Authors
Ziluo Cheng, Lu Jin, Zhen Mei, Yeping Wang
Published in
Cancer medicine. Volume 15. Issue 10. Pages e72283.
Abstract
Previous studies have discussed the effectiveness of the Karnofsky Performance Scale (KPS), Palliative Performance Scale (PPS), Palliative Prognostic Index (PPI), and Delirium-Palliative Prognostic Score (D-PaP) in predicting the survival of patients with terminal-stage tumors, but their effectiveness in the Chinese terminal-stage tumor population still needs to be explored. Therefore, we conducted this prospective cohort study to investigate the applicability of KPS, PPS, PPI, and D-PaP in predicting survival in Chinese patients with terminal-stage tumors.
This is a prospective cohort study that collected data from 449 terminal-stage tumor patients across four medical institutions in China from January to December 2024. The feasibility of using KPS, PPS, PPI, and D-PaP to predict the 7-day and 30-day survival of terminal-stage tumor patients was discussed through ROC curves. Kaplan-Meier survival curves were used to examine the survival differences of terminal-stage tumor patients using four survival prediction tools with new cut-off values.
The study ultimately included 449 patients with terminal-stage tumors. For the prediction of 30-day survival, the area under the ROC curve of KPS, PPI, PPS, and D-PaP was 0.842, 0.749, 0.778, and 0.898, respectively. In our study cohort, the optimal cut-off values were 25, 3, 35, and 9.25. Their corresponding sensitivity was 86.3%, 92.3%, 77.7%, and 76.0%, while their specificity was 69.7%, 44.4%, 67.7%, and 93.9%, respectively.
The results of this multicenter cohort analysis reveal that in terminal-stage tumor patients in China, KPS, PPS, PPI, and D-PaP are all effective for predicting survival. Specifically, D-PaP is more applicable for predicting 30-day survival. Although D-PaP showed the most significant predictive power, its accuracy in predicting 7-day and 30-day survival outcomes was not significantly superior to that of experienced palliative care professionals. Therefore, future research still needs to develop or update scoring tools with better predictive performance.
PMID:
42860033
Bibliographic data and abstract were imported from PubMed on 12 Oct 2026.
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