Comparison of survival in patients with low vs. intermediate prostate-specific antigen concentrations and development of a nomogram: a surveillance, epidemiology and end results program database study with external validation on a Chinese cohort - Jingchang Mei; Guanqun Zhu; Yu Yao; Fengju Guan; Lijiang Sun; Guiming Zhang (PeerJ)
Background In this study of patients with prostate cancer, we explored associations between low prostate-specific antigen (PSA) concentrations and disease progression as well as prognosis. Methods We retrospectively reviewed data of 233,554 prostate cancer patients in the Surveillance, Epidemiology and End Results (SEER) program and of 199 prostate cancer patients from the medical records of the Affiliated Hospital of Qingdao University with PSA ≤10 ng/mL at diagnosis. The patients were stratified into eight subgroups by T stage and Gleason score (GS) and survival curves for the resultant subgroups plotted using the Kaplan–Meier method. Multivariate Cox analyses were performed to investigate the effects of PSA concentrations in different subgroups. After randomly dividing patients into a training set and an internal validation set with a ratio of 7:3, a nomogram model to predict the survival of prostate cancer patients was subsequently established and validated. Results In all prostate cancer patients with Gleason score (GS) 8–10, low PSA concentrations were significantly associated with advanced disease and poor prognosis, functioning as a statistically significant risk factor. Conversely, in patients with GS 6–7 and Stage T1 disease, low PSA concentrations acted as a protective factor. A nomogram model for predicting prognosis was established and validated. We obtained similar results with an external validation cohort. Conclusions Our findings indicate that low PSA concentrations exert divergent impacts on prostate cancer patients stratified by T stage and GS. Specifically, in patients with high GS (8–10), low PSA concentrations represent a risk factor for disease progression to advanced stages and poor prognosis. Additionally, we developed a novel nomogram that effectively predicts survival outcomes in these patients.