Diagnosis of epithelial mesothelioma using tree-based regression analysis and a minimal panel of antibodies

Immunohistochemistry with panels of antibodies is a standard procedure to distinguish between malignant mesothelioma and metastatic adenocarcinoma. Most studies assess only the sensitivity and specificity for single antibodies, even when the paper concludes by recommending an antibody panel. It was the aim of this study to use a novel statistical approach to identify a minimal panel of antibodies, which would make this distinction in the majority of cases.

Two hundred consecutive cases of pleural malignancy (173 pleural mesotheliomas of epithelial type and 27 cases of secondary adenocarcinoma) were investigated using a standard panel of 12 antibodies (CAM5.2, CK5/6, calretinin, HBME-1, thrombomodulin, WT-1, EMA, CEA, CD15, B72.3, BG8, and TTF-1). Regression and classification tree-based methods were applied to select the best combination of markers. The modelling procedures used employ successive, hierarchical predictions computed for individual cases to sort them into homogeneous classes.

Labelling for calretinin and lack of labelling for BG8 were sufficient for definite correlation with a diagnosis of malignant mesothelioma. CD15 provided further differentiating information in some cases.

A panel of three antibodies was sufficient in most cases to diagnose, or to exclude, epithelial mesothelioma. Calretinin exhibits the strongest correlative power of the antibodies tested.