Related Experiment Video
Updated: Sep 7, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Are Prognostic Scores Better Than Clinician Judgment? A Prospective Study Using Three Models.
Yusuke Hiratsuka1, Sang-Yeon Suh1, David Hui1
1Department of Palliative Medicine (Y.H.), Takeda General Hospital, Aizuwakamatsu, Japan; Department of Palliative Medicine (Y.H., A.I.), Tohoku University School of Medicine, Sendai, Japan; Department of Family Medicine (S.Y.S.), Dongguk University Ilsan Hospital, Goyang-si, South Korea; Department of Medicine (S.Y.S.), Dongguk University Medical School, Seoul, South Korea; Department of Palliative Care (D.H.), Rehabilitation and Integrative Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA; Division of Palliative and Supportive Care (T.M., M.M.), Seirei Mikatahara General Hospital, Hamamatsu, Japan; Department of Biostatistics (S.O.), JORTC Data Center, Tokyo, Japan; Department of Palliative Medicine (K.A.), National Cancer Center Hospital, Tokyo, Japan; Seirei Hospice (K.I.), Seirei Mikatahara General Hospital, Hamamatsu, Japan; Department of Palliative Medicine (M.B.), Suita Tokushukai Hospital, Suita, Japan; Department of Internal Medicine (H.K.), Hatsukaichi Memorial Hospital, Hatsukaichi, Japan; Department of Palliative Medicine (T.H.), Tsukuba Medical Center Hospital, Tsukuba, Japan; Department of Palliative Care (I.M.), Senri Chuo Hospital, Toyonaka, Japan; Division of Clinical Medicine (J.H.), Faculty of Medicine, University of Tsukuba, Tsukuba, Japan.
Clinician's Prediction of Survival (CPS) and Palliative Prognostic Score (PaP) demonstrated superior prognostic performance compared to Palliative Performance Scale (PPS) and Palliative Prognostic Index (PPI) in palliative care unit patients. These findings aid in selecting appropriate prognostic tools for diverse clinical experience levels.
Area of Science:
- Palliative Care Medicine
- Prognostic Modeling
- Clinical Epidemiology
Background:
- Several prognostic models exist to predict survival in palliative care.
- Limited large-scale studies compare these models against Clinician's Prediction of Survival (CPS).
- Understanding the performance of tools like Palliative Performance Scale (PPS), Palliative Prognostic Index (PPI), and Palliative Prognostic Score (PaP) is crucial.
Purpose of the Study:
- To compare the prognostic performance of PPS, PPI, PaP, and CPS.
- To evaluate these tools in patients admitted to palliative care units (PCUs).
- To identify the most effective prognostic index for patients with weeks of survival.
Main Methods:
- A multi-center prospective observational study in Japanese PCUs.
- Inclusion of 1896 patients with a median survival of 19 days.
- Prognostic performance assessed using Area Under the Receiver Operating Characteristics Curve (AUROC) and calibration plots for 7-, 14-, 30-, and 60-day survival.
Main Results:
- All four prognostic indices (PPS, PPI, PaP, CPS) showed good performance.
- AUROC values ranged from 73% to 87% across different survival timeframes.
- Clinician's Prediction of Survival (CPS) and Palliative Prognostic Score (PaP) significantly outperformed PPS and PPI.
Conclusions:
- PPS, PPI, PaP, and CPS are effective prognostic tools for PCU patients with short-term survival.
- CPS and PaP offer superior prognostic accuracy compared to PPS and PPI.
- CPS is suitable for experienced clinicians; PPS may enhance confidence for less experienced clinicians.
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Cancer Survival Analysis
Receiver Operating Characteristic Plot

