Benefit-risk Trade-off Research Articles

Design and sample size determination for multiple-dose randomized phase II trials for dose optimization.

The U.S. Food and Drug Administration (FDA) has launched Project Optimus to shift dose selection from the maximum tolerated dose (MTD) to the dose that produces the optimal risk-benefit tradeoff. One approach highlighted in the FDA's guidance involves conducting a randomized phase II trial following the completion of a phase I trial, where multiple doses (typically including the MTD and one or two doses lower than the MTD) are compared to identify the optimal dose that maximizes the benefit-risk tradeoff. This article focuses on the design of such a multiple-dose randomized trial, specifically the determination of the sample size. We generalized the standard definitions of type I error and power to accommodate the unique characteristics of dose optimization and derived a decision rule along with an algorithm to determine the optimal sample size. The resulting design is referred to as MERIT (Multiple-dosE RandomIzed Trial design for dose optimization based on toxicity and efficacy). Simulation studies demonstrate that MERIT has desirable operating characteristics, and a sample size between 20 and 40 per dosage arm often offers reasonable power and type I errors to ensure patient safety and benefit. To facilitate the implementation of the MERIT design, we provide software, available at https://www.trialdesign.org.

A Bayesian quasi-likelihood design for identifying the minimum effective dose and maximum utility dose in dose-ranging studies.

Most existing dose-ranging study designs focus on assessing the dose-efficacy relationship and identifying the minimum effective dose. There is an increasing interest in optimizing the dose based on the benefit-risk tradeoff. We propose a Bayesian quasi-likelihood dose-ranging design that jointly considers safety and efficacy to simultaneously identify the minimum effective dose and the maximum utility dose to optimize the benefit-risk tradeoff. The binary toxicity endpoint is modeled using a beta-binomial model. The efficacy endpoint is modeled using the quasi-likelihood approach to accommodate various types of data (e.g. binary, ordinal or continuous) without imposing any parametric assumptions on the dose-response curve. Our design utilizes a utility function as a measure of benefit-risk tradeoff and adaptively assign patients to doses based on the doses' likelihood of being the minimum effective dose and maximum utility dose. The design takes a group-sequential approach. At each interim, the doses that are deemed overly toxic or futile are dropped. At the end of the trial, we use posterior probability criteria to assess the strength of the dose-response relationship for establishing the proof-of-concept. If the proof-of-concept is established, we identify the minimum effective dose and maximum utility dose. Our simulation study shows that compared with some existing designs, the Bayesian quasi-likelihood dose-ranging design is robust and yields competitive performance in establishing proof-of-concept and selecting the minimum effective dose. Moreover, it includes an additional feature for further maximum utility dose selection.

Optimizing the benefit–risk trade-off in nano-agrochemicals through explainable machine learning: beyond concentration

An explainable ML-driven MOO approach is proposed for the benefit–risk trade-off of nano-agrochemicals. Results highlight the importance of considering the well-known concentration-dependent effect in conjunction with other key factors.

Treatment Outcome Priorities of Older Adults with Newly Diagnosed Blood Cancers Elicited with Best-Worst Scaling

