| Literature DB >> 29300387 |
J Scott Roberts1, Jill O Robinson2, Pamela M Diamond3, Archana Bharadwaj4, Kurt D Christensen5, Kaitlyn B Lee2, Robert C Green5, Amy L McGuire2.
Abstract
PURPOSE: To examine patients' experiences with clinical use of whole-genome sequencing (WGS).Entities:
Keywords: cardiology; informed consent; patient education; patient satisfaction; primary care
Mesh:
Year: 2018 PMID: 29300387 PMCID: PMC6034997 DOI: 10.1038/gim.2017.223
Source DB: PubMed Journal: Genet Med ISSN: 1098-3600 Impact factor: 8.822
Sample Characteristics (n=202)
| No. (%), unless otherwise noted | Cardiology Cohort (n = 102) | Primary Care Cohort (n = 100) | Total Sample (n = 202) | ||
|---|---|---|---|---|---|
| WGS + FH (n=50) | FH− only (n=52) | WGS + FH (n=50) | FH− only (n=50) | ||
| Mean age, in years (SD) | 55.9 (16.1) | 55.9 (12.2) | 55.2 (7.0) | 54.6 (7.6) | 55.3 (11.3) |
| Range | 19–85 | 26–72 | 41–66 | 42–68 | 19–85 |
| Gender | |||||
| Female | 24 (48%) | 19 (36.5%) | 28 (56%) | 30 (60%) | 101 (50%) |
| Male | 26 (52%) | 33 (63.5%) | 22 (44%) | 20 (40%) | 101 (50%) |
| Race/Ethnicity | |||||
| Non-Hispanic White | 43 (86%) | 46 (88.5%) | 44 (88%) | 43 (86%) | 176 (87.1%) |
| Other | 7 (14%) | 6 (11.5%) | 6 (12%) | 7 (14%) | 26 (12.9%) |
| Annual household income | |||||
| $0–$34,999 | 11 (22.9%) | 5 (10%) | 2 (4.1%) | 4 (8.5%) | 22 (11.3%) |
| $35,000–$99,999 | 14 (29.2%) | 15 (30%) | 7 (14.3%) | 12 (25.5%) | 48 (24.7%) |
| ≥$100,000 | 23 (47.9%) | 30 (60%) | 40 (81.6%) | 31 (66%) | 124 (63.9%) |
| Highest education level | |||||
| Below college graduate | 14 (28%) | 10 (19.2%) | 3 (6%) | 11 (22%) | 38 (18.8%) |
| ≥College graduate | 36 (72%) | 42 (80.8%) | 47 (94%) | 39 (78%) | 164 (81.2%) |
Note: N = 8 did not report household income
Primary care cohort more likely than cardiology to be female, p < 0.05
Within primary care cohort, WGS + FH arm more likely than FH-only arm to be college graduate, p < .05
Understanding of Informed Consent
| Survey Item (Correct Answer) | % Correct |
|---|---|
| To study how genomic information is used in healthcare decisions (True) | 99% |
| To test a new gene-targeting drug (False) | 91% |
| To create a map of the human genome (False) | 67% |
| An experimental drug (False) | 100% |
| A blood draw (True) | 100% |
| At least 4 study visits (True) | 97% |
| Completing surveys (True) | 97% |
| Genetic testing of my family members (False) | 95% |
| I have a 50% chance of receiving info from my whole genome sequence (True) | 98% |
| I will definitely receive information from my whole genome sequence (False) | 94% |
| I have a 50% chance of receiving info about my family history (False) | 70% |
| I will definitely receive information about my family history (True) | 60% |
| My risk of developing certain diseases for which there are no known preventions, cures, or treatments available (True) | 98% |
| Personal genetic traits, such as eye and hair color (False) | 90% |
| New information that doctors or researchers do not understand (True) | 81% |
| My results will be placed in my medical record (True) | 100% |
| My results will be discarded when I complete this study (False) | 98% |
| Partners HealthCare System will pay for additional medical tests to follow up on my results (False) | 93% |
| I’m protected by federal law from genetic discrimination by health insurers & employers (True) | 92% |
| My results will not be accessible to anyone outside of Partners HealthCare System (False) | 87% |
| My de-identified WGS results will be shared with other researchers in a national database over the Internet (True) | 86% |
