Journal article
Integration of Clinical and Molecular Features into Prediction Models for Outcomes in Endometrial Cancer
Clinical obstetrics and gynecology, Vol.63(1), pp.40-47
03/01/2020
DOI: 10.1097/GRF.0000000000000498
PMID: 31725417
Abstract
Endometrial cancer recurrence carries a poor prognosis. The rising incidence of endometrial cancer calls for improvements in treatment of advanced and recurrent diseases. Efforts have been made to molecularly characterize endometrial cancer with the goal of improving therapies. The study presented here describes the utilization of molecular features of endometrial cancer tumors that are likely to recur, along with clinical characteristics utilized together to predict recurrence. This work further studies recurrent endometrial cancers to group them into "clusters" based on the tumor's molecular makeups with the ultimate aim to focus therapy on the molecular pathways potentially leading to recurrence.
Details
- Title: Subtitle
- Integration of Clinical and Molecular Features into Prediction Models for Outcomes in Endometrial Cancer
- Creators
- Marina D. Miller - Department of Obstetrics and Gynecology.Eric J. Devor - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Clinical obstetrics and gynecology, Vol.63(1), pp.40-47
- Publisher
- Lippincott Williams & Wilkins
- DOI
- 10.1097/GRF.0000000000000498
- PMID
- 31725417
- ISSN
- 0009-9201
- eISSN
- 1532-5520
- Number of pages
- 8
- Grant note
- R01 CA99908; R01 CA184101 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA Department of Obstetrics & Gynecology at the University of Iowa
- Language
- English
- Date published
- 03/01/2020
- Academic Unit
- Obstetrics and Gynecology
- Record Identifier
- 9984315748502771
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