Cargando…

Predicting invasive breast cancer versus DCIS in different age groups

BACKGROUND: Increasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age. METHODS: We analyzed 1,475 mal...

Descripción completa

Detalles Bibliográficos
Autores principales: Ayvaci, Mehmet US, Alagoz, Oguzhan, Chhatwal, Jagpreet, Munoz del Rio, Alejandro, Sickles, Edward A, Nassif, Houssam, Kerlikowske, Karla, Burnside, Elizabeth S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4138370/
https://www.ncbi.nlm.nih.gov/pubmed/25112586
http://dx.doi.org/10.1186/1471-2407-14-584
_version_ 1782331223170875392
author Ayvaci, Mehmet US
Alagoz, Oguzhan
Chhatwal, Jagpreet
Munoz del Rio, Alejandro
Sickles, Edward A
Nassif, Houssam
Kerlikowske, Karla
Burnside, Elizabeth S
author_facet Ayvaci, Mehmet US
Alagoz, Oguzhan
Chhatwal, Jagpreet
Munoz del Rio, Alejandro
Sickles, Edward A
Nassif, Houssam
Kerlikowske, Karla
Burnside, Elizabeth S
author_sort Ayvaci, Mehmet US
collection PubMed
description BACKGROUND: Increasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age. METHODS: We analyzed 1,475 malignant breast biopsies, 1,063 invasive and 412 DCIS, from 35,871 prospectively collected consecutive diagnostic mammograms interpreted at University of California, San Francisco between 1/6/1997 and 6/29/2007. We constructed three logistic regression models to predict the probability of invasive cancer versus DCIS for the following groups: women ≥ 65 (older group), women 50–64 (middle age group), and women < 50 (younger group). We identified significant predictors and measured the performance in all models using area under the receiver operating characteristic curve (AUC). RESULTS: The models for older and the middle age groups performed significantly better than the model for younger group (AUC = 0.848 vs, 0.778; p = 0.049 and AUC = 0.851 vs, 0.778; p = 0.022, respectively). Palpability and principal mammographic finding were significant predictors in distinguishing invasive from DCIS in all age groups. Family history of breast cancer, mass shape and mass margins were significant positive predictors of invasive cancer in the older group whereas calcification distribution was a negative predictor of invasive cancer (i.e. predicted DCIS). In the middle age group—mass margins, and in the younger group—mass size were positive predictors of invasive cancer. CONCLUSIONS: Clinical and mammographic finding features predict invasive breast cancer versus DCIS better in older women than younger women. Specific predictive variables differ based on age. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2407-14-584) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4138370
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-41383702014-08-21 Predicting invasive breast cancer versus DCIS in different age groups Ayvaci, Mehmet US Alagoz, Oguzhan Chhatwal, Jagpreet Munoz del Rio, Alejandro Sickles, Edward A Nassif, Houssam Kerlikowske, Karla Burnside, Elizabeth S BMC Cancer Research Article BACKGROUND: Increasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age. METHODS: We analyzed 1,475 malignant breast biopsies, 1,063 invasive and 412 DCIS, from 35,871 prospectively collected consecutive diagnostic mammograms interpreted at University of California, San Francisco between 1/6/1997 and 6/29/2007. We constructed three logistic regression models to predict the probability of invasive cancer versus DCIS for the following groups: women ≥ 65 (older group), women 50–64 (middle age group), and women < 50 (younger group). We identified significant predictors and measured the performance in all models using area under the receiver operating characteristic curve (AUC). RESULTS: The models for older and the middle age groups performed significantly better than the model for younger group (AUC = 0.848 vs, 0.778; p = 0.049 and AUC = 0.851 vs, 0.778; p = 0.022, respectively). Palpability and principal mammographic finding were significant predictors in distinguishing invasive from DCIS in all age groups. Family history of breast cancer, mass shape and mass margins were significant positive predictors of invasive cancer in the older group whereas calcification distribution was a negative predictor of invasive cancer (i.e. predicted DCIS). In the middle age group—mass margins, and in the younger group—mass size were positive predictors of invasive cancer. CONCLUSIONS: Clinical and mammographic finding features predict invasive breast cancer versus DCIS better in older women than younger women. Specific predictive variables differ based on age. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2407-14-584) contains supplementary material, which is available to authorized users. BioMed Central 2014-08-11 /pmc/articles/PMC4138370/ /pubmed/25112586 http://dx.doi.org/10.1186/1471-2407-14-584 Text en © Ayvaci et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research Article
Ayvaci, Mehmet US
Alagoz, Oguzhan
Chhatwal, Jagpreet
Munoz del Rio, Alejandro
Sickles, Edward A
Nassif, Houssam
Kerlikowske, Karla
Burnside, Elizabeth S
Predicting invasive breast cancer versus DCIS in different age groups
title Predicting invasive breast cancer versus DCIS in different age groups
title_full Predicting invasive breast cancer versus DCIS in different age groups
title_fullStr Predicting invasive breast cancer versus DCIS in different age groups
title_full_unstemmed Predicting invasive breast cancer versus DCIS in different age groups
title_short Predicting invasive breast cancer versus DCIS in different age groups
title_sort predicting invasive breast cancer versus dcis in different age groups
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4138370/
https://www.ncbi.nlm.nih.gov/pubmed/25112586
http://dx.doi.org/10.1186/1471-2407-14-584
work_keys_str_mv AT ayvacimehmetus predictinginvasivebreastcancerversusdcisindifferentagegroups
AT alagozoguzhan predictinginvasivebreastcancerversusdcisindifferentagegroups
AT chhatwaljagpreet predictinginvasivebreastcancerversusdcisindifferentagegroups
AT munozdelrioalejandro predictinginvasivebreastcancerversusdcisindifferentagegroups
AT sicklesedwarda predictinginvasivebreastcancerversusdcisindifferentagegroups
AT nassifhoussam predictinginvasivebreastcancerversusdcisindifferentagegroups
AT kerlikowskekarla predictinginvasivebreastcancerversusdcisindifferentagegroups
AT burnsideelizabeths predictinginvasivebreastcancerversusdcisindifferentagegroups