A technique for population pharmacody nantic analysis of concentration-binary response data
Background- Pharmacodynamic data frequently consist of the binary assessment (a "yes" or "no" answer) of the response to a defined stimulus (verbal stimulus, intubation, skin incision, and so on) for multiple patients. The concentrationeffect relation is usually reported in terms of C50, the drug concentration associated with a 50% probability of drug effect, and a parameter the authors denote y, which determines the shape of the concentration-probability of effect curve. Accurate estimation of y, a parameter describing the entire curve, is as important as the estimation of C50, a single point on (his curve. Pharmacodynamic data usually are analyzed without accounting for interpatient variability. The authors postulated that accounting for interpatient variability would improve the accuracy of estimation of γy and allow the estimation of C50 variability. Methods: A probit-based model for the individual concentration-response relation was assumed, characterized by two parameters, C50 and γ. This assumption was validated by comparing probit regression with the more commonly used logistic regression of data from individual patients found in the anesthesiology literature. The model was then extended to analysis of population data by assuming that C50 has a log-normal distribution. Population data were analyzed in terms of three parameters, 〈C50〉, the mean value of C50 in the population; ω, the standard deviation of the distribution of the logarithm of C50; and γ. The statistical characteristics of the technique were assessed using simulated data. The data were generated for a range of γ and ω values, assuming that C50 and γ had a lognormal distribution. Results: The probit-based model describes data from individual patients and logistic regression does. Population analysis using the extended probit model accurately estimated 〈C50〉, γ, and ω for a range of values, despite the fact that the technique accounts for C50 variability but not y variability. Conclusion: A probit-based method of pharmacodynamic analysis of pooled population data facilitates accurate estimation of the concentration-response curve. © 1997 American Society of Anesthesiologists, Inc.