Statistical significance equivalence

The following example is based on a risk assessment of di(2-ethylhexyl) phthalate (DEHP) performed by Arthur D. Little. The experimental dose-response data upon which the extrapolation is based are presented in Table II. DEHP was shown to produce a statistically significant increase in hepatocellular carcinoma when added to the diet of laboratory mice (14). Equivalent human doses were calculated using the methods described earlier, and the response was then extrapolated downward using each of the three models selected. The results of this extrapolation are shown in Table III for a range of human exposure levels from ten micrograms to one hundred milligrams per day. The risk is expressed as the number of excess lifetime cancers expected per million exposed population. 

The interaction of /2-hexane with toluene and trichloroethylene has also been examined in volunteers (Baelum et al. 1998). Exposure in these experiments was via a gastric feeding tube at controlled rates equivalent to what the authors stated would be delivered to the liver by inhalation exposure at Danish occupational exposure limits (50 ppm /7-hexane. 50 ppm toluene, and 30 ppm trichloroethylene). Coexposure to toluene and trichloroethylene slightly increased the area under the curve (AUC) representing concentration versus time for end exhaled /2-hexane air concentration, but urinary excretion of 2,5-hexanedione was unchanged. The only statistically significant interaction observed with /2-hexane was an 18% decrease in the urinary excretion of hippuric acid, a toluene metabolite. 

The statistical significance of a computed difference is best quantified in terms of confidence intervals for the means (CLM). If the mean of a profile T falls into the CLM of profile R , both may be regarded as equivalent. For in vivo data, an acceptance limit of 20% seems to be generally accepted for in vitro data, this would be unnecessarily wide and 5% appears more reasonable. 

The licensee shall establish and maintain a statistical control system including control charts and formal statistical procedures, designed to monitor the quality of each type of program measurement. Control chart limits shall be established to be equivalent to levels of (statistical) significance of 0.05 and 0.001. Whenever control data exceed the 0.05 control limits, the licensee shall investigate the condition and take corrective action in a timely manner. 

The parameters examined included WBC, lymphocyte levels, serum immunoglobulin levels, and lymphocyte subsets. The mean dioxin equivalent concentration (TEQ, includes CDDS, CDFs, and dioxinlike PCBs) in blood (lipid basis) from fish eaters (n=7) was 64 pg TEQ/g (range, 18-88 pg/g) compared to 21 pg TEQ/g (18-33 pg/g) for controls (n=4). CDDs and CDFs were the major contributors to the total dioxin equivalents in blood. Of all the parameters examined, only the level of NK cells was reduced in fish eaters, but the difference between groups was not statistically significant. No correlation was found between blood levels of 2,3,7,8-TCDD and the reduction in NK levels, but weak correlations existed between the latter and some non-ortho-PCB congeners and p,p -DDT. 

This chapter introduces basic concepts in statistical analysis that are of relevance to describing and analyzing the data that are collected in clinical trials, the hallmark of new drug development. (Statistical analysis in nonclinical studies was addressed earlier in Chapter 4.) This chapter therefore sets the scene for more detailed discussion of the determination of statistical significance via the process of hypothesis testing in Chapter 7, evaluation of clinical significance via the calculation of confidence intervals in Chapter 8, and discussions of adaptive designs and of noninferiority/equivalence trials in Chapter 11. 

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