Comparing Patient Preferences for Antithrombotic Treatment During the Acute and Chronic Phases of Myocardial Infarction: A Discrete-Choice Experiment

Research Priorities to Increase Confidence in and Acceptance of Health Preference Research: What Questions Should be Prioritized Now?

BACKGROUND AND OBJECTIVE

There has been an increase in the study and use of stated-preference methods to inform medicine development decisions. The objective of this study was to identify prioritized topics and questions relating to health preferences based on the perspective of members of the preference research community.

METHODS

Preference research stakeholders from industry, academia, consultancy, health technology assessment/regulatory, and patient organizations were recruited using professional networks and preference-targeted e-mail listservs and surveyed about their perspectives on 19 topics and questions for future studies that would increase acceptance of preference methods and their results by decision makers. The online survey consisted of an initial importance prioritization task, a best-worst scaling case 1 instrument, and open-ended questions. Rating counts were used for analysis. The best-worst scaling used a balanced incomplete block design.

RESULTS

One hundred and one participants responded to the survey invitation with 66 completing the best-worst scaling. The most important research topics related to the synthesis of preferences across studies, transferability across populations or related diseases, and method topics including comparison of methods and non-discrete choice experiment methods. Prioritization differences were found between respondents whose primary affiliation was academia versus other stakeholders. Academic researchers prioritized methodological/less studied topics; other stakeholders prioritized applied research topics relating to consistency of practice.

CONCLUSIONS

As the field of health preference research grows, there is a need to revisit and communicate previous work on preference selection and study design to ensure that new stakeholders are aware of this work and to update these works where necessary. These findings might encourage discussion and alignment among different stakeholders who might hold different research priorities. Research on the application of previous preference research to new contexts will also help increase the acceptance of health preference information by decision makers.

Country and health expenditure are major predictors of withholding anticoagulation in atrial fibrillation patients at high risk of stroke

BACKGROUND

Guidelines for patients with atrial fibrillation (AF) at high thromboembolic risk recommend oral anticoagulants (OACs) for preventing stroke and systemic embolism (SE). The reasons for guideline non-adherence are still unclear.

AIM

The aim is to identify clinical, demographic and non-patient characteristics associated with withholding OAC in patients with AF at high stroke risk.

METHODS

Patients in the Global Anticoagulant Registry in the FIELD-AF, newly diagnosed with AF between March 2010 and August 2016, and with CHA2DS2-VASc Score≥2 (excluding sex), were grouped by OAC treatment at enrolment. Factors associated with OAC non-use were analysed by multivariable logistic regression.

RESULTS

Of 40 416 eligible patients, 12 126 (30.0%) did not receive OACs at baseline. Globally, OAC prescription increased over time, from 60.4% in 2010-2011 to 74.7% in 2015-2016. Country of enrolment was the major predictor for OAC withholding (χ2-df=2576). Clinical predictors of OAC non-use included type of AF (χ2-df=404), history of bleeding (χ2-df=263) and vascular disease (χ2-df=99). OACs were used most frequently around the age of 75 years and decreasingly with younger as well as older age beyond 75 years (χ2-df=148). Non-cardiologists (χ2-df=201) and emergency room physicians (χ2-df=14) were less likely to prescribe OACs. OAC prescription correlated positively with country health expenditure.

CONCLUSIONS

Approximately one out of three AF patients did not receive OAC, while eligible according to the guidelines. Country of enrolment was the major determinant of anticoagulation strategy, while higher country health expenditure was associated with lower likelihood of withholding anticoagulation.

Aspirin for the Primary Prevention of Vascular Ischemic Events: An Updated Systematic Review and Meta-analysis to Support Shared Decision-Making

Background

Since the publication of the 2010 Canadian antiplatelet guidelines, several large randomized controlled trials (RCTs) have evaluated the role of aspirin (ASA) use in primary prevention. We evaluated the effect of ASA use, compared with no ASA, on ischemic and bleeding events in patients without known atherosclerotic cardiovascular diseases.

