Gynecologic Cancer
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Deep learning algorithms combined with MRI could have a major impact on diagnosing patients with high-risk disease.
A Mendelian randomized analysis was performed to determine the effects of anti-CD20 antibodies on endometrial cancer.
This could be a needed breakthrough for those predisposed to breast and ovarian cancer mutations.
There is a compelling case for the PK benefit of GLP-1s on certain cancer cell lines.
Krystina Dunston spoke about the findings of a study which showed potential in slowing tumor growth in endometrial cancer.
Pembrolizumab plus chemoradiotherapy was shown to improve survival in advanced cervical cancer.
Dr. Andrew Hertler Talks About Current Treatments, Quality of Life for Women With Endometrial Cancer
Dr. Andrew Hertler spoke about the biggest challenges, and most promising treatments associated with endometrial cancer care.
A study identified possible prognostic factors and survival patterns based on histology type in endometrial cancer patients.
A study analyzed the correlation between cancer-related cognitive impairment and neurotransmission pathways.
Dr. Andrew Hertler explains why health disparities exist for Black women with ovarian cancer.
Sexual counseling training in gynecological cancers is effective at generating increased awareness among midwifery students.
The FDA approved dostarlimab-gxly with carboplatin and paclitaxel for endometrial cancer.
The FDA approved pembrolizumab with chemotherapy for adult patients with primary advanced, recurrent endometrial carcinoma.
Pembrolizumab use is increasing among patients with recurrent cervical cancer.
An objective manual screening process may enhance diversity in gynecologic cancer clinical trial enrollment.
Camrelizumab plus apatinib demonstrates robust and sustained efficacy in treating patients with advanced cervical cancer.
The FDA granted approval to tisotumab vedotin-tftv for the treatment of recurrent or metastatic cervical cancer.
The addition of dostarlimab to platinum chemotherapy is cost effective and significantly improves QOL.
A blood-based machine learning assay may be able to differentiate patients with ovarian cancer from healthy patients.
According to a retrospective study, a high preoperative CONUT score indicates poor prognosis in cervical cancer.
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