Identification and Prognostication of End-of-Life State Using a Japanese Guideline-Based Diagnostic Method: A Diagnostic Accuracy Study

Purpose: Prognostic uncertainty can be a barrier to providing palliative care. Accurate prognostic estimation for patients at the end of life is challenging. This study aimed to evaluate the accuracy of end-of-life diagnosis using our unique diagnostic method. Patients and Methods: A retrospective longitudinal observational study was conducted through collaboration among three medical facilities in a rural super-aged community in Japan. In 2007, we established a unique end-of-life diagnostic process comprising (1) physicians’ judgement, (2) disclosure to patients, and (3) discussion at an end-of-life case conference (EOL-CC), based on Japanese end-of-life-related guidelines. Research subjects were consecutive patients discussed in EOL-CC between January 1, 2010, and September 30, 2017. The primary outcome was mortality within 6 months after the initial EOL-CC decision. Sensitivity, specificity, and diagnostic odds ratio were calculated using EOL-CC diagnosis (end-of-life or non-end-of-life) as an index test and overall survival (<6 months or ≥6 months) as a reference standard. Results: In total, 315 patients were eligible for survival analysis (median age 89, range 54–107). The study population was limited to patients with severe conditions such as advanced cancer, organ failures, advanced dementia with severe deterioration in functioning. EOL-diagnosis by our methods was associated with much lower survival rate at 6 months after EOL-CC than non-EOL-diagnosis (6.9% vs 43.5%; P < 0.001). Of the patients, 297 were eligible for diagnostic accuracy analysis (median age 89, range 54–107). The EOL-diagnosis showed high sensitivity (0.95; 95% confidence interval [CI] 0.92–0.97) but low specificity (0.35; 95% CI 0.20–0.53) against the outcomes. It also showed a high diagnostic odds ratio (10.32; 95% CI 4.08–26.13). Conclusion: The diagnostic process using the Japanese end-of-life guidelines had tolerable accuracy in identification and prognostication of end of life.