Literature DB >> 21520036

Evaluation of predictive models in daily practice for the identification of patients with Lynch syndrome.

Christophe Tresallet1, Antoine Brouquet, Catherine Julié, Alain Beauchet, Céline Vallot, Fabrice Ménégaux, Emmanuel Mitry, François Radvanyi, Robert Malafosse, Philippe Rougier, Bernard Nordlinger, Pierre Laurent-Puig, Catherine Boileau, Jean-François Emile, Christine Muti, Christophe Penna, Hélène Hofmann-Radvanyi.   

Abstract

The optimal strategy for identifying patients with Lynch syndrome among patients with newly diagnosed colorectal cancer (CRC) is still debated. Several predictive models (e.g., MMRpredict, PREMM1,2 and MMRpro) combining personal and familial data have recently been developed to quantify the risk that a given patient with CRC carries a Lynch syndrome-causing mutation. Their clinical applicability to patients with CRC from the general population requires evaluation. We studied a consecutive series of 214 patients with newly diagnosed CRC characterized for tumor microsatellite instability (MSI), somatic BRAF mutation, MLH1 promoter methylation and mismatch repair (MMR) gene germline mutation status. The performances of the models for identifying MMR mutation carriers (8/214, 3.7%) were evaluated and compared to the revised Bethesda guidelines and a molecular strategy based on MSI testing in all patients followed by the exclusion of MSI-positive sporadic cases from mutational testing by screening for BRAF mutation and MLH1 promoter methylation. The sensitivities of the three models, at the lowest thresholds proposed, were identical (75%), with similar numbers of probands eligible for further MSI testing (almost half the patients). In our dataset, the prediction models gave no better discrimination than the revised Bethesda guidelines. Both approaches failed to identify two of the eight mutation carriers (the same two patients, aged 67 and 81 years, both with no family history). Thus, like the revised Bethesda guidelines, predictive models did not identify all patients with Lynch syndrome in our series of consecutive CRC. Our results support systematic screening for MMR deficiency in all new CRC cases.
Copyright © 2011 UICC.

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Year:  2011        PMID: 21520036     DOI: 10.1002/ijc.26144

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  9 in total

1.  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

Review 2.  History, genetics, and strategies for cancer prevention in Lynch syndrome.

Authors:  Fay Kastrinos; Elena M Stoffel
Journal:  Clin Gastroenterol Hepatol       Date:  2013-07-23       Impact factor: 11.382

3.  Clinical utility gene card for: Lynch syndrome (MLH1, MSH2, MSH6, PMS2, EPCAM) - update 2012.

Authors:  Nils Rahner; Verena Steinke; Brigitte Schlegelberger; Francois Eisinger; Pierre Hutter; Sylviane Olschwang
Journal:  Eur J Hum Genet       Date:  2012-08-15       Impact factor: 4.246

Review 4.  Prediction models in Lynch syndrome.

Authors:  Fay Kastrinos; Judith Balmaña; Sapna Syngal
Journal:  Fam Cancer       Date:  2013-06       Impact factor: 2.375

5.  Comparison of Prediction Models for Lynch Syndrome Among Individuals With Colorectal Cancer.

Authors:  Fay Kastrinos; Rohit P Ojha; Celine Leenen; Carmelita Alvero; Rowena C Mercado; Judith Balmaña; Irene Valenzuela; Francesc Balaguer; Roger Green; Noralane M Lindor; Stephen N Thibodeau; Polly Newcomb; Aung Ko Win; Mark Jenkins; Daniel D Buchanan; Lucio Bertario; Paola Sala; Heather Hampel; Sapna Syngal; Ewout W Steyerberg
Journal:  J Natl Cancer Inst       Date:  2015-11-18       Impact factor: 13.506

6.  Validation of Prediction Models for Mismatch Repair Gene Mutations in Koreans.

Authors:  Soo Young Lee; 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
Journal:  Cancer Res Treat       Date:  2015-06-05       Impact factor: 4.679

7.  Evaluation of current prediction models for Lynch syndrome: updating the PREMM5 model to identify PMS2 mutation carriers.

Authors:  A Goverde; M C W Spaander; D Nieboer; A M W van den Ouweland; W N M Dinjens; H J Dubbink; C J Tops; S W Ten Broeke; M J Bruno; R M W Hofstra; E W Steyerberg; A Wagner
Journal:  Fam Cancer       Date:  2018-07       Impact factor: 2.375

Review 8.  Diagnosis of Lynch Syndrome and Strategies to Distinguish Lynch-Related Tumors from Sporadic MSI/dMMR Tumors.

Authors:  Julie Leclerc; Catherine Vermaut; Marie-Pierre Buisine
Journal:  Cancers (Basel)       Date:  2021-01-26       Impact factor: 6.639

Review 9.  Effective Identification of Lynch Syndrome in Gastroenterology Practice.

Authors:  Charles Muller; Lindsay Matthews; Sonia S Kupfer; Jennifer M Weiss
Journal:  Curr Treat Options Gastroenterol       Date:  2019-12
  9 in total

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