Prostate cancer (PCa) is a high incidence tumor of elderly men. In recent years, its incidence has rapidly increased in China. Serological examination of prostate-specific antigen (PSA) is particularly important in the early diagnosis of PCa, but its specificity is lower in gray areas with PSA between 4-10 ng / ml. Proposition of prostate health index (PHI) strengthens the specificity of PSA gray area prostate cancer diagnosis, but the composition of the index only relies on serological examination, neglects imaging indicators, and cannot be comprehensively evaluated. Based on the preliminary basis of PHI research in the undergraduate department, combined with ultrasound imaging indicators of total prostate volume (TPV), this research group prospectively analyzed the efficacy of PHI combined with TPV to predict prostate cancer in patients with PSA gray areas, and established an improved version of PHI-TPV combination. The prediction model mPHI assesses the sensitivity of the new model to predict the risk of prostate cancer in the Chinese population, provides data support for puncture decisions of middle-aged and elderly male patients in the gray area of PSA in China, and provides reference and guidance for the individualized prevention and treatment of prostate cancer.
Study Type
OBSERVATIONAL
Enrollment
80
p2PSA test(for calculation of PHI)
Ultrasonic parameters(TPV)
Transperineal prostate biopsy for confirmation of prostate cancer or benign disease
Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, China
RECRUITINGPathological confirmed diagnosis of prostate cancer or benign prostatic diseases
Pathological confirmed diagnosis by transrectal ultrasound guided prostate biopsy (12 needles) according to a standardized protocol. If a suspicious low-density nodule is found during the ultrasound, biopsy to the nodule can be added. Place the prostate biopsy specimen in a 10% Formalin's specimen bag. The specimens were processed and evaluated by the Pathology Department of Xinhua Hospital.
Time frame: 2019/05/01-2021/05/30
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