To explore laypersons’ understanding of individualized cancer risk estimates, and to identify conceptual problems that may limit this understanding.
Risk prediction models are increasingly used to provide people with information about their individual risk of cancer and other diseases. However, laypersons may have difficulty understanding individualized risk information, because of conceptual as well as computational problems.
A qualitative study was conducted using focus groups. Semi-structured interviews explored participants’ understandings of the concept of risk, and their interpretations of a hypothetical individualized colorectal cancer risk estimate.
Setting and participants
Eight focus groups were conducted with 48 adults aged 50–74 years residing in two major US metropolitan areas. Participants had high school or greater education, some familiarity with information technology, and no personal or family history of cancer.
Several important conceptual problems were identified. Most participants thought of risk not as a neutral statistical concept, but as signifying danger and emotional threat, and viewed cancer risk in terms of concrete risk factors rather than mathematical probabilities. Participants had difficulty acknowledging uncertainty implicit to the concept of risk, and judging the numerical significance of individualized risk estimates. The most challenging conceptual problems related to conflict between subjective and objective understandings of risk, and difficulties translating aggregate-level objective risk estimates to the individual level.
Several conceptual problems limit laypersons’ understanding of individualized cancer risk information. These problems have implications for future research on health numeracy, and for the application of risk prediction models in clinical and public health settings.
cancer; numeracy; risk; risk perception
A major promise of genomic research is information that can transform health care and public health through earlier diagnosis, more effective prevention and treatment of disease, and avoidance of drug side effects. Although there is interest in the early adoption of emerging genomic applications in cancer prevention and treatment, there are substantial evidence gaps that are further compounded by the difficulties of designing adequately powered studies to generate this evidence, thus limiting the uptake of these tools into clinical practice. Comparative effectiveness research (CER) is intended to generate evidence on the “real-world” effectiveness compared with existing standards of care so informed decisions can be made to improve health care. Capitalizing on funding opportunities from the American Recovery and Reinvestment Act of 2009, the National Cancer Institute funded seven research teams to conduct CER in genomic and precision medicine and sponsored a workshop on CER on May 30, 2012, in Bethesda, Maryland. This report highlights research findings from those research teams, challenges to conducting CER, the barriers to implementation in clinical practice, and research priorities and opportunities in CER in genomic and precision medicine. Workshop participants strongly emphasized the need for conducting CER for promising molecularly targeted therapies, developing and supporting an integrated clinical network for open-access resources, supporting bioinformatics and computer science research, providing training and education programs in CER, and conducting research in economic and decision modeling.
In contemporary oncology practices there is an increasing emphasis on concurrent evaluation of multiple genomic alterations within the biological pathways driving tumorigenesis. At the foundation of this paradigm shift are several commercially available tumor panels using next-generation sequencing to develop a more complete molecular blueprint of the tumor. Ideally, these would be used to identify clinically actionable variants that can be matched with available molecularly targeted therapy, regardless of the tumor site or histology. Currently, there is little information available on the post-analytic processes unique to next-generation sequencing platforms used by the companies offering these tests. Additionally, evidence of clinical validity showing an association between the genetic markers curated in these tests with treatment response to approved molecularly targeted therapies is lacking across all solid-tumor types. To date, there is no published data of improved outcomes when using the commercially available tests to guide treatment decisions. The uniqueness of these tests from other genomic applications used to guide clinical treatment decisions lie in the sequencing platforms used to generate large amounts of genomic data, which have their own related issues regarding analytic and clinical validity, necessary precursors to the evaluation of clinical utility. The generation and interpretation of these data will require new evidentiary standards for establishing not only clinical utility, but also analytical and clinical validity for this emerging paradigm in oncology practice.
