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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease 2 Review: Evaluating and Regulating Biomarker Use INTRODUCTION The context within which this study is set has developed from the contributions of various scientific fields, industries, and government bodies. From toxicology to cardiology, from the food industry to the drug industry, and from the Food and Drug Administration (FDA) to the federal courts, biomarkers and the scientific evidence needed to substantiate their use have been topics of discussion for several decades. Along with a brief review of biomarker evaluation methods and their uses, this chapter seeks to describe critical areas of background information so that readers from different fields can gain a more comprehensive understanding of the policy and regulatory issues with respect to biomarkers. Methods for evaluation of biomarkers and surrogate endpoints have been reviewed successfully and systematically in the recent past (Lassere, 2008; Shi and Sargent, 2009). This chapter will direct the readers toward appropriate reviews, and it will discuss the evolution of thinking at the FDA—focusing on the Center for Food Safety and Applied Nutrition (CFSAN), in particular—regarding surrogate endpoints. It will also discuss the evolution in thinking in academic and industry communities, to a lesser extent. The contents of this chapter are as follows: Use of biomarkers in areas as diverse as scientific research, medical practice, product development, and public health policy Use of biomarkers as surrogate endpoints Evaluation frameworks proposed from academia and industry
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease The broader context of biomarker and surrogate endpoint evaluation by the FDA, including the legal and regulatory basis for claims made on CFSAN-regulated products Examples are included on blood pressure as a surrogate endpoint, HIV/AIDS drug development, arrhythmia suppression interventions, exercise tolerance in congestive heart failure, and kidney toxicity biomarkers. SURVEY OF BIOMARKER USES Biomarkers have a wide array of uses in a variety of fields. These fields include medicine, oral health, mental health, nutrition, environmental health, toxicology, developmental biology, and basic scientific research. They are used to study the safety and efficacy of interventions, develop understanding of the mechanisms of disease, make good decisions in clinical care, and guide the policies that impact public health. Table 2-1 gives a list of several categories of biomarker use. For the uses in Table 2-1, any biomarker would need to be evaluated to ensure that data supporting the biomarker’s association with the disease or condition of interest and the analytical validation of the test are adequate for the proposed use. In situations, however, where biomarker data will not or is not yet anticipated to be submitted to the FDA for a regulatory purpose or used by professional societies or other groups for clinical practice guidelines or other decision-making processes impacting public health or the practice of medicine, this may be an informal process. Ideally, evaluations are already done by clinicians, product developers, government regulators, professional societies, and scientists; this report’s contribution is to propose a systematic process for biomarker evaluation. Use of Biomarkers and Surrogate Endpoints for Clinical Efficacy Studies and Formation of Clinical Practice Guidelines Surrogate endpoints were defined in Chapter 1 and can be found in several locations in Table 2-1. First, they have been used in approvals of products or claims for drugs, biologics, devices, foods, and supplements. This will be discussed further in several subsections of this chapter’s section on evolution of regulatory perspectives on surrogate endpoints and in Chapter 5. Second, they have been used in the formulation of clinical practice guidelines. As defined by an Institute of Medicine (IOM) committee in 1990, “practice guidelines are systematically developed statements to assist practitioner and patient decisions about appropriate health care
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease TABLE 2-1 Categories of Biomarker Use Use Description Discovery Identification of biochemical, image, or other biomarkers associated with a disease, condition, or behavior of interest; biomarkers identified may be screened for many potential uses, including as a target for intervention to prevent, treat, or mitigate a disease or condition Early product development Biomarkers used for target validation, compound screening, pharmacodynamic assays, safety assessments, and subject selection for clinical trials, and as endpoints in early clinical screening (i.e., phase I and II trials) Surrogate endpoints for claim and product approvals Biomarkers used for phase III clinical testing and biomarkers used to substantiate claims for product marketing Clinical endpoints Biomarkers used as endpoints for clinical trials that measure how a patient feels, functions, or survives; for example, measures of depression, blindness, and muscle weakness are biomarkers that may be used as clinical endpoints Clinical practice Biomarkers used by clinicians for uses such as risk stratification, disease prevention, screening, diagnosis, prognosis, therapeutic monitoring, and posttreatment surveillance Clinical practice guidelines Biomarkers used to make generalized recommendations for healthcare practitioners in the areas of risk stratification, disease prevention, treatment, behavior/lifestyle modifications, and more Comparative efficacy and safety Biomarkers used in clinical studies looking at the relative efficacy, safety, and cost effectiveness of any or all interventions used for a particular disease or condition, including changes in behavior, nutrition, or lifestyle; these studies are a component of comparative effectiveness research Public health practice Biomarkers used to track public health status and make recommendations for prevention, mitigation, and treatment of diseases and conditions at the population level
