Preferences for genetic testing for colorectal cancer within a population-based screening program: a discrete choice experiment

Public Preferences for Genetic and Genomic Risk-Informed Chronic Disease Screening and Early Detection: A Systematic Review of Discrete Choice Experiments

PURPOSE

Genetic and genomic testing can provide valuable information on individuals' risk of chronic diseases, presenting an opportunity for risk-tailored disease screening to improve early detection and health outcomes. The acceptability, uptake and effectiveness of such programmes is dependent on public preferences for the programme features. This study aims to conduct a systematic review of discrete choice experiments assessing preferences for genetic/genomic risk-tailored chronic disease screening.

METHODS

PubMed, Embase, EconLit and Cochrane Library were searched in October 2023 for discrete choice experiment studies assessing preferences for genetic or genomic risk-tailored chronic disease screening. Eligible studies were double screened, extracted and synthesised through descriptive statistics and content analysis of themes. Bias was assessed using an existing quality checklist.

RESULTS

Twelve studies were included. Most studies focused on cancer screening (n = 10) and explored preferences for testing of rare, high-risk variants (n = 10), largely within a targeted population (e.g. subgroups with family history of disease). Two studies explored preferences for the use of polygenic risk scores (PRS) at a population level. Twenty-six programme attributes were identified, with most significantly impacting preferences. Survival, test accuracy and screening impact were most frequently reported as most important. Depending on the clinical context and programme attributes and levels, estimated uptake of hypothetical programmes varied from no participation to almost full participation (97%).

CONCLUSION

The uptake of potential programmes would strongly depend on specific programme features and the disease context. In particular, careful communication of potential survival benefits and likely genetic/genomic test accuracy might encourage uptake of genetic and genomic risk-tailored disease screening programmes. As the majority of the literature focused on high-risk variants and cancer screening, further research is required to understand preferences specific to PRS testing at a population level and targeted genomic testing for different disease contexts.

Preferences for Genetic Testing to Predict the Risk of Developing Hereditary Cancer: A Systematic Review of Discrete Choice Experiments

BACKGROUND

Understanding service user preferences is key to effective health care decision making and efficient resource allocation. It is of particular importance in the management of high-risk patients in whom predictive genetic testing can alter health outcomes.

PURPOSE

This review aims to identify the relative importance and willingness to pay for attributes of genetic testing in hereditary cancer syndromes.

DATA SOURCES

Searches were conducted in Medline, Embase, PsycINFO, HMIC, Web of Science, and EconLit using discrete choice experiment (DCE) terms combined with terms related to hereditary cancer syndromes, malignancy synonyms, and genetic testing.

STUDY SELECTION

Following independent screening by 3 reviewers, 7 studies fulfilled the inclusion criteria, being a DCE investigating patient or public preferences related to predictive genetic testing for hereditary cancer syndromes.

DATA EXTRACTION

Extracted data included study and respondent characteristics, DCE attributes and levels, methods of data analysis and interpretation, and key study findings.

DATA SYNTHESIS

Studies covered colorectal, breast, and ovarian cancer syndromes. Results were summarized in a narrative synthesis and the quality assessed using the Lancsar and Louviere framework.

LIMITATIONS

This review focuses only on DCE design and testing for hereditary cancer syndromes rather than other complex diseases. Challenges also arose from heterogeneity in attributes and levels.

CONCLUSIONS

Test effectiveness and detection rates were consistently important to respondents and thus should be prioritized by policy makers. Accuracy, cost, and wait time, while also important, showed variation between studies, although overall reduction in cost may improve uptake. Patients and the public would be willing to pay for improved detection and clinician over insurance provider involvement. Future studies should seek to contextualize findings by considering the impact of sociodemographic characteristics, health system coverage, and insurance policies on preferences.

HIGHLIGHTS

Test effectiveness and detection rates are consistently important to respondents in genetic testing for hereditary cancer syndromes.Reducing the cost of genetic testing for hereditary cancer syndromes may improve uptake.Individuals are most willing to pay for a test that improves detection rates, identifies multiple cancers, and for which results are shared with a doctor rather than with an insurance provider.

