Evidence map›Paper›PMID 41991638›Full record

ArticleBreast cancer research and treatment2026

The association of an exercise and rehabilitation clinical workflow algorithm on sedentary behavior and performance status from time of breast cancer diagnosis and throughout care.

Kelsey E Maslana, Ryan D Burns, Yang Bai, Mary C Playdon, Paul A Estabrooks, Carson Saviers-Steiger, Emily R Dunston, Patrick Galyean, Elisabeth R Kimball, Susan L Zickmund and 10 more

Abstract read
In one paragraph

Article in Breast cancer research and treatment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Kelsey E MaslanaDepartment of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA.
Ryan D BurnsDepartment of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA.
Yang BaiDepartment of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA.
Mary C PlaydonDepartment of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT, USA.
Paul A EstabrooksDepartment of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA.
Carson Saviers-SteigerThe Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Emily R DunstonDepartment of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA.
Patrick GalyeanDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA.
Elisabeth R KimballDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA.
Susan L ZickmundDivision of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA.
Pamela A HansenThe Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Cornelia M UlrichThe Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Paul C LaStayoDepartment of Physical Therapy and Athletic Training, University of Utah, Salt Lake City, UT, USA.
David SteinbergDepartment of Physical Medicine and Rehabilitation, University of Utah School of Medicine, Salt Lake City, UT, USA.
Christopher S NorenTherapy Services, University of Utah Health, Salt Lake City, UT, USA.
A 'Lisha FinchThe Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Leanne SeckingerTherapy Services, University of Utah Health, Salt Lake City, UT, USA.
Sonal OzaDepartment of Rehabilitation Medicine, Emory University, Atlanta, GA, USA.
Kirstyn E BrownsonThe Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Adriana M ColettaDepartment of Health and Kinesiology, University of Utah, Salt Lake City, UT, USA. Adriana.coletta@hci.utah.edu.

Funding

Creatine supplementation and resistance training to preserve muscle mass and attenuate cancer progression: A double-blind randomized controlled trialR01CA281759 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Neeraj Agarwal, Adriana Coletta · 2023 to 2026
$2.7M
NCI NIH HHS R01 CA281759
6 · The paper itself

Abstract

purposeExplore if a clinical workflow algorithm that connected Stage I-III newly diagnosed breast cancer (BC) patients to exercise and rehabilitation services from diagnosis throughout care associated with a lower percentage of time spent in sedentary behavior (SB)compared with standard of care (SOC). We also examined the relationship between SB and ECOG performance status scores, a measure of functional status.

methodsThis secondary data analysis from the Comprehensive Oncology Rehabilitation and Exercise (CORE) program was carried out among 51 BC survivors (CORE = 33, SOC = 18) with evaluable wrist-worn accelerometer data. Percentage of time in SB was assessed using wrist-worn specific cut-points (Montoye) and traditional cut-points (Freedson) three times during BC care: preoperative, first postoperative visit, and 24 weeks postoperative. Repeated measures analysis of covariance tests (RM-ANCOVA; adjusted for age, cancer stage, and number of postoperative treatments) with post-hoc comparisons evaluated SB over time within and between groups. Poisson regression evaluated associations between SB and ECOG.

resultsParticipants were mostly white (76.5%), non-Hispanic (90.2%), with mean age 58.8 ± 12.3 years, diagnosed with Stage I BC (86.3%) and had a history of more than two adjuvant treatments (56.9%), with no significant differences between groups (p > 0.05). Proportion of time spent in SB (Montoye cut-points) was 73.95% (95% CI 70.60, 77.30) preoperatively; 77.79% (95% CI 74.23, 81.35) postoperatively; and 75.05% (95% CI 71.88, 78.22) 24 weeks postoperatively, although these time effect results did not reach statistical significance in the adjusted model. A time x group interaction was observed with Freedson cut-points (mean difference: 6.15%, 95% CI 0.42, 11.88). Between preoperative and 24 weeks postoperative timepoints, pairwise comparisons indicated that CORE intervention group participants exhibited a significant increase in percentage of time in SB (mean difference: 6.09%, 95% CI 0.24, 11.93). ECOG scores at each timepoint were not associated with SB (p > 0.05).

conclusionCORE program participation was not associated with reduced SB. Strategies to reduce SB should be incorporated within programs aimed at increasing physical activity engagement.

Indexed as

AlgorithmsBreast NeoplasmsExerciseExercise TherapySedentary BehaviorAgedFemaleHumansMiddle AgedNeoplasm StagingWorkflowBreast cancer treatmentPhysical inactivitySedentary behavior

Identifiers

PMID41991638
PMCPMC13292615

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.