Ana Tergas
· Assistant Professor - Gyn Oncology Division DirectorVerifiedRutgers University · Obstetrics, Gynecology and Reproductive Health
Active 2008–2026
About
Dr. Ana Tergas is the Director of Gynecologic Oncology at Rutgers New Jersey Medical School and University Hospital. She is a 2024 Rutgers Presidential Faculty Scholar and a member of the Rutgers Hispanic Center of Excellence. She is an NIH-funded physician-scientist whose work focuses on health inequities in gynecologic cancer outcomes, end-of-life care, and HPV and cervical cancer prevention. Dr. Tergas has been recognized by the NIH and the National Cancer Institute for her leadership in health disparities research and has served on an NCI career development grant review study section. She trained at the University of Miami, the University of Chicago, and Johns Hopkins University, where she also earned her MPH. Her previous faculty appointments include Columbia University and City of Hope Comprehensive Cancer Center, where she held joint appointments in the Department of Surgery, Gynecologic Oncology Division, and the Department of Population Sciences, Health Equity Division. Dr. Tergas is active in national gynecologic oncology organizations, has held multiple leadership roles within the Society of Gynecologic Oncology, and serves on the editorial boards of Gynecologic Oncology and the Journal of Surgical Oncology. She is a committed mentor supporting trainees at all levels and has contributed to several national diversity and health equity initiatives.
Research topics
- Medicine
- Internal medicine
- Surgery
- General surgery
- Virology
- Gynecology
- Obstetrics
- Intensive care medicine
- Oncology
Selected publications
Drug and Alcohol Dependence · 2026-02-12
articleSurgery Open Science · 2026-01-20
articleOpen accessBackground: Changes in opioid prescribing practices have evolved, including perioperative settings. However, computerized clinical decision support systems to guide opioid prescribing remain limited. This study aimed to develop and validate prediction models for perioperative opioid needs among patients undergoing laparoscopic cholecystectomy (LC) and to create a risk-scoring tool. Methods: This was a retrospective cohort study. Using electronic medical records (EMR), we identified patients aged 18-64 years who underwent LC for benign conditions between October 2015 and December 2018. Demographic, clinical, and surgical data were collected. Perioperative opioid needs were classified as none/low (0-3 days), medium (4-6 days), or high (≥7 days), based on self-reported pain scores and prescription duration. The cohort was split into training (70%) and testing (30%) datasets. Prediction models were developed using random forest, Least Absolute Shrinkage and Selection Operator (LASSO), and subject-matter expertise, with performance evaluated by discrimination, calibration, accuracy, precision, recall, and F1 score. Results: = 333), LASSO outperformed random forest with better calibration. The revised LASSO model, incorporating subject-matter knowledge, improved interpretability, achieving an AUC of 0.64 and Brier score of 0.20. Key predictors included gender, pre-operative medication, emergency surgery, anesthesia type, and surgical indications. A nomogram was developed for visual prediction. Conclusions: Prediction of perioperative opioid needs using EMR and machine-learning is feasible and may support individualized pain management, though further refinement of model performance is warranted.
The Future of Cervical Cancer Screening Is Now
Obstetrics and Gynecology · 2025-06-18
article1st authorCorresponding2025-12-11
articleOpen access<p>Detailed summary of therapeutic response at end-of-study time point, organized by study group—OncoTreat, OncoTarget, or Negative control—and then stratified by each individual drug arm. The study was underpowered for statistical analyses of therapeutic response in individual drug arms.</p>
2025-12-11
articleOpen access<p>Prioritized drugs, prediction basis, and dosing schedule for PDX therapeutic study.</p>
2025-11-26
articleOpen accessSupplementary Figure from Clinical Utility of Reflex Testing with Cancer Biomarkers to Improve Diagnostic Accuracy of Primary Human Papillomavirus Screening
Gynecologic Oncology · 2025-09-01
articleGenetic ancestry and genomic alterations of cervical cancer in a diverse patient population
Gynecologic Oncology · 2025-09-01
article1st authorCorrespondingGynecologic Oncology · 2025-09-01
article1st authorCorresponding2025-12-11
articleOpen access<p>Curated list of proteins with high-affinity inhibitor drugs for OncoTarget analysis.</p>
Frequent coauthors
- 1633 shared
Jason D. Wright
- 1490 shared
June Y. Hou
NewYork–Presbyterian Hospital
- 1315 shared
Dawn L. Hershman
Columbia University Irving Medical Center
- 1110 shared
Alfred I. Neugut
- 967 shared
Cande V. Ananth
Rutgers, The State University of New Jersey
- 680 shared
Caryn M. St. Clair
Herbert Irving Comprehensive Cancer Center
- 664 shared
William M. Burke
Stony Brook Medicine
- 596 shared
Fady Khoury‐Collado
Education
- 2000
B.S.
University of Florida
- 2006
M.D.
University of Miami Miller School of Medicine
- 2011
Other
Johns Hopkins Bloomberg School of Public Health
Other, Obstetrics and Gynecology
University of Chicago Hospitals
Other, Gynecologic Oncology
Johns Hopkins Medical Institutions
Other, Post-doctoral research scientist
Columbia University Mailman School of Public Health
Awards & honors
- 2024 Rutgers Presidential Faculty Scholar
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