Observer variation in the classification of mammographic parenchymal patterns

Boyd, Norman F.; Wolfson, Christina; Moskowitz, Myron; Carlile, Thomas; Petitclerc, Claude; Ferri, H; Fishell, Eve; Grégoire, A; Kiernan, Matthew; Longley, Jemma; Simor, Imre S.; Miller, Anthony B.

doi:10.1016/0021-9681(86)90113-x

Cited by 38 publications

(17 citation statements)

References 29 publications

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“…All mammograms for each woman were presented to the radiologist ordered by the date on which they were performed, earliest first. In previous studies, RW has demonstrated good inter-rater [13][14][15] and intrarater [16,17] agreement of density assessment. Mammograms were also classified using the Wolfe system [8], but due to the close agreement (94% agreement between the two rankings) we only present findings in relation to the six category classification (SCC).…”

Section: Methodsmentioning

confidence: 83%

Life course breast cancer risk factors and adult breast density (United Kingdom)

Jeffreys

Warren

Gunnell

et al. 2004

Cancer Causes Control

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Objective: To determine whether risk factors in childhood and early adulthood affect later mammographic breast density. Methods: Subjects were 628 women who attended a medical examination at the University of Glasgow Student Health Service , responded to a questionnaire (2001) and had a screening mammogram in Scotland (1989Scotland ( -2002. Mammograms (median age of 59 years) were classified using a six category classification (SCC) of breast density percent. Logistic regression was used to determine associations between risk factors and having a high-risk mammogram ( 25% dense). Results: In multi-variable analyses, high-risk mammograms were associated with parity (adjusted odds ratio (OR) per child: 0.77 (95% confidence interval (CI) 0.61-0.99)), age at first birth, OR per year: 1.05 (0.99-1.11), smoking at university, OR smokers versus non-smokers: 0.58 (0.36-0.92) and body mass index (BMI) while at university, OR per 1 kg/m 2 0.75 (0.69-0.82). No associations with SCC were found for age at menarche, birth weight, oral contraceptive (OC) use, height, leg length or exercise at age 20. Conclusions: We confirm previous findings that breast density is affected by reproductive events and some anthropometric measures, however most of the risk factors acting throughout the life course which we examined were not closely related to adult breast density.

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Section: Methodsmentioning

confidence: 83%

Life course breast cancer risk factors and adult breast density (United Kingdom)

Jeffreys

Warren

Gunnell

et al. 2004

Cancer Causes Control

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“…This is a wellknown qualitative method of assessing mammographic density with a subjective nature. However, we had previously tested the method using two blinded internal and one external observer with very reliable results [29], similar to other studies [58,59]. The binary approach of the Wolfe patterns in the analysis was dictated by the poor representation of very dense patterns (DY) in our population, although the authors are well aware of the restrictions in interpreting the observed results from a clinical point of view.…”

Section: Discussionmentioning

confidence: 89%

Anthropometric characteristics and mammographic parenchymal patterns in post-menopausal women: a population-based study in Northern Greece

Riza

Remoundos

Bakali

et al. 2008

Cancer Causes Control

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Chest circumference as a measure of upper body fat adiposity appears to be a stronger determinant of mammographic patterns than body fat distribution (measured as WHR). A heavy body build in adulthood is associated with decreased mammographic density. Further studies are necessary to confirm our results, ideally prospective cohorts, looking at the effect of anthropometric determinants on mammographic pattern changes over time and breast cancer risk.

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“…Wolfe’s parenchymal pattern was used to classify MBD into four parenchymal patterns based on the extent and type of density: N1—nondense, no ducts visible; P1—ductal prominence occupying less than a fourth of the breast; P2—prominent ductal pattern occupying more than a fourth of the breast; DY—homogenous plaque-like areas of extreme density (15). This measure of MBD has high inter-reader agreement (16,17) and has been used in multiple previous studies and consistently shown to be associated with breast cancer risk (18–28). This clinically obtained measure was documented by the radiologists and retained at the Mayo Clinic, starting in 1985.…”

Section: Participants and Methodsmentioning

confidence: 99%

Independent Association of Lobular Involution and Mammographic Breast Density With Breast Cancer Risk

Ghosh

Vachon

Pankratz

et al. 2010

JNCI Journal of the National Cancer Institute

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BackgroundLobular involution, or age-related atrophy of breast lobules, is inversely associated with breast cancer risk, and mammographic breast density (MBD) is positively associated with breast cancer risk.MethodsTo evaluate whether lobular involution and MBD are independently associated with breast cancer risk in women with benign breast disease, we performed a nested cohort study among women (n = 2666) with benign breast disease diagnosed at Mayo Clinic between January 1, 1985, and December 31, 1991 and a mammogram available within 6 months of the diagnosis. Women were followed up for an average of 13.3 years to document any breast cancer incidence. Lobular involution was categorized as none, partial, or complete; parenchymal pattern was classified using the Wolfe classification as N1 (nondense), P1, P2 (ductal prominence occupying <25%, or >25% of the breast, respectively), or DY (extremely dense). Hazard ratios (HRs) and 95% confidence intervals (CIs) to assess associations of lobular involution and MBD with breast cancer risk were estimated using adjusted Cox proportional hazards model. All tests of statistical significance were two-sided.ResultsAfter adjustment for MBD, having no or partial lobular involution was associated with a higher risk of breast cancer than having complete involution (none: HR of breast cancer incidence = 2.62, 95% CI = 1.39 to 4.94; partial: HR of breast cancer incidence = 1.61, 95% CI = 1.03 to 2.53; Ptrend = .002). Similarly, after adjustment for involution, having dense breasts was associated with higher risk of breast cancer than having nondense breasts (for DY: HR of breast cancer incidence = 1.67, 95% CI = 1.03 to 2.73; for P2: HR of breast cancer incidence = 1.96, 95% CI = 1.20 to 3.21; for P1: HR of breast cancer incidence = 1.23, 95% CI = 0.67 to 2.26; Ptrend = .02). Having a combination of no involution and dense breasts was associated with higher risk of breast cancer than having complete involution and nondense breasts (HR of breast cancer incidence = 4.08, 95% CI = 1.72 to 9.68; P = .006).ConclusionLobular involution and MBD are independently associated with breast cancer incidence; combined, they are associated with an even greater risk for breast cancer.

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Observer variation in the classification of mammographic parenchymal patterns

Cited by 38 publications

References 29 publications

Life course breast cancer risk factors and adult breast density (United Kingdom)

Life course breast cancer risk factors and adult breast density (United Kingdom)

Anthropometric characteristics and mammographic parenchymal patterns in post-menopausal women: a population-based study in Northern Greece

Independent Association of Lobular Involution and Mammographic Breast Density With Breast Cancer Risk

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