Literature DB >> 12449742

Use of family proxies in quality of life research for cancer patients at the end of life: a literature review.

Siew Tzuh Tang1, Ruth McCorkle.   

Abstract

One of the main goals of end-of-life care is to achieve the best quality of life (QOL) for patients and their families. Quality of life, therefore, represents a significant outcome indicator to evaluate end-of-life care interventions. However, nonresponse bias and nonrandom missing data in QOL research at the end-of-life limits the generalizability and threatens the internal validity of the study findings. The use of family proxy of patients' QOL has been suggested as a solution. Demonstration of satisfactory levels of agreement between proxies and patients is warranted before family caregivers' or other proxies' assessments can be employed when patients cannot provide their own information. Contrary to the conclusion made by Sprangers and Aaronson [The Role of Health Care Providers and Significant Others in Evaluating the Quality of Life of Patients with Chronic Disease: A Review. J. Clin. Epidemiol. 1992, 45, 743-760], it is suggested from this review of literature that terminal cancer patients and their family caregivers agreed at least moderately well on the patients' QOL. The bias introduced by the use of family informants is generally of a modest magnitude. When discrepancies existed, without exception, family caregivers held a more negative view of patients' QOL than did patients. When using family proxies, this is important to remember. The degree of agreement between terminal cancer patients' and their family caregivers' assessments varies as a function of the dimensions of QOL being measured and the patient's health status. However, the accuracy of family caregivers' assessments can be improved by assessing both patients and family caregivers concurrently over time. Several suggestions for future research are provided to better understand the influencing factors of agreement between patients and family assessments and to enhance the quality of statistical analyses on this topic.

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Year:  2002        PMID: 12449742     DOI: 10.1081/cnv-120005928

Source DB:  PubMed          Journal:  Cancer Invest        ISSN: 0735-7907            Impact factor:   2.176


  38 in total

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Authors:  Ruth McConigley; Tania Shelby-James; David C Currow
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2.  How do proxy responses and proxy-assisted responses differ from what Medicare beneficiaries might have reported about their health care?

Authors:  Marc N Elliott; Megan K Beckett; Kelly Chong; Katrin Hambarsoomians; Ron D Hays
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Review 3.  Using QALYs in cancer: a review of the methodological limitations.

Authors:  Martina Garau; Koonal K Shah; Anne R Mason; Qing Wang; Adrian Towse; Michael F Drummond
Journal:  Pharmacoeconomics       Date:  2011-08       Impact factor: 4.981

4.  Measuring health-related quality-of-life for Alzheimer's disease using the general public.

Authors:  Feng Xie; Mark Oremus; Kathryn Gaebel
Journal:  Qual Life Res       Date:  2011-07-09       Impact factor: 4.147

Review 5.  Systematic review of caregiver responses for patient health-related quality of life in adult cancer care.

Authors:  Jessica K Roydhouse; Ira B Wilson
Journal:  Qual Life Res       Date:  2017-03-14       Impact factor: 4.147

6.  What do laypersons consider as a good death.

Authors:  Kai-Kuen Leung; Wen-Jing Liu; Shao-Yi Cheng; Tai-Yuan Chiu; Ching-Yu Chen
Journal:  Support Care Cancer       Date:  2008-11-04       Impact factor: 3.603

7.  Late-stage HIV/AIDS patients' and their familial caregivers' agreement on the palliative care outcome scale.

Authors:  Rachel Krug; Daniel Karus; Peter A Selwyn; Victoria H Raveis
Journal:  J Pain Symptom Manage       Date:  2009-09-25       Impact factor: 3.612

8.  An eHealth system supporting palliative care for patients with non-small cell lung cancer: a randomized trial.

Authors:  David H Gustafson; Lori L DuBenske; Kang Namkoong; Robert Hawkins; Ming-Yuan Chih; Amy K Atwood; Roberta Johnson; Abhik Bhattacharya; Cindy L Carmack; Anne M Traynor; Toby C Campbell; Mary K Buss; Ramaswamy Govindan; Joan H Schiller; James F Cleary
Journal:  Cancer       Date:  2013-01-25       Impact factor: 6.860

9.  Sensitivity analysis for nonignorable missingness and outcome misclassification from proxy reports.

Authors:  Michelle Shardell; Eleanor M Simonsick; Gregory E Hicks; Barbara Resnick; Luigi Ferrucci; Jay Magaziner
Journal:  Epidemiology       Date:  2013-03       Impact factor: 4.822

10.  Caregivers for people with end-stage lung disease: characteristics and unmet needs in the whole population.

Authors:  David C Currow; Alicia Ward; Katie Clark; Catherine M Burns; Amy P Abernethy
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2008
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