EpCAM-based Flow Cytometry in Cerebrospinal Fluid Greatly Improves Diagnostic Accuracy of Leptomeningeal Metastases from Epithelial Tumors

Overview

Journal Neuro Oncol

Publisher Oxford University Press

Specialties Neurology
Oncology

Date 2015 Nov 15

PMID 26566655

Citations 31

Authors

Bojana Milojkovic Kerklaan

Dick Pluim

Mijke Bol

Ingrid Hofland

Johan Westerga

Harm van Tinteren

Jos H Beijnen

Willem Boogerd

Jan H M Schellens

Dieta Brandsma

Affiliations

Soon will be listed here.

Abstract

Background: Moderate diagnostic accuracy of MRI and initial cerebrospinal fluid (CSF) cytology analysis results in at least 10%-15% false negative diagnoses of leptomeningeal metastases (LM) of solid tumors, thus postponing start of therapy. The aim of this prospective clinical study was to determine the diagnostic value of epithelial cell adhesion molecule (EpCAM)-based flow cytometry versus cytology in CSF for the diagnosis of LM in patients with epithelial tumors.

Methods: Patients with a clinical suspicion of LM but a negative or inconclusive MRI in whom a diagnostic lumbar puncture has to be performed were included. At least 5 mL of CSF for cytology, 5 mL for flow cytometry, 2 mL for cell count and biochemistry, and 8 mL whole blood samples for circulating tumor cells measurements and biochemistry were drawn. Tumor cells in CSF and whole blood were detected by multiparameter flow cytometry using EpCAM antibody.

Results: In total 29 eligible patients were enrolled in the study. Thirteen patients were ultimately diagnosed with LM. The flow cytometry assay showed 100% sensitivity and 100% specificity for diagnosing LM, while sensitivity of CSF cytology was only 61.5%. Cell count or biochemical parameters in CSF were abnormal in 100% of patients with LM.

Conclusions: Our results suggest that the EpCAM-based flow cytometry assay is superior to CSF cytology for the diagnosis of LM in patients with an epithelial tumor, a clinical suspicion of LM, and a nonconclusive MRI. Confirmation of these data is needed in a larger dataset to recommend dual CSF diagnostics for LM.

Clinicaltrialsgov Identifier: NCT01713699.

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