Ebook Designing clinical research (3/E): Part 2
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Ebook Designing clinical research (3/E): Part 2
IBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2classic randomized, blinded, parallel group trial: how IO select the intervention, choose outcomes, select participants, measure baseline variables, randomize, and blind. In this chapter, we describe alternative clinical trial designs and address the conduct of clinical trials, including interim mon Ebook Designing clinical research (3/E): Part 2itoring during the trial.ALTERNATIVE CLINICAL TRIAL DESIGNSOther Randomized DesignsThere arc a number of variations on the classic parallel group randEbook Designing clinical research (3/E): Part 2
omized trial that may be useful when the circumstances arc right.The factorial design aims to answer two (or more) separate research questions in a siIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2itamin F. on risk lor cardiovascular events among healthy women (1). The participants were randomly assigned to four groups, and two hypotheses were tested by comparing two halves of the study cohort. First, the rate of cardiovascular events in women on aspirin is compared with women on aspirin plac Ebook Designing clinical research (3/E): Part 2ebo (disregarding the fact that half of each of these groups received vitamin E); then the rate of cardiovascular events in those on vitamin E is compEbook Designing clinical research (3/E): Part 2
ared with all those on vitamin E placebo (now disregarding the fact that half of each of these groups received aspirin). The investigators have two coIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2o test the effect of three interventions (hormone therapy, low-fat diet and calcium plus vitamin D) on a number of outcomes in one cohort (2). A limitation is the possibility of interactions between the effects of the treatments on the outcomes. For example, if the effect of aspirin on risk for card Ebook Designing clinical research (3/E): Part 2iovascular disease is different in women treated with vitamin E compared to those163164 Study DesignsTHE PRESENTTHE FUTUREFIGURE 11.1. In .1 factorialEbook Designing clinical research (3/E): Part 2
randomized trial, rhe investigator (a) selects a sample from rhe population, (b) measures baseline variables, (c) randomly assigns two active interveIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2s, first combining rhe two drug A groups to be compared with rhe two placebo A groups and then combining the two drug B groups to be compared with the two placebo B groups.not treated with vitamin E, an interaction exists and the effect of aspirin would have to be calculated separately in these two Ebook Designing clinical research (3/E): Part 2groups. This would reduce the power of these comparisons, because only half of the participants would be included in each analysis. Factorial designsEbook Designing clinical research (3/E): Part 2
can actually be used to study such interactions, but trials designed to test interactions arc more complicated and difficult to implement, larger sampIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2appropriate for each intervention and multiple treatments may interfere with recruitment and adherence.Ciroup or cluster randomization requires that the investigator randomly assign naturally occurring groups or clusters of participants to the intervention groups rather than assign individuals. A go Ebook Designing clinical research (3/E): Part 2od example is a trial that enrolled players on 120 college baseball teams, randomly allocated half of the teams to an intervention to encourage cessatEbook Designing clinical research (3/E): Part 2
ion of spit-tobacco use, and observed a significantly lower rate of spit-tobacco use among players on the teams that received the intervention compareIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2 and it may better address research questions about the effects of public health programs in the population. Some interventions, such as a low-fat diet, arc difficult to implement in only one member of a family. Similarly, when participants in a natural group arc randomized individually, those who r Ebook Designing clinical research (3/E): Part 2eceive the intervention arc likely to discuss or share the intervention with family members, colleagues or acquaintances who have been assigned to theEbook Designing clinical research (3/E): Part 2
control group. For example, a clinician in a group practice who is randomly assigned to an educational intervention is very likely to discuss this inIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2he effective sample size is smaller than the number of individual participants and power is diminished. In fact, the effective sample size depends on the correlation of the effect of the interventionChapter 11 ■ Alternative Trial Designs and Implementation Issues 165among participants in the cluster Ebook Designing clinical research (3/E): Part 2s and is somewhere between rhe number of clusters and the number of participants (4). Another drawback is that sample size estimation and data analysiEbook Designing clinical research (3/E): Part 2
s are more complicated in cluster randomization designs than tor individual randomization (5).In equivalence trials, an intervention is compared to anIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2this situation, it may be unethical to assign participants to placebo treatment. For example, because bisphosphonates effectively prevent osteoporotic fractures in women at high risk, new drugs should be compared against or added to this standard of care. In general, there should be strong evidence Ebook Designing clinical research (3/E): Part 2that the active comparison treatment is effective for the types of participants who will be enrolled in the trial.1 he objcctiv c of equivalence trialEbook Designing clinical research (3/E): Part 2
s is to prove that the new intervention is at least as effective as the established one. It is impossible to prove that tvvo treatments arc exactly eqIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2e established treatment is no more than a defined amount. If the acceptable difference between the new and the established treatment is small, the sample size for an equivalence trial can be large much larger than for a placebo controlled trial. However, there is little clinical reason to test a new Ebook Designing clinical research (3/E): Part 2 therapy if it docs not have significant advantages over an established treatment, such as less toxicity or cost, or greater case of use. Depending onEbook Designing clinical research (3/E): Part 2
how much advantage the new treatment is judged to have, the allow able difference between the efficacy of the new treatment and the established treatIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2tant problem w ith equivalence trials is that the traditional roles of the null and alternative hypotheses are reversed. The null hypothesis for equivalence trials is that the effects of the two treatments arc not more different than a prcspccificd amount; the alternative hypothesis is that the diff Ebook Designing clinical research (3/E): Part 2erence docs exceed this amount. In this case, failure to reject the null hypothesis results in accepting the hypothesis that the two treatments arc eqEbook Designing clinical research (3/E): Part 2
ual. Inadequate sample size, poor adherence to the study treatments and large loss to follow -up all reduce the pow er of the study to reject the nullIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2gs just represent an underpowered and poorly done study.Nonrandomized Between-Group DesignsTrials that compare groups that have not been randomized arc far less effective than randomized trials in controlling for the influence of confounding variables. Analytic methods can adjust for baseline factor Ebook Designing clinical research (3/E): Part 2s that arc unequal in the two study groups, but this strategy does not deal with the problem of unmeasured confounding. When the findings of randomizeEbook Designing clinical research (3/E): Part 2
d and nonrandomized studies of the same research question arc compared, the apparent benefits of intervention arc much greater in the nonrandomized stIBBIAlternative Trial Designs and Implementation IssuesDeborah Grady, Steven R. Cummings, and Stephen B. HulleyIn the last chapter, we discussed the c Ebook Designing clinical research (3/E): Part 2be serious and not fully removed by statistical adjustment (6).Sometimes participants arc allocated to study groups by a pseudorandom mechanism. For example, every other subject (or ever}' subject with an even hospital record number) may be assigned to the treatment group. Such designs sometimes off Ebook Designing clinical research (3/E): Part 2er logistic advantages, but the predictability of the study group assignment permits the166 Study Designsinvestigator to tamper with it by manipulatinEbook Designing clinical research (3/E): Part 2
g the sequence or eligibility of new subjects.Participants arc sometimes assigned to study groups by the investigator according to certain specific crGọi ngay
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