Summary: Background and objectives: Chronic kidney disease (CKD) is known to be associated with increased all-cause and cardiovascular mortality, but no large studies examined the cancer-specific mortality in non–dialysis-dependent CKD patients. Such outcome data are needed for proper allocation of resources and would help to develop better preventive services. Design, setting, participants, & measurements: Between 1998 and 1999, 123,717 adults were recruited from four health screening centers in Taiwan. The estimated glomerular filtration rate was calculated using the four-variable Modification of Diet in Renal Disease Study equation for the Chinese. Mortality was ascertained by computer linkage to the national death registry after a median follow-up of 7.06 years. Cox proportional hazards regression models were used to estimate the impact of CKD on cancer-specific mortality. Results: A higher risk for overall cancer mortality was found in CKD patients compared with non-CKD patients (adjusted hazard ratio, 1.2). CKD was associated with increased mortality from liver cancer, kidney cancer, and urinary tract cancer, with an adjusted hazard ratio of 1.74, 3.3, and 7.3, respectively. A graded relationship between the severity of renal impairment and cancer mortality was also found. Conclusions: Patients with CKD had a higher mortality risk of liver cancer, kidney cancer, and urinary tract cancer. This is the first large study that showed an inverse association between renal function and liver cancer mortality. The increased mortality could be caused by higher cancer incidence or worse response to cancer treatment. Future research is warranted to clarify the mechanism.

Background: In Confucian-influenced Asian societies, explicit end-of-life conversations are uncommon and family involvement in decision-making is crucial, which complicates the adoption of culturally sensitive advance care planning. Aim: To develop a consensus definition of advance care planning and provide recommendations for patient-centered and family-based initiatives in Asia. Design: A five-round Delphi study was performed. The rating of a definition and 84 recommendations developed based on systematic reviews was performed by experts with clinical or research expertise using a 7-point Likert scale. A median = 1 and an inter-quartile range = 0–1 were considered very strong agreement and very strong consensus, respectively. Setting/participants: The Delphi study was carried out by multidisciplinary experts on advance care planning in five Asian sectors (Hong Kong/Japan/Korea/Singapore/Taiwan). Results: Seventy-seven of 115 (67%) experts rated the statements. Advance care planning is defined as “a process that enables individuals to identify their values, to define goals and preferences for future medical treatment and care, to discuss these values, goals, and preferences with family and/or other closely related persons, and health-care providers, and to record and review these preferences if appropriate.” Recommendations in the domains of considerations for a person-centered and family-based approach, as well as elements, roles and tasks, timing for initiative, policy and regulation, and evaluations received high levels of agreement and consensus. Conclusions: Our definition and recommendations can guide practice, education, research, and policy-making in advance care planning for Asian populations. Our findings will aid future research in crafting culturally sensitive advance care planning interventions, ensuring Asians receive value-aligned care.

Purpose: The study aimed to investigate prevailing ethical dilemmas in terminal care for patients with cancer nationwide and identify related factors after the enactment of the Natural Death Act in Taiwan. Methods: This multicenter study surveyed 800 physicians and nursing staff of oncology wards and hospices through a set questionnaire. A total of 505 respondents (63.1%) who had taken care of patients with terminal cancer were analyzed. Results: The most frequently encountered ethical dilemmas were truth-telling (mean ± SD = 1.30 ± 0.63; range [never, occasional, often], 0 to 2) and place of care (1.19 ± 0.69), both of which were related to communication issues. Dilemmas related to clinical management were artificial nutrition and hydration (1.04 ± 0.66) and use of antimicrobial agents (0.94 ± 0.70). Logistic regression analyses revealed that positive attitudes about the Natural Death Act was negatively related to the extent of ethical dilemmas (odds ratio, 0.426; 95% CI, 0.256 to 0.710]. Conclusion: The enactment of the Natural Death Act in Taiwan would contribute to improving the quality of end-of-life care, which suggests that this kind of law should be adopted in other countries. Educating cancer care professionals in building positive beliefs toward the act is strongly encouraged.

