ArticleEuropean journal of epidemiology2023
The association between body fatness and mortality among breast cancer survivors: results from a prospective cohort study.
Article in European journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled 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.
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Impact of blood lipid levels on breast cancer prognosis: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Randomised phase-2 screening trial of intermittent energy restriction plus resistance exercise versus resistance exercise alone during chemotherapy for advanced breast cancer.British journal of cancer · 2025Trial
- Association of Visceral Obesity Indices With Survival Among Cancer Survivors: Evidence From Two Nationally Population-Based Cohort Study.Cancer medicine · 2026Article
- Effect of Healthy and Tumor-Associated Breast Adipose Tissue on Breast Cancer Cell Migration and Activation.Cancers · 2026Article
- Antibiotic use and survival from breast cancer: A population-based cohort study in England and Wales.Nature communications · 2025Article
- Body composition as a potential biomarker of recurrence risk in patients with triple-negative breast cancer.Breast cancer research and treatment · 2025Article
- Cohort profile: the CORDELIA study (Collaborative cOhorts Reassembled Data to study mEchanisms and Longterm Incidence of chronic diseAses).European journal of epidemiology · 2025Article
- Complex Role of Circulating Triglycerides in Breast Cancer Onset and Survival: Insights From Two-Sample Mendelian Randomization Study.Cancer medicine · 2025Article
- Body composition as a novel biomarker of recurrence risk in patients with triple-negative breast cancer.Research square · 2024Article
- Adiposity assessed close to diagnosis and prostate cancer prognosis in the EPIC study.JNCI cancer spectrum · 2024Article
- Impact of obesity on sentinel lymph node biopsy outcomes and survival in breast cancer patients: A single-center retrospective study.Cancer medicine · 2024Article
- Adipose Tissue Quantification Improves the Prognostic Value of GLIM Criteria in Advanced Gastric Cancer Patients.Nutrients · 2024Article
- Effects of Functional and Nutraceutical Foods in the Context of the Mediterranean Diet in Patients Diagnosed with Breast Cancer.Antioxidants (Basel, Switzerland) · 2023Review
- Association of Mediterranean diet with survival after breast cancer diagnosis in women from nine European countries: results from the EPIC cohort study.BMC medicine · 2023Article
- The impact of poor metabolic health on aggressive breast cancer: adipose tissue and tumor metabolism.Frontiers in endocrinology · 2023Review
- Cancer Care and Nutrition Counseling: The Role of the Oncologist in Patient Learning and Behavior Change.Global advances in integrative medicine and healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
30 authors.
Funding
Abstract
Evidence linking body fatness to breast cancer (BC) prognosis is limited. While it seems that excess adiposity is associated with poorer BC survival, there is uncertainty over whether weight changes reduce mortality. This study aimed to assess the association between body fatness and weight changes pre- and postdiagnosis and overall mortality and BC-specific mortality among BC survivors. Our study included 13,624 BC survivors from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, with a mean follow-up of 8.6 years after diagnosis. Anthropometric data were obtained at recruitment for all cases and at a second assessment during follow-up for a subsample. We measured general obesity using the body mass index (BMI), whereas waist circumference and A Body Shape Index were used as measures of abdominal obesity. The annual weight change was calculated for cases with two weight assessments. The association with overall mortality and BC-specific mortality were based on a multivariable Cox and Fine and Gray models, respectively. We performed Mendelian randomization (MR) analysis to investigate the potential causal association. Five-unit higher BMI prediagnosis was associated with a 10% (95% confidence interval: 5-15%) increase in overall mortality and 7% (0-15%) increase in dying from BC. Women with abdominal obesity demonstrated a 23% (11-37%) increase in overall mortality, independent of the association of BMI. Results related to weight change postdiagnosis suggested a U-shaped relationship with BC-specific mortality, with higher risk associated with losing weight or gaining > 2% of the weight annually. MR analyses were consistent with the identified associations. Our results support the detrimental association of excess body fatness on the survival of women with BC. Substantial weight changes postdiagnosis may be associated with poorer survival.
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.