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

Clustering Latent class analysis Long-term survivors Netherlands Cancer Registry PROFILES registry Patient-reported outcomes measures

Journal

The oncologist
ISSN: 1549-490X
Titre abrégé: Oncologist
Pays: England
ID NLM: 9607837

Informations de publication

Date de publication:
03 2021
Historique:
received: 23 04 2020
accepted: 09 12 2020
pubmed: 29 12 2020
medline: 22 6 2021
entrez: 28 12 2020
Statut: ppublish

Résumé

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. 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. 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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 33355968
doi: 10.1002/onco.13655
pmc: PMC7930435
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e492-e499

Informations de copyright

© 2020 The Authors. The Oncologist published by Wiley Periodicals LLC on behalf of AlphaMed Press.

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Auteurs

Felix J Clouth (FJ)

Department of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands.
Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands.

Arturo Moncada-Torres (A)

Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands.

Gijs Geleijnse (G)

Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands.

Floortje Mols (F)

Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands.
Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands.

Felice N van Erning (FN)

Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands.

Ignace H J T de Hingh (IHJT)

Department of Surgery, Catharina Hospital, Eindhoven, The Netherlands.
Department of Epidemiology, GROW School for Oncology and Developmental Biology, Maastricht University, The Netherlands.

Steffen C Pauws (SC)

Department of Communication and Cognition, Tilburg University, Tilburg, The Netherlands.

Lonneke V van de Poll-Franse (LV)

Department of Medical and Clinical Psychology, Tilburg University, Tilburg, The Netherlands.
Netherlands Comprehensive Cancer Organisation (IKNL), Utrecht, The Netherlands.
Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

Jeroen K Vermunt (JK)

Department of Methodology and Statistics, Tilburg University, Tilburg, The Netherlands.

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