1. Depression, performance status, and discontinued treatment mediate an association of curability belief with prognosis in advanced cancer patients
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Je-Yeon Yun, Ju Youn Jung, Bhumsuk Keam, Na-Ri Lee, Jung Hun Kang, Yu Jung Kim, Hyun-Jeong Shim, Kyung Hae Jung, Su-Jin Koh, Hyewon Ryu, Shin Hyu Yoo, EunKyo Kang, and Young Ho Yun
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Advanced cancer ,Curability belief ,Depression ,1-year survival ,Cox proportional hazard regression model ,Mixed graphical model ,Medicine ,Science - Abstract
Abstract Individuals diagnosed with advanced cancer often experience stress and depression, factors linked to worse survival. Curability belief—defined as the hope and expectation of cure through treatment, based on affective forecasting—may differ from the patient’s actual life expectancy (i.e., likelihood estimation) and has shown variable associations with cancer survival. In this study, multivariate Cox regression analyses were used to examine the effect of curability belief and depression on 1-year survival after adjustment for physical factors. Additionally, regularized partial correlations among physical and psychological factors were assessed using mixed graphical models to elucidate their roles in mediating the relationship between curability belief and 1-year survival. This multi-center cohort study, conducted across 13 tertiary hospitals (including four ranked among the ‘World’s Best Specialized Hospitals 2025’ in oncology), involved 382 adults with stage IV advanced cancer and an oncologist-estimated survival of more than 6 months. Baseline data included demographics, primary tumor site, number of metastatic sites, symptom burdens (EORTC QLQ-C15-PAL), performance status (ECOG-PS), depression levels (PHQ-9), anti-cancer treatment type, patient’s life expectancy estimation, and curability belief. Follow-up data included 1-year survival and end-of-life care (place of death) for deceased patients. Multivariate Cox proportional hazards models were used to assess adjusted hazard ratios (aHRs) for curability belief, depression, and their interaction on 1-year survival, adjusting for significant demographic and clinical factors from univariate Cox regressions. The Kaplan–Meier method was used to plot survival probability by curability belief and depression interaction. Mixed graphical models estimated regularized partial correlations among 1-year survival, curability belief, patient’s life expectancy, depression, primary tumor site, anti-cancer treatment type, performance status, and symptom burden. In terms of healthcare utilization, patients with curability belief were more likely to receive standard or advanced anti-cancer therapy, while those without curability belief tended to suspend or discontinue therapy (P
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- 2024
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