- Email: [email protected]
39P Methods for monitoring clinical trials
99S
Abstracts
38P THROMEOLYSIS IN ACUTE STROKE POOLING PROJECT (TAS-PP): A PROSPECTIVE POOLED INDIVIDUAL PATIENT DATABASE Catherine Cornu on behalf of the TAS-PP Group
Unit~ de Pharmacologic Clinique Lyon, France There is increasing interest in the techniques of meta-analysis, mostly applied to summary data from clinical trials. This approach has the advantage of enhanced statistical power. However the individual specificity of the patients is not explored. Performing metaanalysis on indivi~J~ patient d~t~ can overcome this deficiency, enables intention-to-treat and subgroup analyses to be performed and various factors to be studied in relation to a specific event. The Thrombolysis in Acute Stroke Pooling Project (TAS-PP) is a prospective pooling project of d~t, from thrombolysis trials in acute ischem/c stroke. The trials which will be included in the meta analysis have not been completed, and therefore, we can attempt to homogenize the protocols and the d~t~ collected. The objective of TAS-PP is to answer two questions: I) is thrombolysis a beneficial treatment in acute stroke for both short-term total mortafity and long-term disability in stroke survivors? and 2) which patients benefit most from the treatment? Trials which can be considered for inclusion are those which are randomized, have a sample size of more than 10, are completed, on-going or planned clhdcal trials in acute ischennc stroke, involving a thrombolytic treatment. The identified "stroke thrombelytic trialists" who collaborate have defined a common core of d~t~ to be collected, and they will identify other trials and approach other trialists. The analysis will be performed using modelling techniques on the individual d~tm, pooled in a common file. The results of the study will be expressed in the form of subgroups with different levels of benefit, in order to define inclusion criteria for a further study to vali~tqte these results. TAS-PP has two active units: 1) The Steering Committee, composed of representatives from each trial, which is responsible for defining the objectives, elaborating the protocol, deciding on future policies and the publishing policy. 2) The Data Handling Unit, which is responsible for the aot~ collection, updating the common file, checking a~t. and running the analyses. The secretariat of the project is located in the same unit.
39P METHODS FOR MONITORING CLINICAL TRIALS L. Douglas Case, Timothy M. Morgan and C. E. Davis
The Comprehensive Cancer Center of Wake Forest University Bowman Gray School of Medicine W"mston-Salem, North Carolina Accumulating d~t~ from clinical trials are usually reviewed multiple times before the study is complete due to the ethic~d concern for the patient's well-being. Investigators do not want to continue trials in which one therapy is clearly superior, nor do they want to continue trials in which there is little hope of showing a benefit. In many cases, continuous monitoring is not practical, and group sequential methods are used. We present optimal three-stage designs with equal sample sizes at each stage. These designs are compared to fixed sample designs, fully sequential designs, designs restricted to use the fixed sample critical value at the final stage, and to modifications of other designs previously proposed in the literature. Typically, the greatest savings realized with interim analyses are obtained by the first interim
100S
Abstracts
look. More than 50 % of the savings possible with a fully sequential design can be realized with a simple two-stage design. Three-stage designs can realize as much as 75 % of the possible savings. Without much loss in efficiency, the designs can be modified so that the critical value at the final stage equals the usual fixed sample value while maintaining the overall level of significance, alleviating some potential confusion should a final stage be necessary. Some common group sequential designs, modified to allow early acceptance of the null hypothesis, are shown to be nearly optimal in some settings. An example is given which illustrates the use of several three-stage plans in designing clinical trials.
40P EVALUATION OF DESIGNS FOR PHASE I CLINICAL TRIALS J. Jack Lee, Terry L. Smith and Dan M. Seraehitopol
University of Texas M.D. Anderson Cancer Center Houston, Texas Phase I clinical trials in cancer research typically involve a small number of patients as the first step to evaluate the toxicity and feasibility of a new therapeutic agent. Traditionally, Phase I trials are conducted in an ad hoc fashion. For example, the "3+3" design calls for three patients to be entered at the star~g dose level, with the next three patients entered at the same or the next higher dose level depending on outcomes at the previous dose level. Recently, model-based approaches such as the continual re.assessment method (O'Quigley et al., Biometrics, 1990) and various modifications have been proposed in the literature. In this presenta~on, we demonsU'ate an interactive computer program for implementing various Phase I designs. The characteristics of each design are summarized. In addition, we compare the performance of the U'aditional design versus the model-based design using data from several Phase I trials conducted at the University of Texas M.D. Anderson Cancer Center. The distribution of the maximum tolerated dose obtained from each design is tabulated and compared to the recommended dose reported in the literature. Guidelines are given for conducting Phase I trials to reach maximum efficacy with acceptable toxicity. 41P A MATHEMATICAL MODEL FOR THE DETERMINATION OF THE OPTIMUM TREATMENT THRESHOLD IN THE PREVENTION OF CARDIAC LIPID RISK
M. Cucherat and J-P Boissel
Un~ de Pharmacologic Clinique Lyon, France Hypercholesterolemiais a "continuous" risk factor for coronary heart disease (CHD). Cholesterol level is a quantitative variable and the relationship between cholesterolemia and CHD risk is also continuous (without a natural threshold). Under these conditions it is impossible to determine objectively the treatment threshold from epidemiological data only. In a cost-effectivenesspopulation-wide approach, we have built a mathematical model of prevention, based on the isotropic hypothesis with the epidemiological risk curve, distribution of serum level in the population, biological efficacy of the treatment (i.e., change in serum lipid level), and costs of screening and treatment integrated. This model was used to simulate the evolution of the cost per coronary event saved as a function of the treatment threshold. The influence of the treatment (cost and biological efficacy), risk and cost of screening were studied.
