Decisions and dilemmas in non-metastatic castration-resistant prostate cancer management

Physician preferences for nonmetastatic castration-resistant prostate cancer treatment in China

Introduction

The treatment preferences of Chinese physicians who treat nonmetastatic castration-resistant prostate cancer (nmCRPC) and how they weigh the benefits and risks of nmCRPC treatment are still unknown. This study aimed to evaluate Chinese physicians' benefit-risk treatment preferences for nmCRPC and assist in setting nmCRPC treatment goals.

Methods

A paper-based discrete choice experiment (DCE) survey was administered to 80 nmCRPC-treating physicians. DCE responses were analyzed to produce the preference weight and the relative importance score for each attribute level. The marginal rate of substitution (MRS) was used to quantify the amount of overall survival (OS) physicians were willing to trade for a reduction in treatment-related adverse events (AEs). We further conducted the exploratory analysis, stratifying physicians from 5 perspectives into different subgroups and examining the treatment preferences and OS trade-off in each subgroup.

Results

In terms of efficacy attributes, physicians placed greater emphasis on OS than time to pain progression. With regard to safety attributes, serious fracture was perceived as the most important AE by physicians, followed by serious fall, cognitive problems, skin rash, and fatigue. In the exploratory analysis, we found generally that physicians with less clinical practice experience and those from more economically developed regions placed more emphasis on AEs and were willing to give up more of their patients' OS to reduce the risk of AEs.

Conclusion

Physicians from mainland China value the importance of minimizing treatment-related AEs when considering different treatment options for patients with nmCRPC, and they are willing to trade a substantial amount of OS to avoid AEs.

AI Techniques and IoT Applications Transforming the Future of Healthcare

The role of artificial intelligence (AI) has advanced from an analysis and prediction tool to extending human capabilities. Currently, AI is more of a reliable assistant fueled by human experience and need of the hour in the healthcare along with simplifying daily life. AI and Internet of Things (IoT) have opened new avenues in intelligent diagnostics, drug discovery, clinical decision support, enhancing physician-patient communication, transcribing medical documents, and remote treatment. With the advent of enhanced computational power, AI has revolutionized discovery of optimal and efficient healthcare solutions and has accelerated the development of smart solutions involving IoT-based technologies. Starting from telemedicine to predict possible health disorders, AI is gaining focus to facilitate and advance healthcare solutions in developed and underdeveloped countries. This chapter deals with the scope of AI in the present scenario to future developments as AI will soon surpass human and poses threat pertaining to misuse of cognitive sciences development.

Disability weights for castration-resistant prostate cancer: an empirical investigation

Introduction

Health state valuation and diagnostic-therapeutic pathways at the junction between non-metastatic and metastatic castration-resistant prostate cancer (CRPC) are not well documented. We aimed at: (i) estimating the disability weights (DWs) for health states across a continuum of disease from asymptomatic non-metastatic (nmCRPC) to symptomatic metastatic state (mCRPC); (ii) mapping the diagnostic-therapeutic pathway of nmCRPC in Italy.

Methods

Structured qualitative interviews were performed with clinical experts to gather information on nmCRPC clinical pathway. An online survey was administered to clinical experts to estimate DWs for four CRPC health states defined from interviews and literature review (i.e., nmCRPC, asymptomatic mCRPC, symptomatic mCRPC, mCRPC in progression during or after chemotherapy). Clinicians' preferences for health states were elicited using the Person-Trade-Off (PTO) and Visual Analogue Scale (VAS) methods. DWs associated with each health state, from 0 (best imaginable health state) and 1 (worst imaginable health state), were estimated.

Results

We found that the management of nmCRPC is heterogeneous across Italian regions and hospitals, especially with respect to diagnostic imaging techniques. DWs for PTO ranged from 0.415 (95% confidence interval [CI] 0.208-0.623) in nmCRPC to 0.740 (95% CI 0.560-0.920) in mCRPC, in progression during or after chemotherapy. DWs for VAS ranged between 0.246 (95% CI 0.131-0.361) in nmCRPC to 0.689 (95% CI 0.583-0.795) in mCRPC, in progression during or after chemotherapy.

Conclusions

Estimated DWs suggest that delaying transition to a metastatic state might ease the disease burden at both patient and societal levels.