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Palghar News > Blog > Health > Long-term benefit from anti-hormonal treatment is influenced by menopausal status: Study – World News Network
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Long-term benefit from anti-hormonal treatment is influenced by menopausal status: Study – World News Network

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Last updated: December 4, 2024 12:00 am
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Stockholm County [Sweden], December 4 (ANI): Women with oestrogen-sensitive breast cancer now receive anti-hormonal therapy. Researchers have discovered that postmenopausal women with low-risk tumours have a long-term benefit for at least 20 years, whereas younger women with similar tumour characteristics who had not yet gone through menopause benefitted for a shorter period of time.
“Younger women generally have a higher risk of recurrence than older postmenopausal women, but most studies on anti-hormonal therapy have mainly included postmenopausal women. We therefore wanted to compare the long-term benefit from the treatment in both groups,” says Linda Lindstrom, associate professor and research group leader at the Department of Oncology-Pathology, Karolinska Institutet, who led the study.
In Sweden, 9 000 women are diagnosed with breast cancer each year, with hormone-sensitive breast cancer accounting for about 75 percent of women diagnosed with the disease. In patients with hormone-sensitive breast cancer tumour growth is mainly driven by oestrogen and patients are therefore treated with oestrogen-suppressing drugs, often tamoxifen.
However, anti-hormonal treatment reduces quality of life and the question has been how the long-term benefit against recurrence looks like. About a third of women diagnosed with breast cancer are younger and have yet not undergone the menopause, i.e. they are premenopausal, and are known to have an increased risk of recurrence.
The study includes more than 1,200 women diagnosed with hormone-dependent breast cancer between 1976 and 1997 of which almost 400 were premenopausal. At the start of the study it was not known whether anti-hormonal treatment was beneficial and therefore women were randomised to treatment with tamoxifen for at least two years or no anti-hormonal treatment, i.e. the control group. The outcome of interest was breast cancer metastasis or distant recurrence and today there is follow-up data for more than 20 years after initial diagnosis.
“From the regional breast cancer registry, we have an almost complete follow-up on all patients and this together with a control group who did not receive anti-hormonal treatment makes the study unique. There is also complete data on whether the women were pre- or post-menopausal at diagnosis, which is otherwise often estimated based on age,” says Annelie Johansson, researcher at the same department and the study’s first author.
The women’s tumours were classified as low or high risk based on the clinically used markers. Low risk tumor characteristics were defined as a tumour size of two centimeters in diameter or less, no lymph node spread, low tumour grade, being positive for the progesterone receptor, and a low genomic risk, which was determined by a molecular signature that measures the expression of 70 different genes.
Women with high-risk tumours had less benefit against distant recurrence, whether they had gone through menopause or not. Women with low-risk tumours after menopause had a long-term benefit of 20 years or more. For younger women who had not gone through menopause at diagnosis, a long-term benefit could not be predicted using the clinically used markers. Therefore, new markers are needed, the researchers say.
“We need to work further to understand which tumour characteristics influence the long-term risk of recurrence and benefit in younger patients. We want patients to benefit from their treatment for as long as the risk of recurrence is elevated,” says Linda Lindstrom.
In the next step, the researchers want to be able to link more complex tumour characteristics to the long-term risk and benefit of anti-hormonal therapy, in order to individualise the treatment to the patients who benefit from it.
“For example, we plan to perform multi-protein analyses and use machine learning for image analysis of breast cancer tumours to understand more about tumour heterogeneity – i.e. differences between and within tumors – and how it affects risk and treatment benefit,” says Linda Lindstrom. (ANI)


Disclaimer: This story is auto-generated from a syndicated feed of ANI; only the image & headline may have been reworked by News Services Division of World News Network Inc Ltd and Palghar News and Pune News and World News

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