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease for specific clinical circumstances” (IOM, 1990). Clinical practice guidelines and the systematic reviews that inform them are the subjects for two current IOM studies;1 the reports are expected in 2011. A guideline regarding treatment of a particular disease may identify target levels for specific biomarkers. In order to arrive at a recommendation for a particular biomarker level, clinical trial and observational data must be evaluated. It is possible that more trials will measure a particular surrogate endpoint in addition to or rather than the clinical endpoint of interest. In these cases, it may be desirable to include data from trials that did not measure the clinical endpoints of interest in the systematic reviews. It is useful to mention that professional societies play an essential role in helping stakeholders understand the best ways to use biomarker-related information in clinical practice. One way in which professional societies assist in the understanding and use of biomarker data is through the promulgation of clinical practice guidelines. The committee recognized that clinical practice guidelines could use the committee’s proposed biomarker evaluation framework in reaching decisions. Other methods of rigorous, systematic review, including the Cochrane Collaboration, may also be valuable in assessing the evidence associated with clinical practice guidelines. One consideration that bodies involved in the work of determining the best clinical practice guideline may need to make is that of cost effectiveness. The committee viewed this topic as being beyond the statement of task for this study and well studied elsewhere, but the committee recognizes that comparisons of interventions looking at the number of quality-adjusted life-years gained through use of an intervention or relative to no intervention are useful. The IOM recently released a report, Initial National Priorities for Comparative Effectiveness Research (IOM, 2009c), which identified six characteristics of comparative effectiveness research, or CER (Box 2-1). In general, use of surrogate endpoints in CER would not fulfill the fourth characteristic of comparative effectiveness research, as identified in the report (IOM, 2009c). Quoted below is the report’s description of this characteristic of CER: CER measures outcomes—both benefits and harms—that are important to patients. The committee is using the term “effectiveness” in reference to the extent to which a specific intervention, procedure, regimen, or service does what it is intended to do when used under real-world circumstances. 1 Standards for Developing Trustworthy Clinical Practice Guidelines (http://www8.nationalacademies.org/cp/projectview.aspx?key=49125) and Standards for Systematic Reviews of Clinical Effectiveness Research (http://www8.nationalacademies.org/cp/projectview.aspx?key=49124).
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease BOX 2-1 Characteristics of Comparative Effectiveness Research (CER) CER has the objective of directly informing a specific clinical decision from the patient perspective or a health policy decision from the population perspective. CER compares at least two alternative interventions, each with the potential to be “best practice.” CER describes results at the population and subgroup levels. CER measures outcomes—both benefits and harms—that are important to patients. CER employs methods and data sources appropriate for the decision of interest. CER is conducted in settings that are similar to those in which the intervention will be used in practice. CER has the objective of directly informing a specific clinical decision from the patient perspective or a health policy decision from the population perspective. CER compares at least two alternative interventions, each with the potential to be “best practice.” CER describes results at the population and subgroup levels. CER measures outcomes—both benefits and harms—that are important to patients. CER employs methods and data sources appropriate for the decision of interest. CER is conducted in settings that are similar to those in which the intervention will be used in practice. SOURCE: IOM (2009c). This can be contrasted with “efficacy,” which is the extent to which an intervention produces a beneficial result under controlled conditions (Cochrane, 1971; Higgins and Green, 2008). This implies an important distinction between much clinical research and CER, in that CER places high value on external validity, or the ability to generalize results to real-world decision making. Harms or risks of unintended consequences are also outcomes of interest, because they influence the net benefits of an intervention. Including and giving weight to patient-reported outcomes is particularly important for CER studies in which patient ratings of effectiveness or adverse events may differ from clinical measures. Finally, resource utilization may be highly relevant to net benefits when comparing the full clinical course of interventions over time. Cost-effectiveness analysis is a useful tool of CER, allowing evaluation of the full range of
