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j. Soc. Cosmet. Chem., 48, 283-288 (November/December 1997) Meta-analysis is a cost-effective tool for estimating mildness differences P. B. NEUMANN, K. D. ERTEL, B. H. KESWICK, and G. Y. RAINS, The Procter & Gamble Company, Sharon Woo& Technical Center, 11511 Reed Hartman Highway, Cincinnati, OH 45241. Accepted for publication December 1, 1997. Synopsis Meta-analysis is a quantitative method of combining results from independent studies to form an overall conclusion based on all available data. The objective of this research was to validate the application of meta-analysis as a tool to estimate treatment differences over a series of small, randomized, blinded, pilot studies that followed the same protocol. Three forearm controlled application technique (FCAT) screening studies were conducted to compare dryness and lBS capacitance differences induced on forearms treated with two personal cleansing bars. In each study, subjects' forearms were washed twice daily for five days on randomly assigned fixed volar sites according to a procedure that simulates normal consumer use of personal cleansing bars. Visual dryness and lBS capacitance data were collected at baseline and after five days. Both weighted and unweighted meta- analyses were performed to estimate the difference between the two treatments. An FCAT study that enrolled 105 subjects was then conducted to compare the same two cleansing bars. Meta-analyses estimates of treatment differences derived from the screening study data closely paralleled the estimates obtained in the larger study. The visual dryness difference was estimated to be 0.167 + 0.079 by the weighted meta-analysis and 0.168 + 0.080 by the unweighted meta-analysis. P-values were 0.035 and 0.036, respectively. The visual dryness difference was estimated to be 0.194 + 0.040 by the larger study. For IBS capacitance, the weighted meta-analysis estimated the difference between treatments to be -0.039 + 0.013 (p-value = 0.004) and -0.042 + 0.015 (p-value = 0.006) for the weighted and unweighted meta-analysis, respectively. The larger study estimated the treatment difference to be -0.023 + 0.004 (p-value 0.0001). This example demonstrates that estimates obtained from studies pooled by meta- analysis can adequately predict the results obtained from a single large-base-sized trial. INTRODUCTION The purpose of this article is to demonstrate with a practical example how closely estimates of treatment differences derived by pooling data from several small clinical trials correspond to results obtained from a larger clinical trial when the studies are all conducted according to the same protocol. Meta-analysis is a statistical method for systematically pooling data from a series of studies to obtain a more robust estimate for a treatment effect than could be obtained from an individual study. Meta-analysis techniques to combine studies in a statistically 283