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3
The Biomarker Evaluation Process
The previous chapter’s detailed exploration of biomarker evaluation efforts indicates a need for a unified, transparent process for the evaluation and adoption of biomarkers. Although the principal purpose for evaluation is to ensure that a biomarker is scientifically and clinically meaningful for specified purposes (Palou et al., 2009; Wagner, 2008; Wagner et al., 2007; Williams et al., 2006), evaluation also allows for informed decisions about which biomarkers to pursue and data to gather. This chapter begins to present the committee’s recommendations on the best ways to proceed (see Box 3-1 for the recommendations discussed in this chapter).
The committee’s biomarker evaluation framework was informed by the previously developed qualification frameworks discussed in Chapter 2; the committee determined there are three necessary components to biomarker evaluation: (1) analytical validation of relevant biomarker tests; (2) qualification, a description of the evidence relating to the biomarker in question—as measured using validated tests—to the intervention and disease outcome; and (3) utilization, the applicability of results from the analytical validation and the description of the evidence to the proposed use of the biomarker given the evidence assessment and proposed purpose and context of use. Thus, the committee’s framework has three distinct yet interrelated steps; they are not necessarily separated in time (i.e., some of the steps may occur concurrently) and conclusions in one step may require revisions or additional work in other steps (see Figure 3-1). Previous evaluation frameworks have not explicitly incorporated a process for reevaluating the three steps of the biomarker assessments based on new
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BOX 3-1
Recommendations 1–4
Recommendation 1:
The biomarker evaluation process should consist of the following three steps:
1a.
Analytical validation: analyses of available evidence on the analytical performance of an assay;
1b.
Qualification: assessment of available evidence on associations between the biomarker and disease states, including data showing effects of interventions on both the biomarker and clinical outcomes; and
1c.
Utilization: contextual analysis based on the specific use proposed and the applicability of available evidence to this use. This includes a determination of whether the validation and qualification conducted provide sufficient support for the use proposed.
Recommendation 2:
2a.
For biomarkers with regulatory impact, the Food and Drug Administration (FDA) should convene expert panels to evaluate biomarkers and biomarker tests.
2b.
Initial evaluation of analytical validation and qualification should be conducted separately from a particular context of use.
2c.
The expert panels should reevaluate analytical validation, qualification, and utilization on a continual and a case-by-case basis.
Recommendation 3:
The FDA should use the same degree of scientific rigor for evaluation of biomarkers across regulatory areas, whether they are proposed for use in the arenas of drugs, medical devices, biologics, or foods and dietary supplements. Congress may need to strengthen FDA authority to accomplish this goal.
Recommendation 4:
The FDA should take into account a nutrient’s or food’s source as well as any modifying effects of the food or supplement that serves as the delivery vehicle and the dietary patterns associated with consumption of the nutrient or food when reviewing health-related label claims and the safety of food and supplements. Congress may need to strengthen FDA authority to accomplish this goal.
data; the committee’s framework explicitly includes such a process, while allowing for timely, reliable, and effective decision making.
The evaluation framework is intended to be applicable across a wide range of biomarker uses, from exploratory uses for which less evidence is required to surrogate endpoint uses for which compelling evidence is required. The framework is meant for, but not limited to, use in research, clinical, product, and claim development in food, drug, and device industries as well as public health settings, and it is intended to function for
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FIGURE 3-1 The steps of the evaluation framework are interdependent. While a validated test is required before qualification and utilization can be completed, biomarker uses inform test development, and the evidence suggests possible biomarker uses. In addition, the circle in the center signifies ongoing processes that should continually inform each step in the biomarker evaluation process.
panels of biomarkers in addition to single biomarkers and for both circulating and imaging biomarkers. While the report provides case studies of individual biomarkers, the committee concluded that sets of biomarkers need to be qualified using the same process. In some cases, individual biomarkers within the same set may need to be qualified individually.
This chapter explores the rationale behind the committee’s decision to separate evaluation into three interrelated steps before providing an in-depth examination of each step. This conceptual framework is meant to provide a clear, adaptable platform for statistically sound, evidence-based biomarker evaluation.
