Prediction of Tumor Metastases, Using Interpolation of a Statistical Histogram of the Time Intervals of Detecting Metastases at Cancer Patients after Conducted Operation

Abstract

Prediction of tumor metastases, occurring among cancer patients after surgery plays a vital role in the survival of cancer patients. Prediction of tumor metastases also permits to determine the efficiency of conducted after surgery prophylactic treatment. Today, oncologists expect detection of metastases of malignant neoplasms at cancer patients after operation in accordance with the exponential decrease over time of the number of cancer patients at whom metastases were detected after surgery, which is scientifically unfounded and leads to an incorrect determination of the moment of detection of metastases at cancer patient after operation, and therefore to untimely examination of a cancer patient and his preventive treatment. Predicting in statistics is carried out, using polynomial regression, where a certain relationship, called regression, with a certain accuracy between a pair of studied medical symptoms is determined, multiple linear regression, where a certain relationship, called regression, with a certain accuracy between studied symptom with multiple symptoms is determined in linear form and stepwise multiple linear regression, where a certain relationship, called regression, with a certain accuracy is determined also between studied symptom with multiple symptoms in a linear form.