Cardiovascular disease risk assessment and multidisciplinary care in prostate cancer treatment with ADT: recommendations from the APMA PCCV expert network.

PURPOSE: Androgen deprivation therapy (ADT) is the mainstay approach for prostate cancer (PCa) management. However, the most commonly used ADT modality, gonadotropin-releasing hormone (GnRH) agonists, has been associated with an increased risk of cardiovascular disease (CVD). METHODS: The PCa Cardiovascular (PCCV) Expert Network, consisting of multinational urologists, cardiologists and oncologists with expertise in managing PCa, convened to discuss challenges to routine cardiovascular risk assessment in PCa management, as well as how to mitigate such risks in the current treatment landscape. RESULTS: The experts identified several barriers, including lack of awareness, time constraints, challenges in implementing risk assessment tools and difficulties in establishing multidisciplinary teams that include cardiologists. The experts subsequently provided practical recommendations to improve cardio-oncology care for patients with PCa receiving ADT, such as simplifying cardiovascular risk assessment, individualising treatment based on CVD risk categories, establishing multidisciplinary teams and referral networks and fostering active patient engagement. A streamlined cardiovascular risk-stratification tool and a referral/management guide were developed for seamless integration into urologists' practices and presented herein. The PCCV Expert Network agreed that currently available evidence indicates that GnRH antagonists are associated with a lower risk of CVD than that of GnRH agonists and that GnRH antagonists are preferred for patients with PCa and a high CVD risk. CONCLUSION: In summary, this article provides insights and guidance to improve management for patients with PCa undergoing ADT.

Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.

BACKGROUND: Increasing patient loads, healthcare inflation and ageing population have put pressure on the healthcare system. Artificial intelligence and machine learning innovations can aid in task shifting to help healthcare systems remain efficient and cost effective. To gain an understanding of patients' acceptance toward such task shifting with the aid of AI, this study adapted the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), looking at performance and effort expectancy, facilitating conditions, social influence, hedonic motivation and behavioural intention. METHODS: This was a cross-sectional study which took place between September 2021 to June 2022 at the National Heart Centre, Singapore. One hundred patients, aged ≥ 21 years with at least one heart failure symptom (pedal oedema, New York Heart Association II-III effort limitation, orthopnoea, breathlessness), who presented to the cardiac imaging laboratory for physician-ordered clinical echocardiogram, underwent both echocardiogram by skilled sonographers and the experience of echocardiogram by a novice guided by AI technologies. They were then given a survey which looked at the above-mentioned constructs using the UTAUT2 framework. RESULTS: Significant, direct, and positive effects of all constructs on the behavioral intention of accepting the AI-novice combination were found. Facilitating conditions, hedonic motivation and performance expectancy were the top 3 constructs. The analysis of the moderating variables, age, gender and education levels, found no impact on behavioral intention. CONCLUSIONS: These results are important for stakeholders and changemakers such as policymakers, governments, physicians, and insurance companies, as they design adoption strategies to ensure successful patient engagement by focusing on factors affecting the facilitating conditions, hedonic motivation and performance expectancy for AI technologies used in healthcare task shifting.

Point-of-care AI-enhanced novice echocardiography for screening heart failure (PANES-HF).

The increasing prevalence of heart failure (HF) in ageing populations drives demand for echocardiography (echo). There is a worldwide shortage of trained sonographers and long waiting times for expert echo. We hypothesised that artificial intelligence (AI)-enhanced point-of-care echo can enable HF screening by novices. The primary endpoint was the accuracy of AI-enhanced novice pathway in detecting reduced LV ejection fraction (LVEF) < 50%. Symptomatic patients with suspected HF (N = 100, mean age 61 ± 15 years, 56% men) were prospectively recruited. Novices with no prior echo experience underwent 2-weeks' training to acquire echo images with AI guidance using the EchoNous Kosmos handheld echo, with AI-automated reporting by Us2.ai (AI-enhanced novice pathway). All patients also had standard echo by trained sonographers interpreted by cardiologists (reference standard). LVEF < 50% by reference standard was present in 27 patients. AI-enhanced novice pathway yielded interpretable results in 96 patients and took a mean of 12 min 51 s per study. The area under the curve (AUC) of the AI novice pathway was 0.880 (95% CI 0.802, 0.958). The sensitivity, specificity, positive predictive and negative predictive values of the AI-enhanced novice pathway in detecting LVEF < 50% were 84.6%, 91.4%, 78.5% and 94.1% respectively. The median absolute deviation of the AI-novice pathway LVEF from the reference standard LVEF was 6.03%. AI-enhanced novice pathway holds potential to task shift echo beyond tertiary centres and improve the HF diagnostic workflow.

