Are cancer patients living alone more or less likely to achieve a good death? Two cross-sectional surveys of bereaved families

Psychometric Evaluation of the Good Death Index from Patients with Terminal Cancer's Perspectives: A Mixed-Methods Study

Background

Patients with terminal illness often experience significant physical and mental suffering. This distress affects the patients themselves, as they endure the pain of their condition and their family members, who are affected by the patient's situation and medical decisions. Furthermore, exploring the patients' and their families' concepts of a "good death" is crucial for reflecting on the value of life and for planning treatment or care models (such as advance care planning). Therefore, understanding the issues is essential in improving palliative care and the overall quality of life.

Aim

This study aimed to develop a clinical assessment tool for the self-assessment of patients with terminal cancer to determine whether they are approaching a good death.

Methods

Our good death concept was developed through in-depth interviews with terminal cancer patients and qualitative analysis by experts in a research program. Three themes were analyzed: "living in dying (L)", "experiencing the existential self (E)", and "dying in living (D)." Therefore, the principal and co-principal investigators designed the primary LED Good Death Index (LED-GDI) based on three major themes and 15 subtopics of the LED Good Death concept.

Results

A total of 144 participants completed the LED-GDI assessment. Cronbach's alpha for the LED-GDI was 0.854. We found that the LED-GDI allowed patients to assess whether they were approaching a good death.

Conclusion

The philosophical concept of LED-GDI is particularly in line with Confucian culture in East Asia and emphasizes the importance of living well before death. Therefore, the most critical goal of clinical end-of-life care is to determine whether patients with terminal illness can achieve a good death and live until the last moment.

Risk factor analysis and nomogram construction for predicting suicidal ideation in patients with cancer

BACKGROUND

Suicidal ideation in cancer patients is a critical challenge. At present, few studies focus on factors associated with suicidal ideation, and predictive models are still lacking. This study aimed at investigating the risk factors for suicidal ideation among cancer patients, and developed a predictive nomogram to screen high risk cancer patients for early prevention and intervention.

METHODS

A questionnaire survey was conducted among cancer patients between May 2021 and January 2022. The factors associated with suicidal ideation were used to construct a multivariate logistic regression model, which was visualized as a predictive nomogram to evaluate the risk of suicidal ideation. Areas under the curve, calibration plot, decision curve analysis, and internal and external validation were used to validate the discrimination, calibration and clinical usefulness of the model.

RESULTS

A total of 820 patients with cancer were recruited for this study and 213 (25.98%) developed suicidal ideation. Levels of demoralization, depression and cancer staging, marital status, residence, medical financial burden, and living condition were influence factors for suicidal ideation. Comparing nomogram with Self-rating Idea of Suicide Scale (SIOSS), the nomogram had a satisfactory discrimination ability with an AUC of 0.859 (95% CI: 0.827-0.890) and 0.818 (95% CI: 0.764-0.873) in the training and validation sets, respectively. The calibration plot and decision curve analysis revealed that this nomogram was in good fitness and could be beneficial in clinical applications.

CONCLUSIONS

Suicidal ideation is common in cancer patients. Levels of demoralization, depression and cancer staging were independent predictors of suicidal ideation. The nomogram is an effective and simple tool for predictive suicidal ideation in cancer patients.