Men's preferences for prostate cancer screening: a discrete choice experiment.

BACKGROUND: Screening for prostate cancer (PC) may save lives, but overdiagnosis and overtreatment are serious drawbacks. We aimed to determine men's preferences for PC screening, and to elicit the trade-offs they make. METHODS: A discrete choice experiment (DCE) was conducted among a population-based random sample of 1000 elderly men (55-75-years-old). Trade-offs were quantified with a panel latent class model between five PC screening aspects: risk reduction of PC-related death, screening interval, risk of unnecessary biopsies, risk of unnecessary treatments, and out-of-pocket costs. RESULTS: The response rate was 46% (459/1000). Men were willing to trade-off 2.0% (CI: 1.6%-2.4%) or 1.8% (CI: 1.3%-2.3%) risk reduction of PC-related death to decrease their risk of unnecessary treatment or biopsy with 10%, respectively. They were willing to pay €188 per year (CI: €141-€258) to reduce their relative risk of PC-related death with 10%. Preference heterogeneity was substantial, with men with higher educational levels having a lower probability to opt for PC screening than men with lower educational levels. CONCLUSION: Men were willing to trade-off some risk reduction of PC-related death to be relieved of the burden of biopsies or unnecessary treatments. Increasing knowledge on overdiagnosis and overtreatment, especially for men with lower educational levels, is warranted to prevent unrealistic expectations from PC screening.

Patients' and urologists' preferences for prostate cancer treatment: a discrete choice experiment.

BACKGROUND: Patients' preferences are important for shared decision making. Therefore, we investigated patients' and urologists' preferences for treatment alternatives for early prostate cancer (PC). METHODS: A discrete choice experiment was conducted among 150 patients who were waiting for their biopsy results, and 150 urologists. Regression analysis was used to determine patients' and urologists' stated preferences using scenarios based on PC treatment modality (radiotherapy, surgery, and active surveillance (AS)), and risks of urinary incontinence and erectile dysfunction. RESULTS: The response rate was 110 out of 150 (73%) for patients and 50 out of 150 (33%) for urologists. Risk of urinary incontinence was an important determinant of both patients' and urologists' stated preferences for PC treatment (P<0.05). Treatment modality also influenced patients' stated preferences (P<0.05), whereas the risk of erectile dysfunction due to radiotherapy was mainly important to urologists (P<0.05). Both patients and urologists preferred AS to radical treatment, with the exception of patients with anxious/depressed feelings who preferred radical treatment to AS. CONCLUSION: Although patients and urologists generally may prefer similar treatments for PC, they showed different trade-offs between various specific treatment aspects. This implies that urologists need to be aware of potential differences compared with the patient's perspective on treatment decisions in shared decision making on PC treatment.

Preferences for colorectal cancer screening strategies: a discrete choice experiment.

BACKGROUND: Guidelines underline the role of individual preferences in the selection of a screening test, as insufficient evidence is available to recommend one screening test over another. We conducted a study to determine the preferences of individuals and to predict uptake for colorectal cancer (CRC) screening programmes using various screening tests. METHODS: A discrete choice experiment (DCE) questionnaire was distributed among naive subjects, yet to be screened, and previously screened subjects, aged 50-75 years. Subjects were asked to choose between scenarios on the basis of faecal occult blood test (FOBT), flexible sigmoidoscopy (FS), total colonoscopy (TC) with various test-specific screening intervals and mortality reductions, and no screening (opt-out). RESULTS: In total, 489 out of 1498 (33%) screening-naïve subjects (52% male; mean age+/-s.d. 61+/-7 years) and 545 out of 769 (71%) previously screened subjects (52% male; mean age+/-s.d. 61+/-6 years) returned the questionnaire. The type of screening test, screening interval, and risk reduction of CRC-related mortality influenced subjects' preferences (all P<0.05). Screening-naive and previously screened subjects equally preferred 5-yearly FS and 10-yearly TC (P=0.24; P=0.11), but favoured both strategies to annual FOBT screening (all P-values <0.001) if, based on the literature, realistic risk reduction of CRC-related mortality was applied. Screening-naive and previously screened subjects were willing to undergo a 10-yearly TC instead of a 5-yearly FS to obtain an additional risk reduction of CRC-related mortality of 45% (P<0.001). CONCLUSION: These data provide insight into the extent by which interval and risk reduction of CRC-related mortality affect preferences for CRC screening tests. Assuming realistic test characteristics, subjects in the target population preferred endoscopic screening over FOBT screening, partly, due to the more favourable risk reduction of CRC-related mortality by endoscopy screening. Increasing the knowledge of potential screenees regarding risk reduction by different screening strategies is, therefore, warranted to prevent unrealistic expectations and to optimise informed choice.

