib><creatorcontrib>Syngal, Sapna</creatorcontrib><title>The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history</title><title>Gastroenterology (New York, N.Y. 1943)</title><addtitle>Gastroenterology</addtitle><description>We developed and validated a model to estimate the risks of mutations in the mismatch repair (MMR) genes MLH1, MSH2, and MSH6 based on personal and family history of cancer.
Data were analyzed from 4539 probands tested for mutations in MLH1, MSH2, and MSH6. A multivariable polytomous logistic regression model (PREMM(1,2,6)) was developed to predict the overall risk of MMR gene mutations and the risk of mutation in each of the 3 genes. The discriminative ability of the model was validated in 1827 population-based colorectal cancer (CRC) cases.
Twelve percent of the original cohort carried pathogenic mutations (204 in MLH1, 250 in MSH2, and 71 in MSH6). The PREMM(1,2,6) model incorporated the following factors from the probands and first- and second-degree relatives (odds ratio; 95% confidence intervals [CIs]): male sex (1.9; 1.5-2.4), a CRC (4.3; 3.3-5.6), multiple CRCs (13.7; 8.5-22), endometrial cancer (6.1; 4.6-8.2), and extracolonic cancers (3.3; 2.4-4.6). The areas under the receiver operating characteristic curves were 0.86 (95% CI, 0.82-0.91) for MLH1 mutation carriers, 0.87 (95% CI, 0.83-0.92) for MSH2, and 0.81 (95% CI, 0.69-0.93) for MSH6; in validation, they were 0.88 for the overall cohort (95% CI, 0.86-0.90) and the population-based cases (95% CI, 0.83-0.92).
We developed the PREMM(1,2,6) model, which incorporates information on cancer history from probands and their relatives to estimate an individual's risk of mutations in the MMR genes MLH1, MSH2, and MSH6. This Web-based decision making tool can be used to assess risk of hereditary CRC and guide clinical management.</description><subject>Adaptor Proteins, Signal Transducing - genetics</subject><subject>Adult</subject><subject>Cohort Studies</subject><subject>Colorectal Neoplasms - epidemiology</subject><subject>Colorectal Neoplasms - genetics</subject><subject>DNA Mismatch Repair</subject><subject>DNA-Binding Proteins - genetics</subject><subject>Endometrial Neoplasms - epidemiology</subject><subject>Endometrial Neoplasms - genetics</subject><subject>Female</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic Testing</subject><subject>Germ-Line Mutation</subject><subject>Humans</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Genetic</subject><subject>MutL Protein Homolog 1</subject><subject>MutS Homolog 2 Protein - genetics</subject><subject>Neoplasms - epidemiology</subject><subject>Neoplasms - genetics</subject><subject>Nuclear Proteins - genetics</subject><subject>Pedigree</subject><subject>Risk</subject><issn>1528-0012</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNo1kNFLwzAYxIMgbk7_A5G8qdDW5MvStI8yphNWFN17yZKvW2fbzKR92H_vxPl0x_Hj4I6QG84SzqR43CUbHXrvEmDHiGUJA35GxlxCFjPGYUQuQ9gxxnKR8QsyAqZAZfl0TDarLdL3j3lR3PMIovSBts5iQ_cebW36QH0dvqiraLFc8IgWnwuIqO7sr0vpBn3b1B3Sduh1X7su0LUOaKnrqNGdQU-3deidP1yR80o3Aa9POiGr5_lqtoiXby-vs6dlvJdyGqcV2JzJTPA0h6mqOLeSKeRGS7CVMKmUCCzVCFzzTGihqhxBpcYoSE2uxITc_dXuvfseMPRlWweDTaM7dEMos-PyHLiQR_L2RA7rFm2593Wr_aH8v0b8AApkYeE</recordid><startdate>201101</startdate><enddate>201101</enddate><creator>Kastrinos, Fay</creator><creator>Steyerberg, Ewout W</creator><creator>Mercado, Rowena</creator><creator>Balmaña, Judith</creator><creator>Holter, Spring</creator><creator>Gallinger, Steven</creator><creator>Siegmund, Kimberly D</creator><creator>Church, James M</creator><creator>Jenkins, Mark A</creator><creator>Lindor, Noralane M</creator><creator>Thibodeau, Stephen N</creator><creator>Burbidge, Lynn Anne</creator><creator>Wenstrup, Richard J</creator><creator>Syngal, Sapna</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope></search><sort><creationdate>201101</creationdate><title>The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history</title><author>Kastrinos, Fay ; Steyerberg, Ewout W ; Mercado, Rowena ; Balmaña, Judith ; Holter, Spring ; Gallinger, Steven ; Siegmund, Kimberly D ; Church, James M ; Jenkins, Mark A ; Lindor, Noralane M ; Thibodeau, Stephen N ; Burbidge, Lynn Anne ; Wenstrup, Richard J ; Syngal, Sapna</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p554-6f2d90583169247f11d507e1ca52df3c655e206ae21a183a37f9e276cc726c973</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Adaptor Proteins, Signal Transducing - genetics</topic><topic>Adult</topic><topic>Cohort Studies</topic><topic>Colorectal Neoplasms - epidemiology</topic><topic>Colorectal Neoplasms - genetics</topic><topic>DNA Mismatch