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease treatment outcomes in relationship to the difference in costs. Robust evidence of comparative clinical effectiveness is a building block necessary for resource allocation decisions. Moreover, just as clinical effects may vary in different settings, costs vary as well, so a given set of cost-effectiveness results is often not generalizable. (IOM, 2009c) Comparative effectiveness research is meant to fill gaps in evidence that prevent comparison of available treatments (IOM, 2009c) with a focus on outcome measurements that are tangible to the person rather than biomarkers or putative surrogate endpoints. Occasionally, it may be impractical for many of these studies to examine clinical endpoints; careful selection of surrogate endpoints after significant interaction with patient groups and expert investigators would be necessary. Finally, surrogate endpoints can be found in public health practice when there is a need to estimate the health of populations or short-term impacts of longer-term programs for prevention, treatment, or mitigation of infectious or chronic diseases when health outcomes important to patients cannot be measured. For example, reporting to stakeholders about interventions to decrease diseases and conditions of importance in the population, such as stroke or heart attack, may be done by measuring and reporting blood pressure as a surrogate for the desired improvement in health status, although measuring health outcomes important to patients such as stroke or quality of life would be preferable as guidance to public health interventions unless such measures were deemed impractical. Surrogate Endpoints: Successes The most widely discussed use of surrogate endpoints is in phase III clinical studies used to support applications for new drugs, biologics, and devices and to support claims on foods and supplements. In his presentation to the committee during its April public workshop, Dr. Robert Temple of the Center for Drug Evaluation and Research (CDER) at the FDA outlined the reasons why researchers and clinicians use surrogate endpoints (Temple, 2009). These reasons include when the clinical endpoint is rare or takes years to develop; when the surrogate endpoints seem to be obviously linked to the clinical endpoint of interest (e.g., tumor size in cancer or maintenance of regular heart rhythm in arrhythmia patients); and when other treatments exist, to alleviate the difficulties of conducting trials when a new intervention must be proven as non-inferior to existing treatments. In addition, although it may be possible to use a clinical endpoint in a population at high risk for the disease or condition, studying a population at relatively lower risk using the clinical endpoint may be too burdensome
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease since the number of subjects required would be very large. Dr. Temple noted that the idea of a surrogate endpoint is to enable faster, smaller, more efficient clinical trials that can address urgent needs and facilitate the advancement of medicine. Two notable successes of the use of surrogate endpoints are discussed in the next sections: blood pressure and HIV-1 RNA. The first example details the history of the evaluation of blood pressure as a surrogate endpoint. It may be surprising to readers that blood pressure as a surrogate endpoint for cardiovascular disease endpoints was hotly debated for decades before reaching its current status. Still, there is no broad agreement that blood pressure is a universal surrogate endpoint (Carter, 2002; Psaty et al., 1996). Even though these examples describe successful use of surrogate endpoints, important caveats are also described. Dr. Temple and others have noted surprises and mistakes in the selection and use of surrogate endpoints, and so several examples of these are discussed after the sections on blood pressure and HIV-1 RNA. Blood Pressure Blood pressure is often looked to as an exemplar surrogate endpoint for cardiovascular mortality and morbidity due to the levels and types of evidence that support its use. More than 75 antihypertensive agents in more than 9 therapeutic classes demonstrate the wide availability of agents to treat hypertension (Israili et al., 2007). Although new antihypertensive drugs are approved on the basis of blood pressure reductions, blood pressure’s history as a surrogate endpoint is unusual in that many drugs used to treat hypertension (thiazides, methyldopa, reserpine, hydralazine, guanethidine) were approved prior to the FDA’s effectiveness requirement or the availability of clinical trial data supporting the impact of blood pressure control on cardiovascular outcomes (Desai et al., 2006). The status of blood pressure as a surrogate endpoint for cardiovascular disease endpoints was debated for decades (Perry et al., 1978). Even as one of the most well-established surrogate endpoints, an effect on blood pressure may not fully capture the benefit—or risk—of an intervention. Although some issues are still outstanding, the benefits of blood pressure control are mostly well understood due to comprehensive epidemiologic and clinical trial evidence. Hypertension has been identified as the most common risk biomarker for cardiovascular morbidity and mortality, with a World Health Organization report suggesting that hypertension is the single most important preventable cause of premature death in developed countries (Ezzati et al., 2002). Data suggest that in the United States, hypertension is responsible for 35 percent of myocardial infarctions
