Prognostic impact of dose reduction in androgen receptor pathway inhibitors for castration-resistant prostate cancer

From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.

Pharmacist-Urologist Collaborative Management Improves Clinical Outcomes in Patients With Castration-Resistant Prostate Cancer Receiving Enzalutamide

Background: Enzalutamide is useful for the treatment of castration-resistant prostate cancer (CRPC). Despite its usefulness, adverse events (AEs) sometimes force patients to discontinue treatment. To maximize patient care, we developed an ambulatory care pharmacy practice that allows collaboration between a pharmacist and urologist to manage patients with CRPC receiving enzalutamide. In this study, we investigated the efficacy of this collaborative management.

Methods: A retrospective chart review of 103 patients with CRPC receiving enzalutamide in our hospital between May 2014 and December 2020 was performed. Our collaborative management was implemented in October 2016. Before being examined by urologists, patients visited the oncology pharmacy consultation room for a face-to-face consultation, wherein the oncology pharmacists assessed factors such as adherence to enzalutamide, any AEs and their grades, and provided their suggestions to the urologists. The time to enzalutamide discontinuation and prostate-specific antigen progression were compared between patients who started enzalutamide before (n = 41) and after (n = 62) the implementation of the collaborative management. A multivariate Cox regression analysis was performed to analyze the factors associated with enzalutamide discontinuation.

Results: After implementing collaborative management, the pharmacists had 881 patient consultations. Among the 476 suggestions from pharmacists, 345 were accepted by urologists. The most frequent suggestion was supportive care in enzalutamide treatment (224 suggestions). Multivariate analysis showed that collaborative management [hazard ratio (HR) 0.53, 95% confidence interval (CI) 0.31–0.89, p = 0.017] and higher prostate-specific antigen (PSA; HR 2.41, 95% CI 1.36–4.28, p = 0.003) were significantly associated with enzalutamide discontinuation. The median time to discontinuation (18.9 vs. 7.6 months, p = 0.012), time to discontinuation due to AEs (not reached in both groups, p = 0.001), and time to PSA progression (13.3 vs. 5.8 months, p = 0.002) were all significantly longer in the after group.

Conclusions: We implemented a pharmacist-urologist collaborative management program for outpatients with CRPC receiving enzalutamide. The results revealed that collaborative management was useful for prolonging the time to enzalutamide discontinuation.