Candidate predictors of health-related quality of life of colorectal cancer survivors

A systematic review

M.J. Bours, B.W.A. van der Linden, R.M. Winkels, F.J. van Duijnhoven, F. Mols, E.H. van Roekel, E. Kampman, S. Beijer, M.P. Weijenberg

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The population of colorectal cancer (CRC) survivors is growing and many survivors experience deteriorated health-related quality of life (HRQoL) in both early and late post-treatment phases. Identification of CRC survivors at risk for HRQoL deterioration can be improved by using prediction models. However, such models are currently not available for oncology practice. As a starting point for developing prediction models of HRQoL for CRC survivors, a comprehensive overview of potential candidate HRQoL predictors is necessary. Therefore, a systematic literature review was conducted to identify candidate predictors of HRQoL of CRC survivors. Original research articles on associations of biopsychosocial factors with HRQoL of CRC survivors were searched in PubMed, Embase, and Google Scholar. Two independent reviewers assessed eligibility and selected articles for inclusion (N = 53). Strength of evidence for candidate HRQoL predictors was graded according to predefined methodological criteria. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) was used to develop a biopsychosocial framework in which identified candidate HRQoL predictors were mapped across the main domains of the ICF: health condition, body structures and functions, activities, participation, and personal and environmental factors. The developed biopsychosocial ICF framework serves as a basis for selecting candidate HRQoL predictors, thereby providing conceptual guidance for developing comprehensive, evidence-based prediction models of HRQoL for CRC survivors. Such models are useful in clinical oncology practice to aid in identifying individual CRC survivors at risk for HRQoL deterioration and could also provide potential targets for a biopsychosocial intervention aimed at safeguarding the HRQoL of at-risk individuals.
Implications for Practice:
More and more people now survive a diagnosis of colorectal cancer. The quality of life of these cancer survivors is threatened by health problems persisting for years after diagnosis and treatment. Early identification of survivors at risk of experiencing low quality of life in the future is thus important for taking preventive measures. Clinical prediction models are tools that can help oncologists identify at-risk individuals. However, such models are currently not available for clinical oncology practice. This systematic review outlines candidate predictors of low quality of life of colorectal cancer survivors, providing a firm conceptual basis for developing prediction models.
Original languageEnglish
Pages (from-to)433-452
JournalThe Oncologist
Volume21
Issue number4
DOIs
Publication statusPublished - 2016

Fingerprint

Survivors
Medical Oncology
PubMed

Cite this

Bours, M. J., van der Linden, B. W. A., Winkels, R. M., van Duijnhoven, F. J., Mols, F., van Roekel, E. H., ... Weijenberg, M. P. (2016). Candidate predictors of health-related quality of life of colorectal cancer survivors: A systematic review. The Oncologist, 21(4), 433-452. https://doi.org/10.1634/theoncologist.2015-0258
Bours, M.J. ; van der Linden, B.W.A. ; Winkels, R.M. ; van Duijnhoven, F.J. ; Mols, F. ; van Roekel, E.H. ; Kampman, E. ; Beijer, S. ; Weijenberg, M.P. / Candidate predictors of health-related quality of life of colorectal cancer survivors : A systematic review. In: The Oncologist. 2016 ; Vol. 21, No. 4. pp. 433-452.
@article{a3746cfff4e64e05930069cf03d161ac,
title = "Candidate predictors of health-related quality of life of colorectal cancer survivors: A systematic review",
abstract = "The population of colorectal cancer (CRC) survivors is growing and many survivors experience deteriorated health-related quality of life (HRQoL) in both early and late post-treatment phases. Identification of CRC survivors at risk for HRQoL deterioration can be improved by using prediction models. However, such models are currently not available for oncology practice. As a starting point for developing prediction models of HRQoL for CRC survivors, a comprehensive overview of potential candidate HRQoL predictors is necessary. Therefore, a systematic literature review was conducted to identify candidate predictors of HRQoL of CRC survivors. Original research articles on associations of biopsychosocial factors with HRQoL of CRC survivors were searched in PubMed, Embase, and Google Scholar. Two independent reviewers assessed eligibility and selected articles for inclusion (N = 53). Strength of evidence for candidate HRQoL predictors was graded according to predefined methodological criteria. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) was used to develop a biopsychosocial framework in which identified candidate HRQoL predictors were mapped across the main domains of the ICF: health condition, body structures and functions, activities, participation, and personal and environmental factors. The developed biopsychosocial ICF framework serves as a basis for selecting candidate HRQoL predictors, thereby providing conceptual guidance for developing comprehensive, evidence-based prediction models of HRQoL for CRC survivors. Such models are useful in clinical oncology practice to aid in identifying individual CRC survivors at risk for HRQoL deterioration and could also provide potential targets for a biopsychosocial intervention aimed at safeguarding the HRQoL of at-risk individuals.Implications for Practice:More and more people now survive a diagnosis of colorectal cancer. The quality of life of these cancer survivors is threatened by health problems persisting for years after diagnosis and treatment. Early identification of survivors at risk of experiencing low quality of life in the future is thus important for taking preventive measures. Clinical prediction models are tools that can help oncologists identify at-risk individuals. However, such models are currently not available for clinical oncology practice. This systematic review outlines candidate predictors of low quality of life of colorectal cancer survivors, providing a firm conceptual basis for developing prediction models.",
author = "M.J. Bours and {van der Linden}, B.W.A. and R.M. Winkels and {van Duijnhoven}, F.J. and F. Mols and {van Roekel}, E.H. and E. Kampman and S. Beijer and M.P. Weijenberg",
year = "2016",
doi = "10.1634/theoncologist.2015-0258",
language = "English",
volume = "21",
pages = "433--452",
journal = "The Oncologist",
issn = "1083-7159",
publisher = "AlphaMed Press",
number = "4",

