Literature DB >> 34843026

A case-case analysis of women with breast cancer: predictors of interval vs screen-detected cancer.

Nickolas Dreher1,2, Madeline Matthys3, Edward Hadeler3,4, Yiwey Shieh3, Irene Acerbi3, Fiona M McAuley3, Michelle Melisko3, Martin Eklund5, Jeffrey A Tice3, Laura J Esserman3, Laura J Van't Veer3.   

Abstract

PURPOSE: The Breast Cancer Surveillance Consortium (BCSC) model is a widely used risk model that predicts 5- and 10-year risk of developing invasive breast cancer for healthy women aged 35-74 years. Women with high BCSC risk may also be at elevated risk to develop interval cancers, which present symptomatically in the year following a normal screening mammogram. We examined the association between high BCSC risk (defined as the top 2.5% by age) and breast cancers presenting as interval cancers.
METHODS: We conducted a case-case analysis among women with breast cancer in which we compared the mode of detection and tumor characteristics of patients in the top 2.5% BCSC risk by age with age-matched (1:2) patients in the lower 97.5% risk. We constructed logistic regression models to estimate the odds ratio (OR) of presenting with interval cancers, and poor prognosis tumor features, between women from the top 2.5% and bottom 97.5% of BCSC risk.
RESULTS: Our analysis included 113 breast cancer patients in the top 2.5% of risk for their age and 226 breast cancer patients in the lower 97.5% of risk. High-risk patients were more likely to have presented with an interval cancer within one year of a normal screening, OR 6.62 (95% CI 3.28-13.4, p < 0.001). These interval cancers were also more likely to be larger, node positive, and higher stage than the screen-detected cancers.
CONCLUSION: Breast cancer patients in the top 2.5% of BCSC risk for their age were more likely to present with interval cancers. The BCSC model could be used to identify healthy women who may benefit from intensified screening.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Breast cancer; Breast density; Interval cancer; Screening; Supplemental screening

Mesh:

Year:  2021        PMID: 34843026      PMCID: PMC9189918          DOI: 10.1007/s10549-021-06451-w

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.624


  18 in total

1.  The Athena Breast Health Network: developing a rapid learning system in breast cancer prevention, screening, treatment, and care.

Authors:  Sarah L Elson; Robert A Hiatt; Hoda Anton-Culver; Lydia P Howell; Arash Naeim; Barbara A Parker; Laura J Van't Veer; Michael Hogarth; John P Pierce; Robert J Duwors; Kathy Hajopoulos; Laura J Esserman
Journal:  Breast Cancer Res Treat       Date:  2013-07-26       Impact factor: 4.872

2.  Risk factors and tumor characteristics of interval cancers by mammographic density.

Authors:  Johanna Holm; Keith Humphreys; Jingmei Li; Alexander Ploner; Abbas Cheddad; Mikael Eriksson; Sven Törnberg; Per Hall; Kamila Czene
Journal:  J Clin Oncol       Date:  2015-02-02       Impact factor: 44.544

3.  Combined effect of volumetric breast density and body mass index on breast cancer risk.

Authors:  Natalie J Engmann; Christopher G Scott; Matthew R Jensen; Stacey Winham; Diana L Miglioretti; Lin Ma; Kathleen Brandt; Amir Mahmoudzadeh; Dana H Whaley; Carrie Hruska; Fang Wu; Aaron D Norman; Robert A Hiatt; John Heine; John Shepherd; V Shane Pankratz; Celine M Vachon; Karla Kerlikowske
Journal:  Breast Cancer Res Treat       Date:  2019-05-25       Impact factor: 4.872

4.  Integration of Health Questionnaire Systems to Facilitate Supportive Care Services for Patients at an Academic Breast Care Center.

Authors:  Emily C Wong; Celia P Kaplan; Nickolas Dreher; Jimmy Hwang; Laura Van't Veer; Michelle E Melisko
Journal:  JCO Clin Cancer Inform       Date:  2018-12

5.  Evaluation of breast cancer risk assessment techniques: a cost-effectiveness analysis.

Authors:  Elissa M Ozanne; Laura J Esserman
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2004-12       Impact factor: 4.254

6.  Tumor characteristics associated with mammographic detection of breast cancer in the Ontario breast screening program.

Authors:  Victoria A Kirsh; Anna M Chiarelli; Sarah A Edwards; Frances P O'Malley; Rene S Shumak; Martin J Yaffe; Norman F Boyd
Journal:  J Natl Cancer Inst       Date:  2011-05-03       Impact factor: 13.506

7.  Incidence and prognosis in early onset breast cancer.

Authors:  M Sundquist; S Thorstenson; L Brudin; S Wingren; B Nordenskjöld
Journal:  Breast       Date:  2002-02       Impact factor: 4.380

8.  Strategies to Identify Women at High Risk of Advanced Breast Cancer During Routine Screening for Discussion of Supplemental Imaging.

Authors:  Karla Kerlikowske; Brian L Sprague; Anna N A Tosteson; Karen J Wernli; Garth H Rauscher; Dianne Johnson; Diana S M Buist; Tracy Onega; Louise M Henderson; Ellen S O'Meara; Diana L Miglioretti
Journal:  JAMA Intern Med       Date:  2019-09-01       Impact factor: 21.873

Review 9.  The WISDOM Study: breaking the deadlock in the breast cancer screening debate.

Authors:  Laura J Esserman
Journal:  NPJ Breast Cancer       Date:  2017-09-13

10.  Biology of primary breast cancer in older women treated by surgery: with correlation with long-term clinical outcome and comparison with their younger counterparts.

Authors:  B M Syed; A R Green; E C Paish; D Soria; J Garibaldi; L Morgan; D A L Morgan; I O Ellis; K L Cheung
Journal:  Br J Cancer       Date:  2013-03-05       Impact factor: 7.640

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