Related Experiment Video
Updated: May 3, 2026
Author Spotlight: Advancing Personalized Medicine in Ovarian Cancer
Published on: February 23, 2024
Biomarkers for predicting complete debulking in ovarian cancer: lessons to be learned
Carsten Lindberg Fagö-Olsen1, Bent Ottesen, Ib Jarle Christensen
1Department of Gynaecology, Section 7821, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, Copenhagen 2100, Denmark. carstenlo@gmail.com.
Aim:
We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients.
Patients And Methods:
The study consisted of three parts: Part I: Biomarker data obtained from mass spectrometry, baseline data and, surgical outcome were used to construct predictive indices for complete tumour resection; Part II: sera from randomly selected patients from part I were analyzed using enzyme-linked immunosorbent assay (ELISA) to investigate the correlation to mass spectrometry; Part III: the indices from part I were validated in a new cohort of patients.
Results:
Part I: The area under the receiver operating characteristic curve (AUC) was 0.82 for both indices. Part II: Linear regression analysis gave an R(2) value of 0.52 and 0.63 for transferrin and β2-microglobulin, respectively. Part III: The AUC of the two indices decreased to 0.64.
Conclusion:
Our validated model based on biomarkers was unable to predict surgical outcome for patients with ovarian cancer.