Background: An accurate prediction of mortality in end-of-life care is crucial but presents challenges. Existing prognostic tools demonstrate moderate performance in predicting survival across various time frames, primarily in in-hospital settings and single-time evaluations. However, these tools may fail to capture the individualized and diverse trajectories of patients. Limited evidence exists regarding the use of artificial intelligence (AI) and wearable devices, specifically among patients with cancer at the end of life. Objective: This study aimed to investigate the potential of using wearable devices and AI to predict death events among patients with cancer at the end of life. Our hypothesis was that continuous monitoring through smartwatches can offer valuable insights into the progression of patients at the end of life and enable the prediction of changes in their condition, which could ultimately enhance personalized care, particularly in outpatient or home care settings. Methods: This prospective study was conducted at the National Taiwan University Hospital. Patients diagnosed with cancer and receiving end-of-life care were invited to enroll in wards, outpatient clinics, and home-based care settings. Each participant was given a smartwatch to collect physiological data, including steps taken, heart rate, sleep time, and blood oxygen saturation. Clinical assessments were conducted weekly. The participants were followed until the end of life or up to 52 weeks. With these input features, we evaluated the prediction performance of several machine learning–based classifiers and a deep neural network in 7-day death events. We used area under the receiver operating characteristic curve (AUROC), F1-score, accuracy, and specificity as evaluation metrics. A Shapley additive explanations value analysis was performed to further explore the models with good performance. Results: From September 2021 to August 2022, overall, 1657 data points were collected from 40 patients with a median survival time of 34 days, with the detection of 28 death events. Among the proposed models, extreme gradient boost (XGBoost) yielded the best result, with an AUROC of 96%, F1-score of 78.5%, accuracy of 93%, and specificity of 97% on the testing set. The Shapley additive explanations value analysis identified the average heart rate as the most important feature. Other important features included steps taken, appetite, urination status, and clinical care phase. Conclusions: We demonstrated the successful prediction of patient deaths within the next 7 days using a combination of wearable devices and AI. Our findings highlight the potential of integrating AI and wearable technology into clinical end-of-life care, offering valuable insights and supporting clinical decision-making for personalized patient care. It is important to acknowledge that our study was conducted in a relatively small cohort; thus, further research is needed to validate our approach and assess its impact on clinical care. Trial Registration: ClinicalTrials.gov NCT05054907; https://classic.clinicaltrials.gov/ct2/show/NCT05054907

Background: In the palliative care setting, infection control measures implemented due to COVID-19 have become barriers to end-of-life care discussions (eg, discharge planning and withdrawal of life-sustaining treatments) between patients, their families, and multidisciplinary medical teams. Strict restrictions in terms of visiting hours and the number of visitors have made it difficult to arrange in-person family conferences. Phone-based telehealth consultations may be a solution, but the lack of nonverbal cues may diminish the clinician-patient relationship. In this context, video-based, smartphone-enabled family conferences have become important. Objective: We aimed to establish a smartphone-enabled telehealth model for palliative care family conferences. Our model integrates principles from the concept of shared decision making (SDM) and the value, acknowledge, listen, understand, and elicit (VALUE) approach. Methods: Family conferences comprised three phases designed according to telehealth implementation guidelines—the previsit, during-visit, and postvisit phases. We incorporated the following SDM elements into the model: “team talk,” “option talk,” and “decision talk.” The model has been implemented at a national cancer treatment center in Taiwan since February 2020. Results: From February to April 2020, 14 telehealth family conferences in the palliative care unit were analyzed. The patients’ mean age was 73 (SD 10.1) years; 6 out of 14 patients (43%) were female and 12 (86%) were married. The primary caregiver joining the conference virtually comprised mostly of spouses and children (n=10, 71%). The majority of participants were terminally ill patients with cancer (n=13, 93%), with the exception of 1 patient with stroke. Consensus on care goals related to discharge planning and withdrawal of life-sustaining treatments was reached in 93% (n=13) of cases during the family conferences. In total, 5 families rated the family conferences as good or very good (36%), whereas 9 were neutral (64%). Conclusions: Smartphone-enabled telehealth for palliative care family conferences with SDM and VALUE integration demonstrated high satisfaction for families. In most cases, it was effective in reaching consensus on care decisions. The model may be applied to other countries to promote quality in end-of-life care in the midst of the COVID-19 pandemic.