R W Grant1,2, M Hivert3, J C Pandiscio3, J C Florez4,5,6, D M Nathan4,5, J B Meigs3,5. 1. Division of General Medicine, Massachusetts General Hospital, 50 Staniford St, 9th floor, Boston, MA, 02114, USA. Rgrant@partners.org. 2. Harvard Medical School, Boston, MA, USA. Rgrant@partners.org. 3. Division of General Medicine, Massachusetts General Hospital, 50 Staniford St, 9th floor, Boston, MA, 02114, USA. 4. Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA. 5. Harvard Medical School, Boston, MA, USA. 6. Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA.
Abstract
AIMS/HYPOTHESIS: Advances in type 2 diabetes genetics have raised hopes that genetic testing will improve disease prediction, prevention and treatment. Little is known about current physician and patient views regarding type 2 diabetes genetic testing. We hypothesised that physician and patient views would differ regarding the impact of genetic testing on motivation and adherence. METHODS: We surveyed a nationally representative sample of US primary care physicians and endocrinologists (n = 304), a random sample of non-diabetic primary care patients (n = 152) and patients enrolled in a diabetes pharmacogenetics study (n = 89). RESULTS: Physicians and patients favoured genetic testing for diabetes risk prediction (79% of physicians vs 80% of non-diabetic patients would be somewhat/very likely to order/request testing, p = 0.7). More patients than physicians (71% vs 23%, p < 0.01) indicated that a 'high risk' result would be very likely to improve motivation to adopt preventive lifestyle changes. Patients favoured genetic testing to guide therapy (78% of patients vs 48% of physicians very likely to request/recommend testing, p < 0.01) and reported that genetic testing would make them 'much more motivated' to adhere to medications (72% vs 18% of physicians, p < 0.01). Many physicians (39%) would be somewhat/very likely to order genetic testing before published evidence of clinical efficacy. CONCLUSIONS/ INTERPRETATION: Despite the paucity of current data, physicians and patients reported high expectations that genetic testing would improve patient motivation to adopt key behaviours for the prevention or control of type 2 diabetes. This suggests the testable hypothesis that 'genetic' risk information might have greater value to motivate behaviour change compared with standard risk information.
AIMS/HYPOTHESIS: Advances in type 2 diabetes genetics have raised hopes that genetic testing will improve disease prediction, prevention and treatment. Little is known about current physician and patient views regarding type 2 diabetes genetic testing. We hypothesised that physician and patient views would differ regarding the impact of genetic testing on motivation and adherence. METHODS: We surveyed a nationally representative sample of US primary care physicians and endocrinologists (n = 304), a random sample of non-diabetic primary care patients (n = 152) and patients enrolled in a diabetes pharmacogenetics study (n = 89). RESULTS: Physicians and patients favoured genetic testing for diabetes risk prediction (79% of physicians vs 80% of non-diabeticpatients would be somewhat/very likely to order/request testing, p = 0.7). More patients than physicians (71% vs 23%, p < 0.01) indicated that a 'high risk' result would be very likely to improve motivation to adopt preventive lifestyle changes. Patients favoured genetic testing to guide therapy (78% of patients vs 48% of physicians very likely to request/recommend testing, p < 0.01) and reported that genetic testing would make them 'much more motivated' to adhere to medications (72% vs 18% of physicians, p < 0.01). Many physicians (39%) would be somewhat/very likely to order genetic testing before published evidence of clinical efficacy. CONCLUSIONS/ INTERPRETATION: Despite the paucity of current data, physicians and patients reported high expectations that genetic testing would improve patient motivation to adopt key behaviours for the prevention or control of type 2 diabetes. This suggests the testable hypothesis that 'genetic' risk information might have greater value to motivate behaviour change compared with standard risk information.
Authors: Michael M Engelgau; Linda S Geiss; Jinan B Saaddine; James P Boyle; Stephanie M Benjamin; Edward W Gregg; Edward F Tierney; Nilka Rios-Burrows; Ali H Mokdad; Earl S Ford; Giuseppina Imperatore; K M Venkat Narayan Journal: Ann Intern Med Date: 2004-06-01 Impact factor: 25.391
Authors: Ornella Ludovico; Fabio Pellegrini; Rosa Di Paola; Antonio Minenna; Sandra Mastroianno; Marina Cardellini; Maria Adelaide Marini; Francesco Andreozzi; Olga Vaccaro; Giorgio Sesti; Vincenzo Trischitta Journal: Obesity (Silver Spring) Date: 2007-05 Impact factor: 5.002
Authors: William H Herman; Thomas J Hoerger; Michael Brandle; Katherine Hicks; Stephen Sorensen; Ping Zhang; Richard F Hamman; Ronald T Ackermann; Michael M Engelgau; Robert E Ratner Journal: Ann Intern Med Date: 2005-03-01 Impact factor: 25.391
Authors: Jose C Florez; Kathleen A Jablonski; Nick Bayley; Toni I Pollin; Paul I W de Bakker; Alan R Shuldiner; William C Knowler; David M Nathan; David Altshuler Journal: N Engl J Med Date: 2006-07-20 Impact factor: 91.245
Authors: Ewan R Pearson; Louise A Donnelly; Charlotte Kimber; Adrian Whitley; Alex S F Doney; Mark I McCarthy; Andrew T Hattersley; Andrew D Morris; Colin N A Palmer Journal: Diabetes Date: 2007-05-22 Impact factor: 9.461
Authors: Jessica L Waxler; Kelsey E O'Brien; Linda M Delahanty; James B Meigs; Jose C Florez; Elyse R Park; Barbara R Pober; Richard W Grant Journal: J Genet Couns Date: 2012-10 Impact factor: 2.537
Authors: Jason L Vassy; Kurt D Christensen; Melody J Slashinski; Denise M Lautenbach; Sridharan Raghavan; Jill Oliver Robinson; Jennifer Blumenthal-Barby; Lindsay Zausmer Feuerman; Lisa Soleymani Lehmann; Michael F Murray; Robert C Green; Amy L McGuire Journal: Per Med Date: 2015 Impact factor: 2.512
Authors: Richard W Grant; James B Meigs; Jose C Florez; Elyse R Park; Robert C Green; Jessica L Waxler; Linda M Delahanty; Kelsey E O'Brien Journal: Clin Trials Date: 2011-10 Impact factor: 2.486
Authors: Catharine Wang; Erynn S Gordon; Catharine B Stack; Ching-Ti Liu; Tricia Norkunas; Lisa Wawak; Michael F Christman; Robert C Green; Deborah J Bowen Journal: Clin Trials Date: 2013-11-11 Impact factor: 2.486