Developing and assessing a kin keeping scale with application to identifying central influencers in African American family networks

Promoting family communication about inherited disease risk is an arena in which family systems theory is highly relevant. One family systems' construct that can support promotion of family communication regarding inherited disease risk is the notion of "kin keeping." However, kin keeping and whether it might be capitalized on to encourage family communication about inherited risk has been understudied. The goal of this report was to propose a broadened conceptualization of kin keeping that distinguishes between a structural functional perspective (role conceptualization) and transitional behaviors (skill conceptualization), and to develop and evaluate a scale that would enable this assertion to be tested among a sample of African American community health workers. We developed a scale using four steps: item development using concept analysis and content validity, scale development among a national sample (n = 312), scale evaluation using exploratory factor analysis (n = 52), and scale reduction. We then posed suppositions of associations that would indicate whether the developed kin keeping measure was assessing a specific family role or set of behaviors. Our results included the development of the first quantitative measure of kin keeping (9- and 15-item scales). Model fit for 9-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.09, SMRM = 0.06) and model fit for 15-item scale (CFI = 0.97, AFGI = 0.89, RMSEA = 0.06, SMRM = 0.05). These findings allow us to move toward more rigorous research about the role of kin keeping on information sharing and health decision making. Results also suggest that, contrary to the historical structural functional conceptualization of kin keeping as a role, kin keeping might also be conceptualized as a behavior or set of modifiable behaviors. Ultimately, the kin keeping scale could be used to operationalize kin keeping in various theoretical models and frameworks, guide intervention development to encourage or train for kin keeping behaviors, and test assumptions of whether families vary in the density of kin keeping.

A mainstreaming oncogenomics model: improving the identification of Lynch syndrome

Introduction

"Mainstreaming" is a proposed strategy to integrate genomic testing into oncology. The aim of this paper is to develop a mainstreaming oncogenomics model by identifying health system interventions and implementation strategies for mainstreaming Lynch syndrome genomic testing.

Methods

A rigorous theoretical approach inclusive of conducting a systematic review and qualitative and quantitative studies was undertaken using the Consolidated Framework for Implementation Research. Theory-informed implementation data were mapped to the Genomic Medicine Integrative Research framework to generate potential strategies.

Results

The systematic review identified a lack of theory-guided health system interventions and evaluation for Lynch syndrome and other mainstreaming programs. The qualitative study phase included 22 participants from 12 health organizations. The quantitative Lynch syndrome survey included 198 responses: 26% and 66% from genetic and oncology health professionals, respectively. Studies identified the relative advantage and clinical utility of mainstreaming to improve genetic test access and to streamline care, and adaptation of current processes was recognized for results delivery and follow-up. Barriers identified included funding, infrastructure and resources, and the need for process and role delineation. The interventions to overcome barriers were as follows: embedded mainstream genetic counselors, electronic medical record genetic test ordering, results tracking, and mainstreaming education resources. Implementation evidence was connected through the Genomic Medicine Integrative Research framework resulting in a mainstreaming oncogenomics model.

Discussion

The proposed mainstreaming oncogenomics model acts as a complex intervention. It features an adaptable suite of implementation strategies to inform Lynch syndrome and other hereditary cancer service delivery. Implementation and evaluation of the model are required in future research.

Rural job preferences of graduate class medical students in Ethiopia-a discrete choice experiment (DCE)

BACKGROUND

Human resource is one of the health system's building blocks, which ultimately leads to improved health status, equity, and efficiency. However, human resources in the health sector are characterized by high attrition, distributional imbalance, and geographic inequalities in urban and rural settings.

METHODS

An discrete choice experiment (DCE) with 16 choice tasks with two blocks containing five attributes (salary, housing, drug and medical equipment, year of experience before study leave, management support, and workload) were conducted. A latent class and mixed logit model were fitted to estimate the rural job preferences and heterogeneity. Furthermore, the relative importance, willingness to accept and marginal choice probabilities were calculated. Finally, the interaction of preference with age and sex was tested.

