Comparison of Survival Prognostic Tools in Terminal‐Stage Tumor Patients: A Multicenter Prospective Cohort Study
- 1Jiangsu Cancer Hospital
Abstract
Aim 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. Methods 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. Results 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. Conclusion 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.
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BibTeX
@article{cheng2026comparison,
title = {{Comparison of Survival Prognostic Tools in Terminal‐Stage Tumor Patients: A Multicenter Prospective Cohort Study}},
author = {Ziluo Cheng and Lu Jin and Zhen Mei and Yeping Wang},
journal = {Cancer medicine},
year = {2026},
month = oct,
doi = {10.1002/cam4.72283},
url = {https://europepmc.org/article/PMC/PMC13654485},
note = {CC BY-NC},
}
RIS
TY - JOUR
TI - Comparison of Survival Prognostic Tools in Terminal‐Stage Tumor Patients: A Multicenter Prospective Cohort Study
AU - Ziluo Cheng
AU - Lu Jin
AU - Zhen Mei
AU - Yeping Wang
PY - 2026
DA - 2026/10/01
JO - Cancer medicine
DO - 10.1002/cam4.72283
UR - https://europepmc.org/article/PMC/PMC13654485
AB - Aim 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. Methods 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. Results 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. Conclusion 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.
SN - 2045-7634
ER -