Recent advances in genomic research have demonstrated a substantial role for genomic factors in predicting response to cancer therapies. Researchers in the fields of cancer pharmacogenomics and pharmacoepidemiology seek to understand why individuals respond differently to drug therapy, in terms of both adverse effects and treatment efficacy. To identify research priorities as well as the resources and infrastructure needed to advance these fields, the National Cancer Institute (NCI) sponsored a workshop titled “Cancer Pharmacogenomics: Setting a Research Agenda to Accelerate Translation” on July 21, 2009, in Bethesda, MD. In this commentary, we summarize and discuss five science-based recommendations and four infrastructure-based recommendations that were identified as a result of discussions held during this workshop. Key recommendations include 1) supporting the routine collection of germline and tumor biospecimens in NCI-sponsored clinical trials and in some observational and population-based studies; 2) incorporating pharmacogenomic markers into clinical trials; 3) addressing the ethical, legal, social, and biospecimen- and data-sharing implications of pharmacogenomic and pharmacoepidemiologic research; and 4) establishing partnerships across NCI, with other federal agencies, and with industry. Together, these recommendations will facilitate the discovery and validation of clinical, sociodemographic, lifestyle, and genomic markers related to cancer treatment response and adverse events, and they will improve both the speed and efficiency by which new pharmacogenomic and pharmacoepidemiologic information is translated into clinical practice.
Cancer pharmacogenomics have contributed a number of important discoveries to current cancer treatment, changing the paradigm of treatment decisions. Both somatic and germline mutations are utilized to better understand the underlying biology of cancer growth and treatment response. The level of evidence required to fully translate pharmacogenomic discoveries into the clinic has relied heavily on randomized control trials. In this review, the use of observational studies, as well as, the use of adaptive trials and next generation sequencing to develop the required level of evidence for clinical implementation are discussed.
pharmacogenomics; pharmacogenetics; somatic; germline; targeted therapy
Given the high incidence of colorectal cancer (CRC), and the availability of procedures that can detect disease and remove precancerous lesions, there is a need for a model that estimates the probability of developing CRC across various age intervals and risk factor profiles.
The development of separate CRC absolute risk models for men and women included estimating relative risks and attributable risk parameters from population-based case-control data separately for proximal, distal, and rectal cancer and combining these estimates with baseline age-specific cancer hazard rates based on Surveillance, Epidemiology, and End Results (SEER) incidence rates and competing mortality risks.
For men, the model included a cancer-negative sigmoidoscopy/colonoscopy in the last 10 years, polyp history in the last 10 years, history of CRC in first-degree relatives, aspirin and nonsteroidal anti-inflammatory drug (NSAID) use, cigarette smoking, body mass index (BMI), current leisure-time vigorous activity, and vegetable consumption. For women, the model included sigmoidoscopy/colonoscopy, polyp history, history of CRC in first-degree relatives, aspirin and NSAID use, BMI, leisure-time vigorous activity, vegetable consumption, hormone-replacement therapy (HRT), and estrogen exposure on the basis of menopausal status. For men and women, relative risks differed slightly by tumor site. A validation study in independent data indicates that the models for men and women are well calibrated.
We developed absolute risk prediction models for CRC from population-based data, and a simple questionnaire suitable for self-administration. This model is potentially useful for counseling, for designing research intervention studies, and for other applications.
As the number of cancer survivors continues to grow, research investigating the factors that affect cancer outcomes, such as disease recurrence, risk of second malignant neoplasms, and the late effects of cancer treatments, becomes ever more important. Numerous epidemiologic studies have investigated factors that affect cancer risk, but far fewer have addressed the extent to which demographic, lifestyle, genomic, clinical, and psychosocial factors influence cancer outcomes. To identify research priorities as well as resources and infrastructure needed to advance the field of cancer outcomes and survivorship research, the National Cancer Institute sponsored a workshop titled “Utilizing Data from Cancer Survivor Cohorts: Understanding the Current State of Knowledge and Developing Future Research Priorities” on November 3, 2011, in Washington, DC. This commentary highlights recent findings presented at the workshop, opportunities to leverage existing data, and recommendations for future research, data, and infrastructure needed to address high priority clinical and research questions. Multidisciplinary teams that include epidemiologists, clinicians, biostatisticians, and bioinformaticists will be essential to facilitate future cancer outcome studies focused on improving clinical care of cancer patients, identifying those at high risk of poor outcomes, and implementing effective interventions to ultimately improve the quality and duration of survival.
Two selective estrogen receptor modulators (SERMs), tamoxifen and raloxifene, have been shown in randomized clinical trials to reduce the risk of developing primary invasive breast cancer (IBC) in high-risk women. In 1998, the U.S. Food and Drug Administration (FDA) used these studies as a basis for approving tamoxifen for primary breast chemoprevention in both premenopausal and postmenopausal women at high risk. In 2007, the FDA approved raloxifene for primary breast cancer chemoprevention for postmenopausal women.
