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Article

Genetic Literacy and Communication of Genetic Information in Families Concerned with Hereditary Breast and Ovarian Cancer: A Cross-Study Comparison in Two Countries and within a Timeframe of More Than 10 Years

by
Carla Pedrazzani
1,
Chang Ming
1,
Nicole Bürki
2,
Maria Caiata-Zufferey
3,
Pierre O. Chappuis
4,
Debra Duquette
5,
Karl Heinimann
6,
Viola Heinzelmann-Schwarz
2,
Rossella Graffeo-Galbiati
7,
Sofia D. Merajver
8,9,
Kara J. Milliron
9,
Christian Monnerat
10,
Olivia Pagani
7,
Manuela Rabaglio
11 and
Maria C. Katapodi
1,* on behalf of the CASCADE Consortium
1
Department of Clinical Research, Faculty of Medicine, University of Basel, 4055 Basel, Switzerland
2
Women’s Clinic, University Hospital Basel, 4031 Basel, Switzerland
3
Department of Business Economics, Health and Social Care, University of Applied Science and Arts of Southern Switzerland, 6928 Manno, Switzerland
4
Oncogenetics Unit, Service of Oncology, University Hospital of Geneva, 1205 Geneva, Switzerland
5
Feinberg School of Medicine, Northwestern University, Chicago, IL 60208, USA
6
Medical Genetics, University Hospital Basel, 4031 Basel, Switzerland
7
Oncology Institute of Southern Switzerland, 6900 Lugano, Switzerland
8
University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
9
Roger Comprehensive Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
10
Jura Hospital, 2800 Delémont, Switzerland
11
Inselspital University Hospital, 3010 Bern, Switzerland
*
Author to whom correspondence should be addressed.
Cancers 2021, 13(24), 6254; https://doi.org/10.3390/cancers13246254
Submission received: 6 November 2021 / Revised: 5 December 2021 / Accepted: 7 December 2021 / Published: 13 December 2021

Abstract

:

Simple Summary

This cross-study comparison uses data collected over 10 years from families living in the US and in Switzerland in order to compare genetic literacy between individuals who had genetic counselling for hereditary breast/ovarian cancer (HBOC) and one or more of their relatives who did not, and examines factors influencing genetic literacy both at the individual and at the family level. The study identifies genetic risk factors and signs of HBOC that remain unclear, even to individuals who had genetic consultation, and highlights the gaps in the dissemination of genetic information. Sensitivity analysis examines the dissemination of genetic information from the individual who had counselling to relatives within the same family that did not.

Abstract

Examining genetic literacy in families concerned with hereditary breast and ovarian cancer (HBOC) helps understand how genetic information is passed on from individuals who had genetic counseling to their at-risk relatives. This cross-study comparison explored genetic literacy both at the individual and the family level using data collected from three sequential studies conducted in the U.S. and Switzerland over ≥10 years. Participants were primarily females, at-risk or confirmed carriers of HBOC-associated pathogenic variants, who had genetic counselling, and ≥1 of their relatives who did not. Fifteen items assessed genetic literacy. Among 1933 individuals from 518 families, 38.5% had genetic counselling and 61.5% did not. Although genetic literacy was higher among participants who had counselling, some risk factors were poorly understood. At the individual level, genetic literacy was associated with having counselling, ≤5 years ago, higher education, and family history of cancer. At the family level, genetic literacy was associated with having counselling, higher education, and a cancer diagnosis. The findings suggest that specific genetic information should be emphasized during consultations, and that at-risk relatives feel less informed about inherited cancer risk, even if information is shared within families. There is a need to increase access to genetic information among at-risk individuals.

1. Introduction

Genetic literacy is the ability to understand and use genetic information for health-related decision-making [1,2]. It refers to awareness about genetic risk factors, how they contribute to disease, understanding the chance of inheriting the genetic predisposition and developing the disease [1,2,3,4]. Genetic literacy facilitates seeking genetic evaluation and making informed decisions about genetic testing [1,3,5]. However, there are significant knowledge gaps in the general population, in stark contrast to the current levels of genetic and genomic discoveries and achievements in medicine and public health [1,3,6,7]. Factors like age, race and ethnicity, education and socioeconomic status, and personal and family health history influence genetic literacy [3,6,8,9], as well as access to specialized services [1,10]. Finally, variations in genetic literacy have been reported for people living in different countries [7,9].
Genetic literacy is especially important for families concerned with actionable (Tier 1) genetic conditions, such as hereditary breast and ovarian cancer (HBOC) [11]. HBOC is caused by germline autosomal dominant pathogenic variants; first-, second-, and third-degree relatives have a 50%, 25%, and 12.5% probability, respectively, of inheriting the familial pathogenic variant [12]. In addition to managing the cancer risk of individuals carrying HBOC-associated pathogenic variants, it is also essential to address the potentially increased risk to relatives through cascade testing [11,13]. Due to privacy laws in most countries, individuals carrying HBOC-associated variants have a key role in disseminating genetic information to relatives and in advocating for cascade testing [14,15]. The proportion of relatives who initiate contact with genetic services and their knowledge of cancer genetics increases with genetic consultation [16,17], and when counselled individuals share information received during the consultation process [18,19].
Examining genetic literacy in the context of HBOC helps understand how genetic information is passed on from healthcare providers to index cases i.e., first in the family identified with a pathogenic variant, during genetic counselling, and from index cases to relatives. This is an essential step to support HBOC cascade testing. The purpose of this study is to explore genetic literacy among individuals who had genetic counselling for HBOC, i.e., whether they can recall information about genetic risk factors, modes of inheritance, and probability of developing an HBOC-associated cancer, and how much of this information has been shared with their relatives. Specific aims are first to describe and compare genetic literacy between two groups of individuals, namely those who had genetic counselling for HBOC and their relatives who did not; and second to explore factors influencing genetic literacy both at the individual and at the family level. To achieve these aims we examined data collected from three sequential studies conducted in the U.S. and Switzerland over a timeframe of more than 10 years. Pooling data across studies is feasible, since there are many similarities in the delivery and contents of genetic counselling in different countries [20].

