ArticleRadiology and oncology2026
Analysis of the effects of individualized nutrition and physical activities on body composition during the treatment of breast cancer patients.
Article in Radiology and oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMalnutrition and loss of skeletal muscle mass are common in breast cancer patients and represent negative prognostic factors. Combined nutrition and exercise interventions may help preserve body composition during treatment. The aim of this study was to evaluate the effects of a targeted nutritional and exercise intervention on body composition, assessed by Bioelectrical Impedance Analysis (BIA), in breast cancer patients undergoing treatment, stratified by baseline nutritional status according to the Global Leadership Initiative on Malnutrition (GLIM) criteria. PATIENTS AND
methodsIn this retrospective analysis of the OREH pilot study, 287 patients were included in the intervention group and 194 in the control group. All patients underwent BIA measurements at baseline, 6 months, and 12 months. Malnourished patients (GLIM-positive) in both groups received individualized nutritional counseling as standard care. GLIM-negative patients in the intervention group received preventive nutritional counseling via online lectures. All intervention group patients participated in supervised group exercise. Differences in BIA parameters (fat-free mass index, phase angle, fat mass, total body water, and body mass index) between the 3rd and 1st measurements were compared using Welch's t-test, with p-values adjusted by the Bonferroni-Holm method.
resultsNo statistically significant differences in body composition parameters were observed between the intervention and control groups over the 12-month follow-up period. The adjusted p-value for fat-free mass index (FFMI) was 0.2 in GLIM-positive patients and 1.0 in GLIM-negative patients. A trend toward greater FFMI increase was observed in GLIM-positive patients in the intervention group compared to controls (mean difference 0.30; 95% CI 0.05-0.54; unadjusted p = 0.017), but this did not remain significant after correction for multiple comparisons.
conclusionsThe combined nutritional and exercise intervention did not significantly improve BIA-derived body composition parameters. However, the trend toward FFMI improvement in GLIM-positive patients receiving individualized nutritional counseling suggests that personalized approaches may be more effective than group-based interventions. Future studies should incorporate individualized nutrition and resistance training programs to optimize body composition outcomes in breast cancer patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.