RESULTS

A total of 352 (5632 observations) final-year medical students completed the choice tasks. On average, respondents prefer to work with a higher salary with a superior housing allowance In addition, respondents prefer a health facility with a stock of drug and medical equipment which provide education opportunities after one year of service with supportive management with a normal workload. Young medical students prefer lower service years more than older students. Besides age and service year, we do not find an interaction between age/sex and rural job preference attributes. A three-class latent class model best fits the data. The salary was the most important attribute in classes 1 and 3. Contrary to the other classes, respondents in class 2 do not have a significant preference for salary. Respondents were willing to accept an additional 4271 ETB (104.2 USD), 1998 ETB (48.7 USD), 1896 ETB (46.2 USD), 1869 (45.6 USD), and 1175 ETB (28.7 USD) per month for the inadequate drug and medical supply, mandatory two years of service, heavy workload, unsupportive management, and basic housing, respectively.

CONCLUSION

Rural job uptake by medical students was influenced by all the attributes, and there was individual and group-level heterogeneity in preference. Policymakers should account for the job preferences and heterogeneity to incentivize medical graduates to work in rural settings and minimize attrition.

Can healthcare choice be predicted using stated preference data? The role of model complexity in a discrete choice experiment about colorectal cancer screening

INTRODUCTION

The validity of discrete choice experiments (DCEs) is crucial to its usage in healthcare decision-making, but there is only a limited number of health contexts in which external validity is demonstrated. This study aims to assess the internal and external validity of the DCE in the context of colorectal cancer (CRC) screening, and gather insights into the discrepancy between stated and revealed preferences.

METHODS

Stated and revealed preferences were elicited on an individual level from Dutch residents eligible for CRC screening in a DCE and a field experiment, respectively (N = 568). To identify the determinants of CRC screening participation and their relative importance, five random utility maximisation models that varied in complexity were used. We assessed the accuracy with which the models based on stated preferences predict individual-level screening choice in a holdout task (internal validity) and in the actual screening choice (external validity). Insights into the discrepancy between stated and revealed preferences were gathered by comparing groups of respondents.

RESULTS

Our findings show high internal and external validity. Choices could be accurately predicted for 95% of the respondents in the holdout task, and 90% in the actual screening choice. When scale and preference heterogeneity were taken into account model fit improved; individual-level prediction accuracy slightly increased for the holdout task but not for the actual screening choice. Respondents for whom stated preferences matched revealed preferences were generally in better health and found the GP's support for their screening decision more important.

DISCUSSION

Evidence was found that revealed preferences can be predicted accurately on an individual level. Incorporating heterogeneity improved internal validity but not external validity. Differences between stated and revealed preferences can be attributed to respondents' health and the support of their GP. We suggest researchers to continue investigating the internal and external validity of discrete choice experiments, and the role of model complexity.

The Role of Attribute Screening and Choice Set Formation in Health Discrete Choice Experiments: Modeling the Impact of Benefit and Risk Attributes

OBJECTIVES

This study aimed to demonstrate the econometric modeling of benefit/risk-based choice set formation (CSF) within health-related discrete choice experiments.

METHODS

In 4 different case studies, first, a trade-off model was fitted; building on this, a screening model was fitted; and finally, a full CSF model was estimated. This final model allows for attributes to be used first to screen out alternatives from choice tasks before respondents' trade-off attributes and make a choice among feasible alternatives. Educational level and health literacy of respondents were accounted for in all models.

RESULTS

Model fit in terms of log likelihood, pseudo-R², Akaike information criterion, and Bayesian information criterion improved from using only trade-off or screening models compared with CSF models in 3 of the 4 case studies. In those studies, significant screening behavior was identified that (1) affected trade-off inferences, (2) rejects the pure trade-off model, and (3) supports the existence of screening on the basis of benefit-risk profiles, and other attributes. Educational level and health literacy showed significant interactions with multiple attributes in all case studies.

CONCLUSIONS

Choice modelers should pay close attention to noncompensatory respondent behavior when they include benefit or risk attributes in their discrete choice experiment. Further studies should investigate why and when respondents undertake screening behavior. Screening behavior in choice data analysis is always a possibility, so researchers should explore extensions of econometric models to reflect noncompensatory behavior. Assuming that benefit and risk attributes will only affect trade-off behavior is likely to lead to biased conclusions about benefit or risk-based behavior.