2. Materials and Methods

This cross-study comparison used descriptive data from three family-based studies: a cross-sectional study conducted in 2007 in the US [21], baseline data from a randomized trial (RCT) conducted in 2012 in the US (NCT 01612338) [22], and baseline data from an ongoing cohort initiated in 2017 in Switzerland (NCT03124212) [23]. All studies were approved by the appropriate Institutional Review and Scientific Advisory Boards and Ethical Committees (HUM00011707 and HUM00055949, approved on 10 May 2007 and 14 October 2011 respectively, are exempt due to analysis of fully anonymized data; BASEC 2016-02052, approved on 6 February 2017, is ongoing). For this cross-study comparison we pooled participants and divided them into two distinct groups: individuals who had genetic counselling for HBOC, i.e., “expose-d” to counselling and one or more of their first, or second-, or third-degree relatives who did not have counselling, i.e., “not exposed”.
All three studies recruited individuals 18 years or older using the same procedures, identifying potentially eligible participants either from genetic clinics [21,23] or from a state-wide cancer registry [22]. The 2007 US-based cross-sectional study identified females who had genetic counselling in a comprehensive cancer center with approximately 65% identified as carrying an HBOC-associated pathogenic variant [21]. The 2012 US-based RCT identified females diagnosed with breast cancer younger than 45 years old from a state-wide cancer registry, with 25% reportedly receiving genetic consultation at enrolment [22]. The Swiss-based cohort recruits both males and females who are confirmed carriers of an HBOC-associated pathogenic variant and who joined the cohort between January 2017 and January 2021 [23].
In all three studies, potentially eligible participants were mailed study materials from each recruitment site (genetic clinic or cancer registry). Those agreeing to participate returned a signed consent form, revealing their name and address to the research team, and were asked to approach and pass on recruitment materials to relatives. Relatives who accepted participation also returned a signed consent, revealing their name, address, and degree of biological relation to the person who initiated the invitation. Inviting relatives was not a mandatory requirement for participating in the three studies, while each participant could invite one or more relatives. Details about recruitment of participants and relatives have been reported for each original study [21,22,23]. All studies mailed self-administered questionnaires, which were identical for those that had counselling and those who did not.
Genetic literacy was assessed with items used in all three studies, and was conceptualized as having two components, i.e., objective knowledge of cancer genetics and genetic affinity [9,24]. Objective knowledge of cancer genetics included genetic risk factors, and probabilities of carrying a pathogenic variant and developing the disease. This information consists the “core knowledge” explained during genetic counselling. Objective knowledge was assessed with 13 items, asking participants to respond “True”, “False”, or “Do not Know” to statements related to this “core knowledge” [25]. Objective knowledge of cancer genetics was examined first through an overall score, calculated by summing the number of correct answers, and second by examining each knowledge item individually to reveal patterns of potentially not well-understood information. Cronbach’s α was greater than 0.85 in all three original studies and was 0.88 in the whole sample of the cross-study comparison. Genetic affinity, i.e., perceptions of being informed about cancer genetics and cancer risk, was assessed with two items asking: “How well informed do you feel about the probability of getting cancer?” ranging from 1 “Not at all informed” to 7 “Very Informed” and “How much do you know about the genetics of cancer?” ranging from 1 “Not at all” to 7 “A great deal”. A genetic affinity score was calculated by summing responses in these two items.
Questionnaires also assessed demographics i.e., age, gender, race and ethnicity, marital status, education, employment, and clinical characteristics i.e., personal history of cancer “Yes” or “No”; family history of cancer “Yes” or “No”; years since personal cancer diagnosis “≤5 years” or “>5 years”; and years since genetic counselling “≤5 years” or “>5 years”. We selected five years as a cut-off to assess the relevance of personal cancer diagnosis and years since genetic counselling since international guidelines consider this timeframe indicative of cancer survival [26].
Data analyses were performed in R version 4.0.4 [27]. Demographic and clinical characteristics were described by counselling status (counselled/not counselled) per study and for the total sample. Continuous variables were described using means and standard deviations (SD) and categorical variables with frequency of observations (n) and percentages (%). Differences between the two groups (counselled/not counselled) were examined on two primary outcomes i.e., objective knowledge of cancer genetics and genetic affinity, using t-test for means and chi-square or Fisher’s exact test for counts. The two-sided significance level was set at 5% for all tests, and Bonferroni corrections were used to address multiple testing.
A linear mixed-effect model examined factors that may influence the sum scores of primary outcomes, i.e., demographics, personal and family history of cancer, time since cancer diagnosis and time since genetic counselling, recruitment from genetic clinics or the cancer registry, and country (US and Switzerland). The mixed model incorporated a study-specific random intercept which accommodated for including subjects from the same family unit (non-independent observations) within each study. All factors were considered as fixed effects. To address factors influencing primary outcomes within family units, we also conducted sensitivity analyses by adding a family unit-specific random intercept to the previous linear mixed-effect model. The sensitivity analyses included only family units with more than one member enrolled in each of the three studies.