Data from the year 2010 National Health Interview Survey (NHIS) were analyzed to estimate the prevalence of tamoxifen and raloxifene use for chemoprevention of primary breast cancers among U.S. women.
Prevalence of use of chemopreventive agents for primary tumors was 20,598 (95% CI, 518–114,864) for U.S. women aged 35 to 79 for tamoxifen. Prevalence was 96,890 (95% CI, 41,277–192,391) for U.S. women aged 50 to79 for raloxifene.
Use of tamoxifen and raloxifene for prevention of primary breast cancers continues to be low. In 2010, women reporting medication use for breast cancer chemoprevention were primarily using the more recently FDA-approved drug raloxifene. Multiple possible explanations for the low use exist, including lack of awareness and/or concern about side effects among primary care physicians and patients.
Chemoprevention; tamoxifen; raloxifene; breast cancer; side effect
The Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is develop scientific priorities for cancer epidemiology research in the next decade. We would like to engage the research community and other stakeholders in a planning effort that will include a workshop, in December, 2012, to help shape new foci for cancer epidemiology research. To facilitate the process of defining the future of cancer epidemiology, we invite the research community to join in an ongoing Web-based conversation at http://blog-epi.grants.cancer.gov/ to develop priorities and the next generation of high-impact studies.
The clinical utility is uncertain for many cancer genomic applications. Comparative effectiveness research (CER) can provide evidence to clarify this uncertainty.
To identify approaches to help stakeholders make evidence-based decisions, and to describe potential challenges and opportunities using CER to produce evidence-based guidance.
We identified general CER approaches for genomic applications through literature review, the authors’ experiences, and lessons learned from a recent, seven-site CER initiative in cancer genomic medicine. Case studies illustrate the use of CER approaches.
Evidence generation and synthesis approaches include comparative observational and randomized trials, patient reported outcomes, decision modeling, and economic analysis. We identified significant challenges to conducting CER in cancer genomics: the rapid pace of innovation, the lack of regulation, the limited evidence for clinical utility, and the beliefs that genomic tests could have personal utility without having clinical utility. Opportunities to capitalize on CER methods in cancer genomics include improvements in the conduct of evidence synthesis, stakeholder engagement, increasing the number of comparative studies, and developing approaches to inform clinical guidelines and research prioritization.
CER offers a variety of methodological approaches to address stakeholders’ needs. Innovative approaches are needed to ensure an effective translation of genomic discoveries.
evidence synthesis; evidence generation; stakeholder; clinical utility
To test the effect of novel representations of randomness on risk perceptions, worry, and subjective uncertainty about individualized colorectal cancer risk estimates.
A Web-based factorial experiment was conducted, in which 225 adults aged 40 years and older were provided with hypothetical individualized colorectal cancer risk estimates, using 5 different textual and visual representations varying in expressed randomness. Outcome measures were perceived cancer risk, cancer worry, and subjective uncertainty about cancer risk; the moderating effect of dispositional optimism was also examined.
Representational format was significantly associated with subjective uncertainty about cancer risk, but not with perceived cancer risk or worry. A format using software-based animation to express randomness dynamically led to the highest subjective uncertainty, although a static visual non-random format also increased uncertainty. Dispositional optimism moderated this effect; between-format differences in uncertainty were significant only for participants with low optimism.
Representing randomness in individualized estimates of cancer risk increases subjective uncertainty about risk. A novel dynamic visual format produces the greatest effect, which is moderated by individual differences in optimism.