A Systematic Review of Discrete Choice Experiments and Conjoint Analysis on Genetic Testing

BACKGROUND

Although genetic testing has the potential to offer promising medical benefits, concerns regarding its potential negative impacts may influence its acceptance. Users and providers need to weigh the benefits, costs and potential harms before deciding whether to take up or recommend genetic testing. Attribute-based stated-preference methods, such as discrete choice experiment (DCE) or conjoint analysis, can help to quantify how individuals value different features of genetic testing.

OBJECTIVES

The aim of this paper was to conduct a systematic review of DCE and conjoint analysis studies on genetic testing, including genomic tests.

METHODS

A systematic search was conducted in seven databases: Web of Science, CINAHL Plus with Full Text (EBSCO), PsycINFO, PubMed, Embase, The Cochrane Library and SCOPUS. The search was conducted in February 2021 and was limited to English peer-reviewed articles published until the search date. The search keywords included relevant keywords such as 'genetic testing', 'genomic testing', 'pharmacogenetic testing', 'discrete choice experiment' and 'conjoint analysis'. Narrative synthesis of the studies was conducted on survey population, testing type, recruitment and data collection, survey development, questionnaire content, survey validity, analysis, outcomes and other design features.

RESULTS

Of the 292 articles retrieved, 38 full-text articles were included in this review. Nearly two-thirds of the studies were published since 2015 and all were conducted in high-income countries. Survey samples included patients, parents, general population and healthcare providers. The articles assessed preferences for pharmacogenetic testing (28.9%), predictive testing and diagnostic testing (18.4%), while only one (2.6%) study investigated preferences for carrier testing. The most common sampling method was convenience sampling (57.9%) and the majority recruited participants via web-enabled surveys (60.5%). Review of literature (84.6%), discussions with healthcare professionals (71.8%) and cognitive interviews (53.8%) were commonly used for attribute identification. A survey validity test was included in only one-quarter of the studies (28.2%). Cost attributes were the most studied attribute type (76.9%), followed by risk attributes (61.5%). Among those that reported relative attribute importance, attributes related to benefits were the most commonly reported attributes with the highest relative attribute importance. Preference heterogeneity was investigated in most studies by modelling, such as via mixed logit analysis (82.1%) and/or by using interaction effects with respondent characteristics (74.4%). Willingness to pay was the most commonly estimated outcome and was presented in about two-thirds (n = 25; 64.1%) of the studies.

CONCLUSION

With the continuous advancement in genetic technology resulting in expanding options for genetic testing and improvements in delivery methods, the application of genetic testing in clinical care is expected to rise. DCEs and conjoint analysis remain robust and useful methods to elicit preferences of potential stakeholders. This review serves as a summary for future researchers when designing similar studies.

Health system interventions to integrate genetic testing in routine oncology services: A systematic review

BACKGROUND

Integration of genetic testing into routine oncology care could improve access to testing. This systematic review investigated interventions and the tailored implementation strategies aimed at increasing access to genetic counselling and testing and identifying hereditary cancer in oncology.

METHODS

The search strategy results were reported using the PRISMA statement and four electronic databases were searched. Eligible studies included routine genetic testing for breast and ovarian cancer or uptake after universal tumour screening for colorectal or endometrial cancer. The titles and abstracts were reviewed and the full text articles screened for eligibility. Data extraction was preformed using a designed template and study appraisal was assessed using an adapted Newcastle Ottawa Scale. Extracted data were mapped to Proctor's et al outcomes and the Consolidated Framework for Implementation Research and qualitatively synthesised.

RESULTS

Twenty-seven studies, published up to May 2020, met the inclusion criteria. Twenty-five studies ranged from poor (72%), fair to good (28%) quality. Most interventions identified were complex (multiple components) such as; patient or health professional education, interdisciplinary practice and a documentation or system change. Forty-eight percent of studies with complex interventions demonstrated on average a 35% increase in access to genetic counselling and a 15% increase in testing completion. Mapping of study outcomes showed that 70% and 32% of the studies aligned with either the service and client or the implementation level outcome and 96% to the process or inner setting domains of the Consolidated Framework for Implementation Research.

CONCLUSION

Existing evidence suggests that complex interventions have a potentially positive effect towards genetic counselling and testing completion rates in oncology services. Studies of sound methodological quality that explore a greater breadth of pre and post implementation outcomes and informed by theory are needed. Such research could inform future service delivery models for the integration of genetics into oncology services.

