Analysis of Prostatitis and Prostate Cancer Transformation

다국어 초록 (Multilingual Abstract)

Purpose – The purpose of this paper is to explore the connection between hormonal changes in the body, related gene
expression, and imaging diagnosis between prostatitis and prostate cancer patients, and to analyze the work curves
of comparative subjects to conveniently find the optimal plan for early diagnosis and early treatment with clinical
reference.
Design/Methodology/Approach – In particular, in order to find the optimal method for early diagnosis and early
treatment by referring to the hormonal changes in the body and the connection between prostatitis and prostate cancer
patients and the type of related genes, imaging diagnosis is explored and the work curves of compared subjects are
closely analyzed. The method uses testing of serotonin (T) and leptin (LP) in 50 patients with prostatitis and 50
patients with prostate cancer, and uses a PCA gene expression test and a 1.5TMRI scan test in parallel. Statistical
analysis is performed using SPSS 21.0 software. We propose a three-item logistic regression model to select
statistically significant indicators as independent variables and use whether the pathological result is prostate cancer
as a dependent variable.
Findings – The area of working curve of the subjects with MRI + serum hormones, PSA + EPCA gene test, two tests
(serum hormones, PSA + EPCA gene test) and single serum hormones, PSA test were (ROC1:89.3%, ROC2:82.1%
and ROC3:64.3%), respectively. the results showed that the combined detection of MRI, serum hormone, PSA and
EPCA gene has a high clinical significance for the early diagnosis of PCA. Conclusion: The combination of MRI,
serum PSA and EPCA gene detection has clinical diagnostic value for early diagnosis of PCA, and the diagnostic
value of combined detection is higher.
Research Implications – In the management of this paper, this study has significance in improving the accuracy of
early screening for prostate cancer, find the optimal combination of subject curve detection items, which can replace
the best interdisciplinary detection combination of clinical gold standard live tissue testing, solve the physical testing
damage of patients, and reduce the economic cost of testing.