AIMS:To understand disease perceptions and treatment preferences of patients with high-risk smoldering multiple myeloma (HR-SMM) or multiple myeloma (MM) that recently progressed from HR-SMM, and to estimate the minimum progression-free survival (min-PFS) required to accept the treatment burden. METHODS:This mixed-methods study interviewed 50 patients (HR-SMM and MM 1:1) from the USA, France, Italy, and Spain. Qualitative semi-structured interviews explored symptoms, quality of life, and awareness and expectations of SMM treatments. A quantitative thresholding exercise elicited the min-PFS for patients to accept a hypothetical treatment. Results were reported for HR-SMM and MM. RESULTS:The most common symptoms were fatigue (68%) and pain (56%); 20% were asymptomatic. Most treatment-naïve patients (n = 31/44) accepted physician recommendations that treatment was not needed, burdensome, or not available. Twenty-three patients (61%) were willing to start treatment while having HR-SMM. Patients expected treatments to delay disease progression (30%) or increase life expectancy (24%), whereas 22% expected to be "cured" if treated. The min-PFS for the given treatment was 60 months; 61 and 59 months for HR-SMM and MM, respectively. CONCLUSIONS:Considerable psychological, physical, and functional burdens were imposed on HR-SMM patients by potential disease progression. Most patients were willing to receive treatment to delay progression and reduce symptomatic burden.

Preference information describes the relative desirability or acceptability of specified alternatives that differ across health states, interventions, or services. Studies that generate preference information are being designed to support patient-centered decision making across all stages of the medical product lifecycle, as well as in healthcare more generally. Ensuring high-quality preference research with the potential for impact requires transparent and thoughtful study design, a core aspect of which often includes the development of attributes. Good practices for attribute development in preference studies have started to emerge and demonstrate that developing attributes requires substantial time and effort. Resources to more easily and systematically identify potentially relevant attributes may support the accessibility, interoperability, and reusability of attributes, in turn improving the efficiency of preference study design and comparability of findings across studies. In this paper, we first describe the need for and potential benefit of tools that promote the purposeful re-use of attributes for preference studies. We next present a taxonomy for categorizing and describing attributes that could be applied to facilitate their identification. Finally, we apply this taxonomy to a prototype “attribute library,” developed as a part of a Medical Device Innovation Consortium work group, to demonstrate the potential value of these resources to support the preference research community.

