As many of you know, I’m currently putting the finishing touches on my latest book detailing my wife’s battles against her recently diagnosed breast cancer. Fortunately her cancer was caught at a very early stage and is not an aggressive form of cancer, and she is expected to make a full recovery. However, there are many decisions she has faced regarding her treatment, and her choices are detailed in the book (which I hope to have finished and published in e-book format by the end of the year.)
As a result of her recent diagnosis, I’ve been spending many waking hours doing a lot of research for her, trying to find information that can help guide her choices regarding her treatment.
One area of concern in particular is whether or not she should use the drug tamoxifen as part of her ongoing therapy. Tamoxifen is a hormonal drug that is prescribed for all women with estrogen receptor positive breast cancer (isn’t it interesting that conventional medicine prescribes a treatment for ALL patients regardless of their particular set of circumstances or individual concerns.) Tamoxifen is a strange drug: it can block estrogen from attaching to breast cells (and theoretically lower the risk of breast cancer recurring) but also acts like estrogen as it stimulates other cells of the body (in particular cells of the uterus, which explains the possibility of uterine cancer as a side effect of tamoxifen therapy.) Since Sandy tends to not want to take conventional medications unless there is an absolute benefit to them, we wanted to find out as much information as possible about whether or not tamoxifen therapy might be of benefit to her, and if there is benefit to her taking it, find out how much benefit they would be for her.
And this is where the idea of medical statistics comes in. I’m going to include a lot of information on the research involving tamoxifen in my book, but for now I just wanted touch on the topic of understanding statistics.
Looking at the statistics of the benefits of tamoxifen for Sandy’s particular grade of cancer (which is obtained via a number of analyses performed on her tumor including the Oncotype DX test,) statistics show that 5 years of tamoxifen therapy could reduce her risk of breast cancer recurring in her affected breast, opposite breast, or somewhere else in her body by approximately 50% (notice that studies do not “guarantee” that tamoxifen will do this, only that it “could” do this.) On the surface, a risk reduction of 50% seems pretty good. If we didn’t look beyond that number, it would make sense that most women would benefit from tamoxifen therapy (ignoring for the sake of argument that some women will develop uterine cancer or a second breast cancer which is usually more aggressive than the initial breast cancer, not to mention other side effects such as hot flashes or blood clots that could lead to a stroke.)
However, in trying to understand how medical statistics apply to a treatment you’re considering for yourself, family members, or your pet, you have to look at the actual risk the patient may face in real numbers. Based on studies using the Oncotype DX recurrence score, women like Sandy with a low recurrence score have a 10 year survival of approximately 97% if they take tamoxifen. The same women have approximately a 94% ten-year survival if they do not take tamoxifen. In other words, 3/100 women taking tamoxifen are expected to die from breast cancer after 10 years following their diagnosis, whereas 6/100 women not taking tamoxifen are expected to die from breast cancer 10 years following their diagnosis. The difference between 6 women versus 3 women is 50%! Therefore, tamoxifen is expected to lower the risk of death by 50%. If you look at the real numbers however, we’re only talking about a difference of 3 women. For Sandy, it wasn’t worth the risk associate with tamoxifen therapy to reduce her real risk of only 3%.
And this is why it’s so important to look at the real numbers rather than simply medical statistics. While doctors and pharmaceutical companies love to quote statistics in terms of percentages, it’s vitally important to understand the real numbers behind the statistics. While a 50% reduction in death sounds great, when you are only talking about 3 people surviving if they use a certain medication, that 50% reduction in death doesn’t seem so impressive anymore.
Finally, whatever the statistics or the real numbers presented in the study, keep in mind that the patients being tested are “generic” patients. As much as possible, you must try to determine YOUR real risk or YOUR PET’S real risk in order to make the best decision for therapy.
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