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Record W3049534001 · doi:10.1002/pon.5522

Moderators of the effect of psychosocial interventions on fatigue in women with breast cancer and men with prostate cancer: Individual patient data meta‐analyses

2020· review· en· W3049534001 on OpenAlexaff
H.J.G. Abrahams, Hans Knoop, Maartje A. C. Schreurs, Neil K. Aaronson, Paul B. Jacobsen, Robert U. Newton, Kerry S. Courneya, Joanne F. Aitken, Cecilia Arving, Yvonne Brandberg, Suzanne K. Chambers, Marieke Gielissen, Bengt Glimelius, Martine M. Goedendorp, Kristi D. Graves, Sue P. Heiney, Rob Horne, Myra S. Hunter, Birgitta Johansson, Laurel Northouse, Hester S. A. Oldenburg, Judith B. Prins, Josée Savard, Marc van Beurden, Sanne W. van den Berg, Irma M. Verdonck‐de Leeuw, Laurien M. Buffart

Bibliographic record

VenuePsycho-Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversité LavalUniversity of Alberta
Fundersnot available
KeywordsPsychosocialMedicinePsychological interventionBreast cancerProstate cancerCancer-related fatigueMeta-analysisRandomized controlled trialCancerPhysical therapyConfidence intervalModerationInternal medicinePsychiatryPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Psychosocial interventions can reduce cancer-related fatigue effectively. However, it is still unclear if intervention effects differ across subgroups of patients. These meta-analyses aimed at evaluating moderator effects of (a) sociodemographic characteristics, (b) clinical characteristics, (c) baseline levels of fatigue and other symptoms, and (d) intervention-related characteristics on the effect of psychosocial interventions on cancer-related fatigue in patients with non-metastatic breast and prostate cancer. METHODS: Data were retrieved from the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) consortium. Potential moderators were studied with meta-analyses of pooled individual patient data from 14 randomized controlled trials through linear mixed-effects models with interaction tests. The analyses were conducted separately in patients with breast (n = 1091) and prostate cancer (n = 1008). RESULTS: Statistically significant, small overall effects of psychosocial interventions on fatigue were found (breast cancer: β = -0.19 [95% confidence interval (95%CI) = -0.30; -0.08]; prostate cancer: β = -0.11 [95%CI = -0.21; -0.00]). In both patient groups, intervention effects did not differ significantly by sociodemographic or clinical characteristics, nor by baseline levels of fatigue or pain. For intervention-related moderators (only tested among women with breast cancer), statistically significant larger effects were found for cognitive behavioral therapy as intervention strategy (β = -0.27 [95%CI = -0.40; -0.15]), fatigue-specific interventions (β = -0.48 [95%CI = -0.79; -0.18]), and interventions that only targeted patients with clinically relevant fatigue (β = -0.85 [95%CI = -1.40; -0.30]). CONCLUSIONS: Our findings did not provide evidence that any selected demographic or clinical characteristic, or baseline levels of fatigue or pain, moderated effects of psychosocial interventions on fatigue. A specific focus on decreasing fatigue seems beneficial for patients with breast cancer with clinically relevant fatigue.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.150
GPT teacher head0.462
Teacher spread0.312 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations17
Published2020
Admission routes1
Has abstractyes

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