Response Assessment in Clinical Trials: Implications for Sarcoma Clinical Trial Design

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1 Response Assessment in Clinical Trials: Implications for Sarcoma Clinical Trial Design C. Carl Jaffe Diagnostic Imaging Branch, Cancer Imaging Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA Key Words. RECIST Response assessment Clinical trial design Imaging response Disclosure: No potential conflicts of interest were reported by the author, planners, reviewers, or staff managers of this article. Abstract Response assessment and design of clinical trials require careful consideration of many factors, especially as validated response criteria can ultimately lead to the approval of an anticancer agent. Current anatomic imaging criteria are difficult to apply for evaluation of certain types of tumors, including soft tissue sarcomas. The emergence of new molecular imaging techniques, such as 64-slice computed tomography scanners and dynamic contrast magnetic resonance imaging, provide Correspondence: C. Carl Jaffe, M.D., National Cancer Institute, 6116 Executive Boulevard, Bethesda, Maryland 20892, USA. Telephone: ; Fax: ; Received August 20, 2007; accepted for publication October 24, AlphaMed Press /2008/$30.00/0 doi: /theoncologist.13-S2-14 The Oncologist 2008;13(suppl 2): complementary information to conventional anatomical imaging. Currently the U.S. National Cancer Institute and the U.S. Food and Drug Administration are aiming to revise existing response criteria based on the development of volumetric anatomic imaging for oncology. Reviewing existing and new approaches in the design of clinical trials will help to optimize the clinical development and evaluation of new therapies for sarcomas. The Oncologist 2008:13(suppl 2):14 18 Introduction Tumor response criteria are used to evaluate the response of cancerous tumors to agents being investigated in clinical trials. Because tumor response rates may be included as endpoints in cancer clinical trials, validated response criteria can be key to the success of a trial and ultimately to the approval of an anticancer agent. The majority of cancer clinical trials are conducted at multiple institutions, so both the response criteria and the tools used for evaluating response must be consistent across multiple centers. Traditional response criteria are based on changes in tumor size [1, 2]. However, such anatomic criteria may be difficult to apply to measure certain tumors, such as soft tissue sarcomas. In addition to being potentially difficult to measure, soft tissue sarcomas may not necessarily change in size in response to therapy, at least initially. This is especially true for newer cytostatic therapies such as imatinib mesylate in gastrointestinal stromal tumors (GISTs). The introduction of novel, advanced imaging technologies in recent years has the potential to redefine how tumor responses are evaluated. For example, fluorine-18-fluorodeoxyglucose positron emission tomography ( 18 FDG-PET) detects metabolic changes in GISTs in response to treatment with imatinib during the first 1 2 weeks of therapy; anatomic, sizebased changes reflective of response might not be apparent for 4 6 months [3, 4]. Therefore, anatomic criteria need to be revised and/or supplemented to incorporate the increasingly important contribution that newer imaging technologies could make in the assessment of tumor response. Anatomic Response Criteria Two widely employed sets of anatomic tumor response criteria have been published in the past few decades: the World Health Organization (WHO) criteria were published in 1981, while the Response Evaluation Criteria in Solid Tumors (RECIST) were introduced 19 years later

2 Jaffe 15 [1, 2]. The WHO criteria were developed with the intent of enabling international investigators to compare the validity of their results with each other s results [1]. These criteria are based on bidimensional (i.e., the product of the longest diameter and its longest perpendicular diameter) measurements for each tumor, which are mapped into four response categories: complete response (CR), partial response (PR), no change (NC), and progressive disease (PD) [1]. However, because the measuring methods and selection of target lesions were not clearly described in the WHO guidelines, assessment of tumor response was found to have limited reproducibility [5]. In addition, imaging technology was more primitive at the time the WHO criteria were published, so the emergence of new technologies such as multidetector array computed tomography (CT) and magnetic resonance imaging (MRI) raised questions about how to integrate three-dimensional measures into response assessment as defined by the bidimensional-based WHO criteria. The RECIST were developed by the European Organization for Research and Treatment of Cancer (EORTC, in an attempt to simplify measurement and limit potential for overestimation of response rates [2]. These criteria, with advice guidelines for application in complex situations ( Default.htm), represent a simplification of former response assessment methods and are predicated on a concept that unidimensional measurements are as informative as bidimensional measurements. The RECIST reduce tumor measurements into four response categories: CR, defined as the complete disappearance of all target lesions; PR, defined as a 30% decrease in tumor size from baseline; PD, defined as a 20% increase in tumor size; and stable disease (SD), defined as small changes that do not meet the above criteria [2]. Of these, PR and PD are the only truly quantitative categories in that they reflect a detectable percentage increase or decrease in lesion size. As with the WHO response criteria, harmonization of potential threedimensional data produced by modern imaging modalities with the unidimensional-based RECIST remains unfulfilled. In addition, even more advanced imaging technologies, such as spiral CT, 18 FDG-PET, and dynamic MRI, have been introduced and/or refined since publication of the RECIST in the year The RECIST are currently the most widely used criteria in cancer clinical trials. However, the judgmental breadth implied in the RECIST often results in confusion in how to apply response assessment techniques to individual cases and across cancer centers. The definition of a target lesion can also be problematic. The RECIST state that all measurable lesions up to a maximum of five lesions per organ and 10 lesions in total, as representative of all involved organs, should be identified as target lesions. Target lesions should be selected on the basis of size (i.e., those with the longest diameter) and their suitability for accurate repeated measurements. However, in a case like that shown in Figure 1, determining which lesions should be considered target lesions is not clear, and the target lesions selected may not represent the physiologically most important burden of disease. One analysis has estimated that disagreements between independent review panels and site radiologists in tumor response assessment could occur in up to 50% of cases, with the source of such disagreements including variations in examination technique for obtaining images, in lesion selection, and in determining the edges of target lesions [6]. Nontumorous anatomic changes, such as the development of pleural effusions, may also confound evaluation. Moreover, the RECIST do not account for tumor lesion inhomogeneity changes that often occur early on in a variety of treatment regimens. Finally, the use of target lesions in response criteria can affect data auditing. Requiring all assessors to judge the same target lesions can impair the blinding of clinical trials, because the readers must communicate to each other which lesions were previously marked as target lesions. Thus, anatomical tumor response methodology would be vastly improved through the development and validation of clinical trial acceptable methods and standards to incorporate more modern, imaging-based response evaluation. Imaging-Based Evaluation of Response Development of imaging-based surrogate endpoints applicable across multiple trial centers has both strong rationale and appeal. The more rapid and precise evaluation associ- Figure 1. Computed tomography scan of a patient with metastatic lung cancer. The complexity of the lesion shape accompanied by inflammation makes it challenging to distinguish target versus nontarget lesions using the Response Evaluation Criteria in Solid Tumors.