Methods

We updated a published systematic review and meta-analysis by searching MEDLINE, Embase, and CENTRAL for the period up to March 2023. We included RCTs that enrolled patients for primary prevention of atherosclerotic cardiovascular diseases, and compared use of ASA to no ASA. We assessed risk of bias (RoB) using the Cochrane RoB tool, and certainty of evidence using the grading recommendations, assessment, development, and evaluation (GRADE) criteria. The primary efficacy outcome was major adverse cardiovascular events (MACE) (death, myocardial infarction, or stroke). The primary safety outcomes were intracranial hemorrhage and extracranial major bleeding events. We used a random-effects model to generate pooled risk ratios (RRs) and 95% confidence intervals (CIs).

Results

We included 14 RCTs (n = 167,587) at overall low RoB, with a median follow-up of 5 years. Compared to no ASA, ASA use reduced the incidence of MACE (RR 0.90, 95% CI 0.86-0.94), with a higher risk of intracranial hemorrhage (RR 1.33, 95% CI 1.13-1.56) and extracranial major bleeding (RR 1.67, 95% CI 1.36-2.06). In prespecified subgroups of age, sex, and diabetes, effect estimates were consistent.

Conclusions

ASA use in primary prevention is associated with a consistent reduction in MACE, but at the expense of major bleeding events. Patient values and preferences should be taken into account when considering ASA use for primary prevention.

Misuse of multinomial logistic regression in stroke related health research: A systematic review of methodology

Multinomial logistic regression (MLR) is often used to model the association between a nominal outcome variable and one or more covariates. The results of MLR are interpreted as relative risk ratios (RRR) and warrant a more coherent interpretation than ordinary logistic regression. Some authors compare the results of MLR to ordinal logistic regression (OLR), irrespective of the fact that these estimate different quantities. We aim to investigate the time trends in the use and misuse of MLR in studies including stroke patients, specifically the extent to which (1) the results are denoted as anything other than RRR, (2) comparisons are made of results with results of OLR and (3) results have been interpreted coherently. Secondarily, we examine the use of model validation techniques in studies with predictive aims. We searched EMBASE and PubMed for articles using MLR on populations of stroke patients. Identified studies were screened, and information pertaining to our aims was extracted. A total of 285 articles were identified through a systematic literature search, and 68 of these were included in the review. Of these, 60 articles (88%) did not denote exponentiated coefficients of MLR as relative risk ratios but rather some other measure. Additionally, 63 articles (93%) interpreted the results of MLR in a non-coherent manner. Two articles attempted to compare MLR results with those of OLR. Nine studies attempted to use MLR for predictive means, and three used relevant validation techniques. From these findings, it is clear that the interpretation of MLR is often suboptimal.

Current Health State Affected Patient Preferences More Than Disease Status: A Discrete Choice Experiment in Multiple Myeloma

OBJECTIVES

To examine how disease status and current health state influence treatment preferences of patients with multiple myeloma (MM).

METHODS

Participants with MM from France, Germany, and the United Kingdom completed a web-based survey that included a discrete choice experiment (DCE) and EQ-5D assessment. The DCE elicited preferences for 8 attributes: increased life expectancy, increased time to relapse, pain, fatigue, risk of infection, administration (route and duration), frequency of administration, and monitoring. Multinomial logit models were used to analyze DCE preference data and to calculate life expectancy trade-offs.

RESULTS

Three hundred participants with MM (newly diagnosed, transplant eligible, n = 108; newly diagnosed, transplant ineligible, n = 105; relapsed-refractory, n = 87) completed the survey. The most valued attributes were pain, fatigue, and increased life expectancy. Participants would want an additional 2.7 years of life expectancy (95% confidence interval [CI] 2.4-3.1 years) to tolerate extreme pain and an additional 2.0 years of life expectancy (95% CI 1.6-2.3 years) to tolerate constant fatigue. Participants in a better health state (third EQ-5D score quartile [0.897]) required less additional life expectancy than participants with a worse health state (first EQ-5D score quartile [0.662]) to tolerate extreme pain (2.3 years [95% CI 1.9-2.6 years] vs 3.0 years [95% CI 2.6-3.4 years]; P = .007). There was little difference in treatment preferences between newly diagnosed and relapsed-refractory patients for pain, fatigue, and increased life expectancy.

