FIELD: medicine, oncology.
SUBSTANCE: the present innovation deals with predicting the relapse of serous ovarian cancer after radical therapy before its clinical manifestation. The suggested innovation could be applied in daily practice of pathologoanatomic departments of hospitals, oncological dispensaries, specialized centers and research Institutes. The risk for the development of relapse is represented by a dichotomous variable calculated by the formula determined by logistic regression that includes the combination of several variables being morphological parameters of tumor, that is the area of tumor cell, average ploidy of tumor cells' nuclei, the level of p53 expression the level of expression of estrogen receptors, the level of PCNA expression. The innovation enables to predict repeated cancer growth according to morphological characteristics of primary tumor till clinical manifestation of the relapse.
EFFECT: higher accuracy and efficiency of prediction.
2 ex
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Authors
Dates
2006-12-27—Published
2005-07-25—Filed