Genomic Testing for Relapsed and Refractory Lymphoid Cancers: Understanding Patient Values

BACKGROUND

New clinical genomic assays for lymphoid cancers allow for improved disease stratification and prognostication. At present, clinical implementation has been appropriately limited, owing to a paucity of evidence to support clinical and cost effectiveness. Understanding patients' values for precision oncology under conditions of uncertainty can be used to inform priority-setting decisions.

OBJECTIVES

Our objective was to ascertain patients' qualitative preferences and attitudes for prognostic-based genomic testing.

METHODS

Individuals who were diagnosed with lymphoid cancer between 2000 and 2018 in British Columbia, Canada, were recruited to participate in one of three focus groups. A maximum variation sampling technique was used to capture a diversity of perspectives. A patient partner was involved in the development of the focus group topic guide and presentation materials. All sessions were audio recorded and analyzed using NVivo qualitative analysis software, version 12.

RESULTS

In total, 26 participants took part in focus groups held between November 2018 and February 2019. Results illustrate qualitative preference heterogeneity for situations under which individuals would be willing to undergo genomic testing for relapsed lymphoid cancers. Preferences were highly contextualized within personal experiences with disease and treatment protocols. Hypothetical willingness to pay for testing was contingent on invasiveness, the potential for treatment de-escalation, and personal health benefit.

CONCLUSIONS

Patients are supportive and accepting of evidentiary uncertainty up until the point at which they are required to trade-off the potential for improved quality and length of life. Demand for precision medicine is contingent on expectations for benefit alongside an acknowledgment of the opportunity cost required for implementation. The clinical implementation of precision medicine will be required to address evidentiary uncertainty surrounding personal benefit while ensuring equitable access to emerging innovations.

Mimicking Real-Life Decision Making in Health: Allowing Respondents Time to Think in a Discrete Choice Experiment

OBJECTIVE

To empirically test the impact of allowing respondents time to think (TTT) about their choice options on the outcomes of a discrete choice experiments (DCE).

METHODS

In total, 613 participants of the Swedish CArdioPulmonary bioImage Study (SCAPIS) completed a DCE questionnaire that measured their preferences for receiving secondary findings of a genetic test. A Bayesian D-efficient design with 60 choice tasks divided over 4 questionnaires was used. Each choice task contained 2 scenarios with 4 attributes: type of disease, disease penetrance probability, preventive opportunities, and effectiveness of prevention. Respondents were randomly allocated to the TTT or no TTT (NTTT) sample. Latent class models (LCMs) were estimated to determine attribute-level values and their relative importance. In addition, choice certainty, attribute-level interpretation, choice consistency, and potential uptake rates were compared between samples.

RESULTS

In the TTT sample, 92% of the respondents (245 of 267) indicated they used the TTT period to (1) read the information they received (72%) and (2) discuss with their family (24%). In both samples, respondents were very certain about their choices. A 3-class LCM was fitted for both samples. Preference reversals were found for 3 of the 4 attributes in one class in the NTTT sample (34% class-membership probability). Relative importance scores of the attributes differed between the 2 samples, and significant scale effects indicating higher choice consistency in TTT sample were found.

CONCLUSIONS

Offering respondents TTT influences decision making and preferences. Developers of future DCEs regarding complex health-related decisions are advised to consider this approach to enhance the validity of the elicited preferences.

Tailoring chemotherapy supply according to patients' preferences: a quantitative method in colorectal cancer care

Objectives: The aim of this study was to conduct a discrete choice experiment with patients affected by colorectal cancer to understand their preferences for different attributes of the chemotherapy supply. Our overall goal is to provide evidence on the relative importance of each attribute in order to tailor chemotherapy supply according to patients' priorities in the design or reorganization processes of cancer services.Methods: Focus groups were used to identify the attributes and levels for the discrete choice experiment. The attributes were: continuity of care, understanding, information, treatment choice, and time for therapy. Respondents were asked to choose between two mutually exclusive hypothetical alternatives of chemotherapy supply. Patients completed the discrete choice experiment along with the health-related quality of life and patients' satisfaction questions. Conditional and mixed logistic models were used to analyses the data.Results: Patients with colorectal cancer treated with chemotherapy (n = 76) completed the survey. The most important aspects of chemotherapy supply were: "Providing detailed and complete information" and "High ability in understanding" patients. Preferences were also influenced by the availability of a trusted doctor. Except for one attribute (waiting time for therapy), all other characteristics significantly influenced respondents' preferences.Conclusions: Results should support a policy of strengthening medical doctors' capabilities to communicate with patients, providing them complete information and involving them in the clinical decisions. Specifically, the findings should be used to improve the current provision of cancer care by identifying areas of preferred intervention from the perspectives of patients in order to tailor the service supply accordingly.

