John F. Tomera

	When it comes to gaining regulatory approval in a clinical trial, controlling variability is essential, especially in pivotal Phase III trials. It is here that the patient population being studied can not only end up determining the potential market size for a drug, but also impacts the drug's efficacy conclusion to determine if it meets its primary endpoint.

 Performing an independent analysis of the data, such as a patient's diagnostic status, can have a significant impact on minimizing variability and is hence why patient enrollment plays such a key role in determining a trial's outcome. 

	Too often patient enrollment is recognized as a numbers game where the objective of meeting aggressive enrollment rates is mistakenly achieved by enrolling patients who may not always meet all the inclusion or exclusion criteria.

 This is a common systemic issue that may be due in part to sites trying to meet aggressive enrollment goals or clinical operations staff trying to meet corporate mandates. This is usually done one of two ways, either the investigator enrolls a patient who they admit does not meet the inclusion/exclusion criteria and asks for a protocol exemption/waiver, or their view of the subjective patient enrollment data is biased by the interest to push the enrollment rate up. The first is easily tractable since detailed records of the exemption granted by the sponsor are monitored whereas the latter is more problematic, insidious, and requires active detailed monitoring and in many cases would benefit greatly by a blinded independent central review (BICR). Regardless of the cause the result is the same: a decrease in homogeneity of the population. This problem only seems to be growing and, although it is tracked in most Phase III trials by looking at the size of the intent to treat (ITT) population as compared to the per protocol population (PPP), it remains an area of minimal focus. 

	Since most registration trials require that the ITT population be used in the primary analysis, drugs are being evaluated with up to 50% of patients comprising the per protocol population (i.e., total pooled ITT population of 937 patients, of which 493 comprised the per protocol population).

 This added heterogeneity usually means an increase in variability of response and can put meeting the trial endpoints at risk. In addition, the potential for GCP violations due to multiple enrollment exemptions can often cause serious regulatory compliance issues.

	Pre-enrollment BICR of subjective enrollment criteria can play a significant role in controlling study population heterogeneity and has the potential to improve trial outcome. Using a BICR to evaluate patient inclusion/exclusion criteria can bring better standardization to the patients enrolled and mitigate variability. BICR are advocated by the FDA and are commonly performed in oncology registration trials when the trial's primary endpoint is based on tumor imaging.

 BICRs are usually done by contract research organizations (CROs) who manage the process and describe the procedures as it relates to acquiring the data, training the independent reviewers (IR), and monitoring the IR performance during the conduct of the study.

	In most trials there are two opportunities for a BICR to provide objective review of potential trial patients. First is the inclusion/exclusion criteria assessment and then again upon enrollment, but before randomization, when multiple screening tests are performed. These assessments can be either a simple review of subjective criteria (e.g., cardiac echo quality) or a complex review requiring multiple clinical experts and multiple imaging studies (e.g., early Alzheimer's).

	The inclusion/exclusion criteria should be based on both the sponsor's knowledge of the action or effect of the investigational material and on information from prior studies. Exclusion criteria should not be so restrictive that the available population is too limited to obtain the enrollment goal. However, the inclusion criteria should not be so lax that the acceptable population becomes too broad to prove effectiveness of the study article. Once it has been determined that the patient has met the inclusion/exclusion criterion, the patient is enrolled in the study. After enrollment, but prior to receiving on-study treatment, subjects are screened to establish a baseline for their conditions to determine the degree of disease burden so that the patient may be stratified for randomization.

	Imaging studies and pathological assessments are often important subjective assessment parameters that play a role in all parts of a clinical trial (enrollment, on study assessment, and patient outcome). This is most evident in imaging studies where the FDA has commented on the variability of on-site radiological assessment and the need to control variability. Unfortunately, many companies are often in a rush to enroll/randomize patients and thus depend on on-site assessment of disease burden and/or disease staging. This can create problems particularly when the subjective assessment is difficult to determine and requires a great degree of precision.

