Use of Ovarian Tumor Markers in Prediction of Malignancy Risk in Pediatric and Adolescent Patients

Infographic · Mar 2026 · 1 min read

In brief

Multi-institutional study of 309 pediatric/adolescent patients evaluated preoperative tumor marker combinations for predicting ovarian mass malignancy. β-HCG combined with AFP/CA-125/inhibin A achieved 100% negative predictive value, enabling safer identification of candidates for ovary-sparing surgery and reducing unnecessary oophorectomy for benign disease.

β-HCG was present in all best-performing tumor marker combinations for predicting ovarian malignancy in pediatric patients.
The combination of AFP/β-HCG/CA-125/inhibin A achieved 100% negative predictive value, ensuring no malignancies were missed.
β-HCG/inhibin A/LDH combination showed highest overall accuracy (95.1%) for malignancy risk stratification.
Appropriate tumor marker selection can guide ovary-sparing surgery decisions and reduce unnecessary oophorectomies for benign disease.
Multi-marker panels outperform individual tumor markers in preoperative risk assessment of pediatric ovarian masses.

Written by the GCMD Library team from the infographic.

A three-column comparison layout with medical illustrations of esophageal procedures. Each column contains anatomical diagrams in blue and pink tones showing the esophagus and stomach, accompanied by bullet-pointed text describing outcomes. The left column shows Heller myotomy, the middle shows esophageal dilatation, and the right shows POEM procedure. Bar charts or percentage indicators display success rates for each approach.

Anna M Lin, Katherine C Bergus, Josh Bricker, Mary Fallat, S Paige Hertweck, Geri Hewitt, Carley Lutz, Jennifer H Aldrink, Christina Bence, Lesley Breech, Patrick A Dillon, Cynthia Downard, Peter F Ehrlich, Samir Gadepalli, Jason D Fraser, Julia Grabowski, Michael Helmrath, Ronald B Hirschl, Rashmi Kabre, Dave R Lal, Matthew Landman, Charles Leys, Linda Cherney-Stafford, Grace Mak, Troy Markel, Joseph G Pressey, Manish Raiji, Beth Rymeski, Jacqueline Saito, Shawn D St Peter, Lindsey Asti, Katherine Deans, Peter C Minneci; Midwest Pediatric Surgery Consortium

Introduction: Pediatric and adolescent patients with ovarian masses undergo radiographic and serologic workup to determine malignancy risk before surgery. Commonly examined tumor markers for detecting malignancy among these patients are α-fetoprotein, β-human chorionic gonadotropin (β-HCG), cancer antigen-125, inhibin A, and lactate dehydrogenase. This study investigated the diagnostic performance of these tumor markers, individually and in combination, to assess malignancy risk in pediatric and adolescent patients with ovarian masses.

Methods: This was a planned secondary analysis of a multi-institutional interventional study investigating a consensus-based, preoperative risk stratification algorithm in patients aged 6-21 y, undergoing surgery for an ovarian mass between August 2018 and February 2021 at 11 children's hospitals. All included patients underwent preoperative assessment with ≥ 1 tumor marker(s). Individual and all combinations of tumor marker performance were analyzed. A priori clinical consensus was that the optimal combination of tumor markers should minimize the misclassification of patients with malignancy (maximize negative predictive value).

Results: Tumor markers were assessed in 309 out of the 519 patients, and malignancy was found in 25 patients. β-HCG was present among all the best-performing combinations. The most accurate combination was β-HCG/inhibin A/lactate dehydrogenase (accuracy = 0.951). Three combinations did not misclassify any malignant lesions as likely benign (100% negative predictive value), and the most accurate of these three combinations was α-fetoprotein/β-HCG/cancer antigen-125/inhibin A (accuracy = 0.862).

Conclusions: Tumor markers can support preoperative risk stratification for malignancy to determine which patients may benefit from ovary-sparing surgery and minimize those undergoing an unindicated oophorectomy or oophorectomy for benign disease.

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