}

Bours, MJ, van der Linden, BWA, Winkels, RM, van Duijnhoven, FJ, Mols, F, van Roekel, EH, Kampman, E, Beijer, S & Weijenberg, MP 2016, 'Candidate predictors of health-related quality of life of colorectal cancer survivors: A systematic review', The Oncologist, vol. 21, no. 4, pp. 433-452. https://doi.org/10.1634/theoncologist.2015-0258

Candidate predictors of health-related quality of life of colorectal cancer survivors : A systematic review. / Bours, M.J.; van der Linden, B.W.A.; Winkels, R.M.; van Duijnhoven, F.J.; Mols, F.; van Roekel, E.H.; Kampman, E.; Beijer, S.; Weijenberg, M.P.

In: The Oncologist, Vol. 21, No. 4, 2016, p. 433-452.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Candidate predictors of health-related quality of life of colorectal cancer survivors

T2 - A systematic review

AU - Bours, M.J.

AU - van der Linden, B.W.A.

AU - Winkels, R.M.

AU - van Duijnhoven, F.J.

AU - Mols, F.

AU - van Roekel, E.H.

AU - Kampman, E.

AU - Beijer, S.

AU - Weijenberg, M.P.

PY - 2016

Y1 - 2016

N2 - The population of colorectal cancer (CRC) survivors is growing and many survivors experience deteriorated health-related quality of life (HRQoL) in both early and late post-treatment phases. Identification of CRC survivors at risk for HRQoL deterioration can be improved by using prediction models. However, such models are currently not available for oncology practice. As a starting point for developing prediction models of HRQoL for CRC survivors, a comprehensive overview of potential candidate HRQoL predictors is necessary. Therefore, a systematic literature review was conducted to identify candidate predictors of HRQoL of CRC survivors. Original research articles on associations of biopsychosocial factors with HRQoL of CRC survivors were searched in PubMed, Embase, and Google Scholar. Two independent reviewers assessed eligibility and selected articles for inclusion (N = 53). Strength of evidence for candidate HRQoL predictors was graded according to predefined methodological criteria. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) was used to develop a biopsychosocial framework in which identified candidate HRQoL predictors were mapped across the main domains of the ICF: health condition, body structures and functions, activities, participation, and personal and environmental factors. The developed biopsychosocial ICF framework serves as a basis for selecting candidate HRQoL predictors, thereby providing conceptual guidance for developing comprehensive, evidence-based prediction models of HRQoL for CRC survivors. Such models are useful in clinical oncology practice to aid in identifying individual CRC survivors at risk for HRQoL deterioration and could also provide potential targets for a biopsychosocial intervention aimed at safeguarding the HRQoL of at-risk individuals.Implications for Practice:More and more people now survive a diagnosis of colorectal cancer. The quality of life of these cancer survivors is threatened by health problems persisting for years after diagnosis and treatment. Early identification of survivors at risk of experiencing low quality of life in the future is thus important for taking preventive measures. Clinical prediction models are tools that can help oncologists identify at-risk individuals. However, such models are currently not available for clinical oncology practice. This systematic review outlines candidate predictors of low quality of life of colorectal cancer survivors, providing a firm conceptual basis for developing prediction models.

AB - The population of colorectal cancer (CRC) survivors is growing and many survivors experience deteriorated health-related quality of life (HRQoL) in both early and late post-treatment phases. Identification of CRC survivors at risk for HRQoL deterioration can be improved by using prediction models. However, such models are currently not available for oncology practice. As a starting point for developing prediction models of HRQoL for CRC survivors, a comprehensive overview of potential candidate HRQoL predictors is necessary. Therefore, a systematic literature review was conducted to identify candidate predictors of HRQoL of CRC survivors. Original research articles on associations of biopsychosocial factors with HRQoL of CRC survivors were searched in PubMed, Embase, and Google Scholar. Two independent reviewers assessed eligibility and selected articles for inclusion (N = 53). Strength of evidence for candidate HRQoL predictors was graded according to predefined methodological criteria. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) was used to develop a biopsychosocial framework in which identified candidate HRQoL predictors were mapped across the main domains of the ICF: health condition, body structures and functions, activities, participation, and personal and environmental factors. The developed biopsychosocial ICF framework serves as a basis for selecting candidate HRQoL predictors, thereby providing conceptual guidance for developing comprehensive, evidence-based prediction models of HRQoL for CRC survivors. Such models are useful in clinical oncology practice to aid in identifying individual CRC survivors at risk for HRQoL deterioration and could also provide potential targets for a biopsychosocial intervention aimed at safeguarding the HRQoL of at-risk individuals.Implications for Practice:More and more people now survive a diagnosis of colorectal cancer. The quality of life of these cancer survivors is threatened by health problems persisting for years after diagnosis and treatment. Early identification of survivors at risk of experiencing low quality of life in the future is thus important for taking preventive measures. Clinical prediction models are tools that can help oncologists identify at-risk individuals. However, such models are currently not available for clinical oncology practice. This systematic review outlines candidate predictors of low quality of life of colorectal cancer survivors, providing a firm conceptual basis for developing prediction models.

U2 - 10.1634/theoncologist.2015-0258

DO - 10.1634/theoncologist.2015-0258

M3 - Article

VL - 21

SP - 433

EP - 452

JO - The Oncologist

JF - The Oncologist

SN - 1083-7159

IS - 4

ER -