3. Results

The overall sample included a total of n = 1933 participants from n = 518 family units, with the majority (n = 1660, 85.9%) being from the US. Approximately 70% self-identified as White and 30% as belonging to minority racial or ethnic groups, i.e., Black or African American, American Indian or Alaskan Native, Arab or Arab American, Asian or Southeast Asian, Native Hawaiian or other Pacific Islander for the US-based samples; and African or Asian for the Swiss-based sample (Table 1). Given the small number of participants from minority racial and ethnic minority groups, we treated them as a single group in subsequent analyses.
Among participants, 745 (38.5%) had genetic counselling and 1188 (61.5%) did not. In the overall sample and in each individual study separately, participants who had counselling were more likely to have a cancer diagnosis compared to those who did not (69.5% vs. 50.6%, p < 0.0001). Those who had counselling were older, more likely to self-identify as White, married, and had higher education.
Knowledge of cancer genetics (total score) was overall higher in individuals who had counselling, with approximately 10 out of 13 items answered correctly (11, 9.5 and 9.5 items out of 13 in the three studies, respectively). The total score for individuals who did not have genetic counselling was 7.8 (Table 2).
The items least identified as risk factors in the overall sample, even among counselled individuals, were: “…is from Ashkenazi Jewish descent” (38.3% counselled and 13.5% not counselled), “having a relative diagnosed with breast cancer younger than 50 years old” (57.9% counselled and 63.6% not counselled “) and “…having a male relative with breast cancer” (65.1% counselled and 47.8% not counselled). All other items were answered correctly by more than 70% of participants who had counselling. “Having multiple relatives with breast cancer” was the one item identified as a genetic risk factor from more than 80% of all respondents (81.7% counselled and 80.6% not counselled).
Risk factors with the greatest discrepancies among individuals who had counselling and those who did not were: “…a family history of ovarian cancer” (74.6% counselled and 51.1% not counselled); “…a family history of breast cancer from the dad’s side of the family” (74.6% counselled and 56.7% not counselled); “…a pathogenic variant in the BRCA1 or BRCA2 genes” (88.1% counselled and 53.7% not counselled); and “…have cases of breast cancer in more than one generation” (84.6% counselled and 53.5% not counselled).
Individuals who had counselling reported higher genetic affinity and feeling more informed about the probability of getting cancer and about the genetics of cancer compared to those who did (Table 3). The total genetic affinity score was 7.3 out of 14 among those not counselled. There was a low-moderate correlation between knowledge of cancer genetics and genetic affinity in the overall sample (r = 0.38) and in the three studies (r = 0.28; r = 0.32; and r = 0.50, respectively).
Regression analyses in the overall sample showed that at the individual level higher genetic literacy (knowledge of cancer genetics and genetic affinity) were associated with having had counselling, less or equal to five years ago, a higher education, and a family history of cancer (Table 4). Being younger and self-identified as White were associated with higher knowledge of cancer genetics, while having had cancer was associated with higher genetic affinity. Sensitivity analysis at the family level, i.e., considering whether participants were members of the same family unit, showed that counselling, higher education, and a cancer diagnosis were still associated with higher knowledge of cancer genetics and with higher genetic affinity (Table 5). Younger age and self-identified as White were associated with higher knowledge of cancer genetics among members of the same family unit. Variance partition coefficients in sensitivity analysis showed that only 7% and 6% of variance in knowledge of cancer genetics and genetic affinity, respectively, was contributed by family clustering.

4. Discussion

This cross-study comparison used family-based data collected in the US and in Switzerland over a timeframe of more than 10 years to examine genetic literacy in individuals who had counselling for HBOC and their relatives who did not, and factors influencing genetic literacy both at the individual and at the family level. Genetic literacy was higher among participants who had counselling, compared to those who did not. Our findings support the role of genetic counseling in improving genetic literacy [1,3,18,19,28].
We identified specific risk factors and signs of HBOC that remain unclear, even to individuals who had a genetic consultation. Despite being important red flags for HBOC, early age of cancer onset, breast cancer in male relatives, and having Ashkenazi Jewish ancestry were not recognized as risk factors for most individuals. Genetic consultations provide personalized information and likely focus on individual risk factors. Thus, some of the above risk factors may not have been emphasized equally in all consultations, which may explain our findings. Nevertheless, HBOC cases need to be vigilant in identifying red flags in their family history since a new cancer diagnosis among relatives may provide important information that could change their own plans of managing hereditary cancer risk. Those who test negative (uninformative result) and those who do not qualify for testing are encouraged to periodically contact the genetic testing center and re-evaluate their status. Given the lifelong consequences of carrying an HBOC-associated pathogenic variant, periodic “check-ins” with genetic specialists can clarify important information and reassess cancer risk management plans.
Important risk factors, such as having a family history of ovarian cancer and a family history of breast cancer from the paternal side of the family were less frequently identified among individuals who did not have genetic counselling. This finding further highlights gaps in the dissemination of genetic information to at-risk individuals that have been reported over a period of 20 years [6,7,29,30,31]. Individuals who are unsure about how and from whom HBOC-associated pathogenic variants can be inherited are more likely to overlook their hereditary cancer risk if affected relatives are on the paternal side of the family. One possible explanation for this persistent finding may be related to unbalanced presentations of HBOC from mass media [32,33]. However, in light of the rapid evolution in cancer genetics, tracking changes in genetic literacy is extremely important. As knowledge continues to expand and educational materials are developed and made available to at-risk individuals and the lay public, the healthcare community needs to address these persistent knowledge gaps.
Consistent with studies that examined genetic literacy in the general population [3,6,8,9], participants who were younger, self-identified as White, had higher education, and a personal and/or a family history of cancer were more likely to know about risk factors and to feel better informed about cancer genetics. It is difficult to disentangle the effects of counselling from the experiential knowledge gained from a personal and/or a family history of cancer on genetic literacy. Our data show that having a consultation less than five years ago was associated with both higher knowledge of cancer genetics and higher genetic affinity, while time since a personal cancer diagnosis did not influence genetic literacy. These findings mean that the genetic consultation likely provides understandable and actionable information beyond the information that is discussed in the context of a personal cancer diagnosis [1,3,18,19,28].
Cascade testing for Tier 1 genetic conditions, such as HBOC, relies on assumptions of open family communication and effective dissemination of genetic information within members of family units. However, it is unclear if this communication strategy can ensure effective and accurate information transmission. We explored communication of genetic information within family units using sensitivity analysis, including only families with a member who received counseling and one or more at-risk relative who did not. By adding the random intercept term for each specific family unit into our modelling, unmeasured confounders, like level of family communication and information sharing between counselled and not counselled individuals, were controlled at that level. Interestingly, after adding family unit as a level in the analysis, genetic counselling was still significantly associated with knowledge of cancer genetics and with genetic affinity. Variance partition coefficients of sensitivity analyses showed that 6–7% of overall variation in objective knowledge and genetic affinity were explained by family clustering. If genetic information was openly and accurately shared from individuals who had counselling to their relatives, the variation in genetic literacy in members from different family units would have been observed more easily compared to the variation between members of random family units. This further implies that tailored educational interventions aiming to promote cascade testing should consider the characteristics of the family unit in addition to characteristics of the different individuals.
Using datasets from three studies could introduce a bias in the cross-study comparisons due to heterogeneity among the primary studies. In our case, the three primary studies had comparable aims and recruitment methods, which controlled for such bias and made comparisons feasible. Since participants from minority ethnic and racial groups had significantly lower levels of genetic literacy, our findings point to the widening gap of disparities in healthcare brought upon the clinical application of genetics [34,35,36]. However, participants from different ethnic and racial minority groups were very heterogeneous among the US and the Swiss-based samples, and were recruited primarily from one study. Thus, our findings are likely not applicable to non-White/Caucasian individuals and families, but without any inference to specific ethnic and racial minority groups. The Swiss sample was smaller, which may have also influenced findings regarding the impact of country and year of study on genetic literacy. HBOC status could only be ascertained for clinic-based samples. Finally, for the sensitivity analyses, we removed individuals without any relatives, which may have led to insufficient sample size.

