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BMC Med Genomics. 2015 Oct 15;8:63. doi: 10.1186/s12920-015-0140-y.

The impact of direct-to-consumer personal genomic testing on perceived risk of breast, prostate, colorectal, and lung cancer: findings from the PGen study.

Author information

1
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. dmc875@mail.harvard.edu.
2
Division of Genetics, Department of Medicine, Brigham and Women's Hospital, EC Alumnae Building, Suite 301, 41 Avenue Louis Pasteur, Boston, MA, 02115, USA. dmc875@mail.harvard.edu.
3
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. tvanderw@hsph.harvard.edu.
4
Pathway Genomics, San Diego, CA, USA. tamoreno@gmail.com.
5
23andMe Inc., Mountain View, CA, USA. joanna@23andme.com.
6
Department of Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor, MI, USA. jscottr@umich.edu.
7
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. pkraft@hsph.harvard.edu.
8
Division of Genetics, Department of Medicine, Brigham and Women's Hospital, EC Alumnae Building, Suite 301, 41 Avenue Louis Pasteur, Boston, MA, 02115, USA. rcgreen@genetics.med.harvard.edu.
9
Harvard Medical School, Boston, MA, USA. rcgreen@genetics.med.harvard.edu.
10
Partners Personalized Medicine, Boston, MA, USA. rcgreen@genetics.med.harvard.edu.

Abstract

BACKGROUND:

Direct access to genomic information has the potential to transform cancer risk counseling. We measured the impact of direct-to-consumer genomic risk information on changes to perceived risk (ΔPR) of breast, prostate, colorectal and lung cancer among personal genomic testing (PGT) customers. We hypothesized that ΔPR would reflect directionality of risk estimates, attenuate with time, and be modified by participant characteristics.

METHODS:

Pathway Genomics and 23andMe customers were surveyed prior to receiving PGT results, and 2 weeks and 6 months post-results. For each cancer, PR was measured on a 5-point ordinal scale from "much lower than average" to "much higher than average." PGT results, based on genotyping of common genetic variants, were dichotomized as elevated or average risk. The relationship between risk estimate and ΔPR was evaluated with linear regression; generalized estimating equations modeled this relationship over time.

RESULTS:

With the exception of lung cancer (for which ΔPR was positive regardless of result), elevated risk results were significantly associated with positive ΔPR, and average risk results with negative ΔPR (e.g., prostate cancer, 2 weeks: least squares-adjusted ΔPR = 0.77 for elevated risk versus -0.21 for average risk; p-valuedifference < 0.0001) among 1154 participants. Large changes were rare: for each cancer, <4 % of participants overall reported a ΔPR of ±3 or more units. Effect modification by age, cancer family history, and baseline interest was observed for breast, colorectal, and lung cancer, respectively. A pattern of decreasing impact on ΔPR over time was consistently observed, but this trend was significant only in the case of colorectal cancer.

CONCLUSIONS:

We have quantified the effect on consumer risk perception of returning genetic-based cancer risk information directly to consumers without clinician mediation. Provided via PGT, this information has a measurable but modest effect on perceived cancer risk, and one that is in some cases modified by consumers' non-genetic risk context. Our observations of modest marginal effect sizes, infrequent extreme changes in perceived risk, and a pattern of diminishing impact with time, suggest that the ability of PGT to effect changes to cancer screening and prevention behaviors may be limited by relatively small changes to perceived risk.

PMID:
26468061
PMCID:
PMC4606558
DOI:
10.1186/s12920-015-0140-y
[Indexed for MEDLINE]
Free PMC Article

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