Background: A clear understanding of patients' preferred treatment outcomes is necessary to guide treatment decision-making. In this study, we sought to quantify the treatment outcome priorities of older adults (≥ 60 years old) newly diagnosed with hematologic malignancies and to describe individual patient's willingness to tolerate specific treatment-related benefit-risk tradeoffs. Methods: We developed a values elicitation measure using best-worst (BW) scaling and direct elicitation through a community-centered approach engaging diverse stakeholders. The measure includes 7 treatment priorities: Living longer, Maintaining day-to-day activities, Avoiding becoming more dependent on others, Avoiding hospitalizations/Increasing time at home, Avoiding long-term side effects, Avoiding short-term side effects, and Avoiding high financial costs. Patients complete repeated choice tasks choosing the most and least important treatment priority among repeated subsets using a balanced-incomplete block design. Direct elicitation was used to determine specific benefit-risk tradeoff preferences. Recruitment occurred at a public safety-net hospital following pathologic diagnosis. Patients completed the measure prior to the initial treatment decision and longitudinally each month. Data from the BW scaling measure were analyzed using the count method (best minus worst) and standardized. Results: In total, 48 patients consented (48% lymphoma, 40% leukemia/myelodysplastic syndrome, 12% other). Mean age was 74 years (range 60 - 95); 59% were male; 96% were white; 67% had a bachelor's degree or higher. Fifty-two percent (n=25) fully completed the BWS instrument at least once. The ranked importance of priorities for the entire cohort was 1) Maintaining day-to-day activities (standardized best minus worst, 23.8), 2) Living longer (12.4), 3) Avoiding becoming more dependent on others (7.9), 4) Avoiding hospitalizations/Increasing time at home (2.2), 5) Avoiding long-term side effects (-5.2), 6) Avoiding short-term side effects (-19.5), and 7) Avoiding high financial costs (-21.5). The most important outcomes (including ties) for individual patients were Maintaining day-to-day activities (40% of patients), Living longer (40%), and Avoiding becoming dependent on others (20%), while the least important outcomes were Avoiding high financial costs (52%), Avoiding short term side-effects (32%), and Living longer (20%). Thirteen (52%) patients completed subsequent BWS surveys; 69% changed their most important outcome at least once. Direct elicitation demonstrated that patients were willing to accept additional hospital stays of 1 week (88%), 1 month (58%), and 3 months (25%) in exchange for an additional 6 months of life. Only 25% of patients indicated willingness to require a full-time caregiver in exchange for an additional 2 years of life, whereas patients were more willing to accept a part-time caregiver in exchange for an additional 1 month (38%) or 6 months (79%) of life. Some patients were unwilling to accept an additional 6 months of life if it meant requiring assistance dressing (33%) or bathing (54%). In exchange for an additional 6 months of life, patients were willing to spend $250 (83%), $500 (58%), or $1000 (42%) per month. Conclusions: Older adults with newly diagnosed blood cancers differed when prioritizing treatment outcomes. Maintaining function was highly valued and was frequently more important than prolonging survival. Some patients felt prolonging survival was least important. Many patients changed their treatment priorities over time. These results highlight the need to elicit treatment outcome priorities at the time of each significant treatment decision for older adults. Further, they suggest that endpoints other than overall survival should be considered for clinical trials in this population as prolonging survival may not be prioritized by most patients. This study also demonstrated that a combination of BW scaling and direct elicitation was able to quantify patients' treatment outcome priorities and benefit-risk tradeoff preferences, highlighting the potential for the development of similar values elicitation measures to be used to inform specific treatment decisions in various clinical contexts.

Optimal breast cancer risk reduction policies tailored to personal risk level.

Depending on personal and hereditary factors, each woman has a different risk of developing breast cancer, one of the leading causes of death for women. For women with a high-risk of breast cancer, their risk can be reduced by two main therapeutic approaches: 1) preventive treatments such as hormonal therapies (i.e., tamoxifen, raloxifene, exemestane); or 2) a risk reduction surgery (i.e., mastectomy). Existing national clinical guidelines either fail to incorporate or have limited use of the personal risk of developing breast cancer in their proposed risk reduction strategies. As a result, they do not provide enough resolution on the benefit-risk trade-off of an intervention policy as personal risk changes. In addressing this problem, we develop a discrete-time, finite-horizon Markov decision process (MDP) model with the objective of maximizing the patient's total expected quality-adjusted life years. We find several useful insights some of which contradict the existing national breast cancer risk reduction recommendations. For example, we find that mastectomy is the optimal choice for the border-line high-risk women who are between ages 22 and 38. Additionally, in contrast to the National Comprehensive Cancer Network recommendations, we find that exemestane is a plausible, in fact, the best, option for high-risk postmenopausal women.

Apixaban Dosing Patterns Versus Warfarin in Patients With Nonvalvular Atrial Fibrillation Receiving Dialysis: A Retrospective Cohort Study

