Extrapolation of methacholine log-dose response curves with a Cumulative Gaussian Distribution function

Area of Science:

• Pulmonary Medicine
• Respiratory Physiology

Background:

• Methacholine provocation tests assess bronchial responsiveness.
• Analyzing the entire log-dose response curve, including plateau and reactivity, is crucial.
• Existing methods for plateau estimation may have limitations.

Purpose of the Study:

• To evaluate the Cumulative Gaussian Distribution (CGD) function for modeling methacholine log-dose response curves.
• To compare the CGD function with the Hofstee equation for estimating plateau values.
• To assess the accuracy of these models in determining bronchial responsiveness.

Main Methods:

• Methacholine log-dose response curves were generated in control subjects and asthma patients.
• The Cumulative Gaussian Distribution (CGD) function was fitted to the entire curve.
• The Hofstee equation was used to analyze the upper portion of the curve.
• Fitted plateau values were compared to measured values using the coefficient of determination (R2).

Main Results:

• Both CGD and Hofstee models slightly overestimated measured plateau values when all data points were used.
• The CGD fit demonstrated a highly significant correlation (R2: 0.93-0.99) between actual and fitted data.
• Even when curves were truncated, the CGD model accurately estimated plateau values (mean difference -2.6%).
• The Hofstee equation showed significant deviations from measured plateau values in most cases.

Conclusions:

• The Cumulative Gaussian Distribution (CGD) function provides a robust and accurate method for analyzing methacholine log-dose response curves.
• CGD modeling effectively captures bronchial reactivity, including plateau estimation, in individuals with and without asthma.
• The CGD function offers superior performance compared to the Hofstee equation for plateau value estimation in methacholine challenge tests.