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THE RATIONALE FOR AN INTERRELATED, THREE-STEP PROCESS
Recommendation 1:
The biomarker evaluation process should consist of the following three steps:
1a.
Analytical validation: analyses of available evidence on the analytical performance of an assay;
1b.
Qualification: assessment of available evidence on associations between the biomarker and disease states, including data showing effects of interventions on both the biomarker and clinical outcomes; and
1c.
Utilization: contextual analysis based on the specific use proposed and the applicability of available evidence to this use. This includes a determination of whether the validation and qualification conducted provide sufficient support for the use proposed.
The committee recognizes that including analytical validation in the evaluation framework and separating the evidentiary assessment from the utilization analysis is a departure from many previous attempts to develop biomarker evaluation systems, but found that these processes, although distinct, are interwoven in such a way that it is impossible to responsibly consider one without also considering the others. Although biomarker analytical validation and biomarker qualification will often be considered together (the statistical linkages of disease, biomarker, and drugs can depend on the analytical soundness of a biomarker assay) and have been used synonymously in the past (Biomarkers Definitions Working Group, 2001), differentiating these processes is important (Lee et al., 2006). A National Institutes of Health working group recommended the term “validation” be used for analytical methods (Biomarkers Definitions Working Group, 2001). The American Association of Pharmaceutical Scientists (AAPS), the Pharmaceutical Research and Manufacturers of America, and the Biomarkers Consortium, among other organizations, have worked to reinforce the distinction between analytical validation and qualification (Lee et al., 2005; Wagner, 2002). As discussed below, analytical validation is the process of assessing how well an assay quantitates a biomarker of interest; qualification is the evidentiary and statistical process linking a biomarker with biological processes and clinical endpoints (Biomarkers Definitions Working Group, 2001). The committee determined that qualification could be further separated into evidentiary assessment and utilization analysis, so that the different investigative and analytical processes required to evaluate evidence and contexts of use
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are distinct. Details regarding methods for the gathering of evidence are discussed in the section on Recommendation 2.
It is important to emphasize the necessity of evaluating data relating to adverse events and unintended effects of biomarker use. In every step, the proposed use and its context are critical. For drug development and other medical uses, this entails a risk–benefit analysis, which weighs evidence supporting biomarker use against known inaccuracies and gaps in knowledge that present the possibility of error. For foods and supplements, this entails an analysis of the potential modifying matrix effects of the food or supplement that serves as the delivery vehicle and the dietary patterns associated with consumption of the nutrient or food substance.
The committee understands that a biomarker evaluation checklist of criteria to fulfill for given purposes would be more straightforward to use. But, given the complexities of biomarker utilization, the risks involved with their use, and the evolving nature of science and technology, a checklist-based approach was deemed to be infeasible. First, because any attempts to evaluate a biomarker must consider the context of and purpose for use of the biomarker, scientific and medical judgment plays a role in decision making. Because the purpose and context in each evaluation are unique, there are no precisely relevant past data to consult for guidance. Also, decisions made during the evaluation process are based on probabilistic rather than deterministic reasoning. Probabilistic reasoning emphasizes epidemiological and statistical relationships and acknowledges that the biology is not fully understood. Both statistical methods and decision analysis may be important tools for biomarker evaluations. Both of these were discussed in Chapter 2.
Despite these important caveats, a nuanced understanding of the strength of a biomarker is necessary to develop an evidence-based understanding of whether the biomarker is fit for its proposed purpose and context of use. The committee acknowledges that decisions resulting from the evaluation of a biomarker are dependent on the purposes for which the biomarker will be used. Although some have supported the idea of biomarker evaluations that can be viewed as general and definitive for any proposed purpose or context of use, the committee has determined that there has been no example of this so far and it does not expect to witness one in the future.
The committee recognizes that this approach will require some additional financial and human resources at the Food and Drug Administration (FDA), as was suggested in the Institute of Medicine (IOM) report The Future of Drug Safety and is discussed further in Chapter 5 (2007). However, the process fits well with the mechanisms that the FDA already uses to seek external advice (e.g., the scientific advisory committees). Also, this process would represent a modest investment compared to its
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potentially broad benefits to society by ensuring a stronger evidence base underpinning FDA decisions. Benefit to the FDA itself and its commercial users may also be realized through more consistent and transparent expectations.