	Precision is obtained by making multiple independent assessments of a parameter. These assessments are regularly performed by a BICR following a multi-read adjudication process, which is seldom done in a clinical setting. The issue of site interpretational bias due to partial or complete un-blinding of patient treatment arms or pre-existing conditions can confound interpretation. This can be a major issue in open labeled trials, which require a BICR to determine on-study response to treatment. A recent example of this is a hepatocellular carcinoma (HCC) trial in which the site enrolled a patient based on the results of a site read of a liver CT but the CRO sub-specialty radiologists repeatedly indicated that the lesion was just a hemangioma.

 In this case, the patient baseline status can't change and since the patient doesn't have HCC, he/she is assured not to be a responder. One way of handling this issue is to reclassify the patient. This is often done by changing patient status from PPP to ITT populations (see description below). This issue can often be avoided when independent experts are used for both screening and on study reads.

	When the analysis is restricted to the participants who fulfill the protocol in terms of the eligibility, interventions, and outcome assessment, the analysis is known as an "on-treatment", "on-study," or "per protocol" analysis. The per-protocol analysis restricts the comparison of the treatments to the ideal patients; that is, those who adhered perfectly to the clinical trial instructions as stipulated in the protocol. This population is classically called the per-protocol population and the analysis is called the per-protocol-analysis.

	In the ITT population, none of the patients are excluded and the patients are analyzed according to the randomization scheme. Medical investigators have often expressed difficulties in accepting the ITT analysis, even though it is the pivotal analysis for the FDA and EMA. This analysis is generally favored because it avoids the bias associated with the non-random loss of the participants. Nevertheless, the ITT analysis by definition includes patients who don't meet the inclusion and exclusion criteria and may not have the disease the sponsor is targeting (as was the case in the hemangioma example in the HCC trial discussed above). This can have a significant impact on a drug's chance for success. To demonstrate this issue, the following provides an example of how ITT, which is >15% larger than a PPP, can result in a drug not hitting its primary endpoint.

	Assume an open labeled oncology trial where participants are equally randomized into an active control arm and an investigational drug arm. There is an aggressive push for enrollment from the sponsor, and the investigator thinks the test treatment has a much better chance of treating the patient than the control arm treatment. Therefore, he/she decides to enroll more "borderline" eligible participants to the treatment arm than the control arm with the intent of using the new drug to help a wider range of patients.

	The primary endpoint of the trial is to determine if the investigative drug shows superiority for progression free survival (PFS). Based on previous studies, it is estimated that the response rates for the treatment and control arms are 0.5 and 0.4 respectively. As such, 390 participants are enrolled in each study arm in order to obtain 80% statistical power for the primary endpoint analysis.

	Assume that a certain percentage of the participants were retrospectively found to be either tumor-free or non-responsive to treatments because the patients did not have target disease and a slightly higher percentage of these deviations were found in the treatment arm due to investigator bias (i.e., 60% vs. 40% for control). These participants will therefore not be able to show full response; however they will still be included as part of the ITT analysis. PFS rates in both arms will drop, making it more difficult to show superiority and diluting the treatment effect.

	We are testing the hypothesis that the test arm is superior to the control arm, with an alpha of 0.05. We assume that the response rates for the eligible patients in each arm will be consistent with past studies. Figure 1 demonstrates how the eligibility status of our patient population can effect the ability of a trial to show a significant treatment effect. The horizontal line represents the 0.05 alpha level, p-values to the right of the line are not statistically significant. If 15% of the participants are found not to be tumor-free upon enrollment, the expected significance of the treatment effect is borderline at the 0.05 level (p-value=0.048). If the percentage rises to >15%, the effect is not significant.

	Differences between institutional assessment (i.e., on-site reads) and BICR have been observed in studies and have been a topic of recent debate, particularly as it relates to on study progression of disease as determined using radiological assessments.

 The focus of this debate is centered on informative censoring of a process that does not apply to enrollment assessment.

