Literature DB >> 8826943

Histopathology and growth rate of interval breast carcinoma. Characterization of different subgroups.

C T Brekelmans1, J M van Gorp, P H Peeters, H J Collette.   

Abstract

BACKGROUND: Interval breast cancers are defined as carcinomas occurring within 2 years after a negative screening Distinction has to made between cancers existent at the time of screening but missed for some reason, and fast-growing incident cancers. This is important because the natural history and the implications for the treatment of the patient might differ.
METHODS: Radiologic and histopathologic characteristics were assembled for 104 interval cancers diagnosed within the DOM project, the Utrecht program for the early detection of breast cancer. At a mammographic review for 27 cases, signs of malignant or benign tumor were found (missed cases). For 77 cases no radiologic signs were present on review. Twenty of these cases had a mitotic rate of > 3 and a high tumor growth rate (mean doubling time: 51 days). This combination seemed implausible, therefore, it was thought hypothesized that these tumors were most likely present, although radiologically invisible (masked), at the time of screening. The remaining cases (n = 57) were classified as true interval cancers and further divided into 14 fast-growing cases (mitotic rate > or = 3/high-power field [HPF]) and 43 cases with an intermediate growth rate (mitotic rate < 3/HPF).
RESULTS: Factors associated with the masking of tumors were the histologic tumor type, absence of microscopic calcifications, and presence of dense breast tissue. Fast-growing tumors were characterized by a young patient age, absence of microscopic calcifications, and a high percentage of regional lymph node positive tumors. The 5-year survival probability was 100% for missed cases, 70% for masked cases, 80% for cases with an intermediate growth rate, and 54% for fast-growing cases.
CONCLUSIONS: It is possible to separate interval breast cancers in true interval cases and cases (most likely) existent at the time of screening. Part of this last group is invisible by mammography (masked).

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Year:  1996        PMID: 8826943     DOI: 10.1002/(SICI)1097-0142(19960915)78:6<1220::AID-CNCR8>3.0.CO;2-D

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  11 in total

1.  Differential expression of prognostic biomarkers between interval and screen-detected breast cancers: does age or family history matter?

Authors:  Jan T Lowery; Tim Byers; John Kittelson; John E Hokanson; Judy Mouchawar; John Lewin; Dan Merrick; Lisa Hines; Meenakshi Singh
Journal:  Breast Cancer Res Treat       Date:  2011-03-24       Impact factor: 4.872

2.  A study of interval breast cancer within the NHS breast screening programme.

Authors:  W K Cowan; B Angus; J C Gray; L G Lunt; S R al-Tamimi
Journal:  J Clin Pathol       Date:  2000-02       Impact factor: 3.411

3.  Outcomes of surveillance for contralateral breast cancer in patients less than age 60 at the time of initial diagnosis.

Authors:  C Weinstock; R Bigenwald; T Hochman; P Sun; S A Narod; E Warner
Journal:  Curr Oncol       Date:  2012-06       Impact factor: 3.677

4.  Coexistence of lactating adenoma and invasive ductal adenocarcinoma of the breast in a pregnant woman.

Authors:  A Saglam; B Can
Journal:  J Clin Pathol       Date:  2005-01       Impact factor: 3.411

5.  Mammographic features and histopathological findings of interval breast cancers.

Authors:  S Hofvind; B Geller; P Skaane
Journal:  Acta Radiol       Date:  2008-11       Impact factor: 1.990

6.  Specific expression of k63-linked ubiquitination of calmodulin-like protein 5 in breast cancer of premenopausal patients.

Authors:  Manuel Debald; Frank Alexander Schildberg; Andrea Linke; Klaus Walgenbach; Walther Kuhn; Gunther Hartmann; Gisela Walgenbach-Brünagel
Journal:  J Cancer Res Clin Oncol       Date:  2013-10-22       Impact factor: 4.553

7.  Trends in incidence and detection of advanced breast cancer at biennial screening mammography in The Netherlands: a population based study.

Authors:  Joost Nederend; Lucien Em Duijm; Adri C Voogd; Johanna H Groenewoud; Frits H Jansen; Marieke Wj Louwman
Journal:  Breast Cancer Res       Date:  2012-01-09       Impact factor: 6.466

8.  Non-invasive proteomics-thinking about personalized breast cancer screening and treatment.

Authors:  Manuel Debald; Matthias Wolfgarten; Gisela Walgenbach-Brünagel; Walther Kuhn; Michael Braun
Journal:  EPMA J       Date:  2010-07-14       Impact factor: 6.543

9.  Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study.

Authors:  Kavitha Krishnan; Laura Baglietto; Carmel Apicella; Jennifer Stone; Melissa C Southey; Dallas R English; Graham G Giles; John L Hopper
Journal:  Breast Cancer Res       Date:  2016-06-18       Impact factor: 6.466

10.  Radiological audit of interval breast cancers: Estimation of tumour growth rates.

Authors:  Emma G MacInnes; Stephen W Duffy; Julie A Simpson; Matthew G Wallis; Anne E Turnbull; Louise S Wilkinson; Keshthra Satchithananda; Rumana Rahim; David Dodwell; Brian V Hogan; Oleg Blyuss; Nisha Sharma
Journal:  Breast       Date:  2020-04-01       Impact factor: 4.380

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