We built a simulation model to estimate and compare multiple health outcomes for BRCA1/2
mutation carriers under various cancer risk-reduction strategies and converted it into an online decision tool for use by physicians and patients. We found that early prophylactic mastectomy and salpingo-oophorectomy most effectively prevent cancer, but alternatives that reduce cancer incidence far less substantially can offer comparable survival. MRI-based breast screening yields this benefit through a diagnostic stage shift, increasing the proportion of stage I tumors from 18% to 22% up to 67% to 68%; treatment recommendations vary by hormone receptor expression, which is correlated with the type of BRCA
mutation. A BRCA2
mutation carrier who elects MRI screening may well escape a recommendation for adjuvant chemotherapy, because 81% of breast cancers diagnosed in this setting are smaller than 2 cm, node-negative, and hormone receptor-positive. The online decision tool77
enables direct comparison of many possible strategies for an individual patient, combining various screening methods with prophylactic surgeries undertaken at different ages and weighing their impact on cancer incidence, treatment experiences, and survival.
Decisions about cancer risk reduction are complex and highly personal. For most women in the population, the greatest challenge is estimating risk accurately.78
Imprecision in communicating risk-benefit ratios may contribute to under-utilization of effective strategies such as chemoprevention.79
mutation carriers, cancer risks are higher and better defined, driving greater uptake of prophylactic surgeries and intensive surveillance.57,58
Nonetheless, a significant number of women with BRCA1/2
mutations never develop cancer, given variations in penetrance which are incompletely understood80–82
; removing organs at risk thus remains a gamble. Use of prophylactic surgeries varies by country, age, and prior cancer diagnosis, and aspects of personal experience such as family cancer history and parity play a role.56,57,83,84
Prior decision analyses have assigned a set value to life after prophylactic surgery or with screening and reported results in quality-adjusted life years.25,27,31,85,86
Given our experience of substantial variation in patient preferences, we elected against ranking health states under different risk-reducing interventions. Instead, our estimates across multiple outcomes aim to guide patients in optimizing their quality of life, depending on their individual values: for one woman this could entail retaining her breasts for decades, with eventual diagnosis of an early-stage breast cancer that might require chemotherapy; for another, this could entail maximal cancer prevention by removing her breasts and ovaries early in life.
With rapid growth in therapeutic and diagnostic technology, decision aids are increasingly used in oncology practice. They synthesize diverse data sources and integrate comparisons across disparate (and often conflicting) scales of benefit, such as efficacy, toxicity, and cost. Trials have demonstrated improvements in decisional conflict and satisfaction with the use of decision aids in breast, colorectal, and thoracic oncology.76,87–92
Decision aids weigh the absolute magnitude of an intervention's benefit against competing risks and may align choices more closely with expected therapeutic gains.93
The online format of our decision tool facilitates access and personalization; results are customized for a patient's age, allowing women to revisit their decisions over time should their health status, life circumstances, or priorities change. Additionally, the online tool can be readily adapted to accommodate new data from emerging studies. No decision aid can replace any aspect of the physician–patient relationship; our tool aims rather to channel the discussion toward choices that more fully realize a patient's personal preferences.
Our work has some limitations. The results of any simulation model depend on its assumptions. We initially developed and validated our model with SEER registry data, modeling tumor growth and ER expression as a function of grade52,53,94
; we subsequently applied this same strategy to BRCA1/2
-associated breast cancers, using appropriate tumor grade and ER distributions.13,15,23,55,95,96
Although justified by reports that patients with breast cancer with and without BRCA1/2
mutations have similar outcomes,20,59,60,97
this fundamental approach is difficult to validate. The model lacks data on breast tumor progesterone receptor and human epidermal growth factor receptor 2 expression, given their absence in SEER; because human epidermal growth factor receptor 2 overexpression is rare in BRCA1/2
this limitation is unlikely to change our conclusions. An additional limitation is our use of average BRCA1/2
mutation penetrance estimates, derived from meta-analyses1,2
; our model does not incorporate factors that may mediate individual risk variation, such as birth cohort, family history, lifestyle and environmental exposures, or single-nucleotide polymorphisms in other genes.81,82,98,99
We did not assign a separate prognostic category to carcinoma in situ or consider emerging treatments such as poly (ADP-ribose) polymerase inhibitors. We varied input parameters widely in sensitivity analyses and found that our assumptions about BRCA1/2
-associated cancer risks, the sensitivity of MRI, and the effect of PO on breast cancer incidence were most influential. If MRI-based breast screening detects preinvasive cancers,9,45,100
which have optimal survival and no requirement for chemotherapy,74
or if BRCA1/2
mutation-targeted cancer therapies improve survival with few adverse effects,101–104
then breast screening may provide a better outcome than we estimate; conversely, if mutation penetrance is higher or cancer prognosis worse than we estimate, prophylactic surgeries would appear more favorable. The online decision tool focuses on cancer-free women; it does not report second primary cancer risks, mortality from a prior cancer, or benefit from a procedure performed in the past. We have not measured the tool's impact on decision outcomes in a clinical trial, but pilot-testing among 60 patients and providers yielded high rankings on clinical relevance and ease of use, with a full analysis underway. Future work is warranted to address these limitations of the model and decision tool.
We calculated cancer incidence, tumor prognostic features that influence treatment and quality of life, overall survival, and cause-specific mortality under many possible risk-reduction strategies for BRCA1/2 mutation carriers. We customized these results by age and BRCA mutation and adapted them into an online tool to support joint decision making by patients and physicians. By characterizing the multiple health outcomes associated with cancer risk-reduction options, our decision tool aims to clarify a patient's priorities and guide choices that preserve them.