	Although much attention has been paid to the need to standardize the performance and acquisition of imaging in oncology trials, the on-site image evaluation process remains much less controlled. Usually, these latter evaluations are performed by personnel with variable medical imaging experience who have not gone through detailed training and whose performance is not tested regularly. Typically, there is a pool of readers attached to each site and up to a few hundred readers in total who make measurements and complete case report forms. All too frequently, radiologists are not co-investigators and have not signed the FDA Form 1572, so there is minimal imaging oversight and review on performing the image acquisitions. Additionally, there is often no dedicated training for performing the image evaluations that conform to the requirements of a well-controlled multi-center trial (e.g., Response Evaluation Criteria in Solid Tumors, Cheson, etc.). While the standard of care for clinical interpretation of images by a radiologist at a site may be sufficient for patient management, a radiologist's clinical report is generally insufficient for selecting and measuring lesions required in a clinical trial.

	In contrast, in independent blinded evaluations, images on which efficacy is based are almost always read by radiologists who are trained in the related specific indication. Prior to the readers beginning evaluation of the images, they are trained and tested in a standardized, validated and documented fashion. These central reviews are conducted by a small number of reviewers with specific expertise, thus lessening measurement variability. Also, prospective trial-specific training and testing of readers further reduce measurement variability. Most importantly, the central review complies with the regulatory training requirement to "train the qualified readers prospectively."

 More than 15 years ago, it was recognized by industry, FDA, and other regulatory bodies that if image evaluations were to be used as a measure of efficacy, a controlled evaluation process was required. Not much has changed in the quality of site reads since that time.

	The problem with trying to understand the added value of independent assessment is complicated by the difference between degrees of independence (i.e., lack of complete independence of the site assessment compared to the complete blinded assessment performed by an independent core laboratory). The integrity of the blinding to treatment process can sometimes decrease accuracy of assessment and this trade-off must be compared to the importance of obtaining the data without bias. Since the objective of pivotal trials is to perform a study for regulatory approval the goal of the study is not the practice of clinical medicine but more in the domain of regulatory science in which removal of bias is an important component. This concept does not resonate with everyone, particularly healthcare providers, but the effects of bias can have a major impact on results. For example, when comparing site readers to an independent blinded read in a dementia trial using SPECT perfusion imaging, the data was similar and the variability between site reads and independent reads were fairly uniform across centers with one noted exception: a site reader who had almost a perfect positive predictive value for diagnosing Alzheimer's disease. After investigation, it was determined that >90% of his patients came from a longitudinal Alzheimer study being conducted at the hospital. This example demonstrates how controlling for bias can have a profound effect on reader performance, thus necessitating the need to measure variability. The statistical measurements of variability between readers (inter-reader variability) and within readers (intra-reader variability) is something that is often not well understood and seldom done when assessments are performed in clinical practice or when on-site assessments are used in clinical trials. This is unfortunate and can be a problem because sites are trained at the beginning of a trial; that is when terms are defined and criteria are set for making an assessment. It is well known that if those criteria differ from criteria used in clinical practice, a process called definitional drift can occur over time.

	Two examples which emphasize the need to focus on subspecialty trained experts to preclude issues that could involve misinterpretation of subjective data include the following:

		Hemangioma vs. hematoma. From a white paper concerning the European Congress of Radiology 2010 in Vienna, it was reported that Gerd Schueller, MD, a radiologist at the Medical University of Vienna stated that for oncologic imaging, and for that matter emergency imaging, hemangioma of the liver does not look like a hematoma of the liver, and that "we have to learn the differences."

 The need for subspecialty expertise is real and cannot be ignored.

		Breast cancer diagnosis variability. A disfiguring lumpectomy has occurred only for the patient to learn that there was no cancer present.

 Even though rare, this is not an entirely uncommon event. Such events can occur when the variability of either pathological or radiological assessments are not controlled. Implications of uncontrolled variability per pathological

 assessments collectively compound maximum diagnostic performance to poor prognostic ability. To put it another way, when the false positive rate is 10% for both radiological and pathological assessments, maximum diagnostic performance can only be approximately 81%. Consequently, the inherent lack of control of variability within each subspecialty discipline (i.e., radiology and pathology) lessens the integrity of the diagnosis as well as the prognosis. A pathologic diagnosis is the foundation upon which all other treatment decisions are made and with breast cancer, the pathology dictates the use of potentially curable therapy. Incorrect pathologic diagnoses may lead to negative outcomes as serious as failure to treat a missed case of breast cancer or provision of unnecessary surgery, chemotherapy, and radiation. In 2010 a review

 of 2,564 cases from the Sloane Project reported that in 30% of patients undergoing breast-conserving-surgery for ductal carcinoma in situ, preoperative imaging underestimated the extent of disease resulting in a requirement for further surgery.

