Literature DB >> 7713397

ARCAD: a method for estimating age-dependent disease risk associated with mutation carrier status from family data.

C Le Bihan1, C Moutou, L Brugières, J Feunteun, C Bonaïti-Pellié.   

Abstract

We present ARCAD, a method to estimate the disease risk associated with mutation carrier status using data on families ascertained by affected individuals, in which a germline mutation has been detected. Because the event of interest, the age of onset, is a censored variable, the method uses the survival analysis approach to formulate the likelihood. Provided that selection criteria are clearly defined, the ascertainment bias is removed by including a correction term in the likelihood computation. We simulated family data and selected those with a proband affected before age 17, and at least one or at least two relatives affected before age 46. We show that including the correction for the ascertainment provides reliable estimates of the risk, even when many individuals are not tested for the mutation. An application to cancer risk and germline p53 mutations is presented. We routinely investigate the p53 status for all the children treated in the Department of Pediatric Oncology at the Institute Gustave Roussy, whose family displays at least one relative affected by cancer before age 46. We identified 5 families with an inherited germline p53 mutation. The risk for any cancer for a mutation carrier estimated by ARCAD was 42% within the age class 0-16 years, 38% within the age class 17-45 years, and 63% after 45 years, with a lifetime risk of 85%. These risks are almost entirely explained by the occurrence of the six most frequent cancers encountered in the Li-Fraumeni syndrome.

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Mesh:

Year:  1995        PMID: 7713397     DOI: 10.1002/gepi.1370120103

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  15 in total

1.  Bias and efficiency in family-based gene-characterization studies: conditional, prospective, retrospective, and joint likelihoods.

Authors:  P Kraft; D C Thomas
Journal:  Am J Hum Genet       Date:  2000-03       Impact factor: 11.025

2.  PEL: an unbiased method for estimating age-dependent genetic disease risk from pedigree data unselected for family history.

Authors:  F Alarcon; C Bourgain; M Gauthier-Villars; V Planté-Bordeneuve; D Stoppa-Lyonnet; C Bonaïti-Pellié
Journal:  Genet Epidemiol       Date:  2009-07       Impact factor: 2.135

Review 3.  Developmental origins of fusion-negative rhabdomyosarcomas.

Authors:  Ken Kikuchi; Brian P Rubin; Charles Keller
Journal:  Curr Top Dev Biol       Date:  2011       Impact factor: 4.897

4.  Non-parametric estimation of survival in age-dependent genetic disease and application to the transthyretin-related hereditary amyloidosis.

Authors:  Flora Alarcon; Violaine Planté-Bordeneuve; Malin Olsson; Grégory Nuel
Journal:  PLoS One       Date:  2018-09-25       Impact factor: 3.240

5.  A prospective biological study in relation to a family with Li-Fraumeni syndrome.

Authors:  Olaia Aurtenetxe Sáez; Begoña Calvo; Ana Fernández-Teijeiro; Pedro Pérez; Aurora Navajas
Journal:  Clin Transl Oncol       Date:  2012-05       Impact factor: 3.405

6.  Are there low-penetrance TP53 Alleles? evidence from childhood adrenocortical tumors.

Authors:  J M Varley; G McGown; M Thorncroft; L A James; G P Margison; G Forster; D G Evans; M Harris; A M Kelsey; J M Birch
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7.  Hereditary cancer syndromes.

Authors:  Nils Rahner; Verena Steinke
Journal:  Dtsch Arztebl Int       Date:  2008-10-10       Impact factor: 5.594

8.  Breast cancer in the young: role of the geneticist.

Authors:  Ashley H Woodson; Jessica L Profato; Kimberly I Muse; Jennifer K Litton
Journal:  J Thorac Dis       Date:  2013-06       Impact factor: 2.895

9.  Familial aggregation of urinary tract and bone tumors: searching for a syndrome.

Authors:  Andreas Frings; Jochen B Geigl; Bernadette Liegl-Atzwanger; Andreas Leithner
Journal:  Case Rep Med       Date:  2012-05-20

10.  Predictive diagnosis of the cancer prone Li-Fraumeni syndrome by accident: new challenges through whole genome array testing.

Authors:  T Schwarzbraun; A C Obenauf; A Langmann; U Gruber-Sedlmayr; K Wagner; M R Speicher; P M Kroisel
Journal:  J Med Genet       Date:  2009-03-05       Impact factor: 6.318

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