Public stated preferences and predicted uptake for genome-based colorectal cancer screening

Abstract

BackgroundEmerging developments in nanomedicine allow the development of genome-based technologies for non-invasive and individualised screening for diseases such as colorectal cancer. The main objective of this study was to measure user preferences for colorectal cancer screening using a nanopill.MethodsA discrete choice experiment was used to estimate the preferences for five competing diagnostic techniques including the nanopill and iFOBT. Alternative screening scenarios were described using five attributes namely: preparation involved, sensitivity, specificity, complication rate and testing frequency. Fourteen random and two fixed choice tasks, each consisting of three alternatives, were offered to 2225 individuals. Data were analysed using the McFadden conditional logit model.ResultsThirteen hundred and fifty-six respondents completed the questionnaire. The most important attributes (and preferred levels) were the screening technique (nanopill), sensitivity (100%) and preparation (no preparation). Stated screening uptake for the nanopill was 79%, compared to 76% for iFOBT. In the case of screening with the nanopill, the percentage of people preferring not to be screened would be reduced from 19.2% (iFOBT) to 16.7%.ConclusionsAlthough the expected benefits of nanotechnology based colorectal cancer screening are improved screening uptake, assuming more accurate test results and less preparation involved, the relative preference of the nanopill is only slightly higher than the iFOBT. Estimating user preferences during the development of diagnostic technologies could be used to identify relative performance, including perceived benefits and harms compared to competitors allowing for significant changes to be made throughout the process of development.

Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force

“…Since the middle of the 1990s, there has been a rapid increase in the use of conjoint analysis to measure the preferences of patients and other stakeholders in health applications [3][4][5][6][7][8]. Although early applications were used to quantify process utility [9,10], more recent applications have focused on patient preferences for health status [11,12], screening [13], prevention [14,15], pharmaceutical treatment [16,17], therapeutic devices [18,19], diagnostic testing [20,21], and end-of-life care [22,23]. In addition, conjoint analysis methods have been used to study decision making among stakeholders other than patients, including clinicians [24][25][26], caregivers [25,27], and the general public [28,29].…”

Valuation of Health and Nonhealth Outcomes from Next-Generation Sequencing: Approaches, Challenges, and Solutions

“…Preference-based research has established the importance of accuracy and clinical utility of diagnostic information [15,16]. In the context of NGS, it has been noted that the evidence needed to support estimates of accuracy and clinical utility requires significant amounts of data.…”

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

“…This is the first DCE that studied the preferences of the general population for genetic testing for CRC within a screening situation. However, previous studies did measure preferences for populationbased CRC screening program characteristics (without genetic screening) [33][34][35][36] or preferences for genetic screening test characteristics in general (not specifically applied to CRC). 24 Although these studies focused on different topics and different target populations, their results do provide face validity for the results of the current study.…”