3 16 Response Assessment in Sarcoma Trials ated with validated image data could potentially reduce trial size. This, in turn, could lead to earlier go/no-go decisions on compounds in development, faster regulatory approval, and shorter time to market, all of which would contribute to getting anticancer agents to patients in a shorter time and at a lower cost. However, for image-based response evaluation to be successful, proper surrogate biomarkers must be identified. The definition of a surrogate biomarker is critical: while a biomarker is any measurable characteristic that accompanies a clinical endpoint, a surrogate biomarker is one that substitutes for a clinical endpoint. This distinction has important regulatory implications, because only surrogate biomarkers can function as clinical endpoints, which, if met, may serve as the basis for drug approval [7]. Properly defined outcome data are needed to establish the validity of a surrogate biomarker. Identification of appropriate, disease-sensitive imaging modalities can be key in this process. For example, CT is generally well suited for assessing response to cytotoxic therapy, in which tumors are expected to visibly diminish in size and volume, whereas response to cytostatic therapy such as antiangiogenic agents may be best assessed by imaging techniques, such as PET, that can detect changes in tumor metabolism. Uniform acquisition protocols and analysis of data are also required, but this can be quite challenging across centers, particularly with rapidly evolving imaging technologies and when some data arise from subjective judgments, while other data are acquired in an automated fashion. New Directions in Imaging-Based Evaluations: Implications for Clinical Trials Modern multidetector array CT scanning allows measurement of tumor volume, which could be more informative than bidimensional measurements. As with linear measurements derived from individual two-dimensional CT cuts, decreases in tumor volume generally indicate disease response, while increases imply progression. Volumetric measurements, if reproducibly accurate, provide a more sensitive scale for change assessment compared with unidimensional measurements. For example, if the tumor diameter increases by 26%, the corresponding volume increases by 100% [8]. Volumetric measurement can also be used to more accurately measure and thus characterize asymmetric growth, as well as tumor doubling times, which can provide information about the rate of tumor growth, stability, or shrinkage. Recent advances in CT scanning technology, such as the introduction of 64-slice CT scanners, offer previously unobtainable capabilities for threedimensional reconstruction and volumetric measurement with unrivaled image quality and remarkable speed that minimizes motion and breathing artifacts. However, the implementation of tumor volume calculation using advanced CT scanning techniques in cancer clinical trials has proven challenging thus far. Because the technology is new and not yet widely available, an insufficient number of centers have appropriate scanners to process patients. Ideally, automated techniques should be used to assess subtle changes in tumor volume. However, no fully automated objective methods have been developed, and the semiautomated methods that are being used are relatively time-consuming, labor intensive, and not user friendly. Finally, the inherent heterogeneity of tumors (i.e., hypoxic regions) can confound volumetric measurements. These obstacles will need to be overcome before automated, high-resolution CT scanning can be incorporated into widespread phase III cancer clinical trials. PET scanning can be used to acquire metabolic data about tumors that can complement and/or clarify CT data. 18 FDG-PET, in particular, has been shown to be quite reliable for monitoring tumor response in tumors with high metabolic activity, such as GISTs, during the early stages of treatment [3, 4]. The identification of new imaging agent compounds will likely further expand the utility of PET. For PET scanning to be successfully used for response assessment in cancer clinical trials, the variations that may arise among different manufacturers scanners must be considered. Currently, PET scanners use at least four different types of crystal material that have very different quantum detection efficiencies [9]. PET evaluation can also be subjective: even the standardized uptake value is only a semiquantitative measurement, and while Patlak graphical analysis or other kinetic methods may be more quantitative, they currently are too cumbersome to be used in a clinical trial setting [3, 10]. Thus, as with CT, certain obstacles must be overcome before PET can be fully integrated into response assessment in cancer clinical trials. MRI can also be used to detect and characterize tumors. Dynamic contrast MRI, which allows simultaneous imaging and contrast administration, can be helpful in detecting vascularity. As a low molecular-weight contrast agent passes through tissues, it diffuses out of blood vessels and into the extravascular, extracellular space. Almost half of the contrast agents leak out of blood vessels during the first pass, and the corresponding changes in signal intensity that are acquired before, during, and after injection can be indirectly correlated with physiologic endpoints, including blood flow and vascular permeability [11]. Evaluating these two parameters can provide information about the degree of necrosis in a tumor (i.e., necrotic regions are expected to have low blood flow and low permeability) and about response to antiangiogenic agents [12]. Because The Oncologist

