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1000 Titel
  • 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)
1000 Autor/in
  1. Adam, Salome |
  2. Thong, Melissa |
  3. Martin-Diener, Eva |
  4. Camey, Bertrand |
  5. Egger Hayoz, Céline |
  6. Konzelmann, Isabelle |
  7. Mousavi, Seyed Mohsen |
  8. Herrmann, Christian |
  9. Rohrmann, Sabine |
  10. Wanner, Miriam |
  11. Staehelin, Katharina |
  12. Strebel, Räto T. |
  13. Randazzo, Marco |
  14. John, Hubert |
  15. Schmid, Hans-Peter |
  16. Feller, Anita |
  17. Arndt, Volker |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-04-13
1000 Erschienen in
1000 Quellenangabe
  • 29(11):6259-6269
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s00520-021-06132-w |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8464556/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Purpose!#!Aside from urological and sexual problems, long-term (≥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.
1000 Sacherschließung
lokal Fatigue/epidemiology [MeSH]
lokal Surveys and Questionnaires [MeSH]
lokal Switzerland/epidemiology [MeSH]
lokal Depression/epidemiology [MeSH]
lokal Humans [MeSH]
lokal Syndrome [MeSH]
lokal Prostatic Neoplasms/epidemiology [MeSH]
lokal Fatigue/etiology [MeSH]
lokal Symptom cluster
lokal Survivorship [MeSH]
lokal Pain/epidemiology [MeSH]
lokal Original Article
lokal Classes
lokal Depression
lokal Pain/etiology [MeSH]
lokal Male [MeSH]
lokal Fatigue
lokal Cancer Survivors [MeSH]
lokal Quality of Life [MeSH]
lokal Pain
lokal Depression/etiology [MeSH]
lokal Prostate cancer
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/QWRhbSwgU2Fsb21l|https://orcid.org/0000-0002-6987-705X|https://frl.publisso.de/adhoc/uri/TWFydGluLURpZW5lciwgRXZh|https://frl.publisso.de/adhoc/uri/Q2FtZXksIEJlcnRyYW5k|https://frl.publisso.de/adhoc/uri/RWdnZXIgSGF5b3osIEPDqWxpbmU=|https://frl.publisso.de/adhoc/uri/S29uemVsbWFubiwgSXNhYmVsbGU=|https://frl.publisso.de/adhoc/uri/TW91c2F2aSwgU2V5ZWQgTW9oc2Vu|https://frl.publisso.de/adhoc/uri/SGVycm1hbm4sIENocmlzdGlhbg==|https://frl.publisso.de/adhoc/uri/Um9ocm1hbm4sIFNhYmluZQ==|https://frl.publisso.de/adhoc/uri/V2FubmVyLCBNaXJpYW0=|https://frl.publisso.de/adhoc/uri/U3RhZWhlbGluLCBLYXRoYXJpbmE=|https://frl.publisso.de/adhoc/uri/U3RyZWJlbCwgUsOkdG8gVC4=|https://frl.publisso.de/adhoc/uri/UmFuZGF6em8sIE1hcmNv|https://frl.publisso.de/adhoc/uri/Sm9obiwgSHViZXJ0|https://frl.publisso.de/adhoc/uri/U2NobWlkLCBIYW5zLVBldGVy|https://frl.publisso.de/adhoc/uri/RmVsbGVyLCBBbml0YQ==|https://orcid.org/0000-0001-9320-8684
1000 Hinweis
  • DeepGreen-ID: 97f33f80b59d492ca7b1511f37e81c09 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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1000 Erstellt am 2023-04-28T13:49:30.617+0200
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1000 Zuletzt bearbeitet Fri Oct 20 18:45:13 CEST 2023
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