A New Online Tool for BRCA1 and BRCA2 Carriers
It’s great to have advanced to the point where women with risk for Hereditary Breast and Ovarian Cancer have important decisions to make about cancer prevention and screening that meaningfully impact their lives. Nevertheless, the decision-making is still fraught with challenges – whether it occurs in the context of advice from a high risk breast and ovarian cancer prevention clinic at a busy academic or regional medical center or from a group with less BRCA1 and BRCA2 experience.
This is one key reason that there has been a great deal of interest in services and tools available over the web to assist BRCA1 and BRCA2 carriers – wherever they are – in making good decisions. Peer support, expert curation and analysis, new software, and social media all have important roles to play, and I’m thrilled to be able to say that a group at Stanford University led by Drs. Sylvia Plevritis and Allison Kurian has done fantastic work in creating a tool that may become another key arrow in the BRCA1 and BRCA2 carrier’s quiver.
A New Online Tool from a Stanford Team to Help Support Shared Decision-Making for BRCA1/2 Carriers and Their Physicians
Currently, after receiving the results of a BRCA1/2 test that show that a deleterious (cancer risk-associated) mutation is present, women, depending on their age, face several choices regarding whether or not to undergo risk-reducing surgeries in an effort to prevent future cancers, and additionally, if they choose to undergo one or more procedures, the appropriate timing is sometimes an issue.
Online information sources and decision aids are increasingly utilized in the context of the discussions between physicians and patients to facilitate optimal decision-making. One notable example is the Adjuvant! online tool, which is often used by medical oncologists in discussions with their patients regarding options for breast cancer adjuvant chemotherapy. The success of this format of information delivery in making complex information more easily understandable has led to interest in creating online tools to assist BRCA1/BRCA2 carriers with some of the complex decisions that they face too.
In a paper published online in January in the Journal of Clinical Oncology, Drs. Plevritis and Kurian and their colleagues report that they have adapted a previously published model to estimate BRCA1 and BRCA2 carriers’ outcomes given a number of distinct prevention and screening choices. They also created an online interface (available at the Stanford website via the link below) that allows women with BRCA1/2 mutations and no current/previous diagnosis of cancer to explore the potential impact of a multitude of screening and prevention options that they have at their disposal.
The online tool allows women to compare potential outcomes for a group of women their age carrying either BRCA1 or BRCA2 mutations given the following independent choices:
- Risk-Reducing Salpingo-oophorectomy (RRSO) at age 25 vs. RRSO at age 40 vs. RRSO at age 50 vs. no RRSO
- Risk-Reducing Bilateral Mastectomy (RRBM) at age 25 vs. RRBM at age 40 vs. RRBM at age 50 vs. no RRBM
- If RRBM has not been performed, annual breast screening with mammography and MRI vs. no breast screening
The tool then visually displays expected outcomes for a large simulated group of women of similar age pursuing the various choices – always in comparison to expected outcomes for both BRCA1/2 carrier and noncarrier women of similar age with no risk reduction or screening interventions.
There are several key features of the model and the tool that are particularly noteworthy:
- Since cancer risks and various aspects of anticipated outcomes can vary for BRCA1 carriers versus BRCA2 carriers, women with mutations in each gene are considered separately
- Downstream non-malignant risks of the hormonal changes brought on by early RRSO were added to the model, including risk for osteoporosis/hip fracture-related, heart disease-related and dementia-related death
- In terms of outcomes, the tool shows how many of 100 women pursuing the selected strategy at age 70 would: (1) have died of ovarian cancer; (2) have died of breast cancer; (3) have died of other causes; (4) be alive with ovarian cancer (and how many of these would also have breast cancer); (5) be alive after a breast cancer diagnosis; and (6) be alive with no prior diagnosis of breast or ovarian cancer
- The tool also provides more detailed information for the women alive with breast cancer, breaking this group down into estimated numbers with: (1) local vs. regional vs. distant metastatic disease; (2) hormone receptor positive vs. hormone receptor negative breast cancer; and (3) breast cancer needing hormonal and/or chemotherapy.
This last point may be particular useful for some women in decision-making given personal preferences re: how acceptable screening (as opposed to prophylactic surgery) would be if it might lead to diagnosis of a chemotherapy-requiring cancer, with the associated quality of life related issues.
