3 Regulatory Aspects in Using Surrogate Markers in Clinical Trials

3 Regulatory Aspects in Using Surrogate Markers in Clinical Trials Aloka Chakravarty 3.1 Introduction and Motivation Surrogate marker plays an important role in the regulatory decision processes in drug approval. The possibility of reduced sample size or trial duration when a distal clinical endpoint is replaced by a more proximal one hold real benefit in terms of reaching the intended patient population faster, cheaper, and safer as well as a better characterization of the efficacy profile. In situations where endpoint measurements have competing risks or are invasive in nature, certain latitude in measurement error can be accepted by deliberately choosing an alternate endpoint in compensation for a better quality of life or for ease of measurement. 3.1.1 Definitions and Their Regulatory Ramifications Over the years, many authors have given various definitions for a surrogate marker. Some of the operational ramifications of these definitions will be examined in their relationship to drug development. Wittes, Lakatos, and Probstfield (1989) defined surrogate endpoint sim- ply as “an endpoint measured in lieu of some so-called ‘true’ endpoint.” While it provides the core, this definition does not provide any operational motivation. Ellenberg and Hamilton (1989) provides this basis by stating: “investigators use surrogate endpoints when the endpoint of interest is too difficult and/or expensive to measure routinely and when they can define some other, more readily measurable endpoint, which is sufficiently well correlated with the first to justify its use as a substitute.” This paved the way to a statistical definition of a surrogate endpoint by Prentice (1989): 14 Aloka Chakravarty “a response variable for which a test of null hypothesis of no relationship to the treatment groups under comparison is also a valid test of the cor- responding null hypothesis based on the true endpoint.” This definition, also known as the Prentice Criteria, is often very hard to verify in real-life clinical trials. An operating definition given by Temple (1999) states: “a laboratory or physical sign that is used in therapeutic trials as a substitute for a clinically meaningful endpoint that is a direct measure of how a patient feels, functions, or survives and that is expected to predict the effect of the therapy.” This definition has been used as the operational definition of surrogate endpoints in a regulatory setting. International Conference on Harmonization (ICH) document E8 states: “a validated surrogate endpoint is an endpoint which allows prediction of a clinically important outcome but in itself does not measure a clinical benefit. When appropriate, surrogate outcomes may be used as primary endpoints.” It further states that the “methods used to make the measurements of the endpoints, both subjective and objective, should meet accepted standards for accuracy, precision, reproducibility, reliability, va- lidity and responsiveness (sensitivity to change over time),” thus providing a valid premise to use it in multinational trials. A well-validated surrogate will predict the clinical benefit of an intervention both quantitatively and qualitatively with consistent results in several settings. According to Temple (1999), a surrogate endpoint is a laboratory measurement or physical sign used in therapeutic trials as a substitute for a clinically meaningful endpoint that is expected to predict the effect of the therapy. The U.S. Food and Drug Administration (FDA) is able to rely on validated surrogates for accelerated approval of drugs that provide meaningful benefit over existing therapies for serious or life-threatening illnesses (e.g., acquired immunodeficiency syndrome). In these cases, the surrogates should be reasonably likely to predict clinical benefit based on epidemiological, therapeutic, pathophysiologic, or other scientific evidence. However, in general, trials examining surrogate endpoints, even where the endpoint is well correlated with a clinical outcome, surrogates will be un- able to evaluate clinically relevant effects of the drug not related to the surrogate, whether these are beneficial or adverse. 3.1.2 Support for Surrogates Next, we examine what are the motivations for using a surrogate endpoint. The motivation to use a surrogate can be judged by its biological plausibility, its expected success in clinical trials, and its risk-benefit ratio or public health considerations. We summarize these issues in Table 3.1. 