Literature DB >> 28489507

Development and Validation of the PREMM5 Model for Comprehensive Risk Assessment of Lynch Syndrome.

Fay Kastrinos1, Hajime Uno1, Chinedu Ukaegbu1, Carmelita Alvero1, Ashley McFarland1, Matthew B Yurgelun1, Matthew H Kulke1, Deborah Schrag1, Jeffrey A Meyerhardt1, Charles S Fuchs1, Robert J Mayer1, Kimmie Ng1, Ewout W Steyerberg1, Sapna Syngal1.   

Abstract

Purpose Current Lynch syndrome (LS) prediction models quantify the risk to an individual of carrying a pathogenic germline mutation in three mismatch repair (MMR) genes: MLH1, MSH2, and MSH6. We developed a new prediction model, PREMM5, that incorporates the genes PMS2 and EPCAM to provide comprehensive LS risk assessment. Patients and Methods PREMM5 was developed to predict the likelihood of a mutation in any of the LS genes by using polytomous logistic regression analysis of clinical and germline data from 18,734 individuals who were tested for all five genes. Predictors of mutation status included sex, age at genetic testing, and proband and family cancer histories. Discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), and clinical impact was determined by decision curve analysis; comparisons were made to the existing PREMM1,2,6 model. External validation of PREMM5 was performed in a clinic-based cohort of 1,058 patients with colorectal cancer. Results Pathogenic mutations were detected in 1,000 (5%) of 18,734 patients in the development cohort; mutations included MLH1 (n = 306), MSH2 (n = 354), MSH6 (n = 177), PMS2 (n = 141), and EPCAM (n = 22). PREMM5 distinguished carriers from noncarriers with an AUC of 0.81 (95% CI, 0.79 to 0.82), and performance was similar in the validation cohort (AUC, 0.83; 95% CI, 0.75 to 0.92). Prediction was more difficult for PMS2 mutations (AUC, 0.64; 95% CI, 0.60 to 0.68) than for other genes. Performance characteristics of PREMM5 exceeded those of PREMM1,2,6. Decision curve analysis supported germline LS testing for PREMM5 scores ≥ 2.5%. Conclusion PREMM5 provides comprehensive risk estimation of all five LS genes and supports LS genetic testing for individuals with scores ≥ 2.5%. At this threshold, PREMM5 provides performance that is superior to the existing PREMM1,2,6 model in the identification of carriers of LS, including those with weaker phenotypes and individuals unaffected by cancer.

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Year:  2017        PMID: 28489507      PMCID: PMC5493047          DOI: 10.1200/JCO.2016.69.6120

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  35 in total

Review 1.  Traditional statistical methods for evaluating prediction models are uninformative as to clinical value: towards a decision analytic framework.

Authors:  Andrew J Vickers; Angel M Cronin
Journal:  Semin Oncol       Date:  2010-02       Impact factor: 4.929

2.  Validation and extension of the PREMM1,2 model in a population-based cohort of colorectal cancer patients.

Authors:  Francesc Balaguer; Judith Balmaña; Sergi Castellví-Bel; Ewout W Steyerberg; Montserrat Andreu; Xavier Llor; Rodrigo Jover; Sapna Syngal; Antoni Castells
Journal:  Gastroenterology       Date:  2007-10-26       Impact factor: 22.682

Review 3.  ACG clinical guideline: Genetic testing and management of hereditary gastrointestinal cancer syndromes.

Authors:  Sapna Syngal; Randall E Brand; James M Church; Francis M Giardiello; Heather L Hampel; Randall W Burt
Journal:  Am J Gastroenterol       Date:  2015-02-03       Impact factor: 10.864

4.  Beyond the usual prediction accuracy metrics: reporting results for clinical decision making.

Authors:  A Russell Localio; Steven Goodman
Journal:  Ann Intern Med       Date:  2012-08-21       Impact factor: 25.391

5.  One to 2-year surveillance intervals reduce risk of colorectal cancer in families with Lynch syndrome.

Authors:  Hans F A Vasen; Mohamed Abdirahman; Richard Brohet; Alexandra M J Langers; Jan H Kleibeuker; Mariette van Kouwen; Jan Jacob Koornstra; Henk Boot; Annemieke Cats; Evelien Dekker; Silvia Sanduleanu; Jan-Werner Poley; James C H Hardwick; Wouter H de Vos Tot Nederveen Cappel; Andrea E van der Meulen-de Jong; T Gie Tan; Maarten A J M Jacobs; Faig Lall A Mohamed; Sijbrand Y de Boer; Paul C van de Meeberg; Marie-Louise Verhulst; Jan M Salemans; Nico van Bentem; B Dik Westerveld; Juda Vecht; Fokko M Nagengast
Journal:  Gastroenterology       Date:  2010-03-02       Impact factor: 22.682

6.  Prediction of MLH1 and MSH2 mutations in Lynch syndrome.

Authors:  Judith Balmaña; David H Stockwell; Ewout W Steyerberg; Elena M Stoffel; Amie M Deffenbaugh; Julia E Reid; Brian Ward; Thomas Scholl; Brant Hendrickson; John Tazelaar; Lynn Anne Burbidge; Sapna Syngal
Journal:  JAMA       Date:  2006-09-27       Impact factor: 56.272

7.  Assessing the performance of prediction models: a framework for traditional and novel measures.

Authors:  Ewout W Steyerberg; Andrew J Vickers; Nancy R Cook; Thomas Gerds; Mithat Gonen; Nancy Obuchowski; Michael J Pencina; Michael W Kattan
Journal:  Epidemiology       Date:  2010-01       Impact factor: 4.822

8.  Performance of PREMM(1,2,6), MMRpredict, and MMRpro in detecting Lynch syndrome among endometrial cancer cases.

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

9.  Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer.

