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Changes In Health-related Fitness After Breast Cancer Treatment In The AMBER Cohort Study

2024· article· en· W4402662102 on OpenAlexaffabout
Fernanda Z. Arthuso, Ki‐Yong An, Qinggang Wang, Andria R. Morielli, Margaret L. McNeely, Jeff K. Vallance, S. Nicole Culos‐Reed, Gordon J. Bell, Leanne Dickau, Myriam Filion, Stephanie Ntoukas, Jessica McNeil, Karen Kopciuk, Lin Yang, Charles E. Matthews, Renée L. Kokts‐Porietis, John R. Mackey, Christine M. Friedenreich, Kerry S. Courneya

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsAthabasca UniversityAlberta Health ServicesUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsBreast cancerCohortMedicineCancerOncologyCohort studyGerontologyDemographyInternal medicineSociology

Abstract

fetched live from OpenAlex

Early-stage breast cancer patients often receive multimodal cancer treatments consisting of various combinations of surgery, chemotherapy, radiotherapy, targeted therapy, and hormone therapy. Limited data are available on how these treatment modalities affect different domains of health-related fitness (HRF). PURPOSE: The present study reports the associations between different breast cancer treatment modalities and 1-year changes in HRF. METHODS: Newly diagnosed early-stage breast cancer patients were recruited between 2012-2019 in Edmonton and Calgary, Canada for the Alberta Moving Beyond Breast Cancer (AMBER) cohort study. Participants completed HRF assessments within 90 days of diagnosis and one year after diagnosis including cardiorespiratory fitness (VO2peak treadmill test), muscular fitness (upper and lower body muscular strength and endurance), and body composition (DXA scan). Treatment data were abstracted from electronic medical records. Analysis of covariance examined changes in HRF by different treatment modalities and combinations. RESULTS: AMBER included 1,528 participants of which 41.4% had a mastectomy, 58.2% chemotherapy, 74.3% radiotherapy, 81.6% hormone therapy, and 16% targeted therapy. Receiving chemotherapy was associated with a decrease in upper body strength (p = 0.048), fat-free mass (p = 0.049), and bone mineral density (p < 0.001). Receiving radiotherapy was associated with a decrease in relative VO2peak (p = 0.025) and bone mineral density (p < 0.001). Having a mastectomy was linked to a reduction in upper body endurance (p = 0.037). Receiving hormone therapy was associated with reductions in lower body strength (p = 0.033), lean mass (p = 0.001), and fat-free mass (p = 0.002). Receiving targeted therapy was associated with a decline in relative VO2peak (p = 0.017). The combination of receiving all 5 treatment modalities (n = 55) was associated with increased body weight (p = 0.043) and decreased bone mineral density (p = 0.023). CONCLUSIONS: Different cancer treatments uniquely impact different HRF domains in early-stage breast cancer. Understanding the changes in HRF based on individual and combinations of treatment modalities will inform tailored exercise interventions during and after breast cancer treatments. Team Grant (#107534), Project Grant (#155952), and Foundation Grant (#159927) from the Canadian Institutes of Health Research, Canada Research Chairs Program, Alberta Innovates Health Senior Scholar Award, Alberta Cancer Foundation Weekend to End Women's Cancers Breast Cancer Chair

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.318
Teacher spread0.301 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes2
Has abstractyes

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