Analytical Validation
As previously defined, the term “biomarker” refers to a characteristic that is reliably and accurately measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention (Biomarkers Definitions Working Group, 2001). Thus, measurement itself must be an explicit component of any discussion of biomarker evaluation because it establishes the scientific basis and availability of experimental data that support or refute the context for qualification of a biomarker and its proposed application (Goodsaid and Frueh, 2007). The committee finds that analytical validation of a relevant biomarker test is a prerequisite for biomarker qualification.
Analytical validation is defined as an assessment of assays and their measurement performance characteristics, determining the range of conditions under which the assays will give reproducible and accurate data. Thus, analytical validation is an assessment of a biomarker test that includes the biomarker’s measurability and the test’s sensitivity for the biomarker, biomarker specificity, reliability, and lab-to-lab reproducibility. The terminology used in the recommendation, analytical performance, is not meant to describe how well a biomarker correlates with the clinical outcomes of interest. Instead, analytical validation of an assay includes the biomarker’s limit of detection, limit of quantitation, reference (normal) value cutoff concentration, and the total imprecision at the cutoff concentration. These specifications must be determined and met before data based on its use can be relevant in the qualification steps of biomarker evaluation. To ensure comparison across multiple laboratories and clinical settings, appropriate standards for ensuring quality and reproducibility need to be made available. Additionally, understanding the difference between individual assays is important to interpreting the findings of different studies monitored using different assays (Apple et al., 2007). For biomarkers used solely in laboratory testing, it would be beneficial to assess the ability to compare data from different assay platforms as much as possible and needed.
Though key guidelines and regulations have molded approaches to assay validation (Swanson, 2002), biomarker validation is distinct from pharmacokinetic validation and routine laboratory validation; however, an agreement for a uniform set of criteria for biomarker assay validation
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has not been reached. Method validation requirements for assays that support pharmacokinetic studies have been the subject of intense interest, and the FDA has issued guidance for industry on bioanalytical method validation (CDER, 2001).1 This guidance, though, is directed at validation of assays looking at metabolism of conventional small-molecule drugs and is not directly related to the validation of assays for biomarkers for many other uses. Similarly, biomarker validation is, in many ways, different from routine laboratory validation. Laboratories that perform testing to support human diagnostics and health care are regulated by the Clinical Laboratory Improvement Amendments, or CLIA (Centers for Medicare & Medicaid Services), and accrediting organizations such as the College of American Pathologists (Swanson, 2002).
Because of the diverse purposes of biomarker research and the various locations in which these assays are performed (routine and novel biomarker assays are performed in both bioanalytical and clinical laboratories; novel biomarker assays are also performed in specialized laboratories), neither the FDA regulations nor the CLIA guidelines fully address all possible study objectives. Differences between biomarker assays and those of drug bioanalysis and diagnostics are described in detail in Table 1 of Lee et al. (2006), highlighting some of the unique validation challenges related to biomarker assays (Lee et al., 2006).
In the absence of uniform criteria for the validation of biomarker assays, analytical qualities and clinical performance of assays cannot be objectively evaluated (Apple et al., 2007). To address these challenges, the AAPS and Clinical Ligand Assay Society cosponsored a Biomarker Method Validation Workshop in October 2003 (Lee et al., 2005). It resulted in a validation approach for laboratory biomarker assays in support of drug development. This validation approach, though, was focused primarily on ligand-binding methods to gauge biomarkers measured ex vivo from body fluids and tissues (Lee et al., 2006).
Additionally, the International Federation of Clinical Chemistry and Laboratory Medicine Committee on Standardization of Markers of Cardiac Damage has recommended analytical and preanalytical quality specifications for a variety of assays, including those for natriuretic peptides and troponin assays (Apple et al., 2005, 2007; Writing Group Members et al., 2008). These guidelines were developed to guide both clinical and commercial laboratories that use the assays with the goal of establishing uniform criteria (Apple et al., 2007). The standardization and harmonization of biomarker assays is challenging due to the various analytical and biological factors that influence measurement (Swanson, 2002). By defini-
1
Good Laboratory Practice for Nonclinical Laboratory Studies. 2001. Code of Federal Regulations, Title 21, Vol. 1, 21 C.F.R. 58.
