Journal article
Clinicopathologic characteristics associated with long-term survival in advanced epithelial ovarian cancer: an NRG Oncology/Gynecologic Oncology Group ancillary data study
Gynecologic oncology, v 148(2)
Feb 2018
PMID: 29195926
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
•Of 3010 evaluable patients in GOG 182, 6.5% achieved long term survival (LTS) with survival >10years.•Patients requiring lower complexity surgery and those with smaller postoperative residual were more likely to achieve LTS.•Lower CA-125, absence of ascites, stage III disease, and microscopic residual were independent predictors of LTS.•Histology, preoperative disease extent, and performance status were also associated with LTS.•A predictive model using extensive clinicopathologic data achieved an AUC of 0.729.
To identify clinicopathologic factors associated with 10-year overall survival in epithelial ovarian cancer (EOC) and primary peritoneal cancer (PPC), and to develop a predictive model identifying long-term survivors.
Demographic, surgical, and clinicopathologic data were abstracted from GOG 182 records. The association between clinical variables and long-term survival (LTS) (>10years) was assessed using multivariable regression analysis. Bootstrap methods were used to develop predictive models from known prognostic clinical factors and predictive accuracy was quantified using optimism-adjusted area under the receiver operating characteristic curve (AUC).
The analysis dataset included 3010 evaluable patients, of whom 195 survived greater than ten years. These patients were more likely to have better performance status, endometrioid histology, stage III (rather than stage IV) disease, absence of ascites, less extensive preoperative disease distribution, microscopic disease residual following cyoreduction (R0), and decreased complexity of surgery (p<0.01). Multivariable regression analysis revealed that lower CA-125 levels, absence of ascites, stage, and R0 were significant independent predictors of LTS. A predictive model created using these variables had an AUC=0.729, which outperformed any of the individual predictors.
The absence of ascites, a low CA-125, stage, and R0 at the time of cytoreduction are factors associated with LTS when controlling for other confounders. An extensively annotated clinicopathologic prediction model for LTS fell short of clinical utility suggesting that prognostic molecular profiles are needed to better predict which patients are likely to be long-term survivors.
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Details
- Title
- Clinicopathologic characteristics associated with long-term survival in advanced epithelial ovarian cancer: an NRG Oncology/Gynecologic Oncology Group ancillary data study
- Creators
- C.A. Hamilton - Walter Reed National Military Medical CenterA. Miller - Gynecologic Oncology GroupY. Casablanca - Walter Reed National Military Medical CenterN.S. Horowitz - Brigham and Women's HospitalB. Rungruang - Augusta UniversityT.C. Krivak - Western Pennsylvania HospitalS.D. Richard - Hahnemann University HospitalN. Rodriguez - Loma Linda University Medical CenterM.J. Birrer - Gillette Center for Gynecologic Oncology, Massachusetts General Hospital, Boston, MA, United StatesF.J. Backes - Division of Gynecologic Oncology, Ohio State University Wexner Medical Center and James Cancer Hospital, Columbus, OH, United States.M.A. Geller - University of MinnesotaM. Quinn - Royal Women's HospitalM.J. Goodheart - University of IowaD.G. Mutch - Washington University in St. LouisJ.J. Kavanagh - The University of Texas MD Anderson Cancer CenterG.L. Maxwell - Inova Fairfax HospitalM.A. Bookman - Arizona Oncology
- Publication Details
- Gynecologic oncology, v 148(2)
- Publisher
- Elsevier
- Grant note
- CA 37517 / Gynecologic Oncology Group Statistical and Data Center 1 U10 CA180822; U10 CA180868 / NRG Oncology CA 27469 / National Cancer Institute (https://doi.org/10.13039/100000054)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Accelerated Career Entry Bachelor of Science in Nursing (BSN); Obstetrics and Gynecology
- Web of Science ID
- WOS:000425574100007
- Scopus ID
- 2-s2.0-85036548798
- Other Identifier
- 991019168698104721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Obstetrics & Gynecology
- Oncology