AUTHOR=Song Qi Long , Qian Yinfeng , Min Xuhong , Wang Xiao , Wu Jing , Li Xiaohu , Yu Yongqiang 

TITLE=Urban–Rural Differences in Clinical Characteristics of Prostate Cancer at Initial Diagnosis: A Single-Center Observational Study in Anhui Province, China

JOURNAL=Frontiers in Oncology

VOLUME=Volume 11 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.704645

DOI=10.3389/fonc.2021.704645

ISSN=2234-943X

ABSTRACT=Background: People residing in rural areas have a higher prostate cancer (PCa) mortality to incidence ratio (M/I) and worse prognosis than those in urban areas of China.  Clinical characteristics at initial diagnosis are significantly associated with biochemical recurrence, overall survival, and PCa disease-free survival. 
Objective: This study aimed at investigatingthe clinical characteristics at initial diagnosis of urban and rural PCa patients and to establish a logistic regression model for identifying independent predictors for high-grade PCa. 

Materials and methods: Clinical characteristics for PCa patients were collected from the largest prostate biopsy center in Anhui province, China, from December 2015 to March 2019. First, urban-rural disparities in clinical characteristics were evaluated at initial diagnosis. Second, based on pathological findings, we classified all participants into the benign+low/intermediate-grade PCa  or high-grade PCa groups. Univariate and multivariate logistic regression analyses were performed to identify independent factors for predicting high-grade PCa while a nomogram for predicting high-grade PCa was generated based on all independent factors. The model was evaluated using area under receiver-operation characteristic (ROC) curve as well as calibration curve analyses and compared to a model without individuals’ place of residence factor. 

Results: Statistically significant differences were observed between urban and rural PCa patients with regards to tPSA, PSA density (PSAD) and Gleason score (GS) (p<0.05). Logistic regression analysis revealed that tPSA [OR=1.060, 95% confidence interval (CI): 1.024, 1.098], PSAD (OR=14.678, 95%CI: 4.137, 52.071), individuals’ place of residence (OR=5.900, 95%CI: 1.068, 32.601) and prostate imaging reporting and data system version 2 (PI-RADS v2) (OR=4.360, 95%CI: 1.953, 9.733) were independent predictive factors for high-grade PCa. The nomogram’s area under the curve (AUC) was greater than that of the model without individuals’ place of residence. 

Conclusions: Compared to urban PCa patients, rural PCa patients present elevated tPSA, PSAD levels and higher pathological grades.Individuals’ place of residence is an independent predictor for high-grade PCa in Anhui Province, China. Therefore, appropriate strategies, such as narrowing urban-rural gaps in access to health care and increasing awareness on the importance of early detection should be implemented to reduce PCa mortality rates.