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tion, biomarkers are dynamic and responsive to changes in the disease process, pharmacological intervention, and environment (Fraser, 2001; Ricos et al., 1999). For example, variability in biomarker level is affected by biology (e.g., gender, age, posture, diet), sample type (e.g., blood, urine), sample collection (e.g., transport and storage conditions, collection technique), and analytical factors (e.g., pipetting precision, antibody specificity) (Swanson, 2002). Sources of variability in biomarker measurements are summarized in Table 3-1. Though these background fluctuations affect
TABLE 3-1 Sources of Variability in Biomarker Measurements
Preanalytical Sources of Variability
Analytical Sources of Variability
Biological
Sample Collection
Sociodemographics (including age and gender)
Posture
Exercise
Meals/fasting status
Diet
Diurnal biorhythm
Seasonal biorhythm
Concurrent diseases
Concurrent medications
Overall health/preexisting disease
Gastrointestinal motility
Anesthesia/surgical intervention
Stress
Pregnancy
Menstrual cycle
Dehydration
Kidney function
Body composition (obesity)
Mislabeling
Duration of tourniquet application
Strength of collection vacuum
Size of needle gauge
Dead volume in catheters/collection tubes
Anticoagulants
Local effects of indwelling catheter
Time and temperature prior to centrifugation
Centrifugation speed, duration, temperature
Evaporation/biomarker volatility
Preservatives/biomarker instability
Storage temperature
Transport temperature
Completeness of urine collection
Hemolysis
Effect of glass and plastic collection tubes
Exposure to light
Type of sample
Time of clotting
Purity of reference standards
Lot-to-lot variation in reagents
Antibody crossreactivity
Loss during extraction
Mislabeling of processing tubes
Pre-assay incubation time and temperature
Pre-assay amplifications
Chemical interference by endogenous compounds
Chemical interference by drugs
Analyte or reagent instability in light
Time between intermediate steps
Fluctuations in instrument performance
Correction for baseline/background levels
Post-run calculation errors
Matrix effects
Reproducibility of sample
SOURCE: Adapted from Swanson (2002). Copyright 2010, reprinted with permission from IOS Press.
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both the sensitivity and the specificity of biomarker measurements, and though it may not be possible to establish absolute accuracy, relative accuracy can be informative and the sources of variability can be understood and controlled, allowing for the delivery of high-quality assay results (Lee et al., 2006; Swanson, 2002).
Implementation of biomarker validation therefore requires both understanding and control of the various sources of variability in assay performance (Kristiansen, 2001). Results from biomarker assays are valid only if sample integrity is maintained from sample collection through analysis. It is important to devise standard protocols for sample collection, processing, and storage to achieve uniformity (Lee et al., 2005, 2006). The committee synthesized a variety of approaches to develop its key elements for biomarker validation. Table 3-2 lists important data for inclusion in package inserts and in peer-reviewed publications for biochemical biomarker assays in the preanalytic characteristics, calibration and standardization criteria, and analytic parameters. Other considerations may be needed for imaging and other types of biomarker assays; this is discussed further in Chapter 4.
Validation of biomarker tests should be done on a test-by-test basis and must then be deemed sufficient for the use proposed in the utilization step (ICH, 1994; Shah et al., 1992). Thus, the rigor of biomarker validation can be correlated with the intended use of the data (Lee et al., 2006). The committee finds that biomarker qualifications are often undermined by insufficiently validated tests, which may lack accuracy, sensitivity, and specificity. Additionally, use of tests after biomarker qualification and test validation depends on operator, reagent, and instrument variability, among other factors. In the case of clinical laboratory assays and reference ranges of common biomarkers, for example, absence of standardization can lead to interpretation mistakes (Rosner et al., 2007; Wu, 2010). The nature of health care is such that patients often use multiple laboratory facilities during the course of care (Wu, 2010). Diagnosis and management depend on the accuracy of testing across laboratories (Rosner et al., 2007). Therefore, proper standards and controls are necessary to ensure consistent delivery of high-quality biomarker data and the validation of biomarker tests prior to biomarker qualification. Box 3-2 introduces the case study exemplifying the issues found in analytical validation. Further detail can be found in Chapter 4.
