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Clinical Trial Design

Clinical Trial Design

From the abstract by Eva Szabo, National Cancer Institute, Bethesda, MD:

“Traditional cytotoxic cancer therapy drug development has tended to follow a well established clinical pathway with a sequential series of clinical trials progressing from phase I pharmacokinetic and safety studies through phase II preliminary efficacy trials to phase III definitive efficacy studies comparing the new treatment to standard of care.

Preventive drug development has been far less regimented. Agents for prevention are frequently developed primarily for other indications (e.g., hormonal agents such as Tamoxifen, raloxifene, and finasteride) and their applicability to cancer prevention is uncovered through secondary endpoint analysis of clinical trials being performed for other indications or through mechanistic considerations…

The decision to begin a phase III cancer prevention trial should therefore be based on a thorough evaluation of all available data, including consideration of missing data.

Data providing the scientific rationale for a specific study falls into three main categories. These include preclinical information such in vitro (e.g., cell line) and animal model studies, observational data from cohort and case-control studies, and clinical trials outcomes from early phase cancer prevention trials and secondary endpoint analysis from other randomized controlled trials.

Not all data is equally informative and conflicts from different data sets must be resolved.

Furthermore since information from one or more of these categories is frequently not available, one must decide whether the rationale for a study is sufficiently strong to proceed or if the missing data needs to be generated prior to beginning a large scale clinical trial.

In addition to thoroughly examining the scientific basis for a trial, of critical importance is the assessment of toxicities, both in terms of severity and frequency of occurrence during short-term and long-term treatment.

The toxicities must be balanced with the short- and long-term risks of the cohort to be targeted for intervention. Known safety of an intervention is insufficient information for justification of clinical trials, although the lack of safety information needs to be dealt with appropriately prior to opening phase III trials.

The recent identification of significant cardiovascular risks with long-term (but not short-term) treatment with the Cox-2 inhibitors rofecoxib and celecoxib underscores how frequently long-term safety data is lacking…

The decision to proceed to any clinical trials should …involve consideration of both supportive and negative data in an objective manner though a formal assessment program”.

Dr. Szabo suggests that substances/agents that impact on many different types of cancer are of great interest even if the impact is lower than agents that target single disease areas.

J.Jack Lee, University of Texas, MD Anderson Cancer Ctr, Houston, wrote “Unique challenges of cancer prevention trials include: low incidence of cancer during the trial, slow process of cancer development, targeting relatively healthy population, and complex modality of interventions including behavior/lifestyle changes etc…

“Adaptive randomization, is ethically appealing because: (a) baseline adaptive randomization can ‘match’ subjects with most promising treatments according to the subjects’ baseline biomarker profiles.

This one step toward the development of ‘personalized medicine’. (b) outcome-based adaptive randomization can allocate more subjects to the more active arm(s) based on the available data”

David Ransohoff, Univ of North Carolina, Chapel Hill spoke about the use of biomarkers in clinical trials. He pointed out that there is a history of strong initial claims over validity of a marker, but not reproducible in subsequent research.

The rules of evidence for diagnosis and prognosis are not as well developed as for studies of therapy. He spoke about many common errors including chance, bias, and generalizability. He reminded the audience that a type I error is a false positive while a type II is a false negative.

He reiterated what all speakers said that identifying and defining the high risk population is critical and there must be well-defined endpoints.

Frontiers in Cancer Prevention Research, 2005

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