Comparison of clinical outcomes across anticoagulation regimens using different apixaban dosing or warfarin is not well-defined in patients with nonvalvular atrial fibrillation (AF) who are receiving dialysis. This study compared these outcomes in a US national cohort of patients with kidney failure receiving maintenance dialysis. Retrospective cohort study. Patients receiving dialysis represented in the US Renal Data System database 2013-2018 who had AF and were treated with apixaban or warfarin. First prescribed treatment with apixaban dosed according to the label, apixaban dosed below the label, or warfarin. Ischemic stroke/systemic embolism, major bleeding, and all-cause mortality. Cox proportional hazards models with inverse probability of treatment weighting. Analyses simulating an intention-to-treat (ITT) approach as well as those incorporating censoring at drug switch or discontinuation (CAS) were also implemented. Inverse probability of censoring weighting was used to account for possible informative censoring. Among 17,156 individuals, there was no difference in risk of stroke/systemic embolism among the label-concordant apixaban, below-label apixaban, and warfarin treatment groups. Both label-concordant (HR, 0.67 [95% CI, 0.55-0.81]) and below-label (HR, 0.68 [95% CI, 0.55-0.84]) apixaban dosing were associated with a lower risk of major bleeding compared with warfarin in ITT analyses. Compared with label-concordant apixaban, below-label apixaban was not associated with a lower bleeding risk (HR, 1.02 [95% CI, 0.78-1.34]). In the ITT analysis of mortality, label-concordant apixaban dosing was associated with a lower risk versus warfarin (HR, 0.85 [95% CI, 0.78-0.92]) while there was no significant difference in mortality between below-label dosing of apixaban and warfarin (HR, 0.97 [95% CI, 0.89-1.05]). Overall, results were similar for the CAS analyses. Study limited to US Medicare beneficiaries; reliance on administrative claims to ascertain outcomes of AF, stroke, and bleeding; likely residual confounding. Among patients with nonvalvular AF undergoing dialysis, warfarin is associated with an increased risk of bleeding compared with apixaban. The risk of bleeding with below-label apixaban was not detectably less than with label-concordant dosing. Label-concordant apixaban dosing is associated with a mortality benefit compared to warfarin. Label-concordant dosing, rather than reduced-label dosing, may offer the most favorable benefit-risk trade-off for dialysis patients with nonvalvular AF.

The Case for a Bayesian Approach to Benefit-Risk Assessment:: Overview and Future Directions.

The benefit-risk assessment of a new medicinal product or intervention is one of the most complex tasks that sponsors, regulators, payers, physicians, and patients face. Therefore, communicating the trade-off of benefits and risks in a clear and transparent manner, using all available evidence, is critical to ensure that the best decisions are made. Several quantitative methods have been proposed in recent years that try to provide insight into this challenging problem. Bayesian inference, with its coherent approach for integrating different sources of information and uncertainty, along with its links to optimal decision theory, provides a natural framework to perform quantitative assessments of the benefit-risk trade-off. This paper describes the current state of the art in Bayesian methodologies for quantitative benefit-risk assessment, and how these may be leveraged throughout the life cycle of a medicinal product to support and augment clinical judgment and qualitative benefit-risk assessments. Gaps and potential new directions that extend the current approaches are also identified.

Be Careful What You Ask For: Effects of Benefit Descriptions on Diabetes Patients' Benefit-Risk Tradeoff Preferences.

As more studies report on patient preferences for diabetes treatment, identifying diabetes outcomes other than glycated hemoglobin (HbA1c) to describe effectiveness is warranted to understand patient-relevant, benefit-risk tradeoffs. The aim of the study was to evaluate how preferences differ when effectiveness (glycemic control) is presented as long-term sequela (LTS) risk mitigation rather than an asymptomatic technical marker (HbA1c). People with type 2 diabetes and using insulin (n = 3160) were randomly assigned to four self-administered, discrete-choice experiments that differed by their presentation of effectiveness. Epidemiologic reviews were conducted to ensure a close approximation of LTS risk relative to HbA1c levels. The relative importance of treatment benefit-risk characteristics and maximum acceptable risk tradeoffs was estimated using an error-component logit model. Log-likelihood ratio tests were used to compare parameter vectors. In total, 1031 people responded to the survey. Significantly more severe hypoglycemic events were accepted for a health improvement in terms of LTS mitigation versus HbA1c improvement (0.7 events per year; 95% confidence interval [CI]: 0.4-1.0 vs. 0.2 events per year 95% CI: -0.02 to 0.5) and avoidance of treatment-related heart attack risk (1.4 severe hypoglycemic events per year; 95% CI: 0.8-1.9 vs. 1 event per year; 95% CI: 0.6-1.3). This finding is supported by a log-likelihood test that rejected at the 0.05 level that respondent preference structures are similar across the different experimental arms of the discrete-choice experiment. We found evidence that benefit descriptions influence elicited preferences for the benefit-risk characteristics of injectable diabetes treatment. These findings argue for using carefully defined effectiveness measures to accurately take account of the patient perspective in benefit-risk assessments.