Both bleeding and adverse ischemic events increase with age, compounding the benefit–risk balance of anticoagulants in older patients. We present analyses using benefit–risk methods to better understand the age-dependence of the benefit–risk profile of rivaroxaban in patients with nonvalvular atrial fibrillation (NVAF) or venous thromboembolism (VTE). Randomized controlled trial data from the ROCKET-AF (NVAF) and EINSTEIN DVT, EINSTEIN PE, EINSTEIN-Extension, and EINSTEIN CHOICE in (VTE) were used. For ROCKET-AF, benefits and risks were assessed with incidence rates for key thrombotic and bleeding endpoints and a net clinical benefit (NCB) measure. Cumulative incidences (estimated by the Kaplan–Meier method) were estimated at day 185 for EINSTEIN and EINSTEIN Extension and 1 year for EINSTEIN CHOICE. Incidence differences were calculated for the overall population and age subgroups of < 65, 65–75, and > 75 years. In ROCKET-AF, rate differences in the composite NCB outcome (vascular death, stroke, myocardial infarction, fatal bleeding, critical organ bleeding, and non-CNS systemic embolism) favored rivaroxaban overall and by age < 65, 65–75, and > 75 years (−84, −25, −61, and −150 cases per 10,000 patient-years, respectively). In the pooled EINSTEIN DVT and EINSTEIN PE studies, cumulative incidence differences for the composite NCB outcome (recurrent VTE and major bleeding) were −103, 3, −105, and −544 per 10,000 patients, respectively. For extended VTE treatment with rivaroxaban versus placebo in EINSTEIN-Extension, NCB results were −536, −492, −556, and −601 per 10,000 patients, respectively. In the EINSTEIN CHOICE analysis, NCB favored rivaroxaban 20 mg versus aspirin (−284, −255, −339, and −338, respectively) and rivaroxaban 10 mg versus aspirin (−339, −328, −485, and −80, respectively). This analysis demonstrated a positive benefit–risk profile with rivaroxaban versus trial comparators in older patients with NVAF or VTE, with benefit–risk increasingly favoring rivaroxaban with increasing age. Clinical Trial Registration: http://ClinicalTrials.gov , identifiers: NCT00403767 (ROCKET-AF), NCT00440193 (EINSTEIN DVT), NCT00439777 (EINSTEIN PE), NCT00439725 (EINSTEIN Extension), and NCT02064439 (EINSTEIN CHOICE). Anticoagulants are medications that prevent blood clots. They can treat or prevent health problems caused by abnormal blood clotting. Anticoagulants can be used to prevent stroke in patients who have a heart condition called atrial fibrillation (AF). They can also treat or prevent blood clots that form in the veins called venous thromboembolism (VTE). As patients get older, their risk of stroke or blood clots increases. Although anticoagulants are helpful for these conditions, they can cause bleeding. The risk of bleeding increases with age and certain other diseases, such as heart failure, diabetes, and high blood pressure. When choosing an anticoagulant, it is important to look at both the benefits (reducing blood clots) and risks (bleeding) of the drug. Research studies have tested the efficacy and safety of the anticoagulant rivaroxaban by comparing it against standard treatment in patients with AF (ROCKET-AF study) and VTE (EINSTEIN studies). Our analysis used data from these studies to focus on specific outcomes related to rivaroxaban’s benefits and risks. This analysis compared the frequency of these outcomes between different treatments in all patients and in patients who were younger than 65, 65–75, and older than 75 years of age. In patients with AF or VTE, rivaroxaban had higher benefits than risks overall and for each of the age groups studied. The positive differences between benefits and risks of rivaroxaban appeared to grow in older groups of patients. These results suggest that rivaroxaban’s treatment benefits outweigh the risks in older patients.

Using patient preference information (PPI) to incorporate patient voices into the drug development lifecycle can help align therapies with the needs and values of patients. However, several barriers have limited the use of PPI, including a lack of clarity on its use by decision-makers, a need for greater decision-maker trust in PPI, and a lack of time, budgets, and access to specialist expertise. The value proposition for PPI could be enhanced by making it FAIR: Findable, Accessible, Interoperable, and Reusable. To support the development of a research agenda to deliver FAIR PPI, we reviewed related endeavors in the development of repositories of existing studies, disease models, benefit transfer, and common data standards. We concluded that developing FAIR PPI would require advances in the science of PPI, including the establishment of a consortium, mirroring the Clinical Data Interchange Standards Consortium (CDISC) or Observational Medical Outcomes Partnership (OPOM), to develop PPI data standards, and research into the sources of variation in patient preferences. This will require the science of PPI to graduate from being a body of empirical observations to developing theories that explain variations in patient preferences, simultaneously driving both efficiency in the generation of PPI and trust in PPI.

In health preference research (HPR) studies, data are generated by participants’/subjects’ decisions. When developing an HPR study, it is therefore important to have a clear understanding of the components of a decision and how those components stimulate participant behavior. To obtain valid and reliable results, study designers must sufficiently describe the decision model and its components. HPR studies require a detailed examination of the decision criteria, detailed documentation of the descriptive framework, and specification of hypotheses. The objects that stimulate subjects’ decisions in HPR studies are defined by attributes and attribute levels. Any limitations in the identification and presentation of attributes and levels can negatively affect preference elicitation, the quality of the HPR data, and study results. This practical guide shows how to link the HPR question to an underlying decision model. It covers how to (1) construct a descriptive framework that presents relevant characteristics of a decision object and (2) specify the research hypotheses. The paper outlines steps and available methods to achieve all this, including the methods’ advantages and limitations.