Discrete Choice Experiments in Health Economics: Past, Present and Future

OBJECTIVES

Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990-2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges.

METHODS

A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated.

RESULTS

Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels.

CONCLUSIONS

The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers' confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research.

How psychological distance of a study sample in discrete choice experiments affects preference measurement: a colorectal cancer screening case study

PURPOSE

The purpose of this study was to investigate to what extent the outcomes of a discrete choice experiment (DCE) differ based on respondents' psychological distance to the decision at hand.

METHODS

A DCE questionnaire regarding individuals' preferences for genetic screening for colorectal cancer (CRC) within the Dutch national CRC screening program was created. The DCE contained nine D-efficient designed choice tasks and was distributed among two populations that differ in their psychological distance to the decision at hand: 1) a representative sample of the Dutch general population aged 55-65 years, and 2) a sample of Dutch individuals who attended an information appointment regarding colonoscopies following the detection of blood in their stool sample in the CRC screening program. The DCE consisted of four attributes related to the decision whether to participate in genetic screening for CRC: 1) risk of being genetically predisposed, 2) risk of developing CRC, 3) frequency of follow-up colonoscopies, and 4) survival. Direct attribute ranking, dominant decision-making behavior, and relative importance scores (based on panel MIXL) were compared between the two populations. Attribute level estimates were compared with the Swait and Louviere test.

RESULTS

The proportion of respondents who both ranked survival as the most important attribute, and showed dominant decision-making behavior for this attribute, was significantly higher in the screened population compared to the general population. The relative importance scores of the attributes significantly differed between populations. Finally, the Swait and Louviere test also revealed significant differences in attribute level estimates in both the populations.

CONCLUSION

The study outcomes differed between populations depending on their psychological distance to the decision. This study shows the importance of adequate sample selection; therefore, it is advocated to increase attention to study sample selection and reporting in DCE studies.

Testing strategies to reduce morbidity and mortality from Lynch syndrome

OBJECTIVE

Lynch syndrome (LS) has an autosomal dominant inheritance pattern and is associated with increased risk for colorectal cancer (CRC) and other cancers. Various strategies are used to identify patients at risk and offer surveillance and preventive programs, the cost effectiveness of which is much dependent on the prevalence of LS in a population. Universal testing (UT) is proposed as an effective measure, targeting all newly diagnosed CRC patients under a certain age.

MATERIALS AND METHODS

LS cases were identified in a cohort of 572 consecutive CRC patients. Immunohistochemistry was performed in 539 cases, using antibodies against mismatch repair proteins MLH1, PMS2, MSH2, and MSH6. Microsatellite instability and gene mutation screening were performed in 57 cases.

RESULTS

In total 11 pathogenic variants were detected, identifying LS in 1.9% of new CRC cases. Comparing the results with current clinical methods, 2 pathogenic variants were found with Amsterdam criteria and 9 when using either Bethesda guidelines or our institution's prior clinical criteria. Pathogenic variants in MSH6 were the most common in our series. We also found different outcomes using different age cut offs.

CONCLUSION

Our study demonstrates that UT of tumors before age on onset at 75 years would most likely be cost-efficient and essentially equivalent to applying the Bethesda guidelines or our institution's prior clinical criteria on all new CRC.

