Literature DB >> 18603628

Comparison of predictive models, clinical criteria and molecular tumour screening for the identification of patients with Lynch syndrome in a population-based cohort of colorectal cancer patients.

J Balmaña1, F Balaguer, S Castellví-Bel, E W Steyerberg, M Andreu, X Llor, R Jover, A Castells, S Syngal.   

Abstract

BACKGROUND: Several models have recently been developed to predict mismatch repair (MMR) gene mutations. Their comparative performance with clinical criteria or universal molecular screening in a population based colorectal cancer (CRC) cohort has not been assessed.
METHODS: All 1222 CRC from the EPICOLON cohort underwent tumour MMR testing with immunohistochemistry and microsatellite instability, and those with MMR deficiency (n = 91) underwent MLH1/MSH2 germline testing. Sensitivity, specificity and positive predictive value (PPV) of the PREMM(1,2) and the Barnetson models for identification of MLH1/MSH2 mutation carriers were evaluated and compared with the revised Bethesda guidelines (RBG), Amsterdam II criteria, and tumour analysis for MMR deficiency. Overall discriminative ability was quantified by the area under the ROC curve (AUC), and calibration was assessed by comparing the average predictions versus the observed prevalence.
RESULTS: Both models had similar AUC (0.93 and 0.92, respectively). Sensitivity of the RBG and a PREMM(1,2) score > or =5% was 100% (95% CI 71% to 100%); a Barnetson score >0.5% missed one mutation carrier (sensitivity 87%, 95% CI 51% to 99%). PPVs of all three strategies were 2-3%. Presence of MMR deficiency increased specificity and PPV of predictive scores (97% and 21% for PREMM(1,2) score > or =5%, and 98% and 21% for Barnetson > or =0.5%, respectively).
CONCLUSIONS: The PREMM(1,2) and the Barnetson models offer a quantitative systematic approach to select CRC patients for identification of MLH1/MSH2 mutation carriers with a similar performance to the RBG.

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Year:  2008        PMID: 18603628     DOI: 10.1136/jmg.2008.059311

Source DB:  PubMed          Journal:  J Med Genet        ISSN: 0022-2593            Impact factor:   6.318


  25 in total

1.  The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history.

Authors:  Fay Kastrinos; Ewout W Steyerberg; Rowena Mercado; Judith Balmaña; Spring Holter; Steven Gallinger; Kimberly D Siegmund; James M Church; Mark A Jenkins; Noralane M Lindor; Stephen N Thibodeau; Lynn Anne Burbidge; Richard J Wenstrup; Sapna Syngal
Journal:  Gastroenterology       Date:  2010-08-19       Impact factor: 22.682

2.  Bethesda criteria for microsatellite instability testing: impact on the detection of new cases of Lynch syndrome.

Authors:  Miguel Serrano; Pedro Lage; Sara Belga; Bruno Filipe; Inês Francisco; Paula Rodrigues; Ricardo Fonseca; Paula Chaves; Isabel Claro; Cristina Albuquerque; António Dias Pereira
Journal:  Fam Cancer       Date:  2012-12       Impact factor: 2.375

3.  Performance of Lynch syndrome predictive models in quantifying the likelihood of germline mutations in patients with abnormal MLH1 immunoexpression.

Authors:  Verónica Cabreira; Carla Pinto; Manuela Pinheiro; Paula Lopes; Ana Peixoto; Catarina Santos; Isabel Veiga; Patrícia Rocha; Pedro Pinto; Rui Henrique; Manuel R Teixeira
Journal:  Fam Cancer       Date:  2017-01       Impact factor: 2.375

4.  Comparison of the clinical prediction model PREMM(1,2,6) and molecular testing for the systematic identification of Lynch syndrome in colorectal cancer.

Authors:  Fay Kastrinos; Ewout W Steyerberg; Judith Balmaña; Rowena Mercado; Steven Gallinger; Robert Haile; Graham Casey; John L Hopper; Loic LeMarchand; Noralane M Lindor; Polly A Newcomb; Stephen N Thibodeau; Sapna Syngal
Journal:  Gut       Date:  2012-02-16       Impact factor: 23.059

5.  Strategies to identify the Lynch syndrome among patients with colorectal cancer: a cost-effectiveness analysis.

Authors:  Uri Ladabaum; Grace Wang; Jonathan Terdiman; Amie Blanco; Miriam Kuppermann; C Richard Boland; James Ford; Elena Elkin; Kathryn A Phillips
Journal:  Ann Intern Med       Date:  2011-07-19       Impact factor: 25.391

6.  Performance of Lynch syndrome predictive models in a multi-center US referral population.

Authors:  Omar Khan; Amie Blanco; Peggy Conrad; Cassandra Gulden; Tovah Z Moss; Olufunmilayo I Olopade; Sonia S Kupfer; Jonathan Terdiman
Journal:  Am J Gastroenterol       Date:  2011-07-12       Impact factor: 10.864

7.  UK colorectal cancer patients are inadequately assessed for Lynch syndrome.

Authors:  Maria Adelson; Samuel Pannick; James E East; Peter Risby; Peter Dawson; Kevin J Monahan
Journal:  Frontline Gastroenterol       Date:  2013-08-06

8.  Lynch syndrome in Tunisia: first description of clinical features and germline mutations.

Authors:  Sana Aissi-Ben Moussa; Amel Moussa; Nadia Kourda; Amel Mezlini; Nabil Abdelli; Farid Zerimech; Taoufik Najjar; Sarah Ben Jilani; Nicole Porchet; Farhat Ben Ayed; Mohamed Manai; Marie-Pierre Buisine
Journal:  Int J Colorectal Dis       Date:  2011-02-11       Impact factor: 2.571

9.  Mismatch repair protein expression and colorectal cancer in Hispanics from Puerto Rico.

Authors:  Wilfredo E De Jesus-Monge; Carmen Gonzalez-Keelan; Ronghua Zhao; Stanley R Hamilton; Miguel Rodriguez-Bigas; Marcia Cruz-Correa
Journal:  Fam Cancer       Date:  2010-06       Impact factor: 2.375

10.  Identification of Lynch syndrome among patients with colorectal cancer.

Authors:  Leticia Moreira; Francesc Balaguer; Noralane Lindor; Albert de la Chapelle; Heather Hampel; Lauri A Aaltonen; John L Hopper; Loic Le Marchand; Steven Gallinger; Polly A Newcomb; Robert Haile; Stephen N Thibodeau; Shanaka Gunawardena; Mark A Jenkins; Daniel D Buchanan; John D Potter; John A Baron; Dennis J Ahnen; Victor Moreno; Montserrat Andreu; Maurizio Ponz de Leon; Anil K Rustgi; Antoni Castells
Journal:  JAMA       Date:  2012-10-17       Impact factor: 56.272

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