Qualification
The second step of the committee’s evaluation framework is a factual description of the levels and types of available evidence. This objective analysis is a reproducible, systematic assembly and review of the evi-
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TABLE 3-2 Information Needed for Package Inserts and Peer-Reviewed Publications Describing Biomarker Assays
Preanalytic
Calibration/Standardization
Analytic
Sample handling
Effect of storage time and temperature
Influence of different anticoagulants (type and concentration) for plasma and whole blood measurements
Influence of gel separator tubes
Time and speed (relative centrifugal force) and temperature of sample centrifugation with the effects of various methods for tube filling, mixing, and centrifugation
A low-level quality control (QC) sample with concentration close to reference value to monitor assay bias at cutoff
A negative QC sample to monitor baseline drift
Calibration frequency to be determined based on the imprecision and drift characteristics of the assay
Calibration using defined biomarker calibrators to accommodate any subtle changes in assay calibration curve
Defined limits for the zero calibrator’s reaction units
For antibody assays, identification of antibody recognition epitopes
For activity assays and immunoassays, identification of limiting substrates
Linearity of signal
Reactivity to various plasma biomarker forms (degree of equimolarity)
Cross-reactivity with other related proteins in complex matrix (normal and disease)
Identification of interferences from hemolysis, bilirubin, and lipemia, and potential interferences from heterophile antibodies, rheumatoid factors, and human antianimal antibodies and autoantibodies (neither of which are currently commercially available)
Dilution response (i.e., linearity, recovery) over time and sites
Assay limit of blank, limit of detection, and limit of quantitation
Decision limits and precision at relevant concentrations
Method comparison data, in particular if manufacturers offer both central laboratory and point-of-care assays
Establishment of the decision limit of the distribution of healthy subject reference values
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BOX 3-2
Tumor Size and Analytical Validation (Recommendation 1a)
Tumor size is a variously defined biomarker of efficacy of cancer therapeutics using tumor diameter, tumor volume, or tumor mass, as measured by a variety of platforms and techniques, including magnetic resonance (MR), computed tomography (CT), and positron emission tomography (PET). Different contrast agents and different protocols may be used, all of which affect the precision of measurement. Measurement precision is also affected by patient characteristics. Each protocol, which may also vary by tumor location, should undergo independent validation. There is a great deal of variability in the levels of evidence to support validation for different protocols; thus, analytical validation is complicated by multiple imaging platforms and other assay performance issues. The disparity in evidence impacts the interpretation and generalizability of these imaging endpoints.
Assuming that at least one test is determined to be adequately validated, data collected for the qualification step have shown that tumor size may not always be linked to clinical benefit although tolerance for uncertainty of clinical benefit has been justified by the seriousness of cancer.
For utilization, in 1992, the Food and Drug Administration started granting accelerated approval for drugs that are effective against serious diseases based on surrogate endpoints. Accelerated approvals for anticancer drugs or biologics have been granted on the basis of endpoints such as overall response rate, time to progression, or disease-free survival. Of those granted approval between 1992 and 2004, only about one-quarter have been converted to regular approval (i.e., demonstrating an effect on survival) (Lathia et al., 2009). All of them remain on the market. Concern exists that clinical benefit may be neglected in regulating this type of approval (Fleming, 2005). Tumor size is discussed in greater detail in the full case study found in Chapter 4.
dence. Users of the evaluation framework will need to identify appropriate methods for gathering the evidence for this step. This is discussed with respect to the FDA in the section on recommendation 2. Fulfilling the qualification step requires: (1) evaluating the nature and strength of evidence about whether the biomarker is on a causal pathway in the disease pathogenesis, and (2) gathering available evidence showing that interventions targeting the biomarker in question impact the clinical endpoints of interest. If the biomarker–clinical endpoint relationship persists over multiple interventions, it is thought to be more generalizable.