Background The VOYAGER PAD (Efficacy and Safety of Rivaroxaban in Reducing the Risk of Major Thrombotic Vascular Events in Subjects With Symptomatic Peripheral Artery Disease Undergoing Peripheral Revascularization Procedures of the Lower Extremities) trial compared rivaroxaban (2.5 mg twice a day) plus aspirin with aspirin alone in patients with symptomatic peripheral artery disease requiring endovascular or surgical limb revascularization, with 50% receiving clopidogrel background therapy. The New Drug Indication application includes benefit–risk assessments using clinical judgment to balance benefits against risks. During its review, the US Food and Drug Administration requested additional quantitative benefit–risk analyses with formal weighting approaches. Methods and Results Benefits and risks were assessed using rate differences between treatment groups (unweighted analysis). To account for clinical importance of the end points, a multi‐criteria decision analysis was conducted using health state utility values as weights. Monte Carlo simulations incorporated statistical uncertainties of the event rates and utility weights. Intent‐to‐treat and on‐treatment analyses were conducted. For unweighted intent‐to‐treat analyses, rivaroxaban plus aspirin would result in 120 (95% CI, −208 to −32) fewer events of the primary composite end point (per 10 000 patient‐years) compared with aspirin alone. Rivaroxaban caused an excess of 40 (95% CI, 8–72) Thrombolysis in Myocardial Infarction major bleeding events, which was largely driven by nonfatal, nonintracranial hemorrhage Thrombolysis in Myocardial Infarction major bleeding events. For weighted analyses, rivaroxaban resulted in the utility equivalent of 13.7 (95% CI, −85.3 to 52.6) and 68.1 (95% CI, 7.9–135.7) fewer deaths per 10 000 patient‐years (intent‐to‐treat and on‐treatment, respectively), corresponding to probabilities of 64.4% and 98.7%, respectively, that benefits outweigh risks favoring rivaroxaban per Monte Carlo simulation. Conclusions These analyses show a favorable benefit–risk profile of rivaroxaban therapy in the VOYAGER PAD trial, with findings generally consistent between the unweighted and weighted approaches.

Benefit-risk assessment (BRA) is critical for decision-making throughout the vaccine life cycle. It requires scientific assessment of evidence to make an informed judgment on whether the vaccine has a favourable benefit-risk profile i.e. the benefits of the vaccine outweigh its risks for use in its intended indication. The assessment must also consider data gaps and uncertainties, using sensitivity analyses to show the impact of these uncertainties in the assessment. The BRA field has advanced considerably over the past years, including the use of structured BRA frameworks, quantitative BRA models and use of the patient experience data. Analytical tools and procedures to standardize BRA implementation have become increasingly important. A Benefit-Risk Assessment Module has been prepared to enable the planning, assessment, and communication of relevant BRA information via a structured B-R framework. The module can help facilitate the conduct and communication of defensible BRAs by vaccine developers, funders, regulators and policy makers in high, middle or low-income countries, both for regulatory submissions and in public health responses to infectious diseases, including for epidemics.

Recent reports related to in utero exposure of marketed immunosuppressive biologics led to clinical recommendations to delay live vaccinations for infants due to the concern of reduced vaccine effectiveness and/or increased risk of vaccine-related disease. These delays can increase the risk of children contracting vaccine preventable diseases, yet the alternative cessation of biologics during pregnancy may result in increased autoimmune disease activity for the pregnant person, raising complex benefit-risk (B-R) considerations and trade-offs. Our goal is to develop a conceptual framework for B-R assessment based on the key benefits and risks pregnant people would consider for themselves and their children when continuing (vs. discontinuing) a biologic during pregnancy. The proposed framework defines the decision contexts, key domains and attributes for potential benefits, and risks of biologic use during pregnancy, informed by a literature review of indications for biologics and refined with key clinical stakeholders. The framework includes both the pregnant person taking the biologic and the infant potentially exposed to the biologic in utero, with potential benefit and risk domains and attributes for each participant. To advance this conceptual framework, there are considerations of potential biases and uncertainty of available data that will be imperative to address when quantifying the B-R framework. For these reasons, we recommend the formation of a consortium to ensure development of a robust, validated framework that can be adopted in the healthcare setting.