Findings from Results Disclosure Sessions
| Cardiology Cohort (n = 102) | Primary Care Cohort (n= 100) | Total Sample (n = 202) | ||||
|---|---|---|---|---|---|---|
| WGS + FH (n=50) | FH− only (n=52) | WGS + FH (n=50) | FH− only (n=50) | WGS + FH | FH-only | |
| How satisfied are you overall with how your doctor communicated with you? | 6 (0) | 6 (0) | 6 (0) | 6 (0) | 6 (0) | 6 (0) |
| How satisfied are you with how well you understand the information you just discussed with your doctor? | 6 (1) | 6 (0) | 6 (1) | 6 (0) | 6 (1) | 6 (0) |
| How well was your doctor able to explain new information and its meaning in a way you could understand? | 6 (0) | 6 (0) | 6 (0) | 6 (0) | 6 (0) | 6 (0) |
| How confident are you that you could fully explain the meaning of the info you just discussed to a family member? | 5 (1) | 6 (1) | 5 (1) | 6 (0) | 5 (1) | 6 (0.5) |
| How comfortable were you in asking your doctor questions about the information you just discussed? | 6 (0) | 6 (0) | 6 (1) | 6 (0) | 6 (0) | 6 (0) |
| How much new information did you receive from your results? (% endorsing ‘a lot’) | 58% | 5% | 42% | 5% | 51% | 5% |
| How well do you think you understood your results? (% endorsing ‘extremely’) | 18% | 40% | 35% | 62% | 26% | 51% |
| How would you rate the overall amount of information you received? (% endorsing ‘too much’) | 8% | 9% | 29% | 9% | 19% | 9% |
| 24.2 | 13.6 | 35.8 | 17.0 | 30.1 | 15.2 | |
Primary care cohort participants more likely to endorse “too much” information, p < .05
Primary care sessions longer than cardiology; WGS arm longer than FH-only arm; p < .001
Expected versus Perceived Utility of Results
| Survey item | % Expecting (BL) | % Endorsing (6M) | FH + WGS arm Odds of Endorsing at 6M (vs. FH-only arm) |
|---|---|---|---|
| Accurate identification of disease risks | 79.8 | 80.5 | |
| Influence current/future medical treatment | 85.1 | 68.1 | |
| Influence medical decision making | 86.9 | 54.5 | 1.51 (95%CI = 0.8 |
| Influence patient or their child’s reproductive decision making | 32.5 | 18.8 | 2.11 (95%CI = 0.95 |
| Influence choice of medications | 73.0 | 32.3 | 1.0 (95%CI = 0.5 |
| Influence end-of-life planning | 46.0 | 25.1 | 1.0 (95%CI = 0.5 |
Note: % Expecting are those who responded Probably Yes or Yes; % Endorsing are those who responded Slightly, Moderately or Definitely.
FH + WGS arm more likely to endorse at 6M vs. FH-only arm, p < .05
Analyses reported in this column controlled for patient age, gender, education, race/ethnicity, genetic literacy, and study cohort (cardiology vs. primary care)
Summary of Regression Analyses
| Predictors | Informed Consent Knowledge | Decisional Regret | Satisfaction with Communication | ||||||
|---|---|---|---|---|---|---|---|---|---|
| p | p | p | |||||||
| Age | −.012 | .011 | 0.29 | 1.004 | 0.97, 1.04 | 0.84 | −.004 | .017 | 0.83 |
| Gender | .706 | .261 | 0.07 | .873 | 0.40, 1.90 | 0.73 | .367 | .417 | 0.38 |
| Race | .456 | .387 | 0.24 | .886 | 0.29, 2.68 | 0.83 | .643 | .613 | 0.30 |
| Education | .984 | 0.33, 2.97 | 0.98 | −.009 | .556 | 0.99 | |||
| Genetic Literacy | .945 | 0.68, 1.31 | 0.74 | .048 | .166 | 0.77 | |||
| Numeracy | .954 | 0.89, 1.02 | 0.15 | −.012 | .033 | 0.71 | |||
| Study cohort (Primary care vs. cardiology) | −.367 | .248 | 0.14 | .646 | 0.31, 1.36 | 0.25 | −.071 | .397 | 0.86 |
| Randomization arm (WGS+FH vs. FH-only) | −.041 | .244 | 0.87 | −.106 | .392 | 0.79 | |||
Note: Multiple linear regression models used for informed consent knowledge and satisfaction with communication analyses; logistic regression model used for decisional regret analyses