It is important to note that although this is an objective, evidence-based assessment, the type of reasoning that may be used in this step is still probabilistic rather than deterministic. While deterministic reasoning ultimately means that every contributing factor to the biomarker– intervention–clinical endpoint link is defined and understood, probabi-
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tion and evidentiary qualification were viewed as objective tasks of gathering available evidence, and so they can be conducted separately from a particular context of use. It is also important to discuss briefly, how the committee envisions conduct of the data-gathering process. Data should be gathered from all available sources of evidence. When the evidence is to come entirely from the public domain, it can be gathered according to principles of systematic review (Cochrane Collaboration, 2009; IOM, 2010b). When data not generally publically accessible is made available, such as data owned by companies, for example, then gathering of such data would likely be subject to the same processes as data submission to the FDA for product review.
Evidence evolves even after a biomarker is evaluated; thus, it is imperative that biomarkers be reevaluated periodically so that both the scientific evidence and context-of-use analyses capture the current state of the science. By continual, the committee refers to the need for regular reevaluation on the basis of new scientific developments and data. For instance, continuing with the tumor-size case example, progression of gastrointestinal stromal tumors was found to occur within the original tumor boundaries. Although chemotherapeutic treatment of the tumors may result in decreased cell density and prolonged survival, tumor size (in terms of measurable diameters) was found to generally remain the same. These findings could be cause for reevaluation of the analytical validation step of the biomarker evaluation framework.
Ideally, research findings would dictate the necessity for reevaluation. Post-hoc review should be performed at regular intervals as new information is available to determine how new conclusions should modify the biomarker’s qualification and use. When new, potentially relevant evidence related to a biomarker is found, this evidence would be considered to determine the continued appropriate use of the biomarker across a variety of contexts. In practice, however, research efforts are often piecemeal and new findings may not readily be identified as cause for reevaluation of a biomarker. Additionally, the dynamic context of the regulatory environment may lead to reappraisal of the contexts for which a biomarker has been evaluated. For example, some regulatory environments may, despite attempts to minimize subjectivity, exhibit less caution when evaluating some contexts in which a given biomarker can be used. Thus, given the many demands and time constraints of the medical, scientific, and regulatory enterprises, the committee concludes that to incorporate and consider new research findings, biomarkers may be reevaluated within a reasonable time frame, such as every 4 years, for example. The committee does not intend such a time frame to dissuade more frequent reevaluation: Indeed, the rapidity of new knowledge available may dictate more immediate revisions in the contexts for which a biomarker may be used.
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Rather, all biomarker evaluations should undergo reappraisal on at least such a time frame.
Each step needs to be reconsidered to the extent that research or context has changed since the previous evaluation. The reappraisal process need not consider the biomarker as though no previous evaluation had occurred. The monetary and opportunity costs of this kind of de novo evaluation would render such analyses prohibitive. Rather, the available data can be scrutinized in the context of what had been previously evaluated. By considering additional evidence, it is possible that the expert panel may alter its past findings by revoking recommendations for a previously accepted biomarker use, choosing not to recommend a biomarker for uses similar to those for which it was granted permission in the past, providing a more nuanced explanation as to how a biomarker should be used, or qualifying the biomarker for use in new contexts. Some of these scenarios are indicated in the case studies presented in Chapter 4. Nonetheless, it is essential that the utilization analysis be carried out by a panel of experts, as scientific and medical judgment is necessary to weigh the possible advantages and disadvantages of the proposed biomarker use.
SCIENTIFIC PROCESS HARMONIZATION
Recommendation 3:
The FDA should use the same degree of scientific rigor for evaluation of biomarkers across regulatory areas, whether they are proposed for use in the arenas of drugs, medical devices, biologics, or foods and dietary supplements. Congress may need to strengthen FDA authority to accomplish this goal.
Legislation and court decisions have created a regulatory environment in which different evidentiary and labeling requirements exist for drugs and biologics, devices, and foods and supplements. The committee has concluded that accurate and complete science is critical in all of these areas. While recognizing the differences between the different product categories, the committee emphasizes that none of these categories presents a situation so low in risk to consumers as to allow less rigorous scientific justification for claims. Box 3-6 summarizes the case study for a nutritionally relevant biomarker, blood levels of beta-carotene. This case study illustrates the need for collection of data for nutrition-related biomarkers.
