Artikel
Design and statistical methods for rare disease studies: A literature review
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Veröffentlicht: | 20. September 2011 |
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Gliederung
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To obtain valid and convincing results in interventional and epidemiological studies, it is essential that the study population is of sufficient size. For rare diseases, it is often problematic to recruit enough patients for a study, despite long recruiting phases and incorporating multiple centers. Additional problems when considering rare diseases are in many times a lack of placebo controls due to ethical reasons and the absence of a gold-standard for therapy, as the course as well as treatment of the diseases are often not well-understood. From a statistical point of view, some of these problems can be overcome by using specific study designs and statistical methods for the data analysis, that typically aim on increasing the power of the study. In a literature review, we investigate the design and methods of recently published studies on rare diseases, as well as statistical literature and guidelines on studies of rare diseases or studies with small number of observations. As a first attempt, all research articles published in the “Orphanet Journal of Rare Diseases” and in “Rare Tumors” were examined. Many of them are case studies or include descriptive statistics only. Another big part are observational studies based on registry data, where the sample size is naturally limited. In almost all articles found, standard statistical methods are used for data analysis. In a second part, methodological papers were considered. Often, the statement can be found that there are no designs specifically for rare disease studies and that all designs, that are recommended for small samples, can theoretically be used for large samples as well, even though they are typically more complex, as e.g. adaptive designs or cross-over trials. Only few statistical methods are developed explicitly for the application in rare diseases, but some considerations and modifications on the application of standard methods to small sample sizes can be found. Based on the investigated articles published in medical journals, we think that amongst medical researchers there is only few awareness on the statistical possibilities to improve the evidence of small sample studies. Apart from that, we observed a lack of systematic investigation of the design and the statistical methods for rare disease studies, so further research would be desirable. However, general recommendations are difficult in the field of rare diseases, as situations and sample size numbers vary extremely.