Although you can learn the most from the online tool by exploring it yourself together with your healthcare provider, we will cover some of the more interesting results from the model here on the blog in a future post or two.
Some Important Potential Limitations to Keep in Mind
It is really important to keep in mind that studies of this sort – that involve modeling – are only as good as the input assumptions. In other words, a reasonable approach applied to poor inputs can result in a “garbage in, garbage out” scenario. For this reason, the researchers carefully detailed their assumptions – which are generally supported by the best available literature or are educated guesses in areas where the required studies have not been done (and the assumptions seem pretty reasonable to me). Additionally, they performed analyses called “sensitivity analyses” in order to test which of the particular inputs where significant uncertainty exists might most impact the outcome. This approach yielded a few key things that anyone using the tool should keep in mind:
1. The results related to survival and also the likelihood of developing breast or ovarian cancer were particularly dependent on the accuracy of input assumptions about: (1) penetrance of BRCA1/2 mutations (i.e., the chance that mutation carriers would develop breast cancer or ovarian cancer without preventative intervention) and (2) impact of prophylactic salpingo-oophorectomy on reduction of breast cancer risk. While the team used a reasonable approach to estimate both of these, it is possible that future research may refine these numbers, and this would require updating the online tool to reflect this. We will cover this in some more detail in a future post.
2. Regarding the assumptions about penetrance of BRCA1/2 mutations, they relied on data from population-based studies (as opposed to data from genetics clinic-based studies of families identified primarily via particularly strong family histories of cancer). As Kurian et al and also Drs. Gareth Evans and Anthony Howell point out (in an editorial accompanying the Kurian et al paper), there has been a fair amount of debate over whether it is best to utilize cancer risk estimates coming from population-based studied (which are probably the best true estimates of cancer risk across all BRCA1/2 carriers if we were able to identify all of them) or to use estimates from clinic-based studies which may actually better reflect the risks of women coming to attention in a similar setting with a prominent family history of breast and/or ovarian cancer. It’s likely that inheritance of some lower risk cancer susceptibility alleles (SNPs or single nucleotide polymorphisms) in some families presenting based on family histories in the clinic means that BRCA1/2 carriers in these families may tend to have somewhat larger cancer risks than carriers identified in population-based studies (like those used to guide the Kurian et al model penetrance estimates).
3. Model results related to breast cancer and its treatment in BRCA1 and BRCA2 carriers were particularly dependent on the assumptions made about just how sensitive screening breast MRI is at this time and also whether it impacts survival. We may learn more about breast MRI’s effectiveness – and most importantly, its effect on mortality or lack thereof – in the future. This would require updating the model at that time to reflect future knowledge.
Bottom Line for BRCA1 and BRCA2 Carriers
Despite the above limitations, the creators of this new tool deserve a big congratulations for creating a great resource and for making the tool publicly available via the internet.
In sum, the new tool allows women with BRCA1 and BRCA2 mutations together with their healthcare providers to visualize current best estimates of the impact of various potential prevention and screening options, and then, based on their own personal preferences make an educated decision about the best route forward. If there is a better tool available to complement the physician-patient relationship at the time of key decision-making about potentially undergoing risk-reducing surgical procedures, I have not seen it.
You can check out the tool here; we’d love to hear your thoughts about it in the comments!
What do you think? Will this be a useful tool for BRCA1/2 carriers and their physicians to use to explore prevention and screening options?
How We Know This:
Kurian AW, Munoz DF, Rust P, et al. Online tool to guide decisions for BRCA1/2 mutation carriers. Journal of Clinical Oncology 2012 (published online ahead of print January 9 2012)
Evans DG, Howell A. Are we ready for online tools in decision making for BRCA1/2 mutation carriers? Journal of Clinical Oncology 2012 (published online ahead of print January 9 2012)
Kurian AW, Sigal BM, Plevritis SK. Survival analysis of cancer risk reduction strategies for BRCA1/2 mutation carriers. Journal of Clinical Oncology 2010; 28:222-31.
If you know someone that this post would be useful to, please share it via facebook, email, or twitter by clicking on one of the icons below.