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Updated: Apr 20, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Validation of the prognosis in palliative care study predictor models in terminal cancer patients
Eun-Shin Kim1, Jung-Kwon Lee1, Mi-Hyun Kim1
1Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Background:
Prognosis in Palliative Care Study (PiPS) predictor models were developed in 2011 to estimate the survival of terminal cancer patients in the United Kingdom. The aim of this study was to validate the PiPS model for terminal cancer patients in Korea, and evaluate its value in clinical practice.
Methods:
This study included 202 advanced cancer patients who were admitted to the cancer hospital's palliative care ward from November 2011 to February 2013. On admission, physicians recorded the PiPS-A, PiPS-B, and doctor's survival estimates in inpatients.
Results:
The median survival across PiPS-A categories was 9, 28, and 33 days, and the median survival across PiPS-B was 9.5, 27, and 43 days. The median actual survival was 25 days; overall accuracy between the PiPS-A, PiPS-B, doctor's estimates of survival, and actual survival was 52.0%, 49.5%, and 46.5%, respectively. The PiPS-A and PiPS-B groups for survival in 'days' showed a sensitivity of 48.4% and 64.1%, and specificity of 87.7%, and 77.5%, respectively. The PiPS-A and PiPS-B groups for survival in 'weeks' showed a sensitivity of 59.2%, and 44.7%, and specificity of 61.6%, and 64.7%, respectively. The PiPS-A and PiPS-B 'months' group showed a sensitivity of 37.1% and 37.1%, and specificity of 74.9% and 78.4%, respectively. The 'weeks' and 'months' groups showed significantly prolonged survival rates than 'days' group did in both PiPS-A and PiPS-B, by the Kaplan-Meier method.
Conclusion:
The PiPS predictor models effectively predicted the survival ≥14 days in terminal cancer patients, and were superior to doctor's estimates.
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