? Project 3 Currently, 2.8 million women in the United States with a personal history of breast cancer (PHBC) face years of imaging surveillance. Breast imaging surveillance is aimed at the early detection of second breast cancer events, either local recurrence or new cancers in the other breast, with the goal of decreasing breast cancer mortality. Treatment strategies for primary breast cancers routinely take into account women's clinical and tumor characteristics. However, unlike treatment guidelines, current surveillance guidelines recommend annual mammography for all women with a PHBC regardless of risk. With new information about tumor biology and emerging imaging technologies (digital breast tomosynthesis and breast MRI), we can move toward risk-based surveillance decision making by women and their physicians. Although new imaging methods show promise for screening, their ability to improve early second breast cancer detection and longer-term outcomes is not yet established. The overall goal of this project is to facilitate a shift from a single strategy of annual mammography for all women to individualized, risk-based strategies, incorporating the full range of available imaging modalities and reliable estimates of a woman's risk of surveillance outcomes. We propose to integrate women's risk factors and tumor characteristics to produce risk estimates for important surveillance mammography outcomes: benefits (early detection of second invasive breast cancer), failures (interval detection of second invasive breast cancer after negative mammography) and false alarms (false-positive recall or biopsy recommendations). Early evidence suggests that women's risk factors, primary breast cancer characteristics, age at diagnosis, mode of detection, and treatment choices can be used to identify women at high risk of surveillance mammography failure who might benefit from alternative surveillance strategies (tomosynthesis alone or mammography and MRI). In addition, women at low risk of surveillance failure could minimize their risk of false alarms by receiving mammography or tomosynthesis alone. Our scientific premise is that tailored strategies will improve surveillance outcomes by reducing both surveillance failures and false alarms compared with guideline-recommended annual mammography alone.
Our specific aims are:
Aim 1 : Determine the benefits and harms of surveillance tomosynthesis compared with digital mammography among women with a PHBC.
Aim 2 : Develop novel risk prediction models to identify and directly compare a woman's cumulative absolute risk of surveillance mammography outcomes.
Aim 3 : Identify clinically actionable risk levels for consideration of more intensive surveillance, informed by perspectives of referring clinicians and radiologists. This project will combine clinical and imaging risk factors to estimate risks of important surveillance benefits, failures, and false alarms, supporting a shift away from a one size fits all annual surveillance strategy, toward individualized, risk-based strategies for women with a PHBC.
? Project 3 Currently, the 2.8 million US women with a personal history of breast cancer face decades of annual mammography to look for recurrences or new breast cancers. Decisions about this surveillance breast imaging are complicated for these women and their physicians, especially as we learn more about tumor biology and develop new imaging technologies such as digital breast tomosynthesis and MRI. This project will estimate risks of surveillance imaging benefits and harms, accounting for rapid changes in breast cancer information and imaging methods, to support a shift toward individualized, risk-based imaging strategies for women with a personal history of breast cancer.
| Lee, Janie M; Abraham, Linn; Lam, Diana L et al. (2018) Cumulative Risk Distribution for Interval Invasive Second Breast Cancers After Negative Surveillance Mammography. J Clin Oncol 36:2070-2077 |
| van den Broek, Jeroen J; van Ravesteyn, Nicolien T; Mandelblatt, Jeanne S et al. (2018) Comparing CISNET Breast Cancer Models Using the Maximum Clinical Incidence Reduction Methodology. Med Decis Making 38:112S-125S |
| Puvanesarajah, Samantha; Nyante, Sarah J; Kuzmiak, Cherie M et al. (2018) PAM50 and Risk of Recurrence Scores for Interval Breast Cancers. Cancer Prev Res (Phila) 11:327-336 |
| Mandelblatt, Jeanne S; Near, Aimee M; Miglioretti, Diana L et al. (2018) Common Model Inputs Used in CISNET Collaborative Breast Cancer Modeling. Med Decis Making 38:9S-23S |
| Dabbous, Firas; Dolecek, Therese A; Friedewald, Sarah M et al. (2018) Performance characteristics of digital vs film screen mammography in community practice. Breast J 24:369-372 |
| Alagoz, Oguzhan; Ergun, Mehmet Ali; Cevik, Mucahit et al. (2018) The University of Wisconsin Breast Cancer Epidemiology Simulation Model: An Update. Med Decis Making 38:99S-111S |
| Rice, Megan S; Tamimi, Rulla M; Bertrand, Kimberly A et al. (2018) Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics. Breast Cancer Res Treat 170:129-141 |
| Ray, Kimberly M; Kerlikowske, Karla; Lobach, Iryna V et al. (2018) Effect of Background Parenchymal Enhancement on Breast MR Imaging Interpretive Performance in Community-based Practices. Radiology 286:822-829 |
| He, Xiaofei; Schifferdecker, Karen E; Ozanne, Elissa M et al. (2018) How Do Women View Risk-Based Mammography Screening? A Qualitative Study. J Gen Intern Med 33:1905-1912 |
| Onega, T; Zhu, W; Weiss, J E et al. (2018) Preoperative breast MRI and mortality in older women with breast cancer. Breast Cancer Res Treat 170:149-157 |
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