Literature DB >> 30919569

Nonpharmacological Interventions for Cancer-Related Fatigue: A Systematic Review and Bayesian Network Meta-Analysis.

Chunxiao Wu1, Yan Zheng1, Yuting Duan1, Xin Lai1, Shaoyang Cui2, Nenggui Xu1, Chunzhi Tang1, Liming Lu1,3.   

Abstract

BACKGROUND: Nonpharmacological interventions are the first recommendation for cancer-related fatigue, according to current guidelines. There are many forms of nonpharmacological interventions for addressing cancer-related fatigue, but the preferred means remain controversial and are not stated in the guidelines. Therefore, we evaluated the comparative effects and ranks of all major nonpharmacological interventions, according to different assessment methods, in cancer patients with fatigue.
METHODS: Medline, Embase, Cochrane Library, and Allied and Complementary Medicine Database were searched for randomized controlled trials on nonpharmacological treatments for cancer-related fatigue. We assessed the trials' methodological quality using the Cochrane Risk of Bias tool. A Bayesian network meta-analysis and a comparative effects ranking were performed with Aggregate Data Drug Information System software.
RESULTS: A total of 16,675 items were obtained from the databases, and 182 studies comprising 18,491 participants were included in the analysis. Based on the ranking probabilities, multimodal therapy and qigong ranked best with a Brief Fatigue Inventory; for a Functional Assessment of Cancer Therapy-fatigue scale, combined psychosocial therapies and bright white light therapy ranked best; for the Piper Fatigue Scale, resistance exercise and mindfulness-based stress reduction ranked best; for a multidimensional fatigue inventory, multimodal therapy and cognitive behavioral therapy (CBT) ranked best; for the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), acupuncture and CBT ranked best; and for the Profile of Mood States Fatigue Subscale, multimodal therapy, qigong, aerobic exercise, and CBT ranked best. Comprehensive analysis of the results indicated that multimodal therapy, CBT, and qigong might be the optimum selections for reducing cancer-related fatigue. Most of the included studies had low risk of methodological quality problems; however, 59 studies had low methodological quality. LINKING EVIDENCE TO ACTION: Different interventions have their own sets of advantages for addressing cancer-related fatigue. These results can be utilized as evidence-based interventions for healthcare workers and patients to manage cancer-related fatigue.
© 2019 Sigma Theta Tau International.

Entities:  

Keywords:  cancer-related fatigue; comparative effects; network meta-analysis; nonpharmacological intervention; ranking

Mesh:

Year:  2019        PMID: 30919569     DOI: 10.1111/wvn.12352

Source DB:  PubMed          Journal:  Worldviews Evid Based Nurs        ISSN: 1545-102X            Impact factor:   2.931


  12 in total

Review 1.  Emerging digital technologies in cancer treatment, prevention, and control.

Authors:  Bradford W Hesse; Dominika Kwasnicka; David K Ahern
Journal:  Transl Behav Med       Date:  2021-11-30       Impact factor: 3.626

2.  Impact of a Multimodal and Combination Therapy on Self-Regulation and Internal Coherence in German Breast Cancer Survivors With Chronic Cancer-Related Fatigue: A Mixed-Method Comprehensive Cohort Design Study.

Authors:  Annette Mehl; Marcus Reif; Roland Zerm; Danilo Pranga; Dorothea Friemel; Bettina Berger; Benno Brinkhaus; Christoph Gutenbrunner; Arndt Büssing; Matthias Kröz
Journal:  Integr Cancer Ther       Date:  2020 Jan-Dec       Impact factor: 3.279

3.  Blue-wavelength light therapy for post-traumatic brain injury sleepiness, sleep disturbance, depression, and fatigue: A systematic review and network meta-analysis.

Authors:  Karan Srisurapanont; Yanisa Samakarn; Boonyasit Kamklong; Phichayakan Siratrairat; Arina Bumiputra; Montita Jaikwang; Manit Srisurapanont
Journal:  PLoS One       Date:  2021-02-04       Impact factor: 3.240

4.  Combined effects of acupuncture and auricular acupressure for relieving cancer-related fatigue in patients during lung cancer chemotherapy: A protocol for systematic review and meta-analysis.

Authors:  Han Li; Huan Liu
Journal:  Medicine (Baltimore)       Date:  2021-10-22       Impact factor: 1.817

5.  Acupuncture and moxibustion for cancer-related psychological disorders: A protocol for systematic review and meta-analysis.

Authors:  Yan Jiang; Dan Liang; Yadi He; Jing Wang; Guixing Xu; Jun Wang
Journal:  Medicine (Baltimore)       Date:  2022-03-11       Impact factor: 1.817

6.  Development and Refinement of a Telehealth Intervention for Symptom Management, Distress, and Adherence to Adjuvant Endocrine Therapy after Breast Cancer.

Authors:  Jamie M Jacobs; Emily A Walsh; Chelsea S Rapoport; Michael H Antoni; Elyse R Park; Kathryn Post; Amy Comander; Jeffrey Peppercorn; Steven A Safren; Jennifer S Temel; Joseph A Greer
Journal:  J Clin Psychol Med Settings       Date:  2020-11-21

7.  Prevalence and severity of long-term physical, emotional, and cognitive fatigue across 15 different cancer entities.

Authors:  Martina E Schmidt; Silke Hermann; Volker Arndt; Karen Steindorf
Journal:  Cancer Med       Date:  2020-09-07       Impact factor: 4.452

8.  The Effects of Acupuncture on Cancer-Related Fatigue: Updated Systematic Review and Meta-Analysis.

Authors:  Andrew Jang; Chris Brown; Gillian Lamoury; Marita Morgia; Frances Boyle; Isobel Marr; Stephen Clarke; Michael Back; Byeongsang Oh
Journal:  Integr Cancer Ther       Date:  2020 Jan-Dec       Impact factor: 3.279

9.  The effectiveness of non-pharmacological interventions on cancer related fatigue in breast cancer patients: A protocol for systematic review and network meta-analysis.

Authors:  Yu Liu; Pengzhu Xu; Chunli Song; Tongtong Jiang; Jun-E Liu; Tieying Shi
Journal:  Nurs Open       Date:  2021-11-01

10.  Efficacy and safety of acupuncture in patients with cancer-related fatigue: A protocol for systematic review and meta-analysis.

Authors:  Tai-Jun Jiang; Feng-Ya Zhu; Li-Jie Tang; Zheng-Kang Liu; Xi Wu
Journal:  Medicine (Baltimore)       Date:  2020-10-16       Impact factor: 1.817

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.