Abstracts
38P THROMEOLYSIS IN ACUTE STROKE POOLING PROJECT (TAS-PP): A PROSPECTIVE POOLED INDIVIDUAL PATIENT DATABASE Catherine Cornu on behalf of the TAS-PP Group
Unit~ de Pharmacologic Clinique Lyon, France There is increasing interest in the techniques of meta-analysis, mostly applied to summary data from clinical trials. This approach has the advantage of enhanced statistical power. However the individual specificity of the patients is not explored. Performing metaanalysis on indivi~J~ patient d~t~ can overcome this deficiency, enables intention-to-treat and subgroup analyses to be performed and various factors to be studied in relation to a specific event. The Thrombolysis in Acute Stroke Pooling Project (TAS-PP) is a prospective pooling project of d~t, from thrombolysis trials in acute ischem/c stroke. The trials which will be included in the meta analysis have not been completed, and therefore, we can attempt to homogenize the protocols and the d~t~ collected. The objective of TAS-PP is to answer two questions: I) is thrombolysis a beneficial treatment in acute stroke for both short-term total mortafity and long-term disability in stroke survivors? and 2) which patients benefit most from the treatment? Trials which can be considered for inclusion are those which are randomized, have a sample size of more than 10, are completed, on-going or planned clhdcal trials in acute ischennc stroke, involving a thrombolytic treatment. The identified "stroke thrombelytic trialists" who collaborate have defined a common core of d~t~ to be collected, and they will identify other trials and approach other trialists. The analysis will be performed using modelling techniques on the individual d~tm, pooled in a common file. The results of the study will be expressed in the form of subgroups with different levels of benefit, in order to define inclusion criteria for a further study to vali~tqte these results. TAS-PP has two active units: 1) The Steering Committee, composed of representatives from each trial, which is responsible for defining the objectives, elaborating the protocol, deciding on future policies and the publishing policy. 2) The Data Handling Unit, which is responsible for the aot~ collection, updating the common file, checking a~t. and running the analyses. The secretariat of the project is located in the same unit.
39P METHODS FOR MONITORING CLINICAL TRIALS L. Douglas Case, Timothy M. Morgan and C. E. Davis
The Comprehensive Cancer Center of Wake Forest University Bowman Gray School of Medicine W"mston-Salem, North Carolina Accumulating d~t~ from clinical trials are usually reviewed multiple times before the study is complete due to the ethic~d concern for the patient's well-being. Investigators do not want to continue trials in which one therapy is clearly superior, nor do they want to continue trials in which there is little hope of showing a benefit. In many cases, continuous monitoring is not practical, and group sequential methods are used. We present optimal three-stage designs with equal sample sizes at each stage. These designs are compared to fixed sample designs, fully sequential designs, designs restricted to use the fixed sample critical value at the final stage, and to modifications of other designs previously proposed in the literature. Typically, the greatest savings realized with interim analyses are obtained by the first interim
100S
Abstracts
look. More than 50 % of the savings possible with a fully sequential design can be realized with a simple two-stage design. Three-stage designs can realize as much as 75 % of the possible savings. Without much loss in efficiency, the designs can be modified so that the critical value at the final stage equals the usual fixed sample value while maintaining the overall level of significance, alleviating some potential confusion should a final stage be necessary. Some common group sequential designs, modified to allow early acceptance of the null hypothesis, are shown to be nearly optimal in some settings. An example is given which illustrates the use of several three-stage plans in designing clinical trials.
40P EVALUATION OF DESIGNS FOR PHASE I CLINICAL TRIALS J. Jack Lee, Terry L. Smith and Dan M. Seraehitopol
University of Texas M.D. Anderson Cancer Center Houston, Texas Phase I clinical trials in cancer research typically involve a small number of patients as the first step to evaluate the toxicity and feasibility of a new therapeutic agent. Traditionally, Phase I trials are conducted in an ad hoc fashion. For example, the "3+3" design calls for three patients to be entered at the star~g dose level, with the next three patients entered at the same or the next higher dose level depending on outcomes at the previous dose level. Recently, model-based approaches such as the continual re.assessment method (O'Quigley et al., Biometrics, 1990) and various modifications have been proposed in the literature. In this presenta~on, we demonsU'ate an interactive computer program for implementing various Phase I designs. The characteristics of each design are summarized. In addition, we compare the performance of the U'aditional design versus the model-based design using data from several Phase I trials conducted at the University of Texas M.D. Anderson Cancer Center. The distribution of the maximum tolerated dose obtained from each design is tabulated and compared to the recommended dose reported in the literature. Guidelines are given for conducting Phase I trials to reach maximum efficacy with acceptable toxicity. 41P A MATHEMATICAL MODEL FOR THE DETERMINATION OF THE OPTIMUM TREATMENT THRESHOLD IN THE PREVENTION OF CARDIAC LIPID RISK
M. Cucherat and J-P Boissel
Un~ de Pharmacologic Clinique Lyon, France Hypercholesterolemiais a "continuous" risk factor for coronary heart disease (CHD). Cholesterol level is a quantitative variable and the relationship between cholesterolemia and CHD risk is also continuous (without a natural threshold). Under these conditions it is impossible to determine objectively the treatment threshold from epidemiological data only. In a cost-effectivenesspopulation-wide approach, we have built a mathematical model of prevention, based on the isotropic hypothesis with the epidemiological risk curve, distribution of serum level in the population, biological efficacy of the treatment (i.e., change in serum lipid level), and costs of screening and treatment integrated. This model was used to simulate the evolution of the cost per coronary event saved as a function of the treatment threshold. The influence of the treatment (cost and biological efficacy), risk and cost of screening were studied.