MétaCan
Menu
Back to cohort
Record W4396948218 · doi:10.1200/jco.24.00541

Management of Fatigue in Adult Survivors of Cancer: ASCO–Society for Integrative Oncology Guideline Update

2024· review· en· W4396948218 on OpenAlexaff
Julienne E. Bower, Christina Lacchetti, Yesne Alici, Debra L. Barton, Deborah Watkins Bruner, Beverly Canin, Carmelita P. Escalante, Patricia A. Ganz, Sheila N. Garland, Shilpi Gupta, Heather Jim, Jennifer A. Ligibel, Kah Poh Loh, Luke J. Peppone, Debu Tripathy, Sriram Yennu, Suzanna M. Zick, Karen M. Mustian

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsMemorial University of Newfoundland
FundersNational Cancer Institute
KeywordsMedicineGuidelineClinical OncologyInternal medicineOncologyCancerCancer-related fatiguePathology

Abstract

fetched live from OpenAlex

ASCO–Society for Integrative Oncology (SIO) Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the ASCO Guidelines Methodology Manual . ASCO-SIO Guidelines follow the ASCO Conflict of Interest Policy for Clinical Practice Guidelines . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO and SIO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by providers and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases or stages of diseases. Guidance is based on review and analysis of relevant literature, and is not intended as a statement of the standard of care. ASCO and SIO do not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and 2 (online only) for more. PURPOSE To update the ASCO guideline on the management of cancer-related fatigue (CRF) in adult survivors of cancer. METHODS A multidisciplinary panel of medical oncology, geriatric oncology, internal medicine, psychology, psychiatry, exercise oncology, integrative medicine, behavioral oncology, nursing, and advocacy experts was convened. Guideline development involved a systematic literature review of randomized controlled trials (RCTs) published in 2013-2023. RESULTS The evidence base consisted of 113 RCTs. Exercise, cognitive behavioral therapy (CBT), and mindfulness-based programs led to improvements in CRF both during and after the completion of cancer treatment. Tai chi, qigong, and American ginseng showed benefits during treatment, whereas yoga, acupressure, and moxibustion helped to manage CRF after completion of treatment. Use of other dietary supplements did not improve CRF during or after cancer treatment. In patients at the end of life, CBT and corticosteroids showed benefits. Certainty and quality of evidence were low to moderate for CRF management interventions. RECOMMENDATIONS Clinicians should recommend exercise, CBT, mindfulness-based programs, and tai chi or qigong to reduce the severity of fatigue during cancer treatment. Psychoeducation and American ginseng may be recommended in adults undergoing cancer treatment. For survivors after completion of treatment, clinicians should recommend exercise, CBT, and mindfulness-based programs; in particular, CBT and mindfulness-based programs have shown efficacy for managing moderate to severe fatigue after treatment. Yoga, acupressure, and moxibustion may also be recommended. Patients at the end of life may be offered CBT and corticosteroids. Clinicians should not recommend L-carnitine, antidepressants, wakefulness agents, or routinely recommend psychostimulants to manage symptoms of CRF. There is insufficient evidence to make recommendations for or against other psychosocial, integrative, or pharmacological interventions for the management of fatigue. Additional information is available at www.asco.org/survivorship-guidelines .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.005
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.194
GPT teacher head0.566
Teacher spread0.373 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations217
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicCancer survivorship and careFrench-language works237,207