Literature DB >> 32892304

Using a Chinese time trade-off approach to explore the health utility level and quality of life of cancer patients in urban China: a multicentre cross-sectional study.

Hanyue Ding1, Ayan Mao2, Jiaye Lin1, Martin C S Wong1, Pei Dong2, Wuqi Qiu3.   

Abstract

PURPOSE: A quality of life assessment is useful in identifying a specific health impact on patients who are suffering from various medical conditions. This study estimated the quality of life among patients with cancers of the lungs, breast, colorectum, oesophagus, liver, and stomach in urban China and evaluates the associated factors.
METHODS: This study employed a random cluster sampling strategy to recruit patients with lung, breast, colorectal, oesophageal, liver, or stomach cancer from eleven third-grade class-A (the highest level) hospitals in Beijing between October 2013 and May 2014. We performed a quality of life survey that included solicitation of sociodemographic and clinical information and the use of a EuroQoL five-dimension three-level questionnaire. We applied the Chinese time trade-off method to calculate the health utility values, which were transformed into binary variables (using the median as the cut-off). In addition, multivariable logistic regression analysis was used to examine the factors associated with the quality of life.
RESULTS: A total of 637 patients (91 with lung cancer, 152 with breast cancer, 60 with colorectal cancer, 108 with oesophageal cancer, 154 with liver cancer, and 72 with stomach cancer) were included in this study; the medians of the health utility values were 0.780, 0.800, 0.800, 0.860, 0.800, and 0.870, respectively. The most common concerns for patients of all six cancer types were pain/discomfort and anxiety/depression. The reported health status of patients was associated with various demographic and clinical variables.
CONCLUSION: This study highlighted that pain relief and psychological support are important aspects of patient management for those with these types of cancer. Individuals with factors associated with a poorer quality of life should be targets for additional support.

Entities:  

Keywords:  Breast neoplasms; Colorectal neoplasms; Liver neoplasms; Lung neoplasms; Oesophageal neoplasms; Quality of life; Stomach neoplasms

Mesh:

Year:  2020        PMID: 32892304     DOI: 10.1007/s00520-020-05729-x

Source DB:  PubMed          Journal:  Support Care Cancer        ISSN: 0941-4355            Impact factor:   3.603


  26 in total

1.  The estimation of a preference-based measure of health from the SF-36.

Authors:  John Brazier; Jennifer Roberts; Mark Deverill
Journal:  J Health Econ       Date:  2002-03       Impact factor: 3.883

2.  Preliminary findings of an investigation into the relationship between national culture and EQ-5D value sets.

Authors:  Henry Bailey; Paul Kind
Journal:  Qual Life Res       Date:  2010-05-23       Impact factor: 4.147

Review 3.  Use of quality-adjusted life years for the estimation of effectiveness of health care: A systematic literature review.

Authors:  Pirjo Räsänen; Eija Roine; Harri Sintonen; Virpi Semberg-Konttinen; Olli-Pekka Ryynänen; Risto Roine
Journal:  Int J Technol Assess Health Care       Date:  2006       Impact factor: 2.188

4.  Real-World EQ5D Health Utility Scores for Patients With Metastatic Lung Cancer by Molecular Alteration and Response to Therapy.

Authors:  Catherine Labbé; Yvonne Leung; João Gabriel Silva Lemes; Erin Stewart; Catherine Brown; Andrea Perez Cosio; Mark Doherty; Grainne M O'Kane; Devalben Patel; Nicholas Cheng; Mindy Liang; Gursharan Gill; Alexandra Rett; Hiten Naik; Lawson Eng; Nicole Mittmann; Natasha B Leighl; Penelope A Bradbury; Frances A Shepherd; Wei Xu; Geoffrey Liu; Doris Howell
Journal:  Clin Lung Cancer       Date:  2016-12-28       Impact factor: 4.785

Review 5.  Health utilities using the EQ-5D in studies of cancer.

Authors:  A Simon Pickard; Caitlyn T Wilke; Hsiang-Wen Lin; Andrew Lloyd
Journal:  Pharmacoeconomics       Date:  2007       Impact factor: 4.981

6.  The Functional Assessment of Cancer Therapy scale: development and validation of the general measure.

Authors:  D F Cella; D S Tulsky; G Gray; B Sarafian; E Linn; A Bonomi; M Silberman; S B Yellen; P Winicour; J Brannon
Journal:  J Clin Oncol       Date:  1993-03       Impact factor: 44.544

7.  Risk-Targeted Lung Cancer Screening: A Cost-Effectiveness Analysis.

Authors:  Vaibhav Kumar; Joshua T Cohen; David van Klaveren; Djøra I Soeteman; John B Wong; Peter J Neumann; David M Kent
Journal:  Ann Intern Med       Date:  2018-01-02       Impact factor: 25.391

8.  A pilot study of subjective well-being in colorectal cancer patients and their caregivers.

Authors:  Janet Graham; Pavlina Spiliopoulou; Rob Arbuckle; Julie Ann Bridge; James Cassidy
Journal:  Patient Relat Outcome Meas       Date:  2017-10-19

9.  Responsiveness of the EQ-5D in breast cancer patients in their first year after treatment.

Authors:  Merel L Kimman; Carmen D Dirksen; Philippe Lambin; Liesbeth J Boersma
Journal:  Health Qual Life Outcomes       Date:  2009-02-07       Impact factor: 3.186

10.  Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer.

Authors:  A Simon Pickard; Maureen P Neary; David Cella
Journal:  Health Qual Life Outcomes       Date:  2007-12-21       Impact factor: 3.186

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