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease and strokes, 49 percent of episodes of heart failure, and 24 percent of premature deaths (Wolff and Miller, 2007). Hypertension affects one in four U.S. adults, but the majority of those affected remain either untreated or undertreated in spite of the substantial health benefits gained from modest blood pressure reductions (Wang and Vasan, 2005). Epidemiological, clinical trial data Williams (2005) suggested that the blood pressure–cardiovascular outcomes relationship is substantiated by one of the strongest evidence bases in clinical medicine. Epidemiologic studies consistently demonstrate the relationship between blood pressure and cardiovascular mortality and morbidity, including one meta-analysis of nine studies that demonstrated an association between diastolic blood pressure and coronary heart disease and stroke in 420,000 subjects (MacMahon et al., 1990). Observational studies have also demonstrated the robustness of blood pressure’s relationship to heart disease in adults; despite different assessment parameters (systolic alone, diastolic alone, or systolic and diastolic), the relationship is maintained (Desai et al., 2006). This relationship has also been confirmed in diverse populations, including different genders, adult age groups, and race/ethnicities. In children, this relationship does not hold (Brady and Feld, 2009). Both placebo- and active-controlled clinical trials conducted in the past three to four decades have demonstrated that pharmacologic reductions in blood pressure reduce cardiovascular mortality and morbidity (Desai et al., 2006). While earlier trials compared hypertension agents against placebo, the growing evidence base supporting the benefit of hypertension therapy necessitated head-to-head trials comparing two or more agents, which reduced power of the studies and required much larger numbers of patients to see an effect (Williams, 2005). Many different therapeutic agents—including diuretics, beta blockers, angiotension converting enzyme (ACE) inhibitors, calcium channel blockers, and angiotensin receptor blockers—are approved to lower blood pressure. Effects of blood pressure-lowering drugs Impact on blood pressure may or may not capture an intervention’s entire risk–benefit balance. Different classes of agents, or even agents within a specific class, may have multiple effects, one of which is lowering blood pressure (NHLBI Working Group, 2005). For example, ACE inhibitors are known to have at least 10 pharmacologic effects (Borer, 2004). This notion has generated trials testing whether agents have beneficial effects that go beyond blood pressure lowering. ALLHAT (Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial) compared the efficacy of four different drug classes (a calcium channel blocker, an ACE inhibitor, an alpha adrenergic blocker, and a diuretic) for initial therapy of hypertension. Study results
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease demonstrated that three classes of drugs (calcium channel blocker, ACE inhibitor, and diuretic) could not be distinguished for the primary endpoint, coronary heart disease (CHD) mortality and non-fatal myocardial infarction, but the lower cost diuretics were superior in regard to secondary outcomes and should be the preferred first step therapy (ALLHAT Officers and Coordinators, 2002). The alpha adrenergic blocker arm of the trial was dropped because of the significantly higher incidence of combined cardiovascular events in the alpha adrenergic blocker arm compared to the diuretic, including a two-fold relative risk of congestive heart failure compared to the diuretic (ALLHAT Officers and Coordinators, 2000). Other conclusions have also been drawn from these large, prospective head-to-head comparison trials; some investigators suggest that it is the blood pressure reduction, rather than the specific drug used, that confers cardiovascular benefit (Williams, 2005). In an analysis of 147 randomized trials, investigators found that all classes of blood pressure-lowering drugs have similar effects in reducing coronary heart disease events and strokes for a given level of blood pressure reduction, with the exception of an extra protective effect of beta blockers administered shortly after myocardial infarction and minor protective effect of calcium channel blockers in stroke (Law and Morris, 2009). Although there is still some ambiguity about the use of differing blood pressure agents, the fact that pharmacologically distinct agents have directionally similar effects on cardiovascular outcomes has provided more support for the use of blood pressure as a surrogate endpoint for coronary heart disease and stroke. Regulatory use of blood pressure as a surrogate endpoint The consistent demonstration that diverse blood pressure-lowering agents confer cardiovascular benefits, as well as the substantial epidemiological data linking hypertension to cardiovascular events, provides the basis for the FDA’s use of blood pressure as a surrogate endpoint (Desai et al., 2006; Temple, 1999). However, clear guidance on the use of surrogate endpoints within the FDA is lacking because the Food, Drug, and Cosmetic Act does not specifically state which endpoints—or criteria—can be used for drug approval. Through case law, the FDA has the authority to deny approval of a drug on the basis of its effect on the surrogate endpoint if the surrogate endpoint’s clinical value is unknown.2 In 1992, FDA regulation provided a new method for drug approval on the basis of effects on a surrogate endpoint, called accelerated approval, for serious or life-threatening conditions without available therapy. The regulation stated that drugs could be approved on the basis of surrogate endpoint data if it “is reasonably 2 Warner-Lambert v. Heckler, 787 F.2d 147 (3rd Cir. 1986).
