Objective: Author’s objective was to ascertain the option for prediction of preeclampsia using the integrated test markers on the population of pregnant women in Košice city. Design: Retrospective, longitudinal, multicenter study. Setting: 2nd Department of Obstetrics and Gynecology University of P. J. Šafárik, Košice, Slovak Republic. Methods: The study group comprised 578 pregnant patients of 2nd Department of Obstetrics and Gynecology, the period from 01.11.2001 until 31.01.2005 for integrated test consisting of (CRL, NT, concentration of PAPP-A, uE3, hCG, AFP). Primary outcome was defined as incidence of preeclampsia during pregnancy. Data on incidence of preeclampsia was collected from birth journals and records in 578 patients retrospectivelly. In order to make use of the summary information provided by the markers we have used the method of logistic regression to identify statistically significant predictors of the binary outcome measure of preeclampsia. First we developed an equation based on all available predictors. Statistically insignificant predictors were gradually eliminated from the model (Stepwise regression) until the final model remained, for which a ROC curve was developed and values of sensitivity, specificity, positive and negative predictive values at 5% FP (false positivity) were calculated. Results: The final model of preeclampsia, which is based only on statistically significant markers of integrated test achieved – at 5% FP and 95% specificity – 36,4% sensitivity and 22,7% positive and 97,4 negative predictive value for prediction of preeclampsia in pregnant women. Conclusion: Our results, as well as the results of other studies, lead to the conclusion, that in spite of the multitude of biochemical markers and various options for their combination with ultrasound markers for prediction of preeclampsia, so far it has been impossible to find a combination which would meet the following criteria: 1. high sensitivity and specificity at low false positive values and high positive and negative predictive value, 2. application as a screening method for prediction of preeclampsia in unselected population of pregnant women.

        Key words: preeclampsia, prediction, integrated test