Background: In the OPTIMUM trial in patients with relapsing MS, treatment differences in annualized relapse rate (ARR, 0.088) and change in fatigue at week 108 (3.57 points, measured using the Fatigue Symptoms and Impacts Questionnaire–Relapsing Multiple Sclerosis, symptom domain (FSIQ-RMS-S)) favored ponesimod over teriflunomide. However, the importance of the fatigue outcome to patients was unclear. Objective: To assess the importance of the OPTIMUM FSIQ-RMS-S results using data from an MS discrete choice experiment (DCE). Methods: The DCE included components to correlate levels of physical and cognitive fatigue with FSIQ-RMS-S scores. Changes in relapses/year and time to MS progression equivalent to the treatment difference in fatigue in OPTIMUM were determined for similar fatigue levels as mean baseline fatigue in OPTIMUM. Results: DCE participants would accept 0.06 more relapses/year or a 0.15–0.17 year decrease in time to MS progression for a 3.57-point difference in physical fatigue on the FSIQ-RMS-S. To improve cognitive fatigue by 3.57-points on the FSIQ-RMS-S, DCE participants would accept 0.09–0.10 more relapses/year or a 0.24–0.28 year decrease in time to MS progression. Conclusion: MS patients would accept 0.06 more relapses/year to change their fatigue by a similar magnitude as the between-treatment difference observed in the OPTIMUM trial.

Background and Objectives. Risk-tolerance measures from patient-preference studies typically focus on individual adverse events. We recently introduced an approach that extends maximum acceptable risk (MAR) calculations to simultaneous maximum acceptable risk thresholds (SMART) for multiple treatment-related risks. We extend these methods to include the computation and display of confidence intervals and apply the approach to 3 published discrete-choice experiments to evaluate its utility to inform regulatory decisions. Methods. We generate MAR estimates and SMART curves and compare them with trial-based benefit-risk profiles of select treatments for depression, psoriasis, and thyroid cancer. Results. In the depression study, SMART curves with 70% to 95% confidence intervals portray which combinations of 2 adverse events would be considered acceptable. In the psoriasis example, the asymmetric confidence intervals for the SMART curve indicate that relying on independent MARs versus SMART curves when there are nonlinear preferences can lead to decisions that could expose patients to greater risks than they would accept. The thyroid cancer application shows an example in which the clinical incidence of each of 3 adverse events is lower than the single-event MARs for the expected treatment benefit, yet the collective risk profile surpasses acceptable levels when considered jointly. Limitations. Nonrandom sample of studies. Conclusions. When evaluating conventional MARs in which the observed incidences are near the estimated MARs or where preferences demonstrate diminishing marginal disutility of risk, conventional MAR estimates will overstate risk acceptance, which could lead to misinformed decisions, potentially placing patients at greater risk of adverse events than they would accept. Implications. The SMART method, herein extended to include confidence intervals, provides a reproducible, transparent evidence-based approach to enable decision makers to use data from discrete-choice experiments to account for multiple adverse events. Highlights Estimates of maximum acceptable risk (MAR) for a defined treatment benefit can be useful to inform regulatory decisions; however, the conventional metric considers one adverse event at a time. This article applies a new approach known as SMART (simultaneous maximum acceptable risk thresholds) that accounts for multiple adverse events to 3 published discrete-choice experiments. Findings reveal that conventional MARs could lead decision makers to accept a treatment based on individual risks that would not be acceptable if multiple risks are considered simultaneously.

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.