5. Conclusions

Our cross-study comparison demonstrated the need for increased access to genetic information among at-risk individuals and that the lay public needs more assistance from healthcare professionals to understand complex genetic information and use it to inform plans for cancer risk management [37,38]. Our findings highlighted the role of counselling in improving genetic literacy and demonstrated persistent knowledge gaps and misconceptions, and that important red flags for HBOC remain poorly understood. Continued follow-up with genetic services could clarify and reinforce information that is overlooked or not well-understood. Addressing persistent knowledge gaps about aspects of HBOC, and racial and ethnic disparities in genetic care, should be priority public health goals. Efforts to improve family communication of genetic information should be enhanced with interventions at the clinical (support to carriers of pathogenic variants), legal (healthcare providers ability to provide tailored assistance with family communication) and public health (policies to improve access to genetic services) levels [14,39,40].

Author Contributions

Conceptualization: M.C.K., C.M. (Chang Ming) and C.P.; methodology: M.C.K., C.M. (Chang Ming) and C.P.; validation: C.M. (Chang Ming) and C.P.; formal analysis: C.M. (Chang Ming); investigation: M.C.K. and C.P.; resources: N.B., P.O.C., D.D., R.G.-G., K.H., S.D.M., K.J.M., C.M. (Chang Ming) and M.R.; data curation: C.M. (Chang Ming) and C.P.; writing—original draft preparation: M.C.K., C.P. and C.M. (Chang Ming); writing—review and editing: M.C.K., N.B., M.C.-Z., P.O.C., D.D., K.H., V.H.-S., R.G.-G., S.D.M., K.J.M., C.M. (Christian Monnerat), O.P., C.P. and M.R.; visualization: C.M. (Chang Ming) and C.P.; supervision: M.C.K. and O.P.; project administration: D.D., C.M. (Chang Ming), C.P. and K.J.M.; funding acquisition: M.C.K., N.B., M.C.-Z., P.O.C., D.D., R.G.-G., K.H., S.D.M., K.J.M., C.M. (Christian Monnerat) and M.R.; All authors have read and agreed to the published version of the manuscript.

Funding

The cross-sectional study conducted in 2007 in the U.S. was funded by the Oncology Nursing Foundation, 2007 Major Breast Cancer Research Award. The randomized trial conducted in 2012 in the U.S. was funded by Centers for Disease Control and Prevention (CDC), 5U48DP001901-03 and by the Robert Wood Johnson Foundation (RWJF)—Nurse Faculty Scholars Award (Award # 68039). The ongoing cohort that was initiated in 2017 in Switzerland was funded by the University of Basel, Forschungsfonds 2016; the Swiss Cancer League (KLS-4294-08-2017) and the Swiss Cancer Research Foundation (KFS-5293-02-2021). Publication was funded by the “Publication Fund of the University of Basel for Open Access”.

Institutional Review Board Statement

The studies were conducted according to the guidelines of the Declaration of Helsinki. The cross-sectional and RCT studies were approved by the Institutional Review Board from the University of Michigan (HUM00011707 and HUM00055949) and are currently exempt due to analysis of fully anonymized data. The ongoing Swiss-based cohort has been approved by the Ethikkommission Nordwest- und Zentralschweiz (BASEC 2016-02052).

Informed Consent Statement

Written consent was obtained from all subjects involved in the three studies.

Data Availability Statement

Raw data are available upon request to Maria C. Katapodi ([email protected]).