To further illustrate the assertion that it is not safe to make assumptions about risks posed by products in a given category, consider the numbers of people exposed annually to several public health interventions that use food, compared to the numbers of people annually who
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BOX 3-6
Blood Levels of β-Carotene
Studies have consistently shown that diets rich in fruit and vegetables are associated with a reduced risk of chronic diseases such as heart disease and cancer (Block et al. 1992; Peto et al., 1981). Although fruits and vegetables offer many nutrients, years of epidemiological studies suggested that blood levels of β-carotene were associated with lower incidence of cardiovascular disease and cancer (Hennekens et al., 1984; Manson et al., 1993; Willett et al., 1984). β-carotene is a carotenoid and antioxidant known to be a precursor of vitamin A.
To further corroborate the biomarker’s biological plausibility, β-carotene’s classification as an antioxidant provided a possible mechanism for a protective effect. Though there were no further animal studies or small-scale clinical trials performed, mounting pressures from multiple stakeholders, eager to prevent disease or improve the quality of life for persons at risk of chronic disease, quickly pushed the consideration of blood β-carotene levels as an effective chemopreventive biomarker and impelled large-scale intervention trials to test the possible benefits of increased intake of the nutrient itself were quickly initiated.
Before results from the three large β-carotene trials (the Physicians’ Health Study) (Cook et al., 2000), the Beta Carotene and Retinal Efficacy Trial (CARET) (Omenn et al., 1996a, 1996b), and Alpha Tocopherol Beta Carotene Cancer Prevention Study (ATBC) (Albanes et al., 1996) had been confirmed, the belief in the “efficacy” of increased β-carotene intake became widespread based on the observational studies that demonstrated association, but not causality. This was based on the consistency, strength of association, dose–response gradient, and biological plausibility. Thus, the unfavorable and even deleterious results of the trials were surprising to physician, patient, research-scientist, and policy-maker proponents of β-carotene. These studies demonstrated that assumptions that β-carotene was a valid causal predictor of decreased lung cancer risk were in error and illustrate the public health value of proper preclinical research strategies and evaluative process before permitting claims. This matter is discussed in greater detail in the full case study found in Chapter 4.
take a few common drugs. About 184 million people drank fluoridated water in the United States in 2006, about 62 percent of the entire population (CDC, 2006). Commercially available cereal flours and related products, milk and other dairy products, and fruit juices and drinks can be fortified with vitamin D. Milk and cereals are most frequently fortified (Calvo et al., 2004). Dietary intakes of vitamin D in the United States range from about 4.2 to 5.4 µg per person per day (depending on age and sex), most of which is from fortified foods (Moore et al., 2005). Additionally, about 27 percent of the U.S. adult population took
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a supplement containing vitamin D in 2002 (Kaufman et al., 2002). In 2002, it was reported that about 5.2 percent of the U.S. adult population was taking statins (Freemantle, 2002; Kaufman et al., 2002). The most commonly used medication, acetaminophen, was taken by about 23 percent of the U.S. adult population in a given week (Kaufman et al., 2002). Just over 1 percent of U.S. adults were taking fluoxetine hydrochloride (Prozac) (Kaufman et al., 2002). These are among the most used over-the-counter and prescription medications in the United States. From these and other similar data, it can be concluded that exposure to some public health interventions is much more prevalent than exposure to the most common medications.
Further, many individuals are not aware that public health interventions involving food are not risk-free. Chapter 4 shows the risks of beta-carotene supplementation. The example above highlights a topic discussed more fully in Chapter 2: in order to make informed decisions, individuals need access to complete information (see Chapter 2 section titled “Biomarkers and Communication Strategies at the FDA”). Nonetheless, the ability to interpret this information depends on numeracy, and individuals making complex decisions may benefit from professional advice (see Chapter 2 section titled “Numeracy”). However, professional advice is generally not sought for dietary decisions, for example. Further discussion of issues related to the use of biomarker data and its impact on subsequent health-related decisions was discussed in Chapter 2 (see section titled “Cognitive Biases and Impacts of Evidence Gaps”).