Patient preferences for massively parallel sequencing genetic testing of colorectal cancer risk: a discrete choice experiment

This study enumerated patients' preference-based personal utility and willingness-to-pay for massively parallel sequencing (MPS) genetic testing of colorectal cancer (CRC) risk. Our setting was the New Exome Technology in (NEXT) Medicine Study, a randomized control trial of usual care genetic testing vs. exome sequencing. Using a discrete choice experiment (DCE), we elicited patient preferences for information on genetic causes of CRC. We estimated personal utility for the following four attributes: proportion of individuals with a genetic cause of CRC who receive a diagnosis, number of tests used, wait time for results, and cost. A total of 122 patients completed our DCE (66% response rate). On average, patients preferred genetic tests identifying more individuals with a diagnosis and involving a shorter wait time. Assuming MPS identifies more individuals with a Mendelian form of CRC risk, involves fewer tests, and results in a shorter wait than traditional diagnostic testing, average willingness-to-pay (WTP) for MPS ranged from US$400 (95% CI: $300, $500) to US$1541 (95% CI: $1224, $1859). These results indicate that patients value information on genetic causes of CRC and replacing traditional diagnostic testing with MPS testing will increase patients' utility. Future research exploring the costs and benefits of MPS for CRC risk is warranted.

Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review

BACKGROUND

Latent class analysis (LCA) has been increasingly used to explore preference heterogeneity, but the literature has not been systematically explored and hence best practices are not understood.

OBJECTIVE

We sought to document all applications of LCA in the stated-preference literature in health and to inform future studies by identifying current norms in published applications.

METHODS

We conducted a systematic review of the MEDLINE, EMBASE, EconLit, Web of Science, and PsycINFO databases. We included stated-preference studies that used LCA to explore preference heterogeneity in healthcare or public health. Two co-authors independently evaluated titles, abstracts, and full-text articles. Abstracted key outcomes included segmentation methods, preference elicitation methods, number of attributes and levels, sample size, model selection criteria, number of classes reported, and hypotheses tests. Study data quality and validity were assessed with the Purpose, Respondents, Explanation, Findings, and Significance (PREFS) quality checklist.

RESULTS

We identified 2560 titles, 99 of which met the inclusion criteria for the review. Two-thirds of the studies focused on the preferences of patients and the general population. In total, 80% of the studies used discrete choice experiments. Studies used between three and 20 attributes, most commonly four to six. Sample size in LCAs ranged from 47 to 2068, with one-third between 100 and 300. Over 90% of the studies used latent class logit models for segmentation. Bayesian information criterion (BIC), Akaike information criterion (AIC), and log-likelihood (LL) were commonly used for model selection, and class size and interpretability were also considered in some studies. About 80% of studies reported two to three classes. The number of classes reported was not correlated with any study characteristics or study population characteristics (p > 0.05). Only 30% of the studies reported using statistical tests to detect significant variations in preferences between classes. Less than half of the studies reported that individual characteristics were included in the segmentation models, and 30% reported that post-estimation analyses were conducted to examine class characteristics. While a higher percentage of studies discussed clinical implications of the segmentation results, an increasing number of studies proposed policy recommendations based on segmentation results since 2010.

CONCLUSIONS

LCA is increasingly used to study preference heterogeneity in health and support decision-making. However, there is little consensus on best practices as its application in health is relatively new. With an increasing demand to study preference heterogeneity, guidance is needed to improve the quality of applications of segmentation methods in health to support policy development and clinical practice.

Women's preferences, willingness-to-pay, and predicted uptake for single-nucleotide polymorphism gene testing to guide personalized breast cancer screening strategies: a discrete choice experiment

BACKGROUND

Single-nucleotide polymorphism (SNP) gene test is a potential tool for improving the accuracy of breast cancer risk prediction. We seek to measure women's preferences and marginal willingness-to-pay (mWTP) for this new technology.

MATERIALS AND METHODS

We administered a discrete choice experiment (DCE) to English-speaking Singaporean women aged 40-69 years without any history of breast cancer, enrolled via door-to-door recruitment with quota sampling by age and ethnicity. DCE attributes comprise: 1) sample type (buccal swab and dried blood spot), 2) person conducting pretest discussion (specialist doctor, non-specialist doctor, and nurse educator), 3) test location (private family clinic, public primary-care clinic, and hospital), and 4) out-of-pocket cost (S$50, S$175, and S$300). Mixed logit model was used to estimate the effect of attribute levels on women's preferences and mWTP. Interactions between significant attributes and respondent characteristics were investigated. Predicted uptake rates for various gene testing scenarios were studied.

