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Authors

Andreea Mihai Newtson, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow
Rebecca K. Chung, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow
Eric J. Devor, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242 & Holden Comprehensive Cancer Center, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow
Erin A. Salinas, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242
Megan E. McDonald, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow
Kristina W. Thiel, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow
Michael J. Goodheart, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242 & Holden Comprehensive Cancer Center, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow
Kimberly K. Leslie, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242 & Holden Comprehensive Cancer Center, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow
Brian J. Smith, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242 & Department of Biostatistics, University of Iowa College of Public Health, Iowa City, IA, 52242
Jesus Gonzalez-Bosquet, Department of Obstetrics and Gynecology, Carver College of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242 & Holden Comprehensive Cancer Center, University of Iowa Hospitals and Clinics, Iowa City, IA, 52242Follow

DOI

10.17077/2154-4751.1390

Abstract

One of the prognostic factors most highly associated with ovarian cancer survival is response to initial chemotherapy. Current prediction models of chemo-response built with comprehensive molecular datasets, like The Cancer Genome Atlas (TCGA), could be improved by including clinical and outcomes data designed to study response to treatment. The objective of this study was to create a prediction model of ovarian cancer chemo-response using clinical-pathological features, and to compare its performance with a similar TCGA clinical model.

Keywords

Ovarian cancer, serous epithelial ovarian cancer, chemotherapy, chemotherapy response, prediction model, clinical predictors, TCGA

Total Pages

2 pages

Financial Disclosure

The authors report no conflict of interest.

Rights

Copyright © The authors, 2018.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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