Can healthcare choice be predicted using stated preference data?

Lack of evidence about the external validity of Discrete Choice Experiments (DCEs)-sourced preferences inhibits greater use of DCEs in healthcare decision-making. This study examines the external validity of such preferences, unravels its determinants, and provides evidence of whether healthcare choice is predictable. We focused on influenza vaccination and used a six-step approach: i) literature study, ii) expert interviews, iii) focus groups, iv) survey including a DCE, v) field data, and vi) in-depth interviews with respondents who showed discordance between stated choices and actual healthcare utilization. Respondents without missing values in the survey and the actual healthcare utilization (377/499 = 76%) were included in the analyses. Random-utility-maximization and random-regret-minimization models were used to analyze the DCE data, whereas the in-depth interviews combined five scientific theories to explain discordance. When models took into account both scale and preference heterogeneity, real-world choices to opt for influenza vaccination were correctly predicted by DCE at an aggregate level, and 91% of choices were correctly predicted at an individual level. There was 13% (49/377) discordance between stated choices and actual healthcare utilization. In-depth interviews showed that several dimensions played a role in clarifying this discordance: attitude, social support, action of planning, barriers, and intention. Evidence was found that our DCE yields accurate actual healthcare choice predictions if at least scale and preference heterogeneity are taken into account. Analysis of discordant subjects showed that we can even do better. The DCE measures an important part of preferences by focusing on attribute tradeoffs that people make in their decision to participate in a healthcare intervention. Inhibitors may be among these attributes, but it is more likely that inhibitors have to do with exogenous factors like goals, religion, and social norms. Con-ducting upfront work on constraints/inhibitors of the focal behavior, not just what promotes the behavior, might further improve predictive ability.

The effect of urban green on small-area (healthy) life expectancy.

BACKGROUND: Several epidemiological studies have investigated the effect of the quantity of green space on health outcomes such as self-rated health, morbidity and mortality ratios. These studies have consistently found positive associations between the quantity of green and health. However, the impact of other aspects, such as the perceived quality and average distance to public green, and the effect of urban green on population health are still largely unknown. METHODS: Linear regression models were used to investigate the impact of three different measures of urban green on small-area life expectancy (LE) and healthy life expectancy (HLE) in The Netherlands. All regressions corrected for average neighbourhood household income, accommodated spatial autocorrelation, and took measurement uncertainty of LE, HLE as well as the quality of urban green into account. RESULTS: Both the quantity and the perceived quality of urban green are modestly related to small-area LE and HLE: an increase of 1 SD in the percentage of urban green space is associated with a 0.1-year higher LE, and, in the case of quality of green, with an approximately 0.3-year higher LE and HLE. The average distance to the nearest public green is unrelated to population health. CONCLUSIONS: The quantity and particularly quality of urban green are positively associated with small-area LE and HLE. This concurs with a growing body of evidence that urban green reduces stress, stimulates physical activity, improves the microclimate and reduces ambient air pollution. Accordingly, urban green development deserves a more prominent place in urban regeneration and neighbourhood renewal programmes.