Novel representations of randomness may be effective in improving people’s understanding of the essential uncertainty pertaining to individualized cancer risk estimates.
risk communication; uncertainty; randomness; cancer
Advances in genomics and related fields are promising tools for risk assessment, early detection, and targeted therapies across the entire cancer care continuum. In this commentary, we submit that this promise cannot be fulfilled without an enhanced translational genomics research agenda firmly rooted in the population sciences. Population sciences include multiple disciplines that are needed throughout the translational research continuum. For example, epidemiologic studies are needed not only to accelerate genomic discoveries and new biological insights into cancer etiology and pathogenesis, but to characterize and critically evaluate these discoveries in well defined populations for their potential for cancer prediction, prevention and response to treatments. Behavioral, social and communication sciences are needed to explore genomic-modulated responses to old and new behavioral interventions, adherence to therapies, decision-making across the continuum, and effective use in health care. Implementation science, health services, outcomes research, comparative effectiveness research and regulatory science are needed for moving validated genomic applications into practice and for measuring their effectiveness, cost effectiveness and unintended consequences. Knowledge synthesis, evidence reviews and economic modeling of the effects of promising genomic applications will facilitate policy decisions, and evidence-based recommendations. Several independent and multidisciplinary panels have recently made specific recommendations for enhanced research and policy infrastructure to inform clinical and population research for moving genomic innovations into the cancer care continuum. An enhanced translational genomics and population sciences agenda is urgently needed to fulfill the promise of genomics in reducing the burden of cancer.
cancer; genetics; genomics; medicine; population sciences; public health; translation
Clinical trials demonstrated that women treated for breast cancer with anthracycline or trastuzumab are at increased risk for heart failure and/or cardiomyopathy (HF/CM), but the generalizability of these findings is unknown. We estimated real-world adjuvant anthracycline and trastuzumab use and their associations with incident HF/CM.
We conducted a population-based, retrospective cohort study of 12 500 women diagnosed with incident, invasive breast cancer from January 1, 1999 through December 31, 2007, at eight integrated Cancer Research Network health systems. Using administrative procedure and pharmacy codes, we identified anthracycline, trastuzumab, and other chemotherapy use. We identified incident HF/CM following chemotherapy initiation and assessed risk of HF/CM with time-varying chemotherapy exposures vs no chemotherapy. Multivariable Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for age at diagnosis, stage, Cancer Research Network site, year of diagnosis, radiation therapy, and comorbidities.
Among 12 500 women (mean age = 60 years, range = 22–99 years), 29.6% received anthracycline alone, 0.9% received trastuzumab alone, 3.5% received anthracycline plus trastuzumab, 19.5% received other chemotherapy, and 46.5% received no chemotherapy. Anthracycline and trastuzumab recipients were younger, with fewer comorbidities than recipients of other chemotherapy or none. Compared with no chemotherapy, the risk of HF/CM was higher in patients treated with anthracycline alone (adjusted HR = 1.40, 95% CI = 1.11 to 1.76), although the increased risk was similar to other chemotherapy (adjusted HR = 1.49, 95% CI = 1.25 to 1.77); the risk was highly increased in patients treated with trastuzumab alone (adjusted HR = 4.12, 95% CI = 2.30 to 7.42) or anthracycline plus trastuzumab (adjusted HR = 7.19, 95% CI = 5.00 to 10.35).
Anthracycline and trastuzumab were primarily used in younger, healthier women and associated with increased HF/CM risk compared with no chemotherapy. This population-based observational study complements findings from clinical trials on cancer treatment safety.
The Study of Tamoxifen and Raloxifene (STAR) demonstrated that raloxifene was as effective as tamoxifen in reducing the risk of invasive breast cancer (IBC) in postmenopausal women and had lower risks of thromboembolic events, endometrial cancer, and cataracts but had a nonstatistically significant higher risk of noninvasive breast cancer. There is a need to summarize the risks and benefits of these agents.
Patients and Methods
Baseline incidence rates of IBC and other health outcomes, absent raloxifene and tamoxifen, were estimated from breast cancer chemoprevention trials; the Surveillance, Epidemiology and End Results Program; and the Women's Health Initiative. Effects of raloxifene and tamoxifen were estimated from STAR and the Breast Cancer Prevention Trial. We assigned weights to health outcomes to calculate the net benefit from raloxifene compared with placebo and tamoxifen compared with placebo.
Risks and benefits of treatment with raloxifene or tamoxifen depend on age, race, breast cancer risk, and history of hysterectomy. Over a 5-year period, postmenopausal women with an intact uterus had a better benefit/risk index for raloxifene than for tamoxifen. For postmenopausal women without a uterus, the benefit/risk ratio was similar. The benefits and risks of raloxifene and tamoxifen are described in tables that can help identify groups of women for whom the benefits outweigh the risks.