Cardio-oncology in advanced prostate cancer.

Treatment intensification with androgen deprivation therapy (ADT) and androgen receptor pathway inhibitors (ARPi) have led to improved survival in advanced prostate cancer. However, ADT is linked to significant cardiovascular toxicity, and ARPi also negatively impacts cardiovascular health. Together with a higher prevalence of baseline cardiovascular risk factors reported among prostate cancer survivors at diagnosis, there is a pressing need to prioritise and optimise cardiovascular health in this population. Firstly, While no dedicated cardiovascular toxicity risk calculators are available, other tools such as SCORE2 can be used for baseline cardiovascular risk assessment. Next, selected patients on combination therapy may benefit from de-escalation of ADT to minimise its toxicities while maintaining cancer control. These patients can be characterised by an exceptional PSA response to hormonal treatment, favourable disease characteristics and competing comorbidities that warrant a less aggressive treatment regime. In addition, emerging molecular and genomic biomarkers hold the potential to identify patients who are suited for a de-escalated treatment approach either with ADT or with ARPi. One such biomarker is AR-V7 splice variant that predicts resistance to ARPi. Lastly, optimization of modifiable cardiovascular risk factors for patients through a coherent framework (ABCDE) and exercise therapy is equally important. This article aims to comprehensively review the cardiovascular impact of hormonal manipulation in metastatic hormone-sensitive prostate cancer, propose overarching strategies to mitigate cardiovascular toxicity associated with hormonal treatment, and, most importantly, raise awareness about the detrimental cardiovascular effects inherent in our current management strategies involving hormonal agents.

Water Conservation Overrides Osmotic Diuresis During SGLT2 Inhibition in Patients With Heart Failure.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors are believed to improve cardiac outcomes due to their osmotic diuretic potential. OBJECTIVES: The goal of this study was to test the hypothesis that vasopressin-driven urine concentration overrides the osmotic diuretic effect of glucosuria induced by dapagliflozin treatment. METHODS: DAPA-Shuttle1 (Hepato-renal Regulation of Water Conservation in Heart Failure Patients With SGLT-2 Inhibitor Treatment) was a single-center, double-blind, randomized, placebo-controlled trial, in which patients with chronic heart failure NYHA functional classes I/II and reduced ejection fraction were randomly assigned to receive dapagliflozin 10 mg daily or placebo (1:1) for 4 weeks. The primary endpoint was change from baseline in urine osmolyte concentration. Secondary endpoints included changes in copeptin levels and solute free water clearance. RESULTS: Thirty-three randomized, sodium-glucose cotransporter 2 inhibitor-naïve participants completed the study, 29 of whom (placebo: n = 14; dapagliflozin: n = 15) provided accurate 24-hour urine collections (mean age 59 ± 14 years; left ventricular ejection fraction 31% ± 9%). Dapagliflozin treatment led to an isolated increase in urine glucose excretion by 3.3 mmol/kg/d (95% CI: 2.51-4.04; P < 0.0001) within 48 hours (early) which persisted after 4 weeks (late; 2.7 mmol/kg/d [95% CI: 1.98-3.51]; P < 0.0001). Dapagliflozin treatment increased serum copeptin early (5.5 pmol/L [95% CI: 0.45-10.5]; P < 0.05) and late (7.8 pmol/L [95% CI: 2.77-12.81]; P < 0.01), leading to proportional reductions in free water clearance (early: -9.1 mL/kg/d [95% CI: -14 to -4.12; P < 0.001]; late: -11.0 mL/kg/d [95% CI: -15.94 to -6.07; P < 0.0001]) and elevated urine concentrations (late: 134 mmol/L [95% CI: 39.28-229.12]; P < 0.01). Therefore, urine volume did not significantly increase with dapagliflozin (mean difference early: 2.8 mL/kg/d [95% CI: -1.97 to 7.48; P = 0.25]; mean difference late: 0.9 mL/kg/d [95% CI: -3.83 to 5.62]; P = 0.70). CONCLUSIONS: Physiological-adaptive water conservation eliminated the expected osmotic diuretic potential of dapagliflozin and thereby prevented a glucose-driven increase in urine volume of approximately 10 mL/kg/d · 75 kg = 750 mL/kg/d. (Hepato-renal Regulation of Water Conservation in Heart Failure Patients With SGLT-2 Inhibitor Treatment [DAPA-Shuttle1]; NCT04080518).