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease likely, based on epidemiologic, therapeutic, pathophysiologic, or other evidence, to predict clinical benefit”3 and required confirmatory clinical evidence. The regulation also referenced “well-established” surrogates on which drug approval had been based, but did not define well-established endpoints. Temple (1999) noted that “well-established” surrogates would need to be more than “reasonably likely” to predict benefit. Despite the lack of clarity in the regulations concerning surrogate endpoints, the FDA accepts surrogate endpoints for drug approval and as the basis for authorized health claims. However, different divisions and centers within the FDA accept different surrogate endpoints. For example, the Cardio-Renal Division within the CDER accepts blood pressure reduction as a surrogate endpoint for cardiovascular event reduction, but requires direct clinical benefit measurement for other endpoints, while the Metabolic-Endocrine Division also accepts LDL-C lowering as a surrogate endpoint for cardiovascular events (Borer, 2004). The Metabolic-Endocrine Division also accepts use of glycosylated hemoglobin level and blood glucose control as surrogate endpoints for diabetes control (Borer, 2004). Even so, the FDA has recognized the inadequacy of small six-month trials that address effects of type 2 diabetes mellitus treatments on HbA1c, and now the FDA requires large-scale randomized cardiovascular safety clinical endpoint trials be conducted pre- and post-approval. Within CFSAN, blood pressure is recognized as a surrogate endpoint for hypertension (FDA, 1999). Hypertension is considered a disease-related health condition. As discussed earlier, hypertension—high blood pressure—is recognized as a strong risk factor for cardiovascular disease. CFSAN has authorized a health claim for low-sodium foods based on the surrogate endpoint–disease-related condition relationship, stating either “diets low in sodium may reduce the risk of high blood pressure, a disease associated with many factors” or “development of hypertension or high blood pressure depends on many factors. [This product] can be part of a low sodium, low salt diet that might reduce the risk of hypertension or high blood pressure.”4 HIV Drug Development One of the motivations for the earliest efforts at surrogate endpoint evaluation arose from the acute need for effective therapeutics early in the HIV/AIDS epidemic. The early trials of anti-HIV therapies used progression to AIDS or death as the clinical outcome measures. These studies could be short in some settings, like those in which the effects of the 3 21 C.F.R. § 601 (2008). 4 21 C.F.R. § 101.74 (2009).
