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

Physicians’ Preferences for Bone Metastases Drug Therapy in the United States

AbstractObjectiveSeveral characteristics of bone-targeted agents are considered when making treatment decisions. This study evaluated physicians’ therapy preferences for preventing skeletal-related events (SREs) in patients with bone metastases secondary to solid tumors.MethodsA Web-enabled, discrete-choice experiment online survey was conducted among physicians who treated patients with bone metastases and solid tumors in the United States. Respondents chose between pairs of hypothetical medications defined by combinations of six attributes at varying levels for two hypothetical patients. Preference weights for attribute levels were estimated using a random-parameters logit model.ResultsIn total, 200 physicians completed the survey. Their mean age was 52 years, 57% were in practice for more than 15 years, 37% were oncologists, and 65% treated 10 or fewer patients with bone metastases weekly. Out-of-pocket cost to patients was the most important attribute overall. Among clinical outcomes, time to first SRE and risk of renal impairment were the most important attributes. Statistically significant preferences were observed for all attribute levels for time to first SRE, risk of renal impairment, and mode of administration. Predicted choice probability analysis showed that physicians preferred a hypothetical medication with attributes similar to those of denosumab over one with attributes similar to those of zoledronic acid.ConclusionsPhysicians indicated that clinical attributes are important when considering bone-targeting therapy for bone metastases, but consistent with the current health care landscape, patient out-of-pocket cost was the most important. With health care costs being increasingly shifted to patients, physicians require accurate information about co-pays and assistance programs to avoid patients receiving less costly, yet potentially inferior, treatment

Using the Incremental Net Benefit Framework for Quantitative Benefit–Risk Analysis in Regulatory Decision-Making—A Case Study of Alosetron in Irritable Bowel Syndrome

AbstractObjectiveThere is consensus that a more transparent, explicit, and rigorous approach to benefit–risk evaluation is required. The objective of this study is to evaluate the incremental net benefit (INB) framework for undertaking quantitative benefit–risk assessment by performing a quantitative benefit–risk analysis of alosetron for the treatment of irritable bowel syndrome from the patients’ perspective.MethodsA discrete event simulation model was developed to determine the INB of alosetron relative to placebo, calculated as “relative value-adjusted life-years (RVALYs).”ResultsIn the base case analysis, alosetron resulted in a mean INB of 34.1 RVALYs per 1000 patients treated relative to placebo over 52 weeks of treatment. Incorporating parameter uncertainty into the model, probabilistic sensitivity analysis revealed a mean INB of 30.4 (95% confidence interval 15.9–45.4) RVALYs per 1000 patients treated relative to placebo over 52 weeks of treatment. Overall, there was >99% chance that both the incremental benefit and incremental risk associated with alosetron are greater than placebo. As hypothesized, the INB of alosetron was greatest in patients with the worst quality of life experienced at baseline. The mean INB associated with alosetron in patients with mild, moderate, and severe symptoms at baseline was 17.97 (−0.55 to 36.23), 29.98 (17.05–43.37), and 35.98 (23.49–48.77) RVALYs per 1000 patients treated, respectively.ConclusionsThis study demonstrates the potential utility of applying the INB framework to real-life decision-making, and the ability to use simulation modeling incorporating outcomes data from different sources as a benefit–risk decision aid

Health state utilities associated with attributes of treatments for hepatitis C

BACKGROUND: Cost-utility analyses are frequently conducted to compare treatments for hepatitis C, which are often associated with complex regimens and serious adverse events. Thus, the purpose of this study was to estimate the utility associated with treatment administration and adverse events of hepatitis C treatments. DESIGN: Health states were drafted based on literature review and clinician interviews. General population participants in the UK valued the health states in time trade-off (TTO) interviews with 10- and 1-year time horizons. The 14 health states described hepatitis C with variations in treatment regimen and adverse events. RESULTS: A total of 182 participants completed interviews (50 % female; mean age = 39.3 years). Utilities for health states describing treatment regimens without injections ranged from 0.80 (1 tablet) to 0.79 (7 tablets). Utilities for health states describing oral plus injectable regimens were 0.77 (7 tablets), 0.75 (12 tablets), and 0.71 (18 tablets). Addition of a weekly injection had a disutility of −0.02. A requirement to take medication with fatty food had a disutility of −0.04. Adverse events were associated with substantial disutilities: mild anemia, −0.12; severe anemia, −0.32; flu-like symptoms, −0.21; mild rash, −0.13; severe rash, −0.48; depression, −0.47. One-year TTO scores were similar to these 10-year values. CONCLUSIONS: Adverse events and greater treatment regimen complexity were associated with lower utility scores, suggesting a perceived decrease in quality of life beyond the impact of hepatitis C. The resulting utilities may be used in models estimating and comparing the value of treatments for hepatitis C. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10198-014-0649-6) contains supplementary material, which is available to authorized users

Spatial Boundaries and Choice Set Definition in a Random Utility Model of Recreation Demand

We are concerned with the definition of choice set used in Random Utility Models of recreation demand. In particular, we are concerned with the spatial boundaries used to define choice sets. In this paper, using a model of day-trip fishing in Maine, we examine the sensitivity of parameter and welfare estimates to changes in the spatial boundary. We find that there exists some threshold distance beyond which adding more sites to the choice set has negligible effects on the estimation results.