BACKGROUND: Selection for genetic testing of BRCA1/BRCA2 is an important area of healthcare. Although testing costs for mutational analysis are falling, costs in North America remain in excess of US$3000 (UK price can be 690 pounds). Guidelines in most countries use a 10-20% threshold of detecting a mutation in BRCA1/2 combined within a family before mutational analysis is considered. A number of computer-based models have been developed. However, use of these models can be time consuming and difficult. The Manchester scoring system was developed in 2003 to simplify the selection process without losing accuracy. METHODS: In order to increase accuracy of prediction, breast pathology of the index case was incorporated into the Manchester scoring system based on 2156 samples from unrelated non-Jewish patients fully tested for BRCA1/2, and the scores were adapted accordingly. Results/ DISCUSSION: Data from breast pathology allowed adjustment of BRCA1 and combined BRCA1/2 scores alone. There was a lack of pathological homogeneity for BRCA2, therefore specific pathological correlates could not be identified. Upward adjustments in BRCA1 mutation prediction scores were made for grade 3 ductal cancers, oestrogen receptor (ER) and triple-negative tumours. Downward adjustments in the score were made for grade 1 tumours, lobular cancer, ductal carcinoma in situ and ER/HER2 positivity. Application of the updated scoring system led to four and nine more mutations in BRCA1 being identified at the 10% and 20% threshold, respectively. Furthermore, 65 and 58 fewer cases met the 10% and 20% threshold, respectively, for testing. Moreover, the adjusted score significantly improved the trade-off between sensitivity and specificity for BRCA1/2 prediction.
BACKGROUND: Selection for genetic testing of BRCA1/BRCA2 is an important area of healthcare. Although testing costs for mutational analysis are falling, costs in North America remain in excess of US$3000 (UK price can be 690 pounds). Guidelines in most countries use a 10-20% threshold of detecting a mutation in BRCA1/2 combined within a family before mutational analysis is considered. A number of computer-based models have been developed. However, use of these models can be time consuming and difficult. The Manchester scoring system was developed in 2003 to simplify the selection process without losing accuracy. METHODS: In order to increase accuracy of prediction, breast pathology of the index case was incorporated into the Manchester scoring system based on 2156 samples from unrelated non-Jewish patients fully tested for BRCA1/2, and the scores were adapted accordingly. Results/ DISCUSSION: Data from breast pathology allowed adjustment of BRCA1 and combined BRCA1/2 scores alone. There was a lack of pathological homogeneity for BRCA2, therefore specific pathological correlates could not be identified. Upward adjustments in BRCA1 mutation prediction scores were made for grade 3 ductal cancers, oestrogen receptor (ER) and triple-negative tumours. Downward adjustments in the score were made for grade 1 tumours, lobular cancer, ductal carcinoma in situ and ER/HER2 positivity. Application of the updated scoring system led to four and nine more mutations in BRCA1 being identified at the 10% and 20% threshold, respectively. Furthermore, 65 and 58 fewer cases met the 10% and 20% threshold, respectively, for testing. Moreover, the adjusted score significantly improved the trade-off between sensitivity and specificity for BRCA1/2 prediction.
Authors: Nasim Mavaddat; Daniel Barrowdale; Irene L Andrulis; Susan M Domchek; Diana Eccles; Heli Nevanlinna; Susan J Ramus; Amanda Spurdle; Mark Robson; Mark Sherman; Anna Marie Mulligan; Fergus J Couch; Christoph Engel; Lesley McGuffog; Sue Healey; Olga M Sinilnikova; Melissa C Southey; Mary Beth Terry; David Goldgar; Frances O'Malley; Esther M John; Ramunas Janavicius; Laima Tihomirova; Thomas V O Hansen; Finn C Nielsen; Ana Osorio; Alexandra Stavropoulou; Javier Benítez; Siranoush Manoukian; Bernard Peissel; Monica Barile; Sara Volorio; Barbara Pasini; Riccardo Dolcetti; Anna Laura Putignano; Laura Ottini; Paolo Radice; Ute Hamann; Muhammad U Rashid; Frans B Hogervorst; Mieke Kriege; Rob B van der Luijt; Susan Peock; Debra Frost; D Gareth Evans; Carole Brewer; Lisa Walker; Mark T Rogers; Lucy E Side; Catherine Houghton; JoEllen Weaver; Andrew K Godwin; Rita K Schmutzler; Barbara Wappenschmidt; Alfons Meindl; Karin Kast; Norbert Arnold; Dieter Niederacher; Christian Sutter; Helmut Deissler; Doroteha Gadzicki; Sabine Preisler-Adams; Raymonda Varon-Mateeva; Ines Schönbuchner; Heidrun Gevensleben; Dominique Stoppa-Lyonnet; Muriel Belotti; Laure Barjhoux; Claudine Isaacs; Beth N Peshkin; Trinidad Caldes; Miguel de la Hoya; Carmen Cañadas; Tuomas Heikkinen; Päivi Heikkilä; Kristiina Aittomäki; Ignacio Blanco; Conxi Lazaro; Joan Brunet; Bjarni A Agnarsson; Adalgeir Arason; Rosa B Barkardottir; Martine Dumont; Jacques Simard; Marco Montagna; Simona Agata; Emma D'Andrea; Max Yan; Stephen Fox; Timothy R Rebbeck; Wendy Rubinstein; Nadine Tung; Judy E Garber; Xianshu Wang; Zachary Fredericksen; Vernon S Pankratz; Noralane M Lindor; Csilla Szabo; Kenneth Offit; Rita Sakr; Mia M Gaudet; Christian F Singer; Muy-Kheng Tea; Christine Rappaport; Phuong L Mai; Mark H Greene; Anna Sokolenko; Evgeny Imyanitov; Amanda Ewart Toland; Leigha Senter; Kevin Sweet; Mads Thomassen; Anne-Marie Gerdes; Torben Kruse; Maria Caligo; Paolo Aretini; Johanna Rantala; Anna von Wachenfeld; Karin Henriksson; Linda Steele; Susan L Neuhausen; Robert Nussbaum; Mary Beattie; Kunle Odunsi; Lara Sucheston; Simon A Gayther; Kate Nathanson; Jenny Gross; Christine Walsh; Beth Karlan; Georgia Chenevix-Trench; Douglas F Easton; Antonis C Antoniou Journal: Cancer Epidemiol Biomarkers Prev Date: 2011-12-05 Impact factor: 4.254
Authors: Helen Byers; Yvonne Wallis; Elke M van Veen; Fiona Lalloo; Kim Reay; Philip Smith; Andrew J Wallace; Naomi Bowers; William G Newman; D Gareth Evans Journal: Eur J Hum Genet Date: 2016-06-08 Impact factor: 4.246