Clinical trials and statistical analyses: what should dermatologists look for in a report?
Clinicians need to evaluate the quality of individual clinical studies and synthesize the information from multiple clinical studies to provide insights in selecting appropriate therapies for patients. Understanding the key statistical principles that underlie a clinical trial and how they may be implemented can help clinicians properly interpret the efficacy and safety findings of clinical trials. Several factors should be considered when evaluating clinical studies reported in the literature, as important differences might exist among reported studies, thereby impacting the reliability of their findings. Studies vary in terms of study design, conduct, analysis, and presentation of findings. The key features to consider when evaluating clinical trials are inferential intent (exploratory versus confirmatory), choice of control group, randomization, extent of blinding, prespecification of analyses, appropriate handling of missing data, and multiple end points. Making comparisons across studies is extremely difficult and rarely statistically justified. However, this article will point out issues to keep in mind when evaluating multiple studies, such as variations in design and study populations.
Alosh
Mohamed
M
Division of Biometrics III, Office of Biostatistics, Office of Translational Sciences, CDER, FDA, Silver Spring, Maryland, USA. Alosh@fda.hhs.gov
Fritsch
Kathleen
K
Soukup
Mat
M
Wilkin
Jonathan
J
D002986:Clinical Trials as Topic / Q000379:methods* / Q000592:standards*; D003627:Data Interpretation, Statistical; D003880:Dermatology; D006801:Humans; D012871:Skin Diseases / Q000628:therapy*