Recommendation 3 is consistent with other recent efforts to improve the use of science at FDA and in European regulatory agencies. The renewed effort to strengthen the scientific base at FDA is discussed in Chapter 5 (see section titled “Tracking the Effects of Biomarker Use at the FDA”). Chapter 5 also goes into detail about the different requirements in different product areas. It discusses the use of regulatory authority and where better use may be needed. In order to implement this recommendation, the FDA will need to better implement some of its existing regulatory authority, and it may also need additional regulatory authority. Recommendation 3 is not meant to imply that an identical process be used across all of the centers. Instead, it means that rigorous, complete review of all available scientific evidence is necessary before regulatory decisions can be made. In the case of foods and supplements, for example, this may require Congress to enact legislation to allow the FDA to compel companies to gather and submit data relating to the safety and efficacy of proposed products and health claims, based on both the nutrients of interest alone and on the whole products within which they are contained.
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Addressing Differences in Current Standards for Drugs, Biologics, Devices, Supplements, and Foods
Recommendation 4:
The FDA should take into account a nutrient’s or food’s source as well as any modifying effects of the food or supplement that serves as the delivery vehicle and the dietary patterns associated with consumption of the nutrient or food when reviewing health-related label claims and the safety of food and supplements. Congress may need to strengthen FDA authority to accomplish this goal.
Drugs, biologics, and devices are evaluated on the basis of the safety and efficacy of the entire product. The regulatory framework governing these products, foods, and supplements are explained in greater detail in Chapter 5. The committee concluded that for the utilization step of the biomarker evaluation framework, it is necessary to evaluate the biomarker’s proposed use in terms of the entire product in all situations. In addition, the committee concluded that it is important to evaluate efficacy as well as safety of proposed biomarker uses. Legislation may be required to implement this recommendation.
Currently, the safety of new food substances is evaluated for the individual substances within the context of intended conditions of use, and not on a product-specific basis as is done for drugs. Validity of claims made with respect to foods and supplements can be made on the basis of single ingredients in foods. There are some restrictions on the amount of fat, saturated fat, cholesterol, and sodium that foods bearing health claims can contain, and also on the need for a minimum amount of vitamin A, vitamin C, calcium, protein, fiber, or iron for foods bearing claims. Nonetheless, although review of proposed health claims takes into account the relationship of the specific substance that is the subject of the health claim to the health outcome of interest, it may not adequately consider the modifications of the substance’s effect on the disease outcome by other bioactive components in that food or the diet. For this reason, it is important to include an analysis of the connection between the biomarker and other factors associated with conditions that can affect its efficacy and safety in the qualification process.
In addition to the modifying effects of other material components of a food or supplement on the effect of a health claim based on a single ingredient, it is also important to consider the modifying effects of a health claim on the overall healthfulness of the diet. More research in this area is needed.
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CONCLUSION
This approach to biomarker evaluation extends beyond reviewing the scientific literature to determine biomarker acceptance. The recommended comprehensive evaluation framework is a process by which consensus may be reached about the qualification of a biomarker and considers context-independent and context-dependent qualifications, as well as analytical validation. The committee finds it important to make analytical validation a necessary component to biomarker validation; without high-quality research data, biomarkers cannot be effectively used. Furthermore, it is important to know whether a biomarker has prognostic value and whether the science underlying its role in disease is well understood. Determining that a biomarker has prognostic value and a well-defined scientific basis, however, is distinct from knowledge that modifying the biomarker will bring about clinical benefit or harm. Utilization, the process of making assessments of whether a proposed biomarker is fit for the purpose for which it is being proposed, is the third essential component of the biomarker evaluation process. The committee concludes that these three steps therefore warrant separation to ensure each receives its full consideration. For decisions involving regulatory bodies, the committee recommends that an expert panel conduct the evaluation reviews. Biomarker evaluations need to be continually updated to reflect the current state of the science.
Importantly, the committee has recommended that the scientific information used to inform policy decisions regarding biomarkers should be equally rigorous across proposed uses and product categories. Finally, in the special case of foods and supplements, accommodations are needed to ensure that the entire food or supplement is taken into account when evaluating biomarkers for nutrition-related uses.
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