We developed a benefit/risk index to quantify benefits from chemoprevention with tamoxifen or raloxifene. This index can complement clinical evaluation in deciding whether to initiate chemoprevention and in comparing the benefits and risks of raloxifene versus tamoxifen.
The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice.The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality.Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction.A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines.These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
Guidelines from the American Cancer Society recommend annual breast MRI screening for women with a projected lifetime risk of ≥20% based on risk models that use family history. Since MRI screening is costly and has limited specificity, estimates of the numbers of U.S. women with breast cancer risk ≥20% would be useful.
We used data from the 2000 and 2005 National Health Interview Survey and the National Cancer Institute’s (NCI) Breast Cancer Risk Assessment Tool (i.e. Gail Model 2 with a revision for African Americans) to calculate estimates of U.S. women by age and race/ethnicity categories with a lifetime absolute breast cancer risk of ≥20%. Distributions of 5-year and lifetime absolute risk of breast cancer are compared across demographic groups.
We estimated that 1.09% (95% CI = 0.95% to 1.24%) of women aged 30–84 years have a lifetime absolute breast cancer risk of ≥20%, which translates to 880,063 U.S. women eligible for MRI screening. The 5-year risks are highest for White non-Hispanics and lowest for Hispanics. The lifetime risks decrease with age and are generally highest for White non-Hispanics, lower for African American non-Hispanic and lowest for Hispanics.
We provide national estimates of the number of U.S. women who would be eligible for MRI breast screening and distributions of 5-year and lifetime risks of breast cancer using the NCI Breast Cancer Risk Assessment Tool.
These estimates inform the potential resources and public health demand for MRI screening and chemo-preventive interventions that might be required for U.S. women.
Unrealistically optimistic or pessimistic risk perceptions may be associated with maladaptive health behaviors. This study characterized factors associated with unrealistic optimism (UO) and unrealistic pessimism (UP) about breast cancer. Data from the 2005 National Health Interview Survey were analyzed (N=14,426 women). After accounting for objective risk status, many (43.8%) women displayed UO, 12.3% displayed UP, 34.5% had accurate risk perceptions (their perceived risk matched their calculated risk), and 9.5% indicated “don’t know/no response.” Multivariate multinomial logistic regression indicated that UO was associated with higher education and never smoking. UP was associated with lower education, lower income, being non-Hispanic Black, having ≥3 comorbidities, current smoking, and being overweight. UO was more likely to emerge in younger and older than in middle-aged individuals. UO and UP are associated with different demographic, health, and behavioral characteristics. Population segments that are already vulnerable to negative health outcomes displayed more UP than less vulnerable populations.
Unrealistic optimism; unrealistic pessimism; breast cancer; health behavior
To examine the effects of communicating uncertainty regarding individualized colorectal cancer risk estimates, and to identify factors that influence these effects.
Two web-based experiments were conducted, in which adults aged 40 years and older were provided with hypothetical individualized colorectal cancer risk estimates differing in the extent and representation of expressed uncertainty. The uncertainty consisted of imprecision (otherwise known as “ambiguity”) of the risk estimates, and was communicated using different representations of confidence intervals. Experiment 1 (n=240) tested the effects of ambiguity (confidence interval vs. point estimate) and representational format (textual vs. visual) on cancer risk perceptions and worry. Potential effect modifiers including personality type (optimism), numeracy, and the information’s perceived credibility were examined, along with the influence of communicating uncertainty on responses to comparative risk information. Experiment 2 (n=135) tested enhanced representations of ambiguity that incorporated supplemental textual and visual depictions.
Communicating uncertainty led to heightened cancer-related worry in participants, exemplifying the phenomenon of “ambiguity aversion.” This effect was moderated by representational format and dispositional optimism; textual (vs. visual) format and low (vs. high) optimism were associated with greater ambiguity aversion. However, when enhanced representations were used to communicate uncertainty, textual and visual formats showed similar effects. Both the communication of uncertainty and use of the visual format diminished the influence of comparative risk information on risk perceptions.
The communication of uncertainty regarding cancer risk estimates has complex effects, which include heightening cancer-related worry—consistent with ambiguity aversion—and diminishing the influence of comparative risk information on risk perceptions. These responses are influenced by representational format and personality type, and the influence of format appears to be modifiable and content-dependent.
