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Cancer Epidemiology, Biomarkers & Prevention
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Methodological Challenges and Updated Findings from a Meta-analysis of the Association between Mammographic Density and Breast Cancer

Daniela Bond-Smith and Jennifer Stone
Daniela Bond-Smith
1School of Global and Population Health, The University of Western Australia, Perth, Western Australia, Australia.
2Centre for Genetic Origins of Health and Disease, Curtin University and The University of Western Australia, Perth, Western Australia, Australia.
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  • For correspondence: daniela.bond-smith@uwa.edu.au
Jennifer Stone
2Centre for Genetic Origins of Health and Disease, Curtin University and The University of Western Australia, Perth, Western Australia, Australia.
3Royal Perth Hospital Medical Research Foundation, Perth, Western Australia, Australia.
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  • ORCID record for Jennifer Stone
DOI: 10.1158/1055-9965.EPI-17-1175 Published January 2019
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  • Figure 1.
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    Figure 1.

    A forest plot summarizing all continuous PMD and continuous AMD studies. MLO, mediolateral oblique.

  • Figure 2.
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    Figure 2.

    A forest plot summarizing all categorical PMD studies analyzing the 10% to 25%, 25% to 50%, and 50% to 75% PMD categories. African-Am., African American; CC, craniocaudal; FHBC, family history of breast cancer; MLO, mediolateral oblique.

  • Figure 3.
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    Figure 3.

    A forest plot summarizing all categorical PMD studies analyzing the greater than 75% PMD category and BIRADS studies.

  • Figure 4.
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    Figure 4.

    A forest plot summarizing all categorical AMD studies. CC, craniocaudal.

  • Figure 5.
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    Figure 5.

    Comparison across data sets and estimation methods for categorical PMD. The figure compares the log ORs for studies conducted since 2006 (clockwise line pattern) with those from before 2006 (counterclockwise line pattern). It also depicts the widths of the standard confidence intervals (solid lines) and the Bayesian CIs (dotted lines) for the estimates.

Tables

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  • Table 1.

    Meta-analysis results

    Overall OR estimate (95% CI)Heterogeneity estimate Embedded Image (95% CI)I2 statistic in %Probability of Embedded ImagePredicted ORPredicted Embedded ImageNumber of samples (studies) includedRatio of width 95% CI and OR
    Continuous PMD1.1317 (1.0656–1.2140)0.0092 (0.0051–0.0168)89.32%99.95%1.13520.010515 (8)0.0131
    Continuous AMD1.1315 (1.0232–1.2725)0.0082 (0.0032–0.0247)83.38%98.65%1.13720.01207 (5)0.0218
    Categorical PMD: 10%–25%1.4366 (1.3250- 1.5549)0.0679 (0.0072–0.1715)15.44%100%1.43600.085224 (21)0.1600
    Categorical PMD: 25%–50%1.9845 (1.7427- 2.2632)0.1826 (0.0944–0.3229)51.20%100%1.98570.201821 (19)0.2622
    Categorical PMD: 50%–75%2.5115 (2.0969- 3.0397)0.2855 (0.1670–0.4848)64.92%100%2.51970.315821 (19)0.3755
    Categorical PMD: >75%3.8436 (2.1917–7.2227)0.2660 (0.0112–1.2550)41.00%99.77%3.91900.50356 (6)1.389
    BIRADS–B1.625 (1.2964–2.1292)0.1650 (0.0153–0.5304)36.66%99.88%1.65030.244411 (10)0.5125
    BIRADS–C1.9536 (1.2228–2.9829)0.4890 (0.2041–1.0696)80.57%99.39%1.92340.593911 (10)0.901
    BIRADS–D2.0044 (1.1221–3.4231)0.5788 (0.1559–1.3264)74.1%98.69%1.97270.698211 (10)1.148
    Categorical AMD: 20–35 cm21.4849 (1.2289–1.7695)0.1325 (0.0148–0.3888)43.53%99.89%1.47850.18329 (8)0.3641
    Categorical AMD: 35–50 cm21.7625 (1.5521–2.0296)0.0686 (0.0044–0.2468)14.4%100%1.77160.109711 (9)0.2709
    Categorical AMD: >50 cm22.2117 (1.9208–2.6363)0.1160 (0.0144–0.3247)35.74%100%2.23760.156211 (9)0.3235
  • Table 2.

