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Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics

PURPOSE: Examine the association between obesity and clinical outcomes in early breast cancer and assess if patient, tumor, and treatment characteristics modify such associations in Malmö Diet and Cancer Study patients (MDCS). METHODS: The MDCS enrolled 17,035 Swedish women from 1991 to 1996. At enr...

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Autores principales: Harborg, Sixten, Feldt, Maria, Cronin-Fenton, Deirdre, Klintman, Marie, Dalton, Susanne O., Rosendahl, Ann H., Borgquist, Signe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294507/
https://www.ncbi.nlm.nih.gov/pubmed/37370158
http://dx.doi.org/10.1186/s40170-023-00308-0
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author Harborg, Sixten
Feldt, Maria
Cronin-Fenton, Deirdre
Klintman, Marie
Dalton, Susanne O.
Rosendahl, Ann H.
Borgquist, Signe
author_facet Harborg, Sixten
Feldt, Maria
Cronin-Fenton, Deirdre
Klintman, Marie
Dalton, Susanne O.
Rosendahl, Ann H.
Borgquist, Signe
author_sort Harborg, Sixten
collection PubMed
description PURPOSE: Examine the association between obesity and clinical outcomes in early breast cancer and assess if patient, tumor, and treatment characteristics modify such associations in Malmö Diet and Cancer Study patients (MDCS). METHODS: The MDCS enrolled 17,035 Swedish women from 1991 to 1996. At enrollment, participants' body mass index (BMI), waist circumference and body fat percentage measures were collected. We identified all female MDCS participants with invasive breast cancer from 1991 to 2014. Follow-up began at breast cancer diagnosis and ended at breast cancer recurrence (BCR), death, emigration, or June 8, 2020. The World Health Organization guidelines were used to classify BMI, waist circumference, and body fat percentage into three categories of healthy weight, overweight, and obesity. We fit Cox regression models to compute adjusted hazard ratios (HRs) with 95% confidence intervals (CI) of BCR according to body composition. To evaluate effect measure modification, we stratified Cox models by patient, tumor, and treatment characteristics. RESULTS: In total, 263 BCRs were diagnosed over 12,816 person-years among 1099 breast cancer patients with a median follow-up of 11.1 years. Obesity according to BMI (HR = 1.44 [95%CI 1.00–2.07]), waist circumference (HR = 1.31 [95%CI 0.98–1.77]), and body fat percentage (HR = 1.41 [95%CI 1.02–1.98]) was associated with increased risk of BCR compared with healthy weight. Obesity was stronger associated with BCR in patients with low socioeconomic position (HR = 2.55 [95%CI 1.08–6.02]), larger tumors > 20 mm (HR = 2.68 [95%CI 1.42–5.06]), estrogen-receptor-negative breast cancer (HR = 3.13 [95%CI 1.09–8.97]), and with adjuvant chemotherapy treatment (HR = 2.06 [95%CI 1.08–4.31]). CONCLUSION: Higher pre-diagnostic BMI, waist circumference, and body fat percentage was associated with increased risk of BCR. The association between obesity and BCR appears dependent on patient, tumor, and treatment characteristics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40170-023-00308-0.
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spelling pubmed-102945072023-06-28 Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics Harborg, Sixten Feldt, Maria Cronin-Fenton, Deirdre Klintman, Marie Dalton, Susanne O. Rosendahl, Ann H. Borgquist, Signe Cancer Metab Research PURPOSE: Examine the association between obesity and clinical outcomes in early breast cancer and assess if patient, tumor, and treatment characteristics modify such associations in Malmö Diet and Cancer Study patients (MDCS). METHODS: The MDCS enrolled 17,035 Swedish women from 1991 to 1996. At enrollment, participants' body mass index (BMI), waist circumference and body fat percentage measures were collected. We identified all female MDCS participants with invasive breast cancer from 1991 to 2014. Follow-up began at breast cancer diagnosis and ended at breast cancer recurrence (BCR), death, emigration, or June 8, 2020. The World Health Organization guidelines were used to classify BMI, waist circumference, and body fat percentage into three categories of healthy weight, overweight, and obesity. We fit Cox regression models to compute adjusted hazard ratios (HRs) with 95% confidence intervals (CI) of BCR according to body composition. To evaluate effect measure modification, we stratified Cox models by patient, tumor, and treatment characteristics. RESULTS: In total, 263 BCRs were diagnosed over 12,816 person-years among 1099 breast cancer patients with a median follow-up of 11.1 years. Obesity according to BMI (HR = 1.44 [95%CI 1.00–2.07]), waist circumference (HR = 1.31 [95%CI 0.98–1.77]), and body fat percentage (HR = 1.41 [95%CI 1.02–1.98]) was associated with increased risk of BCR compared with healthy weight. Obesity was stronger associated with BCR in patients with low socioeconomic position (HR = 2.55 [95%CI 1.08–6.02]), larger tumors > 20 mm (HR = 2.68 [95%CI 1.42–5.06]), estrogen-receptor-negative breast cancer (HR = 3.13 [95%CI 1.09–8.97]), and with adjuvant chemotherapy treatment (HR = 2.06 [95%CI 1.08–4.31]). CONCLUSION: Higher pre-diagnostic BMI, waist circumference, and body fat percentage was associated with increased risk of BCR. The association between obesity and BCR appears dependent on patient, tumor, and treatment characteristics. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40170-023-00308-0. BioMed Central 2023-06-27 /pmc/articles/PMC10294507/ /pubmed/37370158 http://dx.doi.org/10.1186/s40170-023-00308-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Harborg, Sixten
Feldt, Maria
Cronin-Fenton, Deirdre
Klintman, Marie
Dalton, Susanne O.
Rosendahl, Ann H.
Borgquist, Signe
Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics
title Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics
title_full Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics
title_fullStr Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics
title_full_unstemmed Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics
title_short Obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics
title_sort obesity and breast cancer prognosis: pre-diagnostic anthropometric measures in relation to patient, tumor, and treatment characteristics
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10294507/
https://www.ncbi.nlm.nih.gov/pubmed/37370158
http://dx.doi.org/10.1186/s40170-023-00308-0
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