Statistics in medicine
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Statistics in medicine · Mar 1993
ReviewData monitoring and interim analyses in the pharmaceutical industry: ethical and logistical considerations.
The characteristics of data monitoring and the need for the use of data monitoring committees in clinical trials sponsored by the pharmaceutical industry differ from those of trials sponsored by government. Data monitoring is a continuous process in industry trials due to the regulatory requirements and the need to more thoroughly evaluate safety of new compounds. As part of this process, interim analyses are employed to make decisions about treatment effects. ⋯ A number of examples of interim analyses, with and without data monitoring committees, are discussed. Issues surrounding the need for external data monitoring committees and recommendations are presented. In particular the issues of sponsor participation in the data monitoring committee and controls of the decision making process are considered.
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Statistics in medicine · Mar 1993
Some FDA perspectives on data monitoring in clinical trials in drug development.
The FDA's interest in data monitoring of clinical trials derives from its public health responsibility to assure the safety and efficacy of new drugs based on evidence from adequate and well-controlled studies. Therefore the FDA is concerned that clinical trials of new drugs are designed and carried out in a manner that will insure the integrity and validity of study inferences. ⋯ This paper describes relevant aspects of the regulations and guidelines, some concerns the FDA has with regard to monitoring of both government- and industry-sponsored trials and the consequences of early termination of trials of new drugs in the investigational and marketed stages. Comments include advice on communication between the FDA and data monitoring committees.
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Statistics in medicine · Jun 1992
Analysis of variance for repeated measures. Data: a generalized estimating equations approach.
Various techniques are available for the analysis of repeated measures data, and the appropriate choice depends on distributional assumptions and study design features. A correct analysis must account for potential dependence between repeated observations on the same subject. ⋯ Computations for fitting this type of model are exceptionally simple. Numerical examples suggest that the proposed approach yields estimation and hypothesis testing results consistent with more specialized methods.
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This paper reviews changes in the use of statistics in medical journals during the 1980s. Aspects considered are research design, statistical analysis, the presentation of results, medical journal policy (including statistical refereeing), and the misuse of statistics. Despite some notable successes, the misuse of statistics in medical papers remains common.
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In a clinical trial one scale of pain relief is scored backwards relative to another (high on one corresponding to low on the other), with a consequent large negative correlation. But two derived scales of total pain, obtained by multiplying average pain relief on each scale by duration of pain (common to both pain relief measurements) gave an almost zero correlation. This apparent contradiction is explained by the inverse relationship between the pain relief scales and the large differences in duration of pain experienced by the patients.