Repair</topic><topic>DNA-Binding Proteins - genetics</topic><topic>Endometrial Neoplasms - epidemiology</topic><topic>Endometrial Neoplasms - genetics</topic><topic>Female</topic><topic>Genetic Predisposition to Disease</topic><topic>Genetic Testing</topic><topic>Germ-Line Mutation</topic><topic>Humans</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Models, Genetic</topic><topic>MutL Protein Homolog 1</topic><topic>MutS Homolog 2 Protein - genetics</topic><topic>Neoplasms - epidemiology</topic><topic>Neoplasms - genetics</topic><topic>Nuclear Proteins - genetics</topic><topic>Pedigree</topic><topic>Risk</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kastrinos, Fay</creatorcontrib><creatorcontrib>Steyerberg, Ewout W</creatorcontrib><creatorcontrib>Mercado, Rowena</creatorcontrib><creatorcontrib>Balmaña, Judith</creatorcontrib><creatorcontrib>Holter, Spring</creatorcontrib><creatorcontrib>Gallinger, Steven</creatorcontrib><creatorcontrib>Siegmund, Kimberly D</creatorcontrib><creatorcontrib>Church, James M</creatorcontrib><creatorcontrib>Jenkins, Mark A</creatorcontrib><creatorcontrib>Lindor, Noralane M</creatorcontrib><creatorcontrib>Thibodeau, Stephen N</creatorcontrib><creatorcontrib>Burbidge, Lynn Anne</creatorcontrib><creatorcontrib>Wenstrup, Richard J</creatorcontrib><creatorcontrib>Syngal, Sapna</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><jtitle>Gastroenterology (New York, N.Y. 1943)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kastrinos, Fay</au><au>Steyerberg, Ewout W</au><au>Mercado, Rowena</au><au>Balmaña, Judith</au><au>Holter, Spring</au><au>Gallinger, Steven</au><au>Siegmund, Kimberly D</au><au>Church, James M</au><au>Jenkins, Mark A</au><au>Lindor, Noralane M</au><au>Thibodeau, Stephen N</au><au>Burbidge, Lynn Anne</au><au>Wenstrup, Richard J</au><au>Syngal, Sapna</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history</atitle><jtitle>Gastroenterology (New York, N.Y. 1943)</jtitle><addtitle>Gastroenterology</addtitle><date>2011-01</date><risdate>2011</risdate><volume>140</volume><issue>1</issue><spage>73</spage><epage>81</epage><pages>73-81</pages><eissn>1528-0012</eissn><abstract>We developed and validated a model to estimate the risks of mutations in the mismatch repair (MMR) genes MLH1, MSH2, and MSH6 based on personal and family history of cancer.
Data were analyzed from 4539 probands tested for mutations in MLH1, MSH2, and MSH6. A multivariable polytomous logistic regression model (PREMM(1,2,6)) was developed to predict the overall risk of MMR gene mutations and the risk of mutation in each of the 3 genes. The discriminative ability of the model was validated in 1827 population-based colorectal cancer (CRC) cases.
Twelve percent of the original cohort carried pathogenic mutations (204 in MLH1, 250 in MSH2, and 71 in MSH6). The PREMM(1,2,6) model incorporated the following factors from the probands and first- and second-degree relatives (odds ratio; 95% confidence intervals [CIs]): male sex (1.9; 1.5-2.4), a CRC (4.3; 3.3-5.6), multiple CRCs (13.7; 8.5-22), endometrial cancer (6.1; 4.6-8.2), and extracolonic cancers (3.3; 2.4-4.6). The areas under the receiver operating characteristic curves were 0.86 (95% CI, 0.82-0.91) for MLH1 mutation carriers, 0.87 (95% CI, 0.83-0.92) for MSH2, and 0.81 (95% CI, 0.69-0.93) for MSH6; in validation, they were 0.88 for the overall cohort (95% CI, 0.86-0.90) and the population-based cases (95% CI, 0.83-0.92).
We developed the PREMM(1,2,6) model, which incorporates information on cancer history from probands and their relatives to estimate an individual's risk of mutations in the MMR genes MLH1, MSH2, and MSH6. This Web-based decision making tool can be used to assess risk of hereditary CRC and guide clinical management.</abstract><cop>United States</cop><pmid>20727894</pmid><doi>10.1053/j.gastro.2010.08.021</doi><tpages>9</tpages></addata></record> |
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subjects | Adaptor Proteins, Signal Transducing - genetics Adult Cohort Studies Colorectal Neoplasms - epidemiology Colorectal Neoplasms - genetics DNA Mismatch Repair DNA-Binding Proteins - genetics Endometrial Neoplasms - epidemiology Endometrial Neoplasms - genetics Female Genetic Predisposition to Disease Genetic Testing Germ-Line Mutation Humans Logistic Models Male Middle Aged Models, Genetic MutL Protein Homolog 1 MutS Homolog 2 Protein - genetics Neoplasms - epidemiology Neoplasms - genetics Nuclear Proteins - genetics Pedigree Risk |
title | The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history |
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