	It's not necessary for all subjective assessments to undergo a BICR process, but assessments that are both difficult to make because they require extensive experience and those that are part of important endpoints of the trial can realize tremendous value from working with a CRO whose expert independent reviewers are subjected to a rigorous training and variability testing. These factors combined with a multi-read adjudication process will maximize the potential for obtaining unbiased accurate data with maximal precision. Since Phase III trials are large (in some cases 100 sites and lasting several years), it would be a logistical nightmare to have to perform intra- and inter-reader variability testing with 100 local reviewers that may require retraining throughout the course of the trial. The BICR read team is much smaller and thus facilitates the ability to determine variability and to retrain as a team or individually if needed.

	Identifying what subjective assessments are important to have independently reviewed is not always straightforward, although it is often clear what assessment(s) will have an impact on trial outcome. The variability of making that assessment is not often well understood. Understanding variability requires statistically accounting for chance agreement. This is where experienced CROs that have done these diagnostic assessments can provide value. CROs provide the experience necessary to collect variability data and understand the reproducibility of the measurement since they regularly deal with a limited pool of independent reviewers (i.e., radiologists and pathologists) and have criteria for testing and retraining. If needed, they can determine if definitional drift occurs by performing intra-reader variability testing.

	CROs also possess the knowledge and experience in both determining if the subjective assessment needs to be independently reviewed and the understanding of what type of training and retesting of independent reviewers needs to be performed during the trial so that precision and accuracy are maintained. However, since the eligibility criteria often requires experts from multiple disciplines who have experience in diagnosing uncommon diseases, the CRO has to have the ability to leverage the subspecialty experts who are needed to make the independent assessments. This requires both strategic relationships with leading academic and tertiary care institutions and advanced digital portals so that a review of images and other data can be done at remote locations.

	An experienced CRO can play an important role in strictly enforcing per-protocol criteria determining what patients get into the trial. Through their enforcement of strict criteria for inclusion and exclusion, as well as through their ability to manage and facilitate a relationship involving subspecialty screening, CROs can positively impact trial outcomes to be more robust, homogeneous, and aligned to regulatory compliance with all bias minimized.

 MS, is Associate Director of Biostatistics and Data Management, and 

 PhD, is Director of Regulatory Affairs and Associate Medical Director at WorldCare Clinical, 7 Bulfinch Place, P.O. Box 8908, Boston, MA.

	*To whom all correspondence should be addressed.

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Articles

Partnering with CROs and using a blinded independent central review can increase trial success.

Enrollment: More Than Numbers

Hstorically, the endpoint gold standard for demonstrating clinical benefit in oncology drug trials has been and still is overall survival (OS). From the FDA perspective, OS provides the most objective and comprehensive means of evaluation, but the analysis is not without its drawbacks. 

Because evaluation of OS requires large patient numbers and much longer follow-up compared with other endpoints, data receipt is delayed. Trials based primarily on survival are therefore always more expensive and time consuming, and FDA approval takes longer than when based on studies using other accepted primary efficacy endpoints, such as time to progression (TTP) or objective response rate (ORR). Plus, overall survival may be confounded by subsequent therapies, unlike endpoints such as TTP or ORR, which are often used as surrogates for OS in patients with solid tumors. 

These tumor assessment endpoints are less expensive and much more time effective than OS, and are, therefore, an attractive alternative for demonstrating efficacy. Because they are based on subjective evaluations (i.e., clinical or radiological observations), however, they are also less objective than overall survival and must be used in accordance with strict quality control measures to ensure validity. 

Specifically, certain design features can be incorporated into a clinical trial to minimize bias and increase precision and accuracy of potentially subjective observer-dependent assessments. To increase uniformity of efficacy endpoints based on tumor assessments, sponsors and CROs must pay special attention to the blinding of patient data. Accordingly, the use of central (external) review committees is recommended, because without independent central review, bias stemming from the sponsor or study monitor's familiarity with particular patients may influence endpoint assessments. Moreover, the FDA can and will question the validity of the conclusions drawn if stringent processes are not put in place to reduce the potential for bias. 

