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Scholarly Works (150 results)

  • Thesis
  • Peer Reviewed
UC San Francisco Electronic Theses and Dissertations (2018)

Breast density and obesity are two of the most common risk factors for breast cancer among women in the United States. However, the importance of these risk factors and their individual and joint effects on breast cancer risk in individuals and on a population level is relatively unknown.

The first chapter of my dissertation provides a population perspective on the impact of breast density and obesity on breast cancer incidence in U.S. women. This study used the population attributable risk proportion (PARP) to estimate of the proportion of premenopausal and postmenopausal breast cancer cases that can be attributed to breast density, obesity and their combined effects. Results from this study suggest that breast density alone accounts for 39% of premenopausal and 26% of postmenopausal cancers, and combined with obesity, accounts for 43% of postmenopausal cancers.

Volumetric breast density software measures the three-dimensional volume of breast tissue and is increasingly used in clinical and research settings. Dense tissue volume may mediate or moderate the effect of obesity on breast cancer risk; thus, identifying the joint effects of obesity and breast density on breast cancer can improve risk stratification and provide insights into pathways driving breast cancer incidence. The second chapter evaluates if the effects of volumetric breast density on breast cancer risk are greater in obese compared with non-obese women. This study finds that the effect of volumetric density on breast cancer risk is dramatically higher in obese compared with non-obese women, with the most pronounced effects in postmenopausal women. The third chapter evaluates how obesity and other risk factors affect longitudinal change in dense breast volume over the menopausal transition in healthy women. This study found no effect of obesity, but a strong effect of baseline dense volume on greater decline in volumetric breast density across the menopause transition.

As a body of work, my dissertation provides insights into the public health impact and clinical relevance of two of the most common breast cancer risk factors in U.S. women. It provides new evidence to improve clinical risk stratification and offers novel insights into the complex causal relationship between obesity, volumetric breast density and breast cancer risk.

    Cover page: Breast density, body mass index, and breast cancer risk: Implications for clinical and public health settings.
    • Article
    • Peer Reviewed
    UC San Francisco Previously Published Works (2016)

    Objective

    We conducted a systematic review to assess the quality and limitations of published studies examining benefits and harms of screening mammography in relation to comorbidity and age.

    Methods

    We searched MEDLINE and EMBASE from January 1980 through June 2013 for studies that examined benefits or harms of screening mammography in women aged 65 years or older in relation to comorbidity. For each study, we extracted data regarding setting, design, quality, screening schedule, measure of comorbidity, and estimates of benefits and/or harms. We reviewed 1760 titles, identifying 7 articles that met the inclusion criteria: prospective cohort (two studies), retrospective cohort (two studies), and decision analyses (three studies). No randomized controlled trials were identified.

    Results

    At least one measure of life expectancy or reduction in the risk of breast cancer death as a marker of benefit was examined in four studies, whereas three studies addressed the harms of screening mammography, including false-positive results. Both cohort studies and decision analyses showed that screening benefits decreased with increasing age and comorbidity burden.

    Conclusions

    The limited evidence currently available suggests that, apart from older women with severe comorbidity, women 65 and older may experience improvements in life expectancy from screening. Given the potential for harm, it is unclear whether the magnitude of the benefit is sufficient to warrant regular screening. Women, clinicians and policymakers should consider these factors in deciding whether continue screening.
      Cover page: Benefits and Harms of Screening Mammography by Comorbidity and Age: A Qualitative Synthesis of Observational Studies and Decision Analyses
      • Article
      • Peer Reviewed
      UC Davis Previously Published Works (2019)
        Cover page: Discussions of Dense Breasts, Breast Cancer Risk, and Screening Choices in 2019Creative Commons 'BY-NC-ND' version 4.0 license
        • Article
        • Peer Reviewed
        UC San Francisco Previously Published Works (2013)

        Background

        Whether timeliness of follow-up after abnormal mammography differs at facilities serving vulnerable populations, such as women with limited education or income, in rural areas, and racial/ethnic minorities is unknown.

        Methods

        We examined receipt of diagnostic evaluation after abnormal mammography using 1998-2006 Breast Cancer Surveillance Consortium-linked Medicare claims. We compared whether time to recommended breast imaging or biopsy depended on whether women attended facilities serving vulnerable populations. We characterized a facility by the proportion of mammograms performed on women with limited education or income, in rural areas, or racial/ethnic minorities.

        Results

        We analyzed 30,874 abnormal screening examinations recommended for follow-up imaging across 142 facilities and 10,049 abnormal diagnostic examinations recommended for biopsy across 114 facilities. Women at facilities serving populations with less education or more racial/ethnic minorities had lower rates of follow-up imaging (4%-5% difference, P<0.05), and women at facilities serving more rural and low-income populations had lower rates of biopsy (4%-5% difference, P<0.05). Women undergoing biopsy at facilities serving vulnerable populations had longer times until biopsy than those at facilities serving nonvulnerable populations (21.6 vs. 15.6 d; 95% confidence interval for mean difference 4.1-7.7). The proportion of women receiving recommended imaging within 11 months and biopsy within 3 months varied across facilities (interquartile range, 85.5%-96.5% for imaging and 79.4%-87.3% for biopsy).

