New Analytical Approach for the Alignment of Different HE4 Automated Immunometric Systems: An Italian Multicentric...

Area of Science:

• Oncology
• Biomarker Discovery
• Clinical Diagnostics

Background:

• Human Epididymal Secretory Protein 4 (HE4) is a key biomarker for gynecological cancers like ovarian cancer (OC).
• Conflicting reports exist regarding the optimal HE4 cutoff values for accurate diagnosis.
• Variability in HE4 measurements across different laboratory platforms poses a challenge for clinical application.

Purpose of the Study:

• To develop an analytical approach for harmonizing HE4 values obtained from diverse laboratory resources.
• To establish a standardized method for HE4 measurement, reducing inter-laboratory bias.
• To improve the accuracy and reliability of HE4 as a biomarker for gynecological cancer detection.

Main Methods:

• Six Italian laboratories collaborated, utilizing distinct analytical platforms (Abbott Alinity I, Fujirebio Lumipulse G1200/G600, Roche Cobas 601, Abbott Architett).
• A common reference calibration curve was established and tested across all participating labs.
• Bias correction was applied before analyzing a common database of 1509 patients' biomarker values.

Main Results:

• The initial evaluation revealed analytical bias among different HE4 detection devices.
• Post-bias correction, HE4 demonstrated significantly better accuracy than CA125 in post-menopausal women for distinguishing malignant from non-malignant gynecological diseases (AUC 0.81 vs. 0.74, p=0.001 for age ≤60; AUC 0.78 vs. 0.72, p=0.024 for age >60).
• HE4 also showed higher accuracy than CA125 in pre-menopausal women over 40 (AUC 0.73 vs. 0.66, p=0.027), suggesting potential for fertile patients.

Conclusions:

• The developed analytical model successfully harmonizes HE4 values across different diagnostic tools.
• This approach enhances the accuracy of HE4 for diagnosing gynecological cancers, particularly ovarian cancer.
• The findings support a new strategy for identifying optimal HE4 cut-offs, improving clinical management of malignant neoplasms.