THE ROLE AND PLACE OF LOGISTIC REGRESSION AND ROC ANALYSIS IN SOLVING MEDICAL DIAGNOSTIC TASK

Diagnostics, equally with  prevention and  treatment, is a basis of medical science and practice. For its history the medicine  has accumulated a great variety  of diagnostic methods for different diseases and  pathologic conditions. Nevertheless, new  tests,  methods and  tools are being  developed and recommended to application nowadays. Such  indicators as sensitivity and  specificity which  are defined on the basis  of fourfold contingency  tables   construction or  ROC-analysis method with  ROC  – curve  modelling (Receiver operating characteristic) are used  as the  methods to estimate the  diagnostic capability. Fourfold  table  is used  with  the purpose to estimate the method which confirms or denies the diagnosis, i.e. a quality indicator. ROC-curve, being a graph, allows making the estimation of model  quality by subdivision of two classes  on the  basis  of identifying the  point  of cutting off a continuous or discrete quantitative attribute.

The method of logistic regression technique is introduced as a tool to develop some  mathematical-statistical forecasting model  of probability of the event the researcher is interested in if there are two possible variants of the outcome. The method of ROC-analysis is chosen and described in detail as a tool to estimate the  model  quality. The capabilities of the named methods are demonstrated by a real example of creation  and  efficiency estimation (sensitivity and  specificity) of a forecasting model  of probability of complication development in the form of pyodermatitis in children with  atopic dermatitis.

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