Defining Models to Classify between Benign and Malignant Adnexal Masses Using Routine Laboratory Parameters.

Area of Science:

• Gynecology
• Oncology
• Clinical Chemistry

Background:

• Differentiating benign and malignant adnexal masses is critical for patient management but remains a clinical challenge.
• Current diagnostic methods often require invasive procedures or advanced imaging, highlighting the need for accessible biomarkers.

Purpose of the Study:

• To evaluate the diagnostic performance of albumin as a single marker versus predictive models using routine laboratory parameters for adnexal masses.
• To assess the feasibility of implementing laboratory-based models in routine clinical practice for improved diagnostic accuracy.

Main Methods:

• Retrospective analysis of laboratory data from 1552 patients with adnexal masses (294 epithelial ovarian cancer, 66 borderline tumors, 1192 benign).
• Comparison of diagnostic accuracy (Area Under the Curve - AUC) for albumin alone versus models incorporating multiple laboratory parameters.
• Development and incorporation of a nomogram based on the most accurate predictive model.

Main Results:

• Models utilizing classical laboratory parameters demonstrated superior diagnostic accuracy (AUCs 0.92-0.93) compared to single markers like albumin.
• The developed models showed high confidence intervals (95% CI 0.90-0.95) for their predictive performance.
• The study successfully integrated these findings into a practical clinical nomogram.

Conclusions:

• Predictive models based on readily available laboratory markers offer a more accurate and implementable approach than single markers for adnexal mass discrimination.
• The developed nomogram provides a valuable tool for clinicians to aid in the differentiation of benign and malignant adnexal masses.
• Further prospective validation is recommended to confirm the clinical utility of these laboratory-based models.