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Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry

BACKGROUND: Long‐term colon cancer survivors present heterogeneous health‐related quality of life (HRQOL) outcomes. We determined unobserved subgroups (classes) of survivors with similar HRQOL patterns and investigated their stability over time and the association of clinical covariates with these c...

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Autores principales: Clouth, Felix J., Moncada‐Torres, Arturo, Geleijnse, Gijs, Mols, Floortje, van Erning, Felice N., de Hingh, Ignace H.J.T., Pauws, Steffen C., van de Poll‐Franse, Lonneke V., Vermunt, Jeroen K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930435/
https://www.ncbi.nlm.nih.gov/pubmed/33355968
http://dx.doi.org/10.1002/onco.13655
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author Clouth, Felix J.
Moncada‐Torres, Arturo
Geleijnse, Gijs
Mols, Floortje
van Erning, Felice N.
de Hingh, Ignace H.J.T.
Pauws, Steffen C.
van de Poll‐Franse, Lonneke V.
Vermunt, Jeroen K.
author_facet Clouth, Felix J.
Moncada‐Torres, Arturo
Geleijnse, Gijs
Mols, Floortje
van Erning, Felice N.
de Hingh, Ignace H.J.T.
Pauws, Steffen C.
van de Poll‐Franse, Lonneke V.
Vermunt, Jeroen K.
author_sort Clouth, Felix J.
collection PubMed
description BACKGROUND: Long‐term colon cancer survivors present heterogeneous health‐related quality of life (HRQOL) outcomes. We determined unobserved subgroups (classes) of survivors with similar HRQOL patterns and investigated their stability over time and the association of clinical covariates with these classes. MATERIALS AND METHODS: Data from the population‐based PROFILES registry were used. Included were survivors with nonmetastatic (TNM stage I–III) colon cancer (n = 1,489). HRQOL was assessed with the Dutch translation of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 version 3.0. Based on survivors’ HRQOL, latent class analysis (LCA) was used to identify unobserved classes of survivors. Moreover, latent transition analysis (LTA) was used to investigate changes in class membership over time. Furthermore, the effect of covariates on class membership was assessed using multinomial logistic regression. RESULTS: LCA identified five classes at baseline: class 1, excellent HRQOL (n = 555, 37.3%); class 2, good HRQOL with prevalence of insomnia (n = 464, 31.2%); class 3, moderate HRQOL with prevalence of fatigue (n = 213, 14.3%); class 4, good HRQOL with physical limitations (n = 134, 9.0%); and class 5, poor HRQOL (n = 123, 8.3%). All classes were stable with high self‐transition probabilities. Longer time since the diagnosis, no comorbid conditions, and male sex were associated with class 1, whereas older age was associated with class 4. Clinical covariates were not associated with class membership. CONCLUSION: The identified classes are characterized by distinct patterns of HRQOL and can support patient‐centered care. LCA and LTA are powerful tools for investigating HRQOL in cancer survivors. IMPLICATIONS FOR PRACTICE: Long‐term colon cancer survivors show great heterogeneity in their health‐related quality of life. This study identified five distinct clusters of survivors with similar patterns of health‐related quality of life and showed that these clusters remain stable over time. It was also shown that these clusters do not significantly differ in tumor characteristics or received treatment. Cluster membership of long‐term survivors can be identified by sociodemographic characteristics but is not predetermined by diagnosis and treatment.
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spelling pubmed-79304352021-03-12 Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry Clouth, Felix J. Moncada‐Torres, Arturo Geleijnse, Gijs Mols, Floortje van Erning, Felice N. de Hingh, Ignace H.J.T. Pauws, Steffen C. van de Poll‐Franse, Lonneke V. Vermunt, Jeroen K. Oncologist Symptom Management and Supportive Care BACKGROUND: Long‐term colon cancer survivors present heterogeneous health‐related quality of life (HRQOL) outcomes. We determined unobserved subgroups (classes) of survivors with similar HRQOL patterns and investigated their stability over time and the association of clinical covariates with these classes. MATERIALS AND METHODS: Data from the population‐based PROFILES registry were used. Included were survivors with nonmetastatic (TNM stage I–III) colon cancer (n = 1,489). HRQOL was assessed with the Dutch translation of the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 version 3.0. Based on survivors’ HRQOL, latent class analysis (LCA) was used to identify unobserved classes of survivors. Moreover, latent transition analysis (LTA) was used to investigate changes in class membership over time. Furthermore, the effect of covariates on class membership was assessed using multinomial logistic regression. RESULTS: LCA identified five classes at baseline: class 1, excellent HRQOL (n = 555, 37.3%); class 2, good HRQOL with prevalence of insomnia (n = 464, 31.2%); class 3, moderate HRQOL with prevalence of fatigue (n = 213, 14.3%); class 4, good HRQOL with physical limitations (n = 134, 9.0%); and class 5, poor HRQOL (n = 123, 8.3%). All classes were stable with high self‐transition probabilities. Longer time since the diagnosis, no comorbid conditions, and male sex were associated with class 1, whereas older age was associated with class 4. Clinical covariates were not associated with class membership. CONCLUSION: The identified classes are characterized by distinct patterns of HRQOL and can support patient‐centered care. LCA and LTA are powerful tools for investigating HRQOL in cancer survivors. IMPLICATIONS FOR PRACTICE: Long‐term colon cancer survivors show great heterogeneity in their health‐related quality of life. This study identified five distinct clusters of survivors with similar patterns of health‐related quality of life and showed that these clusters remain stable over time. It was also shown that these clusters do not significantly differ in tumor characteristics or received treatment. Cluster membership of long‐term survivors can be identified by sociodemographic characteristics but is not predetermined by diagnosis and treatment. John Wiley & Sons, Inc. 2021-01-11 2021-03 /pmc/articles/PMC7930435/ /pubmed/33355968 http://dx.doi.org/10.1002/onco.13655 Text en © 2020 The Authors. The Oncologist published by Wiley Periodicals LLC on behalf of AlphaMed Press. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Symptom Management and Supportive Care
Clouth, Felix J.
Moncada‐Torres, Arturo
Geleijnse, Gijs
Mols, Floortje
van Erning, Felice N.
de Hingh, Ignace H.J.T.
Pauws, Steffen C.
van de Poll‐Franse, Lonneke V.
Vermunt, Jeroen K.
Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry
title Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry
title_full Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry
title_fullStr Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry
title_full_unstemmed Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry
title_short Heterogeneity in Quality of Life of Long‐Term Colon Cancer Survivors: A Latent Class Analysis of the Population‐Based PROFILES Registry
title_sort heterogeneity in quality of life of long‐term colon cancer survivors: a latent class analysis of the population‐based profiles registry
topic Symptom Management and Supportive Care
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7930435/
https://www.ncbi.nlm.nih.gov/pubmed/33355968
http://dx.doi.org/10.1002/onco.13655
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