Efforts to encourage uniform interpretation of endpoint data among assessors and to minimize assessment variability across the study should be part of the study design prior to patient enrollment. A good example of a design intended to reduce variability of endpoint assessments is a double-blind read with adjudication. By this process, radiological images are initially assessed by multiple, often two, independent blinded reviewers. If the reviewers disagree, then a third adjudicating assessment (i.e., a tie-breaker) is made by an additional reviewer who may or may not be blinded to prior assessments. To further minimize variability, all independent reviewers should be uniformly trained and periodically tested to evaluate intra- and inter-reader variability. 

Implementation of double-blind read with adjudication in Phase III oncology trials became more widespread in the late '90s based, in large part, on the need for accurate, unbiased radiological assessment in patients with solid tumors. This need arose partly because of the addition of Subpart H to new drug approval regulations promulgated in 1992, which allowed for accelerated drug approval using surrogate endpoints involving radiological assessment of tumor sizing. By the end of the millennium, however, it had become apparent that although endpoints such as ORR can support regulatory approval in select solid tumors, relief of tumor-related symptoms and drug toxicity should also be considered when making approval decisions. 

Moving into the 21st century, solid tumor trials started using independent endpoint assessment committees (EACs) that used the data from the independent imaging assessment committee in conjunction with information from sites. Although these endpoint assessment and adjudication committees use a combination of independent blinded imaging data and site data, their goals and processes are the same as the independent imaging assessment committee, and their determination of response is often positioned as the primary efficacy result of a Phase III trial. 

This is particularly important because tumor response alone is not always sufficient data for regulatory review. The FDA and other regulatory agencies are looking increasingly to a more objective and encompassing view of the drug's effect, and the use of the EAC offers an evaluation of this efficacy. Data for regulatory submission is not only comprised of bias-free tumor assessment with standardized quantification (e.g., WHO or RECIST criteria), but must also include clinical and pathology data to confirm the radiological analysis. 

Not only do EACs reduce physician bias (blinded reviews coupled with off-site specialists serve to eliminate the potential for prior knowledge of the status of the patient) but they also help to overcome the limitations inherent in imaging that may make precise diagnosis difficult. Especially valuable for subjective endpoints, they provide a far more complete method for determining total tumor and drug effect when a complicated definition of efficacy is required. 

Still relatively novel, EACs are most prevalent in oncology trials, although the FDA's push toward more robust and definitive datasets for regulatory approval means that they will become important to all therapeutic areas in the future. 

Current FDA efforts to draft guidance documents for EACs closely resemble those for cancer endpoints in clinical trials, including survival, tumor response, response duration, relief of symptoms, or composite clinical benefit endpoints. The FDA has intended to develop the series of guidances on oncology endpoints through a process that includes public workshops and discussions before its Oncologic Drugs Advisory Committee, and each subsequent guidance is to focus on endpoints for specific cancer types to support drug approval or labeling claims. 

For oncology trials, the EAC is defined by the oncologist(s), who utilizes data beyond radiology images, including clinical data, pathology results, and other physical measurements (e.g., skin lesions for cutaneous lymphoma, etc.) to more holistically determine the disease status of the patient. Specifically, board-certified oncologists are required, but it is also often of value to have radiology and pathology representation on the committee. All members must be trained under an EAC chair to minimize variability among assessments and to determine the different roles each clinical specialist plays in them. 

The EAC chair should be a member of the committee and will be the point of authority for determining information needed for assessment (i.e., adverse events, histology, calibrated photos, magnetic resonance imaging, etc.). They  should work with the imaging CRO, sponsor, FDA, and radiologist to design the EAC charter, which is essential to ensuring unbiased assessment of all clinical outcomes. Specifically, this responsibility includes development of a decision algorithm for response assessment and determination of work load and time estimates for all committee members. Once the charter and training and testing programs have been designed, full training commences and the program is put into operation. 