Objectives To understand industry practices and challenges when submitting patient experience data (PED) for regulatory decisions by the US Food and Drug Administration (FDA). Methods A two-part online survey related to collection, submission, and use of PED by FDA in regulatory decision-making (part 1) and a best-worst exercise for prioritizing potential PED initiatives (part 2) was completed by industry and contract research organization (CRO) members with ≥ 2 years of recent experience with patient-reported outcome (PRO), natural history study (NHS), or patient preference (PP) data; and direct experience with FDA filings including PED. Results A total of 50 eligible respondents (84% industry) completed part 1 of the survey, among which 46 completed part 2. Respondents mostly had PRO (86%) and PP (50%) experience. All indicated that FDA meetings should have a standing agenda item to discuss PED. Most (78%) reported meetings should occur before pivotal trials. A common challenge was justifying inclusion without knowing if and how data will be used. Most agreed that FDA and industry should co-develop the PED table in the FDA clinical review (74%), and the table should report reason(s) for not using PED (96%) in regulatory decision-making. Most important efforts to advance PED use in decision-making were a dedicated meeting pathway and expanded FDA guidance (51% each). Conclusions FDA has policy targets expanding PED use, but challenges remain regarding pathways for PED submission and transparency in regulatory decision-making. Alignment on the use of existing meeting opportunities to discuss PED, co-development of the PED table, and expanded guidance are encouraged.

Vaccine Benefit-Risk (B-R) assessment consists of evaluating the benefits and risks of a vaccine and making a judgment whether the expected key benefits outweigh the potential key risks associated with its expected use. B-R supports regulatory and public health decision-making throughout the vaccine's lifecycle. In August 2021, the Brighton Collaboration's Benefit-Risk Assessment of VAccines by TechnolOgy (BRAVATO) Benefit-Risk Assessment Module working group was established to develop a standard module to support the planning, conduct and evaluation of structured B-R assessments for vaccines from different platforms, based on data from clinical trials, post-marketing studies and real-world evidence. It enables sharing of relevant information via value trees, effects tables and graphical depictions of B-R trade-offs. It is intended to support vaccine developers, funders, regulators and policy makers in high-, middle- or low-income countries to help inform decision-making and facilitate transparent communication concerning development, licensure, deployment and other lifecycle decisions.

Objective: Patients have unique insights and are (in-)directly affected by each decision taken throughout the life cycle of medicinal products. Patient preference studies (PPS) assess what matters most to patients, how much, and what trade-offs patients are willing to make. IMI PREFER was a six-year European public-private partnership under the Innovative Medicines Initiative that developed recommendations on how to assess and use PPS in medical product decision-making, including in the regulatory evaluation of medicinal products. This paper aims to summarize findings and recommendations from IMI PREFER regarding i) PPS applications in regulatory evaluation, ii) when and how to consult with regulators on PPS, iii) how to reflect PPS in regulatory communication and iv) barriers and open questions for PPS in regulatory decision-making.Methods: PREFER performed six literature reviews, 143 interviews and eight focus group discussions with regulators, patient representatives, industry representatives, Health Technology Assessment bodies, payers, academics, and clincians between October 2016 and May 2022.Results: i) With respect to PPS applications, prior to the conduct of clinical trials of medicinal products, PPS could inform regulators' understanding of patients' unmet needs and relevant endpoints during horizon scanning activities and scientific advice. During the evaluation of a marketing authorization application, PPS could inform: a) the assessment of whether a product meets an unmet need, b) whether patient-relevant clinical trial endpoints and outcomes were studied, c) the understanding of patient-relevant effect sizes and acceptable trade-offs, and d) the identification of key (un-)favorable effects and uncertainties. ii) With respect to consulting with regulators on PPS, PPS researchers should ideally have early discussions with regulators (e.g., during scientific advice) on the PPS design and research questions. iii) Regarding external PPS communication, PPS could be reflected in the assessment report and product information (e.g., the European Public Assessment Report and the Summary of Product Characteristics). iv) Barriers relevant to the use of PPS in regulatory evaluation include a lack of PPS use cases and demonstrated impact on regulatory decision-making, and need for (financial) incentives, guidance and quality criteria for implementing PPS results in regulatory decision-making. Open questions concerning regulatory PPS use include: a) should a product independent broad approach to the design of PPS be taken and/or a product-specific one, b) who should optimally be financing, designing, conducting, and coordinating PPS, c) when (within and/or outside clinical trials) to perform PPS, and d) how can PPS use best be operationalized in regulatory decisions.Conclusion: PPS have high potential to inform regulators on key unmet needs, endpoints, benefits, and risks that matter most to patients and their acceptable trade-offs. Regulatory guidelines, templates and checklists, together with incentives are needed to foster structural and transparent PPS submission and evaluation in regulatory decision-making. More PPS case studies should be conducted and submitted for regulatory assessment to enable regulatory discussion and increase regulators' experience with PPS implementation and communication in regulatory evaluations.

