Cargando…
A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old
BACKGROUND: Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women’s breast cancer (BC) risk, life expectancy, and values but is hard to implement because n...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872276/ https://www.ncbi.nlm.nih.gov/pubmed/36694222 http://dx.doi.org/10.1186/s13058-023-01605-8 |
_version_ | 1784877369472843776 |
---|---|
author | Schonberg, Mara A. Wolfson, Emily A. Eliassen, A. Heather Bertrand, Kimberly A. Shvetsov, Yurii B. Rosner, Bernard A. Palmer, Julie R. Ngo, Long H. |
author_facet | Schonberg, Mara A. Wolfson, Emily A. Eliassen, A. Heather Bertrand, Kimberly A. Shvetsov, Yurii B. Rosner, Bernard A. Palmer, Julie R. Ngo, Long H. |
author_sort | Schonberg, Mara A. |
collection | PubMed |
description | BACKGROUND: Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women’s breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women’s individualized BC risk and life expectancy. METHODS: Using competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses’ Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women’s Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk. RESULTS: Mean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784–0.796) in NHS and 0.768 (0.757–0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538–0.641) in NHS and 0.573 (0.536–0.611) in BWHS. CONCLUSIONS: We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-023-01605-8. |
format | Online Article Text |
id | pubmed-9872276 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98722762023-01-25 A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old Schonberg, Mara A. Wolfson, Emily A. Eliassen, A. Heather Bertrand, Kimberly A. Shvetsov, Yurii B. Rosner, Bernard A. Palmer, Julie R. Ngo, Long H. Breast Cancer Res Research BACKGROUND: Guidelines recommend shared decision making (SDM) for mammography screening for women ≥ 75 and not screening women with < 10-year life expectancy. High-quality SDM requires consideration of women’s breast cancer (BC) risk, life expectancy, and values but is hard to implement because no models simultaneously estimate older women’s individualized BC risk and life expectancy. METHODS: Using competing risk regression and data from 83,330 women > 55 years who completed the 2004 Nurses’ Health Study (NHS) questionnaire, we developed (in 2/3 of the cohort, n = 55,533) a model to predict 10-year non-breast cancer (BC) death. We considered 60 mortality risk factors and used best-subsets regression, the Akaike information criterion, and c-index, to identify the best-fitting model. We examined model performance in the remaining 1/3 of the NHS cohort (n = 27,777) and among 17,380 Black Women’s Health Study (BWHS) participants, ≥ 55 years, who completed the 2009 questionnaire. We then included the identified mortality predictors in a previously developed competing risk BC prediction model and examined model performance for predicting BC risk. RESULTS: Mean age of NHS development cohort participants was 70.1 years (± 7.0); over 10 years, 3.1% developed BC, 0.3% died of BC, and 20.1% died of other causes; NHS validation cohort participants were similar. BWHS participants were younger (mean age 63.7 years [± 6.7]); over 10-years 3.1% developed BC, 0.4% died of BC, and 11.1% died of other causes. The final non-BC death prediction model included 21 variables (age; body mass index [BMI]; physical function [3 measures]; comorbidities [12]; alcohol; smoking; age at menopause; and mammography use). The final BC prediction model included age, BMI, alcohol and hormone use, family history, age at menopause, age at first birth/parity, and breast biopsy history. When risk factor regression coefficients were applied in the validation cohorts, the c-index for predicting 10-year non-BC death was 0.790 (0.784–0.796) in NHS and 0.768 (0.757–0.780) in BWHS; for predicting 5-year BC risk, the c-index was 0.612 (0.538–0.641) in NHS and 0.573 (0.536–0.611) in BWHS. CONCLUSIONS: We developed and validated a novel competing-risk model that predicts 10-year non-BC death and 5-year BC risk. Model risk estimates may help inform SDM around mammography screening. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-023-01605-8. BioMed Central 2023-01-24 2023 /pmc/articles/PMC9872276/ /pubmed/36694222 http://dx.doi.org/10.1186/s13058-023-01605-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Schonberg, Mara A. Wolfson, Emily A. Eliassen, A. Heather Bertrand, Kimberly A. Shvetsov, Yurii B. Rosner, Bernard A. Palmer, Julie R. Ngo, Long H. A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old |
title | A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old |
title_full | A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old |
title_fullStr | A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old |
title_full_unstemmed | A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old |
title_short | A model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old |
title_sort | model for predicting both breast cancer risk and non-breast cancer death among women > 55 years old |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872276/ https://www.ncbi.nlm.nih.gov/pubmed/36694222 http://dx.doi.org/10.1186/s13058-023-01605-8 |
work_keys_str_mv | AT schonbergmaraa amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT wolfsonemilya amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT eliassenaheather amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT bertrandkimberlya amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT shvetsovyuriib amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT rosnerbernarda amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT palmerjulier amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT ngolongh amodelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT schonbergmaraa modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT wolfsonemilya modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT eliassenaheather modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT bertrandkimberlya modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT shvetsovyuriib modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT rosnerbernarda modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT palmerjulier modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold AT ngolongh modelforpredictingbothbreastcancerriskandnonbreastcancerdeathamongwomen55yearsold |