Abstract
In controlled clinical trials there are usually several prognostic factors known or thought to influence the patient's ability to respond to treatment. Therefore, the method of sequential treatment assignment needs to be designed so that treatment balance is simultaneously achieved across all such patients factor. Traditional methods of restricted randomization such as "permuted blocks within strata" prove inadequate once the number of strata, or combinations of factor levels, approaches the sample size. A new general procedure for treatment assignment is described which concentrates on minimizing imbalance in the distributions of treatment numbers within the levels of each individual prognostic factor. The improved treatment balance obtained by this approach is explored using simulation for a simple model of a clinical trial. Further discussion centers on the selection, predictability and practicability of such a procedure.
Keywords
Related Publications
On the Use of Pocock and Simon's Method for Balancing Treatment Numbers over Prognostic Factors in the Controlled Clinical Trial
One apparent drawback to the use of the method of Pocock and Simon [1975] for sequential assignment in controlled clinical trials, where it is desired to balance treatment numbe...
How study design affects outcomes in comparisons of therapy. I: Medical
Abstract We analysed 113 reports published in 1980 in a sample of medical journals to relate features of study design to the magnitude of gains attributed to new therapies over ...
The Magic of Randomization versus the Myth of Real-World Evidence
Nonrandomized observational analyses have been promoted as alternatives to randomized clinical trials. However, randomization ensures balance between groups, whereas nonrandomiz...
Group sequential methods in the design and analysis of clinical trials
In clinical trials with sequential patient entry, fixed sample size designs are unjustified on ethical grounds and sequential designs are often impracticable. One solution is a ...
Sample Sizes Based on the Log-Rank Statistic in Complex Clinical Trials
The log-rank test is frequently used to compare survival curves. While sample size estimation for comparison of binomial proportions has been adapted to typical clinical trial c...
Publication Info
- Year
- 1975
- Type
- article
- Volume
- 31
- Issue
- 1
- Pages
- 103-103
- Citations
- 2298
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.2307/2529712