Acknowledgments

Kari E. Mendelsohn-Victor, University of Michigan School of Nursing, and Beth Anderson, and Jenna McLoskly, Cancer-Genomics Program—Michigan Department of Health and Human Services for patient and relative identification, recruitment, and assessment of eligibility for the randomized trial conducted in 2012 in the U.S. Members of the CASCADE Consortium for ongoing recruitment and retention of individuals with pathogenic variants and relatives and for scientific contributions for the implementation of the CASCADE cohort.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hurle, B.; Citrin, T.; Jenkins, J.F.; Kaphingst, K.A.; Lamb, N.; Roseman, J.E.; Bonham, V.L. What does it mean to be genomically literate?: National Human Genome Research Institute Meeting Report. Genet. Med. 2013, 15, 658–663. [Google Scholar] [CrossRef] [Green Version]
  2. Boerwinkel, D.J.; Yarden, A.; Waarlo, A.J. Reaching a Consensus on the Definition of Genetic Literacy that Is Required from a Twenty-First-Century Citizen. Sci. Educ. 2017, 26, 1087–1114. [Google Scholar] [CrossRef] [Green Version]
  3. Lea, D.; Kaphingst, K.; Bowen, D.; Lipkus, I.; Hadley, D. Communicating Genetic and Genomic Information: Health Literacy and Numeracy Considerations. Public Health Genom. 2011, 14, 279–289. [Google Scholar] [CrossRef] [PubMed]
  4. Smerecnik, C.M.; Mesters, I.; de Vries, N.K.; de Vries, H. Educating the general public about multifactorial genetic disease: Applying a theory-based framework to understand current public knowledge. Genet. Med. 2008, 10, 251–258. [Google Scholar] [CrossRef] [Green Version]
  5. Syurina, E.; Brankovic, I.; Probst-Hensch, N.; Brand, A. Genome-Based Health Literacy: A New Challenge for Public Health Genomics. Public Health Genom. 2011, 14, 201–210. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Krakow, M.; Ratcliff, C.; Hesse, B.W.; Greenberg-Worisek, A.J. Assessing Genetic Literacy Awareness and Knowledge Gaps in the US Population: Results from the Health Information National Trends Survey. Public Health Genom. 2017, 20, 343–348. [Google Scholar] [CrossRef]
  7. Chapman, R.; Likhanov, M.; Selita, F.; Zakharov, I.; Smith-Woolley, E.; Kovas, Y. New literacy challenge for the twenty-first century: Genetic knowledge is poor even among well educated. J. Community Genet. 2018, 10, 73–84. [Google Scholar] [CrossRef] [Green Version]
  8. Kaphingst, K.A.; Blanchard, M.; Milam, L.; Pokharel, M.; Elrick, A.; Goodman, M. Relationships Between Health Literacy and Genomics-Related Knowledge, Self-Efficacy, Perceived Importance, and Communication in a Medically Underserved Population. J. Health Commun. 2016, 21, 58–68. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Haga, S.B.; Barry, W.T.; Mills, R.; Ginsburg, G.S.; Svetkey, L.; Sullivan, J.; Willard, H.F. Public Knowledge of and Attitudes Toward Genetics and Genetic Testing. Genet. Test. Mol. Biomark. 2013, 17, 327–335. [Google Scholar] [CrossRef]
  10. Tilburt, J.C.; James, K.M.; Sinicrope, P.S.; Eton, D.T.; A Costello, B.; Carey, J.; A Lane, M.; Ehlers, S.L.; Erwin, P.J.; E Nowakowski, K.; et al. Factors Influencing Cancer Risk Perception in High Risk Populations: A Systematic Review. Hered. Cancer Clin. Pract. 2011, 9, 2–15. [Google Scholar] [CrossRef] [Green Version]
  11. Khoury, M.J.; Evans, J.P. A Public Health Perspective on a National Precision Medicine Cohort. JAMA 2015, 313, 2117–2118. [Google Scholar] [CrossRef] [Green Version]
  12. Christinat, A.; Pagani, O. Practical aspects of genetic counseling in breast cancer: Lights and shadows. Breast 2013, 22, 375–382. [Google Scholar] [CrossRef]
  13. Kuchenbaecker, K.B.; Hopper, J.L.; Barnes, D.R.; Phillips, K.-A.; Mooij, T.M.; Roos-Blom, M.-J.; Jervis, S.; Van Leeuwen, F.E.; Milne, R.L.; Andrieu, N.; et al. Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers. JAMA 2017, 317, 2402–2416. [Google Scholar] [CrossRef] [Green Version]
  14. Roberts, M.C.; Dotson, W.D.; DeVore, C.S.; Bednar, E.; Bowen, D.J.; Ganiats, T.G.; Green, R.F.; Hurst, G.M.; Philp, A.R.; Ricker, C.; et al. Delivery Of Cascade Screening For Hereditary Conditions: A Scoping Review Of The Literature. Health Aff. 2018, 37, 801–808. [Google Scholar] [CrossRef] [PubMed]
  15. Schwiter, R.; Rahm, A.K.; Williams, J.L.; Sturm, A.C. How Can We Reach At-Risk Relatives? Efforts to Enhance Communication and Cascade Testing Uptake: A Mini-Review. Curr. Genet. Med. Rep. 2018, 6, 21–27. [Google Scholar] [CrossRef]
  16. Forrest, L.E.; Burke, J.; Bacic, S.; Amor, D.J. Increased genetic counseling support improves communication of genetic information in families. Genet. Med. 2008, 10, 167–172. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Hodgson, J.; Metcalfe, S.; Gaff, C.; Donath, S.; Delatycki, M.B.; Winship, I.; Skene, L.; Aitken, M.; Halliday, J. Outcomes of a randomised controlled trial of a complex genetic counselling intervention to improve family communication. Eur. J. Hum. Genet. 2015, 24, 356–360. [Google Scholar] [CrossRef] [Green Version]
