Breast Cancer Clinical Trial
Official title:
Evaluation the Diagnostic Ability of the CDT to Detect Breast Cancer Among Women Population Over Age 40
This study aimed to validate the diagnostic ability of the CDT (cancer detection technology) software to detect breast cancer among women population.
Breast cancer diagnosis is a rapidly expanding research field, whose early-stage detection
may reduce the burden of the disease and permit more effective treatment. It is well
documented that tumor growth requires specific conditions for its development from the
occurrence of a mutation to a clinically detectable cancer. It has been shown that living
peripheral blood mononuclear cells (PBMC) have different ability of cytosolic enzymes
(esterases) to convert hydrophobic substrate fluorescein diacetate (FDA) into hydrophilic
fluorescent fluorescein. It depends on PBMC cycle stage, size, surface state, physiological
states, such as activation and apoptosis.
The important step of breast cancer genesis is the early change of functional activity of
cytosolic enzymes (esterases) in peripheral blood mononuclear cells. Such transformations in
PBMC may be detected accurately by an existing device Flowcytometer (FACS™ MultiSET™ System,
company "Becton Dickinson" GmbH, USA), where measurements of fluorescence polarization and
enzymatic hydrolysis of FDA substrate are recorded. A conclusion about presentation of
breast cancer among examined women is achieved by "CDT" (cancer detection technology)
software, which analyzes mathematically the results of fluorescence polarization and
enzymatic hydrolysis.
Moreover, the combined biochemical model together with additional prognostic parameters
(such as age, ethnic group, gynecological and obstetric anamnesis) increases the validity
(accuracy, sensitivity and specificity) of the diagnostic conclusion.
Diagnostic Solution of the CDT:
1. Mathematical processing of specific blood analysis in device Flowcytometer.
2. Mathematical evaluation of specific prognostic parameters
;
Observational Model: Cohort, Time Perspective: Prospective
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