Medical Decision Making最新文献

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.

Background: When selecting samples for patient preference studies, it may be difficult or impractical to recruit participants who are eligible for a particular treatment decision. However, a general public sample may not be an appropriate proxy.

Objective: This study compares preferences for rheumatoid arthritis (RA) preventive treatments between members of the general public and first-degree relatives (FDRs) of confirmed RA patients to assess whether a sample of the general public can be used as a proxy for FDRs.

Methods: Participants were asked to imagine they were experiencing arthralgia and had screening tests indicating a 60% chance of developing RA within 2 yrs. Using a discrete choice experiment, participants were offered a series of choices between no treatment and 2 unlabeled hypothetical treatments to reduce the risk of RA. To assess data quality, time to complete survey sections and comprehension questions were assessed. A random parameter logit model was used to obtain attribute-level estimates, which were used to calculate relative importance, maximum acceptable risk (MAR), and market shares of hypothetical preventive treatments.

Results: The FDR sample (n = 298) spent more time completing the survey and performed better on comprehension questions compared with the general public sample (n = 982). The relative importance ranking was similar between the general public and FDR participant samples; however, other relative preference measures involving weights including MARs and market share differed between groups, with FDRs having numerically higher MARs.

Conclusion: In the context of RA prevention, the general public (average risk) may be a reasonable proxy for a more at-risk sample (FDRs) for overall relative importance ranking but not weights. The rationale for a proxy sample should be clearly justified.

Highlights: Participants from the general public were compared to first-degree relatives on their preferences for rheumatoid arthritis (RA) preventive treatments using a discrete choice experiment.Preferences were similar between groups in terms of the most important and least important attributes of preventive treatments, with effectiveness being the most important attribute. However, relative weights differed.Attention to the survey and predicted market shares of hypothetical RA preventive treatments differed between the general public and first-degree relatives.The general public may be a reasonable proxy for an at-risk group for patient preferences ranks but not weights in the disease prevention context; however, care should be taken in sample selection for patient preference studies when choosing nonpatients.

Purpose: Evaluating interventions for cardiovascular disease (CVD) requires estimates of its effect on utility. We aimed to 1) systematically review utility estimates for CVDs published since 2013 and 2) critically appraise UK-relevant estimates and calculate corresponding baseline utility multipliers.

Methods: We searched MEDLINE and Embase (April 22, 2021) using CVD and utility terms. We screened results for primary studies reporting utility distributions for people with experience of heart failure, myocardial infarction, peripheral arterial disease, stable angina, stroke, transient ischemic attack, or unstable angina. We extracted characteristics from studies included. For UK estimates based on the EuroQoL 5-dimension (EQ-5D) measure, we assessed risk of bias and applicability to a decision-analytic model, pooled arms/time points as appropriate, and estimated baseline utility multipliers using predicted utility for age- and sex- matched populations without CVD. We sought utility sources from directly applicable studies with low risk of bias, prioritizing plausibility of severity ordering in our base-case model and highest population ascertainment in a sensitivity analysis.

Results: Most of the 403 studies identified used EQ-5D (n = 217) and most assessed Organisation for Economic Co-operation and Development populations (n = 262), although measures and countries varied widely. UK studies using EQ-5D (n = 29) produced very heterogeneous baseline utility multipliers for each type of CVD, precluding meta-analysis and implying different possible severity orderings. We could find sources that provided a plausible ordering of utilities while adequately representing health states.

Conclusions: We cataloged international CVD utility estimates and calculated UK-relevant baseline utility multipliers. Modelers should consider unreported sources of heterogeneity, such as population differences, when selecting utility evidence from reviews.

Highlights: Published systematic reviews have summarized estimates of utility associated with cardiovascular disease published up to 2013.We 1) reviewed utility estimates for 7 types of cardiovascular disease published since 2013, 2) critically appraised UK-relevant studies, and 3) estimated the effect of each cardiovascular disease on baseline utility.Our review 1) recommends a consistent and reliable set of baseline utility multipliers for 7 types of cardiovascular disease and 2) provides systematically identified reference information for researchers seeking utility evidence for their own context.

Background: Many widely used advance directives templates include direct questions on individuals' preferences for cardiopulmonary resuscitation (CPR) in case of decision-making incapacity during medical emergencies. However, as knowledge of the survival rates of CPR is often limited, individuals' advance decisions on CPR may be poorly aligned with their preferences if false beliefs about the survival rates of CPR shape stated preferences for CPR.