  18. Himes, D.O.; Davis, S.H.; Lassetter, J.H.; Peterson, N.E.; Clayton, M.; Birmingham, W.C.; Kinney, A. Does family communication matter? Exploring knowledge of breast cancer genetics in cancer families. J. Community Genet. 2019, 10, 481–487. [Google Scholar] [CrossRef] [PubMed]
  19. Himes, D.O.; Clayton, M.; Donaldson, G.W.; Ellington, L.; Buys, S.S.; Kinney, A. Breast Cancer Risk Perceptions among Relatives of Women with Uninformative Negative BRCA1/2 Test Results: The Moderating Effect of the Amount of Shared Information. J. Genet. Couns. 2015, 25, 258–269. [Google Scholar] [CrossRef] [Green Version]
  20. Ormond, K.E.; Laurino, M.Y.; Barlow-Stewart, K.; Wessels, T.; Macaulay, S.; Austin, J.; Middleton, A. Genetic counseling globally: Where are we now? Am. J. Med Genet. Part C Semin. Med Genet. 2018, 178, 98–107. [Google Scholar] [CrossRef]
  21. Katapodi, M.C.; Northouse, L.L.; Milliron, K.J.; Liu, G.; Merajver, S.D. Individual and family characteristics associated with BRCA1/2 genetic testing in high-risk families. Psycho-Oncology 2012, 22, 1336–1343. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Katapodi, M.C.; Duquette, D.; Yang, J.J.; Mendelsohn-Victor, K.; Anderson, B.; Nikolaidis, C.; Mancewicz, E.; Northouse, L.; Duffy, S.; Ronis, D.; et al. Recruiting families at risk for hereditary breast and ovarian cancer from a statewide cancer registry: A methodological study. Cancer Causes Control. 2017, 28, 191–201. [Google Scholar] [CrossRef]
  23. Katapodi, M.C.; Viassolo, V.; Caiata-Zufferey, M.; Nikolaidis, C.; Bührer-Landolt, R.; Buerki, N.; Graffeo, R.; Horváth, H.C.; Kurzeder, C.; Rabaglio, M.; et al. Cancer Predisposition Cascade Screening for Hereditary Breast/Ovarian Cancer and Lynch Syndromes in Switzerland: Study Protocol. JMIR Res. Protoc. 2017, 6, e184. [Google Scholar] [CrossRef] [PubMed]
  24. Dar-Nimrod, I.; MacNevin, G.; Godwin, A.; Lynch, K.; Cohen, T.M.; Ganesan, A.; Morandini, J. Genetic Knowledge within a National Australian Sample: Comparisons with Other Diverse Populations. Public Health Genom. 2018, 21, 133–143. [Google Scholar] [CrossRef]
  25. Katapodi, M.C.; Northouse, L.L.; Schafenacker, A.M.; Duquette, D.; Duffy, S.A.; Ronis, D.L.; Anderson, B.; Janz, N.K.; McLosky, J.; Milliron, K.J.; et al. Using a state cancer registry to recruit young breast cancer survivors and high-risk relatives: Protocol of a randomized trial testing the efficacy of a targeted versus a tailored intervention to increase breast cancer screening. BMC Cancer 2013, 13, 97. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Mariotto, A.B.; Noone, A.-M.; Howlader, N.; Cho, H.; Keel, G.E.; Garshell, J.; Woloshin, S.; Schwartz, L.M. Cancer Survival: An Overview of Measures, Uses, and Interpretation. J. Natl. Cancer Inst. Monogr. 2014, 2014, 145–186. [Google Scholar] [CrossRef] [Green Version]
  27. Team RC. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2015. Available online: https://www.R-project.org/ (accessed on 7 June 2013).
  28. Schmidlen, T.J.; Scheinfeldt, L.B.; Zhaoyang, R.; Kasper, R.; Sweet, K.; Gordon, E.S.; A Keller, M.; Stack, C.; Gharani, N.; Daly, M.B.; et al. Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative. J. Genet. Couns. 2015, 25, 385–394. [Google Scholar] [CrossRef] [Green Version]
  29. Miesfeldt, S.; Cohn, W.; Ropka, M.; Jones, S. Knowledge about breast cancer risk factors and hereditary breast cancer among early-onset breast cancer survivors. Fam. Cancer 2001, 1, 135–141. [Google Scholar] [CrossRef]
  30. Vuckovic, N.; Harris, E.L.; Valanis, B.; Stewart, B. Consumer knowledge and opinions of genetic testing for breast cancer risk. Am. J. Obstet. Gynecol. 2003, 189, S48–S53. [Google Scholar] [CrossRef]
  31. Hesse-Biber, S.; Dwyer, A.A.; Yi, S. Parent of origin differences in psychosocial burden and approach to BRCA risk management. Breast J. 2020, 26, 734–738. [Google Scholar] [CrossRef]
  32. Gottlieb, N. The Age of Breast Cancer Awareness: What Is the Effect of Media Coverage? J. Natl. Cancer Inst. 2001, 93, 1520–1522. [Google Scholar] [CrossRef] [PubMed]
  33. Sabel, M.S.; Cin, S.D. Trends in Media Reports of Celebrities’ Breast Cancer Treatment Decisions. Ann. Surg. Oncol. 2016, 23, 2795–2801. [Google Scholar] [CrossRef]
  34. Nikolaidis, C.; Duquette, D.; Mendelsohn-Victor, K.E.; Anderson, B.; Copeland, G.; Milliron, K.J.; Merajver, S.D.; Janz, N.K.; Northouse, L.L.; Duffy, S.A.; et al. Disparities in genetic services utilization in a random sample of young breast cancer survivors. Genet. Med. 2019, 21, 1363–1370. [Google Scholar] [CrossRef]
  35. Cragun, D.; Weidner, A.; Lewis, C.; Bonner, D.; Kim, J.; Vadaparampil, S.T.; Pal, T. Racial disparities inBRCAtesting and cancer risk management across a population-based sample of young breast cancer survivors. Cancer 2017, 123, 2497–2505. [Google Scholar] [CrossRef] [Green Version]