Authors:  Aung Ko Win; Mark A Jenkins; James G Dowty; Antonis C Antoniou; Andrew Lee; Graham G Giles; Daniel D Buchanan; Mark Clendenning; Christophe Rosty; Dennis J Ahnen; Stephen N Thibodeau; Graham Casey; Steven Gallinger; Loïc Le Marchand; Robert W Haile; John D Potter; Yingye Zheng; Noralane M Lindor; Polly A Newcomb; John L Hopper; Robert J MacInnis
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2016-10-31       Impact factor: 4.254

10.  Graphical assessment of internal and external calibration of logistic regression models by using loess smoothers.

Authors:  Peter C Austin; Ewout W Steyerberg
Journal:  Stat Med       Date:  2013-08-23       Impact factor: 2.373

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  47 in total

1.  Clinical Factors Associated with Urinary Tract Cancer in Individuals with Lynch Syndrome.

Authors:  Jonathan W Wischhusen; Chinedu Ukaegbu; Tara G Dhingra; Hajime Uno; Fay Kastrinos; Sapna Syngal; Matthew B Yurgelun
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-10-15       Impact factor: 4.254

Review 2.  Recent advances in Lynch syndrome.

Authors:  Leah H Biller; Sapna Syngal; Matthew B Yurgelun
Journal:  Fam Cancer       Date:  2019-04       Impact factor: 2.375

3.  SEOM clinical guideline on hereditary colorectal cancer (2019).

Authors:  C Guillén-Ponce; E Lastra; I Lorenzo-Lorenzo; T Martín Gómez; R Morales Chamorro; A B Sánchez-Heras; R Serrano; M C Soriano Rodríguez; J L Soto; L Robles
Journal:  Clin Transl Oncol       Date:  2020-01-24       Impact factor: 3.405

4.  Clinical characteristics of patients with colorectal cancer with double somatic mismatch repair mutations compared with Lynch syndrome.

Authors:  Rachel Pearlman; Sigurdis Haraldsdottir; Albert de la Chapelle; Jon G Jonasson; Sandya Liyanarachchi; Wendy L Frankel; Thorunn Rafnar; Kari Stefansson; Colin C Pritchard; Heather Hampel
Journal:  J Med Genet       Date:  2019-03-15       Impact factor: 6.318

5.  Community Practice Implementation of a Self-administered Version of PREMM1,2,6 to Assess Risk for Lynch Syndrome.

Authors:  Daniel G Luba; James A DiSario; Colleen Rock; Devki Saraiya; Kelsey Moyes; Krystal Brown; Kristen Rushton; Maydeen M Ogara; Mona Raphael; Dayna Zimmerman; Kimmie Garrido; Evelyn Silguero; Jonathan Nelson; Matthew B Yurgelun; Fay Kastrinos; Richard J Wenstrup; Sapna Syngal
Journal:  Clin Gastroenterol Hepatol       Date:  2017-06-28       Impact factor: 11.382

6.  When Should Patients Undergo Genetic Testing for Hereditary Colon Cancer Syndromes?

Authors:  Gregory Idos; Samir Gupta
Journal:  Clin Gastroenterol Hepatol       Date:  2017-11-10       Impact factor: 11.382

Review 7.  Colorectal Cancer in Young Adults.

Authors:  Anand Venugopal; Elena M Stoffel
Journal:  Curr Treat Options Gastroenterol       Date:  2019-03

8.  Germline Genetic Features of Young Individuals With Colorectal Cancer.

Authors:  Elena M Stoffel; Erika Koeppe; Jessica Everett; Peter Ulintz; Mark Kiel; Jenae Osborne; Linford Williams; Kristen Hanson; Stephen B Gruber; Laura S Rozek
Journal:  Gastroenterology       Date:  2017-11-14       Impact factor: 22.682

9.  Modern day screening for Lynch syndrome in endometrial cancer: the KEM experience.

Authors:  Nina Pauly; Thaïs Baert; Rita Schmutzler; Andreas du Bois; Stephanie Schneider; Kerstin Rhiem; Birgid Schömig-Markiefka; Janna Siemanowski; Sebastian Heikaus; Alexander Traut; Florian Heitz; Sonia Prader; Sarah Ehmann; Philipp Harter; Beyhan Ataseven
Journal:  Arch Gynecol Obstet       Date:  2021-03-12       Impact factor: 2.344

10.  Commentary: PREMM5 threshold of 2.5% is recommended to improve identification of PMS2 carriers.

Authors:  Fay Kastrinos; Hajime Uno; Sapna Syngal
Journal:  Fam Cancer       Date:  2018-10       Impact factor: 2.375

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