Methods: We analyzed nationally representative data from 1,469 adults aged 58+ y who responded to wave 8 (2019/2020) of the Swiss version of the Survey on Health, Ageing, and Retirement in Europe (SHARE) to assess the partial association between knowledge of CPR survival rates and stated preferences for CPR using multivariable probit regression models that adjust for social, health, and regional characteristics. Knowledge of CPR survival rates was assessed by asking how likely it is in general in Switzerland for a 70-y-old to survive until hospital discharge from a CPR performed outside of a hospital. Preferences for CPR were measured by asking respondents if they would wish to be resuscitated in case of cardiac arrest.

Results: Only 9.3% of respondents correctly assessed the chances for a 70-y-old to survive until hospital discharge from a CPR performed outside of a hospital, while 65.2% indicated a preference to be resuscitated in case of a cardiac arrest. Respondents who correctly assessed CPR survival were significantly more likely to wish not to be resuscitated (average marginal effect: 0.18, P < 0.001).

Conclusions: Reducing misconceptions concerning the survival rates of CPR could change older adults' preferences for CPR and make them more likely to forgo such treatments.

Highlights: Many older adults in Switzerland overestimate the survival rates of cardiopulmonary resuscitation (CPR).The study reveals that individuals with accurate knowledge of CPR survival rates are more likely to refuse resuscitation in case of cardiac arrest.Overestimation of CPR survival rates may lead to a mismatch between individuals' preferences for CPR and their actual end-of-life care decisions.Improving the general population's knowledge of CPR survival rates is crucial to ensure informed decision making and effective advance care planning.

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR.

Methods: A total of 307 patients with non-small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen's weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected.

Results: Most respondents (>65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P < 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P < 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53-0.55).

Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions.

Highlights: Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability.Most respondents found the DCE and SW tasks very easy or easy to understand and answer.A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.

Background: Mortality is critical information in evaluating the benefits of cancer screening. However, 5-y survival rates and incidence, without mortality, have been frequently communicated to the public. Based on the literature that people's perceptions and judgments can be altered by the way of presenting health statistics, the current study examined whether mortality alongside 5-y survival and incidence would influence laypeople's perceptions of the effectiveness of cancer screening and screening intention.

Methods: In an online-based experimental survey conducted in South Korea in October 2022, 300 adults were randomly assigned to 1 of 2 groups (mortality: no v. yes) to be presented with 3 different cancers (A, B, and C). The perceived effectiveness of cancer screening and screening intention were measured using 7-point scales for each cancer.

Results: Across all cancers, participants in the no-mortality group perceived cancer screening to be more effective and were more willing to undergo screening compared with those in the mortality group, although the results were not statistically significant on the intention.

Conclusions: In general, mortality had an effect of decreasing the perceived effectiveness of cancer screening and screening intention compared with no mortality, although the effect on the intention was not statistically significant.

Implications: When communicating the benefits of cancer screening to the public, mortality statistics may play a role in mitigating the potentially inflated perception of the benefits of cancer screening and screening intention.

Highlights: Five-year survival rates, either alone or with incidence rates, are frequently communicated to the public in the context of the benefits of cancer screening.However, 5-y survival rates can sometimes be inflated without a reduction in mortality.Including mortality statistics in communications decreased the perceived effectiveness of cancer screening and screening intentions.Mortality information needs to be communicated in the benefits of cancer screening.

Background: There is limited understanding of how risk perceptions changed as the US population gained experience with COVID-19. The objectives were to examine risk perceptions and determine the factors associated with risk perceptions and how these changed over the first 18 mo of the pandemic.

Methods: Seven cross-sectional online surveys were fielded between May 2020 and October 2021. The study included a population-weighted sample of 138,303 US adults drawn from a market research platform, with an average 68% cooperation rate. Respondents' risk perception of developing COVID in the next 30 days was assessed at each time point. We examined relationships between 30-day risk perceptions and various factors (including sociodemographic features, health, COVID-19 experience, political affiliation, and psychological variables).

Results: COVID risk perceptions were stable across the 2020 surveys and showed a significant decrease in the 2021 surveys. Several factors, including older age, worse health, high COVID worry, in-person employment type, higher income, Democratic political party affiliation (the relatively more liberal party in the United States), low tolerance of uncertainty, and high anxiety were strongly associated with higher 30-d risk perceptions in 2020. One notable change occurred in 2021, in that younger adults (aged 18-29 y) had significantly higher 30-d risk perceptions than older adults did (aged 65 y and older) after vaccination. Initial differences in perception by political party attenuated over time. Higher 30-d risk perceptions were significantly associated with engaging in preventive behaviors.

