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. 2019 Feb;33(2):206-212.
doi: 10.1177/0269216318811011. Epub 2018 Nov 8.

Predictors and trajectory of performance status in patients with advanced cancer: A secondary data analysis of the international European Palliative Care Cancer Symptom study

Jason W Boland  1 , Victoria Allgar  2 , Elaine G Boland  3 , Stein Kaasa  4 , Marianne J Hjermstad  4 , Miriam J Johnson  1
Affiliations

Predictors and trajectory of performance status in patients with advanced cancer: A secondary data analysis of the international European Palliative Care Cancer Symptom study

Jason W Boland et al. Palliat Med. 2019 Feb.

Abstract

Background:: Performance status, a predictor of cancer survival, and ability to maintain independent living deteriorate in advanced disease. Understanding predictors of performance status trajectory could help identify those at risk of functional deterioration, target support for independent living and reduce service costs. The relationship between symptoms, analgesics and performance status is poorly delineated.

Aim:: The aim of this study is to determine whether demographics, analgesics, disease characteristics, quality-of-life domains and C-reactive protein predict the trajectory of Karnofsky Performance Status (KPS) in patients with advanced cancer.

Design:: The study design is the secondary data analysis of the international prospective, longitudinal European Palliative Care Cancer Symptom study (ClinicalTrials.gov: NCT01362816). A multivariable regression model was built for KPS area under the curve per day (AUC).

Setting and participants:: This included adults with advanced, incurable cancer receiving palliative care, without severe cognitive impairment and who were not imminently dying (n = 1739).

Results:: The mean daily KPS AUC (n = 1052) was 41.1 (standard deviation = 14.1). Opioids (p < 0.001), co-analgesics (p = 0.023), poorer physical functioning (p < 0.001) and appetite loss (p = 0.009) at baseline were explanatory factors for lower KPS AUC. A subgroup analysis of participants with C-reactive protein data (n = 240) showed that only C-reactive protein (p = 0.040) and physical function (p < 0.001) were associated with lower KPS AUC.

Conclusion:: This study is novel in determining explanatory factors for subsequent functional trajectories in an international dataset and identifying systemic inflammation as a candidate therapeutic target to improve functional performance. The effect of interventions targeting physical function, appetite and inflammation, such as those used for cachexia management, on maintaining functional status in patients with advanced cancer needs to be investigated.

Keywords: Karnofsky Performance Status; analgesics; appetite; inflammation; neoplasms; opioids.

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Conflict of interest statement

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

References

    1. Yamada T, Morita T, Maeda I, et al. A prospective, multicenter cohort study to validate a simple performance status-based survival prediction system for oncologists. Cancer 2016; 123: 1442–1452. - PubMed
    1. Verweij NM, Schiphorst AH, Pronk A, et al. Physical performance measures for predicting outcome in cancer patients: a systematic review. Acta Oncol 2016; 55: 1386–1391. - PubMed
    1. Ferrat E, Paillaud E, Laurent M, et al. Predictors of 1-year mortality in a prospective cohort of elderly patients with cancer. J Gerontol A Biol Sci Med Sci 2015; 70: 1148–1155. - PubMed
    1. Laird BJ, Kaasa S, McMillan DC, et al. Prognostic factors in patients with advanced cancer: a comparison of clinicopathological factors and the development of an inflammation-based prognostic system. Clin Cancer Res 2013; 19: 5456–5464. - PubMed
    1. Jang RW, Caraiscos VB, Swami N, et al. Simple prognostic model for patients with advanced cancer based on performance status. J Oncol Pract 2014; 10: e335–e341. - PubMed

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