Benefit-risk tradeoff preferences for chronic hand eczema treatments

Hand eczema affects approximately 16% of the US population. The long-term prognosis is poor, and 5–7% experience severe chronic hand eczema (sCHE) that interferes with daily activities. Treatments for CHE may be ineffective or associated with adverse events (AEs) that may dissuade patients from pursuing or continuing treatment. For quantification of patient experiences and benefit-risk preferences for outcomes associated with CHE treatments, a web-based discrete choice experiment survey was administered to patients in the United States with a self-reported physician diagnosis of CHE and severe symptoms not resolved with topical agents. Respondents answered a series of treatment choice questions, each requiring evaluation of a pair of hypothetical profiles of medications for sCHE defined by efficacy and risk of several AEs. Improvement in CHE clearing of 25–50% was rated from 1.5 to 3.1 times as important as eliminating a 5% risk of permanent bone problems. The mean maximum acceptable risk of permanent vision problems in exchange for an improvement in CHE clearing of 25–50% ranged from 3.4% to 4.8%. This study demonstrated that patients with CHE rated efficacy improvements associated with treatment of sCHE as more important than eliminating the risks of specific AEs.

Benefit-Risk of Ponatinib Vs. Bosutinib in Chronic Phase Chronic Myeloid Leukemia (CP-CML) Patients Who Failed Two Prior Tyrosine Kinase Inhibitors (TKIs): An Indirect Comparison

INTRODUCTIONPrior to the introduction of bosutinib and ponatinib, CP-CML patients who had failed 2 prior lines of TKI had limited treatment options with generally poor treatment response and outcomes. These newer TKIs are important additions to the treatment armamentarium, but the optimal choice of 3rd-line (3L) treatment has not been established. Clinical trials in patients who have failed 2 previous lines of TKI suggest ponatinib is more efficacious than bosutinib, but with a less favorable side-effect profile, requiring a potential benefit-risk tradeoff in treatment choice. Comparison of overall benefit-risk from available clinical trial data is challenging due to single- arm designs, low overall mortality, disparate impact of characteristic side-effects, and the likely crossover/sequential use of alternative TKIs among patients discontinuing therapy. We therefore examined efficacy outcomes previously validated as predictors of long-term survival, as well as treatment duration and reason for study drug discontinuation, as surrogates for overall benefit-risk in 3L CP-CML patients treated with ponatinib vs. bosutinib. METHODSUsing clinical trial data for 3L CP-CML from Khoury 2012 for bosutinib and PACE (unpublished) for ponatinib, we examined efficacy outcomes including major (MCyR) and complete (CCyR) cytogenetic response, and major molecular response (MMR), durability of response, duration on therapy and reasons for discontinuation among patients treated with ponatinib vs. bosutinib after failing 2 prior TKIs. Outcomes were evaluated at similar follow-up time points: median 28.5 (range 0.3-56.2) months bosutinib; median 30.5 (0.2-39.8) months ponatinib. Efficacy outcomes were defined such that patients were required to demonstrate improvement relative to baseline to be counted as responders. Investigator-reported primary reason for discontinuation was examined and considered caused by treatment failure if due to death, disease progression or unsatisfactory response. RESULTSTreatment response was higher for 3L CP-CML patients treated with ponatinib (N=98) than with bosutinib (N=118) across all measures. MCyR was achieved by 67% of ponatinib vs. 32% of bosutinib patients, CCyR by 56% of ponatinib vs. 24% of bosutinib patients, and MMR by 42% vs. 15%. Patients who received ponatinib experienced more durable responses with 93% of the ponatinib patients who achieved MCyR estimated to retain response after 2 years vs. 59% of the bosutinib patients who achieved this response level. After approximately 2.5 years of follow up, less than one-third (29%) of bosutinib patients remained on study drug vs. the majority (57%) of ponatinib patients (Figure). The median treatment duration was substantially shorter for bosutinib vs. ponatinib, with patients remaining on ponatinib therapy more than 3.5 times as long as on bosutinib (Figure). The majority of 3L bosutinib patients that discontinued did so due to treatment failure (58.3% of the patients who discontinued), while less than one-quarter (23.8%) of ponatinib patients who discontinued did so due to failure. The impact of AEs on discontinuation was similar: about 1 in 5 patients on both therapies discontinued due to AEs. CONCLUSIONSOur indirect comparison using a variety of surrogate measures provides strong evidence of superior efficacy and durability of response with ponatinib vs. bosutinib in 3L CP-CML patients; the higher proportion of ponatinib patients continuing on therapy and the longer duration of therapy also suggest patients experience better overall response and tolerability outcomes with ponatinib vs. bosutinib. Based on the surrogate measures of patient benefit- risk examined in this analysis, ponatinib appears to provide a net overall benefit vs. bosutinib in 3L CP-CML patients. [Display omitted] DisclosuresLevy:ARIAD Pharmaceuticals, Inc.: Consultancy, This ASH abstract publication value, advisory board speaking engagement, advisory board participation Other. McGarry:ARIAD Pharmaceuticals, Inc.: Employment, Equity Ownership. Huang:ARIAD Pharmaceuticals, Inc.: Employment, Equity Ownership. Lustgarten:ARIAD Pharmaceuticals Inc: Employment, Equity Ownership. Nieset:ARIAD Pharmaceuticals, Inc.: Employment, Equity Ownership. Haluska:ARIAD Pharmaceuticals, Inc.: Employment, Equity Ownership.