    Meta-regression results

    MatchingaThresholdingbAdjustmentcInvasived
    Continuous PMDEmbedded Image (95% CI)0.0114 (0.0012–0.0206)
    OR intercept (95% CI)1.0847 (1.0422–1.1549)
    OR incl. Embedded Image (95% CI)1.0972 (1.0435–1.1790)
    Categorical PMD: 25%–50%Embedded Image (95% CI)0.4077 (0.1726–0.6443)0.3051 (0.0213–0.5408)
    OR intercept (95% CI)1.4475 (1.173–1.7678)1.5928 (1.2995–2.0009)
    OR incl. Embedded Image (95% CI)2.1760 (1.3873–3.3904)2.1611 (1.3256–3.4764)
    Categorical PMD: 50%–75%Embedded Image (95% CI)0.5118 (0.1698–0.8712)0.4242 (0.0277–0.7616)0.4284 (0.0453–0.7673)−0.3970 (-0.8094–0.0001)
    OR intercept (95% CI)1.6468 (1.223–2.2797)1.9034 (1.4004–2.5696)1.9073 (1.3548–2.5157)3.3720 (2.3980–4.7325)
    OR incl. Embedded Image (95% CI)2.7465 (1.4359–5.4943)2.9090 (1.4584–5.6765)2.9273 (1.4044–5.4690)2.2670 (1.0612–4.8141)
    • ↵aMatching is defined as use of matched case–control study setup; reference category: no matching.

    • ↵bThresholding is defined as use of an automatic thresholding program; reference category: no use of automatic thresholding.

    • ↵cAdjustment is defined as inclusion of confounders, at a minimum age and/or body mass index (BMI); reference category: no adjustment.

    • ↵dInvasive is defined as invasive cancer type; reference category: noninvasive cancer.

  • Table 3.

    Comparison of estimate distributions of our data set with MCDSS (2006) data seta

    Categorical PMD: 10%–25%Categorical PMD: 25%–50%Categorical PMD: 50%–75%Categorical PMD: >75%
    t test0.12590.03520.00850.0009
    χ2 test0.08460.01200.00080.0012
    • NOTE: A two-sample t test and a two-sample χ2 test for binned data were used to statistically test for differences between the probability distributions of the effect estimates based on our more recent data versus the MCDSS data set.

    • ↵aP values for H0 = no difference between distributions.

Additional Files

  • Figures
  • Tables
  • Supplementary Data

    • Tables S1 and S2 - Table S1: List of included studies and their effect sizes; Table S2: List of candidate studies
    • Figures S1, S2 and S3 - Figure S1: Risk gradients for categorical PMD, BIRADS and categorical AMD; Figure S2: Centered posterior density of the overall effect for categorical PMD, BIRADS and categorical AMD; Figure S3: Probability distributions of the effect estimate for categorical PMD
    • Tables S3 and S4, Figures S4 and S5 - Table S3: Meta-analysis results for re-estimated McCormack and dos Santos (2006) data set; Figure S4: Cumulative probability distributions for categorical PMD; Table S4: Meta-regression results for year of mammography as moderator variable; Figure S5: Predicted effect (change and OR) of PMD (category 10-25%) on BC by year of mammography
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Cancer Epidemiology Biomarkers & Prevention: 28 (1)
January 2019
Volume 28, Issue 1
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Methodological Challenges and Updated Findings from a Meta-analysis of the Association between Mammographic Density and Breast Cancer
Daniela Bond-Smith and Jennifer Stone
Cancer Epidemiol Biomarkers Prev January 1 2019 (28) (1) 22-31; DOI: 10.1158/1055-9965.EPI-17-1175

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Methodological Challenges and Updated Findings from a Meta-analysis of the Association between Mammographic Density and Breast Cancer
Daniela Bond-Smith and Jennifer Stone
Cancer Epidemiol Biomarkers Prev January 1 2019 (28) (1) 22-31; DOI: 10.1158/1055-9965.EPI-17-1175
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