Prostate cancer epidemiology and prognostic factors in the United States - Abudoubari, Saimaitikari; Bu, Ke; Mei, Yujie; Maimaitiyiming, Abudukeyoumu; An, Hengqing; Tao, Ning (Frontiers in Oncology, 2023)
Objective: Using the latest cohort study of prostate cancer patients, explore the epidemiological trend and prognostic factors, and develop a new nomogram to predict the specific survival rate of prostate cancer patients. Methods: Patients with prostate cancer diagnosed in the SEER database were extracted for epidemiological trend analysis. General clinical information and follow-up data were also collected from 105135 patients with diagnosed prostate cancer. The factors affecting patient-specific survival were analyzed by Cox regression, and nomogram was constructed.Results: Among the tumor grade, the most significant increase in the incidence of G2 prostate cancer was observed;the most significant decrease in the incidence of G4 prostate cancer was observed, with an AAPC of -10.39 (95%CI:-13.86~-6.77).Among the different tumor stages,the most significant reduction in the incidence of localized prostate cancer was observed with an AAPC of -1.83 (95%CI:-2.76~-0.90). Among different races, the incidence of prostate cancer was significantly reduced in American Indian or Alaska Native and Asian or Pacific Islander, with an AAPC of -3.40 (95%CI:-3.97~-2.82) and -2.74 (95%CI:-4.14~-1.32), respectively. Among the different age groups, the incidence rate was significantly increased in 15-54 and 55-64 age groups with AAPC of 4.03 (95%CI:2.73~5.34) and 2.50 (95%CI:0.96~4.05), respectively, and significantly decreased in ≥ 85 age group with AAPC of -2.50 (95%CI:-3.43~-1.57).In addition,age,tumor stage,race,PSA and gleason score were found to be independent risk factors affecting prostate cancer patient-specific survival.Age,tumor stage,PSA and gleason score were most strongly associated with prostate cancer patient-specific survival by stepwise regression screening,and nomogram prediction model was constructed using these factors.The Concordance indexes are 0.845 (95%CI:0.818~0.872) and 0.835 (95%CI:0.798~0.872) for the training and validation sets, respectively, and the area under the ROC curves (AUC) at 3,6,and9 years was 0.7or more for both the training and validation set samples.Although there was no significant change in the overall incidence of prostate cancer in this study,significant changes occurred in the incidence of prostate cancer with different characteristics.In addition,the nomogram prediction model of prostate cancer-specific survival rate constructed based on four factors has a high reference value,which helps physicians to correctly assess the patientspecific survival rate and provides a reference basis for patient diagnosis and prognosis evaluation.