Real-World Assessment of Clinical Outcomes in Lower-Risk Myelofibrosis Patients Receiving Treatment with Ruxolitinib

Introduction: Published trial data shows that ruxolitinib improves both splenomegaly-related and nonsplenomegaly-related constitutional symptoms in patients with intermediate-2 and high risk myelofibrosis (MF). However, few trial-based assessments of ruxolitinib in lower-risk MF patients have been conducted and no studies to date have made such assessments in a real-world population. In this study, we assessed changes in spleen size and constitutional symptoms during ruxolitinib treatment for lower-risk MF patients in real-world clinical settings.Methods: This was a retrospective, observational review of anonymized medical record data collected in January 2014 by 49 hematologists and oncologists in the United States. Patient inclusion criteria were: (1) diagnosed with lower-risk MF (International Prognostic Scoring System score of 0 or 1); (2) first treated with ruxolitinib ≥3 months before the medical record abstraction date; (3) ≥18 years of age at ruxolitinib initiation; (4) complete medical history from MF diagnosis until the medical record abstraction date; and (5) never enrolled in an MF-related interventional trial. Minimum quotas of n=50 and n=25 were set for intermediate-1 and low-risk patients, respectively, with a predetermined maximum of 110 patients in the combined total. Spleen size and constitutional symptoms were retrospectively observed at MF diagnosis, at ruxolitinib initiation, and at best response while on ruxolitinib. Spleen size was captured via predefined categories of no splenomegaly (spleen not palpable), very mild or mild splenomegaly (<10 cm palpated), moderate splenomegaly (10-20 cm palpated), or severe splenomegaly (>20 cm palpated). Symptoms of interest included those captured in the MPN Symptom Assessment Form (MPN-SAF), which were categorized as mild, moderate, or severe based on medical notes recorded at each time point. For this abstract, we present findings on the 7 most commonly observed MPN-SAF symptoms in our sample. This study was exploratory and used only descriptive analyses.Results: A total of 108 patients were included in the study (25 low-risk and 83 intermediate-1 patients). Ruxolitinib start dates spanned January 2012 – November 2013. All low-risk patients were ≤65 years of age, and nearly 80% of intermediate-1 patients were ≤65 years of age. The majority of patients in both risk groups (60% and 69%, respectively) were male. A higher proportion of intermediate-1 patients were positive for JAK2 V617F mutation (72%) than low-risk patients (56%). Most patients (92% of low-risk, 77% of intermediate-1) were still receiving ruxolitinib treatment at the medical record abstraction date. Median observed ruxolitinib exposure time was approximately 8 months in both risk groups. In low-risk patients, the combined proportion of patients with moderate or severe splenomegaly (≥10 cm palpated spleen) decreased from 64% at MF diagnosis to 16% at best response during ruxolitinib treatment (Figure 1a). Similar findings were observed for intermediate-1 patients: the proportion with moderate or severe splenomegaly decreased from 53% at MF diagnosis to 10% at best response (Figure 1b). General fatigue was the most commonly observed constitutional symptom in both low-risk and intermediate-1 patients (Figures 2a and 2b). Shifts in symptom severity from more severe to less severe were observed in both low-risk and intermediate-1 patients. Among low-risk patients with fatigue, the proportion with moderate or severe fatigue decreased from 90% at MF diagnosis to 37% at best ruxolitinib response; in intermediate-1 patients, the decrease was from 76% at MF diagnosis to 42% at best response. For most other symptoms, similar improvements in severity distribution were observed.Conclusions: Both low-risk and intermediate-1 MF patients experienced a substantial decrease in spleen size from MF diagnosis through ruxolitinib treatment in real-world clinical settings. Furthermore, for most symptoms examined, there was a distinct improvement in the distribution of symptom severity at the time of best response during ruxolitinib treatment. These findings suggest that lower-risk MF patients may benefit clinically from ruxolitinib treatment. Further studies are needed to assess adverse effects and evaluate the benefit-risk tradeoff of ruxolitinib. [Display omitted] [Display omitted] DisclosuresDavis:Novartis Pharmaceuticals Corporation: Research Funding. Kaye:Novartis Pharmaceuticals Corporation: Research Funding. Cote:Novartis: Employment. Off Label Use: The study discusses use of ruxolitinib in patients with lower-risk (IPSS 0 or 1) myelofibrosis (MF) in real-world practice; currently ruxolitinib is only indicated in higher-risk MF (IPSS >1).. Gao:Novartis: Employment. Ronco:Novartis: Employment. Seifeldin:Novartis: Employment. Mendelson:Novartis: Employment.