4 Jaffe 17 dynamic MRI data are quantitated into pharmacokinetic enhancement curves, biologically relevant parameters can be assessed independently of scanner strength, scanner design, and imaging methods. This allows for comparisons to be made among institutions in a multi-institutional clinical trial setting [13]. Drawbacks to dynamic MRI include complex data acquisition analysis and the lack of commercially available analysis software. Recent data suggest that magnetic resonance spectroscopy (MRS) may also be useful to predict tumor response to therapy, in a manner analogous to PET. Through preliminary studies done at the University of Minnesota, MRS provided earlier indications of tumor regrowth during treatment regimens than did MRI [14]. U.S. National Cancer Institute/Food and Drug Administration Interagency Oncology Task Force The U.S. National Cancer Institute (NCI) and the U.S. Food and Drug Administration (FDA) have formed an Interagency Oncology Task Force (IOTF) with the goal of getting innovative, safe, and effective treatments to cancer patients as quickly as possible. The NCI Cancer Imaging Program (CIP) is working closely with the FDA to develop validated imaging methods as surrogate biomarkers that can be used in cancer clinical trials. Works in progress include developing volumetric anatomic imaging for oncology that may offer the ability to revise the RECIST; development of standard dynamic (contrast) imaging techniques for oncologic drug development and as a possible surrogate endpoint for drug approvals; validation of 18 FDG-PET for oncologic drug development and as a surrogate endpoint for drug approvals; and development of a pathway for accelerating molecular imaging, including first-in-human studies, in diagnosed cancer patients. The different government agency foci in this initiative are listed in Table 1. The specific objectives of CIP include increasing imaging studies using standardized acquisition protocols in NCI-funded therapy trials, collecting imaging data from all NCI-funded trials, engaging the FDA through the IOTF, developing a cadre of oncology imaging specialists in NCIdesignated cancer centers through the Image Response Assessment Teams program, developing functional imaging committees in all NCI cooperative groups, and developing volumetric and functional RECIST. Conclusions Anatomic tumor response criteria, particularly the RECIST, are often used and historically accepted, because their relative simplicity has aided in the assessment of anticancer drugs in clinical trials. However, the RECIST are not without their limitations, and imaging-based response evaluation is poised to play a pivotal role in response assessment in the 21st century. The next few years should prove to be an interesting, if transitional, time, as newer imaging technologies and uniform acquisition protocols and their integration into accepted tumor response criteria continue to evolve. Table 1. Roles of government agency foci involved in the imaging initiative of the NCI-FDA Interagency Oncology Task Force Division National Cancer Institute (NCI) National Institute for Biomedical Imaging and Bioengineering (NIBIB) National Library of Medicine (NLM) National Science Foundation (NSF) Food and Drug Administration (FDA) National Institute of Standards and Technology (NIST) Abbreviations: CAD, computer-aided diagnosis. Role Development and optimization of cancer-specific CAD methods Development of advanced algorithms and generic image processing methods, code documentation, open source software Open source software and related data processing platforms Advanced algorithm development, specialized hardware, GRID computing resources Development of standards for database development Measurement of performance of application-specific software References 1 Miller AB, Hoogstraten B, Staquet M et al. Reporting results of cancer treatment. Cancer 1981;47: Therasse P, Arbuck SG, Eisenhauer EA et al. New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst 2000;92: Choi H. Response evaluation of gastrointestinal stromal tumors. The Oncologist 2008;13(suppl 2): Van den Abbeele AD. The lessons of GIST PET and PET/CT: A new paradigm for imaging. The Oncologist 2008;13(suppl 2): Park JO, Lee SI, Song SY et al. Measuring response in solid tumors: Comparison of RECIST and WHO response criteria. Jpn J Clin Oncol 2003;33:

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