  36. Conley, C.C.; Ketcher, D.; Reblin, M.; Kasting, M.L.; Cragun, D.; Kim, J.; Ashing, K.T.; Knott, C.L.; Hughes-Halbert, C.; Pal, T.; et al. The big reveal: Family disclosure patterns of BRCA genetic test results among young Black women with invasive breast cancer. J. Genet. Couns. 2020, 29, 410–422. [Google Scholar] [CrossRef] [PubMed]
  37. Kosenko, K.A.; Binder, A.; Hurley, R. Celebrity Influence and Identification: A Test of the Angelina Effect. J. Health Commun. 2016, 21, 318–326. [Google Scholar] [CrossRef]
  38. Borzekowski, D.L.; Guan, Y.; Smith, K.C.; Erby, L.H.; Roter, D.L. The Angelina effect: Immediate reach, grasp, and impact of going public. Genet. Med. 2014, 16, 516–521. [Google Scholar] [CrossRef] [Green Version]
  39. Force, U.P.S.T.; Owens, D.K.; Davidson, K.; Krist, A.H.; Barry, M.J.; Cabana, M.; Caughey, A.B.; Doubeni, C.A.; Epling, J.W.; Kubik, M.; et al. Risk Assessment, Genetic Counseling, and Genetic Testing for BRCA-Related Cancer. JAMA 2019, 322, 652–665. [Google Scholar] [CrossRef] [Green Version]
  40. Baroutsou, V.; Underhill-Blazey, M.; Appenzeller-Herzog, C.; Katapodi, M. Interventions Facilitating Family Communication of Genetic Testing Results and Cascade Screening in Hereditary Breast/Ovarian Cancer or Lynch Syndrome: A Systematic Review and Meta-Analysis. Cancers 2021, 13, 925. [Google Scholar] [CrossRef] [PubMed]
Table 1. Demographics and clinical characteristics of the samples.
Table 1. Demographics and clinical characteristics of the samples.
CharacteristicsTotal Sample
n = 1933
Study 1 (2007)
n = 370
Study 2 (2013)
n = 1290
Study 3 (2017)
n = 273
GC (+) *
n = 745
GC (−) ^
n = 1188
pGC (+)
n = 200
GC (−)
n = 170
pGC (+)
n = 313
GC (−)
n = 977
pGC (+)
n = 232
GC (−)
n = 41
p
Age (years)—mean (SD)50.3 (10.3)48.5 (11.0)<0.00150.6 (11.0)48.7 (16.0)0.5348.7 (7.0)48.3 (9.7)0.5352 (12.8)51 (15.3)0.70
Race and ethnicity—White (%)78.469.5<0.00191.094.1167.164.20.3882.895.10.07
Married or Partnered—Yes (%)86.793.9<0.00175.566.50.0299.799.5178.975.60.69
Elementary school (%)10.320.9<0.00018.514.10.0415.722.70.0014.74.90.79
High school degree (%)50.156.924.531.262.361.455.656.1
University/Post-graduate (%)38.920.767.054.721.414.338.431.7
Employed—Yes (%)64.064.1165.567.60.7466.163.80.4859.958.51
Cancer diagnosis—Yes (%)69.550.6<0.000153.511.8<0.000189.759.2<0.000156.07.3<0.001
Family history cancer—Yes (%)80.885.40.0167.571.20.5188.587.20.6181.9100.0<0.01
* GC (+) Counselled; ^ GC (−) Not counselled.
Table 2. Objective knowledge of cancer genetics.
Table 2. Objective knowledge of cancer genetics.
Total Sample
n = 1933
Study 1 (2007)
n = 370
Study 2 (2013)
n = 1290
Study 3 (2019)
n = 273
GC (+) *
n = 745
GC (−) ^
n = 1188
GC (+)
n = 200
GC (−)
n = 170
GC (+)
n = 313
GC (−)
n = 977
GC (+)
n = 232
GC (−)
n = 41
Correct (%)pCorrect (%)pCorrect (%)pCorrect (%)p
Cancer can be caused by a pathogenic variant passed on from one generation to the next91.476.0<0.000196.591.20.0586.372.7<0.000194.092.70.72
Families with a pathogenic variant in the BRCA1 or BRCA2 genes are likely to have cases of breast cancer in more than one generation84.653.5<0.000187.557.6<0.00177.651.4<0.000191.487.80.55
A woman’s risk for getting breast cancer is higher when she…
…has a family history of ovarian cancer74.651.1<0.000180.569.40.0165.547.5<0.000181.961.00.004
…has a relative diagnosed with breast cancer younger than 50 years old57.963.60.0172.061.80.0476.766.1<0.00120.312.20.31
…has a family history of breast cancer from the dad’s side of the family74.656.7<0.000188.587.10.7962.351.4<0.00179.358.5<0.01
…has a family history of breast cancer from the mom’s side of the family87.877.3<0.00193.592.90.9982.775.1<0.0189.763.4<0.001
…has breast and ovarian cancer in the same side of the family82.068.7<0.000188.085.30.5478.966.6<0.000181.048.8<0.001
…has a pathogenic variant in the BRCA1 or BRCA2 genes88.153.7<0.000189.076.5<0.0182.149.0<0.000195.361.0<0.0001
…is from Ashkenazi Jewish descent38.313.5<0.000162.533.5<0.00132.210.3<0.000125.44.9<0.01
…has a male relative who had breast cancer65.147.8<0.000173.065.90.1760.144.7<0.000165.146.30.03
…has a relative with breast cancer in both breasts78.968.3<0.00186.085.30.9675.165.9<0.0178.053.70.001
…has a relative who had both breast and ovarian cancer82.671.5<0.00185.084.10.9281.569.8<0.000181.961.0<0.01
…has multiple relatives with breast cancer81.780.60.5891.594.10.4484.779.70.0669.446.3<0.01
Total correct answers
(0–13)—mean (SD)
9.9 (3.2)7.8 (3.8)<0.000110.9 (2.9)9.8 (2.9)<0.0019.5 (3.6)7.5 (3.8)<0.00019.5 (2.8)7.0 (3.9)0.0002
* GC (+) Counselled; ^ GC (−) Not counselled. Bold: p-value still significant after Bonferroni correction.
Table 3. Genetic affinity.
Table 3. Genetic affinity.
Total Sample
n = 1933
Study 1 (2007)
n = 370
Study 2 (2013)
n = 1290
Study 3 (2019)
n = 273
GC (+) *
n = 745
GC (−) ^ n = 1188 GC (+)
n = 200
GC (−)
n = 170
GC (+)
n = 313
GC (−)
n = 977
GC (+)
n = 232
GC (−)
n = 41
Mean (SD)pMean (SD)pMean (SD)pMean (SD)p