A Decision‐Analysis Tool for Benefit–Risk Assessment of Nonprescription Drugs

A decision analysis tool is proposed for regulatory assessment of nonprescription drugs. The tool is based on evaluation of each of the drug's potential benefit and risk attributes identified using a value-tree framework. The decision tool is designed as two-factor, two-stage instrument. Each attribute is independently assessed based on both the frequency of occurrence and clinical impact of the attribute. Frequency and clinical impact are scored on a 0-3 scale where a 0 score means no occurrence or no clinical impact, and a 3 means high frequency of occurrence or high clinical impact. The tool is initially used early in drug development to facilitate communication amongst stakeholders and to identify important data gaps. After new data are generated during the development program the tool is used again across the same attributes to yield a final benefit-risk assessment. In both the early assessment and subsequent evaluation use of the Group-Delphi technique and a benefit-risk trade-off heuristic may yield more consistent and coherent outputs. The tool allows regulators to maintain flexibility with respect to how final decisions are made, yet allows specificity and transparency during the evaluation. Further modifications can be incorporated to address drug-specific requirements or regulatory preferences.

Can Modeling of Health Outcomes Facilitate Regulatory Decision Making?: The Benefit–Risk Tradeoff for Rosiglitazone in 1999 vs. 2007

Rosiglitazone was initially approved for type 2 diabetes monotherapy. We tested health-outcomes modeling as an aid to regulatory decision making by quantifying the incremental net benefit (INB) value of rosiglitazone (relative to a comparator), both at the time of first approval (1999) and at the FDA advisory committee review (2007). Using 1999 data, rosiglitazone was projected to provide an additional 0.639 years of life (0.373 quality-adjusted life years (QALYs)) relative to placebo but a loss of 0.312 years (0.173 QALYs) relative to glyburide, with uncertainty in reduction of hemoglobin A(1c) (HbA(1c)) level having the greatest impact on the benefit-risk profile. By 2007, rosiglitazone was projected to provide an additional 0.222 years (0.091 QALYs) vs. glyburide and 0.026 years vs. metformin (0.009 QALYs). Modeling suggested that the use of rosiglitazone as monotherapy was not initially warranted, given the uncertainty with regard to benefit. Despite similar net benefit (NB) as metformin shown in postmarketing data, residual cardiovascular (CV) concerns did not support the use of rosiglitazone as first-line therapy. We adapted a mathematical diabetes model to estimate NB and uncertainty of diabetes monotherapy.

Quantifying Women's Stated Benefit–Risk Trade-Off Preferences for IBS Treatment Outcomes

Background The Food and Drug Administration, currently, is exploring quantitative benefit–risk methods to support regulatory decision-making. A scientifically valid method for assessing patients' benefit–risk trade-off preferences is needed to compare risks and benefits in a common metric. Objectives The study aims to quantify the maximum acceptable risk (MAR) of treatment-related adverse events (AEs) that women with diarrhea-predominant irritable bowel syndrome (IBS) are willing to accept in exchange for symptom relief. Methods Research design: A stated-choice survey was used to elicit trade-off preferences among constructed treatment profiles, each defined by symptom severity and treatment-related AEs. Symptom attributes included frequency of abdominal pain and discomfort, frequency of diarrhea, and frequency of urgency. AE attributes included frequency of mild-to-moderate constipation and the risk of four possible serious AEs. Subjects: A Web-enabled survey was administered to 589 female US residents at least 18 years of age with a self-reported diagnosis of diarrhea-predominant IBS. Measures Preference weights and MAR were estimated using mixed-logit methods. Results Subjects were willing to accept higher risks of serious AEs in return for treatments offering better symptom control. For an improvement from the lowest to the highest of four benefit levels, subjects were willing to tolerate a 2.65% increase in impacted-bowel risk, but only a 1.34% increase in perforated-bowel risk. Conclusions Variation in MARs across AE types is consistent with the relative seriousness of the AEs. Stated-preference methods offer a scientifically valid approach to quantifying benefit–risk trade-off preferences that can be used to inform regulatory decision-making.