        Conclusions

        Among Medicare recipients, follow-up rates were slightly lower at facilities serving vulnerable populations, and among those women who returned for diagnostic evaluation, time to follow-up was slightly longer at facilities that served vulnerable population. Interventions should target variability in follow-up rates across facilities, and evaluate effectiveness particularly at facilities serving vulnerable populations.
          Cover page: Timeliness of Abnormal Screening and Diagnostic Mammography Follow-up at Facilities Serving Vulnerable Women
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2019)

          Objective

          To investigate mammography facilities' follow-up times, population vulnerability, system-based processes, and association with cancer stage at diagnosis.

          Data sources

          Prospectively collected from San Francisco Mammography Registry (SFMR) 2005-2011, California Cancer Registry 2005-2012, SFMR facility survey 2012.

          Study design

          We examined time to biopsy for 17 750 abnormal mammogram results (BI-RADS 4/5), categorizing eight facilities as short or long follow-up based on proportion of mammograms with biopsy at 30 days. We examined facility population vulnerability (race/ethnicity, language, education), and system processes. Among women with a cancer diagnosis, we modeled odds of advanced-stage (≥IIb) cancer diagnosis by facility follow-up group.

          Data extraction methods

          Merged SFMR, Cancer Registry and facility survey data.

          Principal findings

          Facilities (N = 4) with short follow-up completed biopsies by 30 days for 82% of mammograms compared with 62% for facilities with long follow-up (N = 4) (P < 0.0001). All facilities serving high proportions of vulnerable women were long follow-up facilities. The long follow-up facilities had fewer radiologists, longer biopsy appointment wait times, and less communication directly with women. Having the index abnormal mammogram at a long follow-up facility was associated with higher adjusted odds of advanced-stage cancer (OR 1.45; 95% CI 1.10-1.91).

          Conclusions

          Providing mammography facilities serving vulnerable women with appropriate resources may decrease disparities in abnormal mammogram follow-up and cancer diagnosis stage.
            Cover page: Mammography facilities serving vulnerable women have longer follow‐up times
            • Article
            • Peer Reviewed
            UC San Francisco Previously Published Works (2015)

            Purpose

            Women with proliferative breast lesions are candidates for primary prevention, but few risk models incorporate benign findings to assess breast cancer risk. We incorporated benign breast disease (BBD) diagnoses into the Breast Cancer Surveillance Consortium (BCSC) risk model, the only breast cancer risk assessment tool that uses breast density.

            Methods

            We developed and validated a competing-risk model using 2000 to 2010 SEER data for breast cancer incidence and 2010 vital statistics to adjust for the competing risk of death. We used Cox proportional hazards regression to estimate the relative hazards for age, race/ethnicity, family history of breast cancer, history of breast biopsy, BBD diagnoses, and breast density in the BCSC.

            Results

            We included 1,135,977 women age 35 to 74 years undergoing mammography with no history of breast cancer; 17% of the women had a prior breast biopsy. During a mean follow-up of 6.9 years, 17,908 women were diagnosed with invasive breast cancer. The BCSC BBD model slightly overpredicted risk (expected-to-observed ratio, 1.04; 95% CI, 1.03 to 1.06) and had modest discriminatory accuracy (area under the receiver operator characteristic curve, 0.665). Among women with proliferative findings, adding BBD to the model increased the proportion of women with an estimated 5-year risk of 3% or higher from 9.3% to 27.8% (P<.001).