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease intervention were large and participants had advanced disease (Fischl et al., 1987; Hammer et al., 1997). Studies could also be short when they were large enough so that only a small percentage of patients who progress to advanced disease drove the principal finding (Volberding et al., 1994). However, the latter type of study could produce misleading results in that a small number of patients destined to progress quickly might benefit from an intervention, like AZT monotherapy, while an even larger number might experience no benefit and even positive harm following the conclusion of the study, because of factors like the development of resistance to the drug under study and others with similar mechanisms of action. Such concerns underscored the need for a more rapid means of evaluating the benefit of antiviral therapy that might reflect risk or benefit to a larger proportion of the study population more rapidly. Early in the AIDS epidemic, it was observed that clinical disease progression was associated with a decline of CD4+ T-lymphocytes (CD4 cells); in the 1990s, a virologic measure that both responded to therapy and predicted outcomes was developed (HIV-1 RNA). The earliest approval of a drug based on a biomarker—didanosine was approved in 1991—used CD4 cell count; however, the development of measurement of plasma HIV-1 RNA by polymerase chain reaction (PCR), which made a direct measurement of viral replication possible, rapidly became the standard endpoint in HIV clinical trials. In the mid-1990s, representatives from industry, drug regulatory agencies, and academia sought to formally evaluate CD4 cell count and HIV-1 RNA as surrogate endpoints for disease progression in clinical trials and in patient management (Hughes et al., 1998). To evaluate HIV-1 RNA and CD4 cell count as surrogate endpoints, the HIV Surrogate Marker Collaborative Group, a group involving statisticians and clinicians from pharmaceutical companies and government-funded cooperative clinical trials groups, was formed. The HIV Surrogate Marker Collaborative Group undertook a meta-analysis of clinical trials to evaluate treatment-mediated changes in HIV-1 RNA and CD4 cell count as surrogate endpoints (HIV Surrogate Marker Collaborative Group, 2000). The meta-analysis found that HIV-1 RNA and CD4 cell count have independent value as prognostic biomarkers. However, the meta-analysis also found that short-term changes in the values of these biomarkers were not adequate surrogate endpoints for determining the impact of an intervention on long-term clinical endpoints such as progression to AIDS and death (HIV Surrogate Marker Collaborative Group, 2000). Their analysis also showed that changes in HIV-1 RNA explained only about half of the benefit of treatment. However, these results mostly reflected the experience of patients on drug regimens that were not capable of suppressing most patients’ viral loads below levels of assay detection.
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Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease person chooses to eat a nutrient or other substance that has been shown in observational studies to be associated with a reduced risk of disease, while ignoring the fact that this research alone does not confirm a substance’s causal connection to a reduced risk of disease. Because these biases are well known, some may try to take advantage of them to mislead consumers. Cognitive biases of healthcare professionals in health-related decision making have been studied in the context of emergent (Pines, 2006), acute (Aberegg et al., 2005; Freshwater-Turner et al., 2007), and chronic healthcare settings (Gruppen et al., 1994; Lutfey and McKinlay, 2009; Redelmeier and Shafir, 1995; Roswarski and Murray, 2006), while cognitive biases of patients have been evaluated in regard to illnesses such as myocardial infarction (Khraim and Carey, 2009) and cancer (Han et al., 2006). Efforts by professional societies can help physicians, dietitians, and other healthcare practitioners be aware of information gaps and common cognitive biases when helping their patients or clients make decisions about their health care. With this knowledge, strategies can be developed and disseminated. In situations where the public and health professionals need to make decisions in the absence of complete, definitive evidence, decision makers need to be able to access balanced, non-misleading data, or they will be likely to make systematic errors in their thinking. REFERENCES Aberegg, S. K., E. F. Haponik, and P. B. Terry. 2005. Omission bias and decision making in pulmonary and critical care medicine. Chest 128(3):1497–1505. Advisory Committee to the Surgeon General. 1964. Report of the Advisory Committee to the Surgeon General. Washington, DC: U.S. Department of Health, Education, and Welfare. Afzal, A. K S. J. Jacobsen, D. W. Mahoney, J. A. Kors, M. M. Redfield, J. C. Burnett, and R. J. Rodeheffer. 2007. Prevalence and prognostic significance of heart failure stages: Application of the American College of Cardiology/American Heart Association heart failure staging criteria in the community. Circulation 115(12):1563–1570. Akl, E. A., N. Maroun, G. Guyatt, A. D. Oxman, P. Alonso-Coello, G. E. Vist, P. J. Devereaux, V. M. Montori, and H. J. Schunemann. 2007. Symbols were superior to numbers for presenting strength of recommendations to health care consumers: A randomized trial. Journal of Clinical Epidemiology 60(12):1298–1305. ALLHAT Officers and Coordinators for the ALLHAT Collaborative Research Group. 2000. Major cardiovascular events in hypertensive patients randomized to doxazosin vs chlorthalidone. Journal of the American Medical Association 283(15):1967–1975. ALLHAT Officers and Coordinators for the ALLHAT Collaborative Research Group. 2002. Major outcomes in high-risk hypertensive patients randomized to angiotensin-converting enzyme inhibitor or calcium channel blocker vs. diuretic: The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). Journal of the American Medical Association 288(23):2981–2997. Alonso, A., G. Molenberghs, H. Geys, M. Buyse, and T. Vangeneugden. 2006. A unifying approach for surrogate marker validation based on Prentice’s criteria. Statistics in Medicine 25(2):205–221.
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