Calculation of the ELISA's cut-off based on the change-point analysis method for detection of Trypanosoma cruzi infection in Bolivian dogs in the absence of controls

In continuous diagnostic clinical tests, the establishment of a reliable cut-off is of paramount importance to discriminate between infected and non-infected individuals. Several standard methods have been proposed to choose optimal cut-offs Where X is the mean and SD the standard deviation of independent negative control readings, and a and f two multipliers. Depending on authors, the multipliers can be set arbitrarily, for example to f = 0 with a = 2 or a = 3 (i.e., cut-off = twice or three times the mean absorbance obtained from the negative controls), or a = 1 with f = 3 (i.e., cut-off = mean + 3 times the standard deviation) To detect infection by Trypanosoma cruzi, the causative agent of Chagas disease, Where X neg is the mean of the negative controls, and X pos the mean of the positive controls. When no controls are available, the above formulas cannot be used. Change-point analysis is a statistical analysis that can detect in a series of (ascending) values, a step indicating a change. Such change exists in a series of negative and positive ELISA values from a titer plate and should be detected with such an analysis. The scope of the present study is to evaluate the change-point analysis as a tool to identify positive ELI-SA reactions when no controls are available. A set of dog sera from a field survey is used to diagnose T. cruzi infection and results are compared to those obtained using a standard approach using cut-off values from the usual equations (1) and (2). Cutoff = a.X + f . SD (1) Cutoff = X neg + 0.13 X pos (2

Calculation of the ELISA's cut-off based on the change-point analysis method for detection of Trypanosoma cruzi infection in Bolivian dogs in the absence of controls

In continuous diagnostic clinical tests, the establishment of a reliable cut-off is of paramount importance to discriminate between infected and non-infected individuals. Several standard methods have been proposed to choose optimal cut-offs Where X is the mean and SD the standard deviation of independent negative control readings, and a and f two multipliers. Depending on authors, the multipliers can be set arbitrarily, for example to f = 0 with a = 2 or a = 3 (i.e., cut-off = twice or three times the mean absorbance obtained from the negative controls), or a = 1 with f = 3 (i.e., cut-off = mean + 3 times the standard deviation) To detect infection by Trypanosoma cruzi, the causative agent of Chagas disease, Where X neg is the mean of the negative controls, and X pos the mean of the positive controls. When no controls are available, the above formulas cannot be used. Change-point analysis is a statistical analysis that can detect in a series of (ascending) values, a step indicating a change. Such change exists in a series of negative and positive ELISA values from a titer plate and should be detected with such an analysis. The scope of the present study is to evaluate the change-point analysis as a tool to identify positive ELI-SA reactions when no controls are available. A set of dog sera from a field survey is used to diagnose T. cruzi infection and results are compared to those obtained using a standard approach using cut-off values from the usual equations (1) and (2). Cutoff = a.X + f . SD (1) Cutoff = X neg + 0.13 X pos (2