Objectivity of the earlier mentioned guidances and workshops is especially critical in fields in which endpoints are determined by clinical or radiological examinations, rather than by predefined laboratory measurements. This is where an independent EAC can be invaluable. Through a charter, EACs can facilitate an unbiased assessment of clinical outcomes in a multicenter Phase III oncology trial to enable a uniform, controlled-assessment process that is independent of the sponsor. Most importantly, the endpoint assessment and adjudication committee charter enables objectivity of endpoint assessment and approximates the critical review that the FDA might impose on clinical endpoint data. The endpoint assessment and adjudication committee charter should be reviewed rigorously in consultation with the FDA, resulting in a charter that may prove to be a useful example in generating independent assessment of pivotal clinical outcomes.

For Phase III registration trials, regulatory agencies must be able to reach objective and definitive conclusions from data. Independence and consistency in the interpretation of the clinical endpoints across different geographic areas and over the course of the study is a primary challenge that can be met by using a central assessment and adjudication committee. The successes of central review committees and, by extension, the success of the trials, depend on prospectively defined procedures, which are agreed upon by the FDA. In addition, the FDA prefers that radiological assessments be done by a central review. 

This role is almost exclusively performed by an imaging core laboratory. Imaging core laboratories or central imaging laboratories have historically been focused on managing the collection of consistent, high-quality imaging data and ensuring minimal variability through a central reading committee. Integration of clinical data with radiological data is often required to make an assessment, and thus quality control procedures, similar to those for imaging data, should be implemented. 

Additional important considerations, such as defining a procedure for adjudication between a site physician's assessment and assessments made by a central review committee, may also need to be addressed. These adjudications can be very complicated and must be prospectively defined and agreed upon by the FDA in order for them to have any regulatory value. 

If implemented properly, the use of an imaging CRO or an imaging core lab helps minimize the possibility of sponsor bias in the assessment process. A sound data management and statistical analysis plan developed by both parties at the outset of the trial should be in effect throughout and should be designed to prohibit sponsor access to the data until the final outcome is determined. Only when the assessment portion of the trial has closed is it appropriate for the EAC to share conclusions with the sponsor. This way, physicians who help deliver the subject's day-to-day care do not perform assessment of outcomes, and the application of uniform response criteria across all assessment individuals is feasible. 

The technological approach that a CRO takes can have a critical impact on the successful implementation of an EAC and subsequent speed of potential therapeutic approval. The right approach can help facilitate the coordination of data collection and the integrated assessment process to optimize workflow and ensure data validity. A fully digitized process that removes bias in document data handling is especially important for regulatory submission, and a CRO with an automated data management system in place can streamline all data capture and transmission, while displaying and launching all the relevant data from the electronic case report form (see Figure 1). This usually includes clinical site data, independent radiological assessments, and pathology reports with histology images. For melanoma trials, skin lesion images with annotations and measurement will also be required. 

Portals that are part of a larger, Web-based, auditable technology can provide a central point for all trial activity and allow project managers, EAC members, and on-site clinicians to coordinate the assessment procedure. Particularly important are automated procedures for quality control, such as the ability to determine the need for adjudication on a specific case and to forward the image to an appropriate adjudication reviewer. This way, the adjudication reviewer can be distinct from the primary reviewer and can possess specified qualifications (e.g., certain level of training and/or experience). 

These kinds of specialized capabilities will become increasingly important as clinical data and the accompanying reports go digital. Additionally, the ability to provide a digital audit trail coupled with an interactive database that combines clinical information with images, EAC and adjudication results will be a necessity for FDA submission and approval moving ahead. 

Endpoint assessment and adjudication committees are helping to reformat the landscape of oncology drug development. Understanding how EACs fit into the trial process and their potential for improving the chances for regulatory success will become a priority for all oncology sponsors in the coming years, and so the quality control measures and technology requirements necessary for their effective implementation demand our paramount attention. 

PhD, is Director of Regulatory Affairs and Associate Medical Director at WorldCare Clinical, 7 Bulfinch Place, P.O. Box 8908, Boston, MA 02114.

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How independent endpoint assessment committees can overcome imaging limitations.