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Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis

BACKGROUND: Research into the clustering of symptoms may improve the understanding of the underlying mechanisms that affect survivors' symptom burden. This study applied network analyses in a balanced sample of cancer survivors to 1) explore the clustering of symptoms and 2) assess differences...

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Autores principales: de Rooij, Belle H., Oerlemans, Simone, van Deun, Katrijn, Mols, Floortje, de Ligt, Kelly M., Husson, Olga, Ezendam, Nicole P. M., Hoedjes, Meeke, van de Poll‐Franse, Lonneke V., Schoormans, Dounya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9291877/
https://www.ncbi.nlm.nih.gov/pubmed/34387856
http://dx.doi.org/10.1002/cncr.33852
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author de Rooij, Belle H.
Oerlemans, Simone
van Deun, Katrijn
Mols, Floortje
de Ligt, Kelly M.
Husson, Olga
Ezendam, Nicole P. M.
Hoedjes, Meeke
van de Poll‐Franse, Lonneke V.
Schoormans, Dounya
author_facet de Rooij, Belle H.
Oerlemans, Simone
van Deun, Katrijn
Mols, Floortje
de Ligt, Kelly M.
Husson, Olga
Ezendam, Nicole P. M.
Hoedjes, Meeke
van de Poll‐Franse, Lonneke V.
Schoormans, Dounya
author_sort de Rooij, Belle H.
collection PubMed
description BACKGROUND: Research into the clustering of symptoms may improve the understanding of the underlying mechanisms that affect survivors' symptom burden. This study applied network analyses in a balanced sample of cancer survivors to 1) explore the clustering of symptoms and 2) assess differences in symptom clustering between cancer types, treatment regimens, and short‐term and long‐term survivors. METHODS: This study used cross‐sectional survey data, collected between 2008 and 2018, from the population‐based Patient Reported Outcomes Following Initial Treatment and Long Term Evaluation of Survivorship registry, which included survivors of 7 cancer types (colorectal cancer, breast cancer, ovarian cancer, thyroid cancer, chronic lymphocytic leukemia, Hodgkin lymphoma, and non‐Hodgkin lymphoma). Regularized partial correlation network analysis was used to explore and visualize the associations between self‐reported symptoms (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire) and the centrality of these symptoms in the network (ie, how strongly a symptom was connected to other symptoms) for the total sample and for subgroups separately. RESULTS: In the total sample (n = 1330), fatigue was the most central symptom in the network with moderate direct relationships with emotional symptoms, cognitive symptoms, appetite loss, dyspnea, and pain. These relationships persisted after adjustments for sociodemographic and clinical characteristics. Connections between fatigue and emotional symptoms, appetite loss, dyspnea, and pain were consistently found across all cancer types (190 for each), treatment regimens, and short‐term and long‐term survivors. CONCLUSIONS: In a heterogenous sample of cancer survivors, fatigue was consistently the most central symptom in all networks. Although longitudinal data are needed to build a case for the causal nature of these symptoms, cancer survivorship rehabilitation programs could focus on fatigue to reduce the overall symptom burden.
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spelling pubmed-92918772022-07-20 Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis de Rooij, Belle H. Oerlemans, Simone van Deun, Katrijn Mols, Floortje de Ligt, Kelly M. Husson, Olga Ezendam, Nicole P. M. Hoedjes, Meeke van de Poll‐Franse, Lonneke V. Schoormans, Dounya Cancer Original Articles BACKGROUND: Research into the clustering of symptoms may improve the understanding of the underlying mechanisms that affect survivors' symptom burden. This study applied network analyses in a balanced sample of cancer survivors to 1) explore the clustering of symptoms and 2) assess differences in symptom clustering between cancer types, treatment regimens, and short‐term and long‐term survivors. METHODS: This study used cross‐sectional survey data, collected between 2008 and 2018, from the population‐based Patient Reported Outcomes Following Initial Treatment and Long Term Evaluation of Survivorship registry, which included survivors of 7 cancer types (colorectal cancer, breast cancer, ovarian cancer, thyroid cancer, chronic lymphocytic leukemia, Hodgkin lymphoma, and non‐Hodgkin lymphoma). Regularized partial correlation network analysis was used to explore and visualize the associations between self‐reported symptoms (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire) and the centrality of these symptoms in the network (ie, how strongly a symptom was connected to other symptoms) for the total sample and for subgroups separately. RESULTS: In the total sample (n = 1330), fatigue was the most central symptom in the network with moderate direct relationships with emotional symptoms, cognitive symptoms, appetite loss, dyspnea, and pain. These relationships persisted after adjustments for sociodemographic and clinical characteristics. Connections between fatigue and emotional symptoms, appetite loss, dyspnea, and pain were consistently found across all cancer types (190 for each), treatment regimens, and short‐term and long‐term survivors. CONCLUSIONS: In a heterogenous sample of cancer survivors, fatigue was consistently the most central symptom in all networks. Although longitudinal data are needed to build a case for the causal nature of these symptoms, cancer survivorship rehabilitation programs could focus on fatigue to reduce the overall symptom burden. John Wiley and Sons Inc. 2021-08-13 2021-12-15 /pmc/articles/PMC9291877/ /pubmed/34387856 http://dx.doi.org/10.1002/cncr.33852 Text en © 2021 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://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 Original Articles
de Rooij, Belle H.
Oerlemans, Simone
van Deun, Katrijn
Mols, Floortje
de Ligt, Kelly M.
Husson, Olga
Ezendam, Nicole P. M.
Hoedjes, Meeke
van de Poll‐Franse, Lonneke V.
Schoormans, Dounya
Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis
title Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis
title_full Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis
title_fullStr Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis
title_full_unstemmed Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis
title_short Symptom clusters in 1330 survivors of 7 cancer types from the PROFILES registry: A network analysis
title_sort symptom clusters in 1330 survivors of 7 cancer types from the profiles registry: a network analysis
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9291877/
https://www.ncbi.nlm.nih.gov/pubmed/34387856
http://dx.doi.org/10.1002/cncr.33852
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