The rapid and continuing progress in gene discovery for complex diseases is fueling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by previous reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
The rapid and continuing progress in gene discovery for complex diseases is fuelling interest in the potential application of genetic risk models for clinical and public health practice. The number of studies assessing the predictive ability is steadily increasing, but they vary widely in completeness of reporting and apparent quality. Transparent reporting of the strengths and weaknesses of these studies is important to facilitate the accumulation of evidence on genetic risk prediction. A multidisciplinary workshop sponsored by the Human Genome Epidemiology Network developed a checklist of 25 items recommended for strengthening the reporting of Genetic RIsk Prediction Studies (GRIPS), building on the principles established by prior reporting guidelines. These recommendations aim to enhance the transparency, quality and completeness of study reporting, and thereby to improve the synthesis and application of information from multiple studies that might differ in design, conduct or analysis.
Genetic; Risk prediction; Methodology; Guidelines; Reporting
Tamoxifen can reduce the risk of developing invasive estrogen-receptor positive (ER+) breast cancer by 49%, but it is unknown how many women in the U.S. are taking tamoxifen for primary prevention of breast cancer.
Data from the years 2000 and 2005 National Health Interview Surveys (NHIS) were analyzed to estimate the prevalence of tamoxifen use among U.S. women for primary chemoprevention of breast cancer.
In 2000, approximately 0.2 percent of U.S. women aged 40 to 79 without a personal history of breast cancer took tamoxifen for chemoprevention (95% CI 0.13-0.31). In 2005, the prevalence was approximately 0.08% (95% CI 0.03-0.17).
The prevalence of tamoxifen use for primary prevention of breast cancer was very low in the years 2000 and 2005. Possible explanations for the low uptake are explored.
Chemoprevention; tamoxifen; side effect
Hereditary nonpolyposis colorectal cancer (HNPCC), also known as Lynch syndrome, is a common autosomal dominant syndrome characterized by early age at onset, neoplastic lesions, and microsatellite instability (MSI). Because cancers with MSI account for approximately 15% of all colorectal cancers and because of the need for a better understanding of the clinical and histologic manifestations of HNPCC, the National Cancer Institute hosted an international workshop on HNPCC in 1996, which led to the development of the Bethesda Guidelines for the identification of individuals with HNPCC who should be tested for MSI. To consider revision and improvement of the Bethesda Guidelines, another HNPCC workshop was held at the National Cancer Institute in Bethesda, MD, in 2002. In this commentary, we summarize the Workshop presentations on HNPCC and MSI testing; present the issues relating to the performance, sensitivity, and specificity of the Bethesda Guidelines; outline the revised Bethesda Guidelines for identifying individuals at risk for HNPCC; and recommend criteria for MSI testing.
To explore laypersons’ responses to the communication of uncertainty associated with individualized cancer risk estimates and to identify reasons for individual differences in these responses.
A qualitative study was conducted using focus groups. Participants were informed about a new colorectal cancer risk prediction model, and presented with hypothetical individualized risk estimates using presentation formats varying in expressed uncertainty (range v. point estimate). Semistructured interviews explored participants’ responses to this information.
Participants and Setting
Eight focus groups were conducted with 48 adults aged 50 to 74 residing in 2 major US metropolitan areas, Chicago, IL and Washington, DC. Purposive sampling was used to recruit participants with a high school or greater education, some familiarity with information technology, and no personal or immediate family history of cancer.
Participants identified several sources of uncertainty regarding cancer risk estimates, including missing data, limitations in accuracy and source credibility, and conflicting information. In comparing presentation formats, most participants reported greater worry and perceived risk with the range than with the point estimate, consistent with the phenomenon of “ambiguity aversion.” However, others reported the opposite effect or else indifference between formats. Reasons suggested by participants’ responses included individual differences in optimism and motivations to reduce feelings of vulnerability and personal lack of control. Perceptions of source credibility and risk mutability emerged as potential mediating factors.
Laypersons’ responses to the communication of uncertainty regarding cancer risk estimates differ, and include both heightened and diminished risk perceptions. These differences may be attributable to personality, cognitive, and motivational factors.
uncertainty; risk; ambiguity; cancer; risk prediction models