            Conclusion

            The BCSC BBD model accurately estimates women's risk for breast cancer using breast density and BBD diagnoses. Greater numbers of high-risk women eligible for primary prevention after BBD diagnosis are identified using the BCSC BBD model.
              Cover page: Breast Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer.
              • Article
              • Peer Reviewed
              UC San Francisco Previously Published Works (2013)
              Abstract Introduction Percent mammographic density (PMD) adjusted for age and body mass index is one of the strongest risk factors for breast cancer and is known to be approximately 60% heritable. Here we report a finding of an association between genetic ancestry and adjusted PMD. Methods We selected self-identified Caucasian women in the California Pacific Medical Center Research Institute Cohort whose screening mammograms placed them in the top or bottom quintiles of age-adjusted and body mass index-adjusted PMD. Our final dataset included 474 women with the highest adjusted PMD and 469 with the lowest genotyped on the Illumina 1 M platform. Principal component analysis (PCA) and identity-by-descent analyses allowed us to infer the women's genetic ancestry and correlate it with adjusted PMD. Results Women of Ashkenazi Jewish ancestry, as defined by the first principal component of PCA and identity-by-descent analyses, represented approximately 15% of the sample. Ashkenazi Jewish ancestry, defined by the first principal component of PCA, was associated with higher adjusted PMD (P = 0.004). Using multivariate regression to adjust for epidemiologic factors associated with PMD, including age at parity and use of postmenopausal hormone therapy, did not attenuate the association. Conclusions Women of Ashkenazi Jewish ancestry, based on genetic analysis, are more likely to have high age-adjusted and body mass index-adjusted PMD. Ashkenazi Jews may have a unique set of genetic variants or environmental risk factors that increase mammographic density.
                Cover page: High mammographic density in women of Ashkenazi Jewish descent
                • Article
                • Peer Reviewed
                California Breast Cancer Research Program Funded Publications (2016)
                Among women diagnosed with ductal carcinoma in situ (DCIS), we identified factors associated with local invasive cancer (LIC) and regional/metastatic invasive cancer (RMIC) and provide 10-year risks based on clinically relevant factors. We created a retrospective, population-based cohort of 1492 women with an initial diagnosis of DCIS (1983–1996) treated by lumpectomy alone. Histological and molecular markers (Ki67, ER, PR, COX-2, p16, ERBB2) were collected on DCIS cases with a subsequent tumor (DCIS, LIC, or RMIC) and a subsample of frequency-matched controls without subsequent tumors. Competing risks methods were used to identify factors associated with LIC and RMIC and cumulative incidence methods to estimate 10-year risks for combinations of factors. Median follow-up time was 12.6 years (range 0.5–29.5 years). The overall 10-year risk of LIC (11.9 %) was higher than for RMIC (3.8 %). About half of women with initial DCIS lesions are detected by mammography and p16 negative and have a 10-year risk of LIC of 6.2 % (95 % CI 5.8–6.8 %) and RMIC of 1.2 % (95 % CI 1.1–1.3 %). Premenopausal women whose DCIS lesion was p16 positive or p16 negative and detected by palpation had high 10-year risk of LIC of 23.0 % (95 % CI 19.3–27.4 %). Ten-year risk of RMIC was highest at 22.5 % (95 % CI 13.8–48.1 %) for those positive for p16, COX-2, and ERRB2, and negative for ER, but prevalence of this group is low at 3 %. Ten-year risk of LIC and RMIC is low for the majority diagnosed with DCIS. Combinations of molecular markers and method of detection of initial DCIS lesion can differentiate women at low and high risk of LIC and RMIC.
                  Cover page: Risk prediction for local versus regional/metastatic tumors after initial ductal carcinoma in situ diagnosis treated by lumpectomy
                  • Article
                  • Peer Reviewed
                  UC San Francisco Previously Published Works (2016)
                  Among women diagnosed with ductal carcinoma in situ (DCIS), we identified factors associated with local invasive cancer (LIC) and regional/metastatic invasive cancer (RMIC) and provide 10-year risks based on clinically relevant factors. We created a retrospective, population-based cohort of 1492 women with an initial diagnosis of DCIS (1983-1996) treated by lumpectomy alone. Histological and molecular markers (Ki67, ER, PR, COX-2, p16, ERBB2) were collected on DCIS cases with a subsequent tumor (DCIS, LIC, or RMIC) and a subsample of frequency-matched controls without subsequent tumors. Competing risks methods were used to identify factors associated with LIC and RMIC and cumulative incidence methods to estimate 10-year risks for combinations of factors. Median follow-up time was 12.6 years (range 0.5-29.5 years). The overall 10-year risk of LIC (11.9 %) was higher than for RMIC (3.8 %). About half of women with initial DCIS lesions are detected by mammography and p16 negative and have a 10-year risk of LIC of 6.2 % (95 % CI 5.8-6.8 %) and RMIC of 1.2 % (95 % CI 1.1-1.3 %). Premenopausal women whose DCIS lesion was p16 positive or p16 negative and detected by palpation had high 10-year risk of LIC of 23.0 % (95 % CI 19.3-27.4 %). Ten-year risk of RMIC was highest at 22.5 % (95 % CI 13.8-48.1 %) for those positive for p16, COX-2, and ERRB2, and negative for ER, but prevalence of this group is low at 3 %. Ten-year risk of LIC and RMIC is low for the majority diagnosed with DCIS. Combinations of molecular markers and method of detection of initial DCIS lesion can differentiate women at low and high risk of LIC and RMIC.
                    Cover page: Risk prediction for local versus regional/metastatic tumors after initial ductal carcinoma in situ diagnosis treated by lumpectomy.
                    • Article
                    • Peer Reviewed
                    UC San Francisco Previously Published Works (2015)

                    Background

                    One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined whether two BI-RADS density measures improve the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared with one measure.

                    Methods

                    We included 722,654 women of ages 35 to 74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000-2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death.

                    Results

                    The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC, 0.640 vs. 0.635). Of 18.6% of women (134,404 of 722,654) who decreased density categories, 15.4% (20,741 of 134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to ≥1.67% with the two-density model.

                    Conclusion

                    The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density.

                    Impact

                    A two-density model should be considered for women whose density decreases when calculating breast cancer risk.
                      Cover page: One versus Two Breast Density Measures to Predict 5- and 10-Year Breast Cancer Risk
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