Nenad Vesić1* and Andjelka Hedrih1
1 Mathematical Institute of Serbian Academy of Sciences and Arts, Belgrade, Serbia,
n.o.vesic [at] outlook.com
Abstract
Prostate cancer is the third most common tumor in men, with a 5-year relative survival rate of 34% for distant SEER stage cases. This makes prostate cancer particularly suitable for estimating the optimal set of clinical parameters essential for monitoring tumor progression or regression post-treatment.
In this study, PSA test results from patients of different ages and races with the same type of prostate cancer were analyzed. Two methods were applied: the method of evaluating established results using exact measures (as shown in Vesić, Mačukanović-Golubović, Ilić, 2017), and a statistical method utilizing mean values. These methods were applied to data from twenty prostate cancer patients taken from the End Results (SEER) Program, as well as to different sub-populations categorized by age and race. The results of these methods were compared, highlighting the differences between statistical analysis outcomes and those obtained through exact measures evaluation.
Additionally, descriptive statistics were performed on a population of 1,187,083 prostate cancer patients from the SEER Program. This included frequency distributions for patient age, race, histological tumor type, chemotherapy status, time from diagnosis to therapy initiation, and correlations between race and tumor histology, as well as tumor histology and living area. A Cox regression model was applied to the entire examined population to identify variables related to survival rates. The initial variables included in the model were: Gleason score, PSA value, median household income adjusted for 2022 inflation, rural or urban residence, age, and race.
Keywords: big data analysis, prostate cancer, PSA test, Cox regression, exact measures method.
Acknowledgement: We are grateful to the financial support from Ministry of Science, Technological Development and Innovation of Republic of Serbia trough Mathematical Institute of Serbian Academy of Sciences and Arts.