بیان سود-خطر ترجیحات تجارت کردن کمیت زنان برای IBS درمان نتایج
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|23738||2010||6 صفحه PDF||سفارش دهید||4000 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Value in Health, Volume 13, Issue 4, June–July 2010, Pages 418–423
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.
Several recent and well-publicized events involving withdrawals of drugs from the US market have highlighted the problem of balancing benefits and risks . In all these cases, interventions offering potentially significant therapeutic benefits were found to carry increased risks of serious and, possibly, life-threatening adverse events (AEs). Decisions to halt the development or marketing of such therapies clearly require balancing benefits and risks. Despite the importance of establishing consistent and principled criteria for determining when benefits outweigh risks, experts have provided surprisingly little guidance to help decision-makers evaluate such trade-offs. A review of past examples of product withdrawals and riskmanagement decisions in different countries reported that decisions, often, are inconsistent and are based on very limited scientific evidence beyond the original clinical trial data relating to safety and efficacy . In addition, the recent Institute of Medicine report, The Future of Drug Safety, a study requested by the US Food and Drug Administration (FDA) to address recognized shortcomings of the US drug-safety system, noted that “in both the preapproval and the postmarketing setting, the riskbenefit analysis that currently goes into regulatory decisions appears to be ad hoc, informal, and qualitative” . The FDA Amendments Act of 2007 called on the agency to collaborate with public and private entities to improve the quality of benefit– risk analysis (H.R. 3580 [Public Law 110-85] §904). Regulatory agencies do not require quantifying or even formal consideration of the values of patients, physicians, or other stakeholders in risk evaluations. The values and risk tolerance of patients with a particular condition may be presented to advisory panels and policymakers either individually or through advocacy organizations; however, there is no transparent or consistent mechanism currently in place for quantifying systematically the values and risk tolerance of these ultimate stakeholders. The case of alosetron illustrates the need for quantitative, preference-based, benefit–risk analysis. Alosetron was approved for marketing by the FDA in February 2000. The approved indication was for diarrhea-predominant irritable bowel syndrome (IBS) in women only. Although clinical trials demonstrated that alosetron provided relief of abdominal pain and discomfort, improvement in urgency, and decreased frequency of diarrhea , safety signals indicated the possibility of serious gastrointestinal AEs. The most serious risk of concern associated with alosetron was the possibility that women with IBS taking the drug would develop a perforated bowel requiring surgery. As a result, alosetron was withdrawn from the market 9 months after launch. In June 2002, in response to pressure from patient organizations and reanalysis of data, the FDA reapproved the drug for restricted use in a more targeted indication under a risk-management program. Understanding the value that women with IBS place on treatment outcomes and their willingness to accept risks in return for treatment benefits can help inform future regulatory and risk-management decision-making. In this study, we employed well-established stated-choice (SC) methods (also known as choice-format conjoint analysis or discrete-choice experiments) to quantify the maximum acceptable risk (MAR) of treatmentrelated AEs that women with diarrhea-predominant IBS are willing to accept in exchange for symptom relief. In a related study published in this journal, these estimates were used to construct preference weights, which were used in an eventsimulation model, to estimate the incremental net benefits of alosetron .
نتیجه گیری انگلیسی
As expected, women’s choices indicated a systematic preference for treatments that provide larger reductions in symptom frequency. In many instances, preferences for symptom relief outweighed concerns about AE risks. For example, the estimated preference weight for no abdominal pain and discomfort is greater than the estimated preference weight for no risk of serious AEs, indicating that relief of abdominal pain and discomfort was more important to these women than is eliminating the AE risks. Variation in the MAR measure of risk tolerance was consistent with the relative seriousness of the AEs. For example, for a treatment offering moderate symptom improvement relative to severe symptoms, MAR for impacted bowel was 1.53%, whereas MAR for perforated bowel was only 0.86%. The estimated MARs for clinically meaningful symptom improvements are substantially above their estimated rates of occurrence across each of the serious AEs of interest . Most importantly, estimating preference weights for treatment outcomes and risks, and quantifying the relative importance of each attribute offer a solution to the problem in benefit–risk analysis that risks and benefits are measured in noncomparable units. In a companion article, these preference weights are used in the first incremental net benefit analysis to use such patient data to compare treatment benefits and risks . One inherent limitation of this methodology is that SC questions ask subjects to evaluate hypothetical treatments. Thus, differences can arise between stated and actual choices. In the present study, potential hypothetical bias is minimized by offering alternates that mimic real-world trade-offs as closely as possible. Subjects enrolled through the Ipsos Observer were not screened to confirm their reported IBS diagnosis. We consider it is unlikely that people who do not have IBS completed the survey because no personal gain was associated with participation in the survey, other than a chance to win one of the five $100 cash incentives. In addition, participation required a commitment of approximately 30 minutes to complete the survey, and the SC trade-off tasks are mentally taxing exercises that are unlikely to attract a casual respondent. Health status is based on patients’ own report of a physician diagnosis of IBS. We have no independent verification of that diagnosis. Nevertheless, we followed up the self-report with questions on type and severity of symptoms—abdominal pain and discomfort, feeling of urgency or soiling clothes, and inability to lead a normal home or work life because of the need to be near a bathroom. About 80% of the subjects indicated one or more of these symptoms were “frequent,” and 75% judged the severity to be moderate or severe. As indicated, this study provided weights for a separate modeling study to estimate incremental net benefits. We thus were constrained to obtain weights that matched the end points in clinical-trial data. Rates for each outcome are reported, and thus modeled, independently. For example, subjects sometimes evaluated outcome profiles that included both IBS-related diarrhea and medication-induced constipation in the same week. The effect of a given diarrhea frequency might be different, depending on the combination of diarrhea days and constipation days in that week. This interaction effect is not reflected in our importance estimates for these end points. Conventional health-state utility weights widely used in cost-effectiveness analyses also treat outcomes as independent and are subject to the same limitation. One could argue that models and importance weights should account for interactions among outcomes, but they do not because the data on which models are based generally do not provide the necessary information to model such interactions. An important topic for future research would be to relax the independence requirement in both the model and the preference weights to evaluate the significance of this requirement. Patients’ perspectives on balancing benefits and risks may be useful in informing both treatment and regulatory decisions. Because risks, often, are inseparable from efficacy, one cannot easily define what level of risk is intolerable without reference to the benefits associated with increased risk. SC studies such as this one may help decision-makers understand the levels of risks that patients are willing to accept in return for therapeutic benefits. Quantitative estimates of preferences for combinations of risks and benefits developed using rigorous and theoretically sound techniques, such as those used in this study, may assist regulatory authorities in evaluating new treatments, making the rationale for decisions more transparent and helping physicians and patients make better-informed choices among treatments. Source of financial support: This study was funded by GlaxoSmithKline. The views expressed herein do not necessarily reflect those of the sponsor. As the supervisor for the study, F. Reed Johnson had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.