Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Sep 30;5(1):408-416.
doi: 10.1089/pmr.2024.0036. eCollection 2024.

Validation of Modified Objective Prognostic Score in Patients with Advanced Cancer in Taiwan

Yusuke Hiratsuka  1   2 , Sang-Yeon Suh  3   4 , Seok Joon Yoon  5 , Shao-Yi Cheng  6 , Sung-Eun Choi  7 , Sun Hyun Kim  8 , David Hui  9 , Ping-Jen Chen  10 , Hsien-Liang Huang  6 , Jen-Kuei Peng  6 , Masanori Mori  11 , Takashi Yamaguchi  12 , Isseki Maeda  13 , Satoru Tsuneto  14 , Tatsuya Morita  11
Affiliations

Validation of Modified Objective Prognostic Score in Patients with Advanced Cancer in Taiwan

Yusuke Hiratsuka et al. Palliat Med Rep. .

Abstract

Background: Modified versions of the Objective Prognostic Score (mOPS) needs to be validated to reflect practical palliative care circumstances in Taiwan.

Objectives: We compared the abilities of an mOPS score of 1.5 or higher versus a Karnofsky Performance Status (KPS) score of 30 or lower to predict 2-week mortality in patients with advanced cancer in Taiwan.

Design: Observational study.

Setting/subjects: We performed a secondary analysis of an international multicenter cohort study of patients in East Asia. Participants were inpatients with advanced cancer in palliative care units (PCUs) in Taiwan.

Measurements: We compared the mOPS-B model, which does not require laboratory tests, with the KPS in a 2-week survival timeframe. We compared the accuracy of the prognostic models using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Calibration plots and net reclassification indices (NRI) for 2-week survival were compared between the two models. Differences in survival between the higher- and lower-scoring groups of each model were identified using the log-rank test.

Results: We included 317 patients, with a median survival of 14.0 days. The mOPS-B had a high sensitivity (0.82) and high AUROC value (0.69). By contrast, the KPS demonstrated good sensitivity (0.77) and an acceptable AUROC value (0.65) for predicting 2-week survival. The calibration plot did not demonstrate satisfactory agreement between the actual and predicted survival times in either the mOPS-B or the KPS groups. Our NRI was positive (absolute value: 22%), indicating that mOPS-B predicted 2-week survival better than KPS.

Conclusions: The mOPS-B may serve better than the KPS as a screening tool for admission to PCUs in Taiwan because it was more accurate at predicting 2-week survival.

Keywords: advanced cancer; palliative care; prognostication; validity.

PubMed Disclaimer

Figures

FIG. 1.
FIG. 1.
Participant flowchart.
FIG. 2.
FIG. 2.
Kaplan–Meier survival curves for overall survival according to modified Objective Prognostic Score-B and Karnofsky Performance Status from the time of enrollment. (A) Modified Objective Prognostic Score-B. (B) Karnofsky Performance Status. p-Values were derived using a log-rank test.
FIG. 3.
FIG. 3.
Receiver operating characteristic curve for the modified Objective Prognostic Score-B and Karnofsky Performance Status to predict 2-week survival. (A) Modified Objective Prognostic Score-B. (B) Karnofsky Performance Status.
FIG. 4.
FIG. 4.
Calibration plots of the modified Objective Prognostic Score-B and Karnofsky Performance Status. (A) Modified Objective Prognostic Score-B. (B) Karnofsky Performance Status. The decile on the x-axis represents the survival time predicted by the modified Objective Prognostic Score-B or Karnofsky Performance Status, and the decile on the y-axis represents the actual survival time. The reference line (red line) indicates a perfect model in which the actual survival time is equal to the predicted survival time.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Stone P, Buckle P, Dolan R, et al. ESMO Guidelines Committee. Electronic address: clinicalguidelines@esmo.org . Prognostic evaluation in patients with advanced cancer in the last months of life: ESMO clinical practice guideline. ESMO Open 2023;8(2):101195; doi:10.1016/j.esmoop.2023.101195 - DOI - PMC - PubMed
    1. White N, Reid F, Harris A, et al. . A systematic review of predictions of survival in palliative care: How accurate are clinicians and who are the experts? PLoS One 2016;11(8):e0161407; doi:10.1371/journal.pone.0161407 - DOI - PMC - PubMed
    1. Suh SY, Choi YS, Shim JY, et al. . Construction of a new, objective prognostic score for terminally ill cancer patients: A multicenter study. Support Care Cancer 2010;18(2):151–157; doi:10.1007/s00520-009-0639-x - DOI - PubMed
    1. Yoon SJ, Jung JG., Kim JS, et al. Retrospective assessment of objective prognostic score in terminally ill Korean patients with cancer. Am J Hosp Palliat Care 2014;31(4):435–440; doi:10.1177/1049909113492557 - DOI - PubMed
    1. Yoon SJ, Jung JG, Kim JS, et al. . Comparison of accuracy among prognostic scores for predicting life expectancy in Korean patients with cancer with weeks of survival. Am J Hosp Palliat Care 2014;31(8):845–852; doi:10.1177/1049909113503486 - DOI - PubMed

LinkOut - more resources