BACKGROUND: MMRpro, prediction of mutations in MLH1 and MLH2 (PREMM(1,2)) and MMRpredict are models which were developed to predict the probability that an individual carries a Lynch syndrome-causing mutation. Each model utilizes data from personal and family histories of cancer. To date, no studies have compared these models in a cancer genetics clinic. The purpose of this study was to determine each model's ability to predict the probability of carrying a Lynch syndrome-causing mutation in individuals with a family history of colorectal cancer and to determine their clinical applicability. METHODS: We obtained family pedigrees from 81 individuals who presented for Lynch syndrome testing due to a personal and/or family history of cancer. Data from each pedigree were entered into the models and analyzed using SPSS. RESULTS: We found that MMRpredict, PREMM(1,2) and MMRpro showed similar performances with areas under the receiver-operating characteristic curve of 0.731, 0.765 and 0.732, respectively. MMRpro showed the least dispersion of mutation probability estimates with a P value of 0.205, compared with 0.034 for PREMM(1,2) and 0.001 for MMRpredict. CONCLUSION: We found all three carried out well in a cancer genetics setting, with PREMM(1,2) giving slightly better estimates. There were some significant discrepancies between the models in cases where the proband had endometrial cancer.
BACKGROUND: MMRpro, prediction of mutations in MLH1 and MLH2 (PREMM(1,2)) and MMRpredict are models which were developed to predict the probability that an individual carries a Lynch syndrome-causing mutation. Each model utilizes data from personal and family histories of cancer. To date, no studies have compared these models in a cancer genetics clinic. The purpose of this study was to determine each model's ability to predict the probability of carrying a Lynch syndrome-causing mutation in individuals with a family history of colorectal cancer and to determine their clinical applicability. METHODS: We obtained family pedigrees from 81 individuals who presented for Lynch syndrome testing due to a personal and/or family history of cancer. Data from each pedigree were entered into the models and analyzed using SPSS. RESULTS: We found that MMRpredict, PREMM(1,2) and MMRpro showed similar performances with areas under the receiver-operating characteristic curve of 0.731, 0.765 and 0.732, respectively. MMRpro showed the least dispersion of mutation probability estimates with a P value of 0.205, compared with 0.034 for PREMM(1,2) and 0.001 for MMRpredict. CONCLUSION: We found all three carried out well in a cancer genetics setting, with PREMM(1,2) giving slightly better estimates. There were some significant discrepancies between the models in cases where the proband had endometrial cancer.
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
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
Authors: Rowena C Mercado; Heather Hampel; Fay Kastrinos; Ewout Steyerberg; Judith Balmana; Elena Stoffel; David E Cohn; Floor J Backes; John L Hopper; Mark A Jenkins; Noralane M Lindor; Graham Casey; Robert Haile; Subha Madhavan; Albert de la Chapelle; Sapna Syngal Journal: Genet Med Date: 2012-03-08 Impact factor: 8.822
Authors: Erika Maria Monteiro Santos; Mev Dominguez Valentin; Felipe Carneiro; Ligia Petrolini de Oliveira; Fabio de Oliveira Ferreira; Samuel Aguiar Junior; Wilson Toshihiko Nakagawa; Israel Gomy; Victor Evangelista de Faria Ferraz; Wilson Araujo da Silva Junior; Dirce Maria Carraro; Benedito Mauro Rossi Journal: BMC Cancer Date: 2012-02-09 Impact factor: 4.430