Objectives: Quantitative benefit-risk assessment (qBRA) is a structured process to evaluate the benefit-risk balance of treatment options to support decision making. The ISPOR qBRA Task Force was recently established to provide recommendations for the design, conduct, and reporting of qBRA. This report presents a hypothetical case study illustrating how to apply the Task Force's recommendations toward a qBRA to inform the benefit-risk assessment of brodalumab at the time of initial marketing approval. The qBRA evaluated 2 dosing regimens of brodalumab (210 mg or 140 mg twice weekly) compared with weight-based dosing of ustekinumab and placebo. Methods: We followed the 5 steps recommended by the Task Force. Attributes included treatment response ($75% improvement in Psoriasis Area and Severity Index), suicidal ideation and behavior, and infections. Performance data were drawn from pivotal clinical trials of brodalumab. The qBRA used multicriteria decision analysis and preference weights from a hypothetical discrete choice experiment. Sensitivity analyses examined the robustness of benefit-risk ranking to uncertainty in clinical effect and preference estimates, consideration of a subgroup (nail psoriasis), and the maintenance phase of treatment (52 weeks instead of 12). Results: Results from this hypothetical qBRA suggest that brodalumab 210 mg had a more favorable benefit-risk profile compared with ustekinumab and placebo. Ranking of brodalumab compared with ustekinumab was dependent on brodalumab's dose. Sensitivity analyses demonstrated robustness of benefit-risk ranking to uncertainty in clinical effect and preference estimates, as well as choice of attributes and length of follow-up. Conclusion: This case study demonstrates how to implement the ISPOR Task Force's good practice recommendations on qBRA.

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.

To report (i) key experiences and (ii) outcomes of the EMA/EUnetHTA qualification process, and (iii) the value and implications of the qualification opinion itself on the IMI PREFER patient preference framework and points to consider for method selection.

Background Thromboprophylaxis extended after hospital discharge in medically ill patients currently is not recommended by practice guidelines because of uncertainty about the benefit for preventing major or fatal thromboembolic events, and the risk of bleeding. Methods and Results We assessed the benefit and risk of thromboprophylaxis with rivaroxaban 10 mg once daily extended for 25 to 45 days after hospitalization for preventing major thromboembolism in medically ill patients using the pooled data in 16 496 patients from 2 randomized trials, MARINER (Medically Ill Patient Assessment of Rivaroxaban Versus Placebo in Reducing Post‐Discharge Venous Thrombo‐Embolism Risk) and MAGELLAN (Multicenter, randomized, parallel‐group efficacy and safety study for the prevention of venous thromboembolism in hospitalized medically ill patients comparing rivaroxaban with enoxaparin). The data from the MARINER trial were pooled with the data from the MAGELLAN trial in patients who were free of thrombotic or bleeding events up to the last dose of enoxaparin/placebo and who continued in the outpatient phase of thromboprophylaxis. The composite outcome of major thromboembolic events (symptomatic deep vein thrombosis, nonfatal pulmonary embolism, myocardial infarction, and nonhemorrhagic stroke) and all‐cause mortality was used to assess benefit and was compared with the risk of the composite of fatal and critical site bleeding. The incidence of the composite efficacy outcome was 1.80% (148 of 8222 patients) in the rivaroxaban group, compared with 2.31% (191 of 8274 patients in the placebo group) (HR, 0.78 [95% CI, 0.63–0.97], P=0.024). Fatal or critical site bleeding events were infrequent and occurred in <0.1% of patients in both groups (rivaroxaban 0.09%; placebo 0.04%; HR, 2.36; P=0.214). Conclusions The results suggest a benefit for reducing major thromboembolic outcomes (number needed to treat: 197), with a favorable trade‐off to fatal or critical site bleeding (number needed to harm: 2045). Registration URL: https://www.clinicaltrials.gov; Unique identifiers: NCT00571649 and NCT02111564.