Improving Risk Assessment for Metastatic Disease in Endometrioid Endometrial Cancer Patients Using Molecular and Clinical Features: An NRG Oncology/Gynecologic Oncology Group Study
Year: 2022
Type: article
Study design: Observational Study
Abstract: Objectives: A risk assessment model for metastasis in endometrioid endometrial cancer (EEC) was developed using molecular and clinical features, and prognostic association was examined. Methods: Patients had stage I, IIIC, or IV EEC with tumor-derived RNA-sequencing or microarray-based data. Metastasis-associated transcripts and platform-centric diagnostic algorithms were selected and evaluated using regression modeling and receiver operating characteristic curves. Results: Seven metastasis-associated transcripts were selected from analysis in the training cohorts using 10-fold cross validation and incorporated into an MS7 classifier using platform-specific coefficients. The predictive accuracy of the MS7 classifier in Training-1 was superior to that of other clinical and molecular features, with an area under the curve (95% confidence interval) of 0.89 (0.80–0.98) for MS7 compared with 0.69 (0.59–0.80) and 0.71 (0.58–0.83) for the top evaluated clinical and molecular features, respectively. The performance of MS7 was independently validated in 245 patients using RNA sequencing and in 81 patients using microarray-based data. MS7 + MI (myometrial invasion) was preferrable to individual features and exhibited 100% sensitivity and negative predictive value. The MS7 classifier was associated with lower progression-free and overall survival (p ≤ 0.003). Conclusion: A risk assessment classifier for metastasis and prognosis in EEC patients with primary tumor derived MS7 + MI is available for further development and optimization as a companion clinical support tool.
Source: Cancers
Authors: Yovanni Casablanca, Guisong Wang, Heather A. Lankes, Chunqiao Tian, Nicholas W. Bateman, Caela R. Miller, Nicole P. Chappell, Laura J. Havrilesky, Amy Hooks Wallace, Nilsa C. Ramirez, David S. Miller, Julie Oliver, Dave Mitchell, Tracy Litzi, Brian E. Blanton, William J. Lowery, John I. Risinger, Chad A. Hamilton, Neil T. Phippen, Thomas P. Conrads, David Mutch, Katherine Moxley, Roger B. Lee, Floor Backes, Michael J. Birrer, Kathleen M. Darcy, George Larry Maxwell
Institutions: Uniformed Services University of the Health Sciences, Walter Reed National Military Medical Center, Henry M. Jackson Foundation, Roswell Park Comprehensive Cancer Center, Duke University, Duke Medical Center, Nationwide Children's Hospital, The University of Texas Southwestern Medical Center, Michigan State University, Inova Health System, Washington University in St. Louis, University of Oklahoma Health Sciences Center, University of Oklahoma, MultiCare Tacoma General Hospital, The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute, The Ohio State University
Language: English
Subfield: Obstetrics and Gynecology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,513
Awards: G1291646684, Gynecologic Oncology Group Specimen Banking, G1980229645, G2809725690, GYNECOLOGIC DISEASE PROGRAM, GYNECOLOGIC ONCOLOGY GROUP STATISTICAL AND DATA CENTER, G4285681, NRG Oncology Network Group Operations Center, Gynecologic Oncology Group, G6105514657, GYNECOLOGIC CANCER-CENTER OF EXCELLENCE (GYN-COE) CORE, GYNECOLOGIC CANCER CENTER OF EXCELLENCE (GYN-COE), GYNECOLOGICAL CANCER TRANSLATIONAL RESEARCH CENTER OF EXCELLENCE, NRG Oncology Biospecimen Bank, NRG Oncology - Statistical and Data Management Center
OpenAlex ID: W4293208767