Literature DB >> 20152588

Evaluating correlation and interrater reliability for four performance scales in the palliative care setting.

Jeff Myers1, Kate Gardiner, Kristin Harris, Tammy Lilien, Margaret Bennett, Edward Chow, Debbie Selby, Liying Zhang.   

Abstract

Performance scales are used by clinicians to objectively represent a patient's level of function and have been shown to be important predictors of response to therapy and survival. Four different scales are commonly used in the palliative care setting, two of which were specifically developed to more accurately represent this population. It remains unclear which scale is best suited for this setting. The objectives of this study were to determine the correlations among the four scales and concurrently compare interrater reliability for each. Patients were each assessed at the same point in time by three different health care professionals, and all four scales were used to rate each patient. Spearman correlation coefficient values and both weighted and unweighted kappa values were calculated to determine correlation and interrater reliability. The results confirmed highly significant linear correlation among and between all four scales. Whether using a reliability measure that incorporates the concept of "partial credit" for "near misses" or a measure reflecting exact rater agreement, no one scale emerged as having a significantly higher likelihood of agreement among raters. We propose that what may be more important than clinical experience or rater profession is the level of training an individual health care professional rater receives on the administration of any particular performance scale. In addition, given that low levels of exact rater agreement could have substantial clinical implications for patients, we suggest that this parameter be considered in the design of future comparative studies. Copyright 2010 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20152588     DOI: 10.1016/j.jpainsymman.2009.06.013

Source DB:  PubMed          Journal:  J Pain Symptom Manage        ISSN: 0885-3924            Impact factor:   3.612


  13 in total

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Journal:  J Neurooncol       Date:  2016-09-16       Impact factor: 4.130

2.  Patient Functional Status at Transplant and Its Impact on Posttransplant Survival of Adult Deceased-donor Kidney Recipients.

Authors:  Kevin Bui; Vikram Kilambi; James R Rodrigue; Sanjay Mehrotra
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3.  Feasibility of Fitness Tracker Usage to Assess Activity Level and Toxicities in Patients With Colorectal Cancer.

Authors:  William H Ward; Caitlin R Meeker; Elizabeth Handorf; Maureen V Hill; Margret Einarson; R Katherine Alpaugh; Thomas L Holden; Igor Astsaturov; Crystal S Denlinger; Michael J Hall; Sanjay S Reddy; Elin R Sigurdson; Efrat Dotan; Matthew Zibelman; Joshua E Meyer; Jeffrey M Farma; Namrata Vijayvergia
Journal:  JCO Clin Cancer Inform       Date:  2021-01

4.  The Functionality Assessment Flowchart (FAF): a new simple and reliable method to measure performance status with a high percentage of agreement between observers.

Authors:  Carlos Eduardo Paiva; Felipe Augusto Ferreira Siquelli; Henrique Amorim Santos; Marina Moreira Costa; Daniella Ramone Massaro; Domício Carvalho Lacerda; João Soares Nunes; Cristiano de Pádua Souza; Bianca Sakamoto Ribeiro Paiva
Journal:  BMC Cancer       Date:  2015-07-05       Impact factor: 4.430

5.  Functional Outcomes and Health-Related Quality of Life Following Glioma Surgery.

Authors:  Philip C De Witt Hamer; Philip C De Witt Hamer; Martin Klein; Shawn L Hervey-Jumper; Jeffrey S Wefel; Mitchel S Berger
Journal:  Neurosurgery       Date:  2021-03-15       Impact factor: 4.654

Review 6.  Immunotherapy in patients with non-small cell lung cancer with ECOG PS 2.

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7.  Karnofsky Performance Score-Failure to Thrive as a Frailty Proxy?

Authors:  Margaret R Stedman; Daniel J Watford; Glenn M Chertow; Jane C Tan
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Review 8.  Moving beyond Karnofsky and ECOG Performance Status Assessments with New Technologies.

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Journal:  J Oncol       Date:  2016-03-15       Impact factor: 4.375

9.  Effects of a transitional palliative care model on patients with end-stage heart failure: study protocol for a randomized controlled trial.

Authors:  Alina Yee Man Ng; Frances Kam Yuet Wong; Paul Hong Lee
Journal:  Trials       Date:  2016-03-31       Impact factor: 2.279

10.  Validation of the Palliative Prognostic Index, Performance Status-Based Palliative Prognostic Index and Chinese Prognostic Scale in a home palliative care setting for patients with advanced cancer in China.

Authors:  Jun Zhou; Sitao Xu; Ziye Cao; Jing Tang; Xiang Fang; Ling Qin; Fangping Zhou; Yuzhen He; Xueren Zhong; Mingcai Hu; Yan Wang; Fengjuan Lu; Yongzheng Bao; Xiangheng Dai; Qiang Wu
Journal:  BMC Palliat Care       Date:  2020-10-31       Impact factor: 3.234

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