학술논문
Identifying classes of the pain, fatigue, and depression symptom cluster in long-term prostate cancer survivors-results from the multi-regional Prostate Cancer Survivorship Study in Switzerland (PROCAS)
Original Article
Original Article
Document Type
Report
Author
Source
Supportive Care in Cancer. November 2021, Vol. 29 Issue 11, p6259, 11 p.
Subject
Language
English
ISSN
0941-4355
Abstract
Author(s): Salome Adam [sup.1] [sup.2], Melissa S. Y. Thong [sup.3], Eva Martin-Diener [sup.2], Bertrand Camey [sup.4], Céline Egger Hayoz [sup.4], Isabelle Konzelmann [sup.5], Seyed Mohsen Mousavi [sup.6] [sup.7], Christian Herrmann [...]
Purpose Aside from urological and sexual problems, long-term ([greater than or equal to]5 years after initial diagnosis) prostate cancer (PC) survivors might suffer from pain, fatigue, and depression. These concurrent symptoms can form a cluster. In this study, we aimed to investigate classes of this symptom cluster in long-term PC survivors, to classify PC survivors accordingly, and to explore associations between classes of this cluster and health-related quality of life (HRQoL). Methods Six hundred fifty-three stage T1-T3N0M0 survivors were identified from the Prostate Cancer Survivorship in Switzerland (PROCAS) study. Fatigue was assessed with the EORTC QLQ-FA12, depressive symptoms with the MHI-5, and pain with the EORTC QLQ-C30 questionnaire. Latent class analysis was used to derive cluster classes. Factors associated with the derived classes were determined using multinomial logistic regression analysis. Results Three classes were identified: class 1 (61.4%) - 'low pain, low physical and emotional fatigue, moderate depressive symptoms'; class 2 (15.1%) - 'low physical fatigue and pain, moderate emotional fatigue, high depressive symptoms'; class 3 (23.5%) - high scores for all symptoms. Survivors in classes 2 and 3 were more likely to be physically inactive, report a history of depression or some other specific comorbidity, be treated with radiation therapy, and have worse HRQoL outcomes compared to class 1. Conclusion Three distinct classes of the pain, fatigue, and depression cluster were identified, which are associated with treatment, comorbidities, lifestyle factors, and HRQoL outcomes. Improving classification of PC survivors according to severity of multiple symptoms could assist in developing interventions tailored to survivors' needs.
Purpose Aside from urological and sexual problems, long-term ([greater than or equal to]5 years after initial diagnosis) prostate cancer (PC) survivors might suffer from pain, fatigue, and depression. These concurrent symptoms can form a cluster. In this study, we aimed to investigate classes of this symptom cluster in long-term PC survivors, to classify PC survivors accordingly, and to explore associations between classes of this cluster and health-related quality of life (HRQoL). Methods Six hundred fifty-three stage T1-T3N0M0 survivors were identified from the Prostate Cancer Survivorship in Switzerland (PROCAS) study. Fatigue was assessed with the EORTC QLQ-FA12, depressive symptoms with the MHI-5, and pain with the EORTC QLQ-C30 questionnaire. Latent class analysis was used to derive cluster classes. Factors associated with the derived classes were determined using multinomial logistic regression analysis. Results Three classes were identified: class 1 (61.4%) - 'low pain, low physical and emotional fatigue, moderate depressive symptoms'; class 2 (15.1%) - 'low physical fatigue and pain, moderate emotional fatigue, high depressive symptoms'; class 3 (23.5%) - high scores for all symptoms. Survivors in classes 2 and 3 were more likely to be physically inactive, report a history of depression or some other specific comorbidity, be treated with radiation therapy, and have worse HRQoL outcomes compared to class 1. Conclusion Three distinct classes of the pain, fatigue, and depression cluster were identified, which are associated with treatment, comorbidities, lifestyle factors, and HRQoL outcomes. Improving classification of PC survivors according to severity of multiple symptoms could assist in developing interventions tailored to survivors' needs.