Quantifying Women's Stated Benefit–Risk Trade-Off Preferences for IBS Treatment Outcomes

Quantifying Women's Stated Benefit–Risk Trade-Off Preferences for IBS Treatment Outcomes

A Multiattribute Model for Evaluating the Benefit-Risk Profiles of Treatment Alternatives

The assessment of the benefits and risks associated with a medicine's use requires careful consideration of a wealth of information of varying format and quality, ranging from efficacy and safety data derived from randomized clinical trials to statistical results from health outcomes studies to spontaneously reported adverse events. Contrary to the expectations of patients, physicians, and regulators, the literature offers little guidance as to how to strike an appropriate balance between benefit and risk. Although a qualitative listing of a medicine's benefits and risks is useful, much could be gained from a systematic and transparent process to evaluate a medicine's pre- and postmarketing performance. The authors propose a representational model based on multicriteria decision analysis that can incorporate both evaluative judgments from different perspectives (e.g., physician, patient) and quantitative data to inform tradeoffs between multiple benefit and multiple risk elements in a logically consistent and transparent manner. The model is designed to highlight the relative merits and deficits of treatment alternatives in well-defined and specific contexts. It is intended to serve as a common platform to facilitate focused benefit-risk tradeoff discussions between scientists, physicians, regulatory authorities, and pharmaceutical companies, and to assist in the communication of clear and consistent messages regarding those tradeoffs.

Are adult patients more tolerant of treatment risks than parents of juvenile patients?

Understanding patient-specific differences in risk tolerance for new treatments that offer improved efficacy can assist in making difficult regulatory and clinical decisions for new treatments that offer both the potential for greater effectiveness in relieving disease symptoms, but also risks of disabling or fatal side effects. The aim of this study is to elicit benefit-risk trade-off preferences for hypothetical treatments with varying efficacy and risk levels using a stated-choice (SC) survey. We derive estimates of "maximum acceptable risk" (MAR) that can help decisionmakers identify welfare-enhancing alternatives. In the case of children, parent caregivers are responsible for treatment decisions and their risk tolerance may be quite different than adult patients' own tolerance for treatment-related risks. We estimated and compared the willingness of Crohn's disease (CD) patients and parents of juvenile CD patients to accept serious adverse event (SAE) risks in exchange for symptom relief. The analyzed data were from 345 patients over the age of 18 and 150 parents of children under the age of 18. The estimation results provide strong evidence that adult patients and parents of juvenile patients are willing to accept tradeoffs between treatment efficacy and risks of SAEs. Parents of juvenile CD patients are about as risk tolerant for their children as adult CD patients are for themselves for improved treatment efficacy. SC surveys provide a systematic method for eliciting preferences for benefit-risk tradeoffs. Understanding patients' own risk perceptions and their willingness to accept risks in return for treatment benefits can help inform risk management decision making.

Los efectos negativos de las intervenciones preventivas basadas en el individuo. Informe SESPAS 2008

Because preventive interventions are usually assumed to carry few risks, research on their negative effects is scarce, as revealed by a review of the Spanish literature. The studies retrieved analyze short-term effects (such as false-positive results of screening tests), but do not evaluate the long-term effects of postscreening interventions (for example: preventive drugs) or even less tangible negative effects (such as medicalization). Uncritical spread of preventive medicine is occurring, with continual proposals for new screening tests (for pre-diseases and risk factors) and new vaccines. The risk-benefit ratio of this spread is, at the very least, doubtful. The pharmaceutical industry plays a key role in this process but the role of other stakeholders (health professionals and health authorities, mass media and society) should also be reviewed. The present article highlights the role of the medical profession, since, without it, definition of new diseases and pre-diseases and the creation of guidelines on the use of new preventive interventions would not be possible. The medical profession has sufficient prestige to lead any change. Before any change occurs, however, scientific societies should conduct an internal debate on their current role in the adoption of new preventive interventions, their relationships with the pharmaceutical industry and their conflicts of interest. Some medical associations are already adopting a more critical approach to the evaluation of the benefit-risk trade-off of new interventions and are analyzing the impact of their own preventive recommendations on the medicalization of life. The adverse effects of the preventive measures implemented in health services should be continually assessed and procedures for the critical evaluation of the benefit-risk-cost trade-offs of new preventive interventions should be established before making decisions on their incorporation in the health services’ portfolio. Finally, in daily clinical practice, enhancing citizen participation in decisions and adopting the approach of quaternary prevention would be desirable.