CONCLUSIONS

Current health state influenced treatment preferences of patients with MM more than disease status and should be considered when making treatment decisions.

Quantitative Benefit-Risk Assessment in Medical Product Decision Making: A Good Practices Report of an ISPOR Task Force

Benefit-risk assessment is commonly conducted by drug and medical device developers and regulators, to evaluate and communicate issues around benefit-risk balance of medical products. Quantitative benefit-risk assessment (qBRA) is a set of techniques that incorporate explicit outcome weighting within a formal analysis to evaluate the benefit-risk balance. This report describes emerging good practices for the 5 main steps of developing qBRAs based on the multicriteria decision analysis process. First, research question formulation needs to identify the needs of decision makers and requirements for preference data and specify the role of external experts. Second, the formal analysis model should be developed by selecting benefit and safety endpoints while eliminating double counting and considering attribute value dependence. Third, preference elicitation method needs to be chosen, attributes framed appropriately within the elicitation instrument, and quality of the data should be evaluated. Fourth, analysis may need to normalize the preference weights, base-case and sensitivity analyses should be conducted, and the effect of preference heterogeneity analyzed. Finally, results should be communicated efficiently to decision makers and other stakeholders. In addition to detailed recommendations, we provide a checklist for reporting qBRAs developed through a Delphi process conducted with 34 experts.

Treatment preferences in relation to fatigue of patients with relapsing multiple sclerosis: A discrete choice experiment

Background

Treatment decisions for multiple sclerosis (MS) are influenced by many factors such as disease symptoms, comorbidities, and tolerability.

Objective

To determine how much relapsing MS patients were willing to accept the worsening of certain aspects of their MS in return for improvements in symptoms or treatment convenience.

Methods

A web-based discrete choice experiment (DCE) was conducted in patients with relapsing MS. Multinomial logit models were used to estimate relative attribute importance (RAI) and to quantify attribute trade-offs.

Results

The DCE was completed by 817 participants from the US, the UK, Poland, and Russia. The most valued attributes of MS therapy to participants were effects on physical fatigue (RAI = 22.3%), cognitive fatigue (RAI = 22.0%), relapses over 2 years (RAI = 20.7%), and MS progression (RAI = 18.4%). Participants would accept six additional relapses in 2 years and a decrease of 7 years in time to disease progression to improve either cognitive or physical fatigue from "quite a bit of difficulty" to "no difficulty."

Conclusion

Patients strongly valued improving cognitive and physical fatigue and were willing to accept additional relapses or a shorter time to disease progression to have less fatigue. The impact of fatigue on MS patients' quality of life should be considered in treatment decisions.

Net clinical benefit of antiplatelet therapy was affected by patient preferences: A personalized benefit-risk assessment

OBJECTIVE

To assess the effect of patient preferences on the net clinical benefit (NCB) of an antiplatelet therapy for the secondary prevention of cardiovascular complications.

STUDY DESIGN AND SETTING

Risk equations were developed to estimate the individual predicted risk of key outcomes of antiplatelet treatment in patients with a prior myocardial infarction using the Clinical Practice Research Datalink linked to the Hospital Episode Statistics and UK Office of National Statistics databases. Patient preferences for outcomes of antiplatelet therapies were elicited in a separate discrete choice experiment survey. Trial hazard ratios, relative to placebo, were used to calculate the per-patient NCB using equal or preference weighting of outcomes.

RESULTS

Risk equations were estimated using 31,941 adults in the Clinical Practice Research Datalink population, of which 22,125 were included in the benefit-risk assessment. The mean NCB was lower in the preference-weighted than in the equal-weighted analysis (0.040 vs 0.057; p < 0.0001), but the direction of effect was unchanged by the weighting. In analyses stratified by the presence of bleeding risk factors, including preference weighting altered the ranking of subgroups by NCB.

CONCLUSION

Patient preference weighting may have a significant effect on NCB and should be included in personalized benefit-risk assessments.