Hassan Roudgari1, Lindsey F Masson, Neva E Haites. 1. Department of Medicine & Therapeutics, College of Life Sciences & Medicine, Polwarth Building, Foresterhill, Aberdeen, UK. h.roudgari@abdn.ac.uk
Abstract
BACKGROUND: Drawing an informative pedigree is fundamental in genetic counselling. It is very common for some parts of pedigrees to remain ambiguous because of the proband's inability to recall the past history of her/his family. Current age, date of birth, date of death and age of diagnosis are the commonest missing information in pedigrees. METHODS: The Scottish Social Statistics website, National Statistics website and English language literature were used to model extrapolations. About 172 Grampian families and three high-risk Grampian families with complete information were chosen to evaluate the influence of extrapolations on models' performance. Differences between original data and extrapolated data were assessed by independent samples t-test. RESULTS: Changes made by extrapolations in age- and cancer-related information were not statistically significant (P > 0.05) in comparison with original data, except for average age of diagnosis of breast cancer (P = 0.03). The differences made by extrapolations in estimated probabilities generated by probability assessment models were small and ignorable except that for Tyrer-Cuzick model for Grampian family 3. CONCLUSION: Extrapolations based on National Health Statistics can scientifically cover missing information in a defined population with minimum effect on performance of probability assessment models.
BACKGROUND: Drawing an informative pedigree is fundamental in genetic counselling. It is very common for some parts of pedigrees to remain ambiguous because of the proband's inability to recall the past history of her/his family. Current age, date of birth, date of death and age of diagnosis are the commonest missing information in pedigrees. METHODS: The Scottish Social Statistics website, National Statistics website and English language literature were used to model extrapolations. About 172 Grampian families and three high-risk Grampian families with complete information were chosen to evaluate the influence of extrapolations on models' performance. Differences between original data and extrapolated data were assessed by independent samples t-test. RESULTS: Changes made by extrapolations in age- and cancer-related information were not statistically significant (P > 0.05) in comparison with original data, except for average age of diagnosis of breast cancer (P = 0.03). The differences made by extrapolations in estimated probabilities generated by probability assessment models were small and ignorable except that for Tyrer-Cuzick model for Grampian family 3. CONCLUSION: Extrapolations based on National Health Statistics can scientifically cover missing information in a defined population with minimum effect on performance of probability assessment models.
Authors: D G R Evans; D M Eccles; N Rahman; K Young; M Bulman; E Amir; A Shenton; A Howell; F Lalloo Journal: J Med Genet Date: 2004-06 Impact factor: 6.318
Authors: D Ford; D F Easton; M Stratton; S Narod; D Goldgar; P Devilee; D T Bishop; B Weber; G Lenoir; J Chang-Claude; H Sobol; M D Teare; J Struewing; A Arason; S Scherneck; J Peto; T R Rebbeck; P Tonin; S Neuhausen; R Barkardottir; J Eyfjord; H Lynch; B A Ponder; S A Gayther; M Zelada-Hedman Journal: Am J Hum Genet Date: 1998-03 Impact factor: 11.025