How informed do you feel about the chances of getting cancer? (1–7)5.74.7<0.00016.14.9<0.00015.54.6<0.00015.74.90.02
(1.3)(1.8)(1.2)(1.4)(1.6)(1.8)(1.1)(1.8)
How much do you know about the genetics of cancer?
(1–7)
4.63.0<0.00015.03.8<0.00014.42.8<0.00014.43.6<0.01
(1.5)(1.7)(1.2)(1.6)(1.7)(1.6)(1.4)(1.7)
Sum score (2–14)10.07.3<0.000110.98.6<0.00019.57.1<0.00019.98.10.003
(2.9)(3.3)(2.4)(2.8)(3.4)(3.3)(2.3)(3.6)
* GC (+) Counselled; ^ GC (−) Not counselled. Bold: p-value still significant after Bonferroni correction.
Table 4. Fixed effects from linear mixed-effect models for factors influencing knowledge of cancer genetics and genetic affinity in the overall sample at the individual level.
Table 4. Fixed effects from linear mixed-effect models for factors influencing knowledge of cancer genetics and genetic affinity in the overall sample at the individual level.
Knowledge of Cancer Genetics
(n = 1895) *
Genetic Affinity
(n = 1895) *
EstimateStandard ErrorpEstimateStandard Errorp
Age−0.020.007<0.001−0.00040.0070.95
Race and ethnicity (ref: White)1.680.18<0.00010.0740.170.66
Education—(ref: Elementary school)1.121.24<0.00010.590.12<0.0001
Employment (ref: No employment)0.260.160.110.130.150.40
Cancer diagnosis (ref: No cancer)0.210.210.330.590.21<0.01
Genetic counselling (ref: No counselling)0.800.27<0.011.590.25<0.0001
Family history of cancer (ref: No history)1.450.25<0.00010.500.230.03
Recruitment (ref: Clinic)2.353.120.991.983.321.00
Country (ref: US)2.823.130.991.383.321.00
≤5 years since cancer diagnosis (ref: Never diagnosed with cancer)0.050.320.880.390.300.19
>5 years since cancer diagnosis (ref: Never diagnosed with cancer)0.360.210.090.290.190.14
≤5 years since counselling (ref: Never counselled)0.860.31<0.010.340.290.21
>5 years since counselling (ref: Never counselled)1.160.34<0.0010.680.320.03
* the number of participants is lower compared to the overall sample due to missing data. Bold: p-value still significant after Bonferroni correction.
Table 5. Fixed effects from linear mixed-effect model for factors influencing knowledge of cancer genetics and genetic affinity in members from the same family unit.
Table 5. Fixed effects from linear mixed-effect model for factors influencing knowledge of cancer genetics and genetic affinity in members from the same family unit.
Knowledge of Cancer Genetics
(n = 1163) *
Genetic Affinity
(n = 1163) *
EstimateStandard ErrorpEstimateStandard Errorp
Age−0.030.008<0.0001<0.00010.0070.99
Race and ethnicity (ref: White)1.470.26<0.00010.0180.240.94
Education (ref: Elementary school)0.980.15<0.00010.540.14<0.0001
Employment (ref: No employment)0.270.200.18−0.0830.180.65
Cancer diagnosis (ref: No cancer)0.720.27<0.010.780.250.002
Genetic counselling (ref: No counselling)0.840.320.011.630.30<0.0001
Family history of cancer (ref: No history)0.500.420.240.220.380.58
Recruitment (ref: Clinic)1.811.800.241.862.210.40
Country (ref: US)2.131.820.241.082.220.62
≤5 years since cancer diagnosis (ref: Never diagnosed with cancer)−0.080.430.830.530.390.18
>5 years since cancer diagnosis (ref: Never diagnosed with cancer)0.200.310.510.200.280.50
≤5 years since counselling (ref: Never counselled)0.190.390.63−0.030.350.93
>5 years since counselling (ref: Never counselled)0.650.450.140.640.410.11
* the number of participants is lower compared to the overall sample. Individuals were members of 518 family units. Bold: p-value still significant after Bonferroni correction.
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Pedrazzani, C.; Ming, C.; Bürki, N.; Caiata-Zufferey, M.; Chappuis, P.O.; Duquette, D.; Heinimann, K.; Heinzelmann-Schwarz, V.; Graffeo-Galbiati, R.; Merajver, S.D.; et al. Genetic Literacy and Communication of Genetic Information in Families Concerned with Hereditary Breast and Ovarian Cancer: A Cross-Study Comparison in Two Countries and within a Timeframe of More Than 10 Years. Cancers 2021, 13, 6254. https://doi.org/10.3390/cancers13246254

AMA Style

Pedrazzani C, Ming C, Bürki N, Caiata-Zufferey M, Chappuis PO, Duquette D, Heinimann K, Heinzelmann-Schwarz V, Graffeo-Galbiati R, Merajver SD, et al. Genetic Literacy and Communication of Genetic Information in Families Concerned with Hereditary Breast and Ovarian Cancer: A Cross-Study Comparison in Two Countries and within a Timeframe of More Than 10 Years. Cancers. 2021; 13(24):6254. https://doi.org/10.3390/cancers13246254

Chicago/Turabian Style

Pedrazzani, Carla, Chang Ming, Nicole Bürki, Maria Caiata-Zufferey, Pierre O. Chappuis, Debra Duquette, Karl Heinimann, Viola Heinzelmann-Schwarz, Rossella Graffeo-Galbiati, Sofia D. Merajver, and et al. 2021. "Genetic Literacy and Communication of Genetic Information in Families Concerned with Hereditary Breast and Ovarian Cancer: A Cross-Study Comparison in Two Countries and within a Timeframe of More Than 10 Years" Cancers 13, no. 24: 6254. https://doi.org/10.3390/cancers13246254

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