3. Regulatory Aspects in Using Surrogate Markers in Clinical Trials 15 TABLE 3.1. Support for surrogates. Factor Favors surrogates Does not favor surrogates Biological Epidemiological evidence Inconsistent epidemiology plausibility extensive and consistent Quantitative epidemiological No quantitative epidemiologi- relationship cal relationship Credible animal model shows No animal model drug response Well-understood disease Pathogenesis not clear pathogenesis Drug mechanism of action Novel actions not previously well-understood studied Surrogate relatively late in the Surrogate remote from clinical biological path outcome Success in clinical Effect of surrogate has predicted A negative outcome without trials outcome with other drugs of clear explanation same pharmacological class Effect on surrogate had Inconsistent results across predicted outcome in several classes classes Risk-benefit, Serious or life-threatening Disease not life-threatening public health illness and no alternate therapy and alternate therapy with dif- considerations ferent pharmacological action known to affect outcome Large safety database Little known about safety Short term use Long-term use Difficulty in studying clinical Easy to study clinical endpoint endpoint (rare, delayed) Long-delayed, small effect in healthy people Thus, a surrogate to be useful has to have unequivocal biological plausibility, be expected to perform consistently in a clinical trial, and possess superior public health benefits. 3.1.3 Criteria for Surrogate Markers To Be Used in Drug Development In epidemiological studies, a useful surrogate marker is a causal factor for the disease of interest, not merely a correlated factor. As Fleming (1996) stated, “a correlate does not a surrogate make.” The higher the level of explanatory evidence the surrogate is able to carry, the better it is to ex- plain the disease process. Table 3.2 summarizes the relationships surrogate endpoints (SEP) can have with the “true” clinical endpoints (CE). Then, sensitivity (SE) of the surrogate endpoint for the clinical endpoint 16 Aloka Chakravarty TABLE 3.2. Relationship of surrogate endpoints with the clinical endpoints. T good T poor Total S good aba+ b S poor cdc+ d Total a + cb+ dN a = number of patients where both S and T provide good disease characterization. b = number of patients where S is good but T provide poor disease characterization. c = number of patients where S is poor but T provide good disease characterization. d = number of patients where both S and T provide poor disease characterization. is defined by a SE = . (3.1) a + c Specificity (SP) of the surrogate endpoint for the clinical endpoint is defined by d SP = . (3.2) b + d For the surrogate to be useful, both sensitivity and specificity have to be numerically close to 1. The relative risk (RR) is defined as a(c + d) RR = (3.3) c(a + b) and the attributable proportion (AP )as SE AP = . (3.4) − 1 1 RR For a surrogate marker to be a successful one, AP has to be numerically close to 1. Schatzkin, Freedman, and colleagues proposed strategies for de- termining whether a biomarker is a valid surrogate for a disease of interest, for instance whether human papillomavirus infection is a valid surrogate for cervival dysplasia. The attributable proportion is a useful measure of association between the surrogate endpoint and the clinical endpoint, but establishing the causality of the relationship between the surrogate and the clinical endpoint require data from either observational studies or, prefer- ably, intervention studies. Intervention studies would focus on the triplet intervention / biomarker / disease in much the same way as a clinical trial would focus on the triplet treatment / surrogate endpoint / clinical endpoint. 3. Regulatory Aspects in Using Surrogate Markers in Clinical Trials 17 3.1.4 Surrogate Markers and Biomarkers Definitions and Differences Biological marker or biomarker, as more commonly known, refers to a vari- ety of physiologic, pathologic, or anatomic measurements that are thought to relate to some aspect of normal or pathological biologic processes (Tem- ple 1995, Lesko and Atkinson 2001). These biomarkers include measurements that suggest the etiology of, the susceptibility to, or the progress of disease; measurements related to the mechanism of response to treatments; and actual clinical responses to therapeutic interventions. Biomarkers differ in their closeness to the intended therapeutic response or clinical benefit endpoints, classified as follows: 1. biomarkers thought to be valid surrogates for clinical benefit (e.g., blood pressure, cholesterol, viral load); 2. biomarkers thought to reflect the pathologic process and be at least candidate surrogates (e.g., brain appearance in Alzheimer’s disease, brain infarct size, various radiographic/isotopic function tests); 3. biomarkers reflecting drug action but of uncertain relation to clinical outcome (e.g., inhibition of ADP-dependent platelet aggregation, ACE inhibition); 4. biomarkers that are still more remote from the clinical benefit endpoint (e.g., degree of binding to

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