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.
Keywords: Ovarian cancer; biomarkers; diagnostic accuracy; primary debulking surgery; proteomics; residual tumour.