RESULTS

A total of 300 women aged 52.6±7.6 years completed the survey (100 Chinese, Malay, and Indian women, respectively). Sample type (P=0.046), person conducting pretest discussion, and out-of-pocket cost (P<0.001) are significantly associated with going for SNP gene testing. Women with higher income and education levels are more willing to pay higher prices for the test. Preferences in terms of mWTP across ethnic groups appear similar, but Chinese women have greater preference heterogeneity for the attributes. Predicted uptake for a feasible scenario consisting of buccal swab, pretest discussion with nurse educator at the hospital costing S$50 is 60.5%. Only 3.3% of women always opted out of the SNP gene test in real life. Reasons include high cost, poor awareness, and indifference toward test results.

CONCLUSION

SNP gene testing may be tailored according to individual preferences to encourage uptake. Future research should focus on outcomes and cost-effectiveness of personalized breast cancer screening using SNP gene testing.

Comparison of the efficiency of colorectal cancer screening programs based on age and genetic risk for reduction of colorectal cancer mortality

Given that colorectal cancer risk depends partly on inherited factors, screening program efficiency may be increased by incorporating genetic factors. We compared the efficiency of screening based on age and genetic risk in a simulated population. We simulated a population matching the size, age distribution and colorectal cancer incidence and mortality of Australia. We also simulated the distribution of genetic risk for colorectal cancer based on the expected number of inherited risk alleles of 45 single-nucleotide polymorphisms (SNPs) previously reported as associated with colorectal cancer. We compared the expected colorectal cancer deaths under three screening programs; age-based, genetic-based and combined age-based and genetic-based. The age-based program would prevent 25.4 deaths per 100 000 invited to screen, none of which would be under age 50; the genetic program would prevent 26.2 deaths per 100 000 invited to screen, 16 of which would be under age 50; and the combined program would prevent 24.4 deaths per 100 000 invited to screen, 16 of which would be under age 50. Genetic testing of 1.5 million 45-49 year olds would identify 91% of the people aged under 50 at sufficient risk to warrant screening, potentially saving 16 colorectal cancer deaths each year. Screening eligibility based on genetic risk profile for age is as efficient as eligibility based on age alone for preventing colorectal cancer mortality, but identifies an additional 7% of the population at sufficient risk to benefit from screening who would not normally be screened given they are aged under 50 years.

Attitudes to incorporating genomic risk assessments into population screening programs: the importance of purpose, context and deliberation

Background

The use of an overall risk assessment based on genomic information is consistent with precision medicine. Despite the enthusiasm, there is a need for public engagement on the appropriate use of such emerging technologies in order to frame meaningful evaluations of utility, including the practical implementation and acceptability issues that might emerge. Doing so requires the involvement of the end users of these services, including patients, and sections of the public who are the target group for population based screening. In the present study we sought to explore public attitudes to the potential integration of personal genomic profiling within existing population screening programs; and to explore the evolution of these attitudes as part of a deliberative process.

Methods

We conducted a mixed methods study presented in the format of a deliberative workshop. Participants were drawn from communities in Ottawa, Ontario (ON) and St John’s, Newfoundland and Labrador (NL), Canada. Individuals were approached to take part in a workshop on the incorporation of genomic risk profiling for either colorectal cancer screening (CRC), or newborn screening for type 1 diabetes mellitus (T1DM).

Results

A total of N = 148 (N = 65 ON, N = 83 NL) participants provided data for analysis. Participants in both groups were supportive of public funding for genomic risk profiling, although participants in the T1DM groups expressed more guarded positive attitudes than participants in the CRC groups. These views were stable throughout the workshop (CRC, p = 0.15, T1DM, p =0.39). Participants were less positive about individual testing, with a significant decrease in support over the course of the workshop (CRC p = 0.02, T1DM, p = 0.003). Common concerns related to access to test results by third parties.

Conclusions

The findings of this study suggest that members of the target populations for potential genomic profiling tests (designed for screening or risk prediction purposes) can engage in meaningful deliberation about their general acceptability and personal utility. Evaluations of whether a test would be personally useful may depend on the experience of the participants in personal health decision making, the purpose of the test, and the availability of interventions to reduce disease risk.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-016-0186-5) contains supplementary material, which is available to authorized users.