Limitations: Cross-sectional samples, risk perception item focused on incidence not severity.

Conclusions: COVID risk perceptions decreased over time. Understanding the longitudinal pattern of risk perceptions and the factors associated with 30-d risk perceptions over time provides valuable insights to guide public health communication campaigns.

Highlights: The study assessed COVID-19 risk perceptions at 7 time points over 18 mo of the pandemic in large samples of US adults.Risk perceptions were fairly stable until the introduction of vaccines in early 2021, at which point they showed a marked reduction.Higher COVID-19 30-d risk perceptions were significantly associated with the preventive behaviors of masking, limiting social contact, avoiding restaurants, and not entertaining visitors at home.

Background: Lung cancer clinical guidelines and risk tools often rely on smoking history as a significant risk factor. However, never-smokers make up 14% of the lung cancer population, and this proportion is rising. Consequently, they are often perceived as low-risk and may experience diagnostic delays. This study aimed to explore how clinicians make risk-informed diagnostic decisions for never-smokers.

Methods: Qualitative interviews were conducted with 10 lung cancer diagnosticians, supported by data from interviews with 20 never-smoker lung cancer patients. The data were analyzed using a framework analysis based on the Model of Pathways to Treatment framework and data-driven interpretations.

Results: Participants described 3 main strategies for making risk-informed decisions incorporating smoking status: guidelines, heuristics, and potential harms. Clinicians supplemented guidelines with their own heuristics for never-smokers, such as using higher thresholds for chest X-ray. Decisions were easier for patients with high-risk symptoms such as hemoptysis. Clinicians worried about overinvestigating never-smoker patients, particularly in terms of physical and psychological harms from invasive procedures or radiation. To minimize unnecessary anxiety about lung cancer risk, clinicians made efforts to downplay this. Conversely, some patients found that this caused process harms such as delays and miscommunications.

Conclusion: Improved guidance and methods of risk differentiation for never-smokers are needed to avoid diagnostic delays, overreassurance, and clinical pessimism. This requires an improved evidence base and initiatives to increase awareness among clinicians of the incidence of lung cancer in never-smokers. As the proportion of never-smoker patients increases, this issue will become more urgent.

Highlights: Smoking status is the most common risk factor used by clinicians to guide decision making, and guidelines often focus on this factor.Some clinicians also use their own heuristics for never-smokers, and this becomes particularly relevant for patients with lower risk symptoms.Clinicians are also concerned about the potential harms and risks associated with deploying resources on diagnostics for never-smokers.Some patients find it difficult to decide whether or not to go ahead with certain procedures due to efforts made by clinicians to downplay the risk of lung cancer.Overall, the study highlights the complex interplay between smoking history, clinical decision making, and patient anxiety in the context of lung cancer diagnosis and treatment.

Background: To assess the impact of risk perceptions on prevention efforts or behavior change, best practices involve conditional risk measures, which ask people to estimate their risk contingent on a course of action (e.g., "if not vaccinated").

Purpose: To determine whether the use of conditional wording-and its drawing of attention to one specific contingency-has an important downside that could lead researchers to overestimate the true relationship between perceptions of risk and intended prevention behavior.

Methods: In an online experiment, US participants from Amazon's MTurk (N = 750) were presented with information about an unfamiliar fungal disease and then randomly assigned among 3 conditions. In all conditions, participants were asked to estimate their risk for the disease (i.e., subjective likelihood) and to decide whether they would get vaccinated. In 2 conditional-wording conditions (1 of which involved a delayed decision), participants were asked about their risk if they did not get vaccinated. For an unconditional/benchmark condition, this conditional was not explicitly stated but was still formally applicable because participants had not yet been informed that a vaccine was even available for this disease.

Results: When people gave risk estimates to a conditionally worded risk question after making a decision, the observed relationship between perceived risk and prevention decisions was inflated (relative to in the unconditional/benchmark condition).

Conclusions: The use of conditionals in risk questions can lead to overestimates of the impact of perceived risk on prevention decisions but not necessarily to a degree that should call for their omission.

Highlights: Conditional wording, which is commonly recommended for eliciting risk perceptions, has a potential downside.It can produce overestimates of the true relationship between perceived risk and prevention behavior, as established in the current work.Though concerning, the biasing effect of conditional wording was small-relative to the measurement benefits that conditioning usually provides-and should not deter researchers from conditioning risk perceptions.More research is needed to determine when the biasing impact of conditional wording is strongest.