The Prognosis of Survival in Patients with Some Solid Tumors Based on Optimal Partitions of Immunological Parameter Ranges.
New logical and statistical methods were used for the analysis of relationships between survival rate of solid tumor patients and immunological variables. These methods are based on the search of the regularities (syndromes) in the multidimensional space. The syndromes are the elements of partitions of allowable areas of variables. To estimate the statistical validity of found regularities the new technique based on Monte-Carlo computer simulation was used. The broad panel of monoclonal antibodies for lymphocyte differentiation antigens was used for subpopulation analysis. The two tasks are described. The purpose of the first task was the evaluation of significance of immunological parameters for prediction of one-year metastasis-free survival in non-metastatic osteosarcoma of extremities. The second task was the construction of the predicting algorithm for prognosis of two-year survival of patients with stomach cancer. The optimal sets of parameters for prediction of survival were found for both tasks. We found out the high predictive value of HLA DR(+) cells percentage in the 1st task, and the percentage of adhesion cells (CD50(+) lymphocytes) is the most significant parameter in the 2nd task. The predictive algorithms were developed.
Kuznetsova
Anna V.
AV
Institute of Biochemical Physics of the Russian Academy of Sciences, Moscow, Russia.
Senko
Oleg V.
OV
Matchak
Gennady N.
GN
Fedotova
Tatyana A.
TA
Zabotina
Tatyana N.
TN
Korotkova
Olga V.
OV
Vakchotsky
Vladimir V.
VV