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Скачать или смотреть Ovarian Suppression Plus AI Treatment Can Have Major Adverse Events

  • OncLive
  • 2020-01-24
  • 1391
Ovarian Suppression Plus AI Treatment Can Have Major Adverse Events
canceroncology
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Описание к видео Ovarian Suppression Plus AI Treatment Can Have Major Adverse Events

Combining ovarian suppression and an aromatase inhibitor is an efficacious treatment method for premenopausal women with breast cancer. However, the regimen (which is given long-term) can cause some major adverse events, explained Dawn L. Hershman, MD, MS, professor of medicine and epidemiology at the Columbia University Irving Medical Center.

Transcription

Several trials were published, one the SOFT trial, the other the TEXT trial. Both of them were very similar in a lot of ways, looking at premenopausal women and the effect of ovarian suppression. We discovered that there actually is a benefit to suppressing a woman's ovaries and giving her an aromatase inhibitor along with it, compared to giving tamoxifen alone.

But the biggest problem with doing that is that it's very toxic. We always think about the toxicities of chemotherapy, but the toxicities from endocrine therapy can be far worse, and they go on much longer. We give these treatment for 5, sometimes even 10 years. It's super challenging to keep people on their therapy. We've done research showing that just even with 5 years of tamoxifen, by the end of the 5 years, only about 50% of patients are taking it more than 80% of the time. The reason why people stop their medications is complicated. But one of the most common reasons why people stop taking their medications is side effects. We know that when we take a young woman and we suppress her ovarian function and we give them an aromatase inhibitor, close to 100% have side effects. It can cause depression, hot flashes, difficulty sleeping severe bowl pain, and problems with their mood. It can increase their risk for osteoporosis, and sometimes even cardiovascular disease. So it's not without significant consequences.

In order to better treat young women, we need better risk prediction models to figure out exactly who are the people at highest risk, so that we can target those women and give them more intensive treatment, and spare women who maybe don't have such high risk cancer.

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