Determining the Optimal Timing of Initiation for Venous Thromboembolism (VTE) Anticoagulant (AC) Prophylaxis (proph) after Orthopedic Surgery (OS).

AC proph after OS results in a decrease in the incidence of VTE with an associated increase in the risk of major bleeding (MB). Several AC agents and schedules are used; however the optimal timing of initiation has not been determined. It is likely that the proximity to the time of surgery might influence both the efficacy and safety of the AC thus altering their risk-benefit profile. Using a clinical cost-effectiveness approach we compared different AC and timings of VTE proph in patients undergoing OS. A meta-analysis of 55 randomized trials was done to estimate the risk (MB) and benefit (averted VTE) of proph in OS using placebo (plac) or different AC (ximelagatranxim, low molecular weight heparin-LMWH, unfractionated heparin-UFH, warfarin-warf and fondaparinux-fonda) and timings of initiation (defined as preoperative (preop) if the first dose of the AC was administered >2 hrs before surgery, perioperative (periop)if between 2 hrs before or up to 12 hrs after the surgery and postoperative (postop) if starting 12 hrs or more after surgery). Means and variances of the MB and VTE estimates were used to parameterize Monte Carlo simulations for a beta distribution using 1,000 replications. Incremental risk, benefit and risk-benefit ratios (compared to placebo) were calculated from the replications. All AC/timing combinations were compared across a range of benefit-risk tradeoff values (risk acceptance) by calculating the percentage of replications with the highest net clinical benefit (NCB; e.g. incremental benefit - incremental risk · tradeoff) for each AC/timing combination. A higher NCB represents a better risk-benefit profile. In addition all anticoagulants were pooled together according to the initial timing of administration and NCB was calculated using random re-sampling of the replications. Analyses were done separately for major VTE (mVTE; proximal deep vein thrombosis (DVT) + pulmonary embolism), and total VTE (tVTE; mVTE + distal DVT) and a sensitivity analysis was done after excluding xim. The reference tradeoff was estimated from the case-fatality rate-ratios of VTE to MB (mVTE/MB=0.39; tVTE/MB=0.10). At the reference tradeoff value, the AC/timing combination with the highest probability of having the best risk-benefit profile was postop xim analyzed by both mVTE and tVTE (99 and 58%, respectively). After excluding xim the AC/timing combination of choice was postop LMWH if analyzed by mVTE (60%) or preop LMWH if analyzed by tVTE (59%). When all AC were pooled those administered postop had the highest probability of having the best risk-benefit profile analyzed by mVTE (48%) and the choice was indifferent between preop (45%) and postop (40%) if analyzed by tVTE. After excluding xim from the pooled analysis the choice was indifferent between preop (40%) and postop (35%) if analyzed by mVTE and if analyzed by tVTE the choice was preop (55%) followed by postop (27%). Our results suggest that:1.postop administration of AC proph has the best risk-benefit profile;2.the results are influenced by the event defining benefit (mVTE or tVTE);3.in some analyses preop administration was best, and;4.periop administration always had the worst risk-benefit profile. We conclude that periop AC proph after OS should not be used.

Customer Loyalty to Whom? Managing the Benefits and Risks of Salesperson-Owned Loyalty

In a study of 362 buyer–salesperson dyads using triadic data (from buyer, salesperson, and sales manager), the authors examine both a customer's overall loyalty to the selling firm and the customer's loyalty vested specifically in his or her salesperson. They find that only salesperson-owned loyalty, a newly identified construct, directly affects the more tangible seller financial outcomes of sales growth and selling effectiveness, whereas both salesperson-owned loyalty and loyalty to the selling firm increase the customer's willingness to pay a price premium. A longitudinal study verifies that the positive effect of salesperson-owned loyalty on sales growth persists over time. However, because salesperson-owned loyalty simultaneously increases the seller's risk of losing business if the salesperson defects to a competitor, managers need to manage effectively the benefit–risk trade-off. Increasing relationship-enhancing activities and value received by the customer builds both salesperson-owned loyalty and loyalty to the selling firm. The loyalty-building impact of relationship-enhancing activities is moderated by selling-firm consistency and by the selling firm's and salesperson's loyalty-capturing strategies.